commit 849682b13b1b439140938528b88f6685f897ff28 Author: Pietro Berkes Date: Tue Aug 27 15:52:41 2024 +0300 Material for ASPP 2024 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..36ab90c --- /dev/null +++ b/.gitignore @@ -0,0 +1,30 @@ +# OS specific +.DS_Store + +# Editors +.vscode +.idea +*.swp + +# Python +.venv/ +build/ +_build/ +dist/ +eggs/ +.eggs/ +sdist/ +*.egg-info/ +*.egg +*.pyc +__pycache__/ +tests-reports/ +.mypy_cache/ +.pytest_cache/ +.env + +# Jupyter +.ipynb_checkpoints/ + +# Project +_archive/ \ No newline at end of file diff --git a/LICENSE.txt b/LICENSE.txt new file mode 100644 index 0000000..4b780a7 --- /dev/null +++ b/LICENSE.txt @@ -0,0 +1,6 @@ +The material in this repository is released under the +CC Attribution-Share Alike 4.0 International +license. + +Full license text available at +https://creativecommons.org/licenses/by-sa/4.0/ diff --git a/README.md b/README.md new file mode 100644 index 0000000..3da4dfe --- /dev/null +++ b/README.md @@ -0,0 +1,10 @@ +# Scientific programming patterns + +Material for the class "Scientific programming patterns", first given as ASPP 2022 in Bilbao + + +# From this: +![](generate_assets/DallE/DALL%C2%B7E%202022-08-11%2020.28.02%20-%20An%20apocalyptic%20monster%20with%20many%20heads%20that%20is%20destroying%20a%20computer.%20Digital%20art.png) + +# To this: +![](generate_assets/DallE/DALL%C2%B7E%202022-08-11%2020.29.56%20-%20A%20tame%20happy%20python%20cuddling%20with%20a%20happy%20scientist%20in%20front%20of%20a%20computer%3B%20Digital%20art.png) \ No newline at end of file diff --git a/code_snippets/factory_methods.ipynb b/code_snippets/factory_methods.ipynb new file mode 100644 index 0000000..4bab5a7 --- /dev/null +++ b/code_snippets/factory_methods.ipynb @@ -0,0 +1,182 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-12T12:14:28.926189Z", + "start_time": "2022-08-12T12:14:28.923089Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "import json\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-12T12:21:00.003395Z", + "start_time": "2022-08-12T12:20:59.997851Z" + }, + "collapsed": false + }, + "outputs": [], + "source": [ + "dict_ = {'a': 3.1, 'b': 4.2}\n", + "with open('my_class.json', 'w') as f:\n", + " json.dump(dict_, f)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-12T12:23:03.889266Z", + "start_time": "2022-08-12T12:23:03.883050Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "class MyClass:\n", + " \n", + " def __init__(self, a, b):\n", + " \"\"\"The basic constructor takes 'raw' values.\"\"\"\n", + " self.a = a\n", + " self.b = b\n", + " \n", + " @classmethod\n", + " def from_random_values(cls, random_state=np.random):\n", + " \"\"\"Create a MyClass instance with random parameters.\"\"\"\n", + " a = random_state.rand()\n", + " b = random_state.randn()\n", + " return cls(a, b)\n", + " \n", + " @classmethod\n", + " def from_json(cls, json_fname):\n", + " \"\"\"Create a MyClass instance with parameters read form a json file.\"\"\"\n", + " with open(json_fname, 'r') as f:\n", + " dict_ = json.load(f)\n", + " a = dict_['a']\n", + " b = dict_['b']\n", + " return cls(a, b)\n", + "\n", + "my_class = MyClass.from_random_values()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-12T12:23:12.242599Z", + "start_time": "2022-08-12T12:23:12.237477Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'a': 0.842940228048758, 'b': 0.2797222990193814}" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "my_class = MyClass.from_random_values()\n", + "my_class.__dict__" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-12T12:23:44.439726Z", + "start_time": "2022-08-12T12:23:44.432540Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'a': 3.1, 'b': 4.2}" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "my_class = MyClass.from_json('my_class.json')\n", + "my_class.__dict__" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python [conda env:bog]", + "language": "python", + "name": "conda-env-bog-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/code_snippets/walker_initializers.ipynb b/code_snippets/walker_initializers.ipynb new file mode 100644 index 0000000..a3920de --- /dev/null +++ b/code_snippets/walker_initializers.ipynb @@ -0,0 +1,287 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:13:12.648377Z", + "start_time": "2022-09-02T11:13:12.165387Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:14:10.246402Z", + "start_time": "2022-09-02T11:14:10.235135Z" + }, + "collapsed": false + }, + "outputs": [], + "source": [ + "class Walker:\n", + " \"\"\" The Walker knows how to walk at random on a context map. \"\"\"\n", + "\n", + " def __init__(self, sigma_i, sigma_j, size, map_type='flat'):\n", + " self.sigma_i = sigma_i\n", + " self.sigma_j = sigma_j\n", + " self.size = size\n", + "\n", + " if map_type == 'flat':\n", + " context_map = np.ones((size, size))\n", + " elif map_type == 'hills':\n", + " grid_ii, grid_jj = np.mgrid[0:size, 0:size]\n", + " i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10)\n", + " i_waves /= i_waves.max()\n", + " j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \\\n", + " np.sin(grid_jj / 10)\n", + " j_waves /= j_waves.max()\n", + " context_map = j_waves + i_waves\n", + " elif map_type == 'labyrinth':\n", + " context_map = np.ones((size, size))\n", + " context_map[50:100, 50:60] = 0\n", + " context_map[20:89, 80:90] = 0\n", + " context_map[90:120, 0:10] = 0\n", + " context_map[120:size, 30:40] = 0\n", + " context_map[180:190, 50:60] = 0\n", + "\n", + " context_map[50:60, 50:200] = 0\n", + " context_map[179:189, 80:130] = 0\n", + " context_map[110:120, 0:190] = 0\n", + " context_map[120:size, 30:40] = 0\n", + " context_map[180:190, 50:60] = 0\n", + " context_map /= context_map.sum()\n", + " self.context_map = context_map\n", + "\n", + " # Pre-compute a 2D grid of coordinates for efficiency\n", + " self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size]\n", + "\n", + "walker = Walker(sigma_i=3, sigma_j=4, size=200, map_type='hills')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:15:44.357965Z", + "start_time": "2022-09-02T11:15:44.351558Z" + }, + "collapsed": false + }, + "outputs": [], + "source": [ + "class Walker:\n", + " \"\"\" The Walker knows how to walk at random on a context map. \"\"\"\n", + "\n", + " def __init__(self, sigma_i, sigma_j, size, context_map):\n", + " self.sigma_i = sigma_i\n", + " self.sigma_j = sigma_j\n", + " self.size = size\n", + " self.context_map = context_map\n", + " # Pre-compute a 2D grid of coordinates for efficiency\n", + " self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size]\n", + "\n", + " @classmethod\n", + " def from_context_map_type(cls, sigma_i, sigma_j, size, map_type):\n", + " \"\"\" Create an instance of Walker with a context map defined by type.\"\"\"\n", + " if map_type == 'flat':\n", + " context_map = np.ones((size, size))\n", + " elif map_type == 'hills':\n", + " grid_ii, grid_jj = np.mgrid[0:size, 0:size]\n", + " i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10)\n", + " i_waves /= i_waves.max()\n", + " j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) +\\\n", + " np.sin(grid_jj / 10)\n", + " j_waves /= j_waves.max()\n", + " context_map = j_waves + i_waves\n", + " elif map_type == 'labyrinth':\n", + " context_map = np.ones((size, size))\n", + " context_map[50:100, 50:60] = 0\n", + " context_map[20:89, 80:90] = 0\n", + " context_map[90:120, 0:10] = 0\n", + " context_map[120:size, 30:40] = 0\n", + " context_map[180:190, 50:60] = 0\n", + "\n", + " context_map[50:60, 50:200] = 0\n", + " context_map[179:189, 80:130] = 0\n", + " context_map[110:120, 0:190] = 0\n", + " context_map[120:size, 30:40] = 0\n", + " context_map[180:190, 50:60] = 0\n", + "\n", + " context_map /= context_map.sum()\n", + " return cls(sigma_i, sigma_j, size, context_map)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:15:49.092194Z", + "start_time": "2022-09-02T11:15:49.086575Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "walker = Walker.from_context_map_type(sigma_i=3, sigma_j=4, size=200, map_type='hills')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:19:37.723607Z", + "start_time": "2022-09-02T11:19:37.717518Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "def flat_context_map_builder(size):\n", + " \"\"\" A context map where all positions are equally likely. \"\"\"\n", + " return np.ones((size, size))\n", + "\n", + "\n", + "def hills_context_map_builder(size):\n", + " \"\"\" A context map with bumps and valleys. \"\"\"\n", + " grid_ii, grid_jj = np.mgrid[0:size, 0:size]\n", + " i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10)\n", + " i_waves /= i_waves.max()\n", + " j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \\\n", + " np.sin(grid_jj / 10)\n", + " j_waves /= j_waves.max()\n", + " context_map = j_waves + i_waves\n", + " return context_map\n", + "\n", + "\n", + "def labyrinth_context_map_builder(size):\n", + " \"\"\" A context map that looks like a labyrinth. \"\"\"\n", + " context_map = np.ones((size, size))\n", + " context_map[50:100, 50:60] = 0\n", + " context_map[20:89, 80:90] = 0\n", + " context_map[90:120, 0:10] = 0\n", + " context_map[120:size, 30:40] = 0\n", + " context_map[180:190, 50:60] = 0\n", + "\n", + " context_map[50:60, 50:200] = 0\n", + " context_map[179:189, 80:130] = 0\n", + " context_map[110:120, 0:190] = 0\n", + " context_map[120:size, 30:40] = 0\n", + " context_map[180:190, 50:60] = 0\n", + "\n", + " return context_map" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:20:25.815725Z", + "start_time": "2022-09-02T11:20:25.811489Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "class Walker:\n", + "\n", + " def __init__(self, sigma_i, sigma_j, size, context_map):\n", + " self.sigma_i = sigma_i\n", + " self.sigma_j = sigma_j\n", + " self.size = size\n", + " self.context_map = context_map\n", + " # Pre-compute a 2D grid of coordinates for efficiency\n", + " self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size]\n", + "\n", + " @classmethod\n", + " def from_context_map_builder(cls, sigma_i, sigma_j, size, context_map_builder):\n", + " \"\"\"Initialize the context map from an external builder.\n", + "\n", + " `builder` is a callable that takes a `size` as input parameter\n", + " and outputs a `size` x `size` numpy array of positive values.\n", + " \"\"\"\n", + " context_map = context_map_builder(size)\n", + " context_map /= context_map.sum()\n", + " return cls(sigma_i, sigma_j, size, context_map)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "ExecuteTime": { + "end_time": "2022-09-02T11:20:26.367914Z", + "start_time": "2022-09-02T11:20:26.362287Z" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "walker = Walker.from_context_map_builder(\n", + " sigma_i=3, \n", + " sigma_j=4, \n", + " size=200, \n", + " context_map_builder=hills_context_map_builder,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "a" + ] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python [conda env:bog]", + "language": "python", + "name": "conda-env-bog-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/code_snippets/walker_next_step.ipynb b/code_snippets/walker_next_step.ipynb new file mode 100644 index 0000000..9b9cc32 --- /dev/null +++ b/code_snippets/walker_next_step.ipynb @@ -0,0 +1,223 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "8ad9fe94", + "metadata": {}, + "outputs": [], + "source": [ + "class Walker:\n", + " # ...\n", + " \n", + " def sample_next_step(self, current_i, current_j, random_state=np.random):\n", + " \"\"\" Sample a new position for the walker. \"\"\"\n", + " # Combine the next-step proposal with the context map to get a\n", + " # next-step probability map\n", + " next_step_map = self._next_step_proposal(current_i, current_j)\n", + " selection_map = self._compute_next_step_probability(next_step_map)\n", + "\n", + " # Draw a new position from the next-step probability map\n", + " r = random_state.rand()\n", + " cumulative_map = np.cumsum(selection_map)\n", + " cumulative_map = cumulative_map.reshape(selection_map.shape)\n", + " i_next, j_next = np.argwhere(cumulative_map >= r)[0]\n", + "\n", + " return i_next, j_next\n", + "\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " \"\"\" Create the 2D proposal map for the next step of the walker. \"\"\"\n", + " # 2D Gaussian distribution , centered at current position,\n", + " # and with different standard deviations for i and j\n", + " grid_ii, grid_jj = self._grid_ii, self._grid_jj\n", + " sigma_i, sigma_j = self.sigma_i, self.sigma_j\n", + "\n", + " rad = (\n", + " (((grid_ii - current_i) ** 2) / (sigma_i ** 2))\n", + " + (((grid_jj - current_j) ** 2) / (sigma_j ** 2))\n", + " )\n", + "\n", + " p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j)\n", + " return p_next_step / p_next_step.sum()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "95148e45", + "metadata": {}, + "outputs": [], + "source": [ + "class Walker:\n", + " # ...\n", + "\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " \"\"\" Create the 2D proposal map for the next step of the walker. \"\"\"\n", + " raise NotImplementedError(\"`_next_step_proposal` not implemented\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da34226f", + "metadata": {}, + "outputs": [], + "source": [ + "class GaussianWalker(Walker):\n", + " # ...\n", + "\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "class RectangularWalker(Walker):\n", + " # ...\n", + "\n", + " def _next_step_proposal(self, current_i, current_j):\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "class JumpingWalker(Walker):\n", + " # ...\n", + "\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cfd90d16", + "metadata": {}, + "outputs": [], + "source": [ + "class Walker:\n", + " # ...\n", + "\n", + "\n", + " def _compute_next_step_probability(self, next_step_map):\n", + " \"\"\" Compute the next step probability map from next step proposal and\n", + " context map. \"\"\"\n", + " next_step_probability = next_step_map * self.context_map\n", + " next_step_probability /= next_step_probability.sum()\n", + " return next_step_probability\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "72041675", + "metadata": {}, + "outputs": [], + "source": [ + "class GaussianWalkerWithProductInteraction(Walker):\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " # ...\n", + " def _compute_next_step_probability(self, next_step_map):\n", + " # ...\n", + "\n", + " \n", + "class GaussianWalkerWithSumInteraction(Walker):\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " # ...\n", + " def _compute_next_step_probability(self, next_step_map):\n", + " # ...\n", + "\n", + " \n", + "class RectangularWalkerWithProductInteraction(Walker):\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " # ...\n", + " def _compute_next_step_probability(self, next_step_map):\n", + " # ...\n", + "\n", + " \n", + "class RectangularWalkerWithSumInteraction(Walker):\n", + " def _next_step_proposal(self, current_i, current_j):\n", + " # ...\n", + " def _compute_next_step_probability(self, next_step_map):\n", + " # ...\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5ee2e200", + "metadata": {}, + "outputs": [], + "source": [ + "class Walker:\n", + " def __init__(self, size, context_map, next_step_proposal, next_step_proposal_arguments):\n", + " self.next_step_proposal = next_step_proposal\n", + " # ...\n", + "\n", + " \n", + " def sample_next_step(self, current_i, current_j, random_state=np.random):\n", + " \"\"\" Sample a new position for the walker. \"\"\"\n", + " # Combine the next-step proposal with the context map to get a\n", + " # next-step probability map\n", + " next_step_map = self.next_step_proposal(current_i, current_j, **next_step_proposal_arguments)\n", + " selection_map = self._compute_next_step_probability(next_step_map)\n", + "\n", + " # Draw a new position from the next-step probability map\n", + " r = random_state.rand()\n", + " cumulative_map = np.cumsum(selection_map)\n", + " cumulative_map = cumulative_map.reshape(selection_map.shape)\n", + " i_next, j_next = np.argwhere(cumulative_map >= r)[0]\n", + "\n", + " return i_next, j_next\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/code_snippets/walker_with_plotting.ipynb b/code_snippets/walker_with_plotting.ipynb new file mode 100644 index 0000000..bfc2e05 --- /dev/null +++ b/code_snippets/walker_with_plotting.ipynb @@ -0,0 +1,105 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "2120045b", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "class Walker:\n", + " \"\"\" The Walker knows how to walk at random on a context map. \"\"\"\n", + "\n", + " def __init__(self, sigma_i, sigma_j, size, map_type='flat'):\n", + " # ...\n", + "\n", + " def plot_trajectory(self, trajectory):\n", + " \"\"\" Plot a trajectory over a context map. \"\"\"\n", + " trajectory = np.asarray(trajectory)\n", + " plt.matshow(self.context_map)\n", + " plt.plot(trajectory[:, 1], trajectory[:, 0], color='r')\n", + " plt.show()\n", + "\n", + " def plot_trajectory_hexbin(self, trajectory):\n", + " \"\"\" Plot an hexagonal density map of a trajectory. \"\"\"\n", + " trajectory = np.asarray(trajectory)\n", + " with plt.rc_context({'figure.figsize': (4, 4), \n", + " 'axes.labelsize': 16, \n", + " 'xtick.labelsize': 14, \n", + " 'ytick.labelsize': 14}):\n", + " plt.hexbin(\n", + " trajectory[:, 1], trajectory[:, 0], \n", + " gridsize=30, extent=(0, 200, 0, 200), \n", + " edgecolors='none', cmap='Reds'\n", + " )\n", + " plt.gca().invert_yaxis()\n", + " plt.xlabel('X')\n", + " plt.ylabel('Y')\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8b1035c", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "class Walker:\n", + " \"\"\" The Walker knows how to walk at random on a context map. \"\"\"\n", + "\n", + " def __init__(self, sigma_i, sigma_j, size, map_type='flat'):\n", + " # ...\n", + "\n", + " def plot_trajectory(self, trajectory):\n", + " \"\"\" Plot a trajectory over a context map. \"\"\"\n", + " trajectory = np.asarray(trajectory)\n", + " plt.matshow(self.context_map)\n", + " plt.plot(trajectory[:, 1], trajectory[:, 0], color='r')\n", + " plt.show()\n", + "\n", + " def plot_trajectory_hexbin(self, trajectory):\n", + " \"\"\" Plot an hexagonal density map of a trajectory. \"\"\"\n", + " trajectory = np.asarray(trajectory)\n", + " plt.hexbin(\n", + " trajectory[:, 1], trajectory[:, 0], \n", + " gridsize=30, extent=(0, 200, 0, 200), \n", + " edgecolors='none', cmap='Reds'\n", + " )\n", + " plt.gca().invert_yaxis()\n", + " plt.xlabel('X')\n", + " plt.ylabel('Y')\n", + " \n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/generate_assets/DallE/DALL·E 2022-08-11 20.28.02 - An apocalyptic monster with many heads that is destroying a computer. Digital art.png b/generate_assets/DallE/DALL·E 2022-08-11 20.28.02 - An apocalyptic monster with many heads that is destroying a computer. Digital art.png new file mode 100644 index 0000000..d1e94e3 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-11 20.28.02 - An apocalyptic monster with many heads that is destroying a computer. Digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-11 20.28.04 - An apocalyptic monster with many heads that is destroying a computer. Digital art.png b/generate_assets/DallE/DALL·E 2022-08-11 20.28.04 - An apocalyptic monster with many heads that is destroying a computer. Digital art.png new file mode 100644 index 0000000..a0c4b73 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-11 20.28.04 - An apocalyptic monster with many heads that is destroying a computer. 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Digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-11 20.29.56 - A tame happy python cuddling with a happy scientist in front of a computer; Digital art.png b/generate_assets/DallE/DALL·E 2022-08-11 20.29.56 - A tame happy python cuddling with a happy scientist in front of a computer; Digital art.png new file mode 100644 index 0000000..787d0f4 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-11 20.29.56 - A tame happy python cuddling with a happy scientist in front of a computer; Digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-11 20.29.59 - A tame happy python cuddling with a happy scientist in front of a computer; Digital art.png b/generate_assets/DallE/DALL·E 2022-08-11 20.29.59 - A tame happy python cuddling with a happy scientist in front of a computer; Digital art.png new file mode 100644 index 0000000..df65cdd Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-11 20.29.59 - A tame happy python cuddling with a happy scientist in front of a computer; Digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-14 10.26.06 - a lot of eyes, digital art.png b/generate_assets/DallE/DALL·E 2022-08-14 10.26.06 - a lot of eyes, digital art.png new file mode 100644 index 0000000..724984b Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-14 10.26.06 - a lot of eyes, digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-14 12.23.55 - A duck with glasses sitting in front of a laptop, digital art.png b/generate_assets/DallE/DALL·E 2022-08-14 12.23.55 - A duck with glasses sitting in front of a laptop, digital art.png new file mode 100644 index 0000000..aba3ce2 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-14 12.23.55 - A duck with glasses sitting in front of a laptop, digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-14 13.34.02 - A messy pile of paper with numbers on it is on fire in an empty dark room, digital art.png b/generate_assets/DallE/DALL·E 2022-08-14 13.34.02 - A messy pile of paper with numbers on it is on fire in an empty dark room, digital art.png new file mode 100644 index 0000000..36f9e5b Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-14 13.34.02 - A messy pile of paper with numbers on it is on fire in an empty dark room, digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-16 09.22.38 - God descending on the holy trinity of computers on a digital altar. Digital art.png b/generate_assets/DallE/DALL·E 2022-08-16 09.22.38 - God descending on the holy trinity of computers on a digital altar. Digital art.png new file mode 100644 index 0000000..80e494f Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-16 09.22.38 - God descending on the holy trinity of computers on a digital altar. Digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-17 08.30.13 - God descending on the holy computers on an altar in the digital age. Digital art.png b/generate_assets/DallE/DALL·E 2022-08-17 08.30.13 - God descending on the holy computers on an altar in the digital age. Digital art.png new file mode 100644 index 0000000..ba2f2d1 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-17 08.30.13 - God descending on the holy computers on an altar in the digital age. 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a man is disgusted by smelling a gross pile of garbage including rotting fish and rotting eggs, digital art.png new file mode 100644 index 0000000..aa1a095 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-19 11.07.45 - a man is disgusted by smelling a gross pile of garbage including rotting fish and rotting eggs, digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-19 11.09.56 - a pretty woman is happy about smelling some delicious cocoa, digital art.png b/generate_assets/DallE/DALL·E 2022-08-19 11.09.56 - a pretty woman is happy about smelling some delicious cocoa, digital art.png new file mode 100644 index 0000000..041b6ad Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-19 11.09.56 - a pretty woman is happy about smelling some delicious cocoa, digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-19 11.11.14 - a man smelling a disgusting pile of garbage including rotting fish and rotting eggs, digital art.png b/generate_assets/DallE/DALL·E 2022-08-19 11.11.14 - a man smelling a disgusting pile of garbage including rotting fish and rotting eggs, digital art.png new file mode 100644 index 0000000..9d736b4 Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-19 11.11.14 - a man smelling a disgusting pile of garbage including rotting fish and rotting eggs, digital art.png differ diff --git a/generate_assets/DallE/DALL·E 2022-08-19 11.12.06 - a man is disgusted by smelling a gross pile of garbage including rotting fish and rotting eggs, digital art.png b/generate_assets/DallE/DALL·E 2022-08-19 11.12.06 - a man is disgusted by smelling a gross pile of garbage including rotting fish and rotting eggs, digital art.png new file mode 100644 index 0000000..f206f1c Binary files /dev/null and b/generate_assets/DallE/DALL·E 2022-08-19 11.12.06 - a man is disgusted by smelling a gross pile of garbage including rotting fish and rotting eggs, digital art.png differ diff --git a/generate_assets/explain_the_walker.ipynb b/generate_assets/explain_the_walker.ipynb new file mode 100644 index 0000000..11ba988 --- /dev/null +++ b/generate_assets/explain_the_walker.ipynb @@ -0,0 +1,1511 @@ +{ + "cells": [ + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "from matplotlib.backends.backend_pdf import PdfPages\n", + "import matplotlib as mpl\n" + ], + "outputs": [], + "execution_count": 2, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T08:39:25.127Z", + "iopub.execute_input": "2022-08-14T08:39:25.137Z", + "iopub.status.idle": "2022-08-14T08:39:26.175Z", + "shell.execute_reply": "2022-08-14T08:39:26.185Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "sz = 14\n", + "bg = np.zeros((sz+1,sz+1))" + ], + "outputs": [], + "execution_count": 217, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:37:47.981Z", + "iopub.execute_input": "2022-08-14T09:37:47.993Z", + "iopub.status.idle": "2022-08-14T09:37:48.010Z", + "shell.execute_reply": "2022-08-14T09:37:48.020Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "def draw_grid(ax, sz):\n", + " ax.vlines(np.linspace(-0.5,sz+0.5, sz+2), -1, sz+2, colors=\"black\", lw=0.5)\n", + " ax.hlines(np.linspace(-0.5,sz+0.5, sz+2), -1, sz+2, colors=\"black\", lw=0.5)\n", + " ax.set_xlim(-0.5, sz+0.5)\n", + " ax.set_ylim(-0.5, sz+0.5) \n", + " return ax" + ], + "outputs": [], + "execution_count": 218, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:37:48.193Z", + "iopub.execute_input": "2022-08-14T09:37:48.204Z", + "iopub.status.idle": "2022-08-14T09:37:48.221Z", + "shell.execute_reply": "2022-08-14T09:37:48.233Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(bg, cmap=\"Greens\")\n", + "ax = draw_grid(ax, sz)\n", + "ax.scatter([7],[7], c=\"red\", s=100)\n", + "fig.savefig(\"walk1.png\", transparent=True)" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 219, + "metadata": { + "collapsed": false, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:37:48.791Z", + "iopub.execute_input": "2022-08-14T09:37:48.802Z", + "iopub.status.idle": "2022-08-14T09:37:48.933Z", + "shell.execute_reply": "2022-08-14T09:37:48.954Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "bg = np.zeros((sz+1,sz+1))\n", + "bg[[6,8], [7,7]] = 1\n", + "bg[[7,7], [6,8]] = 1\n" + ], + "outputs": [], + "execution_count": 195, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:20.150Z", + "iopub.execute_input": "2022-08-14T09:25:20.161Z", + "iopub.status.idle": "2022-08-14T09:25:20.176Z", + "shell.execute_reply": "2022-08-14T09:25:20.185Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(bg, cmap=\"Greens\", vmax=2)\n", + "ax = draw_grid(ax, sz)\n", + "ax.scatter([7],[7], c=\"red\", s=100)\n", + "for i,j in zip([1,0,-1,0], [0,1,0,-1]):\n", + " ax.annotate(\"\", xy=(7+i, 7+j), xytext=(7, 7), arrowprops=dict(arrowstyle=\"->\"))\n", + "fig.savefig(\"walk2.png\", transparent=True)" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 196, + "metadata": { + "collapsed": false, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:21.500Z", + "iopub.execute_input": "2022-08-14T09:25:21.510Z", + "iopub.status.idle": "2022-08-14T09:25:21.765Z", + "shell.execute_reply": "2022-08-14T09:25:21.788Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "bg = np.zeros((sz+1,sz+1))\n", + "bg[[6,8], [7,7]] = 0.5\n", + "bg[[7,7], [6,8]] = 0.5\n", + "bg[[7 ], [8]] = 1" + ], + "outputs": [], + "execution_count": 197, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:25.732Z", + "iopub.execute_input": "2022-08-14T09:25:25.741Z", + "iopub.status.idle": "2022-08-14T09:25:25.755Z", + "shell.execute_reply": "2022-08-14T09:25:25.764Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(bg, cmap=\"Greens\", vmax=2)\n", + "ax = draw_grid(ax, sz)\n", + "ax.scatter([7],[7], c=\"pink\", s=100)\n", + "ax.scatter([8],[7], c=\"red\", s=100)\n", + "ax.plot([7, 8],[7,7], c=\"red\", lw=3)\n", + "fig.savefig(\"walk3.png\", transparent=True)" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 198, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:31.185Z", + "iopub.execute_input": "2022-08-14T09:25:31.194Z", + "iopub.status.idle": "2022-08-14T09:25:31.427Z", + "shell.execute_reply": "2022-08-14T09:25:31.446Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "bg = np.zeros((sz+1,sz+1))\n", + "bg[[6,8], [8,8]] = 1\n", + "bg[[7,7], [7,9]] = 1\n" + ], + "outputs": [], + "execution_count": 199, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:32.184Z", + "iopub.execute_input": "2022-08-14T09:25:32.195Z", + "iopub.status.idle": "2022-08-14T09:25:32.214Z", + "shell.execute_reply": "2022-08-14T09:25:32.225Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(bg, cmap=\"Greens\", vmax=2)\n", + "ax = draw_grid(ax, sz)\n", + "ax.scatter([7],[7], c=\"pink\", s=100)\n", + "ax.scatter([8],[7], c=\"red\", s=100)\n", + "ax.plot([7, 8],[7,7], c=\"red\", lw=3)\n", + "for i,j in zip([1,0,-1,0], [0,1,0,-1]):\n", + " ax.annotate(\"\", xy=(8+i, 7+j), xytext=(8,7), arrowprops=dict(arrowstyle=\"->\"))\n", + "fig.savefig(\"walk4.png\", transparent=True)" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 201, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:39.931Z", + "iopub.execute_input": "2022-08-14T09:25:39.943Z", + "iopub.status.idle": "2022-08-14T09:25:40.229Z", + "shell.execute_reply": "2022-08-14T09:25:40.249Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "np.random.seed(42)\n", + "bg = np.zeros((sz+1,sz+1))\n", + "i = np.random.randint(-1,2, size=(50))\n", + "j = np.random.randint(-1,2, size=(50))\n", + "j[i!=0] = 0\n", + "i[j!=0] = 0\n", + "i[0]=0\n", + "j[0]=0\n", + "#i[i==0] = -1\n", + "#j[i==j]=-1\n", + "#j[i==j]=1\n", + "#i==j\n", + "i+7,j" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 202, + "data": { + "text/plain": "(array([7, 6, 8, 8, 6, 6, 8, 7, 8, 8, 8, 8, 6, 8, 7, 6, 7, 7, 7, 7, 6, 6,\n 7, 7, 6, 6, 6, 8, 8, 8, 7, 8, 7, 7, 8, 7, 8, 8, 6, 8, 6, 8, 8, 6,\n 6, 8, 7, 6, 7, 7]),\n array([ 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, -1,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, -1, -1]))" + }, + "metadata": {} + } + ], + "execution_count": 202, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:43.403Z", + "iopub.execute_input": "2022-08-14T09:25:43.415Z", + "iopub.status.idle": "2022-08-14T09:25:43.442Z", + "shell.execute_reply": "2022-08-14T09:25:43.453Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "i.cumsum()+7" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 203, + "data": { + "text/plain": "array([ 7, 6, 7, 8, 7, 6, 7, 7, 8, 9, 10, 11, 10, 11, 11, 10, 10,\n 10, 10, 10, 9, 8, 8, 8, 7, 6, 5, 6, 7, 8, 8, 9, 9, 9,\n 10, 10, 11, 12, 11, 12, 11, 12, 13, 12, 11, 12, 12, 11, 11, 11])" + }, + "metadata": {} + } + ], + "execution_count": 203, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:44.486Z", + "iopub.execute_input": "2022-08-14T09:25:44.497Z", + "iopub.status.idle": "2022-08-14T09:25:44.519Z", + "shell.execute_reply": "2022-08-14T09:25:44.529Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(bg, cmap=\"Greens\", vmax=2)\n", + "ax = draw_grid(ax, sz)\n", + "ax.scatter([i.cumsum()+7],[j.cumsum()+7], c=\"red\", alpha=0.3, s=100)\n", + "#ax.scatter([8],[7], c=\"red\", s=100)\n", + "ax.plot(i.cumsum()+7,j.cumsum()+7, c=\"red\", alpha=0.3, lw=3)\n", + "fig.savefig(\"walk5.png\", transparent=True)" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 204, + "metadata": { + "collapsed": false, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:25:50.619Z", + "iopub.execute_input": "2022-08-14T09:25:50.629Z", + "iopub.status.idle": "2022-08-14T09:25:50.863Z", + "shell.execute_reply": "2022-08-14T09:25:50.881Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "def next_step_probability(current_i, current_j, sigma_i, sigma_j, size):\n", + " grid_ii, grid_jj = np.mgrid[0:size, 0:size]\n", + " rad = (\n", + " (((grid_ii - current_i) ** 2) / (sigma_i ** 2))\n", + " + (((grid_jj - current_j) ** 2)/ (sigma_j ** 2))\n", + " )\n", + "\n", + " p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j)\n", + " return p_next_step / p_next_step.sum()\n" + ], + "outputs": [], + "execution_count": 209, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:36:39.525Z", + "iopub.execute_input": "2022-08-14T09:36:39.537Z", + "iopub.status.idle": "2022-08-14T09:36:39.552Z", + "shell.execute_reply": "2022-08-14T09:36:39.563Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "bg = next_step_probability(7, 7, 2, 3, sz+1)\n", + "plt.matshow(bg)" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 214, + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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OEJAqZwhIlTMEpMoZAlLlDAGpcoaAVLlTZynxoAxqyWiD5c/SyXBLQKqcISBVzhCQKlfUlXjWdTdHREbEOf2ZnqR+K+1KTESsBT4OvNbjOUlqUVFX4q476HQhOn0+cVGqUNExgYjYBOzMzKd6PB9JLTvp8wQiYinwBTq7Agu5vV2JpSFWsiXwfuBC4KmIeAVYA2yNiPPmunFmbs7M9Zm5fozF5TOV1BcnvSWQmc8A7zn6czcI1mfm//VwXpJaUtqVWNJporQr8ezr1/VsNpJa5xmDUuUMAalykS0ulY2IPcCr81x9DjCIg4vWPT1rWvfdLsjMc+e6otUQOJ6IeCwz11v39Ktb0309Feu6OyBVzhCQKjdMIbDZuqdt3Zru6ylXd2iOCUgajGHaEpA0AIaAVDlDQKqcISBVzhCQKvf/bgu5LIj4iG0AAAAASUVORK5CYII=\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 214, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:37:29.171Z", + "iopub.execute_input": "2022-08-14T09:37:29.184Z", + "iopub.status.idle": "2022-08-14T09:37:29.283Z", + "shell.execute_reply": "2022-08-14T09:37:29.303Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(bg, cmap=\"Greens\")\n", + "ax = draw_grid(ax, sz)\n", + "ax.scatter([7],[7], c=\"red\", s=100)\n", + "fig.savefig(\"walk6.png\", transparent=True)" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 216, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:37:38.672Z", + "iopub.execute_input": "2022-08-14T09:37:38.687Z", + "iopub.status.idle": "2022-08-14T09:37:38.928Z", + "shell.execute_reply": "2022-08-14T09:37:38.949Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "grid_ii, grid_jj = np.mgrid[0:200, 0:200]\n", + "my_i = np.sin(grid_ii/130) + np.sin(grid_ii/10)\n", + "my_i /= my_i.max()\n", + "my_j = np.sin(grid_jj/100) + np.sin(grid_jj/50)+ np.sin(grid_jj/10)\n", + "my_j /= my_j.max()\n", + "#grid_jj\n", + "\n", + "fig, ax = plt.subplots(figsize=(10,10))\n", + "ax.matshow(my_j+my_i, cmap=\"Reds\")\n", + "ax = draw_grid(ax, 100)\n", + "#ax.scatter([7],[7], c=\"red\", s=100)\n", + "fig.savefig(\"walk7.png\", transparent=True)\n", + "\n" + ], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 227, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-14T09:43:00.706Z", + "iopub.execute_input": "2022-08-14T09:43:00.723Z", + "iopub.status.idle": "2022-08-14T09:43:00.972Z", + "shell.execute_reply": "2022-08-14T09:43:00.998Z" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "# Simulating some data" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "parameters = {\"sigma_i\" : 2,\n", + " \"sigma_j\" : 3}" + ], + "outputs": [], + "execution_count": 2, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:41:44.483Z", + "iopub.execute_input": "2022-08-08T19:41:44.491Z", + "iopub.status.idle": "2022-08-08T19:41:44.503Z", + "shell.execute_reply": "2022-08-08T19:41:44.569Z" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## in a maze" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "initial_act = np.ones((200, 200))\n", + "initial_act[50:100, 50:60] = 0\n", + "initial_act[20:89, 80:90] = 0\n", + "initial_act[90:120, 0:10] = 0\n", + "initial_act[120:200, 30:40] = 0\n", + "initial_act[180:190, 50:60] = 0\n", + "\n", + "initial_act[50:60, 50:200] = 0\n", + "initial_act[179:189, 80:130] = 0\n", + "initial_act[110:120, 0:190] = 0\n", + "initial_act[120:200, 30:40] = 0\n", + "initial_act[180:190, 50:60] = 0" + ], + "outputs": [], + "execution_count": 3, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:41:44.514Z", + "iopub.execute_input": "2022-08-08T19:41:44.521Z", + "iopub.status.idle": "2022-08-08T19:41:44.533Z", + "shell.execute_reply": "2022-08-08T19:41:44.573Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "plt.matshow(initial_act)\n", + "plt.colorbar()" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 4, + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" 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"2022-08-08T19:41:48.390Z", + "iopub.status.idle": "2022-08-08T19:41:50.279Z", + "shell.execute_reply": "2022-08-08T19:41:50.286Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "plt.matshow(initial_act)\n", + "plt.plot(rw.trajectory[:TIME,1], rw.trajectory[:TIME,0])\n", + "plt.xlim(0,200)\n", + "plt.ylim(0,200)" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 11, + "data": { + "text/plain": "(0.0, 200.0)" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 11, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:42:08.182Z", + "iopub.execute_input": "2022-08-08T19:42:08.191Z", + "iopub.status.idle": "2022-08-08T19:42:08.277Z", + "shell.execute_reply": "2022-08-08T19:42:08.285Z" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## in a mountain area" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "grid_ii, grid_jj = np.mgrid[0:200, 0:200]\n", + "my_i = np.sin(grid_ii/130) + np.sin(grid_ii/10)\n", + "my_i /= my_i.max()\n", + "my_j = np.sin(grid_jj/100) + np.sin(grid_jj/50)+ np.sin(grid_jj/10)\n", + "my_j /= my_j.max()\n", + "#grid_jj\n", + "plt.matshow(my_j+my_i)" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 56, + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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7evP4hej4e+vJFoBhVjzzid01hwbBzvdqU3fTglXt8SB2V2L2U4vAy7iACOJSAM0odD1DAmn3gCGPTH0UIpygQKXTBlsALsDQmk7AsLl5le3DfTKxgkEAD8ABhE0Fp3B+TiUgKeprdaa0B3QDVBkQ76feECpkfRaA6hAQYgAbK0UxFyiZ6FQW5nALDhez4gEwFLadWgM/onNW3gY4AJO9WVEwxccFGNipJFV31avg4NSPLOCFYa4plxDsuPJMGAyC3J4EML5A/vpRWDDWGXEwiBn8KjCYLU282tHqAOHCowPDcxtmxXMBh5270WmS24EvRDi0JTjcFVHCk3aIEvZmz5KgYEDRmvpAYYi3L6DpHosBQ0SAanotplJBunbayhzcg1SBgUkTGF4TZjfXXipQ1jYRmBh5ShtTO06wm1OihC1MD1FIkxzEogRq6iI3gGYdStsCCI/MzzRV/bX//yJIxuvV60UDGOYJ5x4YhohfAPgV5sCP//Ve3st7+bVc3gRzqCGzSTERs6zDbo2T97BYAMkaYqHRHRAq6bAXvQgEEAsRzo91PJSdMzgtJD9KYbMDOSMgwWWBHYBZaaao4zX0ezxG3ZqbFgBcfa80OR493Y87iTEGZw07FebwIM7Bfn7YoKNdfJbk7rMmQ5XQWdB9CutMYG9PYbKFQ82+nfa3/ZCtDXB2RdW0mDSHQXnTLc1DVwqmOO61C48saO6NADDah/oX8txEWzBM5OO5g0CYoNqt/kpZb3YNwIKbYrGXm1ANFqIf7FCtTtpo9K9lSqY4zn9el39e4xzKmCkPoP5Pk6kma6Byv6OdXylvAhwAr1Ch3wCGW6wOHh4aA4AJGMKXfbe4xmOfwHUgqNHVvBscNqV9pu7GrH2GVE3M9MvT+D6Ntq+UcHJlBlgE+NEKfAD5oqmoQ5uCebzjkw2KoMppV5MmMOx8ot0EQYkyQII93jsY7K4iCtkgOJRtgIngJLbfd5u8sRrFJgNnFQV5DADqQAe5tO8UO1e/lVIV8wQGJFB6o6fYzBzrRjAERx4mWJgRKzBEOzQaGouA0Kgb6AngCymxkZmf7Pch6h717tHP2BfxsabIjezDYXsYULj19djEj7Fb/18nGCxAUMbGZKouoDFdywLA4eV7VN4MOESMQm2M8azDHQRM2kK8bqTToFrLrBS7WuxBO/Ng1mIHU/msKMY00L56R3Rt6Ik9aKL6VL/poVN9rH6abrXpgdHJG0yADI2hkSQwtEtcQawuGwDRiSfBrvkjIizr78YxVB9sBjXFwKiBThTGdDTatY3GsTf3oN6K9Xe9feq11+sdi88k23OKGo0RRbaIKtpK/HsbdZzEi2t3sLrsb0s/ibiPqb/U4+q9R+lPpTni81WQrN/JCfXSp/TajjER+TFUv/OgvBnNoQ6iLCtIxNtyzEMweKXidUDHir3JBXrX4NN1jkbWm+ub/ocVEPR6/leuz+pyrWP9bA3wyVmyvK+fraDRbkyPecDNv18HaKnuUkct/6hfxk37zjPYWEF5BYX4fV76QP1svd4EuoVJra/rMeu5mK4TT13pOQbtfX/UtX+tbVKOq4P+MviBT/af2zJ9/3VzIsqbAYfvdrlbGv9evjtFLxTpOz3hd/l83+fyXW+PL/zD3+73vtj1vhlwSHurXrguz/G2HBOvwyf/RW5U1RCGm7MeUB7L71O9xpgw7m5S+d9kSxZN46ELdPlcbupUP8t4BERb2G3t5X39TJTzf4DFPVzOj9Gud78f7sy4XsVax9FGl3t6V//pnozncEHPvzdfU2a2WvrCqJ/FMojXPeu4vK7HZCRpjfUov78K3MMNed//6EFd1/dBuqLP0KO2+laB4dsAkrejOSiZ3VoHaulsquoLpTQ7DIAMbgLpBRh0GUBSOpkqLCBq+p24jnjUz8YxeePyO/aviyAJo54RoUkehj3VLx6+7iPqFp6BTe0aT2HsPEJ9oyMDQAejg8GqODz6hou2UEsAgyjj0IZD2wQAuQhJ54FyynWg5IDVuHaaMiqt7fawg1Icq6O9ZTSo4goS0Uab0gJkDFHNenAqd1J+y0AhvndIy+PHeQh13cXcf7xKWf+5n8yTQZlQ1gmn9pv1e3GpGBZBejRoBg29nDfa0p8FZmfrOFFGrL5S3gw4kGLKtQB4pSNARMhcQmLLZiU7vd145hJ0toIEyuwi45ERkwE04p0yl9Da+7r2fu0AmQZtqUvcWXOJ2jmVoj72e8SjjspqmaiIITKArsvolF0YJzecKtjUFk5ZC6gJkiwW5AXCIRuExAfHXAIYurI9YO8B4NSGUxpEGacv566DMa6p+yDJdqwDJJdvjvZ66MpUDFdmWfqqARhxHrIJQoTQicAOFqfwWI4NxUkKVlszAvcQ7PHCT1ZZU4DfoWyBUICtWNW53W3VZtR79JeYZKbBH7lCoi+UPrQ+gNKHClio9x8iDN204LwG3hEsyKxqPCVQT/3/Ch2h/uk9wqXv1vJmzIr38l7ey9sqb4I5kGIkKA0kBjJzcaCkCiUaZr4/AMEeLKfhFQqn8OlgDcKDBteswz4LkFDOALnQyq+pzgbJIm6K0mDMlDNj2CPGklJ19hyGyshrBMzNePbmwT6MJoyTGCe14Z5TBns4dEySthyKwA/0hGAOhzZ8lC1nzUMaDmW8iDGIYA+RGAYARDgfwbwia3Uyr2gAGQzMPltvvs98Cl+HQfl5PVS8cxAxiGz5eCTQ5UjSQpbFmallO0Dsuxk+rcNtG20R4dOnt5XV2er+4m3QS53j3kjtP9FXIt9ozdUQS9dlMOSJjZZl7UBhnt4Oebn1Vi4M4eIiFWcTZOuECCPPZI09ea28CXAAUAai5qo+W5dAHjREiOAjJYUgovwEXQFVXuIfBjWv4BCdOROKinVsAJ6OfJgW1D2Pg5R8DmFK5A19vPDKbqxR5nE7CgWMxLYEoLtJQQKikQ2aCOhii4K4t0vMgbVB6exE6OBp4VUN+gHGwqvQHE4xgACAj9LwIlsOjK6MoztIeJru7u3Xu2Wulk7DJOuU5kAkTg3z4g5ElaJRDUSUbzou+T2nOglQXk+6G8vCKWGCqEA8QEy8rR8tvApdBTDT6qU3HNLMlBNOk6J3hvjvavSdAAjfxmBOSAzvQxhbHpRnO9HVPKX4Uwf+2s8aSpq3elD9zNrTVgd5f4vvvaYD4a2AQzROsIeoZ3cmwG4z9WALnKG1Fk7nqgxZpN7l9D6IJzGyF9QPcHDkR49ZwDv4Yh9m/skHQpIdGI84Tssx9UYONmQA4VmOYyAScDJn4hHuLXMuRGHSIcoRo8OWbHcH0ObTWLwPe/pQW7J9SMNHZw4vsuGlG0Ac0nD0hkMYR+cxeM5mgySAoXsb+kDJxCUdzsJKO900k00AzrAUUMwAEYoCIBBw5pPIc5ScE9VrJRwD/9NLtkV5Yg6XunercwAigKneVB8++IExwSQgPAQHfZhqsAbg5YBu5fnaojfvXdTHKyC8lDcDDnyG7lRMgxRb/DCavgLAGBKxzRQ10ctyeqQnINhCnenSZHBg6AMYwuQZNLEkB13o4FpCTDLHAflqPZQbajdOPcW7+pfUMw4BALolXCEYjc4ELCemuxdqu3DPzESHXvMyxOA5tSWd/ihbDowAho99w9EbPvaG0x89AKszum98kwPk5CHElQSza67NhyAqLkqGsNcweXXU2SE76E1uRE9RpUq5fFuYsAUjIM4Qa+DKpII19AoO3drn5Yz6W8LdAEQA0JMHMMQGPw4Asd1BgACXTX84mYSOdop+VATbYA8RWKXePjEXaisa46VRF4BQtVWjyHkUKSA/KG8CHAjeaAtSWhjruImAU6Jw0QC58MXixB9rDtEQwyMx24oA/EYXcAgtpNLEAIXKJB7RZWC2F9Xi7KX2bKXUB+yW2jtJBtQs38zdj/igkGaD4AljBhwZna7dJ46ptvZLt67wIi1nzY+9XQYH4NmZz9gVi+fdocIUsxs4wCHaonT+KJZiznMaxCImBYIQzOuh2Na3bMB5uqnYxiAXBbQRmnsZYv1F6CX3625o0lS6fzcYQ9Q96326+XIGMFLuiEUd4NP29QC8X58zOOSuV4u3Ii+tTOpKSK0h2kcZNtAV7rXByCGZ7VwYayvvAVsL4lmsvxJmBR/DyxfjwpJ1asiNeSxaqZP7cHNjm0cjNTpmio6FKQRzKEAwKCAtzAE3usP1JxP1fZFMBvQwSgoxv3G4AYiwdCC44Y6ZgAXeNkGNN+6vgkME/oS7zrSFLU2GAIaX3nB0n0HL4AAwBkih1DlAHCQADOE2dAfgIXVOl10sVFJN0Tk6t3ojqqppahsBOvIraIvxQCbesqCp5YOszGHN7jQSzDo4uMZwyqj3BAxnmUx8izw6yLe8o9waECjAcAZr0NFOF3AopmeCQ2HOdRWmJ5iJ3cvie+xAUQPIYoFh5knxLRliZfOj8ibAgRTgUzEtTIGPex0AEQ1Rc+5FMg2bXpdz1LoXNE1PRJnxAFzZQrURL5pDnPMBQLiOkJ2e3fxpKDcyMlQhMzNVgIjLDoDIQQCU5CrIRCw2U7ZXU6OtNnbQ6di34nBKfbrGcJ4N58mQ3iA+KLRzzpqVUt8r9Zj0mcu9p9FWkdQl960MTIx77s9wE0PUE/NOwrNt42erWAlEtpryfI05ZDyDnafHfh6hMfRm2koAQ+6VSQ4GV2AYe2UGa1BUs8L6VWgAo39drIG6bsMF+kzmogYSmRMVsFgZgSVpdlBmcU9FrClo3pYhGD8obwIcgjlMfMqLeaQM/bD5gBIdqbs8OCozLj0QHTIAJzprqsdLivAVGAIsqvqcdnSc+76Fq9AW+SpYKoIPwEvXI+ZIT3X7OgDiwBgE6vntYuaLxKqHKBq1i1cjjs29GpxOh30NIGl0MIZ+Fn1hodMGCoVSlzbN9qxtFbe4lglEaSxBLpqDit9zB5kAD1WBKo8sSG42EquBJTOYBWcfAPloO7zYMxSAe2LMTTvVvdQbwACGcwBDbqzrZoW91zQr+Nas0DlKMvvPaB8Abgp4sBwbIEgDOLJsofSnYBDBIgQjvZ+bJxE68Ki8CXAgHUh7BxDD2zCoVCKl20+WLJPua1vcjRGzkOZBMRn4hi3c7RwdYtIkJD2o2Ei+QbkXZ177FuzIO6p6evOF8cSiZMlUa/Nagy6CLoS9SYJELi++aY9Iwx6gcvaWs+bpM+Z5NkgPbwRDT9cXgMmM4ACFczbJsq0Ks3qNYWX8CsNyaIT+AFzps5ClDwQD4mnaAIssbfDUbeQpBHlaZg1czQqL9BzxCxpRqbHblWsrUe8Y+KspEbtrz+Cg43/OHriP/mPtpFcALWzhalb4blw+0YmUPlWYRD7a0u94APFrzOE9QvK9vJf3clveBHOAAu2ojKGoMpOd6VRKNO1RYhozTmgON+dP9rAIiuy6AzAYAlf2sNqH1Y35SeaAZA5gNYTnwnr8ekxzcH1F1VKbVwE22ENJ0hqBXMDwVoiMnZ6+CHMIO/v0yD8Aky//IjwWWzuZQtjRVZBcWdYXZQ5FcIPYvQWQ95y1mBhuJqqnZbPjnDGIJG0WmtMKAvfMISJm4/cswMlNCXETKuodZsXp9T7gDMJZw+EaWh7jDGISJLUwLJ1NipJFqHorlAYLCPe4OAMZrMfOJ1GHYA9VkCym7o3WneVNgIOZFQUQsigiPgHqYzgElmJWUHQoj6C8nN9PFdQtRbIY/IvmkOBQbuKdIHm5qUsJcyK9Fm5DSIIDJTgMEBzBKnFMbqKiANzLYPZ2ocFioiTzyFx0lxlrmCJuqrgZkUDjrzVdlfPgAJAC3Oy+m02xaKsJjOM+LDfnDhymXJtxzxezUjakiZHtIz7QQ43PnKP1N2fDvsa/RHtmDEwVXaPeYTIs5oQ9a+oOwAAGPjX1Bj51jnPoVXPwuiyZxwDY9gDdNDZlgmxIYKA0rXxsSIAlMix/NivChMPD8ibAAarOHKLUWXPMEjFTBBoCw3ZS1hS2ruePWYuuM//SmSfR6CaaLUChxsrjgSAJorwuQ3saIAG3DzdawCEGsN/sYBRYjhGGxE7czYXGzuBWku0SHoJDrKYUse/l5xHYVAJ8qr4ABCi4RjMJbY/AQb8gOFBx1Q1wGPecTKdx5pjidF0F2uwzpBalU/YuKq9j1KV3pJ4nIj2rthL1TkES6ZkItpAgMTEHTe2Bujp70MJGfeZTXS/NLjjaoZMH05H3J4Vs5AAx2lwWLUJ905xop4mhRa7Am/JGwAHgl+sAo7x5inBDpsBSGjFFrGzQ6/knQbIyiI4bcNDCHPz9ZHromA0L2l+qFYyBBgUMkAD8JobPfmFIXADSmASlyzN8/cEwKpUWNVcoPdjHYyyvHqKmlCjRS0jwYkIAocDTYAvnCg6LCfaFmUNkTKYZHMo9Fx3McWxUVI6zxjOQ8MC4kcsSE1BMCWnC3QrgNlK2z/Ue7RDgoIVB6CRIGmhosgZawAGi1oeWEGozKShZBHEFB4JuzjwbQLG/bALDMDeGEO79Jdr4K+OteIm7WooCCPXeAaKqsMBCkezwa4mbHp10YQ3V9qsmRYBC1RxCaYb659OaiWvF6mxY7UT7vRjsuDCkGEvpyYBmLMRkjgAzlRYBCLlp613U0cRQ6uIhYEQ7ngMcqgkBlEFR2yp8+SsTW8BhBdII8kl3L2PSZwDM91zLe6VJf8qI16DQHl8SKxMR/YMKKCCur2hPGfg2173WG6gaw2AMLUAimMOh5so8xPrTqaAubq4GOEgyrMpCybdsTOrPnKaFASiDGkE2GiuZfb/Zam7IrVmhX5UISUU7cjjc/J9yhq5CC7BQJJ+Brt9HsocrOMysgC/AoAMQUIAizAsFZt9jKQEMIUhulCABDBaQrKi8Lk3jcRDOGFBcenFcc52CFSrssRV6Dw7enpmxKdZCxNhJ1lCo9IOQ4Pl5NsOAaOPFhx+Xk/dJC3MYM1r6eIG859V/H2bWpD81zxLGBSSiX0yaw9o3irkJDFd3sqJiPlU35QEf+AswHJoaGgcwnDKA4RRbMxO2QNcZGIogSTQiYY3GGiDoxh7vw8YUIoZh44u5Qc4c5MasePvMQQA6BJzLs8v/yqwvOWNq6RA00fcakz7Fqldw0DLLlc5cA1RSPEoTo1JlR/0wKW5MC3U6q+QA0SgDoOqCIhIym1wLQ6prSWJywezNqHRavF62e/Kg0bnyjsbvZeMUKh00GsCFSldg4DymsIdzmGBr5B/3qKPOwDDd4KD6cR89VkEod47mApwajMlBIt8j2mRsHBSzrvJYrau0/HwCbQmGC1YY7eDmUxUegRtgcHBoLwYEQACFgLqADwFOAYkDhJQbKJUKxsWZiBaMDUwgZujGBigBEMKg2NxXcDE3RKz/pWjZvN1r6rib8ibAAargl14+cJgvN1JCpAt1OaMMh51ald3aB+qKt0lMTJPBfzWDVIa7acyIwRzUz6GO+Lje1Ph9oiGYdkN3lUEBscdXvW7rUm6E/oDy2sLJ7TCn+Vp2VKqzpSwjoRbBSIM3uXPn1YXTasNJgXfwnBjEAFZgtPUEojJfRmoyxaxQsRWsybCCHWjJH+pjaVqZKMgFSTUUm4TmfnFhDmXiiLaRxQtzlnrnwF9NiQEMyRwOAwI+ugHCKaDegT7AgXpUJmYCRe6tUBYbaWNjDsJAa/b9zQLBQqBhifYhix4NII3JA0hhXFlfBYf3IKj38l7ey215M8whzYpp8dWKXaHUlxBjRlLHT7syMbOGoikA9f1wOyV7qG6nyh5uknTkzxKA5kopW8q2SoOhgOYdWNhDnpRytWqa4p64Q7byQ5NpgWFire0RpxUMW7sjPSj5vsYvFNERGLNnsAmeNAedmUMxLabfj9qF3kBuJsT6AaUR51DEWtNgdHLvhiU6rUYM7cJX66YGWdukmKx16X5llLXudZ1EtEN4JkJnCNbArqEla0jm0IHejS2k5uCdopoWuTSZ8zWJMQcVtu9v4cIZ3SU8X6wMVXER2xlZtFMJw37zmgNUQadA0/1mH5MnQZkgIoKEws2ZCvfoaNfzY6KOU6zC6onosylhg8AEJAAJCqY56Pj8RnMg90XDRaXstGn48mQ2VICIQxiagBnHerfLpCV1qTLUKWkZdGuZl1LPYtzFdbcMDmAMkPx8McdCqU/h1k2vSbwtW5JFFGAIZ+m2TM0hVuZS6pTxfmXjmSEpJw0HieqtWNsi9IY4JIBB7oFhdlPGc3m4KQFgAMPRgbODHBzQBZHSSkXcNFhsLgAgBjXvIZ2A1tKsUFVQ2FXeCObN4mF++WtpowkuQWYPyhsBBwDHaaIRA5EijQ+TnCVBwgWVOjC8Eapf/FGcw3CrFdFxCWNNYDjd9eQAEZ2aQ0gSmNrsyA0MgFCyWIN0ozG7fa9mI5b8l4BlfWLAmQ952LNrDgR778KiBHietaJlVtaSNOUGLFcBbsya/v++2NoTSFQQHcCQ+kMwrinUfBFvo/TSVgQoDd2EYpzEBNAcMF2sHSBZdZoBnBS3pLDFjBW4Yw4yjovPpyjZFKcxgd9gTO6iPN0r0e0ZsH4UjCGBwZ+1h6jSBzhUzxcTQDw0Km6u3TRnrC1bYPDMWixzloDBoiZkAkgPWXvMeoE3Aw5qDdfYVr15Yg4h76xkSVdRQGJee6C+eczrinQNXqpuzDrTTcBwBkuQ4ZN2tRla2MM0dSHXBORIbs7r2nJh4IxkBLmQ58p93DVlAhPQ2TspwbNjYUkuqnMP0cEe7tri6tr1wTMFM10HSRzDVbi9McXsOB0AUUB0uh4uafI0WIPVJ2bomAwElEApiHa4AoSqP4cfv7bDDTikuVnAgi7gMLdH1I97hEbr6DMuPAKw5wUY9DwHewAMKFazAt4PmEde1GasAKog3y5+MUaX1rAWYViovcQNKCD89r0V8IZxH7A6OFAjG6jEAGvOsDNzCLoOa1haGwdTQ6zhz5OesDKGAIazmhUyfNSq4wbXmxoigY/k0bXdsRyzA7nJUtgR2WRRPCgGDNw1j6k29Chj/tDXTKz4eAGGOvAnF2+0U9flGB2fS/1MZ7BdQ4NXmzqm+vAyKLxXjvqQt6cl2DUTg4iAXhlE1my67+G9oQeHVPaQ4FDbQCoIDsCLezN97gzTJpPu53JQEJmB4TwHc/D/1zU1ea+IoG3kyyMHB9020HlmlaZ54VJNtlwoyNNMIPyovA1wUAzXjvjMDACdbfGMU1OKJLIx+PLLIVLgevP9kIk9TLpDMQukzHTn+N1LwIoDWYpI/t3pJ9lHsNOYAIjMqA2j0pZxW5frKjO5KEZymvq61DVeU7nZhE8LtAEM1ayI19O16O0xazsONjbAYXL3FtOisrtIrpvXegLYiinQYffdtReiUf+pjhHfcTdBFKI5fVwmjcnMuKl7re+4N8vDWWYyzW5mRmoMFRhCc+jFrFhvFZU9y7Tk5fZFhiSCzJqOMNPc9et9LfvZ5ew3DVLK2wAHZw7UxTM0B013IaFoBcouHuUAMz5KMmh0+rR1/ok0K7yTrko6RaRazHQOWFSFxwUYLJS6XDNgs1z3jlqEN3LVLfoAdQDcJvCrnXBcd9jgSHs8xLs4BjHYfe7IcHJdBmI1K+Tm91DeFxOsKuKxkKqGkdcEONUjEiJkrB0YbeGvmaAgv7fl+nod9PCObhWwdrL2pRICrFkvr3Md+PVc8axre8xtjtoO0WeW42yRlmY/uPQHGX0lcmBm0FMNglKxtQ8VIIhBLNBgbACSXjrjNMZdEFIoxwyxrb8hP7au9LT79goy4M2AA0YjVttU7IaYKqtDpIobinFzY9OOiVLV8bp0hJzF4nPU/5XPkxKXHngHDBUcavirOEOQGNmFqTAQGwSP3y2vAZBSATQ/dXnOapbPEV6LqHttZx3Hru1R23P9/2SfLm0YgyZAYG2ru0VFeTniwUqgIUTWgRtNodEXaKnrfO2X9tF5cpz45lK/2g8CDKb2qW3h9za/F6AYfaEXRhkM013fqjoLkhUYJtNCzG3pZrYqlfEg/j2Lmsz+IuptqglG5KZ3sluOdnlgd2Ic9l7ey3t5L5fytsChzDQ5+yxx+Yno+R3MU8PNZ1UIS3oo5X+ox+rNb9xMecs1P/zfeoxgrt/t7y/1e1Cv21kvz1OO1bvvPpg1lvPXa6kMZmJba6lmyOXezO01xT5UprHW5cH7Wza4fn5TLixmPedy7KXe9TvZN8c9nkoyTLcPZT7gnjVgfKeep5ojr/W7lYVP11Ov+f4UwFsDh1v17CtQHl33iOYar31BkL5S19f+910rr/WKUh5dyyNs+V6U7+dvfc/KV7Bvf0eaAxH9AoC/A/O4n6r6W4no1wH4NwH8ZgC/AOAnVfVvfwsnnTtkJHGh8bpu9LGuxMzPSlHAhDqN5cFkC3NcuMrD89xqYhfUfWXLwh2/Tpuq3L6P5/zfF60vSrjzDWjUui2Ca/3f3Wevhk/fXUc837Rj/Y21zS6lxNpUB4odP38hEprk/6INHjXhUlddrjfa72H9Mb5PutRVx/9pOb4+6rXU5yn4LXJRMI24F/KwzdAIiq6k4iFca5xDzePGZN9lzv9T+r/H76F+xvN9Q1zf2pduyneDOfxjqvpjqvpb/f1PA/h5Vf1RAD/v7z9dIoY84qX9oaXDzANkfGZRonZHM3lmvZnLMXmOspKzHhvhygkk0zWxr5egmxvBcz2IbCWdxzto/C/q1ua66XJtynSpw3T9NwMllj2vx0zn53IcX4/D+npdq1E+VxrXibzmGOA02ikyGK2/xQMMIoz6/p5g/M7N/3BzvWsdMrfGdP2v1H/pL1jPVc9ZAP72weyDewzo2C3cvBKE3EWayLxY0+c8fS+B5va35vYf4fS1v5XMaQ/K98Jb8RMAftxf/3EA/z6AP/T6V6zxtPnAC2T0Bo2cedHR1NejA3GDSucqA4bKTJBuJ443hMk74MerYuwt2BikYmvhS/QllRuu/qWHcQ5Eo04MAwivXwysYEUgjJh3GuepqebGa6Qrs64vMdYzn2NiAGGbM4ZnYAkS0vJZJqeh+nu2OMqW/roLkmGehLrcOE4ZblfFNUrUO60SPLVbAZMy+2obYD3dc16vKwb2aJPKLi7Rs9EbGDOp0lF/6OhnscBv3GMtiV/j2hmUolYAA1suBm4eMVuYA6ztiHS+QOIBJoCtq2jNlms3X3MRoFNNWLZo3EwnlwA9t9N6n9bynTIHBfDvENFfJaKf8s9+WFV/2V//LQA/fPdFIvopIvorRPRXXvTzHEAaqbBq5QIgYgcftkQg0kqH4DGw4jvSPIfC7f+R54yZXMpvotnNls2va/MkG80ZwNbKoGfo1qZHsoioV/NIt1K3AL68zlLfUT97iF9nvJ5m8xgEsVNUGRS3TKq2R9PyehlUPNqrXsv1QaNNN54/X+5hzJ7xSDBYjpNGhWGNe7a2yZQJ7MFzbYMJUOj6/et3Ca/V17J7lTo07yPRX7Y2Jr3WbEA3Bm1bPmLQkx8TD2pcwGAGhjxus+fsd1vzNo9+Z30PjSCNIY2z70ujaeJYy3fKHP5RVf0lIvqvAPh3iej/Vf+pqkq320MDqvqzAH4WAP4Xf/B/o7p9tIpuziCArJhupZM1SlCwY+Lmz+zB/hlPlKp4RNQRRQg2jXyNZwY522IVCOgEZOOM89cNFnUmAlCzCM47j0W1n+NmRaeJ+kW9fCCoA8KlfhUEC0hkwpsGSNPxeQBAMofq/XCmFDNjNlRMh/YQ+MwRVVObNQEHKo+lyOXj3m6A+uIya2/EepHw0a/9IO9bAWyf5WSLNvB73gIgBqirfx7Xlf2hrDp8yKJKfVEmbaJSf28zbSMRcLDEXPDX/FqVwbH+IQKMWD17U1vkjXN0FSaLeWhtROICyHUVMcO3BnABEZ+EEnyABAVsDNlmYMj2cAC3C3qMDt8ROKjqL/nzrxLRnwXw2wD8ChH9iKr+MhH9CIBf/fSZyNGvzNCwwSPbmFXt9egswBg0E+1dqaN3cCIHCafedSEP4OukztExJBZGnQJxYYjOOKFFQWoFhkSZ+GEHiBZmk80sGim9GtvME/VMsJgHfjxkGwBSj5GmM2gQMFKyX27aGBCx2o8wAMSpO6IdpuqRV29kZBIfVWX1SJ4rFlRZIl5A1xvjvzfpFck41kHvbGqjpT1KX1jYz51ZcWd2pmtvcftVgBBEcl9kLka4S9w8juTPnn1pn2EwzZd4TwRt/oO9g5peQ6jdrEA1K5gn9pBsIcZMaxMw6DaYeOSZRG3j7wVzIKKvA2BV/Tv++h8H8C8D+PMAfi+AP+LPf+4LnAy6b9C9QfaWM6skWMTg8c6wjZl15MPDdOOr+pwzA5v9S+z5EamEXcM6ceRPiAWVfMJu0jk8Eeox9LkEMPzJkQUZQCzXDnBIKhpoDiQYSAHBGACRyCUHxAoMm7MF2GulYBVawLIM+GgHwCPtYPUQOCrWG+Ld+EReB5fvS2ncTFtHbjNTycV4IjvitOhqvfcxeMmOjUS8KyMIxhAgmYzCr3EFhmEe6NwvanOE/qLjuiFIxhOL/aLeuZWAn+wSXbu5PuUzVdRbsQ2ACGExWALzyOlQSxEv4zhwNVUMJKxPeee7AQYpzBuI/kKYGNVN+U6Yww8D+LMulmwA/qSq/ltE9JcB/Bki+n0A/iaAn/wOfuO9vJf38iWVbxscVPU/AfDfuPn8/wvgt39LJyNA92aPjSG7M4fdaLfsw6RIWhkmRGoOSNt1nSkBZFSkxZjbbBG7Qgf856o/HoxOyGzMkE4yeQmTmxS4LCoCMLvoiuAmjuhx7bI7Y3C2YHUdM7bsxhris2QNm86mxyRGuv5AC3PwNkmvjLMGY0KUh9pk5eZWv1pLYZIBNiOzx4Zk+5W1I7Gcu64FqWW0ETCLf1TMJppYUzUtgkkAhTG4iSXtdc9NtIf6PcwFcVLMoaJDMNwZ418dXcd0HBIzRYGylUa0m5+ADoJlPKMp0pHulv5XVySAcJOri+EpcE86FqfpKjtnO4ZwCkR/oXuzs5S3sfCKCbobHZKdIU8BDgUYNhTNYdjbtVNNZkUpYe+OZcpaAALZA8i3UOPoFDSOiUCWAIe63PtuHb4d7HrDRJdp0OV93LisXwDBPihgAkM+aw4WAOZxaLBkIFx6r2srU1FAQ30LgOgY32H4Kj9AyDNSkQPEOlCIwGR5NuD6grLlXLC2cqBoARh0CY2+bmozhNdqOlaNYdVgponiTpwdLH+0y7iAXPCV8Ua+QpS5aC/RBqDsYw2KHsaCf9gwAAII4PQVpW5q0ik2mDMTlJjmUPWrgkpawWH1flXhEbiaEu1qpl1iNB6UNwEOSgR5av7gHBiyE/o+D5wxY8wV/ZQgGchuz5FYVcfGJ7DP2W1U9k5KDUv2HwcKdZAIWxPIjr9ugroq8NWWlqqnJBBQ2tGyI+1q2bW0gRZbW6E+ICKhaj6v03V6K3REfpr6mu1psTVliXS+9moFcCYoaAFSKu2po61Tc1hvDk0DeHWdWv3GPa994DJRtLJnRWoO+glBUpNN5q5RDmoSdeda34GjHTQDhN93ZgykKQluqTOYPVeqJw2y3/Pl3FLAIRq6CJLp8Vo8X7qZNwKAv3Zg2Kp7vkwmhaG9feZAmIChP/ng2cgGR5lRL2p+7QivMIdcalvyF1BzYZLjJiFnDHXtJz4j/70ECiVH+3u6DKC4FIf6Hq44YFBkWUDBmAPKMQYMKUqGSZEb6aqbEmp5AR0c6BFzSIAgGxCdch9FRLCMX7v44KcQWIGJVeE0sNQTtoFvK0AqVADZgOEOqyZXZjENBjjcs4UKlNFW4/vBHgIkR19LcyujmZA5MgB/3T1BMI+6U17raCo4e6qM4vp7DCYCd4EwgRpZeq+S1Oh2oVQRtaMdkjUwFWBYTNUQuqtoW8y0rxRzABH6M0OeKDUGAMkaphn1zqwI1vDAhtIKDqE5xIMNJAAMoGAADdDY9cnZA2CNPZKaDJ93TZYS13Xt9GE7F3BIDaHUdS8oX4DBjtV8ZE725qDQ1Duzunbw0NBHbKJrfnqCelJf9GhPtfT0DNsnkm0mBYwqC88gQTzaiwvYjtWZNLGsyWtQ7l81KeY4jjL4i7fmalaEW3cFh6v+opHsIaJfM+mP/XawxKg7Fy9WFvI/AcTOhBJ3HDyUFXo4gAp5pjH235PXvTnRXyI0mj32h2fzARhjZOg0Q68ZEZKjP7555qAMA4YwI8KsiIFSBk52lGIjr667e7OCLswBupgMzTtGZFp2kOA+OqrpDZ6AJWbF15hDAYeM1qydfmUMUcdgDptafd2kwOYmRFNgcyu4KbgZU+Am9uzMgZa2iPiEyL0pQhDhMft2B4rTzYPT2lbc1LD75RmnqTCseDioAtHOc3aox8wBaXpdmcO459YHdAaMwhwm3SXY1DSTjzbJsaiU4qzVD8gwcB51N3MT4MP7JzBYFhGU1IFhmFZx7/mEzfqep5QaxsTizOECEGlyDeYwR/cWTeEi3s4i7p3mMAXK3ZQ3AQ4gMyUGONjHIcxpHTTBGrzxU3yKDkDXyclMSy0U1ymvJ2+tJgNSYxggEbMI4KZIAIyvzbjNW0DjmtYQ7yEkFhvamYHsDgihJ4RnItjC5ixhE7CbFcwCbgJm9YegUfGwlBEZwCDx8O3auw9oYbZZjtmAwgUxOmloZD5oiN3LcQ5gCKYFBHOomsPdva/tNHfcYSMHCCC1ljAdZIMBJVDMK/uM2JCbAiCAW7BMUyvAIUwt/43KoKoXiJmAA8kU2NdapDkAIFb4xuCkruDGmZDXGr3mFyn3qkb9YoBDxI5UobEGgsmizWTAU2VYrzDtKG8CHJSQ4GBMwT5Pt95eZ41BJ4HKGjCoXZy3vqjMAc4M2gCJOBeF76mARIiXQGEdAg92edDxH3T6XM+BAnZbed4UOpkVCt0dGJwt8CbgZiwBALatg1mxsRgwsIJJ0SKL99Ie4gDRhdHFn13Q6l3RmSBNIae5wnByDlgApuD7bEoedMVhgvH4obGRLj7JsCazogBptNMkNrrmkkJsK+YVA9QktQLTS6SI//NFBIOCgyVg4JAMKgTW7td4ABQtyjbw6cCYmNKscMAKYbvDdZkBEuk+dq3hEauKn0vtisdzDRAbbRWTKE3vJ7OCxvOjwo//9V7ey3v5tVzeGHMYHgogKPYyq7Z5Volw4TvmMH4AuHgr3HFNooMG++wXDCLMCTM3qh2NkXk56eC1To9s6WktAAM1fmHSFwDTGDYBtmFKcOvYNkEL5sCCrQm21tHIGITtmqWupM8lTIoujO7PhwuSJzf0xsYgSG39Byv0HNmLlWmo+U65tam31WBinZf2KexhmrFWlpX3ePFCtMIYtmE+BHOgZvECzMYWhpl1b2IBxcwSyrUfvZu7UJoag4i6E5n3JqbUw3QG9rUoZlpYPUayF1/SHmZK7HPRStuIx388MrviXMmshpkghR0A94yhenEAjL7ImL0jS3kT4AAG5Km4LovmcBk4VZEGrqr0o6Lhz6bhtgqXVdwk7+ABEuHN0OlGfnFbGijUjQe1WxcKmaZQX5spAcA6/j5MibYZMOytYwtwaB07+2ckaCwJDHxzcQLCKWwAoYxTGBvbRZ1NcHTGyQ0nM86zgcgAQiLPRjEzgjIHWARIWFvRbFI88FbUKMYYTJONHMCwmSmYpkTTBATAPAHcDDSr9sIsU+qCVYOx1IwGlADQGkNE0DtDuNR9Ma9soZ7pDMrIgLEac5Nu8dPrVftW7VO+yhVArOuLix3tcAMO1YSY+tTq3ZnaU/Pe4eOle2R5E+CghKE3VM3hkX8/bE0AGfDzYG9I+4F4uD/fn0kokRwYjGICiRDZVnD4btnSAXoBECk8ul7gjCFAYds69taxN8FTswvfW8fOHRsLnvgEO3tgXJmDKEEwBMlTGl6k4cl9tS/SsHHDCysaM5gV59nQecyYySQiL4OLkmB4qnRvq0UEzkaphXRiDZmHwvNMRDuh6gvhtt0kAQEAWgADqbEo1gTK+NXKpkJjMJA0BgUAXQhnb2hNprqvDAo0lj6bm9PFx2AQQHpzwL6KN7cbpAUcirhdm8p1jDjXKtiucT+3oFByduR5fULVl2u/jfImwAEE9KcBDJrMQUe4cLiwwr8fFKmo0haJVhhEbWhXo21Ngb/u9n3EbkG9AEMFCXdxAoVxPKDL+XvFrJjAYXG9xft0UxYTAgB4tw6/bcYUnvcTe+t4ah3PzXICPLWOJz7NvCAxoCAB+0W2cnFdCaLGGg5lnNLwpIyXbl2hidh5WHA0RjsVL6TGIlLU89n0ZPO7k3k40iwr3orcoSvvx9JQ5J8kOBQzcfVCODDwFuaD3JpXjUcdqAClXfvVrAiwDHA4hZNBsde9s6JTs3q7HaokaWpY3zMWQe7FsN9DYViUO7nXCSeidrM/3fUhYDIHVvYwgUOK9zcRo9meAyQelTcBDsYcBjCIU+o0J1b/vtNJALMq/amgH9jMpgEOLVxWQeHjPfkWdRi7UAVTCTeoA0RurHJXVubQdL5JoaEEW2iawNAcHIIxPG0nnjYHhe3EczvxxDM4PLMzCOrmrYA81BwObRBlHMp4kW1iDi99wws3fOy2zLix4OVsGdx0ng2d2GbTjIcorr8AW6GhzRT2Zm1TroswzWYIvSHuiwMFhZeGrX1aAEEyKAOEvRmLamTvmRRb0ENgahNxsDzdvAIwmVrBoA5uIAI6cU4+4sEd4QVdw8mBMDvsf+Qzvk08SHs/dmKb0hWmWVH6C83a1WRWFJZ18e4szOGLmuJvAhwQ4ODAkCi463XgrHam+7FH0M91MKxBP1AP/HkQHWizlLmzEiT6QHYtgT1TgFX9TcKgzHFD6coc0PTipmwFHLatJzA8O1t43k58aEcO6GceYLFTxx7gQPJQc+jKOLThFMbBJz66LbfLho0EmzQfVGIgscRNsOsRoDkuIl1/gAUSeYCRJjDo3PmjUYvmUGMVAExCY2gK29aTKewBDg4MYWJt1JNNBSBwTtdxiZymVoDDi2wODgYuH7mlwHtQS2AjBwUFZ30s/wONPDpuakSQWHWTJzjo0GamUphn9qkVHC7MQRdGsSzKg19DtPnDme2NgIPSrC9IrBnYrzNqzBxhZ9bAHxOJ72dKBSZVuneFitHJjKxkt6O7iZbWScntaO8QzhzUqbJ1+utWb1NQVqXMEzj4DdpkaAtNsO0d2zb0hA/7mWbEh3biw3bgs3Ykc3jmMx8BDs3NinZz8zvIWUPDwQ2HNOw+s34kmcDhhQYwjAEGnB5pSKQQYggDErkUY2R08mXtbjvkRj401jdgtFN22AgDD3YYbKFpsoWnrU9CLADs3L8lEwtYzCwXCjYRnGKMqtHw/BzRB/wcYWZZJD1BYaxCgIwmteYwUyObRoG62K1G207lNXDgGwAAZrZQY0G8/9lFaQaxfSWYQy5DLkq97vOMGoE/ITwByGCfxnMHriWCfqoqzawQIfQ+BKapg3c3PVyNT9omY22FyoiOvMXfmAmLWZGUGRgm0uKi3LaOZweHp82A4bPtwId24EM78VkzcHhmM2wDGD7wUZiDfMKs2NBh5sVH2rE7C9lEsEkH992UflIwDe+HVwtEzUGjobPiPNVZBGX4dALFBBDAlElyAQZy5hDh4AAesgUDgp7g8MRngsNOgo07dgeG/RWzosO0l81v8k6CgxmbCBh71n2Img1rEfIJKIz4wiQIY2l7ZCFLkEAIkuP9nE9usKzZRF1AoOgJOQHFc1mUB4QpHgvKHjOHV+SI9/Je3suv5fJmmEOaFWFKABfW0LaerGHz0OBwV7UvYFaYIq3YlHB6mDCzoqfm4LOfryew8FkYBS5r/TVZg84rPkuZzIoqABVbOoTVO9bwtA2x8Y41fNZe8OxmxQc2FvGBTux0DrMCcqHRVk2C4MCLbjjUTIqPHlzCMCGzQfBNj5Ng7JdzmMlhM2iYHb0rpDMkgnY6FS9RERrqzAigrn9I/cjNCACT8Bii4/N2TmYEADxxL9pLMIehwQBAWzSH7iZF5yFIfqQdm7IxJyjYPTl3fQsIa6lBVKGQwR6scgDUl757WzFN3ooM278r1VuR5inGmqK7gLFqStR4kDCLQsAvYeV35U2AgwJjKXKNld+uwT+1kwCmpDfSKfBnLeHTVyWcpOjqWaeFbNFhCkyM3gGB+a+FxEwOz4wEDLsvPRVxg2/89ys4gHSJ6FM3leYYhjAlALjOcAWGr7UXPNMKDgd2OvGUZoVeBgNgA6KDsGvHoQ0vuqU2wSSuV/j7B4JVbWfqsUTcvcJhVsAyMSvryD4dXyvNNfJFuBnjQUx3EaChMRgIdDz5M3AvzO4OEFGPW3Bw86p7gAaTYtOW4FBLpMsHkAvYVK0fGUgw9JKCn3z28H4k3jdCm4n1PHdNXbwVlyAxwkVzyHiQ4vqtq3YBTNGjD3aOsHZ/+J/vZ6FQ7pHiIzAGTwWGKkQBSJ82Yyw0WoNc4nVXRmNBF8ZJipPYxDVnDjkDks2AAPsyXB4Zw11l1iIsUbxZOr4WgJiSsYSnpQBDCzt6s7pFh//Qhhi5AsPXmoW3faCj6A0GDjudaFDwEh8rYHTytnCWwJDRdnoVMQWUaemnz9v9tBNinIjpOiq+Q8ht5x+5J4I1sHfeYIcVGJIxODB8aAeeKzjwgY3lRn8p4Oevu9fp0JZACRiAfC5XtpT1jgVacIcMAvgEXQdIxDFeUXvnE40SplwgmcawtlEKks4KSgBUBooVfQHABAzp2WM8FPFfUxbeEDgM1hAq9SRAOmNYFeoaLrxRgMONuwqEUxSiJg7dxdpHIMr0XSJYcMOYDeM+u0w9BLabWTEVeAeHADwAkwJv/nkZ7rgQ2XwmfPKO/8wnnsnExw9kguSHZA0dH/gFDTrA4aYtOkyEayRouhkg1L03eAycEOymc2Ao/HHMdDszYxRZwBRJcWUupXg91iXnd+Hhd8DwnF4ba5+dO57pxO4MorZDFWnjuhsUnQjsMwDXLLK1zl7vHtsZKqE3MQbRrI6iYW6OPqEt+kZ0nPBzYjxHeH8Bh2qaAphC8TOhcBUegSswtAG2rYKDs216xa54G+CAqqoibSMu9Kf54AkTIoAgo+Hcrrw3KxwUWHEqDxoHAL0BLZTsZpSQi73QOddC+NnM1BA4NYwKYAGFeFxVeI5ZuonH/WtG9jUWHwDW4TeSHAAbi1NlA4pQ4GOG/MAv2NGLWXHjyqRu4ECM5iyhsotOBgYf6IQQ45lPdBgQbK4xbCR4aicE7gVqffqJs3uDsbUXUcSZaJpfEyiT3et43tz7lMFNa/yCA8QersrwtHjbVWBI1y7ClVnAksysYLL+kW0VbkbvI1H3LXQMX95+qsVCdDZGKkyeI5LSbWiLm8j6dwKkgkCDjbpJQYV8RqlRjEFILtseckGVjBNRz6CuCQwRxDZ5+PC4vA1wiAaoLhaEOCVeGZ3CYoMG12CXhwuNKNYS6Ljp/myCmc8ELJYASMn/ZzMAC1Jki9unQLEt4nWt0zApKG+WJn0GMAFfaCdbqaPVb9jN14cByB5CpANDZQ13cQ4MMqZQLjkyJgsxBCeECDuZHb5Tx0mM0wfhqQEWHSczNowIVLPBvdcLezsigWEkV67gMOzfVu51iKkxGdR7HaCweVtYO/QEz9pOT3QmAK4CLUPQwBM76rD7L2IgGnU/PZJy89yPGwk6C04WNDZRk1ltDUbGFARQULaF9RcDCMAEbqLyv6kfrYJkibKN3ykAkkl4Sl9LRlbaM9r4zQuSWdw2nyPxZm9EK2GxACZgWM0KcSUntmo7wTbLBDB0MsQvs1ljhapAhfP3u47OHNl5iH2fA3aRrcJ+pYukTp0HfZ7q579JgeY0L5jay/va8RsETz4onshAoQY+DTq96AcZvixoSqZBQBJoOtlAeaENO3Uc1FKgjBDkjRoOv/bNNRxy7SDq478GSAxLnzGX66ltEisor0FX431GPMKO32/AIepfgSGBBjL1j0bAi4/dAIgdHaLsv+GgpD3ZAxfWShKDjP3aOXNG2sXrYA8cYdIRRer9AAU0S9ukJZJmhY5VoWmujj4GFGDgsWw923fx8NFF5JjL2wEHn2nnwTPe1/wEtcOvS5NNbS+dcxw5HcOIfTLnTqjxe0iZwVAd4zXIZkH73HtWNSvy2fMVVhMjPvNz1d8e9ZFyrSMIqRUm0Eon5RAVQ2D043KmWIOOUl5QdBI0V+vjvNAxiLiAUw1BzsAozPdmvX9MVbm/TlM0tbfaREvr713vMZd7V92UnAApQ2wlTbNiaA8KkDhAKKCSxwhoeG10rFGp9a7XZaCIrMNFec17X8TI0hRKo2Um9uD9pjKHGjU5bVq0mLTRf3NSimsrbV4Du+7K2wGHm7LOMhMo4Pq/GRgGhYx1+sEg6ncqK1gbanR0GszB/jENstsv5+ePh8Z0s9b6LXVvBeii068l3ZflwlazwgaFtQk7ezjQ8rhj+S0ADkp3vzcDW7zuy3EEZDvcbqZ7U+6OqgMz3t+VW1OK5PL/AAgo0DFHPd6JueNc1/t0x4iAGMAP6jxbquOzV75y+W68LhPS5dCbz9ZT3JX3CMn38l7ey2150+DwRWcZYNjS/Vv4Tv2du9+6/f0ayPOFTv74er6V+q1Fbm5daCz9lTnBFl19a7/b9b6bPHJlrkXxndV1/N4X66539TfXK3/yuPq/R78XQXW1fDfqZydanj913PewvC2zQq8DdSy3LunUdQTlxHtzRzGY5AIQdVlurN+v5yo/nxFvOv3+zc1XDN/9A5XZjEkXKjV0S5r21qy/N67pGkPQwRnZGMJZdF7zMDAAc1PaK3qVnkbnj3PFQOnlszqgwp25fr4GR0m5f7q27+StGJ/Ze/Xj1dpoOWdtD/vtPt3HuHbxlXLdNaYGRiuGjiyxytEGgtoWK4hwuS9cvksZmg+UblDqORacUfaD1AGjLdb38XIVuMv3sy9Bp+/a76gDchlPpOW++Oe0RnLO5e2Ag1cq6gogl1evwFA7nYAtjsFVQ9F2q9DX1GjxOs4TMfU5UON/kTmqdgBfV5GbFTwSfEOn1KFGJ07EtfvenKLzb9eIRAHh1AbRswQfMV50S5W+q0U9vmgzO1mBkW9/viwDlwCGWLq9JTvosJRphzZ/zZ4YZsykUtotIk8jWW2sfoXXM+orMgDDnu2Y0HRiuJIPrHpfAjhOZWzx28rYHSgTzMr1NigEcgG/RqOD5f+8DhX8Dm35eDSh1PddlkS12QZI9ki6AkQgpH9W7heh9J9cg1HW88g88ay/l14RP16UzEUPJADTJ9jO2wCHqJxnaYoNTTV8zUzgfLbQ59wQJGIWMNTjlfLVm3h6gpMu5rPuMqTN3Meh3GSJnA+1c8d7j5B8zBy8eqFfkgJc62dJZ4QUXRQnWdahJmMR0OHus8i7cFDzcN9zeBhgkY6N1D7z3w5vxFpEGS9oDjINL9pw+K68h26+nJunwWGv/Zrc3y+eMSkGcveHyBh0IjzNYHfMIXfmYnjMibsEPQgqwt2bCs5IQqOEQ1ouFAOAA5atqqngKAJjB+PJXbWiszkhzsiOqQ2sbfoEEpz1Pr3dExSFJ2DQ0l8Q/STTC9KUoBi4ZxLq93DylAng4VMGHAILMCMMx1zxZIhnoyGyNu3R6DICfV7zV7wNcAAsdTchAQKADRzRaQAxKVh4sAOPWRCh9MPfMofs0JTAcPRms6RH9MUGL+KP3n1dQAUsz/MQYJaU8bZSfpdZ/SbYTZG4SZ1ANINfF0YnSzQCWJCXpTAbwHBow+e6g32kMSRDfwHrtE/UzU25XJtRZPZcDlsCQwBNnP+j7Dhk89cbTmk4PVTUXjNepNkA8nbswjj7yOJs7VgHzU0TUTy8hztAGKPwAd46WBgHtbz/L2RgyMpgv3ZWtTZZlgwwRixLpM+Ltoj+sbbB57J7vTnrnvXu0Q6MwyeUM/pN58EuEX2EPJdmAEXJXA6r9p1pMVzgWRGgAgRorN+Jg5zQptsUFr4O8HCfWlRfnOxheRvgoLAFKayZwxHwmbWzrVUhzV2nahG2jtfYBh0X2pjHVPrns13Q4KM3dL+RZ2/2eR/AILH70TQTLKzhUQNXl2de1qA6ClsFOlyZEfDT0DwK76Xb7LjRHFvAJLnMeg333ek0/UXl4arMAz6wdcPnuufA+Fz2fP9RN3wsABGp5F6k4UU23+/CgOHsLYEhlsAHOKRptmgJwBwboMolfB0j0jKbU8EOGEyKj4+6r7dHJ0Zniwbdi5nFF83BmZEM5lBBMuqe9Q4G5f3l7M0TB3kdfacsa2zb4wORkj6ei7kwwCHMjzLf5OC3a49Q6woQ9q9ZoNCYiLxBrC1jTQigrGClrwpzgFFuxljyS2yrWruCiG/9taIEYcIGytiHT2UYPstmLmcfFF4KMIhwgoJ2HrStD62B5FPgAA9vXWzQtJHthnWn1Wc3YCAgI0DDVLK0bds08yVzTvbEEDrwQs3WV+Aan2BLlIe4eeiGz6WAg+74KDu+IU85e36zP+Gjp7AHLMfi0S0B7SGMl3PLdozsWtaeY0VmguvSVhqsgdSEtLJo6TWx7LUSfULYWAvDcz/CY0H8/GNx2TAfAOCQAMMAhpbAcPSWTPMMpiSWT1OELeGug0Hem0hHv+xZkWZF6Uc1rikYwDDBNAGCEPrNAAhrswoYAyCoTkoFhG9Dtr28CXAgtYazUNCoFKAUFLzh9GO1DbsO8HBqH+h1tWUtOjGHsUekyOjQAGwTk84j+WznYUb00bkpmQPGSs6bKVEJufemRnz9RGzYb90cgMOk+Hhu03u+YU1RhF1cJPK1ECcO2qZQ4el4V+gjl0PMkIAxh48OGN/sY3B83nd83u2Yj6fNoiswGLCyL3d3nUFCpwGqij9HCNp6mk4huAlUGe2ajS3PO+oyxNvMB+mLxXYdOR3CBHuUzyH0BQBpRq11/3hu+Ng3fHRweDkNKM7T+83JuUN59Bc6fRPiTEsPs5465YQT+SPvAis1rFHAzJGy8Gp4QQrVcGtM/bWqL+hoAvH6qSjEQ6v1FXR403EO7+W9vJcvr7wJ5gAFuId2U2iUZ/SN2dWy7dh+E7kWn8kUfh5ZgtdS3ZbBGEJJ730wB+mLxhD0UClT01dBafZZL7abmwqx10A8xtp+B3wNujemyUvY+AOCvbrwhNkXHLU0Px5nguKLbQ0gTYlqTtSZE8BkTrycs04T5hiAIeSu2oyu2ad9UVKYYY2gUv3yNDHGWCJe41YA2NbzsWJUGSc1HNyxa0kTt5pZGcNAt8zhxetfWcPLWcyKs6GfDeJ7agZroHMwBz5dgDxRdm0vmkPtR7WEZBUMg+ALr7w9Wa3bVI+ZWWdmpbXxXpXnNHHabPe35OTX8mbAgQ5bSgyU9Q8lwUrSb7WkGpmnXy0vZGPKhTtrkeJKC1AIFV368G/HtutpM8ZuTfEaxVasAHFbKZeLPEFH7Llp1YhOb3culvsMgPhit2Xazo2NHg9wkIfrA8LG7iAcsuGjbjhkDIyPxaT4vG94kS0HB4AcIClCdrYBEq7oBFIqHh0sAFpe+6Ik9a0ARCxRiSYNdo/HFmBQTMUyUdRYFgMHwabm2fjUpjax+xeAfB3AEPpK1Ds0h+PY0E+GdLLdv04CwoxwcODTdYYTuckwdbhJ6tVfzYoiI5gm4695fM9ERY9jaAUbMrbBTdgADxlbSGpJjfBaZOebAAdSa0Qh02BjphRfAB9JO0V9WzwdQTXNk6fksuGy0qwCcfVDV1ConTlV5hj8oTI70gNDbwikX11Qo1KO9OLAEDpFC1FyxLDAZztVKae53popkEtts1sAkDZYwJTg5MES9po38ZCW3ggAPlsaECQwdAOHcOEdnd3WbqkzTMBa9q3wCx8BQJebH8IbMrBHG6DSMiOYNi6soQRWBdgn2JJt2+e5Hp64g2UzzQH3SWJDs+hKw1Wrtj2g6SoNH89gSs00FmcO/WQDh5OBgydg4MMnkw5wMIaziJF1/1XF6FOlJDAUcFAq7JORe6hIxP00LLEV5HklMe6Lb3BjeuZbZw4AbAuGmTnEKkqCq6uizhosgy9g4goxeRah2Vsxh2Fj7HZVQCHNB2A2ISZ1mWa3UxEjJzo4e5Oy42ugNAfV9uuTiu5G/QRI82lc+zWWX8qgEBCe9LS9F5aMyw+zLcNExEMbTm3JCg5lfN73HBwVGCLXZgLDyUWh52KGefWrX/+RV8cV+chPYLOjg0Qk4fFZL4KLIi1bF5napjNjbx1dGHvjbI8XGVGzdSl8fC/iXyo4HN2Yw9E9tiHFx4bzcFDuBDnaxBj4CAHSqscHDYAIULjZZXt4K0YjRe6QCRzYJhx1JhpWKWeQ3mASySLKxGTHlDZ/694KqDWeFQMI+9heJ0VSAMo2uJwidR7gIPQKOKAMRimgENQXYT4UUIj39Ub2Yk7c0cGoAgbyW9owjPReYcaImTyp5CdDwkTBI/wVGDEbJ484/1NtL8edOzaJXZ767Pb0UtcJBH2O/TIBs6ODStu+mW3SFgDgPHnY2Z2h52jLaDOgsCyPCblbOWxtFGYFRuYkLmtQxCYGkZk5BouIOJXebF1NI0sHaPlF25wbophatf3CzZ3t2c0bE6ZTeCW6gyIA0xgOZ5cHGwAc7pUIs+Jw9tALMCQ4eH9d9asoNHYgBwIcaAaJNl5bXylMwtkCxbHRFTJJDOGilZXyJsCBNJhDfgIAEFUwaAwgt7Vsh+ygUZpi1rTTNhZ7SgMcxmw2aQq4AYekf1TMiuvNfCQmxY019gAQXykgh7tvgwFfxsKXGUQLoDiVfnaqDVhnPvnExiXP4ZSUZA76CSp9SMsNZCs4fOxbDo46Y0b8Qg+33TnYwsS2kmWVSMAHzCE2n019hjXBNEAmKLGKzYK6yYVFAEAXQRdCY02QWLcsqLEwNf6lgkMEx1UXbdRfToYe7uQ7CeRaAx9w8dF1Bu/PAQpmWsRDl70yH/SjanIhwEEHSAigvqu5FlYgziQMPEYmqowDC8ZBuL0nUd4EOGAFh5yJffbYCyKq21DF94uwnxwcEhNqxRdhjCZtwQ6ZotfWoJU4JhjDne5QSwUHHo+JAgpSPJIygNTNKMDDKYJZeCfefVBE8Naznjio2e7SDg512/k123IMiFM415qEIBmgcPSG42xFkecEB12V+XxgYQ6LPX03S/nsGEo8EU1tlfeuxYIjN7/Et08s+pM0G+CNBWdnbC3yj461o3eagwIzOAjN0bLVfDoYcOZAnUCHaQkBCHzGe/+9Ey5GAnQOUODVWxE7bZcyJhfvLz6gpQFghUgBiQBSn7wkgYPG3hZrvMRXARyMOSjgQUJ1g6U0KTbbA4GdSoXinxQ0IhEflRjISXULS6iducx+ifSKK3OQAhRx/qlS9+BgYpt/RYzNyKZgZwdjRWM8M2JXrbp8PNKiAzbT7b4GY6XSj3bZzsVSzhxq1N/R+eqJCEUesMERbOGkx0B65/KNtspbRdlGEVE6qPLQlYbdHHa0+r6lMtbidAY3MZBgximSeSnDi3UbPettOsBhRHpKr94Int2Uri8kABzBHOw9UMFBB0iIsQdaQfTB4pMMJw8A7TbgqdugF6lt5f1LRl+LfhbgMHZgw62pF+U9COq9vJf3clveBHNIs6KGgXoRIGdVuD0+Kf5hn4YNdUceqjmxxCnMYmOZASfzAjPKJ3PQ+63TMa7D3E92jdIAdOQ+GFYXpPkUafFNcxjHALOrMxhErH7sQpMYV+3sR8zh9GXGsc4k9pqY7WyG9CXAB8jZM91zE9O612eAhT1UOSjMCnJdxmfEtKOFygyIoj3BV816XygeDUvJzugsYB7rctbuEe2ZeRhgmop6sNxdcNMQG90TEXrDYczA3tv5+dTZtHC94V6Q1HFRRdROc8DFbV1MCmsHb4NgEdFebfSzwRyGQP4dmRVE9HMA/gkAv6qq/5B/9usA/JsAfjOAXwDwk6r6t8nW3f4fAPwuAN8A8D9Q1f/7J38jwWFpGX8bg8XEu0XxT7EPk3gzlSoeljiFKjgCMxBMzxM46MW0+BQ4gIYoNAltiuLGdPMpNuDx04h7MdLVmfoDMm9CuPVCjAtwIFxt7DhnJGZZl1nX9RG9m+iobj68tl5gBda4r7ObrrTVAg7gci9pAIK1obqQGzqRn8dNDOTA0NQiiM17Rb5ZcrU4q2mh2ZY0XKchEve57hnDkNGPZjbwMXQGe2/6AlA+O7V4LXQGh+7AcGd2kZZVyuNBMkCChCCTqaou4BazIoLwgEkgf2VR5hdiDn8MwL8O4E+Uz34awM+r6h8hop/2938IwO8E8KP++EcA/FF/fr0o0I7aIqUHOThkGOgS9JHxAxF2/QpzIGByTaYXorCCqbMnOOiFOUzuTBTUj58sacjVmU0ThbiHAqjMYWFINdZDdQSDFU+GfdeFRhmRgmObM4sWfbwQDZcwcgBTCLSEN+Lk1BeAEtRzE/k3aw7fHjiAfbyHntOsH3BljtF2oUEBk0djbCREkLKz053moEC6uQEHhRI+H3U3BjDHMCQrcFCwZ500B3YhMgHi9GRFdcJRDLpYCxetgKyTKBNkGyAhMvqn+PggGVpEMogE2wIyryDAJ8FBVf8iEf3m5eOfAPDj/vqPA/j3YeDwEwD+hJrU/peI6O8noh9R1V9+7TdIQpAE5tFtZobAJtycJLQo/q7cBjBM7KG0dVXNhxh5NSsmNbnrww6fN3Tt9OUHZ0GSUoGvFNDSd2EwJHgYeXorLGI0mQWGuzPDYYEMMWZW33npXqEPdT5jBSKUvC6z9vgFnGTmV0b+RTuVwJ4S+ccLy5piRCptrne4gHrttFwG/SSqiUI2YLikS9tH9KlTbjTfhyR2hcI9OGScSUQQCqa4jQAEKgAB4AoMhw/8E2jhygyzoqu/Vu9fJT+JFhZxCYLS2VvBBGk+0WwBBEiPDeXmxd6nRK+CZAi+hFcR4NvVHH64DPi/BeCH/fVvAPCfleN+0T97FRwARXupN43KkzGKYVr4jBsVjY7glb3N0R8BODHTR6fVxWQorIGD+r1iVlSAuC1hIxYVfqKANkrTRAoQtH1cB8IpCFK4phPW4e50oFClXIob+S8eMge3scO2zlmlri1ZtYUYFH3MoBn5d87AGhX6dkF0mulanRgMTHXTBLk01QW+qaz/jsBmXo++zLarbRLgECZLfCa4AkMBCOCGMRRg4MmsUGMTDgjBHDLVYY82GmARi67MW+F9wduHOkG24bnT0q5Vm4NS0Rw0I2opzAy+uR+lfMeCpKoqPdo145VCRD8F4KcA4A/+s/886PwADndWkocxQMTTVWQnafmvrGyuglx/KxpPCyg4SOQaewRD0AIQ5TPvOPaZlnPpJ8ABSZdV3S1VzAozKTTBIAEi+4MBA2XEyvxde21mR2cFN6OZTDYa1+ZYszJNYeTACIHuZdYMIIh2ihm0gmm89/bK9ryYX8v1EIoYiRHko2WmWycGdYBTHasS40ClEReRnZ/GDxMwVjJhPOsAB3KTwkBv1L26LYGqJwxTIoBhxDk4MJzq7kwFdzFASEHSKnhxZ3p+yFwqYKnCQM3SzkmjydVd+8UACXePMzKnRTAQ+oQr89sFh18Jc4GIfgTAr/rnvwTgN5XjfqN/dimq+rMAfhYA/rl/7l9W7mrbLVVwqDcy7PDSSYArAt6GOsT/VuZQTAsAQ0kubIHTtJg7PIlehaRaov8lVXb/PK8mA/z1DBCzgOap91eAKPVTB0xRjMQphPu7H4KbD6TLYqk6ay6DAxh0mmSAQlDnR5rDYA/eQb2C5H8yBNjFZRv4YxCzjok9Km7Rs1omCmcBzUGieLFS8S/3Js+lSFPTrnu0QfaHGs8QmkO0Q2oJ3ofOwhwCGA5JcKAu3n+8IiLp/bJr0tEBiLIdiHzpuhDQ2MeBDNMUmLxf0zOvY0a/Z8zhzwP4vQD+iD//ufL5HyCiPw0TIv/zT+kNdrXWeEpsN6G6bkhB3tGn7eyiUk4hSeJ4VMKRZdYcMOivAwBQZ74BCsEURocvoCBItF+Zqh1MNiMEQKi5MfmGEQEGEAYEow7OjG0BGql7DAZATNV0ZhJLctVH3qrOTza2AHV9CXK2HCJjNSNqO12A4YHb9878okRsZMYsA1BrJ+v4DqI+OJI5bvDVaYNZ1UJKvuW9mxyk6ZGqi+KGi9vaYw6GWwLhquCa2ksVG63PJEC4hhaMYQKG08HhLPZl9qdyr8hm97g3ymyrW3ncQ4CnydJM0qFVCciE3IZ57MQ4+E7AgYj+FEx8/PVE9IsA/jAMFP4MEf0+AH8TwE/64X8B5sb8GzBX5j/9qfPHxdJpO1orl4FIALNTQnJh0mfQ6O8CjISc9RGNEPUojTFYwzLTLWyhup1iJgiVuSrMl44f98BdaUHxoHHDrLDTXRv4fs99psuJg2FrFpx251RbhKro57Wzx0Ym0wVhmBWTna2uyHuD1lDodYBYG6yD5mqKRVtd2MN664tZkWbB0p7rHqcTOyQUxqXzP4LVxepGVOC231pNTrvutd7LWpvaX5ZHAoFPOAkKFRi62P8dHGjYSpPHgthBOyrc1DpIs+uWgIFGiB3QZo/5ELPF29H6AGVT3xHtKF/EW/F7Hvzrt98cqwB+/6fO+V7ey3t5++VNREgSgq57IlWnbabMDrOCCECfZ5Kgmq9FSF4EyZj5V81hZQ0yWEMqyzKu9VVB0lFZnV2k/XyWZDbks5LTXvXfl6CTsOszfzbA3RLigGC+fJ+dUq5sOsyDsDzo5vKCNQSdroulgi3U2bNEk8Y1cZ1JZf0sWBZSAE7TKy6msHxjx+QJqD2WA/O0xvBNWgiZUhDeH8YxZmKk0RUsJILQ4vPxZzCakrMjTNC7FboTM6oeLSmRj+d8DHeZWcMZgqQf1GUwB2BoDiE+NfbrIl8PQdDNTJlYXpemYx9EI9gDXM8amo0OTeZ7oDl8d4s65XIwSAFGtHRMtxu9U+SybB8YwKCo1/MPgJiAoTzs927AI1xOlSqXCLfQHm5LaidO/OM5Ig0ZCQxT1GXUFQEKPpb9GNvpCGPwhN0ei3RkmGIPg8KqT1/W9zW0nOZ4BdTrvGvLNWBMP7lAzaykEQmYTbYcR2J1UrIBmRqTlGMiNsDbd6i7k+Axt0WE1cchpe6XfvKwv9S+sXgiymfUdQBD9xOJgUNOQEWQrAI2mMdQJ8uQZu3AQIib2TbWDlTqT7RW/DWj4q2AA+DOesUUENKHuyVuQM2jZweZTRWCZLUtq42b4ku1L2U+V3b0PMb1j+maboBhESTj9yFkwhv7B+I6gZbf4xn8dL2mmFDymsmuZRKq/LtkUJlp8KFzH9B6cUCuTp3aoLSVjLaf2jxn2zJgKvjW+tXv3wVBFSetDRAf/FIGSDl3uDyhNyAZM37tA/5xgK2uOFH6xOrVqn1mnVym43QGSCgKe4rJxUABItYOXVADXijYQzaM1T/7PJDHExFUBKBmk6ToaHRxgPS+ZkDhrwN8og/eRWSW8jbAwetG3oFig08qVNQ2/pzZA+BtKDbr1Ps+AcMECnNQTqW647h6jI7OgXqNCzAsHd9gIWZx5M2gMhMEqCUAlkeeLgfWGCR3nfnyP7+KbGBggEK2+TAtJuBYBsT0GvNgr22YJtalPcv/lkKqdpnmkjGgy3Um1/pRBI2V3822yt8jBxrMLszSIrUd4JeA6TzXdlj7y2SqLn0sj5H63dFnqhlBMr+/tFFgSLprAhgEGjsxhy/TQ8ctd6m1g1bhNa4J+IqYFUBpsPqZPdF9vxr/e50d3fzW/Hqd0aZoynhfv5ud4x4Y8n/wWdDrpamgD5Mh1wU8uj48qP9NO8W0SOpRgaifP6jDWr/1M33l/+s5KijcnAco7CM+5vL/BcuogmgAARbwXOuFa3ul9lM/KMfH67s6T9e//ub0fZ2u+Xptev96fV9n8wXYKrSRxv6rX7C8AgKPyuXn38snSqWxb7To3Wiu5bt1/W+8Hb7S5W6Phe/3JXzZF5Alt1uun9mTUpn8aJ4I7X9LQy4DeAqMouX//v16jhrrn+8fXLMde3NA/A/L+UtG4Vz8Uoou177Wd6rj+nqasuv/b6b/tX2W8qi918+m5+V+rfcNwJwVK8Pli6k4xSQQptWtN791V6fLtcX/btp2rVPe++Uct5PCdD2hadDD/nD7en3vIdL5+frwzx/+zqNyGTOf/srbMCumzjQWmuTr7CB0uXn1pq//q/VXwHUY8sEyvjeClmDhu07LY60GkS6/Z9dD7hnQlNXK78Vx1cUai7CoXOA6kGjp/PWzMqBW8KqfX8Civg97mpDRp+nZADxOmfL8NfI03KshBNa2qe/H7422diPrcuvXwb+2xWjLuA6a240xtxV7Pes6nfVcpcTbGrFsx2vpd1E/5Bqeem/Wa5nuH4/7bsFL5YRltSX5svx1bcW08Crcmt6vEiB4nCsWZ2mLXJxz+9brfgiy5dLfy3t5L+/lUt4GcwCgzcJCJ0rXltnkdtYcs9yKhImUPpnVmTBnGUURxcwjkrO0EtBMdNTJBnT1TOGz4chalIXrtQWSO+JHnoJczo2R74HKa9zNSFrqWpiBz5YauQsqO6qFgBR+ebCeSfEPdzH5+dzdmowsZlBfLEWxqEfH87iucb7JK7LcJ6tjuZe1DaoZUla55uvCCrI966webGL5XSCu1wOwSrzEuGYMF2qe32f8vBeU7T4Sv/oxEXPSeMRpNAJVN4pI6ZvzBVqfiQguZxLkn2U7FbbNxdRd2nJc91yPR+VtgINTI8twQ8lnprX9bbyWVipac/Cv1Kmy2PBZR8PdybcTqxsr2mQbayuGQmz/U6LhjpvqVMCh0XSDprRfSf+WARBt0G4+r8cCFhlZgcGzIE10G6XKMVBFB0BUj0eu6LNjY+FYekQjtV1Q5uLCjExW071N991Nk/v9mECwbNwC1PqW/lA1iwDbhrHaML7j7bFqH+MC4O5RpGmYl+lu9ai75eNY7o2U57tcFL7EGjHBNAKB3ZSI+hHQBRchuZoN/l6ZgY095Tzbwyef+L1qUsz9rrbT0MQelTcBDgpAt4GAspWBXwdPdgoqsy/mjnBX4QAFRYlmtMZZE7DGYhVoeQ0DCAAZmQeyQUFdcdfKg/042gcQBJjBVhtOn7f62ajfAMWStr0kYAUHQLitXdjDnWal0Q4U7eExGVm8sXyml6aW2k7L9+Map3bCyGQVDR+zroNN9P+pycpsP08IpQ1KG019oaFMJqN9coexwjDst1Y3IpV+4e7Ioo4IRt1zVW3UQWz1pwGE5dFIphHBj456LAJsnGcljAQ71IOmaXzpCgjwevICDI2gDhYALDtUs4e99j5V+t0Evq8AxJsABxAgjSE7Z8UAq5S08TxVdBk8+BQ4xKMwDJvUxpLmeuuIfJ2D/59j1SKphT9HgAV5R1p911U85bg542YBoz5RtwSIbR0YAwwmYIg0cQEMziAsLZoBxKPMWGDfCyLbLGbNwvtVx+clPkMVwOZAEP15AQhrAl8TEzNzkIdx2rycFM4YvmkLRpbuCTwXgHDQjPYcgKGlb9ywqPxxHWtzMqeFTvReK5OKzEtApvkjsczhJLAVkMFSgVxOLeAh8DHZwdmnJA6yUmNfHBCsnYx5KDsg8ACGMaHeA0NMOsAyZvC4vBFwIGMODZB9Zg6yeTLNDVnh6CQALqzhjirVoJk1Th6EvEniM60BAyZgyHQAsXxaMRZF6dLbvSg5w/HOLwUgAAeGrJvXb5vrl+/9WTfPodgUupUe6ABBTW29htvZNyw624McILTzmFF7pZuDQciGMvg9VVoAhB+f7RWsKdpaXbOIC5huTrl31bxaTccAhm3839qkpLAP4CwAYZPGK+Dg1xTh53HfbDYHcI66R+4NKd9jjABFKSbZWux7bOP89HBmDnpBCQ6XHJKMBCrrO5wmuG6eDWrj0aecOYiz7nhWvhkzXwXmoOQgsJMPEvt8BYYcIJU5hK36CnNIOutjOMQfkmHWAdZBzMTTXEZPLihltGSuhUDG+D+KOVKaRUbJmS2Y0RUYov6abWCAMAHDZrtOB3NAU1ATkINDTRF3m1AVyH0mlQEhGes0CEDHiA0IgOhUom6dUfU5f4CZKTQ2NHYAVp9V7QeWRroFh4UGV1ZVWdamy3HxXm2GX8XZuMbVtonxzNEP/L3Mda8AYW0Z1kgxCVJzuXZEWwfiuT37MB001+lotk/iC5cYmQCFtoBDo9FfWgWH2aSY2TZ9NcABBMgToe80MYe+L8BQZtWrWAWgxiPU0ysyBDdms+iMmWAFxhZA8CXTNvsaO6CRPzFXIdIAhhuAWIW22ukHXY4Z8AoMAZABCBdg2CTBgZqCm237Zpu5OHt4RXMY2acJRJzZi+2aeR60RJ7B2kENcIZAY9EjIdsrch5mer0KznE/6nVFG/lMeTUrCptwE0u2+tkwK9C8fQhDmPW+gbjW0RIl+Y0OgOz2++hz3StARGEESAQoeIVWtwwBfHjfap78pWScVk8yW7tRtlGYoVQExo1zoglGDSxmxAqmy/4XkxZzU94IOJADgD2675UpOwwdy6C5ilXFtnyFOeQ6CB/YMftLvY/sHZwxVoSyrdPvOavUZbyxtuJBC5dOfxHRMMykBITKJPZiR28K2d2MaApsCtoE5IOCWcFN0Jplno609OwAcW2PsamN7Qk5logLs7cp23VbVJh16pzAyEHUAAIdCRIBEIC/XkD0zpUZQDSJy5OAhtFOwQ6qDjNpL0gTC54uz4BrtEMFiHTBCo0ku56BKXWpMDWJ/PW1EhQsK12mAQquXwTIer5JY6AODt2Yzv2OV1QmwgIOEwjQBKRy0WjuRe4M0HtQ+PG/3st7eS+/lsubYA5KQH8arEGSOSx0e5kxgJiZUTSHGwEgTAqfwbQmKOGRAUhi5ouH/980imFHT4lQHmgOac6m5lCZg8/Si9hYzYehOSj0hjXwJmAXtFpTtCZoHA912v8KcxDOXa9O1jQrelcIMYSNApsGMTwv2U7BJFz8tEQ9YVZgaqsvxBzqfSzsIe/xakqk7jKYQwiz1AZrIN/tKsU/3DEH2y1s7FTtzCFiUjiYktV7CLCaJxsh1U5F68zvzIi9XpfNf1qsOg0zo5DRyhxcu5pd3kN0BGYzojKIW+ZA+CqYFXC9wYAhNAcJzaHQ7erSA4Ie6auVDVda+KCh3pHV7PVBg2l4I9ro6PbaO0GYE486falTpcsRHRk3D8BM/TYHgm2ABOCDYA9gcFBoirZ1tBbgINhYsAVAODC0MiBqUR8M3UFi8/0yAeBk2/+idwXITAw5DS1rIJEyLE0ZDfOLYi+E9N9jtNldG2E+X2ocxWVb26m6cRMcwlMDJDBwemzCzBoguWowob+EiQVgbKIb4BB19z42ElmHGUEFHOxPtBXH2hIm6KlgFxSpmHKkkVRoubgwtRYTI80KnrWFqa1uXOTThBUA8Up5E+CghAEMDhLAKtBp0Rxm5hB+bA278qYDZAIRn820eaftJV+jA0XmDawg4b8XORUH0BRb8VIvGh3/RnMwYakwhuj0GwwQgBQfaRfwpuDWsW2mL+zNRt/mrxsp9tYNGGjstF2LxCyphNht++gNm888Z284mXFws631Qpxktd2mo15MAxhOj2dgnYHU21gDHIBbEK3eigxeumgOKyggRdnUXoooe6e/AEDdBSw9Nw6UuTFx6DAUAGF1j1Wi5B2GKfJaauoRUZ/cXsG/z6cDRGTrbksq/C36Uu0/pX0A1OClKm5PGtwdKNwxsRBqj9uua/3q8b++jyXMin2wBaAAw66jwrVzAEOZnlZarv4g2P6U6cZTkO/yNDGHECFXkKizYQMyx2CyBrqYFmts/+rDt2t30Ct1kw3QfXgisA8zojXBtnVsTfC0dWwODs+to7Fg524MggQb9xwQ8Sxe/wCIUxtOYTxxx4tPPQcpmu+1aQDBoLOhM4/ctUzAaWo5TqvT1F7hRckUe/SYOSQ4FPbns9zMHIoJ0XS4b92kAgB2QGjNgHFrHUzIjYVrW0RJoFRCD1FWGGfj3HG8u0grzMDBUO8MwmFaWYxECLXhvYn6kc/4fFodqdHYOc07y5TDculDFRwsYHCdbGjuU4spkaY4j2Py3OfNPfHyJsBBCZCnMCkKOOx6H/wTdBIY4cK5me69AJAuK4HbkzBK0UfDTvsUrCARDH0Bhk8lTq03+MIcHBgGYyjawu4dfhM0f2xbx946nraOp9aTOexs75/4THBgcvPiZkQKCIc0iJ44lXEKY3ff6cENL9KwcUNjxUHGIM6zoXvbduYR6uxRe+gxKxbmYI6OXHsxAUS1+0Nr8PuZzKGNe6zbMCGoOWAWLw1wY165idVYLkCZbZHAwAmeZ5habCBhdedxH33nr3D5hhYRABcgAdj9ZoZthBPZ1Hsw12GqvqZdzZpDBYZrUOAtKNyaFQ4WH6+/GeXtgMMeLrzixiuUOwdO2JgxO6XwBNxFBALe6RwgUmzyrMrKxYhsKB3cQaEZDYwIIO40aPIXtKWHIKm40Lub+AXaFBzg4GbEvjkobKcDQcfzZrD/xCeeuGPjjmfuYBLsDhD3g4Ehzaj0KQ0fZcOTGtC8cMMuGz7yho0FH1nwcjYwKU7nysYkFNrJZtPusRGsFt5btYbo+BJh5jdtVJlDUN6GYSaWe87uwmWWNK8211a2JtiKebWxXMwrLoAZ8QqiZl51H4XV1Kp1j3pLhjPDTccBEmZeaAY40TkAQr1PxU5rk8h9p11dmANSu0r3bmEJwANQKIAb5xnxHw/6Lt4IOICr5qBzANCOOSLQO0f4rZlNeIpowBoVGDalvTZbsirT2n0dh8902mMWXECieDR609Lp6QsKkrqo8IUuT3VT1xbGbLjvxhD2rePDduJ5O7Fzx4d24EMzcHhuJ574xO7mxE72iAHRSuLGrjZDdhhjOLjhWU987NboT8z4vBv7eOGGxhsaKV7YzI1o85hNiQE5nYk5e0iTKLJpC+FRgtkKDgkMDvR3QiOzMylnB9W82tm0l43Gc5hXCQ43C+3SzPLp91ROBtVIcTYHSK93MHEhhVCDkng4dJgVlDSAXJdB0a+yb6UgOfrQJXy6mCh35umdqVojR8eE9MgUfzSzvRFwGGaFawvOHB4F/gSdBJCiU0YF3p0fmBTpeChbZGAud/XdpQdVrjfSTybFPlR91ayYbMY7ulxt6OKJ2PaObfMO3zqe9xPPreO5GTgYMBx49rDNZz7xzAee2YBjpw5GiJJXj4WozZIHNxxqjye2rvAiG3YSfOSOz/tWNIwNH9l6YLhJTzbKTcS2YrT7Oo0A29B5cuEVPTArRsfNqMYboTFMiBBjd2cNYV49sZtdxbwysKxmxdwe4mB5KEN8+n0RE2V32XBww8e+lYjTIWieR3PGMLw5uXtduDhZh0lxYgSKNUyC5Jhglh78yKyoAFH61MWrU7WaAIJiir995kCDMciuQ6nfDBRi4IT41IqdGS47IkULNrEIcADct0+TMt27+ffF3XjaCNLpHiSKe26YFYvQtnb8BIYSxRmaCezzCnptMxMitAUA+LCbGfHcTnxte8GHduKzduC5nfiMXwAEOJzGGOKZOhruzYoOGwgBDIc2fPCB/7nseOINW9+xc8c3u+2pZDa8dZdgElz1CDcxDAADHHy0uHdH77w6MTM6QFCJbOS4nwsohHcmzKsBDtZWGwme+SzAMNqhtkn0j0Obt4f1g2c3tTYRvNCWdW/ex8JMJ1LgaBlFqSX0XMIDdjqTyHD8sYNWhpN/C2bFRXdYXft3oFAAF7ia4o/KJzyd7+W9vJdfq+UNMYcSDejMIcQ5Chuz2JphZzbWKfBnnSmB4tsH0IX9Iehsr8VZSO9cfNtDj1Aa8K1t7EwVy/Af2dJAoL3b02HrtVI/F9lWN2WIjc/beWENn7UXfNYOfGBzUj/TiQ984JkP7NTxRCcYrtTf7NXXYayhO3v4XHccbrQa69ixU8c3+xMYio0En/dtFvWcsVXBrneF8IgXyPUKCkweI2CasUakpeYWgdULwX6PQ1/YWVJ7eeKOpxbCbDcW1U5szp42FjSYmzdK1R0ElO1w+nVXHeabJNikZZ1rH/t4bCACjsOuX9y0sPUofv994dYlWCx0KxQm+kiTufVW6IVBAK49VI9euH15mGnEHj0bHr4H5U2Ag9IwJ9TNCACXwJ9t6+mqCioZrqqNjf4+ChcO4akLuzLtr7sBBGCd0KIDnSJnCC0jNxspW9Zp7MAFvCJIar6uNwpAuuPCnFiFRwAFGA4HhgNf4xd8rb3g2cHhA5nm8IFe8BQmBYkDxA04KOPQDR2EQzd80AOfe+RZmCQ77T4QBJv0iZqH4t980BwuVo7YAKftQlDhyVt0pzkMMXmYEzEJABjA4PpCeGrCS/PchtdmNrGqOOvnWm5UB6WJ1V1w/SgbDm3YyDxA3+z7AAbME9CIvFScSAtqLLMmykVrtmmyA0QBBxJ6dZIZ4KCT3hATzsPFZyUWJIR7ABk1yl8FcABhuCo9GhAAeL8P/NmLCLWRTODwSIALcAiX1ekM4mDG2W3W7CI4mcExC/YSIbfE3SNdoZ+oW4g+gdxsqjtgbsrW9BK/8Lyd+Gzzge/i4w9tL/iMXxIcPvCBr7FZvx/4wAcyJrHTiR0GDu2mPURtVnvRBgHjxZnD7pFgu4zBZOcQBxtFu4CDeDSm4oUaqNvrkwc4iOjwFAGDOeS9Hx6m0WntfoaG9IgthCj7zA6kLsqu+kuDYqcR7VMHd2gwob0ABpCHtvT4RN2j3nQDDjGUTpjXWzPsdgjT8AGN6g4HxvZ5RTOsoeqTt+JO3J5iQoaYO4BhBIcBDg6p1TU8Km8HHHadwoQBJDA8bTajVhEqZpXw798hexUkT1elhS0y8KXbTNGEcYT6LDx1cGMRFjY7qLIWumxKfNDmuU6DMawiW3haEvh8ZqzA8KEZOHx9M0CowPC19tEAgkyQ/Dq/YKcTH+hw5jAGBTBmyw5zjXUQPijjBQ27Njxpx+e6+7GCpgYKDdeZEjBazlCwmxrDzLD4APYNX8/eoE0gwrmG4XLrKzj4I4KYIn5hL8LjE5/40M503z6zmVoAHBx7mlcf6ACTppkFIAEuSleCgNO0AICDNnyuW8ZIfNM3ur8LKJvL5u1sD8BNDKB4rjxXSEfG1ygPs2L6hXDuLCZqCpBNh+t3cvvOXr0Qc+M+bq2jcbT349ntbYADYJXaFLwZzQYwAUNEBD63UKRdoXZ1ukYE3oHDiAoknCrYqONFNjTiQZd7Q2PB0W0WDKorwrnFuZIn2ZCxoatR5rnjZLRm0Mi4GUtEX7jkVmAIcFiB4e9rn+OZD3ydP+LrwRzImEOAwhM8CCrAoQyI7iZWJ8KuHQcaXqjngGYWsJpJEmbFWuogqfEDRA0EoHsAUGNF98xQofmshTDyTqR+5BrSXQToE/f01jzxia/xSzKHqrtEezQy1pBAudSnK6dp8RLgoB2sAxxrPddS12dYsSEVRxuLIAs3B2xm7+bv1LJbdzDT+jNa+hBQzYmqYQ1dAcCIB3FWamtMrkwsmBDRfluvUZMvu5CzBl+GHIPHIt5iAA1giE4CIN1VG/dXw4W7EjYSnMrgIjC90Cy0HW5iMFkqLwIgrLnYRsTcn0oMRZgbevUI0QCIEH9WW3pbgCE6fOgLgNnRlTFUYPhAoTm4WUEWCLWHSYFMIjS1dQR8voBxkGDXwcSaBnPwg76gPyvaa21DJoaw+voFO1aVJmpe1z/U6MYQEcOMqILjZw4Kz3wOYXYyr4xBBZMKcOBFoBUycOjK2D1u/3PVZE8VHCW0qxJZGe/HgrZ+YUni+aMiJDF1qBI7Y5lob2SHRXOYAsUWEwJAmhF1GX/0s7zHRae7h2wrbwQckDSobRUcTGN4KsDwoR1GMXn4tqsv+86PDcAjAht2DJD4CAOGl6UZiHRarBYmhf3P06qReHJmz8V4rZINgMmW1snTEsCwt+62tFPmYkeHvpC6Ar0UMDj8mI/4QB07BE8k2AnYATRXm+r4FgAdCsuEZiCwinTxpQ7TVYRMoK3p0exc92pWtP8pjE5qbMWD0NaSeScAn90kdaSYAF4Dhq+1j/hAQ3N4cvNqp44P/JJ6Q4LDjQbTYbpDsIqmYgItW4MJzwjZvR69OSi0sQRel7paxmrybVMcIMRAgDJxrA6gqG1Uxew4zvWrMCXMC1GzgknqWBvbZBvBYtVMe7Rqt5a3AQ7wKLg2x8rvTbDzqNgTnxYa6wMJwBQyHOCQxRu1g8FqA/PQljcd7QT6Zs+vlE71tSvOAQqq/jx/p4ZzhyAUKwX3AD8fDENkM5CIjg/A3xtdTpDglwkcniDYIfjgwPBElgS1gWwR0FIEiu6gYI9+Ocbqyt6XGR02iAAPwWYbUF0JzwtIvMTpfEyxjpkVQM2CZv+nsTiqhj7fuSgj+jEYQzAEAAkMVZi9MIcVHLxenRitblsWfYSRdd+1pZsTMGA5udukw91WrrZuplQEgil5BJ0l10l3NgoOiAOFRut4qaAQ7+keGNbEP0w6AUOwMcBMq4ggfcVZ8R4E9V7ey3u5L2+DOUyuLNMZALNDK+XeWKZFRoBRyQh0ySQny6q7HT3VaFa1B9SWfAZ7ACA8z6DVXJB8wQDbTFBZw2PmoJPrKEQ3AM6GPHaDfbbMsF9fN0EjHDqFNnT3Tjidpj6xhh2EnRixjUor7KGrQrKNPIqLgO6Myyh2RwfjAx0QMI78bZ8x3cTYtVvQkzI6d7e9e27Kcoq186kMUrKdo9ZbX70dZUaL9gDgeSp6BjYNxtCTKQCYWEOYFumKXTw32R6kYBDazZaGnYwxRd2j3hEsdfp1PTVb+r63bsu9m5TYGTHvgpInDBJTg7R0Ki6Cdr28YlLYcZomRbIGdm2Hi1lRdIatMO8wm0LQf5RGMMrbAAfAU3qZSh0XXKMeg3LagiLF5gM5TImdx2KjKOHB7coZcXKgYUeHEJluIUD3c4WwxGT2p3V8AliKfiEJEAMY9GJPry66CgzhPQgRbvNBsbuoGgE81gaSUY+mvksGOnFpp3YDDI0IvJBDJqsn52AwgOjp7hQX2ToOathxYqeGJ2o4KIRGycF5kFFqUYJ4m4VlJ2Rtl7rFDTjkPSw28FYAE7BYlr38JkMzhsHc15LXxRCL84AmMDwVHWoFBwMGslwVGneYbUKhEx2UdY/fziXiamL4i9/Dw/93CucEIGo7YBELSJtltGZPW5h2g460ATcCcl2rM0wLzUl1WoeSLsql79Ew18Ojt/HrZsXbAQcas200bM4mXjHOGaWnthADKVchFoCI9flMfRLPDtiNFmV3gfpxfnNFBeJhr+xuuOhc6ll/SKn4ncxjca3PnOi1zpJRv6hX+NG37PCa9bNwJRMPd3iAEhR7tAEUO1zAdkDYqSH2rGzFl93d/gXJUNsJ08xq12KD7NDNP5OpzQ8Xc3fqOBHeHwEX1/BGghNsKexXocFLBBVFW9T6j6CrITjHb0aA15N7JADgiUxjMEA9y3FDdL2NVfDb14OpwEDBYj68LQIIS9+bJi0XUUkiuIi9HxgbFmmInchCyJ76T7x+RZCs6fYDFNaVovF6TXRT+12AL19Wes3ljYDDnIchyvq++utXlXUFhvgMKCDhKv04h4U4Tr7sZHpzNNzc+EjQ0PzfHXPQ9Fqwf4fKuerv1pvXlrDnEaUn4/83N7WB7FHMiLYEuTTiFMhiBjEzK84xhEq7Ro+UrMq2wj8rM7aD7N3gY3KdXoeptx7Hy72tAFkZZP3Nu3UjUYf6usYrrEFQgy1Qfu+o7eB1r5c7X6tMn41n+39O+uvvkiJjl6P7KHD1iT/6bPwvJtb4eP2tvM+vtPldeXOC5J0NdBeIM/73egXvSu1Ul87yLf7Gazbbl11WYPh+lZUdTf/7QpGGr5c1kCmZxQOw+CKlXuc98F4B+RE4fbLcmQ6PjnuN938XylfAWxFuwdkXHq/llQUMj+zY10pHpdlzYEs9bw12uSvq13jnv6+fTwFAr3zn7voe/X6/ua196bxdr503PpPSse+6eJxfHnSRrus1cvr/q9tSShvY+Wh6jO9fX8cxXWe9opfELPHbtn7mwbWifve+3W2NxXis9ayu3HFenr6/1qOW6X6vWDD9j8b7YP31s0fn+ER5rQ8/Km/ErEAq/ncAkSsqlUZHiEAU4uF9oPuVULEst0ayRcKTuZPRsMNLMEsM6LieGuhyF+MwiukTogTy78RzXFf+Zj48jVt2yhFP0JU9os9DfnMAWyz/DgMIzp1rw4SobeHCoyoEAlH11yi/N9o5ogfrAI2FbJFyTuozHtTvEdBSmBsByAxRzfudv1faRYhKu7DFY8BDof1/DEZTTaFR6H5wSgEEWYAgH/Xe1PqtdS994zoZlDCGGOxaric+z2uk8s96nH1vbA4dsTbz74XJG+OHlnsw7snjSerNgANKw4YbyFRfxq4jx99OpqbHIhlW29j0QDMV/kaQBMbaCgMFO98RKcJK7sDT119o/iZP19RlZCoe3oorEzBzw9ZlsHs2ulhQUs1y3EgsRbwKDmU8I67NrikGxqEbDu14UV8shY7DZ66dBIeGTiBuv1oeslAXrA2iXQwYDjWFvQM4vHMdnhGpg/BScj7Y78fCopEDwVY0zqteY5Bl2+lo89sSAKGUXo1TDfStDcY9Z1VzofrvNwh2D0rqRCmgAm5+aCRuDHFaJwZwxxhGe2/5OgCjrt4UZVvQlwynAETugcGZuzQW7KnfJtTl/hUsSrsYSBSxUmyzaHKAECVAqAigNlGYzsVD82JNFyyzQlRxfsLAeyNmxXt5L+/lrZW3wRxi1pB5c5FMyCKMkzyxiC+cGqG5Q/kPl2PQp4k5+Gwczx9lwykNh6M/YDNd7ONwqmeM8mvIa/LZUGQ2K67MIdZhKAAPnBL2BXl+zWIbppyiOMnq+LFvlmTEzYGa59FYgzMI6inA7R7H0YJvOnuImXoEhUWgk80cBxQvqjgUePE2OCpTgD2/lGsAgMOToZxiTOuUhkNaMq9ozy4jaEgfMAcl9d26zbYQJQtQkaL8x2I5j104qKGp5MrJw3Pht+wLI7FLJ5nclG2xAcOciMQ3gOW6qI+8B7LhkNIOylbv6KO1v4TpIaNf51L/+sgOCnOPL21jXZmiE3vHci6RxMPW+li/I5CnGIi+xsI4vX0B5GuO9UEPyifBgYh+DsA/AeBXVfUf8s/+RQD/YwD/Hz/sf6mqf8H/9y8A+H0wdvPPquq//anfAGB7IBCj81C6z26pwQ8ZfvQXul6yEFncAplZETcv/190hgQEf36RDS89zAq70Yc0HL3h8IQwNVtUgpjTxSn1Wa2P+66Zh82JJkAfgBUrGBmKk4dp8VG2jJD8nHYL+qGOQ3uaFix7xoN8PuI4k2+Ky3O2iHroDiFaHjrMic+V00R5geV5sNRxWz7bw9rpo26ZLcmeGS/S8NI3S+veh5nW07S41xzCvctkKeY2Flub0TCSIuSxAtYGljEhNNbMRRFrIapXYcfpQU1meoSbcrRHTfYywGHU/wmHbvgoOz5qgKLV70Wsvi8OGt33uzg7T1vrqbAlLQ5AiNd+GbG94hR2QIDtxYmyxmK8RvGuKiGXfIuDQyeyncYi7qS3EhUIb2vCfb52K1+EOfwxAP86gD+xfP6vqer/rn5ARL8FwO8G8A8C+K8C+PeI6L+uqvcre6IooN12du59RHud3bdm621yj9UiSuhswHK3iUscE2JSzHDx/NIbXnyjjBUYzt7Qxe3ocrMztX1JgXZbwjAkhfpsmotogMzCQ55FKfzRjRQfi/+8kWDXzWZKnzEBzAuFRm1zUZWBwzpTWjl8InlRxkdteHFw+Fx3fC77eI7XumUquc9lx0fZ/NEcYDe8+ACJrfViBq2azZ02E0Fiaa97kEA8R1ndzo1kdrVMi6UoF1U1zDrDBRyUkyUBcLaweT1H3Wu9AeBjt4nlpdc+4wzCJwHpPol0zqzmkUUsUwxa0ofbHcGUkK5OUvL+M4Al5ItPKQTCxTvFhA2PV8pG+SQ4qOpfJKLf/KnjvPwEgD+tqh8B/KdE9DcA/DYA/7fXv0a+e5Ih3VkDjk6LLON+ZQOArYcQEM4I9KARnlzdViEexS5PBgzzTBedO4AhbrRtrLrMBMEGwqS4EZOIfBUnG0ioUi5HBwDcLAat0ZL5vgYExWiIgRCvYR39ST3UuPjlr0u2bSY/XEyMJLOAg0MFCN3xDXnCN/ozviFPAJAD5Jt9x4ts+Pzc8eKmxdFHotZqkj1y347IUUDZfCk1N8JaLq7IhgtAdGF8IJswXqjhiXomcrlL9rJmgjLm8JTA8I3+XMDQ6g1Yf/m871ZvYbycLYGh+6bDvbNtwluAgbqphjX/aF5W7UfBGmJpdxxXUtGHt0J8otDGF2+fqiVLjs83/+yk1wXJ70Rz+ANE9E8B+CsA/ueq+rcB/AYAf6kc84v+2etFAZyWQEVoJFY5aQAEMPuSY/u2VLYR6y3aq+AQinqmiivgEGbE0YM1DGBI2iYMFQeE1ay4oL5FrylbOi9yl1O6RZdMLEyKz/t++SxK5IUc/4zKmUv3iTqOWKqskd/izsamVN5f0CZKHcDw9+T5AgwxY36z7/hm3/F53/HSN3zet4spBphnR5w9fAocCEBjQmNbl9DK8cMlytljqxs6EsOGWzJMzMOXax+0lZDn0YbBJg7dDCy9DQIsPxa28A15KvX2tuo7PvYNH88NL+dmE8rZcJ6DaWrsg3JWYJizT0/7nyzgUBKf25oMtj5HbI4Y5AQ1OoMAwNlyMgq9Z2vRdjY5MF3XBNXy7YLDHwXwM35pPwPgXwXwP/xWTkBEPwXgpwDgf/KH/hDwX/pgItolqm9cYgwmaYOm7o2xiUfIyWx+rIE1p7QUyIL+BlMAMJkRscOydHdP5S5ORVSqLqg7N5Svw7DYac/31yhjD0IMeo3e3ZlJYSdn3YghzDhwmpvTQSIFuimbEV/s7JfKHGS/zJpjYARzsBnTwMFE1GAMR7G3Y/OgId5e61fXoJj5oQkS0sYEEAlVBPGap8kinrvaKkph9oVZ+7Qe4j5NXOx6VcDBNYbPxQAhGEPUG8AAht7wcjYcAQy9QQ4Hh5OA0xK82IY2NDYbltFV8nUNa3DmkFHWYrlELC2997sKEjCQUFFgs9WfKgRutjI02mljQWfKRXiPyrcFDqr6K/GaiP4NAP9Xf/tLAH5TOfQ3+md35/hZAD8LAH/wZ35G6RiptPL25XVv3rl6ot7uNtSpnJmDXtMlUpTUkXm6K+FwQACQbMGAwcwHiT010z4cNuNDYKjXn7svE9DUsjHHvoYxoy53YRXt1vfhhcnt29gG+Ae2BLMHTjTdc13Een1hY0eK+rpvRZgTHyVYw5MPjKek05/3zeh0AIOwz5yu1qcJNou2XzRjVnf2kB6iJgY0rQQZtSPBInaqCq/CM5+ZPXrn07NBlX0rbsAyvBH1PFHvAQxbsgUA+Obh4HhY3SswxE7cONmA4BygQN2XViRzGAFNgEtVFI4KTRPCWCjgK+UQYRxQZJ+KpMeiBBIxIHERvXm2KGECM39vmAMR/Yiq/rK//ScB/DV//ecB/Eki+t/DBMkfBfAffPKECvBpSmu1ksX/V92FXazT9JLzYV19tpYa7Ti5m4Rw9paDr7IFVRpb44XCDCRjSIU5bcWlkcMNFTfUj7W1/SHO6VQ3s7ev1z7Xw3bIFhAOz69weIaiQ7fMmxj0+dG+FeG6MxepqfEA8Lm/HjPmfkunD2k5a1YzLIAVwL024/e0TlixWlFkJOEVnrMpZYAcF/OQe256C8A8Pq0NYKCOXbdcag080hxo0hzCE/Mim21sswDDx9MFyXObGEM/m+kLB2d/oZPs0f21mxN1I90BDqVNRuMsm9r43hUKS1wrmAOqmqY3W8VYhDYFt5LQlimB+HaLQi9fxJX5pwD8OIBfT0S/COAPA/hxIvoxr84vAPhn7CbqXyeiPwPgP4LJbb//k54Kbwg6KDW2cbkRcSYjFDToZcmWHHkSwi22lhC5tIBCuthcTQZCWWaIA8KqLgN+QwWT+2m9sd5wZb8C8uW2ntTDb5KK5r4OObMuVLmuL5nWJSjloEg/PI9BESs77xYjVQEuACI8ER9TpR+C4zf7js/PAQ5hRrx0HxirGbbs8ZG6TPreMIGDktnTNkuWeJW4L40c0GmwiAIUp6fUO5sJrM9sOSY26thl7HoFXM20EUo/olLDNRmemKh7eiccHBIYjmZ1P9hMCAcEYAYHLrtrW2r66FP+vPSh1BpovCemkf08QELGwNfoq230tehn4AEO4iEDrw3PL+Kt+D03H/9fXjn+XwHwr3zqvO/lvbyXt13eTIQknyaORIy9fSypxErMrhFn4JQzbKfIqsQ31EHSNKFJJIsdtvP3+gN/dLwGhsocCnMVleYqeWp6jF2KIrAnd6FW3/8CF/Np3Q9hXYDW25jpahRl3f7tbscra49YF0EZ7Zi+e/GAn2Jnv4hR6Y/JHEyAC3fvYAw8TDFg6DOpxD+wb0OTcfuautpmOMGaOkM2gTRJs3JmDi4oa8fJnOnbMvmwjBTzd8whdtgODeejR32+OHOIuke907t1bOinuS3lZMDNCToGc+A0KQBOMRKT+5KcLt+t3I6+E6+VXXuQwiBa6ScyHmHGIpiFMwf1hDHKCr2NlbHyJsCBBOAXE1LMMPBKKNv+me4CFNVUXYNyVhGrZsSppYY5p0gWIa0OCIBTsgSGAQq5ZTpcUApzImygOxXe/+TNdPswc60AdvMUgF7Np3rtdRVdvD6l4fS9LcLO/igbnvnM1HJr8htgtrEjKCxsbMDAIUyJl97Szg4zAkAOkPNstq+o2OB4pM+kRoObtnLRNr06DhQqBIqNhBwoeidsW5iVjL51A0oeqzJPZrxEpnKW9GRlVilcvVk1OA6wYLgX2XAKT3Wv9QaA82iQTpCjAQc5MDD4xDArOvJ99CN2k+IWHBZXZpqm1k3GHpm+AFl971YJscrBYNIimnp+Hz9RAAMD0MeZ198EOARzAAgCzUSkEo21w90yCt1chY0ouuY3m7S4xfy01S2ksSLOHwJjCbUzByj4Z6kurzfSj6m+6Vt7MQVJtw8Fdt0FHEwQIWcRGAwpXFN70UsSGBgfPKkpgMnOjtDrR3b2amPXMHLAo/4y6rFNdvbLOSIfQ4AToUuQz2v6zKVkOxVdxneFys1hJZR39yBt/aJDAB7hys0SvTJnKrTYLnFti2iPBFwHyDVSNjwxBgyc4CAhPp4EOtkZgwGByyDGHE4kMMzaQ3QW2H6ZwA040AQOIOR2eNq8T3WAgo02GxOpRXRnD40Gc2gYQPFYj3xr4ADPdzCuOBOlCMzlJx7tFdt/dbUdqWLH4AfcLKn7uvilD6EsA1QWUJiYQ3Z4TNRwLckcqojEcNeSX5ajvm5+bYgFSmVBjBJ07+nJECU8exTcNNP5TmC5+5dEOPa9WbGGkkfIc4RBhzciIv+mGdODfOS06L+VbVEyh2inmyCfamE4gKYy727fbINFeTfXXHcWyDi71TEyLgdIjA1y2ifBIRaJAciYjYjbiLqnq9JZgboAmaLjQTbwDwMFIMyJwiASGPTCHO7BUxdvhZu/DTnwjU2PtuLoV7EDd0w+HGyGxq5Z321X5ne7kAL8AkDhkQ4D1WQ3JpFr14urBvCZOCIQPwkOQbeGLRyAABQgCGBItKfZJ+2up1dvKpA3M0DCbiiNOIfo6GXgqGssAxyqWTQep3BurnIy49RuocKtT1R6DZDNAZD7ho4wcsAGhi2i8pnTgeFhSHBE/p2UgT1U27OaYLhpqwBQ9+4QY+xqHiDTTJtBt53YxVmW+taEoT+FF+vwzVzCzV1TsN8FyQU45E5WJZir1j3rXWMYAhQO90gcM3MYZkWAhI5+9ZpZEUPgxqxQVgcGmvQF61MougMNTUKGS1Q52vnmfpTydsCh7D8X/chYUMSOEzjZA4ao5zPOjLAxNRdUdPoeP5Cmg4MAMPSERPf6fz9l2os34HD52TQrUMwKpOZguodlZrbXSICIysxaxACK3iTva2dzTTZqeJGx78Nd3MdKoyMgrIJDrhOI9SWnDZAQGuV0l12whJsAH+CBCXa5+TEANNuJOOjwMCuqe27sdC5pLgJIoGBmiEi6uVdwiNuT7ZcJfeI8fHXPdhr1rm7Kg9J04BMGEg4EgINFCpJamEMFBx0gWk3h6D8JDoWBhhgpNuFQhEZvDhBaAKIPFgHvWuo7t715cIAC7VDMXBODfquLlTE43M4CYAIMwylp9MobeypEMQeJGogyxEYYLSuq8vBO2DGvg4N35ikVMOYb2kq9nHKbaaHJcMTra5ct6a05EeDgocl+nu5Uet5r8n4l66No0Qgh78JT7EKl0iHc4nRgdbZgNvXMtoAbE+ye1Dnjo2lmtBTulO00KfBhZgqnSJ11EwvwCZDghTlUj1a0n0SODh0gc/HABCi4NwJwhpCMgQZDOIeZbOCgk0nBXW+Yg74iSI6JcLQRQaJdWIfIrYNNhLmR3o1k25qM9u6eRHkz4GDMYQaIsfYAvt+iDgbgHSLTRhLGQqTVjHKTIlyPJHPHTeYgMyhwggVuwEFf6fQBEhjeCqaJ8gEYoa/qblwoYsOZoP8E31krLqF4XTJASsQAwnc2Ol6JGK3RouEWvQshN1DgqwkBDGBwcEiBrQb4oLT1DbvKliqzI9Ho+OaC84OrAh/nChahmswhREthTZDg3NvBf78AxeQmluEBi3wdk2u7AmK4KSswOEPgYwYHOjXfJzDcaA7kfbtKRNUkjffZPmzfF6FpwoFqAsHkziymeNXAXmMOry8Cfy/v5b38mi1vgjmQAnwqlGJjEUdwOHqlHV5U2LTvKUWsELXuzp/sIWayZA2zWVFNiel9sotCCQvS382Iudw2RTbYzFbExsi8zDrMp2ARQJndwCPWQwEUj0a49TamXLREwp8MJ49Q8rCxAVzsbO2cKwvTCxHhwGdhWospZm21mBSFPcR9Sq8Oj+fUZ3JthYtqGGal+Dkncdo9GuSrFiNEOHaGAobFmW2ROo59H0DGwaR7tiyeqjEM8frCGg7rz0AxM9K0UGelOvWpO2F7apt47W5McZGRXJSdYmdSsCV/P74HVDaLV+nBmwCHalZ0jK3nQJQAEc9xM8PdmduLCaEub13PD0Uujc3BfxPjPlPkeK2XDj93/HtupuGai07f7MaFMBrp+DEuwT01w6yoppZirFztmGlxJPSIJc9hWz8KCosELLGKMpdZr0FNi/AIlKAewYj8C5taK5BeQTQBIi5mMSngSrq08Z0M9FE1E0PN9IokO+uKRFUtgT4O5qUd6uvceiBc3IDHnVC6aFdgyPrFZ32YEgEMlHEO9p6LIMmnGiCsgmQ8Y4An2APEYOZEmtFKHuE49Lj4YvQrE7sD+DALkm5S3I4XL28CHAjWcNNiJcCnmxkgYqBHoJR1KBew6ndrKTPXnd6QWFSAYegNejsbps34mtAGLeDgjIExUq7DOneA9wQQVI4hY1UGG2Vpuwf/BKtQJduXUSkTqHxqlepdMpsMgV6AYdjRgyVU9jBpNF6hSXMoQKqlVwYwRMdXdiaVg97vOWgARETSOkAAsAxJfnzGS7Ba0p06Qy57WGTinuLNCnc3udZQgYHLwK8CZDKDKkim5qDWl5I9aEaAVs0BsNdD1B7xCUpqbKq0z3XF63CPGxv15ds8JJxwYyrjVQR4E+AAVTcrAHbPA2D3nR3ehBwg4opLhyCnmkQ6A0QZF+ZdoDGLVQYQbqfSuWlxO3GhgFe6rA+ENkr3JQLFWwWBwRAmgCCAvA2I1AZmHEsKnJxeDPuup5NV9bX6tnlr3cNgNPVYv1FzYeZKyggnfzBrWhvcA8OdWYEA0oU2U6EQSgEMVECkBPaUDIGsFkU7GrkyKwVhBLzBZ0xwWa58Y1YkwCzgEDEwvHpjamh01PnEEB/7MCvugMFea0ZFkrmf/PVon+hDlGsiRtBcsIP0eA07219TTqbsZllOqC5QprftQXkj4OAIHH7u8EmzgQKx2qyBBzQo+kf4boHc+CNLmcEms6AO/Bq9Vju9YEb5pcPf+fBNb/A0cTkgQ0/ISxqp9J1aM7mFFBNHeGK6p7knMrdnHw2hZB4NtEhFZ8BRFXqgmiHI+IBMmR45GFZgWGI+op2qu3cChgoOXT8dLBYmBdmFkWsNesOoojAVgDgDIOxkqgCVGTWX6pR+MZU7cFDgNlq2ACIwQPKuHTLOoQ9gMHNDfLKRGRBEr+Zp7MQd10UKapY414KAbEIwVh2TTNGslslo2B40t82D8ibAwexUt8fcVQN4Q7M9x+zC/dpZsqIhuNAgD3H+ipTRYa9i42NgiA7PDh4JMpUOho3s15ELruIYpQtbkNAFPN5CVzbDBCG1QZR0dzahtNtLAcANJqypVdQAogCJX8e0xuRCqccjw6EFZdAvcSAXcFiBdLT75dZFPXwcaCjQ5ZrTpIyqdDcxvF0GUDoIIkwwNbTt5XR3zDIAIhnPDAzIOi7rbEo/4a450fCqUaVupRMwjHbSoTcUgEiBPRdMGd9ieF5ICLCx3WfJL+UkMp4vrR60/NYKj/ImwAGIQWmRXlPkWAQsic2WGTRTivIAgOn/i1lRgSE7+3SzderQFRiuZsUAiFWUJMFYMMO1o5ebBtjrADwybwv5SBh5A1FAw+lxpynxaFJz+6rZlwwzt4BbAQ4rMCzLrCmfywBfzYWFhU1aDL4YOIyFVyskFHMh7mkcF2DSHVHiSzLoorUHGUBUgLy7hpw8BkBOdVLc95fls1r/ZJoJCpqv0f21rwlJULCAl1HcA7de8yDKBJwCgMvGRf55ttlg3ZezPGJzXt4OOHRzQU3IvHTOEK0m9K+zdfSDtcIxFldgKO/juEtHTwDQca7oTB0Tc5jqo7VT+u300ZsDv4hwFbhUMAV5We4ITaCIJbsT7yafMcmuR917Y3tmFDStUYfqI00K0mQU6fjtcW2U1zS1n960191x0S5TQ8V1jualuEwZh6RLL85FpR1oPZ9NKqFB2HfrTFGOr8Cw9LsInAsRewIL1LrpPaDk/SsgEc9VpxLJwLrsZy4YaU4wKAYpBuiTawy63BufbKqmcztmXinvQVDv5b28l9vyNphDUM5C/YHrZ+QImWJT/W6Zge/K9VzLeW+OuRyPhTqmllB+A5hEL7Mrh7CkpKBE+ZFiPAN6lt+ryjshZvuFEoagFu0jsEw/gFvfpan9e/O+G3O7UTCKm7aKNo+2mFTv+hrzZw8Z1pjf83jN3xwNqnFu9tOs9ykriKHJRFthsB4lnY/N+mLcuLUu6++sTHNpJ9S6PvqfFJZQWcNYUASE+7oIkqHKR/uosxudfm/+fBo35ZpeMymAN8gcVmU76dfNYKWlkrc2LTB37jsAiHLz+bAHb44Fbn/70XU8urY7YHz1fenUVDs0at+iHGhrv5vKMiDuwO7R/x/V9XJ/7upbzpumxoPfmK93bRO6/95rA2Bpw4f3dj3+5trvnmPCiUcClPfl0aftfxdgyPMvn5XvAxigEuZcAsHot2tfXvvba+XNgcMPZLmADV6/Md8CuHzb5Yv+xmuA+/0q38/f+l6Vr2Ad3oZZUUqusIz3l6hJTLT9YVQk5mOSthbVO843lRBwVpHr4Si5/uviS6+C23K967Gv/v9Sd53+N/1kUfGngEAtx99Vafltopv/0WjT1W08XXN4FfTmf1OdaDr+7p7cnh/A5K246yeP+sZa//r+0f2jpb5rH6r3ePq+NYJG3EKIplmfYvxVpkDLDfCxkO3F5fVyvRmEd9OXvsiYAd4KONQbSTeVKP/X5ZhHn9kJxk+k+2s5r/uE7GvR0QpA5LERu+AAY5mkzVmW5187l9/ISK5xuWFLnS7vsXweF8Dl8/gsYiHK8XeZseKKRwSe17+2WXyPiuu4tC/dXD+try/XPtqqFi2KejzGeWm6dxdQr9/BsDLGsfV+6vS98fs6XJjFxYzlNy/1urmG2p5aYm4MGKKNyO8hYbgLxBZRrY1DZG3A470tmInf8+vk0aeUaWrTR33qiwDE2wAHwKLismLeKXhudOVx0+pKtVuAiP8BSeW1xhDEgFeM4Kmg+/6/EP8MEOKa7ACKbe26XdNwXfq54gbl+ntMDztXBLmUz+N9vZElOUfWsTKsAANWX2cyUuZdO5wWhHRgyz+jnSiCgiJlGyODdqLD2oI3jMVvtb3iJ2o7h31f7k0ct9avrhi8tB0t7TW1g2a/GX1lvjejLeL8DhC1H+QqP7+/PvPnArFy3VTux9RnYZNIRn26UGzCNBKMiGi088oEGL6moAICWSa0bCua2modD9n/VlD7hKjwdsAhkqFMS0spO8mlg9SOs3Suy7mLmHRpkElgGp1b83ueETsPikHlHT0OlvmHx02qwED5nNd++d8KILi0QW7KG6PQQSGBgdUnsFVB8xqoz+FcAGIRJqcEpDy3Hflg1wkY4jFCm9N5tOosAcC12evgauXeY657BY7MjJSDfG6jOCZZBHDtH0bHLCVdxmIAGve39Js172Im7/HkKzURy6UPe5uqErABdGL0KvZFWBf11vtJLF135qD10dY+RVj72u2Yie+8wh7eBDiM2dMqLHVpafO1662Ah38G4PEsMv1Aecj43n3DDDAY5t/o8AbcvurRA2VQBs5yqtKhaaQUrzepWT6GWjclzElo42Y2zQcIgOdYRPMAssh85IuuagakbAofrSLm6ZA8QLypCiXzNQoUnTrTsfn2AW0spZ9FVvIz6pBrZGDpdD3TDF+Acsk/kACRE4hOKdqzrRoMPFuYXzrf66pRVLASZJjy2D2F0i2IVuod4BDX44Fr+bpuMqOarlndcomcjbyyelWJ0vMAlGspJp9txjyAQTYHh2avrQ1GfxrP1n5jXNFoTzwubwIcQPCKDiAASkdo5J8XsLiZVcK2u5y+UtroKO4Ln8Y0jRcJEHFMWUJb7XS9WZEZJSmfd3wJlF+Tga51a7XDV2DAyJnZNMGBmoKbr8ScUqM9AgeAYrGW+EKePM5rrmMw14U8ABw0Bnty62Npw2gjDZe9X8C1jVZ6PNjDaAOZ2mkGhkxE26xdEjyDUcXrcllTe0S/yBhjj0fpMci97lHvGPgVEDxZMHLCKLaV/wa7DSuQnGAA2AKsOO+SBzV0KqtfAAMSFAIYsk/dAMNoq5mxTqbpTfmE1fFe3st7+bVa3gZzgKFfPsrMKo1sht1wQUJgUMxbVVbHE/melLawiYzSSQac2VX0YmaTrfqj7ut5YuGVi1KxbTz0Qdr1KgoV208WVjAzJj92G7OhNEA3nWfFpsAmID+GN8mt6yOpKvPIJbXu06CAZWgWAhGDKMmuT57OHk67FgJGZGbcL8RMSMBp94oJ8wrIbvXOdTGq1/ii4hlIE2w1F6o50dT6Q2ENuoV55X0h9JJmfJ6KIHnJjBX14ppqTW2RX72Z4eMp9zrXSQUzUPJl+cjgNHWzJE7NUCixreLsUT/yhXyzGDO8DmPGB/s+Hex9hwdTAHDPGsIsn8bMMlZuypsAB3WzQjYkEABe+UK9V2oJzBTJtaWbH8BQx8Q6EPmKSAiG7UcDCIQKEMhIZ55LqsteDLehwVRubhXUlhtpAGF1NiAAZNNsA/XPdPNB4MDAFRxY0JqiNd+rwU2KxutFebuqDfZOnJmaeyjnnSHEEHKA6FgGSTToAhB9AG0usiK3tT3EWO9svmiriyC5TAANts1bAqiOflA0B7C3URVnQ3vAtXuomwxhYgGw3BYOdMOt7svtdeT3jI2fUyrwDsiqI1FNqBclliP7V3YqTxOwtI9pcdX1XUTGDanPhdltbbCa4HdCP9J8e628CXAwzWGAQd/9Jm2A7LNtLj6rXipKSD0g/fFlbFhsPvkM5gDRfZAX5kCEzCHBqU947gAgASU6vIHDEKmiPsDKHKLjD/tw1KcAw64JFABsI+EAhk1Am4KagJuibYZqrYk9SHMjl0hNXy7HzgeMvTdFba9JGolhhBXnaRRLSSFkDVyBVynyfFLmo2AqA8rvDXEAKcZ6iaVMLujFIzHpLg+AQTcddrqzKuIi0LrHJu9xug8xkt64JiVV8e8EpQGOREN7qYlVghUw6mrrYBpLe/ngZoalJsgtIK1fYGmjKWYjrquhsNAh3E7MIccLzWKk3xdpo80f4TXwRsBBCZCdBhAEcyjAIFvtFBUF9QoQcd7yAzZzeaahAASGbbEWHqVIDBIdnAdQBMqPJd9jebJOP+blgVmxio2J8oUxTMxhBYbNgcCfAdhGNr5P5LoF3KMckrGlnm1Gyzh9w5pTbLfy3hUdDSBJ/3p4MhwvLSbnNFAQn6GJy74VXvcBoqWdSqdM9yQKKLAxhWinyYxoALbwSOgkzFIzRhVZp2vKPOBqVtTd1wNjpDMkXZKcdScUcdZfAyNfwhUgMIApoiIj14K7gbNP1b5Ur8/7Tm3PZAw8M4XRpxbvVxuAMM6J4mu+L28CHEADCAIkAP9sGTiTco+opDo46NTpsoQSHBRXxjPFCjdcO7gEi+BClRMcyiY5Nyua5hDX0rkvM+IAvtQXNmMMdowCu4A2AW8Kbh3bJtg220kbALYm2FvHXna8CmB4BA5dGHujseOVB9q03nCS4vRAqn6y53+hiWKHtybMsEhUYzR+AGmwhk+BQ4I7Y7gp2/j/xBZCdwmmEOaVe2xW7SXMLOAROBC6Spo93U0tIYbwqHvUO9y/Jl/NZsM1ijIyMjmD8PpNO63J3DakZUanAQ7Zj4KBFg1r9ClazO+57wFxDtdlyjaUa3kz4NAdFMKUAIotvg2qPVx6oTnovT+7FmcN6VZK08CSdw4buXTwhpEO7RYckOAA0IUy3/vv78BBBw3c/PUuI4ZhU9BuGkNrDgpN8LR1bM2m6J0DHAwwNrKNdF8Dh3WvzOZ2jO2WxeBuDILZt5wnHikWiYfN6p2X2DN5ETIh6kj2UpYV34CDnUMHODS/VZU5uLaQbGErLIEDHCRNLCYzrcLEqntlrm2Ru3/Frl9kmwx3NgYVdVfiyWwdYna4JclygNb6kfUrZVgSZQao0Ug3CJtoVpOi9qPUBrytAxSQ4LCYqisoxLi5McV9L+bb8ibAQYM5+GMIkm6DF8Veg05G40dncZNiWk9QDCoL9Q324FOeqAWVxK7QsceBK+wxC0YeQGCmgIn2Nzf2Ag403yzAb5izIXHzQXefEV2B572nvrBtgqftNHBoHc+b3dmdu+2uTQMcNu5oMSAKdxSQ77NpO3PbVvMNTZyFsODoDY0ZjRUHtfTOZMwOq22Rl7H/8YB1upoxykSOx8unq/lVmUMB0fTSuAlBBRgCDADTXjY2UTZMLPI6fSFwCObQBEdnnNQyZkRI0cPMOHi6x0IAHyXX57RYyieXEwBT5kpVxsispWPyWbWr6lG4TjKfMFULKATgxjEIMP54c0+8vDlwCFEO8PetDJxNrwFAN+sJ7n4gk5xEzkR/aMeYpX2/hpwF2e3YjtzFeNrzoiY2eVS3iwqvWJnDrTdiHx2+bYJ9P7G3jqet47l1PDd7DwBPfOKpdTzxib0AA0PB2etGEWUcyg4QjI99w5NPKy99wws3fOxbahfMAuaG02foM0wNJttgttiw2gaQ6sIccAcQEzCMaFA0DxEHxj13D02YD6G7tDSvTHfZfM/QamKFCQbMAJGbCpedxrswNmacTfBytsKe1LuNM5qDTYcJ8yo22HXxEbCZmRmpcRGXflXZ6CtmxRUc6MIM1qjii4jLg4llWDmPc98Vfvyv9/Je3suv5fImmAOomhU6mRVBtdNlFZQy7No2u6tqyPCcRMcYw5SSvbO5kGLPBp+9zNTASEc+aQ46C5JfyKzQhQ76MeGKC1t6E9cXTHgEgH0fGsPTZgzhuZ340E48NTMrPrQDz+yaA3Xsbl40187XmbLDtpw/tOGUhic+8eK7BW0k2KRhY8FH2txub7FS2M7n7s5ObZgYHu8PoZyhyLexq6Lk3b2vzGFaLDWtHRn6Qtt6mhO7swUAyRj21tHITC+GYuOebfBo1/HQYADz2BzS3LwSvJzOorjhPBWn08jIy6vh/8aIj0H+HqVnJ1gVL/uAmJmq+bq2zby2wj9bRMZVx5Jirk4CfmyOE+tOgHum7eXtgMOTmw+7PQMuTIbGUHz85LQSQFGlx3qCtSQgqLmsYqNUaWr+7PAR+4Yu2nEFiQQHSg/FSgfXOgHlhlKx9eJGRt1cY6BtCI/77uDQOp73MzUGA4YDH9qJZ99z7bmdeGJ7vzs4NBIwFO3GrOjKOLRBQDik4aNsOPxcT7zhRTZ87AY0re8GNC7wAcDL2UBuj5+nB1I5QKCkuVdvH1t/QnNb3QiSoRuFGUE+6CNuoRXBcW998tJEW+3c8cQd2yLO7vSKWeHtcKq1eegw1bx64eb9q+Xkc8JMDKEGJbHFU+yiZFniz4yxhWC4ENsicmsRtbX0HzdH4nWYbxmr0AYgAAtwFPE+zQhgrDn5hFnxJsBB2RiDuAsvNAfz75eB02xGbQUcIvgngKFuHlsj8iSAQW0vydgjUphyE1nTA+gBSITIVmIlKnNY6wRcmAMSxYstvZlngr1+296xbT31hOf9TI3hs+3Ah+3AE5/4rB34rJkf6plPfOAjgSEeoTe04n031sDoMOZw0IZnPvHRmcMzn/hmf0pRc2PB5303oIk2Z0E7FS8JECbYSbN9NhFgG+nehaYFS1OpXqZ12flNBGjj4anZWfC8ndg5tJeOp3ZiI8GzP+/cJ+3lnjkwpBlAAEgdJhjUCzc03rLeH4tb9Dyaaw7m89bQH7yqTGR7iISOlWJkAYcHDPQaBDUDRNWwqmtf1nD7YGGFbcMn0zcPDhEhGcAQPn548E8MnEont+yo4bIyZfph0A+Gfz+2ne9NfIdp+053oMjgFzc5JtHSqfK094Xek4fZf1+WEfOoH7Vr/MLeOj7sPpM7MHxte8GHNkDhs/aSzOEDH3jmAx/oxE5nYQ6SHotauhIO3dDBOLjho+z4wNa7PpcdO3V8Q56wi82aG0myCHgbE+CUewh2vavt0BVg6yA6BGF6IEi6KViAwURQO3g1IcJ0eG5DiAUMHIJFhTBrIKnYMzILE5vqOkysg8OsGKbWN7tgo5ZuYcKYfD7G68PYhDnDePIwiHsqCJSh3MzD3AKuwvYkSAIzOCRz0AIQQ2ycYkGKeG9gG0zMze/ixbkrbwIclAB5cm0hXHkAyIN/QrGPwJ+tSfr4myvRES7MN8NUQJMq3RMkGCcpuoaJwujdQobT5OBFlxC/c/GsD+zpRXPImbEE7VR3XI1feN7OdFNegeEFn7UDX+MXfOBgDgc+0FHYw4nmJgXf7HUk4DQtXrThAx34XG3g2/d37Nzxjf5k7lF6mmIm2AHjY99sDUdvaKQ4GzvY+vKtbgOveosAY3RTpySMBDXOEowtFC2hmBAJDDyDwzN3PPOJZz4MQAqLaskc5vYQtbYQZ1KAAeQpjI9kZsk3ac/6r+3w8bAhdAYYkA4vhtfNzA21aFIGenjAiiszdhBD6UoJEJNZUUCBhumQbLTGgnhfq1GjAG4jR+/KmwAHEAYwuLYAALwLuHXse59mjqfWk+I+cU9XVQUHJoG4a2oFBwHh6BYAtDXC2X3G8MhACUbhEXKW7SdmQweGlSrfgQMwbOigzO6KA5DRfNvmddssXuGz/cBzERu/tr0kY/gav+Br7QVf4xc8Ozh8nT9ip44PdGCnE0/UwRA8+WwZAyLao4MMHNBw6IYXbdjFYyZiQOkGhubMy267AzZYP6c9TbkaOBUBRIBFGsZu3skcLvd+FpIDFBoptgCHAgo79xRjnxwMhnlloPBFTSxri9nMAoBnOvGRN2wi2MS+GwFmcx8b5sWIjORM6QCEoEhAbAodoMAYO38v4BDlYlYEE41YkIh6nExVnSJH16hRwJgYkbo5/thh+abAIYAhffxbn2bUp+2cOgngswpdb1wtFRxOaTiV0UhsgPisB2B08G62dETIqZjdCAyqHHQ5l9+tHb/Y0jUWg9mWVgMzXX5yYHjeXFvwDv+hHfih7QWf8UsBh4/GHOjFjgnmQAeeCnNgErSJr9pTh9nZL2hGp3VLIHmSjs/pxC47GhS7z5qtmCjf7COGgh2YI3DqYM11GkyaQUaxyAm4MgeLxNTssJtrC2E67s1Ext1ZwlPr+KwdKcKmMOvay/MCDk90JoNazayuNDEpAPicdux6JotqEHyzfO+uj9W6mFAZ3cKjKms0qczMQQVjZ/DLCUvXKvrVELeL+QBcPDtr1CiAKXKU6elhXd4GOAAZ+ca75GrDbbNBs5eBE9GAQSXvFOlb0ckjAwMcTmGc2tBIUojahKcOHp22d05Xk3S2m6OeEDRnxJs7GxFzix1dI/rWwKbnzbwRX99s4H/WDnzGL/ihzQDBHh/xgQ98nS28LYBhpxMfHBj29FbcDQZCJ8IH/f+3dwa5jdxAFH1Fui058S4DZJlL5CA5X44U5Ciziwew1U1WFqwi2epuY2zAM4LBDwiyDUsW2ezPql+/6IWLBJ613AxA0SxyiTw8YoCSpwf757AlaG67pwuWIoVovU+j13f6syRWU2Tv4S3mrh95nwiwuuZepTnFhYdwWZFDTwyrKKojyT7V8jMs+hQLYNLEsxZy9IpPcEK8GsE2Zy+3VHWTinW2LvbKoEXH8jMc6Eu9siNINtGwaQ6eWqzTB2BVzetF3GipGVCb84pzdOIIwwQ1MDCwi9uIHMRTimyqvYW4V1HDyfJMzzcBM/5sS1Y9sglOSYVFMrOW3HjRbCaZ8po5lfq972YxK0syb72FgH44Skk1XGzbDzNbLl0ih2h5X9VLrCR3HTWcuzLlKp2wqOHX8FKiB7HUo6YViYnMvZQ90Q4M2sx1BmaFJMKkgYgy24kpEdvBJRNtZ4soMW/DzyBKSCXteJYJSUoKgdBpOCkIauXj0sPgr+3nSVujlD17GgHFmHVv/o5T1RkuqzQC4CyLibMXS68sxZLMxCvVCglFdzH33aypphVBcu07OcL2EJv+topAtmYsq34JtTMY+rK4tvb/q1TCv27W55ZOeLQAbFIJF3P7NK23lr+WIt0IOdB1HeZOiMob84+Hl6cVOaROONsvZbozcJHMnYZKEkGUiy3mIOWI8LLoI7Pf2ElJ7oDzdt4cigPwSGgDqLn0sdB2RAwPoaUVR8TQ0oqlEINkzqJMQBQxr836syVbDDNKQpkppDp7SqaZoJl2rPQxmnfAnlEWDXXBxVAqQn1TU76aKy8POjkUw1WujWTA6po7KZzCUis2jRy8YrPs6i9QBElPMRICUkTJSSOzmaAuGgk6EbWR4x780JeMrHQt1XT1m4Ug1HwQ9YQpL2j0DlL/Ux05tLSiq3p16YSLjsAuMRTHqK7I1uf65kuZCOZj8JKeRw7LyvXWL5JT1Rx6RfrYEejkEMncEbiIEnKsDUoAl3a214oggiiz5ds5B5IdHxcCK/flakhd1BBC2xn9YkHXau1CW0h2A8yrPPqX+FJ2RH8YMZztKKGzJM6SOAncizAhBBEmPz/tCpnMJMqsuZY8n68HENgQRLJVmjR0x9S3X3CirSp+itxJLgKwzdMearWJFjXc2TWHtQN0jxg2EVS4MJEqOUySmuZwdaMnhIRwT+Li1Z08lTnJuiFIX0tlHi0aDcVE1chBmsYSPbIIFj80gvDCSZWsjsrh9ftW+XIjU1+NAHaJwdeZ3xt95+7eZuq4DXKgMd6dtdtCuXkqKdQF0mrZwKqeHQ/CpCzSatlEkl3xgBJ0f3tcOqLor0+SojIn7Hp+Bzn0x7ft231bWe60UeA9ZbhU4fFshqezLWYnhrMIkwQmokUOwc4vupoPlEwmkrqd1AfQdr1s0VKSQohuCc4hQIYUwiYSAAjd3GW1/w5mQqj/rF+UTgrun+hdjsCGGJwke39HmYdCDEWMTNzjG0eLFq7XRzZyKEfsZv9ARM2VIH3sp1DKnbVUS+AUIktIpRJmJJG69MnXSPna3tBP1fKps1LmaxWv+r27LWM2Q1Wu9w5wSAxeigVWrf2v2Bxugxy+vOjXv/7579vj4+NXmCiPt0Ppl/Yabmn3AT++6y+8FW3qn56evpTxvQ3P9rhFnOzx9PT05fd3jO29UOCbPX4Erq/dQ/f823e/i9lqPwy+1iIcRIwH+OPwHY/EtB8NEflXVf/82Z/jo/CZx/eZxwaff3xHGKXMgYGBXQxyGBgY2MUtkcPfP/sDfDA+8/g+89jg849vFzejOQwMDNwWbilyGBgYuCEMchgYGNjFIIeBgYFdDHIYGBjYxSCHgYGBXfwPXpSF+aEGaXUAAAAASUVORK5CYII=\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 56, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:52:23.771Z", + "iopub.execute_input": "2022-08-08T19:52:23.779Z", + "iopub.status.idle": "2022-08-08T19:52:23.896Z", + "shell.execute_reply": "2022-08-08T19:52:23.919Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "rw = random_walk_model(parameters, seed=45)\n", + "rw.set_activation_map(my_j+my_i)" + ], + "outputs": [], + "execution_count": 68, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:34.095Z", + "iopub.execute_input": "2022-08-08T19:53:34.103Z", + "iopub.status.idle": "2022-08-08T19:53:34.116Z", + "shell.execute_reply": "2022-08-08T19:53:34.126Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "TIME=2000\n", + "for t in range(TIME):\n", + " rw.evolve_step()" + ], + "outputs": [], + "execution_count": 69, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:34.295Z", + "iopub.execute_input": "2022-08-08T19:53:34.304Z", + "iopub.status.idle": "2022-08-08T19:53:36.480Z", + "shell.execute_reply": "2022-08-08T19:53:36.517Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "plt.matshow(rw.activation_map)\n", + "plt.plot(rw.trajectory[:TIME,1], rw.trajectory[:TIME,0])\n", + "plt.xlim(0,200)\n", + "plt.ylim(0,200)" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 70, + "data": { + "text/plain": "(0.0, 200.0)" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 70, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:36.492Z", + "iopub.execute_input": "2022-08-08T19:53:36.500Z", + "iopub.status.idle": "2022-08-08T19:53:36.634Z", + "shell.execute_reply": "2022-08-08T19:53:36.651Z" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "# Evaluating some data\n", + "\n", + "The parameters should still be recoverable even with background \"noise\"" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "rw_eval = random_walk_model(parameters)" + ], + "outputs": [], + "execution_count": 71, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:51.309Z", + "iopub.execute_input": "2022-08-08T19:53:51.320Z", + "iopub.status.idle": "2022-08-08T19:53:51.335Z", + "shell.execute_reply": "2022-08-08T19:53:51.346Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "TIME=2000\n", + "lik = 0\n", + "for t in range(TIME):\n", + " lik += rw_eval.evolve_step(sim=False, dat=rw.trajectory[t,:])\n", + "lik\n", + " " + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 72, + "data": { + "text/plain": "-9306.592515719194" + }, + "metadata": {} + } + ], + "execution_count": 72, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:51.445Z", + "iopub.execute_input": "2022-08-08T19:53:51.456Z", + "iopub.status.idle": "2022-08-08T19:53:52.935Z", + "shell.execute_reply": "2022-08-08T19:53:53.166Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "class gridsearch_dat():\n", + " def __init__(self, ps, actual, grid):\n", + " self.name = ps\n", + " self.actual = actual\n", + " self.grid = grid\n", + " self.res = None" + ], + "outputs": [], + "execution_count": 73, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:52.952Z", + "iopub.execute_input": "2022-08-08T19:53:52.962Z", + "iopub.status.idle": "2022-08-08T19:53:52.976Z", + "shell.execute_reply": "2022-08-08T19:53:53.172Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "sigma_i = gridsearch_dat(\"sigma_i\", 2, [1.4,1.6,1.8,2, 2.2, 2.4])\n", + "sigma_j = gridsearch_dat(\"sigma_j\", 3, [2.4,2.6,2.8,3, 3.2, 3.4])\n", + "gs_list = [sigma_i, sigma_j]" + ], + "outputs": [], + "execution_count": 74, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:52.990Z", + "iopub.execute_input": "2022-08-08T19:53:52.999Z", + "iopub.status.idle": "2022-08-08T19:53:53.013Z", + "shell.execute_reply": "2022-08-08T19:53:53.177Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "#just to be safe\n", + "pdict = parameters.copy()" + ], + "outputs": [], + "execution_count": 75, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:53.026Z", + "iopub.execute_input": "2022-08-08T19:53:53.034Z", + "iopub.status.idle": "2022-08-08T19:53:53.049Z", + "shell.execute_reply": "2022-08-08T19:53:53.182Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "sim_dat = rw.trajectory[:TIME,:]" + ], + "outputs": [], + "execution_count": 76, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:53.062Z", + "iopub.execute_input": "2022-08-08T19:53:53.071Z", + "iopub.status.idle": "2022-08-08T19:53:53.085Z", + "shell.execute_reply": "2022-08-08T19:53:53.188Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "sim_dat = np.expand_dims(sim_dat, axis=0)" + ], + "outputs": [], + "execution_count": 77, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:53.098Z", + "iopub.execute_input": "2022-08-08T19:53:53.108Z", + "iopub.status.idle": "2022-08-08T19:53:53.122Z", + "shell.execute_reply": "2022-08-08T19:53:53.194Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "for p in gs_list:\n", + " res = rec.grid_search(p.grid, p.name, sim_dat, pdict)\n", + " p.res = res" + ], + "outputs": [], + "execution_count": 78, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:53:53.140Z", + "iopub.execute_input": "2022-08-08T19:53:53.148Z", + "shell.execute_reply": "2022-08-08T19:54:09.614Z", + "iopub.status.idle": "2022-08-08T19:54:09.541Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "def plot_gs(P):\n", + " fig, ax = plt.subplots(figsize= (35,10))\n", + " for tr in range(3):\n", + " ax.axvline(P.actual, c=\"red\", lw=5)\n", + " ax.plot(P.grid, P.res, \".-\", c=\"black\")\n", + " fpname = P.name\n", + " ax.set_title(f\"{fpname}\", fontsize=35)\n", + " ax.set_xlabel(f\"Parameter Value\", fontsize=20, color=\"grey\")\n", + " ax.set_ylabel(f\"Likelihood\", fontsize=20, color=\"grey\")\n", + " ax.tick_params(axis='both', labelsize=20,labelcolor=\"grey\", color=\"grey\")\n", + " ax.annotate(f\"actual={P.actual}\", (P.actual, np.median(P.res)), size=30, color=\"red\")\n", + " return fig, ax\n", + "\n", + "mpl.rcParams[\"axes.prop_cycle\"]=mpl.cycler(color=[\"slateblue\",\"rebeccapurple\",\"orchid\"])\n", + "mpl.rc('axes',edgecolor='grey')" + ], + "outputs": [], + "execution_count": 79, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2022-08-08T19:54:09.556Z", + "iopub.execute_input": "2022-08-08T19:54:09.565Z", + "iopub.status.idle": "2022-08-08T19:54:09.580Z", + "shell.execute_reply": "2022-08-08T19:54:09.620Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "with PdfPages('param_rec2.pdf') as pdf:\n", + " for P in gs_list:\n", + " print(P.name)\n", + " fig, ax = plot_gs(P)\n", + " pdf.savefig(fig)" + ], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "sigma_i\n", + "sigma_j\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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of file diff --git a/generate_assets/walk1.png b/generate_assets/walk1.png new file mode 100644 index 0000000..17db928 Binary files /dev/null and b/generate_assets/walk1.png differ diff --git a/generate_assets/walk2.png b/generate_assets/walk2.png new file mode 100644 index 0000000..19eaf67 Binary files /dev/null and b/generate_assets/walk2.png differ diff --git a/generate_assets/walk3.png b/generate_assets/walk3.png new file mode 100644 index 0000000..d35862b Binary files /dev/null and b/generate_assets/walk3.png differ diff --git a/generate_assets/walk4.png b/generate_assets/walk4.png new file mode 100644 index 0000000..e8fe67e Binary files /dev/null and b/generate_assets/walk4.png differ diff --git a/generate_assets/walk5.png b/generate_assets/walk5.png new file mode 100644 index 0000000..f71b005 Binary files /dev/null and b/generate_assets/walk5.png differ diff --git a/generate_assets/walk6.png b/generate_assets/walk6.png new file mode 100644 index 0000000..1529b07 Binary files /dev/null and b/generate_assets/walk6.png differ diff --git a/generate_assets/walk7.png b/generate_assets/walk7.png new file mode 100644 index 0000000..51eb2a4 Binary files /dev/null and b/generate_assets/walk7.png differ diff --git a/notebooks/01a_Classes.ipynb b/notebooks/01a_Classes.ipynb new file mode 100644 index 0000000..5e8eb35 --- /dev/null +++ b/notebooks/01a_Classes.ipynb @@ -0,0 +1,590 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# The smell of classes" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## The \"data bundle\" smell" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:51.531289Z", + "start_time": "2018-07-27T17:05:51.526519+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "def momentum(mass, velocity):\n", + " return mass * velocity\n", + "\n", + "def energy(mass, velocity):\n", + " return 0.5 * mass * velocity ** 2\n", + "\n", + "def update_position(velocity, position, dt):\n", + " return position + velocity * dt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:51.905235Z", + "start_time": "2018-07-27T17:05:51.900153+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "1.2000000000000002\n", + "1.0\n" + ] + } + ], + "source": [ + "# Naive\n", + "mass1 = 10.0\n", + "velocity1 = 0.9\n", + "\n", + "mass2 = 12.0\n", + "velocity2 = 0.1\n", + "\n", + "print(momentum(mass1, velocity1))\n", + "print(momentum(mass2, velocity2))\n", + "print(momentum(mass1, velocity2)) # ??" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "We have two parameters that will be sent to these functions over and over again: `mass` and `velocity`.\n", + "\n", + "Moreover, the parameters cannot be mixed up (e.g. the velocity of one particle with the mass of another)." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:52.116795Z", + "start_time": "2018-07-27T17:05:52.112569+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "1.2000000000000002\n" + ] + } + ], + "source": [ + "masses = [10.0, 12.0]\n", + "velocities = [0.9, 0.1]\n", + "\n", + "print(momentum(masses[0], velocities[0]))\n", + "print(momentum(masses[1], velocities[1]))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:52.548364Z", + "start_time": "2018-07-27T17:05:52.544726+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "1.2000000000000002\n" + ] + } + ], + "source": [ + "particle1 = {'mass': 10.0, 'velocity': 0.9}\n", + "particle2 = {'mass': 12.0, 'velocity': 0.1}\n", + "\n", + "print(momentum(particle1['mass'], particle1['velocity']))\n", + "print(momentum(particle2['mass'], particle2['velocity']))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "All of the functions above can be rewritten as a function of this particle \"instance\", eliminating the bookkeeping for the individual parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:53.571400Z", + "start_time": "2018-07-27T17:05:53.567192+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "1.2000000000000002\n" + ] + } + ], + "source": [ + "def momentum(particle):\n", + " return particle['mass'] * particle['velocity']\n", + "\n", + "print(momentum(particle1))\n", + "print(momentum(particle2))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "An annoying thing of this solution is that we have to remember the name of the keys in the dictionary, and the solution is sensitive to typos.\n", + "\n", + "To solve this, we could write a function to build a particle, a.k.a a \"constructor\"" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:06:20.004037Z", + "start_time": "2018-07-27T17:06:19.998500+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "1.2000000000000002\n" + ] + } + ], + "source": [ + "def init_particle(mass, velocity):\n", + " self = {\n", + " 'mass': mass,\n", + " 'velocity': velocity\n", + " }\n", + " return self\n", + "\n", + "particle1 = init_particle(10.0, 0.9)\n", + "particle2 = init_particle(12.0, 0.1)\n", + "print(momentum(particle1))\n", + "print(momentum(particle2))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "`particle1` and `particle2` are called \"instances\" of the particle \"class\".\n", + "\n", + "Python classes are a way to formalize this pattern: creating a bundle of data that belongs together. E.g. the parameters of an experiment, the results of a simulation, etc." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Introducing classes as a data bundle template" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "ExecuteTime": { + "end_time": "2018-08-04T13:04:49.208543Z", + "start_time": "2018-08-04T15:04:49.203180+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "class Particle:\n", + " def __init__(self, mass, velocity):\n", + " self.mass = mass\n", + " self.velocity = velocity\n", + "\n", + "particle1 = Particle(10.0, 0.9)\n", + "particle2 = Particle(12.0, 0.1)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:07:09.818544Z", + "start_time": "2018-07-27T17:07:09.814535+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "particle1.velocity" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:07:09.997264Z", + "start_time": "2018-07-27T17:07:09.994114+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "12.0" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "particle2.mass" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:07:11.559629Z", + "start_time": "2018-07-27T17:07:11.555632+02:00" + }, + "pycharm": { + "name": "#%%\n" + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'mass': 10.0, 'velocity': 0.9}" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "particle1.__dict__" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Class methods" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T12:13:56.972938Z", + "start_time": "2018-07-27T14:13:56.969323+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "1.2000000000000002\n" + ] + } + ], + "source": [ + "def momentum(particle):\n", + " return particle.mass * particle.velocity\n", + "\n", + "print(momentum(particle1))\n", + "print(momentum(particle2))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n" + ] + } + ], + "source": [ + "class Particle:\n", + " def __init__(self, mass, velocity):\n", + " self.mass = mass\n", + " self.velocity = velocity\n", + "\n", + " def momentum(self):\n", + " return self.mass * self.velocity\n", + "\n", + "particle1 = Particle(10.0, 0.9)\n", + "print(particle1.momentum())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "We have been using class instances and methods all along..." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'A scanner darkly'" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s = 'A scanner Darkly'\n", + "s.capitalize()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'apple', 'banana', 'pineapple'}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = set(['apple', 'banana', 'apple', 'pineapple'])\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'apple', 'banana', 'kiwi', 'pineapple'}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.union(['banana', 'kiwi'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "toc": { + "nav_menu": { + "height": "174px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_position": { + "height": "953px", + "left": "0px", + "right": "1253px", + "top": "127px", + "width": "320px" + }, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/01b_Classes_teacher_edition.ipynb b/notebooks/01b_Classes_teacher_edition.ipynb new file mode 100644 index 0000000..76a36ec --- /dev/null +++ b/notebooks/01b_Classes_teacher_edition.ipynb @@ -0,0 +1,279 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# The smell of classes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The \"data bundle\" smell" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2021-08-11T12:50:34.342224Z", + "start_time": "2021-08-11T14:50:34.336560+02:00" + } + }, + "outputs": [], + "source": [ + "def momentum(mass, velocity):\n", + " return mass * velocity\n", + "\n", + "def energy(mass, velocity):\n", + " return 0.5 * mass * velocity ** 2\n", + "\n", + "def update_position(velocity, position, dt):\n", + " return position + velocity * dt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2021-08-11T12:50:34.776689Z", + "start_time": "2021-08-11T14:50:34.769617+02:00" + } + }, + "outputs": [], + "source": [ + "# Naive\n", + "mass1 = 10.0\n", + "velocity1 = 0.9\n", + "\n", + "mass2 = 12.0\n", + "velocity2 = 0.1\n", + "\n", + "print(momentum(mass1, velocity1))\n", + "print(momentum(mass2, velocity2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We have two parameters that will be sent to these functions over and over again: `mass` and `velocity`.\n", + "\n", + "Moreover, the parameters cannot be mixed up (e.g. the velocity of one particle with the mass of another)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:52.548364Z", + "start_time": "2018-07-27T17:05:52.544726+02:00" + } + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Introducing classes as a data bundle template" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2018-08-04T13:04:49.208543Z", + "start_time": "2018-08-04T15:04:49.203180+02:00" + } + }, + "outputs": [], + "source": [ + "class Particle:\n", + " pass\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Class methods" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T12:13:56.972938Z", + "start_time": "2018-07-27T14:13:56.969323+02:00" + } + }, + "outputs": [], + "source": [ + "def momentum(particle):\n", + " return particle.mass * particle.velocity\n", + "\n", + "print(momentum(particle1))\n", + "print(momentum(particle2))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "class Particle:\n", + " def __init__(self, mass, velocity):\n", + " self.mass = mass\n", + " self.velocity = velocity\n", + "\n", + " # Method here\n", + "\n", + "particle1 = Particle(10.0, 0.9, 0.0)\n", + "print(particle1.momentum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "We have been using class instances and methods all along..." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "s = 'A scanner Darkly'\n", + "s.capitalize()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "x = set(['apple', 'banana', 'apple', 'pineapple'])\n", + "x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "x.union(['banana', 'kiwi'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "\n" + ] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "toc": { + "nav_menu": { + "height": "174px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_position": { + "height": "953px", + "left": "0px", + "right": "1253px", + "top": "127px", + "width": "320px" + }, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/02a_Serialization.ipynb b/notebooks/02a_Serialization.ipynb new file mode 100644 index 0000000..b25b441 --- /dev/null +++ b/notebooks/02a_Serialization.ipynb @@ -0,0 +1,455 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Serialization demo" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 1, + "outputs": [], + "source": [ + "import json\n", + "import numpy as np\n", + "import pickle" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## pickle is simple but can be dangerous" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [], + "source": [ + "class SomethingSimple:\n", + " def __init__(self, foo, bar):\n", + " self.foo = foo\n", + " self.bar = bar\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "data": { + "text/plain": "(__main__.SomethingSimple, 3, 'two')" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "simple = SomethingSimple(foo=3, bar='two')\n", + "\n", + "with open('simple.pickle', 'wb') as f:\n", + " pickle.dump(simple, f)\n", + "\n", + "with open('simple.pickle', 'rb') as f:\n", + " simple_bis = pickle.load(f)\n", + "\n", + "type(simple_bis), simple_bis.foo, simple_bis.bar" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 4, + "outputs": [], + "source": [ + "class SomethingSimple:\n", + " def __init__(self, foo, bla):\n", + " self.foo = foo\n", + " self.bla = bla" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 5, + "outputs": [ + { + "data": { + "text/plain": "{'foo': 3, 'bar': 'two'}" + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "with open('simple.pickle', 'rb') as f:\n", + " simple_bis = pickle.load(f)\n", + "\n", + "simple_bis.__dict__" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "Even worse when you have a simple class name change" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 6, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "Can't get attribute 'SomethingSimple' on ", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mAttributeError\u001B[0m Traceback (most recent call last)", + "\u001B[0;32m\u001B[0m in \u001B[0;36m\u001B[0;34m()\u001B[0m\n\u001B[1;32m 8\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 9\u001B[0m \u001B[0;32mwith\u001B[0m \u001B[0mopen\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m'simple.pickle'\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m'rb'\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;32mas\u001B[0m \u001B[0mf\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m---> 10\u001B[0;31m \u001B[0msimple_bis\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mpickle\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mload\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mf\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m 11\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 12\u001B[0m \u001B[0msimple_bis\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0m__dict__\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n", + "\u001B[0;31mAttributeError\u001B[0m: Can't get attribute 'SomethingSimple' on " + ] + } + ], + "source": [ + "# Simulate a name change of the SomethingSimple class\n", + "del SomethingSimple\n", + "\n", + "class Simple:\n", + " def __init__(self, foo, bar):\n", + " self.foo = foo\n", + " self.bar = bar\n", + "\n", + "with open('simple.pickle', 'rb') as f:\n", + " simple_bis = pickle.load(f)\n", + "\n", + "simple_bis.__dict__" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## JSON is still quite simple, and allows you a closer control" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 7, + "outputs": [], + "source": [ + "class SomethingNice:\n", + "\n", + " def __init__(self, foo, bar):\n", + " self.foo = foo\n", + " self.bar = bar\n", + "\n", + " @classmethod\n", + " def from_json(cls, fname):\n", + " with open(fname, 'r') as f:\n", + " dump = json.load(f)\n", + " return cls(**dump)\n", + "\n", + " def to_json(self, fname):\n", + " with open(fname, 'w') as f:\n", + " json.dump(self.__dict__, f)\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 8, + "outputs": [ + { + "data": { + "text/plain": "{'foo': 3, 'bar': 'two'}" + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "so_nice = SomethingNice(foo=3, bar='two')\n", + "so_nice.__dict__\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 9, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\"foo\": 3, \"bar\": \"two\"}" + ] + } + ], + "source": [ + "so_nice.to_json('nice.json')\n", + "!cat ./nice.json" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 10, + "outputs": [ + { + "data": { + "text/plain": "{'foo': 3, 'bar': 'two'}" + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "so_nice_again = SomethingNice.from_json('nice.json')\n", + "so_nice_again.__dict__" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 11, + "outputs": [ + { + "data": { + "text/plain": "{'foo': 3, 'bar': array([1.2, 3.4])}" + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "not_so_nice = SomethingNice(foo=3, bar=np.array([1.2, 3.4]))\n", + "not_so_nice.__dict__" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 12, + "outputs": [ + { + "ename": "TypeError", + "evalue": "Object of type 'ndarray' is not JSON serializable", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mTypeError\u001B[0m Traceback (most recent call last)", + "\u001B[0;32m\u001B[0m in \u001B[0;36m\u001B[0;34m()\u001B[0m\n\u001B[0;32m----> 1\u001B[0;31m \u001B[0mnot_so_nice\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mto_json\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m'not_so_nice.json'\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m", + "\u001B[0;32m\u001B[0m in \u001B[0;36mto_json\u001B[0;34m(self, fname)\u001B[0m\n\u001B[1;32m 13\u001B[0m \u001B[0;32mdef\u001B[0m \u001B[0mto_json\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mself\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mfname\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 14\u001B[0m \u001B[0;32mwith\u001B[0m \u001B[0mopen\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mfname\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m'w'\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;32mas\u001B[0m \u001B[0mf\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m---> 15\u001B[0;31m \u001B[0mjson\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mdump\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mself\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0m__dict__\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mf\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m", + "\u001B[0;32m~/miniconda3/envs/bog/lib/python3.6/json/__init__.py\u001B[0m in \u001B[0;36mdump\u001B[0;34m(obj, fp, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)\u001B[0m\n\u001B[1;32m 177\u001B[0m \u001B[0;31m# could accelerate with writelines in some versions of Python, at\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 178\u001B[0m \u001B[0;31m# a debuggability cost\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 179\u001B[0;31m \u001B[0;32mfor\u001B[0m \u001B[0mchunk\u001B[0m \u001B[0;32min\u001B[0m \u001B[0miterable\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m 180\u001B[0m \u001B[0mfp\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mwrite\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mchunk\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 181\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n", + "\u001B[0;32m~/miniconda3/envs/bog/lib/python3.6/json/encoder.py\u001B[0m in \u001B[0;36m_iterencode\u001B[0;34m(o, _current_indent_level)\u001B[0m\n\u001B[1;32m 428\u001B[0m \u001B[0;32myield\u001B[0m \u001B[0;32mfrom\u001B[0m \u001B[0m_iterencode_list\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mo\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0m_current_indent_level\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 429\u001B[0m \u001B[0;32melif\u001B[0m \u001B[0misinstance\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mo\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mdict\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 430\u001B[0;31m \u001B[0;32myield\u001B[0m \u001B[0;32mfrom\u001B[0m \u001B[0m_iterencode_dict\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mo\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0m_current_indent_level\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m 431\u001B[0m \u001B[0;32melse\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 432\u001B[0m \u001B[0;32mif\u001B[0m \u001B[0mmarkers\u001B[0m \u001B[0;32mis\u001B[0m \u001B[0;32mnot\u001B[0m \u001B[0;32mNone\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n", + "\u001B[0;32m~/miniconda3/envs/bog/lib/python3.6/json/encoder.py\u001B[0m in \u001B[0;36m_iterencode_dict\u001B[0;34m(dct, _current_indent_level)\u001B[0m\n\u001B[1;32m 402\u001B[0m \u001B[0;32melse\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 403\u001B[0m \u001B[0mchunks\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0m_iterencode\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mvalue\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0m_current_indent_level\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 404\u001B[0;31m \u001B[0;32myield\u001B[0m \u001B[0;32mfrom\u001B[0m \u001B[0mchunks\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m 405\u001B[0m \u001B[0;32mif\u001B[0m \u001B[0mnewline_indent\u001B[0m \u001B[0;32mis\u001B[0m \u001B[0;32mnot\u001B[0m \u001B[0;32mNone\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 406\u001B[0m \u001B[0m_current_indent_level\u001B[0m \u001B[0;34m-=\u001B[0m \u001B[0;36m1\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n", + "\u001B[0;32m~/miniconda3/envs/bog/lib/python3.6/json/encoder.py\u001B[0m in \u001B[0;36m_iterencode\u001B[0;34m(o, _current_indent_level)\u001B[0m\n\u001B[1;32m 435\u001B[0m \u001B[0;32mraise\u001B[0m \u001B[0mValueError\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m\"Circular reference detected\"\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 436\u001B[0m \u001B[0mmarkers\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0mmarkerid\u001B[0m\u001B[0;34m]\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mo\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 437\u001B[0;31m \u001B[0mo\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0m_default\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mo\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m 438\u001B[0m \u001B[0;32myield\u001B[0m \u001B[0;32mfrom\u001B[0m \u001B[0m_iterencode\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mo\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0m_current_indent_level\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 439\u001B[0m \u001B[0;32mif\u001B[0m \u001B[0mmarkers\u001B[0m \u001B[0;32mis\u001B[0m \u001B[0;32mnot\u001B[0m \u001B[0;32mNone\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n", + "\u001B[0;32m~/miniconda3/envs/bog/lib/python3.6/json/encoder.py\u001B[0m in \u001B[0;36mdefault\u001B[0;34m(self, o)\u001B[0m\n\u001B[1;32m 178\u001B[0m \"\"\"\n\u001B[1;32m 179\u001B[0m raise TypeError(\"Object of type '%s' is not JSON serializable\" %\n\u001B[0;32m--> 180\u001B[0;31m o.__class__.__name__)\n\u001B[0m\u001B[1;32m 181\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m 182\u001B[0m \u001B[0;32mdef\u001B[0m \u001B[0mencode\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mself\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mo\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n", + "\u001B[0;31mTypeError\u001B[0m: Object of type 'ndarray' is not JSON serializable" + ] + } + ], + "source": [ + "not_so_nice.to_json('not_so_nice.json')" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 13, + "outputs": [], + "source": [ + "class SomethingWorking:\n", + "\n", + " def __init__(self, foo, data):\n", + " self.foo = foo\n", + " self.data = data\n", + "\n", + " @classmethod\n", + " def from_json(cls, fname):\n", + " with open(fname, 'r') as f:\n", + " dump = json.load(f)\n", + " dump['data'] = np.array(dump['data'])\n", + " return cls(**dump)\n", + "\n", + " def to_json(self, fname):\n", + " dump = {\n", + " 'foo': self.foo,\n", + " 'data': self.data.tolist(),\n", + " }\n", + " with open(fname, 'w') as f:\n", + " json.dump(dump, f)\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 14, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\"foo\": 3, \"data\": [[1, 2], [3, 4]]}" + ] + } + ], + "source": [ + "not_so_nice = SomethingWorking(foo=3, data=np.array([[1, 2], [3,4 ]]))\n", + "not_so_nice.to_json('not_so_nice.json')\n", + "!cat not_so_nice.json\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python [default]", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.5.5" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git a/notebooks/02b_Serialization_teacher_edition.ipynb b/notebooks/02b_Serialization_teacher_edition.ipynb new file mode 100644 index 0000000..669c093 --- /dev/null +++ b/notebooks/02b_Serialization_teacher_edition.ipynb @@ -0,0 +1,207 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Serialization demo" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [], + "source": [ + "import json\n", + "import numpy as np\n", + "import pickle" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## pickle is simple but can be dangerous" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [], + "source": [ + "class SomethingSimple:\n", + " def __init__(self, foo, bar):\n", + " self.foo = foo\n", + " self.bar = bar\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 4, + "outputs": [], + "source": [ + "simple = SomethingSimple(foo=3, bar='two')" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## JSON is still quite simple, and allows you a closer control" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 7, + "outputs": [], + "source": [ + "class SomethingNice:\n", + "\n", + " def __init__(self, foo, bar):\n", + " self.foo = foo\n", + " self.bar = bar\n", + "\n", + " @classmethod\n", + " def from_json(cls, fname):\n", + " pass\n", + "\n", + " def to_json(self, fname):\n", + " pass\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 8, + "outputs": [ + { + "data": { + "text/plain": "{'foo': 3, 'bar': 'two'}" + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "so_nice = SomethingNice(foo=3, bar='two')\n", + "so_nice.__dict__" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python [default]", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.5.5" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git a/notebooks/SomethingNice.json b/notebooks/SomethingNice.json new file mode 100644 index 0000000..82264bc --- /dev/null +++ b/notebooks/SomethingNice.json @@ -0,0 +1 @@ +{"foo": 3, "bar": "two"} \ No newline at end of file diff --git a/notebooks/exercises/particle_update_position.ipynb b/notebooks/exercises/particle_update_position.ipynb new file mode 100644 index 0000000..b3d829a --- /dev/null +++ b/notebooks/exercises/particle_update_position.ipynb @@ -0,0 +1,146 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Exercise: Add the function `update_position` to the `Particle` class\n", + "\n", + "- Make the function `update_position` into a method of the class `Particle`\n", + "- Where do the position `position` of the particle belong? Modify the class constructor if necessary\n", + "- Once it is done, create a particle with mass 2.1 with velocity 0.8 at position 8.2 . Update the position with dt=0.1 and print out the new location." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2018-07-27T15:05:51.531289Z", + "start_time": "2018-07-27T17:05:51.526519+02:00" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "def update_position(velocity, position, dt):\n", + " return position + velocity * dt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.6800000000000002\n" + ] + } + ], + "source": [ + "class Particle:\n", + " def __init__(self, mass, velocity):\n", + " self.mass = mass\n", + " self.velocity = velocity\n", + "\n", + " def momentum(self):\n", + " return self.mass * self.velocity\n", + "\n", + "particle = Particle(mass=2.1, velocity=0.8)\n", + "print(particle.momentum())" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8.28\n" + ] + } + ], + "source": [ + "position = 8.2\n", + "new_position = update_position(particle.velocity, position, dt=0.1)\n", + "print(new_position)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + }, + "toc": { + "nav_menu": { + "height": "174px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_position": { + "height": "953px", + "left": "0px", + "right": "1253px", + "top": "127px", + "width": "320px" + }, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/exercises/solution/particle_update_position.ipynb b/notebooks/exercises/solution/particle_update_position.ipynb new file mode 100644 index 0000000..ee12582 --- /dev/null +++ b/notebooks/exercises/solution/particle_update_position.ipynb @@ -0,0 +1,131 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Exercise: Add the function `update_position` to the `Particle` class\n", + "\n", + "- Make the function `update_position` into a method of the class `Particle`\n", + "- Where do the position `position` of the particle belong? Modify the class constructor if necessary\n", + "- Once it is done, create a particle with mass 2.1 with velocity 0.8 at position 8.2 . Update the position with dt=0.1 and print out the new location." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.6800000000000002\n" + ] + } + ], + "source": [ + "class Particle:\n", + " def __init__(self, mass, velocity, position):\n", + " self.mass = mass\n", + " self.velocity = velocity\n", + " self.position = position\n", + "\n", + " def momentum(self):\n", + " return self.mass * self.velocity\n", + "\n", + " def update_position(self, dt):\n", + " self.position = self.position + self.velocity * dt\n", + "\n", + "particle = Particle(mass=2.1, velocity=0.8, position=8.2)\n", + "print(particle.momentum())" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8.28\n" + ] + } + ], + "source": [ + "particle.update_position(dt=0.1)\n", + "print(particle.position)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + }, + "toc": { + "nav_menu": { + "height": "174px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_position": { + "height": "953px", + "left": "0px", + "right": "1253px", + "top": "127px", + "width": "320px" + }, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/simple.pickle b/notebooks/simple.pickle new file mode 100644 index 0000000..576e61b Binary files /dev/null and b/notebooks/simple.pickle differ diff --git a/notebooks/walker/Step_0_Introduction/Step_0_Introduction.ipynb b/notebooks/walker/Step_0_Introduction/Step_0_Introduction.ipynb new file mode 100644 index 0000000..eec521d --- /dev/null +++ b/notebooks/walker/Step_0_Introduction/Step_0_Introduction.ipynb @@ -0,0 +1,286 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:35:27.540830Z", + "start_time": "2022-08-18T11:35:27.028238+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:18:30.408Z", + "iopub.status.busy": "2022-08-20T06:18:30.402Z", + "iopub.status.idle": "2022-08-20T06:18:30.968Z", + "shell.execute_reply": "2022-08-20T06:18:30.957Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from walker import create_context_map, next_step_proposal, plot_trajectory, sample_next_step" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Examples of how the code works" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "The walker code works in the following way:\n", + "\n", + "The function `next_step_proposal` to creates a map of the probability of ending up in any position, given the current position, some map parameters, and the size of the map" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:18:30.980Z", + "iopub.status.busy": "2022-08-20T06:18:30.974Z", + "iopub.status.idle": "2022-08-20T06:18:31.108Z", + "shell.execute_reply": "2022-08-20T06:18:31.138Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "proposal = next_step_proposal(current_i=100, current_j=50, sigma_i=10, sigma_j=5, size=200)\n", + "plt.matshow(proposal)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "The function `create_context_map` creates a context map that tell us regions in the image with a higher probability of being looked at (e.g., very bright spots in an image)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:18:31.125Z", + "iopub.status.busy": "2022-08-20T06:18:31.119Z", + "iopub.status.idle": "2022-08-20T06:18:31.352Z", + "shell.execute_reply": "2022-08-20T06:18:31.385Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "context_map = create_context_map(size=150, map_type='hills')\n", + "plt.matshow(context_map)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "The function `sample_next_step` calls `next_step_proposal`, combines it with the context map that is passed to it (in `compute_next_step_probability`), and then stochastically selects the next step." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# How to simulate a trajectory\n", + "\n", + "in order to use the walker, the user has to create a context map. Then, for a number of timesteps, sample a step, always passing along the new position information." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:18:31.369Z", + "iopub.status.busy": "2022-08-20T06:18:31.360Z", + "iopub.status.idle": "2022-08-20T06:18:32.535Z", + "shell.execute_reply": "2022-08-20T06:18:32.542Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "i, j = 100, 50 # initial position\n", + "sigma_i, sigma_j = 3, 4 # parameters of the next step map\n", + "size = 200 # size of the image\n", + "context_map = create_context_map(size, 'hills') # fixed context map\n", + "\n", + "# Sample a next step 1000 times\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = sample_next_step(i, j, sigma_i, sigma_j, context_map)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:18:32.556Z", + "iopub.status.busy": "2022-08-20T06:18:32.553Z", + "iopub.status.idle": "2022-08-20T06:18:32.670Z", + "shell.execute_reply": "2022-08-20T06:18:32.701Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, context_map)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "83px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_0_Introduction/show b/notebooks/walker/Step_0_Introduction/show new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_0_Introduction/show @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_0_Introduction/walker.py b/notebooks/walker/Step_0_Introduction/walker.py new file mode 100644 index 0000000..07433f8 --- /dev/null +++ b/notebooks/walker/Step_0_Introduction/walker.py @@ -0,0 +1,81 @@ +import numpy as np +import matplotlib.pyplot as plt + + +def sample_next_step(current_i, current_j, sigma_i, sigma_j, context_map, + random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a next-step + # probability map + size = context_map.shape[0] + next_step_map = next_step_proposal(current_i, current_j, sigma_i, sigma_j, + size) + next_step_probability = compute_next_step_probability(next_step_map, + context_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(next_step_probability) + cumulative_map = cumulative_map.reshape(next_step_probability.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + +def next_step_proposal(current_i, current_j, sigma_i, sigma_j, size): + """ Create the 2D proposal map for the next step of the walker. """ + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + +def compute_next_step_probability(next_step_map, context_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + + +def create_context_map(size, map_type='flat'): + """ Create a fixed context map. """ + if map_type == 'flat': + context_map = np.ones((size, size)) + elif map_type == 'hills': + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + elif map_type == 'labyrinth': + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + context_map /= context_map.sum() + return context_map + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() diff --git a/notebooks/walker/Step_1_classes/Step_1_classes_exercise.ipynb b/notebooks/walker/Step_1_classes/Step_1_classes_exercise.ipynb new file mode 100644 index 0000000..2ce015b --- /dev/null +++ b/notebooks/walker/Step_1_classes/Step_1_classes_exercise.ipynb @@ -0,0 +1,208 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 1. Take a look at this (working) code\n", + "\n", + "... and run it." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-15T08:17:58.966008Z", + "start_time": "2023-08-15T08:17:58.961545Z" + }, + "execution": { + "iopub.execute_input": "2024-08-05T14:06:56.784Z", + "iopub.status.busy": "2024-08-05T14:06:56.776Z", + "iopub.status.idle": "2024-08-05T14:06:56.789Z", + "shell.execute_reply": "2024-08-05T14:06:56.793Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from walker import create_context_map, plot_trajectory, sample_next_step" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-15T08:18:00.805824Z", + "start_time": "2023-08-15T08:18:00.167515Z" + }, + "execution": { + "iopub.execute_input": "2024-08-05T14:12:32.248Z", + "iopub.status.busy": "2024-08-05T14:12:32.244Z", + "iopub.status.idle": "2024-08-05T14:12:32.938Z", + "shell.execute_reply": "2024-08-05T14:12:32.947Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "i, j = 100, 50 # initial position\n", + "sigma_i, sigma_j = 3, 4 # parameters of the next step map\n", + "size = 200 # size of the image\n", + "context_map = create_context_map(size, 'hills') # fixed context map\n", + "\n", + "# Sample a next step 1000 times\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = sample_next_step(i, j, sigma_i, sigma_j, context_map)\n", + " trajectory.append((i, j))\n", + "\n", + "plot_trajectory(trajectory, context_map)\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 2. Rewrite the code to look like it would in your wildest dreams!\n", + "\n", + "How could you restructure the interface of the `walker` library so that the functionality stays the same, but the code is less smelly?\n", + "\n", + "1. could this code work better/more efficiently as a class?\n", + " - e.g. `walker = Walker(...)`\n", + "2. how should the setup/initialization work?\n", + " - e.g. which parameters would you pass to instantiate the Walker class? How do you pass them to the class?\n", + "3. which functions should be part of the class? \n", + " - e.g. is `sample_next_step` a method of `Walker`? Is `create_context_map` a method of Walker? How about `plot_trajectory`? If so, call them with `walker.sample_next_step()`\n", + "4. what would the import statement look like?\n", + "\n", + "**Important:** We are *not* asking you to implement the changes in `walker.py`! Imagine the new interface, and write the code that would use it in the next cell. Of course it won't run (yet)\n", + "\n", + "Here are some things to keep in mind:\n", + "- Which things will you do a lot? They should be easy to do. The interface for doing those things should be simple.\n", + "- Which things should be modifiable from external code?\n", + "- As a rule of thumb, think about how it sounds when you read it aloud\n", + " - “Giving orders”-style\n", + " - “Telling a story“-style\n", + "\n", + " \n", + "For inspiration think about how you call code from other libraries. Here is an example of instantiating an object and calling one of its methods:\n", + "````python\n", + "import scipy as sp\n", + "\n", + "# Sampling from a gaussian with specific mean and sd:\n", + "# Create a Gaussian (normal) distribution object\n", + "gaussian_dist = sp.stats.norm(loc=mean, scale=sd)\n", + "# Sample 10 values from the Gaussian distribution\n", + "samples = gaussian_dist.rvs(size=10)\n", + "````\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# Write the code that uses your new `walker` interface here!\n", + "# walker = Walker(sigma_i=3, sigma_j=4, ...)\n", + "# ..." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "jupyter": { + "outputs_hidden": false, + "source_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_1_classes/exercise b/notebooks/walker/Step_1_classes/exercise new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_1_classes/exercise @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_1_classes/solution/Step_1_classes.ipynb b/notebooks/walker/Step_1_classes/solution/Step_1_classes.ipynb new file mode 100644 index 0000000..8997336 --- /dev/null +++ b/notebooks/walker/Step_1_classes/solution/Step_1_classes.ipynb @@ -0,0 +1,200 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# 2. Rewrite the code to look like it would in your wildest dreams!\n", + "\n", + "How could you restructure the interface of the `walker` library so that the functionality stays the same, but the code is less smelly?\n", + "\n", + "1. could this code work better/more efficiently as a class?\n", + " - e.g. `walker = Walker(...)`\n", + "2. how should the setup/initialization work?\n", + " - e.g. which parameters would you pass to instantiate the Walker class? How do you pass them to the class?\n", + "3. which functions should be part of the class? \n", + " - e.g. is `sample_next_step` a method of `Walker`? Is `create_context_map` a method of Walker? How about `plot_trajectory`? If so, call them with `walker.sample_next_step()`\n", + "4. what would the import statement look like?\n", + "\n", + "**Important:** We are *not* asking you to implement the changes in `walker.py`! Imagine the new interface, and write the code that would use it in the next cell. Of course it won't run (yet)\n", + "\n", + "Here are some things to keep in mind:\n", + "- Which things will you do a lot? They should be easy to do. The interface for doing those things should be simple.\n", + "- Which things should be modifiable from external code?\n", + "- As a rule of thumb, think about how it sounds when you read it aloud\n", + " - “Giving orders”-style\n", + " - “Telling a story“-style\n", + "\n", + " \n", + "For inspiration think about how you call code from other libraries. Here is an example of instantiating an object and calling one of its methods:\n", + "````python\n", + "import scipy as sp\n", + "\n", + "# Sampling from a gaussian with specific mean and sd:\n", + "# Create a Gaussian (normal) distribution object\n", + "gaussian_dist = sp.stats.norm(loc=mean, scale=sd)\n", + "# Sample 10 values from the Gaussian distribution\n", + "samples = gaussian_dist.rvs(size=10)\n", + "````\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:45:09.308173Z", + "start_time": "2022-08-18T11:45:08.852431+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:21:31.332Z", + "iopub.status.busy": "2022-08-20T06:21:31.327Z", + "iopub.status.idle": "2022-08-20T06:21:31.339Z", + "shell.execute_reply": "2022-08-20T06:21:31.343Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from walker import Walker, plot_trajectory" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:21:31.938Z", + "iopub.status.busy": "2022-08-20T06:21:31.932Z", + "iopub.status.idle": "2022-08-20T06:21:32.867Z", + "shell.execute_reply": "2022-08-20T06:21:32.871Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# Create a Walker instance\n", + "walker = Walker(sigma_i=3, sigma_j=4, size=200, map_type='hills')\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:21:32.883Z", + "iopub.status.busy": "2022-08-20T06:21:32.879Z", + "iopub.status.idle": "2022-08-20T06:21:33.026Z", + "shell.execute_reply": "2022-08-20T06:21:33.033Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, walker.context_map)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": false, + "source_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_1_classes/solution/walker.py b/notebooks/walker/Step_1_classes/solution/walker.py new file mode 100644 index 0000000..3e583a0 --- /dev/null +++ b/notebooks/walker/Step_1_classes/solution/walker.py @@ -0,0 +1,91 @@ +import numpy as np +import matplotlib.pyplot as plt + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, size, map_type='flat'): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = size + + if map_type == 'flat': + context_map = np.ones((size, size)) + elif map_type == 'hills': + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + elif map_type == 'labyrinth': + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() diff --git a/notebooks/walker/Step_1_classes/walker.py b/notebooks/walker/Step_1_classes/walker.py new file mode 100644 index 0000000..07433f8 --- /dev/null +++ b/notebooks/walker/Step_1_classes/walker.py @@ -0,0 +1,81 @@ +import numpy as np +import matplotlib.pyplot as plt + + +def sample_next_step(current_i, current_j, sigma_i, sigma_j, context_map, + random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a next-step + # probability map + size = context_map.shape[0] + next_step_map = next_step_proposal(current_i, current_j, sigma_i, sigma_j, + size) + next_step_probability = compute_next_step_probability(next_step_map, + context_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(next_step_probability) + cumulative_map = cumulative_map.reshape(next_step_probability.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + +def next_step_proposal(current_i, current_j, sigma_i, sigma_j, size): + """ Create the 2D proposal map for the next step of the walker. """ + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + +def compute_next_step_probability(next_step_map, context_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + + +def create_context_map(size, map_type='flat'): + """ Create a fixed context map. """ + if map_type == 'flat': + context_map = np.ones((size, size)) + elif map_type == 'hills': + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + elif map_type == 'labyrinth': + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + context_map /= context_map.sum() + return context_map + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() diff --git a/notebooks/walker/Step_2_plotting/Step_2_plotting.ipynb b/notebooks/walker/Step_2_plotting/Step_2_plotting.ipynb new file mode 100644 index 0000000..55845ae --- /dev/null +++ b/notebooks/walker/Step_2_plotting/Step_2_plotting.ipynb @@ -0,0 +1,166 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:27:54.689Z", + "iopub.status.busy": "2022-08-20T06:27:54.685Z", + "iopub.status.idle": "2022-08-20T06:27:55.297Z", + "shell.execute_reply": "2022-08-20T06:27:55.319Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from walker import Walker" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Simulate a trajectory" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# Create a Walker instance\n", + "walker = Walker(sigma_i=3, sigma_j=4, size=200, map_type='hills')\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "walker.plot_trajectory_hexbin(trajectory)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.11" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_2_plotting/show b/notebooks/walker/Step_2_plotting/show new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_2_plotting/show @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_2_plotting/solution/Step_2_plotting.ipynb b/notebooks/walker/Step_2_plotting/solution/Step_2_plotting.ipynb new file mode 100644 index 0000000..4001be7 --- /dev/null +++ b/notebooks/walker/Step_2_plotting/solution/Step_2_plotting.ipynb @@ -0,0 +1,167 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:27:54.689Z", + "iopub.status.busy": "2022-08-20T06:27:54.685Z", + "iopub.status.idle": "2022-08-20T06:27:55.297Z", + "shell.execute_reply": "2022-08-20T06:27:55.319Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from walker import Walker\n", + "from plotting import plot_trajectory, plot_trajectory_hexbin" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Simulate a trajectory" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# Create a Walker instance\n", + "walker = Walker(sigma_i=3, sigma_j=4, size=200, map_type='hills')\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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""" + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_2_plotting/solution/walker.py b/notebooks/walker/Step_2_plotting/solution/walker.py new file mode 100644 index 0000000..ed075c5 --- /dev/null +++ b/notebooks/walker/Step_2_plotting/solution/walker.py @@ -0,0 +1,83 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, size, map_type='flat'): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = size + + if map_type == 'flat': + context_map = np.ones((size, size)) + elif map_type == 'hills': + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + elif map_type == 'labyrinth': + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_2_plotting/walker.py b/notebooks/walker/Step_2_plotting/walker.py new file mode 100644 index 0000000..4a8eac2 --- /dev/null +++ b/notebooks/walker/Step_2_plotting/walker.py @@ -0,0 +1,101 @@ +import numpy as np +import matplotlib.pyplot as plt + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, size, map_type='flat'): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = size + + if map_type == 'flat': + context_map = np.ones((size, size)) + elif map_type == 'hills': + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + elif map_type == 'labyrinth': + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + def plot_trajectory(self, trajectory): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(self.context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + def plot_trajectory_hexbin(self, trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/Step_3_break_out_the_context_map_initialization.ipynb b/notebooks/walker/Step_3_break_out_the_context_map_initialization/Step_3_break_out_the_context_map_initialization.ipynb new file mode 100644 index 0000000..83d413c --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/Step_3_break_out_the_context_map_initialization.ipynb @@ -0,0 +1,173 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 1. Take a look at this (working) code\n", + "\n", + "... and run it. We discussed that the `context_map` varies independently of the walker. Identify the part of the code that will be affected by this change." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:27:54.689Z", + "iopub.status.busy": "2022-08-20T06:27:54.685Z", + "iopub.status.idle": "2022-08-20T06:27:55.297Z", + "shell.execute_reply": "2022-08-20T06:27:55.319Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from plotting import plot_trajectory, plot_trajectory_hexbin\n", + "from walker import Walker\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": false, + "source_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + }, + "outputs": [], + "source": [ + "# Create a Walker instance\n", + "walker = Walker(sigma_i=3, sigma_j=4, size=200, map_type='hills')\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))\n", + "\n", + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 2. Modify the above code to reflect the idea of a separate context_map module\n", + "\n", + "1. how would the import statement change as a result of needing a separate context_map module?\n", + "2. what input arguments do the context_map functions need to take?\n", + "3. how does the initialization of the walker change?\n", + " - i.e. instead of \"map_type\"\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 3. (optional) Actually break out the context map initialization\n", + "1. Move context map initialization to three functions in a separate `context_map.py` module which all return a `context_map` array\n", + "2. Modify the constructor of Walker to take a `context_map` array instead of a `map_type`\n", + "3. Modify this notebook to use the new code and see if the code you wrote works!\n", + "4. Try to run all the types:\n", + " - Run one simulation with a flat context map\n", + " - Run one simulation with a hill context map\n", + " - Run one simulation with a labyrinth context map" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/exercise b/notebooks/walker/Step_3_break_out_the_context_map_initialization/exercise new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/exercise @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/plotting.py b/notebooks/walker/Step_3_break_out_the_context_map_initialization/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/Step_3_break_out_the_context_map_initialization.ipynb b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/Step_3_break_out_the_context_map_initialization.ipynb new file mode 100644 index 0000000..39aad03 --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/Step_3_break_out_the_context_map_initialization.ipynb @@ -0,0 +1,289 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 2. Modify the above code to reflect the idea of a separate context_map module\n", + "\n", + "1. how would the import statement change as a result of needing a separate context_map module?\n", + "2. what input arguments do the context_map functions need to take?\n", + "3. how does the initialization of the walker change?\n", + " - i.e. instead of \"map_type\"\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:27:54.689Z", + "iopub.status.busy": "2022-08-20T06:27:54.685Z", + "iopub.status.idle": "2022-08-20T06:27:55.297Z", + "shell.execute_reply": "2022-08-20T06:27:55.319Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from context_maps import flat_context_map, hills_context_map, labyrinth_context_map\n", + "from plotting import plot_trajectory, plot_trajectory_hexbin\n", + "from walker import Walker\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Flat context map" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "context_map = flat_context_map(size=200)\n", + "walker = Walker(sigma_i=3, sigma_j=4, context_map=context_map)\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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zknPJZQQlnaZR5Gqu070E8oNmlVbgQRuCNmANkTzABK7hHD4S6UqsjiPKwlIoNIrwJYAyqySGzigVXlwhz6XNQVkwxYFeYyi5IgCARcQziULGUMw17YL+n5NKtggAKfkHq/A0u+XOZxy1uHI7m4mllodYx+9E8IocxmHhzecMYJFMwImOrSsnaSCJKtIpI0ZLHphIES/J4UghdOtqPREnhDtQmLlNy4UnHrKV0RRzL+txw2DzmBz8WUk0y4ijGjfeZrFVxxGARKppA15kuO7eqxAeXCfPoglnyoWn1TGK40Pf/+YpFCcIefgxkDLiqQJiu3RsWRdvYr8Qy0+Y9Z4Tgq0yzKpm610G8olIw0UaOJ/9ulUBsJNg1hCFFIIb5AyuYA9XsFfrcLGYD2Q6X5NiMwHAVACcRhnplJFKhYUQAtTghhTixHMHtuNBuY7RHLJaP0ARPiwhjpXEUCAsk052yWALK3I9EYzWrn8lHmS3a2l1SCsYV/QdSrAUCo18zRUUb9YyqTcowIeXzdxYAFfKTIuYFRhjY5+INAAeZTWjtTZQAG8xiG9IMQoK0CKc+ZCB/CpjuZ3NZHCEv7CD6RzgFTmMJpxJp4w0ykmnzKJuy0QtrmQSxG6CySSIXYQAxnhYNHW0ARs6aT/VF0zRxNSc3QTxIBOp0Wrm2uMrm3RLFyAbf7YTogtWMI1EyVq9q4nixEAJlkKhcVSweqfl0Gqi8aGFxxlLg3AlVNYzjQNcz06b+0dTg5M0YBBOVl0vvqUfzcLSdekkDdTgxqsMYy67mMhBkqniJX61OrcB4+fN1MRpN8EU4KsLoDl1uOo1Tleyh7cZ3N1L0GNU4c5ugvCnmQ2Ec4FZgglAOuW8zlJWyhiWEWtlLf2RnfhpWX5gTDYpxYtmnHDDQAmeFg1uFScGSrAUCg2TYEVTi6tso0V0LZbVGZ+LAXzOAAAGyiM8ySq8aLXY52WGkUkwz7GCNCq4nh0slgl6wbGJ29iCh2wlgCYCaMKfJnwduMXm4sebDCGTYOodHM1TKrx4QY7kAX7nCvaSJQNYKbrmMu1ppBDczjQCZSOPs1rfvpQ4nDEwlkNEUM9l7OMy9vGqHMp3oh8AA2QZ57Tr+beNUNYIY3xLceKiBEuh0CjDQx/dEU0tefj3+Hv4yiaGUcpdbLCKuawiiqkUcCH79Ya5l5LFpVoatTkzybd5fgPG2NMRPNlLELsJwp02LmI/0dSSSDUXsZ8X8Ke+C8NPfxWx9JMVXM4+7mIjBdJXTxjpK+JkNU+wikjqqcSNh5lApggGwF22MorDTCefiRzkFraChAUkcQebcMLY9moUhzEAO7Q2VooTGyVYCoUJIciXxsSLBKqPWbB8ZROpVJBCJSlUkEKFnmZti4laWr0j/I9USvCiAneqtEcl7lTjhjOSWGqIp5oEqomjGiezzLnRFHMD23iSsV36PO8wmH5UMoISHmUtN8vpdmNEvc1gWcp81uBHC0X48HcmWsSbmoQLq4hmlYzij+zkSvZyC1u5kj0E00glbqwghlEcJg//Pvsciq6hBEtx2pMiKxhAOcuIPaZMQSEls8hlBIc7FKcifNhAOJW4k0QVlWaiYy5Azhh4gRVWbkOAD0inSUsvd5etXEQWqVSQQDWR1NpNzK/GlXz8WNyNOVYGIfiHHMtr/EIkdfyd33lATjzunR0myiLu53fcMLCbIB5mAlU2mg4DIATvSGOd3JXs1dPY3yCDNs2BWoUSq5MFJViK05ph8jCPsxp3DPyRnRzE+C29O5mC17KLq9jT4T6H8GIXwRzGm2z8WUBSh33nXpdDuctGI15zJlFklWFYiyt5+JGHH/lmj3I8jqmLeI1w4xE5jpdZzkgOcx07j3sSxl/ZihsGVhHFU4yxSj6xQhMt87H3h/AmjIZeXqmip1GCpThtGSiP6GJVhws+tJCq1Tl1NVNwmjygi9Wn9GcT4YznIBexH0DPPouknsh28acy6UEu/mTjTwMuDOYI7zCIfSLIoqDYHquIZiglTKVAL5ptwplNhLOAJCrMBNFDtvJHuZMAsySOJpz5iDS7M5ycpIG57KYVwTZCySSY5xnJg72chBEoG7mMvezS6s0MWl9Dby2+V4kHs8mmQnpQiTvleFCBx9H6MTPOJs/i+V1s1BNgFCcPSrAUpy1nko+7lsJ8HWczloNcQyYJVOs3RUcYIMv0cSSf0Z93hNHiSJGV+j6NuPA7oewhCFfaSKKKJKqIopZgGgmmkZFmdVYjWAYSlhBHAb4dClajcOE5RvGWHMy55HAeOQTTyFx2cxWZrJCxfEs/9oog/o9dXKiJqDmxVHOHnGrTvZdItZnlmEkzTuwhiDI8CKax15IwriaT88nmErIowZPvZTI/kUgNbnjTymxybB7XiqBKmgTM6Co01bAdxJso6oillr+wrUfXq+h9hJSy51tD9zLV1dX4+/tzBnNwcTA1V6FoT6Ks5DV+wRXJk4xmuYhDSMkIDlOBh7EdUieEynpe5ReCaGI1UTzKOP3bvZts4zL2MotcC/fTNkJYQBKriMYZSQJVTKSIy9nn8No/pT8hNBBMI9/Sz6L3oYs0MJEiLiCLgWYd4etx0eNhnzCACtwZxWG9WPZNhvClSMVLtnAdO3FB8m8yaMGJZ1lBhtkYjfYcwps/MbNHSwHekouIp0afzAzQhBM5+FOMDxW4E0gTATQSRCOBNFnUVnWVTxjAu2JQTy1fx1c2cxNbWUU0q9tNrVZAq2zhV76jqqoKP7+OR+AoC0tx2pIrAvhYpnEtu7mFrWyVYVQIDzY62M3BQ7byGGsIools/Hma0RauqGbhzEek84lMYxSHOJdcRnOIDI6QwRGqcGMJ8WwggmkUAFCKJ28yhAfNRtHbwjweU4IXa81mV7UKJ34lll+JJVWWM4dspnLAInmjBSdqcWOYmVV3A9splZ5cxy6iqQUgkloeZgLPMZL/sARP2viafuTjRwalZFBKMI2EUU8ATZTSM41gA2Qj8dRgAOYyi+Ec5gL2k0olaVSQRgXbCeEb+lm4C12kgQBNvAJp5Gzy9JljB/DFGal/tvZcxR4OSh8WiYQe+QxHz5vJmRwggjpWowTrWFAWluK0xlkaeIVlpFDJKs1CciQpQUjJw6xlIgepwJ1bmEaJnRiQOSGynrPJs7K6uksmQTzM+E4HBl4os7jJjgusGjcry6QET3xpxpM2NhHGw0xgFrncwlYacOYvzKRYeIM8KgBFwveYP4+JybKAh/idbPy5UcwwbpSSdMq4gP1MpghnrQFuCZ58TzILSTTOJ9PwlC28yyI9MzAXPxIdiE0+zPgudevviEDZyIcsxF3LaLxdTOuR855KdMXCUr1HFKc1bcKJZxlJC4KJHGSqZul0hqn1UTNOzGdcp2LlpH0vPCK8+Eikcw3n8AATWEtkp+MuAP7BGM5nDm8yRN+2mijuZnKnYuUpW7hcs8g+Io1/MIZdGAtslxPLX5hhdcyNnMn9TKIBZ0ZQwmOsZhEJbCMET9q4k40Ibb5WkfDtUbECbX4Xxg4UOkKwW4TwpBjL1cziY82tGUYD17OTT1nAHXIjg2Qps2Qu3/OdRTf2RKoxYOwz+B7pvMtAmnHif6RyG1P1/R5jDeOk4zVxHXEZe3V3puLYUS5BxWmPPdegPabKA/xBS0J4kRHsFiF29/WSLdzOZsZxkOfkKFYKY7dzgxCsJ5L1ROItm2nCBT+aCKHBqgNFFe7U4cpf2ar3zPuGfrxBhkM1UNewm2AaKcKHTxhAi3DmV2Lxl8b3e54VNo4S7BIh3C8n8RS/MYIS5rOGVxjGKyxjKKVMpaDXWhnZFCwzjggv3mMQH8s0zqBAdxfOIo9Z7TICwZi8soEINhJuYYV9I/vRgAsIwf9kKpdpccTHWMPD8tgsrUDZyHntehwqjg1lYSkUwGcMIIsA/GjmNjYbp/PaYIAs0+uiPqM/S0W8zf2iZC1psozXWco0CnSrJEbW4CFbCZd1+nvUCTdahRPlwpN9IohC4WvxaMaJh1nLBWRjAP7NEF53UKziZZWeWv8aGUeTIqRkEoX8i2VEU0sJntzDJBpxpghv3SbYJUIsLK2b2KYLqnMvWQ7m8avOWia1CGeWiARuZjq3cwbLiaHRrGw6Dz9mcjHPCGNSTU27AuMG4aq7gN9jIIUc7ZbxEGuPydIyWVeqiW7PoSwshQLNNShH8hq/6K7B5e2sh1BZz6OswQ0Da4jUJw2bM0SWMJfdDDHLqCvWWiilUcGDrKMVJ/pTQRkebJehbMP4KMTHKn4WIBt5jNWkUUEzTjzNaH4TDs6kkpJb2IozklVEsUEYJwV7yRbmsYmp2liOdUTwDKOoEe6cx4VGITVbh8nSeo4VDKcEgDpc+K2nZ2NJyVBKuVYrgs7tSsskIdhNCLsJ0Ue1VOLGnUyx2YHeFi3CmaflaF5lGQCuSB5iLX+RMynsosvT3LpaTDyz2zXbVXQPJVgKhUZHrsFA2cgnLASgEWfWE0k6ZfrMqCGyhP9jt83U7xK8eJtBzGctyVTp24NpZCoFetysvYAB/INVRFFHFW48wnh2deB+bM9UChhKKU048QYZACTLSh5iHdHU0orgbQbxFamWN/X2N3gpGcMhXMym/P5CXM9NHtaE6hozoW/GiU9I6/KpomUNV2sTm98gg2p7LZvssFcEsUzG6lmbrkj+QCb/ZHSXzmOyrnYRhNQmUZumASi6jxIshcKMzxjABA6SQiW3sZln5CjOJ9tiZpUHbcxjMwBfyhRSqbCwqEw044QTkiEc4RlWso9AAtuNCSnCh1I8SafMSsDMeY6ReqKEo5gKa10x8AhriZE1eof4Ejx5grF6d/OOSKDaIo0eYCFJXVqLTewI1QKS+Jz+XZ7ijJTMYzNuGNhAOL90M762mTCmUaDXf03lAB/LNIetLHPr6mPSuFtzIZ+I05pPNpRgKRRmtHcNDmMB3jaaz5q4xMboj2K8+Adj2COCiZPV3MIWhlHKYMqs9g2jjvmMowgf0ihnCKXMZbfVfo+zhjI82CZD+YU41mvuvY74kSQCaSSWWlLaDYAMo4G/sYl75eQOE0zAWBRchI+evp6Nv0NF1XbpIaEaJw/ihGQtURiE4GzyGEopDTjzr3YTnbuCybp1x0AO/iRR1SUry9y6asaZQJqoxpUthHVrPYqjKMFSKNph7hr0ppVCfPiINLII5G0Wd3jsGiJ5jlF67OWA8OMeOZnJFHIj2wltV3vliuRuNnAb09hOiN7LEKAGVxaSSH8qdAtsGgVMo4CH5HjWdZLBtlzEcUD68SLLrWZvgTHN+zL28qbmLrRHk3DhYTle/+zJVFnFuRyiBy2qK+Qe/qRZvfn4skAmMVeLfX3AQGONWBdwk20ka2NgzP8PkjQX7mgOOXQec+vqQ9KZrMUJVxNNm1DJF8eKEiyFwgafMYAGXKjAgxXEEEIDH/OTxT7fk8zX9COUBgZyhIP4sJxY6xu5EKwklvUykqvZzcVkWcSDUqnkCvYQQJPdtHVX2UYa5cwmm6kUch/ruUVO79BNNUUWcA8b9JHvTzCWy9irz93aTgg/kOzQ9QhuJ7SXso8v6G93f2dp4Ar2MIZicvAnhAaGUKoLZ3eEaogs4TxycKeNcZqANOBMPDUWRdFf08/uOWbJXCKpZQchZBHI5ezlQrLsjmMBWE8Eixwcx2JuXe0khHvZACh3YE+hBEuhsEGbcOJrUvXnE8zSm1cQw5sMoVQY2xAV4ctWB9w9jcKFtxjCYpmguwlNXGvmBnyDIXxFioXwtQhnthPKLhlMMI0M4QiPsoZb5TS7o+4vYx9uGNhPAPcwiVac9L6BN3AmOV1w67UfKX89OyiQvnatvBhq9M+UZtbP0MT3JLOMOCro2B1pzmXss2gC/DMJ/JsMnuY3i/ewa/dJya1sxhVpFZMz5wge7COQ8RxiF0E8ICY6tD5z62oFsbzCMgJpogJ35Q7sIZRgKRQOYOoSvpOQLrub2mNyEw6llBhquJ0t+msLSOQrkWr32DbhxONyLK/zC3HUcA8beFSOs5m6/aM2Dj6aGjxoYxCHccNAIT7kdGGasr9sYoLWj68QH2KoxQljXK1eupBrI/vNo5P+HZeQxSVkUYcLy2UsLzsQc2ptV890NnnEUW0liHezgVLpRSJV7CCEFcRQLIwlAw/KiVzDbgbZiCeaCKGREM2C608F42UR64jU+xXaw7yrxXXsxJM2ynHnccYqd2APoQRLoXCARuHCUmwXCXcLIaiSbtzR7pu+I409K4UHj8pxvMCvTOAgfyCTj0i32u9nEphBHoMp41a20KbZHiuI6VL8KZBGXLWVxbRrHOtFq0VH+K7iTSszyOcNMmjq4HZ0hdzDBKyLeNNtvPd0syzLMRRzPTspkj78RAKriOZ3IjsULHNckDzKWgC+lv34ihSbbbgCZaNFAo4nbWwmjKcZ3WlSi8JxVPNbheI44i5bOYNCziHH5s12KXH8k1E2BcVbNhNPtf642Gyulb2GrXGymjdYogsOdN0dCNBfllvEsXxp5i426c+fYAwt7SygQRxhJvn4d3HkRzVuXCzO15+bJ1i8y0A+EWkkywre4Jcunbc9ufjxNKMZyyHOI5sQs76DHbGeCH4kid+J0K2u+XKNhaC+TzqfkOZQN5LTna40v1WCpVAcBxJkFeeSw5kcwKeT4ZD/I5XVROnClKD929kN9TrOspmEca3cqfc+LMODKzi32ynf5sTKav7FcnxoYTHxPMtIm+d1lgaGUsIUCplKQafuQoA5zAHgEvZxjVYIbBIrEy7SwFVkchV79M7tJn4lhv0EkEoFYzhktwHtPgJZSTSriSaJSi5kv8PWVz0uLCKBMjws6vQA3iOdL+hPcw/OBztVUYKlUJxAnC/3cytb9ecH8WYzYZzJAf3m3YLg3wzlNrN4li1K8OQAfuThRz5+BNHIdVo6Nxhv9KYkDFfZxixyuZpMi4LlGeKSHvtsI2Qx/2A1zkj+w2C+EPYzB8EoXn8gUxchR2kvVua4yTYEkibhAlISQBOVuIMQJMgq7majnqpehwtfkcIgysigxCI78AVG8JNIJFWW85rWnulY2EcgNzOtR74cnMqoAY4KxQlEuvaNfSfBfEg6h/DmWVZaWBrlePKDSEZK+CvbqMSdfE2UzB82MwIlumh9x3ecKy/kbHK5gr1WdV8AqbKcfSKoRz7bJhHBv2UGt7C108zBMFmHAUE/rYh5FVGE0WBR92SLatzsihVgacUIQSUeOEkDl8s9XE0mbmbW1W1M44Aw3hRNySRnk0saFUyhgGbpxB+6KKb2qNO6wCt6DiVYCsVxYiUxHMSb51hJOPWAcTaTeSzrR5HMjzKpSze6T0QaYbKec7XU8wV8o79WhofFTCiAeWzmFjmt06w3R/mOZBKoZjY5/J3fuV9Osuh5KKTkb2yyGvsxkYNsJZRVRFGJBxW4U4EH6ZRxJgf0/f6OY2nl5lzKPv5oZnmaMHcnVQl3FpLEfhnAayxjBCWM0Jr7VuHGF6TyPck04IJrB53pBbaTZdrH9BTHjhIsheI4EUmdhVjB0Sy35cQe3bGL38qFlGQTYLGtFE8+ZQBLieN7vgOMcZ3hHCaFSuaQzTekdO+DWC1A8KocSgR1jOQwT7KKv8uJ7BIhCCm5g02cTR4GrOcZDTWrRbPHP1nJEelJBR5U4IEnLdTixlZC2Uy4Xg9nTg7+FOGDm5kVm4s/RVjH+HLxpwWhJ6YsJ5YXGW4cPaLR0mFpseJ4oQRLoThOXGiW1WdiFVF8RPox9eabzgE99mUSqp9JoEU44yyPWgbf0I/NhHMHm7iOnayS0TZv9t2hTTgxX47jUdYwghKeZBUPygnMJJ+zyaMNwVOMJoNSziOHvQTyFoMJpFF7NBFII2eRb3Vub1rxpoZ4aiy2n8kBDuPF1ZxjdcwGEcm1dN5vEYxF2XnSX++3mEWAhVgpThyUYCkUfUATTtzONLtC5S+bmMYB3DULIZlKRnAYXy3DsAFnDAiaceYdBlGNG340U44H3rRwMVm6n6oRZ1wwkEGp3gXCkzZuZivzGd9zn0m48Igcr4vWc6zACXSxWiFicZKS88ghkSoqcGerONoBQkhJKhUkUq1v+5xU9hHELWyx6nQPxknCPUEWgVYNghUnHkqwFIpextzBV40rfrSwm+AOraorybSos2qPqSefN63cySZuYypPsJr+VNDfThJD+5jOBA4yXhaxRkQ7/Fk6o71omYsVGN1t0zjAWIq5m43cJqdiEE4IbTRIItXU4YIHrTgDwynhUvZZuRIrceNJxrBFhPfIurPauVQVJyYqKqhQ9DJjzTp97ycQgO1mo9+dpYERsphr5U6SZCWAbkk5yr9Yjl8HBbpNOPETCfxEAvvNbs6PshZP2bX36owm4cIjjOcdBnI/E3WxAkAIXmIENbjSnwouZZ8uVueQSxvGPoOmiFEKlVY3qaXEMZdZPSZWYExB15fYY2dV9DTKwlIoehMp8dLmaTXhRII2rmInIYyQxUymiAkU6d0gQmjgOUZRb+dP0+QK7GhGly3cMRBGPWV4sotgPbUc4F0WcY2cRUsPFrk2CRc+tTMxuEx48rocyr1s4P/YTX8qmEQRbcAzjKbB7LOvJBp/mvRJzvY6ehwruWa9FcPMkmIUJxZKsBSKXmScmXW1kQi9fc+jrNGFzEQVbnypdYj/mDTy8SOBauZoHcA/J5W3GIwrBs4mjz+xo0vCZUrZbk8wjSzkG6qlG2V4kEUgLzCiVxu2LiWOKRQwlmILsVom4nCSBp5mFNkEkCf8CZSNjKaYtUR2eeS9o7QIZz3ml9JJXZii71AuQYWit5CSa8zGhpj3mvOilSazP78q3LibyeQJ4zf9SuGBACuxQghahDM/iGQu5Ty+7+Ko+vdI5xv6sZJostt1bPejmUSqmUk+QxxINz8mNNdgtZZ4bhIrAINw4hcRr1+LCuHBIpHQa2JlYj0RACzpySbHih5FWVgKRS8xiuIOM8/acAIMuljlmiVhnCez9VR1c7Eyx4NWzifH6rxPMZrfiKZFOOMlWxjDIe5iI24Y6Ecl/2AsrZr15Crb6E85hfjiTxM3s5VhlJJANVvouRiRLcqEJ3+WM/CgjYPCp1ffyxEeYyz9qGQ3wX29FIUdlIWlUPQSnTV59aKVCty7JVaAzS7of+FMlok4PR5VL1xZLuJ4hPE048REDvIA63DR6rNahDM7RSiVwoN84c8u7WYdb5Za3puUC88TQqzAGHfbJUJszhZTnBgoC0uh6CV+I5orOJcb2cYZFPIGQ9hEOM5mbX6K8KVRHP0zdFSsAAqFLxfK85nGAW5lKwfwtUgeMGejiNDTzU2i9Q951NIycUAbxni8BEuh6ArKwlIoegshKBOe+uBEA4I84U+2CNQf3RUrEy4Y+D8tTraY+A733ygi7FpaJvLMBevkG+SgOMVRgqVQnAB0R6yQktvYgj/NZOPPV1qGYUd0JlqF+NKGsQ6sfdNchaKvUS5BheI4kUgV42WR1fYkqpirWUkOixUwhUImUUQrgmcZZeXes0dH7sEW4cxB6UMstcRTTRmeXfuQCkUvogRLoehlDJpLcBZ5ViM2zOmKWAXIRm7VLLJPGdDl5rntRetCsvgC4/DFfPx0wdrcy5mCCkVXUIKlUPQyC0gihAaLQYLmSGAV0XxFimOjRdq5Aj+x01GiMzaKCN6QGdzGFqZzQBesPPyYyEGVeKE44VCCpVD0MrtECPcwpcfO111XoC1+JYab2UoyVUTLGoqEr54pmKAES3GCoZIuFIoTAGdp4CqZyaVyL0NlCcmykrlyJ6PlIYukiGN1BbanRrizBeOIj8kUAipTUHHioiwsheIEYDKFXGdjpLuJw9KLtxnEVAqO2RXYnhXEMJLDTKGQT0mjUJvK60MLvrRQg1uPvI9CcawowVIoTgCStRZOh/DGm2b82o0XCaeev7Nef97eFeguWwmnnnDqiDD7txRP3mRIh7Gx1UQxj81H3YIc7TwhOGphRcsa/shOanAjHz/9MZQSRlHMBiJYSxT1alqvopdQgqVQnACY4kX/I5VGXLiXDQC8y0AuYL/VtN2pHOAKuUcXJlvTeAFaEHzKAKqx3zi2RrizRYYxksNMppBPGWC1T4ys4TlWdFibNZ0CABqkMx+Rzo8kKfFS9CgqhqVQHGeulTt5Xv5KgDx684/TBCsfPz2W9D7pNONsU4wuZx9nUEgaFXbFqgAfHmG8Q13OVxADGBM62mMuVrn48REDWEUUBfjY7JboSRt/Zgff8R0XyqxO31uhcBRlYSkUx5k/sAeAL/iRGVyCh2wlUhsaeARPRnAYMMa1Em1k6q0misN4UYw3h/HCl2bmkK13hq/EjQ9JZwFJDs+0snALUqtvj6WGh1hHMI3k4M89TKbKTABdZRsL+QaAbYQQTCMxZsenU8Y3pHTh6igU9lGCpVAcZ5YSx5kcAGCsPEg5HgBU4M4AyvV6LVti9RfO1Du7h8p6rmMnM7RzNePE16TwKQO67IozdwuaW1mPsRo/WmyKFRi7vR+QvsRRw3sMZKcIBYxCFkcNB7QEDoWiJ1CCpVAcZ55jpC5Yj7OGVxgKGNPJK3GnDUEefqwghpXEUCR8+Vz+QJDm+vOSLVzOXi5mH+6auC0ljncZSInw7va6TNmCV2oWIIAfLTTjxL8Yhi/N+ErrkSauNhyDLcKZbAK6vRaFwhZKsBSK40ybcOI1mcHNbAPgVrYCxtEeW0Q4Z8uL7Gb1nUcOEynS41bbCeFNhrBPBB3zujZoE3fbz/Fyw8BL/HrM51cojhUlWApFH/ADybpgmSgwuc/ai5WUunV1njZhuAAf/ssQ1hLpWDsnB7jKzLJqTzUduxgP4cN+AntkHQqFPZRgKRR9QJtw4jk5grvYpG+7ha1MlwfIIpB9BJBFIK4Y+BM7LI59haFdSqhwhMmygPPJBozZiWmUMVpL/mhDsJpoPmEAxSfIdGDF6YkSLIWij1hKPH9ip0VaehrlpFFu95i/MUVPbOgpomQtd2jC+QkD+EikG9ciy7ia3YzmMLPIYyb5LJbxSrgUfYaqw1Io+og24cTbDAKgHHeu5Sze0p7bo0LLKOwpXGUbD7IOb1rZTgjvk66/limCeUBM4jamsp5wnJHMIo/3WMQdciMRsraDMysUPY+ysBSKPmQJ8QTSRC2uXMI+zjabl7WFUH4iEYkghQoq8KBI9Gya+I1sN6vfcuevbAMb/W4P4sMemhlAhS5cM8nnZ5nAKwzrUfekQmEPJVgKRR8SQgPh1DGXPFw0pdhEGB+Szi4Rou/3K7E9/t7mcSuAyVhPQ+4IZyTnkssKYtiiBj0qjgNKsBSKHuBquZtgGnmTITSKzv+swmQdV7KHszsRqt4iVNbzEL/rzxtxZinxVHaxM3sZnuyk99erUIASLIXimHGWBuayG4DZ5PA3aT8xoq+FykQ/zQ0I8BX9+IwBVIqejY8pFD2NEiyF4hhpE06sklFM5CAAL7KCr2U/3mEQTZq1lSrLeYw1Ft3OtxPCOww6rkJlYi2R3M1kY3cNJVSKkwQh5ck3UrS6uhp/f3/OYA4uanyB4kRASh5jDeM4ZLG5Hhe8aLV5yBzmqPEbitOeVtnCr3xHVVUVfn5+He6rLCyF4hjxl02kUcZBrPv42ROr5cQosVIouogSLIWiiyTJSgZSRhplpFNuMY7DUaZSSJD8lW2Eso1QdhGiUsMVik5QgqVQdIG5cidX2+i5l48vuwkmk2DcaOMmtuIEvMUg/kAmnjY6mmdwhAyOAJmsJZKHmdD7H0ChOIlRgqVQOEiorOdy9gLGzL5dmkDtIYhAGqnDlXLhCYCLNHAj27menRbnaEPwJ2YCkEEp4zjIWIpJour4fhiF4iRECZZC4SBXsAdXJFsI5T4mkUgVkynkr2wjjhqqcOMGOYMy4clXpHAj263OsZoovVtFEb7slwGMpfh4fxSF4qREOc0VCgcIlfWcr432GEYpS/iK/7CUq9lDHDUA+NPM7WwGKUEI7mSK1XkmU8QS+SXj5MHjun6F4lRAWVgKhQ18ZDMpVJBCJSlUcIbZ2PiOGMchzuQAS4lnuwi12ZcP4DHWcJE8rwdXrFCc+ijBUig0RstDzCCfFCqIpq7T/TcRxghKrLbfxFa2yDAq8MCAfTfGs6xkFdHHtmiF4jRCCZZCoXE7mwmjQX9+EG+yCCSLAPYRyH4CqRGWvfa+ld/iTStzOZtivHiF5aRSwe1s5i0Gd+hzT6aKZJVsoVA4jBIshUJjBTFcShYVuPMXZnS5ZZFBOPGsHMl/WcI4Dll1vbDF70QwRiVdKBQO0eNJF/Pnz0cIYfGIiIjQX5dSMn/+fKKiovD09OSMM85g165dPb0MhaLLfEwalbgRSBNTHIxZtcfNRr1VRyixUigcp1csrIEDB7J06VL9ubOzs/7zM888wwsvvMB7771HamoqTzzxBDNmzGDv3r34+vbscDqFwpwwWcfdbCSYBm5gBi3C2eL1OuHGJhnOdAq4ha0sk3FWLsCOSJXlvMYy/fnLDKMZZ7IIIA9/gmhkDvuZTKFVjCyc+mP7cArFaUCvpLW7uLgQERGhP0JDjaMWpJS89NJLPPDAA1x00UUMGjSI999/n/r6ej755JPeWIpCoRNNLUMpJZZaFvKNRWr5IFnKM3IF0ynQt12jjQxxhFQqLMTqTibzo0hmsUggVwQghaBMePKOGMy1nM2NTOdzUi3OESQb2p9WoVCY0SuClZWVRVRUFImJiVxxxRXk5BjrV3JzcykuLmbmzJn6vu7u7kyZMoU1a9bYPV9TUxPV1dUWD4Wiq2whjO1mwwYfYw1L5JcskV/yIisYRqnF/ueTTZx07HftAbNhiHcyme0izP7OQpAtAnlLDGEGF1OlDU2cSX4XPo1CcfrR44I1ZswYPvjgAxYtWsR///tfiouLGT9+PGVlZRQXG/314eGW47TDw8P112zx1FNP4e/vrz9iY3t+XLjiNEAI7hRnWFk29nBGcoONbhUm3GQb3u26sXcqVjbW9CZDADiHXMTJN+1HoThu9LhgzZo1i4svvpjBgwdz5plnsmDBAgDef/99fR8hhMUxUkqrbebcf//9VFVV6Y+CggK7+yoU9vCWzbwnf+Zy9jl8zGiKmS/XECYtY07p8ghf8IPFthuZ3jWx0lhJDLW4Ekkdwznc5eMVitOFXk9r9/b2ZvDgwWRlZXHBBRcAUFxcTGRkpL5PSUmJldVljru7O+7u7r29VMUpSLBsYDKFpFHG1HaZf0uIoxJ3LiWrw3NM4CATOEie9GMHIUykiECaLPa5h0lki8BurbFJuLBExnMh+zmXXDYR0flBCsVpSK/3EmxqaiIzM5PIyEgSExOJiIhgyZIl+uvNzc2sWLGC8ePH9/ZSFKcZ7rKVz1jATWyzEqtVRLGfAHYRwnOMcOh8CVRzHjlWYgVQbGN4Y1dYSCIA4zioki8UCjv0uIV11113cd555xEXF0dJSQlPPPEE1dXVzJ07FyEE8+bN48knnyQlJYWUlBSefPJJvLy8uOqqq3p6KYrTmFRZzvXssPv6RA4ykZ5pQNuEE4fxOqZz5Al/dslgBlLGTPL5jAE9sjaF4lSixwWrsLCQK6+8kiNHjhAaGsrYsWNZt24d8fHxANxzzz00NDRw0003UVFRwZgxY1i8eLGqwVL0KE+yCn+aaUHwM4l8TzIP8DsJ9HyGqTsGXmMZH8o01hAFHcRjO2IBiQykjHPI5XPZH9nN8ygUpypCypMvLam6uhp/f3/OYA4uwrWvl6M4AflZfqVl+Z1JLv48yDomU0QzTmwi3KqJugdthFFPOHW42mux7gD7CeBDuidcJhemDy3cx0Q2CRXLUpz6tMoWfuU7qqqq8PPz63Bf1UtQcUpTiTv9KWcyRbQgeJRxrBeRnR4XKWv5gJ+7/H79qORR1hqFq4sWV5NwYamM4wKymUKhSr5QKNqhBEtxSuOExFOrlSrAzyGxAnDF0O33rMNFF65c/PCWLYTRwGOM5TcR0+GxmwnnArJJpaLb769QnKqoicOKU5JyjJ3WH2YtITiedRcnq7lf/s7bLNa3FeHj8PFtCO5hMh8zgDpcSKRaH1nyMOt4Vq5giCy1e3wWAYAxI9FNdq2RrkJxqqMES3FK8gyjqMaVNCq4h40Wr6XKcp6VK7hebidVlhtH2gN/lDv4L4uZhmVh+iKMCUPZ+PMuAzt8X2cks8nhPTGIa5hl9fpQSnmeFXaF6wieVOCOM5IkKrvykRWKUx4lWIpTkq0ijJuZTg7++rYkqkBKJlPIUEq5nH28xjI+4Geul9u5kr1WfxDLieVC9gOwgCS8aOn0vRO1oYxDOKJvW0w8V3EO35NEC8K+cAlBFsYCZOUWVCgsUYKlOGUpFj7M4wyLbXewCXdtZlUJnjTgTCR1dts1TaVALxS+iCx+IY47mMK9TCLbTAzNqcQdJymZz1p927OMpFR48YoYzlxmWQnXP+QqQqVxxMg+zS2YoiwshcIClXShOOlwlW204NRp9t1gWcpf2WaxbRZ5+s/LieUj0hlNMXew0aqR7ccM4A/s0Z/HUMt/MM5520sgy4m1GnFvAGpx43FW6dvuYrLFWkuFF68wnM/kAK5gD7PIZTTF/JfFvCEzdAsrRVlYCoUFSrAUJw3uspUr2cOl7GMboTwmx9EorH+FI2Qdf2Y7kykCoBZXPiSNQny5l/X4aW69QRyhUbiQKKvwppVWBM8zknvZQCuC98Qg3mMQw+VhHmQdvmbuwP5U0N9MUO5nIhtFBE7SQAT1vK+lxNfjwjY7DXFNwvWNTOEuNjCQcu5kk1XiRXO7QZMKxemKEixFzyAlCVTjbXZTb8DFGEM61o4NUjKBg/yVbfpk3lEc5jFW87CcoIuWp2zhSvZwMVm4YaANY9zpAwZSJYzNk2+W0/lQE5OBlPMvuYw0ygF4ieFswVpcNotwLmIOAOPkQR7DcnZbJoFs1Ip8DcKJ9+XR+q0rObfTj1cofLlDTuUisriWnbor0JR4sYdgR6+UQnFKowRLcUz4yGbOJJ9zyCXRRtujtUTyrBzVpVHz5kTLGm5iK6O1sRuH8eJb+nE1uxlGKY+xmkfkeCZTyB/ZSZAWb9pEGG+QQZ6wjDMVCx92yGAGUwagi9Wn9GeRSCS4k8azGZRYbUujgtHyEOtFJHPkfn37xwyg3sFOLAYh+JJU1slI3doCo5WlBEuhMKIES9F1pNR73k2hAHetyLYRZ47gqe8WRj3jOMS/Wco/5BgyheM3XnP3nxsGmnHiC1L5lAE0CRd2yWCe4jeGUcr3fKcfV4gPbzKEdUSCEHjLZqKpJY4aUqhgAOWka2JgIpMg3mWQQ+sab6dh7nzW8L4cyPXs1Le910kKvC1M1taFZDGWQ+w0m5CsUJzuKMFSOIw9ayoHfxaQyC/EUWdmSSXLCh7id6Kp5QV+5S05mK9I6dhFKCXjNfdfhOb+20A4rzGUInG0QXIFHtTjapEocQgvfiWGyRRyJXuIkrUE0NzhZ8okiLuY4lCj2XBZR6S2JhN1uOBNK65IC7G6ienddoUahOArUvnKwcnICsXpghIsRcd0YE39SiwLSSSTIJs352wRyE1yOn9jE2dQyI1sZzwH+Vb2I4QGdhJCljb00E22kUEJF7Dfwv33bzJYbd6PT0quYTdXsBe3du2TIqnnarOsPkdIo5xEqtgrAzsUGF/ZzAv8arW9fWYhQBVu+udSKBQ9hxIshU26ak3ZO0cKFWQRyBnaAMUhHNELamtw5X05kNEUk0GJLobt3X/mxFHD/5HZpc+ykmhNWIP5hu+sig9fZRlF+LBSRrPLTrxoNtl6iyVzfiSJ/QRwG5v183rSqse0FApFz6EES3GUY7CmTATKRv7MdgZSRhR1Hb6dLy3cwlb9eTnurCGKL0m1cP+ZU4YHNbiSSTCLSKAIH8ZxkLnsttivEWe+IJUfSKZCGPsKzpW77FbKR1PLlezVn7sgSZYVZGsp5qE2xOojBvC+GMR5Mhsn7T1z8Cedch5hLQ/KCWwR4R1eA4VC4ThKsBQ9Yk2ZGMFhZnCgW+vwp4nhlBBOPQelD0UcfRTjjTttPMkqfGmhDcFKEaOJ7BGL8/xGNG8whBJxdGz9DJnH1Zpl1orApd3Mq/8wmDTKmaTVbgG8wS8drncDEQTLBv6kTTZuwEVvy+SGgRnkswUlWApFT6EE6zTnKpnJVWR2y5qyxW9EcxZ5DMV+R/IFJOKMpBlnAmkkilqiqMWTNqKo0yyzwx2+zx6CSJBV3MoWi559DTjzmBhnse8QWcLf2AQY091HmKWml+NOEE0YEDwmxhEja3iXRZ1+zmpc2UMw97Bej2OZWjgdxouVRPOlSppQKHoUJVinMUmykuvYBXTPmrJFk3DhZTnc6qafix9PMoY8/GyLoJQE00i0Jl7R1HKFmYuuPemU8X/sxhlJI86sIpozOYAbbYTLOg5r1lWMrOER1uKKZCPhRFNjcR7TSiZTyFek0uDgn8QmwjEIQaw0ns8kUiuJYU83hF6hUHSOEqzTmD+apWHfwjRaeqAFULKs5EWW68+bceJ5RrKbYA7jZf9GLgSJsorr2cGPJPE2g1hAEi/wq8340RiKAUv3X6BsZAQlnEc2bzEEJyl5jNX40cJugjAgrNLSTVZROuWcIQvYaSfpYiuhFlbjBm0a8ANMJIAm+0KsUCh6DCVYpykDZJl+0wdwwUALxy5YATTixtHBg24YuJ/1gNFdVyh9ycOPfPy0f/0pxguAv7CdRKq5nS1kUMqbDOnQ4jH17zPxHf0YQQmzyOVDmU4ATcRSSyuCzYR1mvL+AL9Tjrv+vAXBWwzmr2y3GgK5EWPfwErhQaU2LFKhUPQuSrBOU241y87Lw48GB1sIdcYmEcFcOYsUKomjmgSqiaeaGGrwpI0UKq3GZnxOKmuIIpFqmnHCCckZFOqp8LZYSbSFWAH8TiSH8CaSOqZxgM1awoML0kqs3iOda9tlFrYh9NZOAK5I/sp2wNip3cQ+Arma3cwily0ynJXEsJooao/BlapQKDpHCdZpSqOZNfV3JvbouQ8Lbw7jDUTr25ykgae1VkrtEcC55ALGkR8LSeRZVloVBpszmSI8ZKtFt3aDEHwnk7mR7VzIfhaToAuYOWV48D/6WwmWc7vMQXusJ5wxFOOKZDTFjKaYeQg2a+K1ghibXeQVCsWxoQY4nqaUaW6sMjxIpQIn6djNurtkUKqL1RosC2rz8WOKNpZ+AUncwtYOxcrEC/xq1az2ZxJowJlEqhnEEe5jEqVm/Q0BFpFwTPE6U/wKYAUx5OCPiyZed7GRv/N7t8+tUCjsowTrNGUbYbQgCKaR+azlXX5mjtyPh7RuNXSseMoW7tDSyr8nmUcZZxblgrvZqKfV/9FsvIYtXmI4tzGVCtxJoZK3WcRlci8u0nh8nXBjKfEAXMB+Dgof7mKKxTm2Eko/aX84Yj6+XMpsNtqooWrGyaJ7+s8k8DLDOGIWx2rBiTHyID6y4z6GCoWiawgpe/mrdS9QXV2Nv78/ZzAHlx6KvZyOBMsGzieb2eTgpzWJrcWVBSTyHf0oFV498j63y83MJodDePMXZtAoXHCRBh5gHRPtdD+3RwXuXCbOI1lW8oY2/dfEuVxIs3DmcrmH69lJG3C+tu1hudaiKPhYOI8LeIVlJNgYp2LOQhJ5UYzokfdUKE5VWmULv/IdVVVV+Pn5dbivEiwFHrKVM8nnIrKI1ZIL2hCsIIavSGGfCOr2uc0HHr7EcCRG92AGpQTT2OGxrzKUC9hvkfDwEsPxpoUr2GMxAdjEtyRzAdkALCWO5xnJRIp44Di76Urw5DlGqtZMCkUnKMFSdAshJaM5xMVkWSRH7CCYr0hlLVEYHKw1SpNl3M96q4QHc5pxshurqsCd5xnBTkK4j/WM1VLwtxFChllniwP4EteuGBiMgyNL8OIMCvDvZMRIT7KNEL4lhTVEYhDK465QdIYSLMUxkywruYgspnIAVy177iDefE0Ki0iwmwXnK5v4mh9svtaME5kEsY1QthFKIb58wE96/KoNwRE8caNNL+hdTDxvMISL2K/3Auwq1bjiZ8Ma60kWEc/XpJAjAnr1fRSKU42uCJbKvVXYJFsE8CyjeEcO0uNcUdRxC1u5ll0skLbjXOM4ZPG8BE9+JoFthJJJsEV2Xqosxx0DLQg+Ip3P6U+bcMJNtjGXXVzCPmaSzwgO8yLDmc847mEDXrRShgc/kch5ZNu1oNYTzj6CGEoJgyjr+Ytkhietxm4XCoWi11AWlsIh7MW5vieZ18VQfT8XaWC61q19GbEdp49LyTgOUYgPBcL6Zp8my7ibDfr7LSaehSRyFxst4lomqnHTk0f6gkrcuFSc32fvr1CcjCiXoKLXsBXnuoJzKROenRzZPcytLSeMdWNvMZh72aDvs5JonmUUjTiTTCV3sIlUO6nxWwi1iM91FEfrLtcwi2Kz0SYKhcI+SrAUx4U35RKSqOJhxrNWRPXqe6XJMu5io1WCRTNOzOZCplDIX9hus1FuR7zKUDIJ4jWW9eRyySSQFcRyFnn8hyFWbaQUCoWRrgiWSmNSdJssbRpvKvaLcLuLh2zFS7bgJVvwl00M5ojNbMDHGYsUggkUdVmsAG5hK9M5wPckd+m4z+hv8bx9kXEaFdyoNfNN7+X4mUJxuqCSLhTdJotAziKflB4WrKvlbquR9/YwJTp01Ci3My5iv83tjzKWR1hntf1+JvIUqyy2jexg4GSVWQd4hULRfZSFpeg2+wgEMApWD3qWgzuwlPYRyF1MBowNfEvxYrzsmQ4W7bElVgAP2tmehx/fk2S1/Qi9E99TKE43lIWl6DY5+NMGBNFEMI2U9dCNObad628l0bzACJpxpkU46wLlQRs/83WPvGdX8KaVGlwtOm3k4ccPJHET2/RtDTjzB86hRigLS6HoCZSFpeg2TcKFfPyBno1jSSy7aXxJKnXCDTfaOEfm8Chre+y9HKHJxp/Jg0yweG4SK2ckOwlmD4G8zlAlVgpFD6IsLMUxkUUASVSRSgVr6ZlMQUM7wRrBYS6Q+5lAkd4Vw8SjjCUPf95lUYfn/I1ohnMYbzrvRt+AMx+Txtek0CKceVSuZjyH2E4IYdQTQT0v86u+/6sM1cVqMfE8z0iHW1gpFArHUYKlOCYcTbxIkpVEUccqoqCTm3l7wTJPwMjFj0StS/pDjGedKZ2+kxDaJIqoxHIi8AbCGaUlS6wlkjYElXjwCQP0Dh6j5SHGc4hWBC8znDPJ50r26ueowZW/KrFSKI4LSrAUx8ReLfFiMEcIlI1UCA+rfUbKYh5lDW4Y+Ip+vCEzbIqWt2xmCoU2M+6+JZnFJJCNPz/wLW4YLFoh7SaIdMo7XGuAWReMnQTzdybyOKsZSzFBNHIbUy0a1rrKNm5mKwBfkcIB4YdvuxlXpjiWEiuFovdRMazTnKnyADfIbZwlc0mRFbjJts4PMmMvQewlEC9auZ4dVq+bixXAxeznRrZZZBV6yFbelov4lu/5G5ttvs+HpJMlAomkTj/XHLJJ1gYxvsRwi/03Edbhuj8gHYTgJUZQgyv9qeBS9lnsczl7iaKOUjz5mDQAvqWfzfOlUsEM8jp8T4VCcWwoC+s05kKZZZHVBtAGFEpfcvAnhwDtX39jarYN60EKwStyGP9iGTPJZ6FMZJcIASzFahVRbCac29jCxVrd039kBolUcitbbRYFm/MQ6/i7nGix3kvIYha53C8nkSmCdbfgDoK5T0zW13AzWy16D+4kmC2aoJUJT16XQ7mXDfwfu1knI8kX/kTIOq5gDwBvMoQGraNKPn4U4UO02fnagASquYtNNEtnlou4zi69QqHoBqo10ynEbJnNVAoc2neI2UwpMGbCNeJit/N5NW66eJnELA8/vbntPLmJc8klG39uYjrDKbEQq38wllbhxCyZwx2aFdWAM544btFV4K6PHQEowIdYaqnDhfuZxL9Yrr82Q1yi/+wq2xjHQfLxYwAVbCTcsvehlLprcA+B3Mo0HmUN4znEFkK5h8m6WKfKcr2N08sMYyFJeNHC/7GbC9lPI87MYyrZasyIBUNlCWeRx0ekUSR8+3o5ihMINV7kNOUcckmx0/S1M9wxkI0PHxBHMd4kUkUiVSRRRRw1+NHMUEoZatY4tg1BofQhhwCOYIxdJVPF46xhKCVWYgXwk0gCCXewGU/aqMOFnYToM7JGUcy1drpcmIvVC4xgObE8zmqGUspT/Gb3s7UIZ1YSC6Cn4ZsjONqNIokqJlOkJ1q8yjALy/Is8gHjNOMfhbGdUy1uvCEziKaW0RQznzXcLKdTrVLaQUouIYvr2Y4zkEkQRSjBUnQPJVinEE8yhjvZqM9+akXwJalkaYkRABeSpb9eiA/vMpCRHGY6B0innHTKKcKHL0nhRUbQJFxwlW3EUU2yJmLJVJJEFf40E08N8e3ceaO16cDtxcrETyKJLBmIE5L9BGAQTjhLA6lU2BWrI3jwCWncxhYA/GniJZZzEB8Ah9LVbSGk5HY2cxb5tAHPM5I/msXi/slK3dXohkEfX7KLYIvzGITgKTmaV/mFaOp4gN+5X07s9tThsfIg/8duviKFX0R8t87R17jLVu5gE9M0q78JJ34jpo9XpTiZUS7BUwwhJWeTx5/Zji8ttAHf0Y/3GMjZ5OkxoE8YwLsM1K2HQNnIHPZzHtn6dN5K3PieZL6nH1XtrQUpCaZRF7BEquhHpYV4zeIiK7Ey4SINpFBBBqVkUGq3F99PJPAt/cgRAUyWBTzE7w5dh47e24RJrM4llzbgWUaxlig+48dOXZWvMpTvhHUCRoKs4l8sw5M2viCF/4gMh9bbnpvkVi7UYn33MZFNx9Lt3fQnfhwzGCNkHfNZQzJV+rYvSeHNbl4PxamLGi+iIEA2cgPbOVMbpmhOKZ78mwy2E2olRB6ylbPI42L2EUk9YPxmvIQEviSl0/jDIFnKi6zQn9/DJLaIcN2CyqCU69jZaXrqzyTwXwbrbjU/2cRX/KC/XocLmwhnMrb7CP6ZGeQJG+4/KQmmgRhqeZaVnaziKMuIJYNSgmkE4BWG8n07wRohi7mXDRauyycZ3a0kjAhZx4f8pD/vrmg5ScmLLMeHFh5nrM1r0tMMk4d5kN8thmk24cQ1nGOz7EFxeqMES6EzXB7mNjYTTZ3N13Px0+NHmwmnXrueTtLARIq4jH3014qCDcAaoviCVHZrmYC2MCVgmNhIOAM5YtNqWUUUEzlotf0azqZY+OAkJWeTy5/YaXEDvIdJVODBn9nOaBvW2c1Mw4NWoqm1eERSh0cXEj1MVOKGL82Y5if/RALfkUwuARgwptibCojbcyPTyRaBVts743a5idnadWxB8BRj+E10zaU2RJbwvCbMdbjwJGNYLyK7vBaHkJJL2Mf17MAZY41eII2E0aCsK4VdlGApLHCTbfyBTK7S0rTtUY479zLZ8lu4lAzmCJeyj3Ec0jfvIogv6c8aoqyKZdtbQ/a4m8l408J81lKHC/OYyn9Zor9+C9O4lS26YPYmlbjxJanMJocI6qnDhbuZQgtOFmvqjDpc2EgE4zhoMcn4BUbwEwldcssFywY+YYGFNfoWg/hcDHD4HLfKLZxPNk044Y4BA/AfhvAVKT3qImwfr1pEPKuJ5jHWKOtK0SFKsBQ2iZdVzGOznnRxGC+WEYsHxrTvCOqpwJ172ouWRpys5hL2MZ0D+s3YlKCxhHiaxNEcngXya32fr+jHXoK4g026dfMTCbzICP7NUpKp4mMG8J4YxBL5pc21f0kK8VTTz0YWpLkLzpwK3MkigCJ8OYg3RfhwEB+CaOQmtpGLHyuIYTPhenq+v2ziSwfEtjvk4sd7DGSNA+2pTPxZbueydgXNAO+TzkISKRf2O+Q7Scmn/EgQTTzMeMZwSLd8fyKBfzG80zifI5jHq1oRvEEG35HMSyxnIOXKulJ0iBIshV2E5mL7Mzv0pIzv6ccXpDKfNaRS2aFogWMJGrfLzcwmBzC2VTqDAovWSDczjVAadOvqGmZRI9wJkI18wY9217+dECpxpwIPyvGgDcH17LS57yWcZ50s0gnuspUf+bZLx4DR4jyED3FUE0dNh27H/QTwIWmdCleIrOc5Vth154LxOu4j0OZ5TO7Aaly5nPNoRXAh+7mBbThjvJaPMu6Y0u9jZA3PsYJgGqnAnccZyw4RyghZzNOsUtaVolOUYCk6JUA2ciPbmK65cErx5FdiuJQsfZ9K3PRGtIfw4UEmUCuONpA1JWjcovXbM/EjSawlkn+w2u771+FCMd4W1pWJD+RCPeHjWFlJNBV4UIE7TXoECupwZTlxNIp2lR1SsoSvHD7/Ybx4iPHkmhUKO0kDV7CXYZSwjVCiqSWMetoQDDOrYwO4k8mcQSFbCWOlWXzKllg9x0hGcNhmcXgjzqwlkiwC9SjaSA4zghJ+JoHnxUh935GymAdZhzetHMKbhxhPfjeSMczFKhc/HmCisWmwlMq6UjiMEiyFw4yQxdzGFqI6+BZvYi2RPCws50BFylo+4Gerfd8nHV+a7Y6fN2FuXYHxJjiTPGaSr2fkAVbtkHqCrYRyH5Noa+cWi5dVvOVA3KoMD27kTCrbWQ8m68KcVxnKTPI7nBv2CQN4VwyyEKsWBK5ImnHiUs6jXrhaJGM4wt+ZwIZ2iRZxsprHWU0Udd1KxmgvVnczRbdmlXWl6Aqq04XCYTaJCP4sZ3IhWXo/P1+aLRIsTPyHIfrPnrKF88m2GV8BGEgZjzHWQrCacbJIRABjM9k2nDhH5jCTPAba6Li+l0C7iRfluLOYBDYTxl/Zpo8eMfEuA3GjjUCacNHeWyCZwEGGUspf2M6/GQrAJFnIcErsrrU9wTRyKftYKuPIFQH4yybiqSbRrPbIRHsr1MQzjOQeNgJwFXsIkQ0M5AjRmpDsJYjhlFCBB3PYzyhZzGAtBukI9VoSSHsOCD9ukdN4hLVkcITHWc1/ZMfJGO6ylSSqmEqBXiPWXqyQkmu04u8fSFZipehRlIWl6BImobqUfXb7DppYTwQpVOhJER+Qxv+RabFPDv5EU2M1mNHEToL11lAd8SLD+YlEJlHE1ezWhasGV74mhW/oR52ZO3OCLGK+Nrn4n4xiJ8G8xyKbaem9zTJi9ey6rpCHH6+TwU5CaBHOuMtWRlPMZAoZwyG9jOBKzuGINt+rPS7SwC1ssUrGcMagD+ZMoYIUKomn2ur6tI8TOkkDi/gaMGZ57hVBXf5citML5RJU9Arj5EHuZKMuVIX48Dn9+Svb8DJrjbSWSIZz2EqEsgjocq/DRxlLNe5cwR6qcWMsh2y2YTIvFBZS2hSulxjOShGrHzNX7uRq9tCEEwX42cxAPFFowJkthLGZcN1au4pz9EGT7blI7uOvbCcfX65nZsdZiVJaJGOU444/zZ2K921MNXbJb8dT8jdGcpiFJPKiGOHoR1ScpnRFsNQ8LIXDTOWALlbbCeEvzMAFg4VYAWRQyjOMsjq+O415LyKLStw5jDcTOGi3Z2C6mZtMCsFKEcMNzOBxxpKLH760cBtbcJZHRfQDBrKOCNwx9KpYleDJhZzPVZzDZ/Tv0rFfksI9TOJizucRMUEfi1KPC6XYTmkXUnK+nqHZr/MUeiH4RqTwIBOpw4UgmnBGUo47vxPBR6TxMOP5iKP1X2uJtClWAB9qs8NmkkeE7Dw2qlA4iophKRzmDTLwxuh2GsIR/sVyixu9KUHAi1auYxetCFyO0cU2mDLeZnGn+9XgZrVNCsFKYlglo/iMBQTSRAalbCZcf/1pOZpv+d7uedcTwSIScELygIN9DNsTRgPfdPAeHXEJWYyimDs5gyqcSdAsxnx87QrRSIqJppZaXFmK441zN4oIrpNnk0wlefhZzUAbKI+OpPk39jP/dosQNspwRnKYy9nDyygrS9EzKAvrdOIYvb/lwpMHmMBzjKQWVyurxNVMnGKoPWaxcoRKTaju53fGSesWTwAG4cRqogGYQiFgtEKcHLgeYdSTRhnudiy7UjxZSCIfM4AirXM8GOuyXmt3U29FkI0/P5HAywzjLiazQRPPjoinhmGU4CQlcbpg2U9Dv0BLiPiZBOu0/U6oEB5sFBHGmFc7QdykrXUx8RwSPrYO1/ke4+iVdBtJNApFd1ExrNOECbKIW9nCywxnrYg65vOFyno+YaHFtmrcOk2O6Cl+IIk3yKAVwX1sYCoFtCB4nHE2P595kkU2/iRQZVaV1T2eYwQTKWIwR8gmgGwCGEAZaVpGYyuCXQSToQ3LfIyxR3sBSskbWpcPR6nDBRcMemwwG38iqeNz+vOJMLrhYmQN77IIAzBX68fYkwTJBsrx6NTNOEwe5hl+Iwd/bhAzenQNilMLldausCBYNnAnG/GlhREcZi3HLli2XHA9KVY/kEQMNVaFtmDM6lsq4gmQjVTiztNavGwqBTzEWh6X49hCGBmUaONLjljUP9kSiRXE6NaXLQ7jRXi7YuZzySVNsyCGcMRqirMLUhcrgJvZyhYZphdfx7abI9YZ7eN3ps8RYNaa6nyyAfidyB4XK6DDVlAKRW+jBOtUR5v55Ku1UOop3LrR8bwrnKclDdjiXjZwr9wAGNPen2OkhWg9xpouvdc8zmBOuwLnVgT3Mol/sBoP2lhOLFsJtSgINonVjySxmyA9BTyZKputmYJp5B42sEZGMZlCizqvCtzt9kS0hSk+WIE7H2lJDl6yhbPIA+AbrGd19QUx1HCvXM9KYtho1rNRoegOSrBOcc7kgM0i4GPlHK1u5wC+3MNkPmPBMZ/zBYYzkSKrcSGNONvtzTeIMt5kCe8wiGcYRRS1Xe7uHkATUzXr6k2GMILDHMSb7SKMd+QgbmIbyVSyiAQMWAZ+63HhXQZSLdxZQgJgrEWKo0avX0qnTF/TOA7Z/P/oTKxWEcXLDNf7LDpp8cF/MVzvBTiTPLxoJR9fPZuwr8gmgEJ8iKGWMznAmRygDhfWyiiWEcsGIo7rQEnFqYGKYZ3CBMsG/stifGmhHHeCaOI7knlVDDum83rKFj7iJ/xo5ilGs0zEcYfcyCzt231PspQ4XmQEF5Jlt8mtCdNnPFb+Ryq+NBNMI6Mp7nDfT+nPO2Jwh/tcK3fyh05GuwC8Rzo5BJCLP2HUcxFZjOOgLpBFeFv0FlxOLE+KMYAxieRdFhFNLS8zjB9Fcqfv19sIKUmnjMkUMokiQmnQX3uI8azrgViq4uRHxbAUFq7AvQSyifBO52GZHzuaYorx5oA4+gsULWsYxyHCqMePZgrw4VeMhbgfkN4rguVHM8E08DUpRFJHG4IvSKUSD65kD5eyV89O7AmxAuy2m2pBUIEH+fixhTCSqOJzB+qqthDGHLLxseGWfZlh3M4WDuPFp6Tps8WK8WY7oUTJWi4ki7PIs+rabqp3gu6nsvcmUgh2EcIuQnhDZpBGGfPYTCLVBJn1iVQoHEUJ1imKyRXYjBPPMrLDhIL2pFGud1pvk4KNhDPGhqXxEen6DbYr5++IelwwIPSb+2iK+YCfKcGT7dpkZIHRTfiuGMRiGc8/WNXhCI6usJooyvCkDA/K8GAUh5lCIZkEcTtTkd1wY20TYVwnz+I1fiHMzMrYQihLiec6dhJOPSMoZgOWDWgPCh9eYxjvy4FcwH7man36AP7NUpbIBL6m3zGlsh8PpBDsJoQi6WPV71GhcJQT7zdbccwEywZu0tr3fEi6cXSENArKEEr5k9zBYuIpEO3Mbym5iCwmU6RvckbaFKt3GEgzTpwrc/CglRvZ3q21luBpcRM3dc1oQ1i0BgqjQY+FmI7bIUPwpbnHxOpdBurp4TrSKMaVuHdLrExUCg+ukbP0PnsAwyjleX4lD3+GcIRzybUSLBO1wo2PSKdMejCdA3jSSiqVzCZHnztm4Gj9k0JxKqIE61SjnSvwf6QCUI8x1pdINYlUcxl7WS5j+Zg0XbhCaeCvDgqPNy08wrpjXq65WJlYSTT/YjiXsI9L2GdRgLyPQBKpJIwGfZZXT1FtI1W/JzEIJ36USbrA1OFCqlnx9VgOESwbKOsgdfwnkcRPJIGUDOYIF5vFuX4nstOCXoXiZEYJ1ilGe1egQZv1tJBEQOJNC0lUMZ5DTKeAqRRYCNePMtGhWUuX24nzmNhBMP2o1DuGd4VGrUD2bTGYJTKem9mqj/3wpZmnGY0vLcxjc5fPbY8sAviRpB47nz1WEs1scqjHhSJ8LATLGeM06I9J7/xEQrCDUHZoca5RFOvxRIXiVEUJ1imETVegRr1w5UuzBIFkWcHVZDKRgxbC9QlpCNDHTXSVBpy5n0nMY3O3xApgJvnMJB+kscnuywwngSpuZDuR1PFQJz39bmEar7KsS+9ZhytXk8l2GUomQb1WL7SNUErxJJQGC7EyEdkN9+ZB4cN3J0jdlULRm6i09lMFKXmMNYzjEHsJ5Dam6tZVR5gLlzlZWnr1TPIdXsImwgijntgengxsohZXq0y7lxjOIbypxZW/8zvR1HEIb8Kp63ajzGacKMULibEnoolCuu9ua8CF5xlJtghgkCzlH6zW43V7CeQZRhFMA/sItJjbdarxiFzDRA7yIsNZKHrfolWc+Ki09tMQe67AzsgWgTzKeJJlBW/wi749hcoujwMZobntusoKYniBEXzHdx3uZystPJBGFmg3vrvkFH20vD3eJ516XDqM1blhINqG6MYcoxDfx3q+kf24nh140UozTnxIOv8jFYNw4gAd/7EqFKc7SrBOATpyBTpKtgikq83VHRkj7whTKLRKi3+OkYRSz4Xs77BHoSetehf6OGqsOsRvIoxXGEYbTlThRoNmkW+W4XibCeAwSriYLAtR/IZ+eNHCWeRTjSsPM8Hq/eexWR/50RkJVPM3s7ibGwauYyfXspPvZD/+LYY6dB6F4nRFCdbJjp2swK7iLbveuHYHId22qjrjLjba3H4AX+5kCpMo4ja2cBn78KOZWGoYaDbEEYxZeA8wkTYb1mZeO1HfRQjfyH5cyH5duC5kPw1aT/ddhLBLhFid57D0cliwbGFaWVi7xroKhcIaNQ/rJKe7rsD2dKffYG+JlYl6XMgkSH+ehx93MoVK4cEPIpl/YWwxdTZ5DKSMJpz4in5czrnM5GIu4nybYmWPOuHGRyKdq5nF+6RTi2uniSOPMo73SacV+zVaZXiwzCyDrxI3HmAC9dr3xX0E8jwjHV6nQnG6oiysk5gOXYFSEk81tbh1WNdj4sJ23crBunddb9CAs11ReI+B/IkdAOTixz1MplJ46K//IJJplYI/sIdVRPE/+luMv5AdiEhH1GlFuiaLayb5rLEzkqVFOPMR6Xwu+3M2eZxPNm0IthLKNsLYSQg1WhLFa3Iob7GYQJp4jNU4YxSre5mkjxxRKBT2UYJ1EnM5e/Glhf0E6K5AH9nMmeRzDrl6C5xdMpgVxPAb0cZJsu0IlI0W86JMdEesbucMMgnmn6y0OcuqPR1ZMDexDYB1RPAUY6i3kRGqF9L2Aibh+siBuqgW4cwPJPNDB50mqoU7L8vhzGftaSlW3rKZOG0GWHe/TChOb5Rg9SAespVJFNodhdFdDuHNVsJobefeMqVZ+9HEEI4wQ+YzhQJ9Im0zTrhgYCBlDKSMm9hGnvTDgGA9EewiGBcMPdKxwsRM8inCl/cZSAuZJFBts5uFo/yPVN5msN6z0B4BspE57KcadzYSzmG8aTbVUknJSA5zAF9KhHe319ITrBbRvCUHEUcN/yZDFytv2cxYDump7o7ghKQVJ9YSecIPVvSWzTzNb8RRQxVurCeir5ekOAlRdVg9yFUyk+vY1SvnrsaVNUSzkmi2EE6rcCJINvC5jTlUOfizgER+IQ4P2phEIZMpZCBlDgctX2C43dlNx5NdBPEZA/idyA57+d0uN9ns0FGDK/W46tOC72cixXhzGK++HyYoJWmUcy45TDmGLzrLiOUpbczIiYhJrAZQQRVu3M1kckVAXy9LcYLQlTosJVg9yF/lVi5iPwfwJa+HamqcMM4UMh+dUY0rewgig1LdmgL4hVi+o58xUcHGzT1YNjg0aLEaNy7lPAxCIKRkEoXMZbfuzukpvqIfHzCQflQyh/0WTXftYW+O0gBZxiss7/ZaviCFtxjSqSXXE3jJFt1taxpzD8akkgP4WuybRBUx1LKaKNrM3Gjm1+pBxvP7CTpbSomVojNU4XAfs4po3hWDeux8TlIyiFKmUMRECgmiSZ/Ka5rqCrCTEDJFsN3zlAlPq1qrMjwIpNHC8tpEuH7jlkKwklh+kzFMopBrNDefLT4kjRK8GMyRTjtk/JkZemp5oGxkjGbJ5eLHmwxhDMU2E0H+zA7WmSVAOElJMpUMooy1RDKCw92qDbuULH4msfeKd6VkAOWcSy5nUKBbU004sYJYFpLILoKtvmh8Io1fMArw5W1tUKSvbNIFK4sA9pplUp5IKLFS9DRKsE4CDEKwnTC2E8ZrciiDOMIAytlOCHsIYg7Z3MJWrmQPi2RCh66unQQzyKxeKYAmthBGAy56e6bNNsarOyEpwpdv6GdR/GrONWQ69HkeZjx5wh8hJdewWz/OPLliExG8zlDAaJGcQw6jKeZ9BgIQI2v4EzsYSqlVB4w6XNhOKAfwxRUD/SlnIOX665+Tii8thFNHBPWEU8e7DLKybnqKVFnOHWyysKZM5BCAD81cxl7jBrMvFG046VN6r2AvP8okSvGiRrjzlhzE9ewkhUq+4Ecel2NYKU6c5rdKrBS9QZcFa+XKlTz77LNs2rSJQ4cO8c0333DBBRfor0spefTRR/nPf/5DRUUFY8aM4bXXXmPgwIH6Pk1NTdx11118+umnNDQ0MH36dF5//XViYmJ65EOdyhjFK5TthOrbFspErmQPYTRwFnn82EGm2mG8GEQZy4jFmxbGUGxVT1WOB8myklQqSNEeSVQdc1eLu5jMNmEUQ3fZyj1s0C2FjpIrTI17Tc17x8mD3Mt6vLUEBZNAmQY8ZhNgdZ7JspCHWEc2/rwlhhzT5+gqUymwKVZgHJbpKB/xE804USyNvRPNeYjfWSkLeYVhFqn/fYESK0Vv0WXBqqurIyMjg+uuu46LL77Y6vVnnnmGF154gffee4/U1FSeeOIJZsyYwd69e/H1NX6DnTdvHj/88AOfffYZwcHB3HnnncyePZtNmzbh7Nw3gfBA2cgQSsmglCQq+YwBrBNRTJYFPMTv1ODKSwxnK2FUC/c+WaM9WoQzn8oBupW1UCZ2WkC8hyC+ESn0l+Vcw26LIY2macP2yMaf1xlKII082EnndBNF+HALW3ULwpdmgmmkBcHLjGCRSOj0HEJK/kCmPnV3OyG8yRD2E9hp7Gk7xi4VyVThK5uoOY7/h5/Tn1EUE98DMUA3DHZjiZMpYgil3C6ncbCP5mIpsVL0Jl0WrFmzZjFr1iybr0kpeemll3jggQe46KKLAHj//fcJDw/nk08+4YYbbqCqqoq3336bDz/8kDPPPBOAjz76iNjYWJYuXcpZZ511DB/HccwFKoNSq5vAXWzkOnk2QzgCgC8t+liLfOnLZsK1b/UhfS5gTtLAQG2d/jThQRv1DuYD7hVBPMhEPpA/WYy2qMWVLALYRyBZBFKCF8+wEg/aeJeBbBehCCnJJMshK8FWM9lK3JjPeJstj9rjJVu4l/WM12Jd35LMG2Q43MmiUniQK/1IpJohHGE10Q4d1xNUCg/ullN4lhXEU0MJntzFFA7hTQgNJFBNvNkjkSqb9WkbCec9BlqMTmk/mTmAZpKo5OAxdJbvLkqsFL1Nj8awcnNzKS4uZubMmfo2d3d3pkyZwpo1a7jhhhvYtGkTLS0tFvtERUUxaNAg1qxZY1OwmpqaaGoyy5Kr7n7vNoAb5DYuIctimwHIJoBthOrfhq9lJ/9hCP2otOhTF08N8dToSQE50p9thDKpXQPX44GTNHAf65lKIS0I/sFYmwW27fE1bygrJT5mz6tw4xLOs0gAuF5ux4M29hHIXoK4W26wm1hxF5P5G5uJppZNhPEJA2zut59Ah9YaK6uZz1riqKEZJ15mOIsdsMjMcZEGyvHQBKv0uAoWQEU70XqWlVzPTI4IL47gxUatLilWVvMOi22eYySHidW+WB3Bg7uYQpHw5UKZpRdZ38dENhFu8/g4Wc055DCNAovGvyZqcOM+Jln1WXSUB/idAVoBui/NRmGVRlH9gHS+FP07OYNC0TE9KljFxUa3Uni45R9MeHg4+fn5+j5ubm4EBgZa7WM6vj1PPfUUjz76aI+tM7RdIWsJnrzACDYJ401jrYzieVYwmxx+JpF5YioespU57Od6dlqdL4kqksxiFFexB0/ZqsdUanqpk0F7sXqccaztJL05mwCmU8CV7CFH+rNKxIAQHJbe+GrjRNYTYSFW/rKJOWQDkEoFX/Bjh+9xH+vZSATR1BqtUGGdxOEo5vGqUjyZzzj2ia5lxQ2Th7mFrboVXUXfWMQm0XqTJYRTzy1soUD6Ek0tUdSSTJXNESrmhFNvIVYA39GPyRQyiDIuY5+FYLlJYx3eueQwuF1z4PYE08gf2WmzK70jmBc9O4FFzPN6drJVhrFfBNo4UqFwjF7JEhTt4glSSqtt7elon/vvv5877rhDf15dXU1sbPczop5mNKuJ4gL2k045YTTwNKvYLYP4ln78Rgy/EMt0CriVLdwup9IoXPicAXwn+zGH/VzKPvw1q6QKN3xosXDNXMh+vdv3X+RMinu4w0J3xArgK1JJooozOcAD/M4/JKwSMdzMNIJoRCIo42jQPkA28g6L7Ba1fkp/9hHIEI7oFmcIjZxN3jF9PlvxqscZ26WEglBZzw1s10eXlOPOfxnCUuKOaW3HQgXuBGo1dWc5MBxzObFkEqRbUO3FCoyJOM/JkbzBUoZTwiSKyJd+nEMOM8jHTxPBNgRriWQhieRiaUWF0sCLLGcch0iRFWR1Q1ju4AyCbHQ1+SvbmEwRd7ORm+V0q44tCoWj9KhgRUQYLZTi4mIiIyP17SUlJbrVFRERQXNzMxUVFRZWVklJCePHj7d5Xnd3d9zde+5bcatwYjlxLCeO/rKcC9jPFApIp5x01lPGdtZqtT5plHMWefxMIgCNwoX1MoIzKNQFaxEJnEEBYTTwEQPIIYAMSplIEcE0Mo0DfEJaj62/u2IFxpvbs3IUgJVoHeFon8FBspQ5ZDOBIlzbFW+9ylAWkGRx41lFDJ/KAbzEcoJopAUnfDuxFuzhI5u5mw3djle5SAMXs48/kIknbbRhtELeZ2CHLkhv2Uw/s6GVEkEmQT3aEaN9DdtS4ijCh5nkEdluxMhTjGYzYTzDSsC2WJkoEr6slDHMJJ+72WARAzuMFwtJZBEJdhshH8GLZTKOGRzgGnbbtbLiZDXF5m2vzDAIYfE7ZOJfcjiDOUISVfyBTL00QaHoKj0qWImJiURERLBkyRKGDTOOfmhubmbFihX885//BGDEiBG4urqyZMkSLrvsMgAOHTrEzp07eeaZZ3pyOQ6xVwTxT0bzHzmEc8lhNjkE08hscvR97mQTq2U09bhwBXv4A5m4IqnGjVcZigHBZeyjDA8+IY0W4cxvxJAlA7mLjUymsMcE61jEykRHogXQT1bwPCss0jZ+JJH/MqTDG36F8GAuxoScv8lNnGOjVZL9zyUZSgkzyWMiRbhj6Fa8arg8zM1m7r8dBPMKwxwK/r/McqtMvtVEMR/bX6S6g/mgyjaM4j+GYiuxWkiiLlaJVHcoViZatP8xc7H6mn68SYbdLMpQWa8nHmVozYrHcYgA2WhlzY6TB3mMNZThweeyPwtIsilc7akS7rwih/Ew67iSPayWUco1qOgWXRas2tpa9u8/2oEgNzeXrVu3EhQURFxcHPPmzePJJ58kJSWFlJQUnnzySby8vLjqqqsA8Pf3509/+hN33nknwcHBBAUFcddddzF48GA9a7AvqBAefEQ6n8kBTKJQdxea+JrvySJAHxu/miheZjgVwoM50ng9dhJi8W18DVG0IkimihhZQ6HZzcZJSiZQZJHsYKIGNzYQQZPQ/nukZDBHiKGG0RQzkYPdFisTtkVLsEpEcwRPMgm2SDSZTS4TKWKjjGADEWwkvEeyI6NlDTPJ50zyLZrk5uLHc4x0OF5lGrViquuycP852G4pQsuSLMIHL1oIpMk40binkJLJZoLlDFzKPi5ln8VuOfjzMQO6JFYAy4gjjmqLWNVF7GcA5Xwo09lIOKE0WAhUZLuO/G0IfieCeqy/mJiGTAbTyE1s43L28r1MpgJ3DuPNZmE72QMp2UGIXrSuXIOK7tJlwdq4cSNTp07Vn5tiS3PnzuW9997jnnvuoaGhgZtuukkvHF68eLFegwXw4osv4uLiwmWXXaYXDr/33nt9VoNljrm7MFWW8zDr9MapKVTqVtVyYq1uhO2bMtYINzbLcEZTbGVljeMgD3fQJb0OF1bKGBaRQD8qjTVMGt0WKykJo55UKkmlnBQqSdGyulyQ3MZmVskoKoUH85hKsGxgFMWMopgRHCaAZs7kAGdyAAOwVwaxHqOA7SOww+a05njJFqZQwFnkW4hiDa4sJ45FxLOPQIeFJkzW8RwriKTeYfdfR9zNZC4ki0vJIr8HWzUlUK1nOq4miqkU8gf2WOzTgDOvMJQnWN0lsQLYLkK5g6kMlEd4iV/17emU8xSrbB7ThmAfgWzTEoR2EUxDJ9etEB9cMBBBvUWz5zflEJq17hwhNBBGPSHaz+YJGElUMYpi3e2uUDhKlwXrjDPOoKN+uUII5s+fz/z58+3u4+HhwSuvvMIrr7zS1bc/ruwTQVzNOTwjV+iznf7CDMrwYDKFHJGe7BYheHTwLXwlMYymmKkU8KVM1V0oBzmahLGZMBo5KtaJVBNJHbPIY5ZZ8sJBvNlPAD+SxBZ732bbESermUoBAygnhQo97taebPxZRIKFSJQJT34mkZ9JxFkax5SYBCyZKtIoJ41y5rKbStzYKCP4jP6WgyQ1bLn8wOgW20gEi0lgLZFdjheZi1URPjzGWHJ6oPYnXos12RIsT9nCWA6RSFWXpjqZvhxsJJwthDHVRhlELW7czhYSuihW5tTQeVbqfgJ4h4EcxpvRFPMrMTZnpdnCnTZK8CSinRvzBrbbPcYAVOBBKZ4cwI+d2O95qVDYQ/USdICnGc17/IwnbQTQxOXs1TPiiuTRqbzNWN9sVxPFbTiRQDUf8JPu+8/FnwJ8iKWWn0lguTiauSakZBBH+AOZFm2ToqijGG+CaMRdth51GbbDVzZzBgXMJE+vi+mMXYTwDf3svt4mnPT2R28zWLe+RlPMcDPraxglXC+P1tiFUc91cqeVyy8PPxYTzy/EdXuWU3uxupMpDk1XdgRTcoSp675JpCZTyCiKLbrkd5WVxOhlAu0JpYFQGrotVt6ymX9qSRomMgmiAF/6U67H6PpRyV1s1KcAXM1u/i0zrL60mNOg3S5Ma2zPHgI5gieleFFq9u8RPCnDU7kAFceMEiwHKBeeVEgPPKnjbjZY9IWLpg4DsJYoPraRWFEr3HhCjuUmthJBve77/5z+rCOSWLKYTCHLzVKtpRDskUEWxZ2ZBJFGOcMpYTgl1LFFdxnuIhgnjEMKZ5LPOA463PdvE2EMo4TztRvoK3KoQ644W9bXPDYRSy1/ZRutWgLAuWaJF9W48ms3XH7meMhWfuBblhLHQI70ilh506KLaxJVXCL3WYlUIT5sIlxPdHCUcjyIodZmd5AfSKIJZxpx5icSuzVs8q9sI4RG/XkbcCdTdMs1UDZyGXu5hCyLkTXetHIXm5hMIS/KETatrZXE4K8d44QxHpdKJVW4cRXnOpSAoVAcC0qwHCRKs6JsNTF9gwy+ESl2j10rotggI5hBHlexRxeuFs2hNJpivGTL0ZiLlNzOZgZQQTVu3Mx0ioU34bKOGeQzk3ybLsOu8BaD+FwYO1CcJfO4g41dFi0TJuvrWTmKF1nOTPLJ1zqfH6vLrz1XaDGfMzkA0ONiBcbCbxO3sUX/uRAfVhLDSmLIxr9bggvwmTQWXpfgSRgNNODMzUynQHQvXuYlWxjEEf7MDqu0eWeMXSfKMV6fCuHBdzKZ88m2+aVmNIf5lIW8KQfzJamWBeQ0ITFmOppb7h+RpsRKcVxQgtUBQkpGUcwFNuYyAXxDP61AOIsFsuMU31bhxE8ksUQmWAgXGDsCjOGQbmXNIZuzyKcNeIIxetHxYeHNR6TznUzmVrbYjIEAvMkQLiKLUBr4mAF40cr57NcdliuJ1sUKMDaelRyTaAFkimC+kqlcxj5CaeBlhrGGqB4d327eTaE3xAqM3dVN9JRImeOqCYXJinuZ4d0SKz/ZxEOsYzClVs7oInzYRigriLG4/hGyludYiRsGDuDLk4xmjJYUZP5l7AZ2MIMDPCzHM4lCK5FqA3YQylLijG5EheI4oATLBl6yhbPIYw7ZVk1bvyOZWeTihoEthDGBIiKp5wr28IEDBZH2hMuUuDFYlnKj1tXgLYboyRVO0uCwy888+D2QMoZqCSMmPiDd6pieEq33GchYDhFHDWmU86OwP+qkO5SYFab2tFgdwVOPR4Kxu8adTOkRkbLHTyTwi4jv1rEpVFj93wJcy1k2Y18msQqnngP4cjeTKReeZBPIJ6QRLWuYSoHeXSSJKj7iJ/14k0itIIZVRPf5GBPF6YcSrHYky0qe51d91lItrvxEApdqzXJ/IY42BBexn8vYyxtk8DDruJy9LJXxVmMdhJQ8w0oMCO5jkp76bS5ccVSTgz+hsp6HWIcLkuXEsp4IZstsvWYm0CzmsJ8AFhPPMuKo0uqhImQtV5Np0fJnKKU04swugvUEjle0pqS2MEVkzieb88mmQTru6mnDiYUk8jwjeIFfmUk+v8lomyPto2UN55DLVAps1qK15yA+fE5/CrQu5Pn49rhlNY+p+NHMDWxjNIdZ1oUaru6Qix+vaUMqu0NJu64SBoztkWyJlYs08Ay/6SUaEdTxHj/b/T0woURKcSKhBKsd8VTjTSsNOPMmGfxCHI3ChQnyoB7H+pz+nEsOgyjjQ9LZRBgjKOEmtvKgnGBxk/sDmfq3YCckbe0SoVuFEzkE4CbbeIS1uiiN5pCFawqM4zh+IY4lJJBtI3W7BC/2EWghWHn48QRjiKVGFyxboyvs0ZV9oY3L2IcXLXxDCpeQxTw2c70MoVa44SrbGM9BziVHLxNwlGSq+DvrqdEKWptsZGR2G61Mo1J4UIkHCdIyQ7Cn2Usg/ajkccbazfR0hGK8aQP9StTixn4CbO7rgsGi/KIjC90kUis1kapQIqU4QVCC1Y5dWn2IKwZdrNpTLjxZIJO4iP1cw26eZyT/YTFjKGYch/SCSCGl7l4BOuyFdyl76W8WI/CmlSac2EWIXtS5hyCLc7hI4/j3DEoZQilDKdUb8P6LYSwljiZcMAhBPv5cKmfbbWJr4hp262NDbmMqFTh+sxpKCfPYxGxyWUIchfgQQy1PsIpdMoSZ5BGgWVNtwAYiWKil+HeEE5IzKOBi9umNXHuCaFnDX9iu9yzcKwPxo0mPLR3oJcF6gIm4YjjmRIUW4UyJ9NLbOvnRzGxy+IpUq30bhQvXyFkWVro9anGltpcmDCgUx4ISrHYcFt4USy8iqGcgR9ikzSlqj7mVFUo9X5LKlezlr2xlkwynWTgzgYP6/q924vopx4MK3MnFOFtrL4G04WSRNj2ActxkG2mUM4RSBlJmV4B+JsEqI68zd06yrGSaln33BGPIFF0r7vyZRFqkE/exgRkcoETLTBtIOQO1NO5SPPmZBH4ikVIHC1UBPiGNb2U/LmA/s8lhPZGdH2RGtKwhnTISqeJismwmo5t/YVhLZK+NhZFC2KzZ6w4H8SGSenYQzGDKuJy9/CiTbFpuTcKFYvUnrziJUb+9NthOKBHkk0GpLlgmV7+pt1y58GSljGEGB7iQ/TzJGKZzgEjqOZ/9fCVTeYi1+jkX03Fg/SeRxE8kAcZamVf5xaLQ1h6VuOlzt27V2jd9Sv8up4+7SAN3swEXJL8RzQpiunS8CfMedO3X/wwj+YU4DN0sIK0XrnxCWpcbCc+SOdzB5g73ySSIxcSTjx/5+PX5FGlHKcKXEZSQSTAhNBJJnV0rS6E42VGCZYNthDKTfIaYxVl2E0w0dZxPNpsJJ1FWMlFrtJpFAI3ChU9kGvPYzDQKOISP/i1+OyGd9mcz4SQl9/M7YTRQg6vVsEEDgjz82E4oWwnlAH56Ioe3bCGOGj60kQXYEc7SwFx2kUwVVbjxL4Z1O9mguoO2QEMpZUkXJwUfK3+R2/SEGVvU4sq9TOryUMgThSKtxVc49XzMAO5iU4dWlkJxMqN+o22wjVDA6CLykK00Chc+ZQDTOcAEDjJMHuZvbMaTNjYRxseaQPxGNLeyhRQquZf1+vlCaGCqPMAKYu2OeTBxFZkMo5QGnLmdqV2qz/lUOG55OEsDQylhMkVMpAg/Lbb0CsOOKRNslwhhqwxlKKVU4kYTLnpm2kzyeUsOPm5BfFfZZiFW2wlhObGcTR79qTjpxQqM9VYA0dTyFKP5A3uUlaU4ZVGCZQNbcawC4cdyaZxC/Ay/AXAIb/7BWIJoYLQsZh+BbCWUEZRYZNdFUcff/7+9O4+usjwQMP58BAgBk7BEIAEElwFBFFxqkdaFZVTaal06Ol2sTrWdtiOdHpczVafV1nZsx7GezjhqF6d169RxztGeqbaKdpiIKJUqAm4IsiRKiEQgAUIIyTt/JLnkQhIM3OTmTZ7fOfeQm9zly+WePOf77vu9L3/i87zBQ2EKpYxtM1zTQyWXNQ/SONiTSTvSXqSgaSXcxznmoA8FtvYgk5nO+wyhnr9jDsPZxem8SwMJW7txefr6JIdfhKlMZAv3cxzvk8cPWNRrYgVNn2EBlLCdBhL3stSr+W5ux0qKGM0GJrEl9TnWo0xiTquh5ncxnct5LXUiMTT94W/xa47lESZxAav5DKsYTw03sYQv8Pp+4RoWdnEDS+jHoZ1Muq8DRWoRYyhlLMspOujPlva1PBmZ2sv6Hou5njP4eXJCRh67s1pm9MgL9fyARRxPVa+JFewd2j6YPQyjjvLmKbGGUccUqniFDzervxQDg9WsX2jkMt5gJ/0pZSw7m1+anFbnq5y5z3lR32Ux/ZuHY6ylgCOoThs2/DIjUwMFWka4tQ7XZbzOy2EkWxiUtq7Qg0xpOjfoID9Hah2pj/Fu2pIiXRWpff2Ek7iDhRzNNm6nlOvDGdRkaSBDb40VpA9tn928vD00Hf5cSVGWt07KLIPVbALVfIE3APgKK1Lfb5nv78iwlc/yVtp9+hNYThH3M4XlyUjGhhp+yVOpnw9sdViwrXAdQU1qKffWfs2T7KYfH4RBVDGIKvL4IO3fpq+rGNS09lGS9IhItVae5HN9OJPb+b+sRqs3x6pFy9D2rzZPybWcIm7i44c80bDU0xisZu9QyB+YwLn7zH5+Nus5Iby/32J10BSCa5OzUtfLk3yWhyJOYDPLKWJpG+dwtQ7XmZQxm7K0+eC2MZBCdjOweUXXtp63tZawDWbPfof7nm8ent5dkdrXhqQgLVo/YwFVoencrEHsSa3NtK/vMLPzqym3oV8I3MrzvTpWsHdoO+yNVVsnvEux813dIkn4cTgZYL9otReNYdRxTVjKBgpYRwHbyGUqm4GmRR87WjJ+ZzKA33MUY8J2pvM+zzGG7yWnAU2j24axixGpSy3Dm/8dwa7U163DBj0jUvtqHa0idqWt1dSeC3k7I8unD2IP05r/P27j1F4ZK2g6h+x81hgr9Xq+s1sJScLzoWS/YHWkvfWofsqCdicWDSQ8yxHcy7TUzILvsXexvvokh0qGUEnHC/i1Dhs0zVHXEyK1r0oG8wiT+FobS6gvpyhtaqZNDM7YcOydyQBWhhFMpWq/Wfd7k2c5gnUUsJbCDqf/kmJnsFr5aHiP77SaneJQ5B9gzrsLWU0+uw9pmPeHDVu2HBW28knWMof1qdnv95DwPGN4giNZxsgO90IzoZSxTKWKMyjnMdpfZDNmIUlYzbBsb4bU5QxWs2NDFTfzAgMIVDA47TDgzzieTQzm2ywBmkYEfo/T9nuM/jQyhPr9ZqfY77n4gOtYylw2UJvJWcd7kDlhPd/ipdT19xjCkxzJU0zo1iUqShnL13mVqVQxItRmfEkSSd3HYNF0aO16ljKg+Rje4c2x2kA+t3AaZUkBs8KG1O0fZjLlbaw59GGVk8+ukMM/sqSTy3fEI6/VUhY3cxovUNLle1NtqUryUocFe/NeltQXeMAbuJzX0oaX5wCLKWY+s1OzTcxlb7CWdHKm8LYsSsbyfT663/pYvcVTTEh9LvcXbMlKrAAGhT2pc+pOpSIr2yApM/p8sCaHKi5lVdr37mcKtzCTna0mrG39xy5To7AWJWP5LqfxGiN4LgNTIvUk9UkOP6dpdou/YhUjw44D3CPzTgiV/IwFnMomAJY1zxEpKU59+pDggNDAv/K/qes76M+POLXDc4Ae45iMbsMLSUlGhnD3RIsoYRlNUzRdxQr+iRnd8ryDwh6uZAUXsAaASvK4g1N4OXGaIilmfXoP6995NvX1FnKZz+x2Y/VDPsJjHMNPyc6ceFFKEu5lGo3ALMo5Lmzu8qecGD7gpyxIxaqWHO7kZGMl9QJ9N1ghcATVADQCV3Buh7OjP5uM5+5kuue5dNKaZCh/4EgAvsarJKGdk9My5EpWUsLew495NDCfV7r0OSV1j757SDBJ+GH4KIexmyc4KmuDAvqCX3IcZ1LGJLYwl/UsYEKXPdf9TKGcfAqo4yzKgaah7ZLi16d3FxYm4/hdcrSx6mJbk0GpZe2vZCWDwp4D3OPgvZ4U8W/JiexpfmuvJ58HOrkCs6SeqU8HS93nMY7hPYYwgl1cyptd+lynhfeYywYagH/hFGctl3oJg6Vu0V3D3PPDbv6elwH4bybyZjKiS55HUvczWOo2LcPcc2nkqlZrjmXCwNDArLCBH/AcI9jFevK5n+My+hySsqvvDrpQ90sS7g3TuJtnmEU5vw2beS058Kq4SQhNk2bt+1ljCEzmA85mHbMoS02wW0c/DwVKvZDBUrdakwzlD+FIPsFarmYZ3wizOgzLoLCHH1FKDoH5YTYhSSgKO5nLBs5mHeNaLRtSwWCeZjxPM4FNSc+cwV7SwTNY6na/5Dg+TjnHsJWrWME9TG/3tl9nGVP4AIDzWcOMsJGT2JQ6ll1LDs8xlqcYzwoOd8Sn1IsZLHW7rckgbg8f4VYWcxGrWR4O5/lkzH63Oz2Upy2QeTXLUl+/ShFPM4HnGENtqzkfJfVeBktZ8WJSwn+FiVzCKq5jKWvCUCqaD+PlhXquYgXn807afWrJ4VEmsoDxVCSHZWOzJWWRowSVNf/BVF5nOIdRz028SP/QCMDfsny/WAF8kXk8mBxnrKQ+ymApaxqSfnyfGVQzgGPZwlUsB6CYts/RepTfcWyo6s5NlNSDGCxl1fvJYG7nIwBczGr+JqzkBN4H4LcczSNMTLv9t3ip27dRUs/gZ1jKiIGhgct4nULqDur+W8hlGHV8rnnaplLGcBfTIUlYFYbxOd5kKHUu7yL1YQZLGfEZVvHXvJWxx7uTk1MnCpcm4yhlXMYeW1KcDJYO2eBQz8WsAuB/OIpNDO70Y5zOu0xiCwA38TG2JwMzuo2S4mewdMguYDUF1LOefO7iRBo7efLu4WEnlzTvnf0nk/hTUtwVmykpcgZLhyQ37EntXY1kJw/zBHRyUeEidgHwJsOcsFZSuwyWDslAGhhA0/lTeTSQR8NBP9a9TKMhceCqpLYZLB2SmiSXy8InKGJnu7fJIXAzLzCSWq7lDHbQNJXSSVTylVbLjNzIEr4bTmNVMrzLt1tSfAyWDtm2JJdt5Lb78yvCSkZSSyOwjkKqk1xODJu4nNcAWM1QBtLAEdRwJwv5STiJp5MJ3bPxkqLh8Rd1qVNCBZ9tPrdqJUWpWN3K8+TSyAsU8w1mMZ/ZLKaYgTRyPUu5OrxCTvNUTZIEBktdaESo5R/4U+pNVsrY/WJ1KzOoT3LYmQzgFmZyP1MA+DRr+GdKGRp2Ze8XkNSjGCx1iX6hkRtZwlB2A9AILGIMN7Jkv1i1CEnCQ8kUvs1MdtCfE9jM3TzLpPBBln4LST2JwVKX+CKvcwKbU9dXUkRVkscGCgCoYEi7Kw2/mJRwNXPYQD6HU8uPWcjFYRUjQ9uT4krqGwyWMq7151Ytn0KVMhaAh5gMwCd5hxGhtt3HKE/y0z7X+irLeZjf80B4kuvCS/xlWGfApD7GUYLKqOGtPrd6kdHMoCJ1OBDgFUaykhFMpYpLeYu7md7uY+1MBnBLmMmnWc0sypjEForZSTHrOYf1AGwMg3mZUfyC453OSerl3MNSRp3MptTnVrXN51u1HA4sCHV8iZUczVYAplPZ4WPlhzomU0UtA1hBEa9yOPuOGyxmJ59kLWdRlulfRVIP4x6WMmoRYziPNUxmC7OaI/Iqh/OlsIILWJ2aCWMVQ7mLE8kJjYxmB0dQw1hqGNd8GUtNKnxtqSWHcvIpJ581FLKA8d3y+0nKHoOljKpNBnBDOJ37eJoRzXMEXsYbabdZTz6byeM6llLCdvp3MPlgJXmUkU9Zc5w2NP+7mTxCJyfZlRQ3g6WMyyGkYtWW8dQwnprU9dZ7Sy1BKuMw3iWfXYlvUUlN/GugjCkIdXyGVXy2nYUc991bavnavSVJH4bBUkaMDju4m2fIpz7t++dxAaPYwSaGuLck6ZD4F0QZUUBdWqx204+vMZddSX/WU5jFLZPUWzisXRnxNsPShpw/wBQ2JAVZ2x5JvY/BUkYE0t9MjzIxW5siqZcyWMqIyaRPUJvTwVB1SToYBksZUUY+leSlrs9mQxa3RlJvZLCUEduTgVzLWanrY9ievY2R1Cs5SlAZU5EM4fNhHufxDk8xIdubI6mXMVjKqMpkCPdxfLY3Q1Iv5CFBSVIUDJYkKQoGS5IUBYMlSYqCwZIkRcFgSZKiYLAkSVEwWJKkKBgsSVIUDJYkKQoGS5IUBYMlSYqCwZIkRcFgSZKi0OlglZaWct5551FSUkKSJDz++ONpP7/iiitIkiTtMmPGjLTb1NXVMX/+fIqKihgyZAjnn38+5eXlh/SLSJJ6t04Ha8eOHUybNo277rqr3duce+65bNy4MXV58skn037+zW9+k8cee4zf/OY3LFq0iO3bt/OpT32KhoaGzv8GkqQ+odMLOM6bN4958+Z1eJvc3FxGjx7d5s+2bdvGfffdx4MPPsjcuXMBeOihhxg3bhzPPPMM55xzTmc3SZLUB3TJZ1gLFy5k5MiRTJw4kS9/+ctUVlamfvbnP/+Z+vp6zj777NT3SkpKmDp1KosXL27z8erq6qiurk67SJL6lowHa968eTz88MP88Y9/5I477uCll15i9uzZ1NXVAVBRUcHAgQMZNmxY2v1GjRpFRUVFm4952223UVhYmLqMGzcu05stSerhOn1I8EAuvfTS1NdTp07llFNOYfz48TzxxBNcdNFF7d4vhECSJG3+7IYbbuCaa65JXa+urjZaktTHdPmw9uLiYsaPH8/bb78NwOjRo9m9ezdbtmxJu11lZSWjRo1q8zFyc3MpKChIu0iS+pYuD1ZVVRVlZWUUFxcDcPLJJzNgwAAWLFiQus3GjRtZuXIlM2fO7OrNkSRFqtOHBLdv387q1atT19euXcuyZcsYPnw4w4cP55ZbbuHiiy+muLiYdevWceONN1JUVMSFF14IQGFhIVdeeSXXXnstI0aMYPjw4Vx33XUcf/zxqVGDkiTtq9PBWrp0KbNmzUpdb/ls6fLLL+eee+5hxYoVPPDAA2zdupXi4mJmzZrFI488Qn5+fuo+d955J/379+eSSy6htraWOXPm8Ktf/YqcnJwM/EqSpN4oCSGEbG9EZ1VXV1NYWMhZfJr+yYBsb44k6SDtCfUs5Lds27btgOMTnEtQkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhQFgyVJioLBkiRFwWBJkqLQP9sbcDBCCADsoR5CljdGknTQ9lAP7P273pEog1VTUwPAIp7M8pZIkjKhpqaGwsLCDm+ThA+TtR6msbGRt956iylTplBWVkZBQUG2N6lPqK6uZty4cb7m3cjXvPv5mnevEAI1NTWUlJTQr1/Hn1JFuYfVr18/xowZA0BBQYFvqm7ma979fM27n6959znQnlULB11IkqJgsCRJUYg2WLm5udx8883k5uZme1P6DF/z7udr3v18zXuuKAddSJL6nmj3sCRJfYvBkiRFwWBJkqJgsCRJUTBYkqQoGCxJUhQMliQpCgZLkhSF/weBNBz1k0sgWwAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hills context map" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "context_map = hills_context_map(size=200)\n", + "walker = Walker(sigma_i=3, sigma_j=4, context_map=context_map)\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + }, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Labyrinth context map" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "context_map = labyrinth_context_map(size=200)\n", + "walker = Walker(sigma_i=3, sigma_j=4, context_map=context_map)\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + }, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/context_maps.py b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/context_maps.py new file mode 100644 index 0000000..773867d --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/context_maps.py @@ -0,0 +1,37 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + +def flat_context_map(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/plotting.py b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/walker.py b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/walker.py new file mode 100644 index 0000000..39c9afd --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/solution/walker.py @@ -0,0 +1,60 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, context_map): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:self.size, 0:self.size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_3_break_out_the_context_map_initialization/walker.py b/notebooks/walker/Step_3_break_out_the_context_map_initialization/walker.py new file mode 100644 index 0000000..ed075c5 --- /dev/null +++ b/notebooks/walker/Step_3_break_out_the_context_map_initialization/walker.py @@ -0,0 +1,83 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, size, map_type='flat'): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = size + + if map_type == 'flat': + context_map = np.ones((size, size)) + elif map_type == 'hills': + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + elif map_type == 'labyrinth': + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:size, 0:size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/Step_4_break_out_the_next_step_probability.ipynb b/notebooks/walker/Step_4_break_out_the_next_step_probability/Step_4_break_out_the_next_step_probability.ipynb new file mode 100644 index 0000000..3ee36ae --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/Step_4_break_out_the_next_step_probability.ipynb @@ -0,0 +1,241 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# Break out the next step proposal\n", + "\n", + "- We want a separate module for `next_step_proposals`, living in a separate file\n", + " - a Gaussian one (it's the one currently in the Walker code), called `gaussian_next_step_proposal`\n", + " - a square one (you can find an example below), called `square_next_step_proposal`\n", + "- As discussed, this can work by passing the fuction for a `next_step_proposal` as well as the arguments for that function to the Walker constructor.\n", + "\n", + "# 1. Your Dream Code\n", + "The following is our current code. Modify it as though you had already written the module as in the previous exercises.\n", + "- Modify the imports\n", + "- Modify the Walker instantiation to take a `next_step_proposal` function and a `next_step_proposal_arguments` dictionary as an input\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true, + "execution": { + "iopub.execute_input": "2024-08-05T15:58:32.267Z", + "iopub.status.busy": "2024-08-05T15:58:32.261Z", + "iopub.status.idle": "2024-08-05T15:58:32.274Z", + "shell.execute_reply": "2024-08-05T15:58:32.278Z" + }, + "jupyter": { + "outputs_hidden": false, + "source_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "from context_maps import flat_context_map, hills_context_map, labyrinth_context_map\n", + "from plotting import plot_trajectory, plot_trajectory_hexbin\n", + "from walker import Walker" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2024-08-05T15:58:32.842Z", + "iopub.status.busy": "2024-08-05T15:58:32.840Z", + "iopub.status.idle": "2024-08-05T15:58:33.445Z", + "shell.execute_reply": "2024-08-05T15:58:33.449Z" + }, + "jupyter": { + "outputs_hidden": false, + "source_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "context_map = hills_context_map(size=200)\n", + "walker = Walker(sigma_i=3, sigma_j=4, context_map=context_map)\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))\n", + " \n", + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# 2. Implement the changes in the code\n", + "1. In a new module `next_step_proposals`, write two functions for two different next step proposals: a Gaussian one (it's the one currently in the Walker code) and a square one (you can find an example below)\n", + "2. Modify the constructor of Walker to take a `next_step_proposal` function and a `next_step_proposal_arguments` dictionary as an input\n", + "3. See if the dream code you wrote works with your implementation! (Don't forget to restart the kernel)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# What the square next step proposal could look like\n", + "\n", + "This is an example of what the square next step proposal function could look like.\n", + "\n", + "Notice that there are 4 arguments. `current_i`, `current_j`, and `size` are known to the Walker, and can be passed quite easily. `width` is a parameter that is dependent on this kind of next step proposal, and will be passed in the `next_step_proposal_arguments` dictionary." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2024-08-05T15:54:14.653Z", + "iopub.status.busy": "2024-08-05T15:54:14.646Z", + "iopub.status.idle": "2024-08-05T15:54:14.749Z", + "shell.execute_reply": "2024-08-05T15:54:14.762Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def square_next_step_proposal(current_i, current_j, size, width):\n", + " \"\"\" Square next step proposal. \"\"\"\n", + " grid_ii, grid_jj = np.mgrid[0:size, 0:size]\n", + " inside_mask = (np.abs(grid_ii - current_i) <= width // 2) & (np.abs(grid_jj - current_j) <= width // 2)\n", + " p_next_step = inside_mask / inside_mask.sum()\n", + " return p_next_step\n", + "\n", + "p = square_next_step_proposal(100, 50, 200, 14)\n", + "plt.matshow(p)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/context_maps.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/context_maps.py new file mode 100644 index 0000000..773867d --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/context_maps.py @@ -0,0 +1,37 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + +def flat_context_map(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/exercise b/notebooks/walker/Step_4_break_out_the_next_step_probability/exercise new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/exercise @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/plotting.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/Step_4_break_out_the_next_step_probability.ipynb b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/Step_4_break_out_the_next_step_probability.ipynb new file mode 100644 index 0000000..fe04893 --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/Step_4_break_out_the_next_step_probability.ipynb @@ -0,0 +1,237 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + }, + "source": [ + "# Break out the next step proposal\n", + "\n", + "\n", + "- We want a separate module for `next_step_proposals`, living in a separate file\n", + " - a Gaussian one (it's the one currently in the Walker code), called `gaussian_next_step_proposal`\n", + " - a square one (you can find an example below), called `square_next_step_proposal`\n", + "- As discussed, this can work by passing the fuction for a `next_step_proposal` as well as the arguments for that function to the Walker constructor." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "execution": { + "iopub.execute_input": "2022-08-20T06:27:54.689Z", + "iopub.status.busy": "2022-08-20T06:27:54.685Z", + "iopub.status.idle": "2022-08-20T06:27:55.297Z", + "shell.execute_reply": "2022-08-20T06:27:55.319Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "from context_maps import flat_context_map, hills_context_map, labyrinth_context_map\n", + "from next_step_proposals import gaussian_next_step_proposal, square_next_step_proposal\n", + "from plotting import plot_trajectory, plot_trajectory_hexbin\n", + "from walker import Walker" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using a Gaussian next step proposal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "context_map = hills_context_map(size=200)\n", + "walker = Walker(\n", + " context_map=context_map, \n", + " next_step_proposal=gaussian_next_step_proposal,\n", + " next_step_proposal_arguments={'sigma_i': 3, 'sigma_j': 4}\n", + ")\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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IXtK32+nCT0Jz0s78K2Wf6lghMK+GmRVzqLC3OoUesh6aMyvGtHQrP6wwrZBm8mM4s4K384WrHiiBaT90lKkA2dau44hhVQZjXFFN47P1o1HRz9th62ZUk/MJXMyGzePh0j1n007/UJk1Vdm78nji43r42kj3l8rTEKPyUAnCxaxURqUwK8aqNNNR87q2plg0X4YMOIyYM2Q+LcFKG4bG61Z1nPFsH/vG7B0kEVUlyF4wO8N2YafEUUFDcchg5XecMBwmxl3PXSYEe6uofWPCgzVbaYFhKaxLZVqxVIK+ThcubZX4XXW+p9SI3+siYFgBAgQIEKBRoFEzLCMMPknYFGxZXi7UgGw/AWTJUJUSXTYsdWiPyzDA0vbWhOOC7tJN25dVGJcp2DBUBw0/xiVG03AzLLls8TEsSGVy2bJ0eEjbdlEUZiU6WFCFYXHpO2xL0op9Sg+ZCIUYk7KZlm5K6bAmp3ViOnYthWFpqgeKApNqvgwraj8ws4tFbFalGzqiiq2FMQSDU2G7DgQG63KBZ7Yswa5hXdPJ57Ydha1zPxrFhkWFvPidLpx3w+3eHsOhgr0vPhO7NYFRWWmnrTmjYrZHjbFpmRnHxbC4PdKqQMa0ohrldi3mOGPGaB8AoNBc9ea8roptC4otUriu46DB2lK1kxPB6Yq1scy44rFPMqhOU26bNInDocbNvHydK1z5DpN0sS4IUxziQMCwAgQIECBAo0CjZlhmGCA8biD41u0d6LafSPmizl2ZrAjFxTY+G5biucPD+VBH3OH+0rJnkotxiRI1k7Y8PMaES0H0GlN14FSRzLwENBdB9JXMnK0a/889kVhpgxAVbFaMUdmSc5hJ3bK9KhQyOHNKCHkzqrBNMxPYucSIwbBii6cmJZxJMXtH1H6gensbsitWt9MRQqHbbIsxgYgtLjt2DibR2/chxHF592W1sjRODAJxPisg2Cd9GJbUsMqz+zEsaIKE7mPD8rRXKaGzHBsVY1je0xBCmslZF2NUqg1SV8ru1Y6ipyfgTEcwWLxN05TYFgAYmn/7sDqhRK4oJ20/rzINXSOER8ryc4FnLvKMnVnvun0VP1uWh3cgf6fVb5Nqs/J4j90sKbYHYCytissPgOUTeHpfBzasAAECBAjwu0OjZlg0RPgTiHOtTB/PNLd3oCAZqt6AOpXSroCbxO1lps4B4V6CfNIicTMrJn6x+xqKGMY8iUxBomZSFpfIZKbF9dzEkXLcIZnktARVyld1+qoeWvfwIHPNw7HTokfgITArwGJRjFkl6rItK1G33OoSbPc67iVITIRs1hUmsqTOoNqyTMaqBC/BiC1aRtl17dmO9Xan4uGyCIVm6NL1VKbFEOUHaHC6iDfTIl5twupfsW+obevMDfdobLWNWb4gCbvbW9FGeMytIoJnJ+DYqnTVLqnJ25DueHWGVWblw5S9wNrNxbSECeDMw5NrLpR+YfC6sfsDse1YACiYx6Im3Y+VibL7gzr2LftyrLpczIu9x8Rh0swurXqAqrboQ3qPFY2JqQvsq0FblrPf5QugUc9riP3Gra2hMKMBwwoQIECAAL8zNGqGZergy1Uw3aophPzxZVZqyB+dwrWOkjDz3vphbwSmpaqKqSrmiLYr2AxMZVZKkFM/aYgYTp7Dwuy0SZW0cw9f21U8Qo2vPUXZekQKcYXkcc218gizFINZAUBSOMqlbsaoEkMys0qwRVKRVbkZlsyoVMblSOWOlyCzVTGbFmNLXnYxNZIGUZiVCkMITcOdwFRbCTtA6B+qp6nLAzUWi1auR4V+DcjSseopSxXtgztqBXVFJNHtfaxNQwKjsrbMq5M6HqCMUcGHYcXhJehiWGyOnKnxquTtpNhSvObpOWZCNq+L2a7sfHY/1h9AnN98H7s++yGnCXEi3nC7lvoeqw6uMRhWQ0GsIc6P8mFYXl6E7rBbyn28bFkuj0jBlh0HAoYVIECAAAEaBRo3wwo5DEv0APQPyunBrNg2xgKAgCDNqavWesCZB8O8cgjPd1ZLlfeprInbLli8M1BnJ7uG3zmmIJX5rLjqFNbjARpge26JW2ZbLA/wYFYedg7HU0yWwr08AhtiVqotS2RYOuKX0AHbhkUZw7JtWFT2DtQUu5hmmA1eNx6Yiq0ESj+hRPAk4+3EJGbG6O1sL6almkBUFs3TtEFm5RW1oqFYjyqzEr09ueelppxjP/BPYVis3UzKWJsutJnixamAB9KlANiyOZTVsXU9yiuJncSOc6qLncO5HYtmYn+7RPbgsDDVS1BmLYc2D0v5XsT0EvRJe85dVY9VbVnO98JzXush0KZGPWBZFFP4DevD6FdxrlWFxY+nMqHRcWhgqg15oIorUjTv1ExF50wQNZXBgHciJXIx5buJM9hxa7B9fdapwQ/mW3YOVwUyw24sdVEDaiLPkCuxJpECnh85PxfnEP94ycb3sC64tTcwUCXyActxa2cDVlhTKtkHBtX4B09jHxv+0Wn4S2FS4pnmLsNK2sqzf7CJmizf4/ouoYZ/GZUDDuGj5qWy8XNIihVeiQkfhzJQWWlDcpixzvVWEcY1YDGVrj2wsAngAFxhynhd6MQ7nxIwXT4XkHlMMuVbIzQcd7pi7wZ3SZfvQ0XNMVf/y2nVzT2mat9HJRjXgNWQy7rucY7PN0ByZVf7mUadyeVxIFAJBggQIECARoHGzbA07nEqh/9QpALXpGAvI7HifstVgWrgzUNiWHLaJISHg9H4xEPrGMET3cpXrwnwSYlU4F3Wf/v54HEx7ojBC+d9A6/n8FUT2WkP1+eGmZXj7kw0mVmpIXhCHtJ3vMxKZFiMUXHjPZEldT+YhCBidyKVYcU8z66oBBYOyE6z5+DSv8C0WB9hzESY72CfA36s/YtL36pUz5e64AzfOcUFP6YvMi2fqR7q0ieig4W4HhkQH7MCrAnfTPWnMi12LZUhe7UjY1ZswjCb8O2I6FFoijMMV/+qDht25Zu6yeuS7WOskqqTtnXnXeTvAmfUkI6NyxFKfY89PhQNThz2fX+FbyZ3mFC3Kns6BGalCw+qsnWCQ6JNAcMKECBAgACNAo2eYXm6VHK2JW+5COKxkqljs/JmVo4Ny97GKhez+ShMS4TJRCVbp86ZIr+Ie8sNrYxpKbpwL6ZFFHbEdd/qfUT46Lzd7rGCPluxa7m3Sp0TytkEq1t1qRC3LcMUlg0xpH1hvjXkrWbw3y6GFUfwWwaXFK+IeuJEVVOTmVSIMhdoW+q3n4GHC9IId3nmEjy3NTJm6twJgGXkZ0Vi0r2m9gvY1/CwZbmcLmSp2HlO6mZUfgFshXdGU9qSs2dlErDYtlba34alTvyO1X6s7biDA2OB4svIX0FWb4a9ldkZW01ao4Qv9+MsDaJ8Y/iSHYyVghus+bvIisDfH6V9KNztYIMTKw/W7EvQFJuVpw3LIy/mlshaLWsbg1mxfLUvEeebEA8ChhUgQIAAARoFGjXDsrzgrJ9SsE5FkmhQ2teoyxvQj1mJgTcbcoNl8h+3RniIB8zVVV3unEsponTMCRU7x5vB8cCYxFninUtm6n0Y8/LSf/syK4/9TNoiqlSl1rW9W3OWrud167ushCB9E1lSDysThdVAt2FicHYUtu1aegPLi3BmRUyE1X1KyB/G3liAVEMjiNjnc6ZgrwEetR+eP5fJ0tSxkzBCwOqTTVFQFv+T7AGcUautbYHbPL3UAiqLZhAlYd5mcntB2YrLqeicBUF65pCyVZmWRmjczIrfQ+AWrH10u10YS2Ivob2uIkKE8DbTXP3Q3T6AZcsyFE0Mdzd39X/2YkH2kgPcjEs2V8ZlX/5ZIda8WJPPt9LFooRr+HsN+2gjBLYuBWQIGFaAAAECBPi9odEzLDEYLQBpuXGX1KhO+hWEINX7T03rihTW0PLqgFsaMKXrMinLvp4wIVQqu/h8PI/4HCPnU+LWeftNeHZ5FinX8bqfJHX52LvcW0F37Ve39qHqBFEp7BHkLZtjxbeCJyD7rTIr3U+U5YY+jf9WmRZbjFGdE6QT6pL8XZOLPbZqv1JtqqwBxYhNnH2r7e+iz0q29KxqWmFjHu+Yeln3u+PxPJCPUetNrCN1GZGGmJXElKny1jGCxa4JytPcg9FmY4wB+7UTIdRty/Z598Q2UQMYuyb6+11Dup5yDntcuE9h8Ate7fV9VDVVvseKz+f1jVKPUfa7w1FRkLgopYWAYQUIECBAgEaBRs2wvCV7YbR2SY/+11IZUzwMioHp6X0mzivXjX1/bqtwHYAYzFFOSpKbIpK5mFYs3beS7ZK6+PHUv2wx4FcX8YQ2ci8RoqSF0qu2KpVZsf3MdsX3E5NL7Kq1i7G2CNWhQvUobCiUkBcjcR1jb2Ub4yEwKXG/5z5/O5faTl6MStyKv2M9s9f+WG0fk1nx8+W2VPOZN6ZGTGhEPca7LF5t4q4TZsOS8ymhIA28FCprkhLqrX3yD0lD4nXcT3h/G4Qfe/e7dxwIGFaAAAECBGgUaNQM67eCeJhVgAB+cC38eUQKodjDAhwSfhNteDjwSzY/JT+7fzXqAYtQ5/nlCOksUzkhRl1JIW+ENKP6zI2ZqSUoJYekNnTuE/v+vuFZKJzyN/BcRKoL+RiipH3vBUft0eBaWpQ4mYdQJX7PqgaNjecYU9GrmIKegav6mKszc31mBnhFfcT2m1Tjv1UYqnFfLAu8yxbruZz2J0q+veUZ4k5V/+ST73Uug3qohxWfKn1HDTnmVXbawDO79nO1OvFVERmq7oxNDhZUg2pbqvmm0LbiumdeZTVjPFfM91QAiaMve35G4rx+rGuoTckP8WrzX2Kgiueah3jvQCUYIECAAAEaBRo1w7JGZ5kGECqyLfV4Jh3ZO9jKvBr1kBplpgWipL2K4yOhiZKaKzAuK4P4TNJWsJyqIXZcx8j5RJBeXMzKh5V5PZ7KtHgoKGGlY1edq1uTSOdS6tQXk5xZ0FF2ClsKIqw59aguG8GDnNqyF9uyEDwROE4Rmuiubj2A+2HhSNwGCP/NnCvY1ndFW0r484jSvHgMey7xXF+2QtV6s7cm8W9/Br/3wAuqV4dI7ZTJt/xdgHKoZz/3bmN1ArZTR1SqS0AIr8TlazZblxXAkbtVdhsx5fYyhDp39SWfNpXfX/ezypXBtk6+a3KvorHwfa9jnuOdFqEyK5Uhizv8yuj/XotaFaXP8InQ6nM531n+vQGBe+12fwQMK0CAAAECNAo0eobFvXGZ8GzCvbiZGpKfx7+xJUWTgK0YahI1TgoL0WSlpPXU/PTzbKtIYabpLC/CtpLE7JGW4jtx6UTeR5RtLOnOOcaz6NbximjmBN0VyiLcRpwR7QrwyUkNq2t2rsbDEXEp3HRLtFa+ddGopiNqX4BJ6kyCdk0gtsPrmIRwCTpiL+1q8knFsSU7k2qcUTGbFd9CZl5sRduoqXO2wJhUVAl+6wquajqsjAupan/wknDVPuLLtD0YmNrGrKPwbi/WDZUu72ZcslbCNAkMFvZIYSSsTtQJxFGWpiavLyivYljNsNNedkaV1UZ4m7D20jwZFOD0N0Ppl4bIHE25XaiiQZDagL+f9juivBvq+0tM7zxx68XGXFoS1v6sSDEUC1Qhr87EXvZDUdWYwm/l0Z2pOQrjEtqJkzsCpa/FRsCwAgQIECBAo0CjZljEBGzHLyeoKnWkHS5JKKYLnmYjOxEEIybl87vIJ/GQSjE8BH0XcBQYFjUVqZtLyz5bSriE5pLY+HPKaSJJd6xwwr4G4HLKYmmXFE4dKUtlswqr5ZKpBhfbZOGOooYlBTtLUdhefqbGw+dEiXyMxjzGlAUXYcJZWoJ5BYJI5/jBBHExLJaus9kak9gZ04tQDfWmLu1TmRZLM0neNDWYwm+pnlj/YKG7DIF9qMyKt7vCgBi82lyVpDmrlu284rHqZUzx5QNAiMal+qh9jMbvY7cXqxN2js22NaK7mBVfBoQwmyZbuVIOjyWVidk2ObNzmJWV1gRWbOXVK+1lKG1itZPCylzvq/2c7F00iOs7RHzeX/G99WVW4rsNeDIs38ACbL9XtxeZk5iOteXfT5nK8eDc9sHOAqOi+sYuEhHqMA4EDCtAgAABAjQKNHqG5WYblLMuZ2l32WYliJXWfjhSgcm8zJh+nLMkTTzFMwyN29MLctokEttieVaGLEnD8JDc2LMaTHqDdAxnm6K9yiWRKXr0GFK3y62I1aeyW3IzMtwSlJXP0o6tkNi/DYNJ5vahbDkOW7LVbMYlBb+NEYpJhEkItzcx+5bfEuuqh5kh2DlUL0EmsTOmVWen682QS2Ln7MxQGJfh2Eo4yzRY/7DryVD7CSucoxZg/cHxyLS3alt7gLePYqNgLM1iWj4SMCf/dv051FvQRBDpWRk0hWmJMLlXqG2HVJaOYXUSK4yTnwegw3Z11BsyO+a2Us6wZJZmGBpMQ2HArveUdWJeFc77yt9feetiXobHsaqGJIYtmqg/XO+z/7ncqdZQd6gnx9on27AkpmUoh2rUrQmIgYBhBQgQIECARoHGzbAESQSCLYsHpmSSDfeAkkd+kQ0wZsWW/3ZWrVMmJChBar2gzleS56fYu1ySszez4tKzIerFIe+L6W2kSN+qDSsehkXUa1A5LR2sslg718W0iLMMPGMazO5h26wIZ162NG7ormUpGDTOkOV2MYkGw74pY1iGIqf55YtzdVRvwAhnWA6zAoB6Q+e/uV2LS/KMaSlehFEdhqHYS7jNSukXQv8gqjTP58extLWJxbB4q3EthHQpyybsFf4CYvPLxiYTGgyXhK7cl8hBg8UoE1wLwZgWZ0nWRRsKJixeT53nJdqwGmwfO5+1jWEQx8bo0y7EY+tmVsp77MG8GmZY9rsRF3tmW/mdlL4JupLnjumsXOwQmBafI0uExR2Fb4qilYmFgGEFCBAgQIBGgUbNsLQoQGw3JGdKiBDjjzh5YprBaxoVNwOwSzCnLE0QOd2X8rwGVFuWSVzecpJNAhA8/WTpmRjELaGxMrp04Y6kHY93kR/85m9QxlQZGxUlNEXKotyWodyWEMGeZedxRqVLV2JVby10aN+IuZ8pPdgV0UAzHK9A++4RKi+oqEKU9qPcS5DZQBQvQbtymD2k3gyhzrAZlp1Xx2xXytaR3DX+m/oxq6g8N4mYxJHq/TxBVe+reNg06/hMlKXEJXWrc8IcW61j/2Vs1TfmXpSdY904pDuUjL1rIdX+ZPcXZstiEO2XfnEcuV1KZFiG3Lb1UbWdHAYM2F6CrH1Ye6iMKiqzJ80Qf3szK82uC5Fhaa53mkrn+EWmsHZKG5etkYpta1+Lt6Eu3TYGCPw/IuyG9n7d+Q6q5aYEh8SwGvWARcTOIL549tfR5KoDa5famRmoDmf0YiGZNHnLV349BLd2NUyLNWDZeQ24w0Lt3OKApQxULqOuMEipkwRdHd6r/Go1qceqHV4DTPXLxMPqyKo6ZzjTQJkKiatX7Q8IFzTiGFWZwKLLH7cEISxSVHF/Vlew9YN4rp97dL09ONUL7u3qQNXQh9AwNJhRRdWkfBDdDjcELqcbdcCCnPacOMyS/KMmX4tq1FGls+uqA5cCExoI22l/YaLKAEWV9jL5B5NAVybwskngbKBi+fG8g6zfqa7qBiX8t6oC9GofADCjmjNQRVWBQnlfhbTGfisDExuovAYsrg5vYOKwVAXemlvnfXYJnsIApsvfLGWha/dARoULq6YCrl6U9xONOsIuKwtx6ioeBCrBAAECBAjQKNCoGZYWpSAR67cYJYbbjxnTYpI12LEeqhLd+SldkEsEsthK46EoqmQrqARdahtDTnuxJ9UdVj3W5XxBf5pK0KVK0JS0Kn1pzkqurK5VFaEX02LhsJx5rqywvhZfDlOV1H2CqYY045AZlrhEBTtXVS3V84nDtpQuGPC5u7Qhu7Mb8UjuPkZ8lwQvukvz/gXPNIPnEhSKSlBVA8MkQrgtWyJnfVaRpKnQMXiYJnbPELuwyQ6xtsp7RylxJorbjIoxLlaPqkrQi2mpy5cYCmszTI27rYvOL4CsqgXgsN+o5mJWjB1wlhSx04xFRUjDzErdb1CX2tCfYXk4QLkYlqwjZG0rbikLk8bZs8x8XcxL9/gO8HOYVso5FrD7DWNWjN0R4vTxOBAwrAABAgQI0CjQyBkWQKKybUmULjhJUqR/boIRpAiun2f6XdXNkxtWhPs1ZOtRbFigAqNSbBJ+k4JFe5VrXwNSmOR0oUhK8bi1O8Es7TSrOC4l2UXXIUhgsrTNIyQxmxaTvPl0QoFp2WmVaYm2En6MS6qzt7pq/9C5RB4isls0g5oWXaK93KEB92RgxyVad2wgiuQejTKXdduIb0vn1PCQ3H2M+JK90rfdfRi+B7j5UGlzaI6U7AQyVpmVvVH6FKXiPsZQ7f4QYvnEc2tqmsOs2LQHwtrSuoYaQNcLar9QAyxbDEtmUnzSNmsf1cEiShymy5hVREkLzMrKF5iTrQ1y267suvZwunDecfsY5TvlPLBHJajaIJVhscAJupDH2o29YNxJDK6tyUYPhdFrpnNdK9/RuvA+wvqxBqfvx4GAYQUIECBAgEaBxs2wIuA2LF8XGQhMi9s5ZA8mjRJBh8sYDzOEMepg30WRSD3BJU5F0hUn8rrCsRA57THZ0MWsVG9Br8mGqkSm6r5jPYbPZFKq6KY1U9RT21tFB+4KPAvqWvCSKq7QKtOKCNd1toZ9H9lWwYLihnUDEbsQOnFCPIlbFV4LK6reZqpLtOhhptqsjKgsyVMvyd3FqBRmFXX3D1/v0J8khdtJ3sZO23NvMsU7kIcnYu+OwOxUVka57cquA50xcCKdSzTqsGTblqXZjCvKPYJttqFsxeupaT7NgQeyJU578LBYMdoHAAziz6wYaxKYFcsnCqNybFdUTkuu8H5egjLTijU5XP1WUaVtxSV/eJ59H5O924qmRHyvRXuWtOX9g+U716YCc2d5rH7iQcCwAgQIECBAo0CjZlh6lFpitwQKP/rjDpnkSI6OpGcfwucoyCzDsZU17CXouXii1xIgcKQrrgf2sFf5sy8lX5qHpUhqcdg1OJSJhi4JjdeV8DskPYZrAT8+zw3E8UBi4A5Pik1LlPJ8bB8sYC6zUYR1O02JswSJIpHHCu1j3deZq6MyOD75V/E0MwzNmWjKvMyUpUEok9htCZ4YxOUFqKmMikvhTr5v2J6fYa90S+MAcbV3HB5l3N7F2psZPJlUbzNuxTuN6FRiWwCgsVBdrN00+UFieQk6C2I6zMq6vxN2izEqU/XUFNsHAKIkpjcg4MGmIl4Mi3ofK9iyNNV2pTAsTxbto2Ryefm6vAQJTNZOih3UdNmuHNuWl10LEPqFpuRr7u8pJQCNBDasAAECBAjwO0OjZlgkCmgRL7FCyVO8mZy0IzmagicLIEiVilRCRC9BPyhMTpwX4/LyURgVVPbE98ewVflKY8L1fhLDsg9V7Xcak47ZfkHaUjyGHC9BdqpjR+RrBKorA6pMS2JY7LpMArS3auQEu3CaZnLvsp/DsFQvsyiX2N2eZlyaF+fvAO45VoLHmYtBKW2rec3D8mDUwGFiWOIcHWcCo3WIau9giy8Kti1u11LsuI7nmLf9i5imy85hqjarn8Cw3AumOvfki2Iy5mu628faetis2D7mAah4BFrfKHYsVc6V873nYcn7XAxLfHTurqnY8fh7K6dFJqSGXTOVb4mpeAsSkwrsS2HgAqNS7+P+ngI0sGEFCBAgQIDfGxo1w9LrTZCQKl15MC1F2mLZXP1rCnMHFD09UfS94qKPfuAl8LBhuebK+DAqlUVJDMtX+nJvfXXfcTAs1WblinwhGKq4tEXl5/ILlApKnMgILEu1hUA9RxPm1ZjSOZTr3GXGpWmayyvQy7vMqxyAM5+LE0eFUfH7CWnqigvYkORO3PNuXDYtO1/yEpTzVIb1U7wEYzEs1TbhmncTwybM5+yoti2VkZuaI31zD12VYanP4PFgXoGnhftLcT39lghR51wZgt0phs1KTlNXRAuVWfEt7wOU57mC3zI7l4tFO3VAVe2PapdkXnvsuYUYf6ydVGZFuM1RaFfFrkVVxuVpw4K0DwHDChAgQIAAv0c0aoal1VNo4Vhio53kNhAfW4nupX9VvFl47Cv7DrEcW1y2A8GzS5WG/Tz/PBmWD6PyZVjUnafUSUwwNqk8u7PciCBJqV5EIW9WK6YdJmNLb6qdCx7nKjYJM+RI9dY1ZMaj6Sb3KnOYFaS0CpFhcYlStZkZsk1EWnDRZ+kJX09AUXLn0j3kYz08Qv0Zlmx/cB7M42F9GZbTtl6SMgD33DtWVyG3TZhHQFHnbPGpdsJ+l4eu3P+gtKPEsFzzsOwfXqsjqEv5xGgfwLZH8XlYkI+NKFvGmiJejEpNU35965pU8BhkbSlveb3xxRF9q8CpKNZurK/yZYKI8E7b72LI+WYBjr1aTDfkSej0G4++JDIsl6e3Pxr3gBUxodX7f3iJq/PKKkLn4wf3pDf146w4YViZPjf2MXZ7TeRt0EXdyxDrcsignucQk7rVQx4qBD+odaB+zEyhY6qdl13fcXV2D2Bco+hyjmEHyeeYlAjCh7IVjPZWmSg/h3/X7Amo8Q5YsdzoTe4ko6hXDBJDtQQ5X1D3uYKoKu7s3gOW0u5qG/+sActpW69pDFJaeXdM6qFiV4RGP5doaHAGL2VJHygOT+oAJmYW7NmH0xYsw0vHj0RNYgI8g077rQDs0T6A1UZ+gWudAUsZlCIND1TsHNaeWpQKwqk6ULEBSk3DBcfZgtWX/VxcGBEHLCZsyIIEn27ApqsIJo2GHDOcfuLRl/4XB6wAAQIE8MId73+BcctWIxw18PipY490cQIcJjTqAUuPmCD1omimgEsdtlSsqsMkF1fw34CbunKmJV/SG4q0I7GchlSBikOFKFmLbMvzXPUckzoSJQ/nxJ49RvmVgqtSkdcKxC5py6V+9VDLKtoN1yRjriq02QcVwjn5udEzJwleRpO3FeHBVOXnc0FiWEqZVEalLLgJU2BU6hIUPo4VUvge9RhVyhfa3nfCuA/D8mLVrqUnFFZNNXhOYwBisCTqsY+rVGVVoWsBU2ESOn+lVYcnJZirpJ+ngGaaGLa+EABw0qIf8fiJYx1ti8AQ1AUwY7WPlfZ2W7fSVMpn5+iC04WLUfG0ad/fySeGrQ1QnC14IyiaDC8VP+H1xZiVvUNj4bGcvuy0qT1Zmk0TYap9psFgqveQm1m5HDM8nS5kdaHldBHPx8guetxHBggQIEAjQLftu5BRXQMA6Lh7D7ruKDnCJQpwuNCoGRaJmNBDqqI+xhisSP3czmI6EkRDDMuR6mIUTLVdxcWwvFmTKPW5mZUHoxLOJSaFyy2WM5I4pBqVWXGduGyYFSceOszKx14o5itFcE0yVlaMlMI5qVsmLbKL8MCemjBh0q6DhhgWLxCRArpahVMYFWewTr6v0V7NFxwrXAFQXWm1bb0YltLGPrZUKxNSpr9bu2OQV6mwOnHUFKrec0l1eNi2FPd2qhGJbYll4WV2ubXLyWHrCqX0SYtXYsP4ltah3EGFuN/Bhhxfom73dSI4V7BjAItZ8XM4+1JtVzaziprStYhhgth54O+8kvZiVj4ThznTYoG9ufHbYVM0xAIB2+2h2/uUaSLsOGLSBh0zWLuZh9HpImBYAQIE+F1h6MbNAIBVraxB6qRlKzxVZgEaHxo1w9IiBojNsDTuuumhy/WxKZmCXtvxNrOyuH5XkTi9GBZ3dfeR/iWGxSVyhS35MivnODVPcy38pl7T8TbyW1I7tl2DSmnHndnW7QueRKr7OpPMuIu1K0AqhSoaq0VxBHp2LnXZufjEVMVuw0MAaQQu7zLeR2T7jXsBToEFenmZAZ6eZg2GV/KwV7knl6pt6z5HtVk6ZfNmWp5QbFeqBx7VqOMpxqVtuyxerBlWm7imM7iWn2Fbdg7lx6kLDDpMizFkuYwiNNPE4E1bAAAPTpiAl196GR1K96DbthKsy8+Xpne47MYqs2JERPL4s/c1xKwEhqXXm8o5MsNi9iqWRtTkjIozLVPp6KZSkV5w3GHta7FvJKtXm1WFNIe5qUyL2bRCzAZp3zbkMGE/T0L2neC2LR3wnDYRTBwOECDA/yK67tyFjJoaHExMxPasptiWlQUAGP/jCs/jsyor0W5PKfLK9/+axQzwE9GoGRapN6Dphsce1aVPhql4oVlhguyfXBKUvVlc4YmEa6u38WVaXhN5XZ5+9hMo7MkrIKbbrsHSlKf5/A1XSBd/yYw/D2ckTDKzT2XLMfDJnoKtJ6xeXqUvYm3JeX7+nuJ8LdNl+LLZHg8LpNicxOCt7NamT8fwApfIFS8zV7Bih1U1GGZJmIgKyLYRZy6OfA0vL0G/JSh82bRq7oW7bry8BLl9V5fvo867cTxB4evN6bJtsR9iu6lh0RRWS+VXUepSwzZY6sC0ujrMuv9Bnv/n6dPx7+PG8XbUIwZumPENrpozg/edO046Gx/1Heq2aUmLMTZss5Ly601/ZhVlzMqQ0oiaIIbduIbMsBgbg5cNixsRlf6tMC1mn+I2LFMDdNYw9vVDzADFjYvWKaLXJ59UzybR2/djp6gMzCRCv3JspzTi/y1S0agHrAABAgQQMWTzZt99XUp2YUNuPnLLy/HEu29h0FbLOSNKNISoidyK8l+rmAF+Ihr1gEUiBkjIkkQ0UYrgAkZDGk/HC80VeJVHuLAP+Vmhmey06cGsfD3+1HwqhW6xjlGYlhq+xaDuvBgz412PwZ5RVxirxlgN03d7SFeunhWDaRE5jwndSkQZmHA8B5ndhAdVVT1ARenOz/7o14Zi3XD2IHtEOazWne8buNZnbpUkuavsy9dLkPp6h6q2LM/nskGUunAvPUGcvs/sTaw+fUKeUQq+6KZfmC3X8urCua5oCDzihVxm1bNRM00MLrQGoS3NstFubxleHzYSl/wwBwBw++TP8NKIY/HoR28jq7oKlQmJuGPCObjuu6noWLYba3JbyfMdPZa091saRAx2K25JlDbMrFwMywBshkUUhgWVYXnZstSPk6ZJ+cSUGRY1Nec+ITVsiX2q/PkAKHHef5tKOfMl7UMUhix7CTps2fRSkvkgsGEFCBDgd4Guu3Yio7YGlYmJWJNveQhuz8pCTdjSUw8v3IRX3nwBWdVVWJPXEhOvvAmzO3VDu72lAIDVeQVHrOwB4kOjZliIGlwqoUKcOIdsEZ4HxBidxaUuFCnSkfLYNe10HAzLy0vQNWfGJbErkrYUX0w5l0vl6pwNwYZlCKKrcAxDLC9Bxi65pK7M5xDnzjjRKeygtFJKuiO7C/9NefvI92GHitdyzDBEOodL6uzq4nwwxf7oZYf0AqFwSZhQGZXaftI8LHWfnO8lubuO8bBlsrTKrN0LOCpsWmRcip1DXeRPnEvjihWoBLRldkVNYMjO4pzyPtX0wovEvDqpUAZVGudMWWZcDEM2WerApEgEwzdvBADUamFcd+6lePnNF/lxkwYOx4PHn4qIFka/bVugU4rSJunYm5wueWy6PALFeVgNxQcUtg0yK3uLKGNaDsPijMpOU9VbkDpvhC8Im28lB2VmdivRhkV5n1GMjZwxM1atuTw9odiyWD9hzSX1JWFup3YIkS4a9YBFolEgYvUYIoxKhEXqZm6idoOZrgHMqShT/QAqjaFOKLYu5FMwj4GK5asDVcxJv5BVQbzDqwNTVH77NdEVln9YVVWCXGQ2cFFC3BpV7nxhd3xuULevFdL4wZoyVJlETIkqVSKs/EukY3m+4nZuCsIIuCusqmpUkpQIH1/lQ+fTfpIqV1UF8o8/5HzR6UINYOs7gDnCid9A5XLG4OF7PIQeNYwP74ceHwTDaW9AVLMxAcBR8/EPjqIeZU4YUNS0AHEJLKaXKljaz8rqVh+61LxKmdklR2yyBqmQaaJpdTVW57XE7iaZePijd/j9/nraRZjSox9ArXrvuXMbAGB1bkHM9mH56tpVzvspv4v8XY2ajtt6VB64JBUg7IEKsAYn8TcAylWDdr46YHkFAuCCGlP9sZfRHqhETxhuKrAHLvsSMRT54o3s/7ZqkKWZ4xpz4KDU+QAwBx7i9Ol4EKgEAwQI0OjR4sB+jNq4lqffHjQC515xPc5fNBfNqisBANM798TignbSeT1KtgMA1uS2+vUKG+Ano1EzLEslaEscjO5GCTRbPcgldib9EqY2VIyQxGFWJhzJ0tpS8VBprSQ/lZLb2cJRzTQUksnlQMGN8KYUHFM+xpSuBSbBmY43hEs16Jqlax8nqoocymNtmUTNaKbuVQE2C3OFQbL3GkJanaDMnDnsbIM1E6sD4uzjUjg32CqyoPh4fJe3alCFzLDkPPd6ZrKDhTWhVy63X0Bbccsldp/J4CKzYvnuaQysTKy/ebNp6Vm5M5HCtAThWw1GzJiIqpVgaUKopB4ExHaLzbQoFX7zH8opyvak1Uvx2MdvSddrtX8vnn7vVXTe7cQRPH7DKhy/YRUeHT0Brw4+FsQAepRYDGtNTquY7QPITFhtF4d5qe1FJXd1eevBrOx8Go3KeapqMJbTBQNXJbF3Un6PqeAVwSYR81Pt7c9hWtyRjfUCnbjeJ0oI79PxoHEPWAECBPifREZNFcau+xH3fvmB5/5jNq3zPffiRd/h1cHHIrm+Du32WQ4Xa5oHDheNAY17wDJMl7sniZqOAwYLDcL0yYxZseCdgn3FbcNSHQvse/JZjL4CukuKkN3aVWnYLkMMZgVYEpvqok6EZ7bqgO130i7blaGI217xkJSJhjyUiy1BUVtiItw6ToXYSEzCjG0/JASCU4d9GyZMsmYyqPtcpWhuuG1aVCbUMRrO40qHwKzYcSrDUu1dbhbl7hcNLSFDTOo/nUExlHtOFmeVIRqPAHkCL9vyr4Rct7xOePuwtncmeHOpnrEUsNvGltWlMigOULfMmIyLF85G2DRdp9TrOhIYK/FBs6qD+PKFBxA2opbDRWo69qakezq2yFvq6qtexwCQ7MqOBsSQtpw9seewmRaNRgW2ZdEPqjAsdg71YlYKnOC3svcMERgWDYXscst0JxbT8m85+7ohKWWZsHgRHO0KOQQbVuMesAIECPA/h7OX/eA5WAFocLACAJ1StN2/h6d/aN3lsJUtwC+LRj1gUdN0hS6BaQoMw9bdao60AwhSkCaM8oq06KutjUdK92VYXqGZvKVjLw8w1RuQSyZ+SxCI9aPqvNljeHgXOWGouOuYfI7CtGA4Hn98cT0mcWry84nP7/wmyjGy9C/lK/XnhFtS0q52dPbFNfnbPtXtFah4DXptffd5s+uYE8pVVi3YPr0migMejIr3R4F1qt1aIVZS3TChO8TOldkluL3SsRHyn0q7uOreY9n7hpqFPccFF10H6nN0+72l+NeU9wAA+5JTceNpl8IkmsyYKWAQDeubtYyp/ZDbyZvV+m4N0/ne8PfV5PvENETm5cOsKGdYrG1jGChtUObWzjPsd9VOEsCpf5bHv6esrVn7MDZNnFtzHwGfb0CswhF4e7H6oFEPWAECBPjfQ2GzXPTeVYzzlszFLadd5HnM8lbtUJSVg5ffeQ5ZNVU4Yf0K3H/c6WCfT80AFyy0hklZgN8IGrdbu2HYc41MW5IxLcmD2n/2Pu7txaRfO82Dw1JHyhXzrD/rWs5+QSKm8h/fxyRz5T4s3/qj1h/zPFKPNew/+zir3HZZ+LPaz86OMSi3W3F2pdSFc335Gk5dOftcxximYzc0TaeMpulqB/6c6vN41KNanzyttpfQhn5toLY1sRfqI8p1CI2jHU31OsS/7DZiPY/rmmJf8Ol/vH/wclCHqavPyuuIWrYTV1tTZx9vJ7vvuN4Ju6+Jf7wNlT+7jNIzqO2vvBvqOyLWlV+bsmvcN2YiokTDhDXLcPzaH+XrCvW8rGV73HbS+QCAC5Z+j0sWzZbaxt3GPv2E14FHn+Hny3XufDeE75HruySnKaWWTYpSoa3Ud9TOpyZATVCTWn+G4f6z9/FjDevP85r83Vbuq7zzUtl5v2N9SP4+8bpQ3mOrX7Pvm0Oy40HjHrACBAjwP4dVLVrjlSGjAQB3Tf0QmfY8Ky9807UvHh51CgDg1lmfY+z65b9GEQP8QmjcA5aXtCKM/L4SAGctTFqBW5pzSYLsXEcybFBabGA/qFg2+Rz3sR7HcMlFeS4PaU6V/Hz/1LqkbqnRqTd3nav15ZauqPQsEov1qDO1/lzsVZXQPI8j4IsxHmI7xdOG6v3i7Re+7FDoF5J0T+FI8n7t7dG/Y9apcj3PPhZn+dVrxPOsXu0ZT90/O/wEbGqWi+zqStw+7ZOY93t94DF4u99RAIAHvpqEftu3KNd3l7vBvuLHGH37O+Vsxf0+KezJpA7bMqwwTZwdKcyKpb3fZ+9jJSbHf5vSHzWtP99vgRmr/yntyDVM7n7GnzlONO4BK0CAAP+TiIRCuP2k8xAlGk5auwwXL5yNNvtKoXuF/iYED40+Dd926IFEI4qnPnsZbfaX/vqFDvCz8ftxuqCUb3lcPLZPiDQhHsrAGQEA7nXEjmFbL1cXH8HAc94LHGkOgGT3kM5xXcspu683jV9+rGPjOYcd4wp/oJxrwomYwM+NfWnGGuxU7HPUtvDYp3pkeh1K1H0ejoTu68c5aStm2bxvQISyu9o/niY15es0eI5YDubtxeqESbm62tZivSneoodS12q+UmYivH9+x6jvIFMN/nH+DNz27We47dvPUKeHUJSVg03ZedjcLA+bmuViU3YedqQ3w60nXYRX3n8WvUuK8d9PX8TFZ16PfSlpvmX323o+mOubImQo77qTrzwoD1hqurx5+W1U78BY7zHfx67FAtqyB2IdiDiRguL9ljBGJZ7DbuNHg0xA9bI+VBvW72fAatBHOYAEdRCKdYyadq23A+7ueij4Kef86uBfz59eVu4KHGNEca2i2wjwM6rksOHZESdApyaGbN2IDmW7kRyNoMueXeiyZ5d0HBvI9ic3AQAUlO/Ff754GX84/VrUaeH4bkYpuu7bhv57NmF+dlcUpeUdnodoDO/BbwS/nwErQIAA/3OIhEJ4fNTJAABCTbQs348OZSXoWFaCDmW70aGsBB32OgMZQ0VCEnrtLsYDU9/CzSdcAlPzoQWUotveYhy39UccV7wC+VX7AQBd87fj7gEX/uLPF0DG72/AIsQtuQurW1rHuPMpUURcnwnCklTpIxg5GgyZxVACR5riE2rl6/JL8omWIndWJHUe50Z+PqlY6gRalVn5pX8ueB0raT5B1OM+fnUtbF1SvTIh1W+/3/U8cQgqipj9xa9/eJTZdWg8zaBocbzmSsvXdF/UWQfLn0273o2GEEc7udcmc06Iu52U4ynRsD2zGbZnNsPsjj3sTGsga7V/P3qWFOPRL94EAGxtmoNeu7fh2C2rcMvcT/HQUc4cLQqK7mXbMHbzChxX9CNaVu5z3XNmfp+Ybe2wajjvAF/Xy97nqnNhITBNaVxuGrCvYTpBrqTjpOuxdlMGY3Zfdg9xsBYmBsvXkMuuLDxoX8cuit97rMGj3Q+NqR92p4u7777bXuvI+cvLc6gzpRR333038vPzkZycjFGjRmH16tWHuxgBAgQIAMAZyOa27crzeu3exn+ft3IuLl4+C91Li3HD/MmY/N79eOuzf+PiVbPQsnIfavQwprXpg32JljpxQfPOmN2i56/+HAF+IYbVo0cPTJ8+nad1FnQRwMMPP4zHH38cr732Gjp37ox//etfGDNmDNavX4+0NLcBNCYIcaQDcbRXVgmmqpQghIGx8uGS9FxSsLJqbSypwCXoMonKpG4Jg+0TWZiw3wlhQ7g9RVwEUTqIhaASV5m0Q7vw+/gZgD0Zj10XulLHXFIU8lld67Hr2rPOtRjH+Jzj2w4e7MVv4Ubf5WGEHzz8DGPEioOIV3v5tSEPwmvK++W6sLeMNXNB2r4/qyvmFgyxjyj3gVRUb/dhXvc+/Vtz5/myJLEd4z3Hq+wNnEtVMVtoR2UlFKcOFEl+d5MM5FaW8/RNP3whXbImlIA5Bd0xvW0f/JDXBUN2bcCYrSsQIToe73+as+q2yiq8NAo+bEVd/gN20G5oxAlYqzAeHmbJPtbFtKyd0rMQZSFH9btBpEjUHt9TzzKLzNu9z1UH9rO4vr0acbP7GPhFBqxQKCSxKgZKKZ588kncfvvtmDhxIgDg9ddfR25uLiZNmoSrrrrqlyhOgAABAkgYd/kdePrTlzCieL2UP7VDX0xr1wfzCrqiHgkAgOTaOty06DMAwKQux2BbWg60yKHojQMcLvwiA9bGjRuRn5+PxMREDBkyBPfffz/at2+PLVu2oKSkBGPHjuXHJiYm4phjjsG8efN8B6y6ujrU1dXxdEVFhfVD17l0wlmArrl1s0zyU6QiUS/Lwt67JF0/ZqVIbADcDmWqV6lGhEx2QeUkxYWWq6Z14RidLVVvSs/F9dsiA1OkOKpcOK7gt0S+r1Ov7HhNuD5RriE+u/DYutgO8n1j5rvax3vrSLrUdY7LJqKkRXdqJnBSlRUJK6tIZSXufX7MSuxjlNs02bNS+Vxu0rBPNqmvZMrtouoCiF4LbrqkYPlYq2yy5EzVLVsyQriW7/vjai83U/FrS1/m7QH1FSSacx127asnXoV/zPgAZ6/8geevad4KM9r3AgjhC1Vesnom8qv2oyQlE691P84uI3suu51YfRkedcUXUBTcyAHXd4otokg1XVgsVXlfWfkpY0cxvFj5ckoyS4Ot8SJM86XrzjfF9Y7HYIXsmXWlP6jfAKmfQ7ou1Tx8DmLgsNuwhgwZgjfeeANTp07Fiy++iJKSEgwfPhx79+5FSYm1+mdubq50Tm5uLt/nhQceeAAZGRn8r6AgWGwtQIAAPx/3HncWXhh4PE//5Ycv8MCMt5AUsQTkVhVluHjVtwCAJwecgtpQwhEpZwALh51hjR8/nv/u1asXhg0bhg4dOuD111/H0KFDAQgjvQ1KqStPxN///nfcdNNNPF1RUYGCggJLIlEkAqppzoivjvwq02KSoe7sM1mer7QvlFt9DnaoMOlSPNdiWi7ZT0ozgclZUNLZTZTF9cyQtZdJgjTErmgzL2hOvfLlAmSJzWUPEKHqpDmbZfXHJDTi2K6UOjaVLfWQ3J06l7csX1zATz3W5Y3Ij2WSr9u+4Jo47ANCBLbFpXufWawM4kRbdqjCJkxbehZNji5WQeVzXAuIhjRnqfWG3FXVoouHKAxLLaulfZDb0LFXepfR1P3b0pc9CWm/fQ16HgrP6NJyUCBMncUJxX7/9IgTUR8K4br5XwMAxm1ejnYHduOvx1+GW+Z/ggTTwA/5nfFtm17QojIDNkP2e8pZrc1meH/XuBaDhphmxKoMyrUccoUSSsGWryfsE81YC1sEkruG2u+6B8MiKpNjNiuRWQHWN1TNC8lpGpLzqU4cG7ai5eLfAt5v2LfZ/U0GQexvkILDzrBUpKamolevXti4cSO3a6lsqrS01MW6RCQmJiI9PV36CxAgQIBDwcQVCwAAm5vlIio4ggHAC0PG4tV+o3m6y95deP+jR3HUtnWIaDoeGTpR8G4JcKTwi8/Dqqurw9q1azFy5Ei0a9cOeXl5mDZtGvr16wcAqK+vx+zZs/HQQw8d+sVDumvkR0gTRnqFEYR8mJdO3MxKlQi9vKjU/quEsOESLZOwiKgKZgxKlti5ucterFFkWqYtX2hsiXpbYPRlWoRaASwBgNjSm6aI/zHnb8g6aceuoclpsc7VOvaRyk3dg83q8jEu+4YOt9StnMPYi3ici2G5JHWlDkR7ompTdA5iJ8tJ6hGhRq1qZmtkUrpon7QP0ticIOruB/yiIUZf7AvzBRXl+7hClUmPqvZrtc5FG5Z9O6WNeTsKNmJT0WK4WJnrXPBz1XePl1Vl1R7jB1V/2NvU2lpctnAWAOC5EceD6u52em7oWJy2diGa1lYBAFKi9QCAN3uNQlFWDrSoY/NljIZHSGL9LySrYjTdYUtsgU3uccqYif3tEh/HIYjKkvXsnWALOzJ7lFcoJ247UzQlbLDWmC1LczMrL98AQGZVdv9j359YzMp6Ts3TPs08YuPBYWdYN998M2bPno0tW7ZgwYIFOPPMM1FRUYFLLrkEhBDceOONuP/++/HJJ59g1apVuPTSS5GSkoLzzz//cBclQIAAAQAAFyz+Hpk11SjKysGU7v08j6lJSMRrA0YBAHanZuBgQhIAYF9yE5y+bj5O3TAfeR6TiAP8ejjsDGv79u0477zzUFZWhpycHAwdOhTz589HmzZtAAC33norampqcO2112L//v0YMmQIvvnmm0OfgwVY0gDXsWp86/y2R3q2VaR+J99D4ovLhuVdLNWGwSQcQoWdzLTE2BiRJWsmdHAWBSGwBTTpHGLbMkw2z4IJZYQ6UrbBJEMfZuUVuFJlWpwtqbYszalrnUldMqs1lS3ViZtR+WzNkJN2SeQKs3JJ9BLD8p7r5oJog+QsWTlYtWmJtiChzYTbelS5w7KdZmFMWzbGMCYuMS0+L4/1IbsIbGly5ZqeUO1ALk9ALwbszaxMgWX4t6EPsxIZVpxegrFsWBx2I4xfuwwA0HbfHnzy8qNY1LoDFhV0xOKC9tiflMZv806/o3DpklnIrSrnl7h5/mf896rs1rjsxBvgeNnaZWB1zbw8eVpz2j3s7QqvmtskpsXfPftGzIbFNAlqMFzpwj6efoyVcU2J4yXoa7PiLMrRZKnMiqppD9un27OUwDyEUBeEUi+d0G8bFRUVyMjIwHEdb4RuB7OkiVYNmAkhXnFmgr0Ns6368bSuR3Xi/FYcAfxcoj1DNCnqI1UtwdbPAYSPiil3fLZcNxtgNHtrrepK5X1R2TWdKGm2sqxcJuXr6TWRmD+r94DlcmIJaS4hgKddde7UvbMP8jbMrgvXft7RWR4bqFj7sfbhAxf1EDpUbwR7q74JlAhqXftQviVy2nC2xHZtZoIDb9uovOX7DactXcfwfuBOO+1u71Pa1G/VAAlek+iFLdWI06aCmhBwDzqiGlAUMjzPUfeLAoavY0acAgfgehcnrFiKP875Fl1373IdujE7DwvbdMRLg49FaVomjt64Fmf++AN0k2Lgjk1oUm95DNZrOu4bcRa+6DSIt48ekd9FNj9Lq2dpE3rEfgftrcbTdqNGWdq+qGHw9xZR+xjuNMUmDCtOVF5Q3dl93OkR0gXVn+CIAe+BCrDUgH4DlfoNcL4TcKucNSAaqcXiT/6B8vLyBv0Tfn+xBAMECBBAwRe9B+CL3gOQdbASA7cWYkjRJgwu2owupbvQqawEncpKEI5G8c8Tzsb37bphfU4+7pr2AR+sVjUvwN1Hn4st6YcpQnuAn4TGPWCFQ6Bhm7KGHerqMCpZPeWS9r1UGC6XXXvrUkMQX6cLBnXtK0oFiZx5mhqypM5EQqIYw4nmZvgmUwUxSZsojMugjopHcbV3pHEPCc0vXA832sqSk6kTQcqyLxt29gFuVmuGySExK3ZtZ5+sAnTaS8nX4OjkeFv6MCwGQTp3LSnEVD68jol0CWuutqzeZc4QKpnl2lfiqPrYzVl/08Tgx5D7hasvKWyPKizDC+42ZltRJajkeTAqKw2edqRseG4djYayFRxruAONj5YjHoZFlf6+NyMVU3v3wjc9e4MYQNPqSlw0/3v8ac436Fy2C2YIGLJ1I5749DVk1NUAACKajj1N0vHhh4/wyz89YDxe7XO875purC1MQcfOSL9L+65MKSARAmr7ybumpbBviqH0pjicp1xBbxnbCTkqQXGqirVPcWAT0lzdH2bOFUp/4MzcyXeFYdMQW2Wt4Bd3aw8QIECA3yr2pzTB1936AAA6lO0GKMWZK+bzwQoAwqaB0YVygO7rlnz1q5YzgIVGzbBoWAflLMphVY7tys+OAjmte0nqbCvrXOMKC6MYu0U7iGqzcpgWO9k+h4fmsdKa4QhKIusSz2UuryLDcu4n2zfiMl2qzhYK0xIlKNVmpUpZrjoPHQKzEm1YCrNypHrF6YKlNeoWy1RHCRWcjFJILu6AIx6z9lLsLDAc5m0ypqWwGC4bCwIwd6hh0x3sc7mvh+JYQTUKTWHnnKXrSppPs3C3uV/QWzlslP1bcUhy2bAEm3Asxxnp+l7OMyrrctnVlIfwoJBHrduAi+d+j6ePH4uVBQXcJ4HHhTUd2+aW3BxENA1pdbXIrTqA+044DfPbdUSI2X/ttv7HjI+ke7wx+UnMbN0T73c7CrWhRKWwFnTILAsQ+4PcpqLtmDlScduSIduwiE/oJvmCcpqqDEsIuuAKBuDjsi7aq1y2KtWGpdg8veyTlBCYh+DW3qgHrAABAgRQkVtejqfffAPptbUYXFiIi/94FVa2bO17fCQUwtZmOei4Zzc6lu3G3LZd8UG/YY6ji+0LsSUzF6989Cw/r8eebeixZxsuXDUbk7odgw+6jEANSfolH+1/Ho16wDLDGpDAvAPZVnMxK8PljSanqcSw3F4sADylu4bc2lV9NqiXd5nNgJT7seP4Om4ahaawPcLm+AkeatJWI4LOm3qWzSmz7CItPTPbqmFVmK0hJIbvcfLkrX0NgS05ru92nr1SuepJZtruwJKXoOodyBmWbK+CRh0m5VpmxIdlShOHGTOVde/CHAMrn7WJ5tgdiHIfdz6ctGJucKRvucyi7dPpK4xFK33L5SXo0WF9vARlrz2FUfmwI0fC9mJOfue4bY5uL0Ef70APbQcxKe778AOk19YiqmlIr63FGy88j7F/uwWlGRnc7ZyYTj113bkNHffsBgC8NOkFvDh8NF4ePhrl9vpXhABZVQeRW31Aqrqnh4zHSesWo135Hly7/Cucs24OLh9/PXY1yZJYDl8fkRuhlTZlW0OzjzcdGxazXbH3l3kJqjboWDYsxa3dNfFfDGTrslmxtlfTRGBd4HnWudb2uhWT0W3fNvx11GWoSkiW2brwXY3l6KiiUQ9YAQIE+H0hHI2iPqy71VpxYuKixTh2zTrU6TpuvvBcPPX620ivrUV6TQ1KMzJcx3cu2YXPnn1Cyrty3kxcOW8mirJysLB1B3Qr2YEeJduFqDQWdqRl4ayzbsXYwuW4a/Z7aFZbiVYHy6wBKwAuWDcbAHDLok9x94jzDss1G/WAZSboAsNy7FZGgiLdM8ndZU+xtp6TWFVd60+wYbnmZQlSHd+ypUE4K1I8C7mamQi/4XmMJ+NidjSu81bKFAPukEayfSpWKB6/uhZZlakwK9XewZiVOGdH9Q5ESGVWylango1A9qZs0IZFicNEeSge+ySDpdn9BNap1JupsCVuRxEZl8Kg2ORjHoqHzc9iz6ALfUZhVg6zl5lV7OC3LO3WMPh6znoEkQYUhqU5efKxbmbVrPIgvnnkIaxpmY+rrrgMlYlJ9j6VGatltvbnHijHXR9/BgB4csJYjNywAQAwq3sXbCjIBUB5HRWUluGJt95B/61b3ZVio+2+PWi7bw9Pr8ltiTntumFw8Sb021mEASWbMKXrAMzu0B2J31oNtK55Sxhh4j1P01Vum1Exu6VtpzI14gS6NlgFmnL6MMynFAMAOJ58biZlpRUvYA+tippmOHHLEjw0/HRUhpMDhhUgQIDfBzrsLkVmTQ2Gb9qMV59/CZdd8wdUJsVpE6IUD779EdJrarG8TQG+7tsL0+59FADw7xPH8MNal5XhT9/MwMRFSxDyir/ngTtOOhuzO3bH3pR0kChw9OY1+O/HL2HQ9s0AgK57dgAAdjVpigNJTQ7hiX/fOBhOQlqkFgBw7prv8VL/MQ2c0TAa9YBlJuqgiTazEliVn+3K7YXmSIi+DEu1XanSkgeoH8MS52GpW86SvBkXNHDvL7ZIHD9GYVZ8QUeTClK3kyeCeLyzbjbpbdcT51f4zsnxsxuGGrZZObpxtp86XoIhN5MSt4xREo06rJU9FlEbxgeUOEFOXcFO7TSTeA1+CmcExF6KgretndY483K8CNkKE76eoKzOhbbXFDbujnChMCvxcZX+69fP5WC0PozKK7ySX0QSXzuY07YAMLCoCK8+/yIu/dMfcDA1US6zB0Mesr4Qx65aBwC459wJuGbatwiZJmb16IKlnVqj9Z4y/HnKDEycvzTugervp5+NDwcO4UuKkKjVPovbtoNBCNocKENO7QF03bcdgLX4o8mWyxJskbxulfeJeYLyuYMRa7+mUYc1RxmDsirMN3JNLKiRahTbFtWIE7Ra9QD28wD0fOfltMGNd8DZ677HC0PGuL4dFsOKX/0bzMMKECDAbwo1YUuSGVi4Fa898xKa1NQClKLPlmIM3lDoec7WnCxUJFsD24vPvIGz5y0GALw/fCAeef19zLzzEZw9bzFCpomZPbrgtJv/jN4P3ovNzXN8yzGscKN3+RISUNjMWg5p4PbN6LF7GwBrwApgg1Jk1lXz5NK89oflso2aYRlhDRpjVgKrcsWo87FhSbYRRfJzLSzHJU5HomnYS1CRcD1sWEzqdXn6sbk0zFYixBLkYgZnVrJkwz0CTScWnsu+cSg2LB+GZYrzK3zm3bg8AT3iAnIbli1h87YQvAMBACHq2KrYNiTPS9EYs2LsRTed34oNy8+uLwaidRiWXVZb8jVNptO3pWPeThoQleuLrxBh389hU+w46sQOVOpaUxiWw8QFtsX7lMK4XJ6gHs/qsqvYW8Em52/Dsp9HzQ+5bVRuL0HFFqlT1CdZF0iORHj5BhZuxeq/3CmV+c4LTkFNQhht9uxFu5IytC3dizale9Gk1loOpFmltTyISQjun/QxMqusScAze3XBkxOOx/L2rS2vTxO489xT8fZ/XkJVQgJS6+ul+/TcsR1EM9Bx72702rENvbZtR48d29F1904kRa0G67xvJ7qXWgxrVX6BM6eQByaOpaGwq5j1D2ZTMsDnYfHvAJ9bKduwYjItlweowprEaCbqAqsejAqQWZSfViWBRnD3rHd5MeYVdMHfxl8EI0Tc31firLoSDxr1gGUmElDPAcve38DEVLGi1SjfrnWVPAynaj2zXTyfuj8gruCp9gBlCB8iwBnAIKTFwcs6V37pncHO+ZA5Ls7sKxxDTaQ8iNvV2efFEwd8wbVZLJuq3jPDwgDlUtnKaj+uKgpRR+VnD1RaiA1GdtqOas0GJ02jfJ/OBypFLaqkRTUgU1fwLR+wrHMMu01MvuI15W7DfBBTJm5yVSFX+xEnLA8bVO1zHecLeyu0tfMxswvu69YOf/i2tbNVPzLSAEUpcqrL0WnPbnQoK0GCEcX2rKbYnp2F7U2zUJbexFKL2e02sGgz3nrmBSQYrIMfOu55+/O4jtMoRWZVDZZ3aIW7LzwZyzsWACYBgWk5zxgE7faWAQAWdm6H0avWS+e3L9uDH+/8PyRFoq5rH0xMwsr8Aszo2gOXL5wJAFjZqhUM+9ujcZUXBTQgOVKHvqVFaFO+BzNb9cLelHS3IMjNARSazlSA9mWEgNZWWi7PIU0K95ie4g4GIB/rFejY7UgD5FSV44mvXkXP0m28HA+OPg2RRN0OzcQKDH6fwOkiQIAAhxeUovnBcnQo240O+0rQsawEHct2o8OeEqTX1fqeVhsKYXtWFrZnNcWOrCxcMO+HX7HQwLujBuKuS05GXSjs2qcbBi6YNR8AXIMVQ1IkioNJSVjVsiVW57fC6rxWWNWyANvSs0E1DUM2bQIA7ExvigMpTaDZ5DC5vg59dxVhcPEmDNyxCd1LtyFsG0DbHijFo4NP/wWe9sii657t+PeUV5BbVY4DiSmSSvBwoVEPWEaCBqIwLDPsZlYu92lBdQEwhuBtFHYH3vR3iabqDy+VILsM48FcSpYZlzMp1D5BcLpw1IeKRG3I0hcxIRji2YPIj3FoDMtn6xWKx4dZiSyKupwu7DYIK8xKUP9pjFlxFaCVDoWsSmHMKsQYl2ZCZ2zLfmhdk8VTFzO2YQoqQcPW4xmmkrYlYcOue0MjvC+ZUca6GFtiafsGgspQVRM6obnsQ1VHG80pMGfjh6j+zaypxLGbVmHg9s3Q+crUykGEIu/gAXSMMTBFNQ1bs5phU24eahISkH9gP1rt34e88nIkRaPoWFqKjqWl3oXwwe7MNOQeOHhI53ghyYig7b4ybM7PAey1lzTTxC2TpuHM75ag2UH5o7qoY1sM2lQEAPiyX288eso4FDW1Bict4rBjq84pethMojC7OYZtXY8hRZswqHgzeu4qRtjHuePs9XPRq2wrbjr2cpSlZDjvPJ+6ILMta8u+JbIbe+zAxvYPl9pXVuVZodWc34A3o5LOUbQqx29agX9Nn4TkaASFWc1x3alXYNI7/0ZmbTVoGDATbLaufk81x2M/HjTqAStAgACHBjZInbBhOQYXb0LIa+E/H0SJhuKsbGzKycWmnDxszMvDppxcFObmoD4Ukr0EQxThaBS5B8vRat8+tDywD632WgPZGQuWNngvv8FqX1oKsg7GL7mfNmcFTpuzAgDw5dCemN+9HbbmZuGqL+e4jn1m/CisbNuKD1ifD+yLLbk53CYpIqWuDv2Li/C3byYDAI4qXI+jCr1Zmhe67d2OkdvW4JMuw+I+5zcJSvHHRdPwpwVfAwDmtumCmydcjMrE5F/kdo16wDLDABIcZgUwt3ZIebGkfACSblVc+A9ws4kGA6cCAsOST5GcLvgaIXaa6aYVZwuRcfGJworNyrF3qUZ4QfetSt/K40jFj8MQz8rEyuPl2gx42A0FxwovpwrrGFNKi/YqTbceNmTn6Yxh2awpxNL2cTqhfB93vlC2fjAFGxZnVEo6Yhsfo5r14IauOWyLBbBlqzCzPsWYlmDb4u2tuMBzd3Zmu+NtTtz2T7+2pYBuGnho8iSMXbdCGqTW5LbEt516oiIp2S4TO9nZ7m3SBJty8rC5eXNEQiHPSb9iGa1pIhR1YR1b05pia35TQOtgHaRT3HHRaVh7nexIEQvLO7fC18O6Y9qI7tiVk4HU2lp8f/GjSIwY2NoiC2127YvrOifNX4WT5q/y3V+Sk4Z2Zc5EYejU6ouEILOyCl888B+k1NWjKCcbvYu3+TIoLxiEQBfsTB93G4LJ3QbCCAm2aT51AW7nK9X2rSwXFBOqDdqlMXEvr+TFqKx8liZIoPW4Z9p7GL9hGQDgzQEj8cioUxANs0Lbzx62/qABvXcU4c+zpiKzphp1oRAeOeEkLG7eIo6HsNCoB6wAAQLEh9T6Ohy3YSUfrGZ36IYHjj8NxU1tt+4YamCXmvxnojopEefeeiXeffhF32OWdWqFr4f1wNdDu2N3bgYAR91bnZyI7wZ0wpj56+IerOLBKT/8iEEbt/J03y3F6LV1O4atL8SAQie/WZXlhbgjsylaHtjP8w1CsCMzC8VNs7G1aTaKm2ajOCMH29KysSM9Cxct+Q43zf0CAPB+j+GedrXGguyqCjw55WX02r0NEU3DfceegQ/6+bPFxEg9rv/ua1w6f7Y0cF85ZyYWn3F+3Pdt1AOWkUBA7Il6Yhgm1UswlpQPOBIh+w3AveifGh4mHrCAspzdEGeZA3Wyp2qPUiRqIkjU6mRj6pLChO3P8Bzjj6F6SireYtC83JbtYzhrcuerNituqwozRiXbq/SQwZlVmDEthVGFNWU/MbnNSmVWamw4FSYIojaT4kzLrgyWH7KZVdQuR8TQONuK2t6C0aiVJkRmWsyzEFHNdzoFUe2VAptpMDST0NYHwim48rw/4v7J76JV+T4cs3ktdmY2xaPHTUBVYpKHrRYApWhWXYHW+8vQdm+ZtS0rQ+u9ZWhaXY0pfXrjxVGjsSfTiu7g2ByBjJpKTHriBaxvlYd7z5mAfZmp1mXtetrZIt233qsTw7jg4Su4d2eiHS49wYig35ptOGrJZoyZv873/J8KcbACgGumzvY87uYLz8b8dh2xr0kqhm7Ygj/MnoXhmzZBpxSt9+9FRk01eu0sdk6wqyXRcNz1B+zejLW5BQAALapoc7zedXXLaZLTh/myRi47pMLg4mBYIqNqXlmOASWbMXDHJgzYWYismkokRiNINKI4kJSCG06/FIvadJTOTYhGELY9QfuUFOHpD19F+zLLjvlxv4FY3qYN7vn0IwzaWsinpsSDRj1gBQgQIH4sbNsRp1x1C/464wtcsGQuzlsyD0dvWot/jj8DlUlJaLuvDAX7y9B27x603l+GNvvK0KSuzvd6V86ejQvnzcObRw3HC6NHoaypE5bo6DUb0GP7LvTYvgvHrNqAOy4+FSvbtMSEJT/ipIUr0atop+91U+oiuOeZz7G4V2tsaJuLvuu346ilmzFkxRak1tR7nrOtRSYKdh34qVXjiw9G9Ef34hL02GaVtyYcRts9ZTh37kL02ertWJFRW+PKUzFo+2a81XvU4S7uYUFOVTkG7N6EAbs2Y+CuzWhdXuZ5XFlKGq47/XJszc5GRk0VF3rCNIJn3n8VqfVW33ng0/cAALvT0nHnaWfi2249oFEDt371BTJqatC5ZBe8p4O7QWhcK/n9tlBRUYGMjAz0uvw+kFRL9y7ardxLr/tL+TytLk/B2QSVt6qO3wsqi2Eijan8hiMdQ/UC82BeLmmbH6OcI24P0XNMegwvqRtw2fW8Jg67WKzKtASGxSf/KjYrPSTbq0IhgzOnsC2pJ/A0Y1j2ObZ0nqBFOaPinoOIbcPic67gnocVtR+o3t4yWxZLRwwd9YbNsAyN5wEO0+Jzt+x8M0q4XYv1A6c/KHO3mL3SFKRwvzZWv6WC6D20cCPu+/Q9FByIrVIzCcGOzKbYmt0MRTnZ2JqdjS052dBNE9d8+y36brW85CqSknDeTX/EqtatAJ3ioTc+wLlzFvte1yAE83u2w6yBnTFy+SYcvWxTzHIw1CaGkFQnz4t647whWNK/Df59y/txXSNeXHPj+ZjVtzNm3/AYmpfH57E45ua/AQBfQ0uLCu1kAB3LSvCfj19DRWISRl79L5ia5kwa5x6BDbzTcNuwfmpgYwDIrinHwBL/AcogBOuat8TanJZIidah2+4daLd/Dw4FH/cfiHtPPhUVTVLse1O8/NJLGL12He44cTzum/IVysvLkZ7uz7yBgGEFCPA/ifntO+HkP92CW6ZNxqnLl2B/SiqKmzVDUbMcFGVbA1NRs2xsz26GurD1meBqc/tDN7VvTxyzdj1u/WIKemzfieefewMn//167MtMxUmLVvrfu1tb/OvyE7GhoDm0MPDmhKEIEQMjlm/G8/dM8jzn9bOHYHH/trjh+W/RcYv8sbz4nQU450P/wfHn4LwZi9C8/CD2ZDTB/tQUpNbUYX6XDpjfsQO2NM/Bh487Czp2ffABRG0bBR+wIsT5bQDFTbNxMCEJ6XW16FVSjJ3pTbE3KeMXKbsfmtTV4KjtazBg92YMKNmM1hXuAWpjs3zsSM/ClK790Kz6IMZtWI4zVy045Httz2yKe045Hd927+FSVc7v0AGj167DwMItcV+vUTOs7lfdD9LEiuYs2q34/B5XJAWVaQnzfRSbFY+ooCkiDJs8TqibZSk1STmbsiUb6vyGwqy4pKRK2AKLapBZKftFr0QG36VPxHL7eAn6MiwPG6AagsfTE1D1Agwrnn8h2U6VGI5yJsWYVaIeldIJtrjKvQaJ6bAuwmxZcqXoSiUYnFVpnFlFuO3KZkt2ut6wHowzLFPnjCrC2FfUPiYqMy/GuExDg8lYl8q0WFptY4MILJ1tFfbOHigOeyVV09ymRl3trWoj0mur8dn9T6N9aRnmdW2PC2+5HIVX3BHjphYiIQ2lWWnYnZ2O0hxre8lH8/l+kzivpYr9TVPQdP/hn5gq4pUJwzDh+5VofqAS//eHU/HOqMEwI1ab6XUmCq/+P37siX+7EWtatYQWkRmxFhV+R4B2ZbvxzmtPIbPGKrtBCM674EasyS2QvH5FtgU0zJ7jfY/T6qox6dMn0PKgw6wNQrAuuyUWt+yIRQUdsCa3APd9MwnDijfEXVebcnL5IpgMe1Ob4I6JZ+DbHt0d71LBjtZ7azE+f+w/2JaUhNa1tQHDChAggAximhi+eSOybE83BgqgOjEB8zt0RFW8S3rYqEhJxh+vvRifPvA0hq8rxD/fnux77HtjBuDopRvRfP9BhKMmWpaWo2VpueexfoMVgF9ksFrVsQV6btrF0+dOW4yUOstRYlnn1gCsBSavnjIbN38yjR/38CnjsKZVy5jX1kwTV8+ZgRtnfSXl65SiOpx4uB6hQfx1/mdoeXAf9qSk46tO/bA4vyOW5bdDRbKlqks2avH6B0+hS9muBq4kQx2sAKBZVSX+++brUt6etDQsbdsGe9NSUZ5i3TOj1j9SiopGzbC6/vl+kFSbYTHWFIa0pDoAV8w616J/OhWWpbDtKSymG49AQKVtPFPMeUw6lm0SZwFAxrpUpqXGhRMYV0OMyuV5aBLfYLuHNn/DOy2qiJx5VwrTUuMB8qgVVLBVedusEkI2ewo5rCrRzuPMSvNmWImaY9MK2RXHI11A9hr0g0kJIvaDmPYDMqZVb3emiGLTqjdC/Hedzb7qbIYV5YzLsXcBFtMybCbFguqaLIAum2QVlfsNTKFvxOElCAAt9+7HQ++/h+Gb/O1FdaEQZnXriil9e2NGz+6oTEl0pGLXIpn2SXb+uGU/4vn/yCq99a2bY+rQ7rj+/VkAgAW92uLPd5wDM4kge18lWu4vR+6eCuTtrUDzPRU495MlvmU70vjPGaNx/UczXfnrWuahKLsZippnY2uzbBQ1z0ZR0xzsTk8HMXV0L96ByU897nnNee064w/nXA0ACsOyfrvfafs75PEe+3sJWpujitfgqSkvwwTBpROvw4qW7azjNSAlWovHv3gNw7fGx6rG/flvaFpbiWaVlWhaU4msqir8ZdrXcZ2rogJABvD7Z1hmGCDKJGEzTIUo4PLH0uujCQBEp85AxUL+8NVh7bQr0rf/x861hpJ9qGkS3pt4tG8+GVj5QAnrK1kFoHxiMI/SrayH5IRvsc+V1sOCtM8VNkosP1clUKUM9n7VPdZrWoDuV+eOy7quDFhMBagOVImC+o8NWEm6Jfkm2ANTouY9kIWJgbA6YDHVYBxu7QYfqOzBhU0Ytq9fZw9cYXsbIiZC9oDFnT3s+7EBTO1DhFBoigs8k5T4WklKQF0YBBo1cMqiFVjWtgBFzXNcDj18OoVBccHc+fj7Z18gtb4eNeEwlrRr6/qwtdy3H+33lOGElatwwspVqAuFMLNHF0wZ2AvT+3RHVaLNBFThzk5PH9YdzxQfgz996riDEwKYic6NhqwswjP3vYtb7z0d5fkpqG6VhI3IRVg30G9psTRgfXhBP5TlNsHVj7ujUhxOLO/TCkbIUv8OWLbVl9l5DVYA0HVHCbruKHHl14TDUuR5hvvGn4IbZkxFk/o6vDnkKP7t4qtNe4RhU0OseUbkpxRPTHkVX3QdiBkdesuqwNpq3DH7AwDAG/2PwbLW7az7UIpnP3kRI4vc0wQ2N2uODnudkFq70jPRouIA7p5wOjblNwfVmlvX14GJixZ51k1lYiLmdOuE8cu9J2zP6d4RuxPCwPK1nvtVNOoBK0CA/2X021KMJ1+1lnE4+W9/xso2rV3HtNq7Dw9N+gAjNlisamGHdrj1vHNQ1DxbPpBQgFJ027ULJy77EScu/REdSvdg3IrVGLdiNWpDIczqZQ9e/bqhKtlbjfXkWcdJA1bTimp0t9Vs04d1wdDlWzDox6145M6Pccs9E2GkhKAZJi5+8wdc9OZ86VrTT+6Gv/+fJbUXds5G5r5qZJUdXlXgnfefjLlDOwKwGO+VL8/BRe8eunOBiMLm2Sgo2+c5WHX710OYuGgxmtTXYVtmFmZ17h6ftiMOPPf58xi2bQOO3bIKfa6TGd2tcz5DblUFijJz8PTwcTy/3f5S12B11qV/waqWBUiur8O0Z+5Ds+pK3Hbaufik32BnFQtY4akmrFiGcxfOR59tTnR2kxBolCKiaTjrpmuxpnULDNxchI8efRYqlrVvjUfGHQ1cd3dcz9ioBywzJDIsx6HCVCak+jIrYWJqrOUprK0tTdr3jqVOMlVVoLA0BQ+mypYGYctVsHNUiVpzJGoeUYerZGS1ootxiROVeVnkH/EYa90hmuRyyAxLURf5uazrJkJhpgKUXdOTwrKaj7GmJD2KpJD1EUjmDIupAL23IsPSFacLvYEvhQEiqAJtNZ7mOFew6wNAHXGcPFSGVU+8mZUzkRmIKmt0sWNMPtkY9pb1E4IDGU68tskPPYWIpuHr/j1RH7Lupxsmjv9xDZrUWazqwdPG441jRoBqGqjLam9t1rRtgTVtW+DR08eg2/ZdOGnpSpy45Ed0KCnDuGWrMW7ZatSFQ/i2bxc8fP5YbM1r5izfYrf9/J5tMXRVEQAgZ38l+mywlpD/+LR++PDsAXjs9g8xcEUxHrvrIzx8+1jcdv9U9F1mrSk1fUJXDJy3FZn7avDcuY56sf0G77lAPxf3/N9kLBjeFi9cPxKV4UTfwerzMb1xyrQfeXphtzYYvNaZaLypRQ467tqDjS2a4/h7/wK9Hmi1dz/++c7nGL3GGhDeHD4cozeswX2fWUznq159EE10VP08WhuB8/Fg75Ey8V9lWAnRCIZts9R55YnJFmuzrzeiaC1OXWsxoDvGn4ua5AR+7cLmOXjguFPx9xmf8WdpVlMBMwxUhRPx4shRuG3qF7jmu2n4dEB/0LCO7ju245yF83HKsqVIU+bp/Wfccbhozg9oWlWNp048DmvatgA0irpE653Y3iwTox+4GX+c+h1alu3HO8cNBAkHE4cDBPjdozBPZklh08TJi390HbegYzvcctFZ2No824mQ0BAIwdqCfKxtk49HzxiDbtt24aTFK3HiopXoUFKG8YtWo9+mYlzwjyuwtWWWdGruPnnOUu5eK72uYx6MFB0L+7fF6O83oP/ybXj3rJf5cWt75CG5qh6Z+xqeePtzcdnXl+DkN1fglHd/xJB5RRgyryjm8eJgde4DV2BJhzZovq8Cb/7zNbTfVYbsikoAQKddpbjk2x9QmpaBTrt288EKAC6aNw8XzZvH03ubOBOtfy6e+fQl/vvUS/4m7Ttqi1OG22d8jLf6j8SUbv1QnxAGJRreHHwMKpOScN+X1gTf676biplduwOE4J3Bw3Hl97PQZt9evPXSswgbBvpsd9hUUXY2wkYULfcfQFVCAk5ZvBxNq6qxulU+njnxWM+y1odDeOaU0VaCUKAmfqeLRj1gUR2CA4WVZy1bITMsL/sJIC9RwVyp2VZdikLXvKVjL5iKDYuvvWZq3GWaMTe2IKBhyAFRvSRqKEZ2NXwPty1xI7xjw+J5irE2JsfgjIoqaXsrsCnXSsB+Cy0KwWsZs0pUbVf2Mck2m2L2qiQ9ypkV2yZqbCszqyQ7X7ZhMWZ1KE4X1itigLm32w4VNrXnLvN2xIOQaUCzV/HTXUzKO0QUAUAIC9/E+pk9ydiu+2iUtYHDvPP3HYhZfgD4qn9P3HDFuahLCAOUgrqWIVa3MkMmGgU0inXt87ChUy6eOPc4dC/ehcee/RBdtu3GpHtfxiunDsfUYd1RltcE4UgUrUu8JyO/cf1raLXDv8zdVpcAqxt8pMMCPY1i2oXdMOaLtUgr94/moWJuv/ZY26MFQlED+5qn4pI7L8Gcax7jqxoDwD2TPo/rWu8OHQoz5PQDkwCt95bhmlnTkRSJYmGbDlhU0AFbmjVH9z07cM333+DfR5+I4sxsXLlgBkYUrQco0Kz6IFof2AsAKE9Kxp5M2XHhuaPGIMmox4Q1S9CtdAfu+/pd/HX2ZHzQbyjeHTAcuzKbOrZnAD13bccxhWsws2t3tNm7B82qrMF44NYiAEC9rmNq716YdNQQ/NCpA5pE6vDWUy+gb9E2pJZZ5bj5srMQTSQATOtbEHI0VFrYcOx1hAKRgGEFCPC7Rss9+/HO/Q47+WpAD/zp6vMxauV6nD97IUb/uB46pRi/dBWGbLgfHw4fgEkjh1jLZfwcEIK1bVvgotsvw5v3vYIu20rx99em4u+vTcXyLi3xff+O0H2WkI01WP3qoBSDZm49pMEKAEYsK8SjD36IXU0zkFxXj5FLvD0u9zVJQUpdPV+t+LrLL8DTr7zN95/x5+tQKUwfSKqvx9UzZ+DK72fy1ZhPWr0MALAnNQ05VRZLPX7DKmzKzkXHMrcbOQCcctnfXHn7U5rgrvHn4LHRE3DGigU4f+lc5Ffsx1XzZuCKH2ZiWtdeqE5MkM554c2XsTK/FXrt3C7lb8jNxfnXXoO9GU24kFqZnIRJI4aib5HDvFQizyafN6mptc0RcTJ9BY3arb39nfcBfOKww6qkJdUBX2bF3Kh1gWGFFEblMKyfbsMSl6hgrItNHjUUr0HGtHj4HtPxDmMsyfEk9HGFFyeQ+jCrQ5k47GJaakBgDW5mpfszK2trHBKzAixW5TAsK6acyqgY40oizIYVdduw7ApTJwyrMCiBaT9svc20uC2LMS3bxavW3taZIe45WGNaHwHmHVhjM69aO11rp+uMEHdxZ2Gd+CRjV7/QkL/nAN6861UU7DnAy7q4U2uceaflHg2TIH/vAZw1ezHO/W4RWuyv4MftbZLqdnu2cSA1BVfdeAE25zfnbU406njIKraqtPoanDZzBcbNW43+a4pjzpv6vWNp5wL03+B8sL8a2AMZVTUYvrYQU/v0wOBNW9C0ynIYWVHQCqfdfKMVAYNSjP1xNe6Y/Bla7d8vXfOHdh3Rv7gIiYYcioqhXtORYBo8feU5V+L7Dt1cx524Zhn+MG8Gnj16LKZ17Q2dGhi9YTUuWjQHQ4o2x/V8RdnZaFtm2RG/6dUDXXbtQmqtNdhnV1a5jt/XJAXHPnQTDqSlgGgUOfsrsPDPDwEAhj77N5Q1s4MhE8CsrkXhpff//t3aAwT4PSOpNsJXoWUDVrOyKrx035so2HMARXnN8I/LT8ab97+G7sW7oJkmjwC/s1kmnjz9eDx1ymiM+nEDzp9lsa5mHh8XhuyDVbj7zS9w0a2XOd4fMVCdnIhJJw7GexMGInvfQZwwfw3GzF2Lfqu3/W4Grykn98SJk/3X0GLourUEi7u0xsD1VpT28Ysd3eYJK2Q959MnjAEAtN2zBw++/z4Ge4QmqgmHccll1yKxLoL5j9zJA8mKYIPVR70H4/HRJ6EuFEaqvSq0oWmoDVsC06krF6Fb6U489eFreGPQSDxy/MmY3rU3pnXvjS67d+KCRd/jnCXzXdcXwQYrABi7smG9bVpNLTKrqnEgzZocfPF0x5mla3EJvm/WocFreKFRD1im7nifUXEycAM2K3WCqq6ZzvIUusyodMWWFc/if2rAVM6qCOWMitvCbAbEZCjHhsEkavuacJagMG2mwOxdnGkp3nzQHG8izqMVdTH1ErfVRSp9GBY/Tpp4zRiVP7MCLI9AlVk53oBuZsW2jFmlMIZF/BgWs2FFkeCyYdlt6ooOK8OgGrddhal1DcasGONi1+LXJqarbzQ038s6Xz7m1K9X4LanvvZVrxXlZeHCOy9FadM0VCYloEltPTrtLsXGVrm8nQgFaIjg24Fd8e3ArmhWXolmtnOAiqyqarz+0KsYuXoTjv9xLb4d2JWXS/Wc9Vo0s6J5Cj45vR8+Ob0fWpUdwJ9fnIlRs/0nod761kT8/cav0fQwu6l//Y8eaFZYiUFvb2344AZwyeeXoLxpCvZlpeDC1xfGPDalLsIHq1gozs7C3G4d8JevvsL1X8/wPS45EgENUXTZsdNzsBJxxo8LccaPcvkMQnDfCadjSo9+aFnu2BQvXjQH/XYU4cazLsa27Cysa9kCdxSchS3Ns3HbV180WH6G8278I1rvLcNDb34MAFjZpiVuueIMGBoB0SjKMprgQNNUaKBoWlmFS775gZ974qKVmD/ImrRMCIVxCMuLHKYl2QIECBAvEmsiSNsf2xMusS7iO1itaZ+Hi/95KUqaZcDUNMt1GEDPQv8lOwBgb3oTbGiVZ/0VyH8LurXDK+NGAABuf/srhKPeaigACEcMtNhTDvhYE/J3HUDvH7d77mO45p7Zh32wAoBx964+LIMVALx+yuv4dOR/GxysAODBS8bixdNGoLh505jH7crMwDf3PRZzsBKR0sBg5QedUowoXI/PXngEHcpKUa/peOqYsdifnIJeO7fhk+cfw9jVjufjnM5dUJkQO0TUP848HQBQkpGOeV074rQFywEAUwb0xCl3/AlrW7fgfWtfuuMBefmUuUircZ7jtNkrftIzAY2cYVnLgtgJMcJCyFva92JWgBVRQV0AkO1Tl6Rg+YBbKjYVtqIu+qdrJl+Ogs27idpMis3BYLYtdc6OQShMZrsC8yi0WSXzHGNFE2bH8yIp8zqIuoPtFx6B+jAt15IrOm2QWTGpnAevDRm8rlm0iiTdm3GJdiuVWaXo1ovAGJXoHWhtHYYVts/hrEilmzaY3cogTqQLzsqYhyHkfqLRhud2mSDQoiZuu+ortNq8HysHtcT007ph3rD2qNJsW6wdzeSLk3vj1G9WoFPhHswZ3AG3/G0iKCGIGjrqwzpMQ8OgdUU44Yc16LTDil7ebftOfKb3BmV2T/u+MU11gqfic6cfjbPmLEG7kr24eNp8vDZhODSNItGIoOemHRiypgiDVhWh39ptSK6P4t7rT8SnJ/SV3p2Tp6zA3578JsYNLbTbsLfBYxoTqtIT8dnYPnj0gjG49Isf8PfXp3oeN2STpf7bnpWJKf16448zvvO9JtWBJvXegs0H/YfgrKWWmm1Lsxw8dtxJ+POsr9Gl1Iq4UaeHcNwGS3W3Obs5bjrrQqzNb4kPBw7GEx+8if7FW/H0u6/jteEj8fBJE7CuZT6G/eMu9Nu2BcM2bcY1337ruue9H34CAFjQuR2GbtqEYRsKUa/ruPeCk0ATCGfizANQ00xkHqzGJVNldWNC1OCaFgLH3h0PGvWAFSBAY8OQr7ag9SbLuN5n4Q70WbgDl2WlYOqJ3fH1ST1Q3LwZACAa1nHfLePx0nVvYeTCzRg1fwO+Gdkd3Tfswglz1+L4eWvRYq/jTHEwORHzev00uwBDZUoSHj/neNz/wme4/Y2v0bLsADptL0X/dcVIrnczrolfLcOnJ/Tl6QHLtsY1WP0ece9Tk3HvU5OxNS8LbXzc+kV8OGwg+m+OzQRPW7IYj77/jiu/XtfxwLhT8E33Xnjgk3fRbu8ePP3+a9IxzFGjKCsbl198FXZlNgVAsSuzKS74w59w07QpuHLOLFw6bw76Fxfhugsvxo6sLHzfpQu+79IFk/v3wZRHn/As1/zOHXDj5OkAgPeOHoRdzTJ9n+GyKfPQpKYOa9rm4Yfe7XHF5/Y8NErjspOqaNRegq0f+BdImkVj+ZyrkMlnTjMPNYdZeS+rLkr74tLqgNt2FSIiw/KR0G2p3LQpibjMurrEOvMOM7j3IFsYUD7XMDRueGdMi9vIDDniBfciNOGKL+frIubBsDiUuTkqwyI6dZgVY6iKzYox1UQhioUayDYlZLGnJGWuVRObRSXrEaRo9jE2k0rR6qS0Y7uyWZtWz1mPi2E10H6GGEsQzDvQXiqEymnmJVhLw6hm3oF2XrVhpWvrQ7h94hTkbK/ENxd1Q50WxsjJG/lEWZMASwe0xpcn98KcoR1hhHRc+Mp8XPG29ZLXh3QkRB2vsMrkBHw7uAu+HtYDc/t2QG3Iug+b2+dENYnxYVAibOimgY9vex7di+TYeHszUrC4Zxss7tUGhe2y8cLf34ZuUpz22lUoy09HvxXFeOqW9zxvUZWagNQq75WCf2189c8eKB7UFFed+H1cxy8a3QY9F+xEcrUTZmn68V3xw4D2+MdDU36pYjaIqy68HN927Y6bp36Jq+bMdO3fn5KCDc1bYEjRZkQ1DfPbd8SUXn0wrUcv7G9ieeiNWrcGj7/7NtJrazGra1dcfuUf+HwsHVGsvvkOJHqohv9+4el44K1PUK/rOOaRm1HS3PLsI8o3IKuqCt/+6Uk0qanDn289GzvzMvHRTS8AAE545c/YnZNu2bCq67Dy7Md+/16CVHSnFhwCiBJOSQ2zpPPByXGs0IX1k8RjnHWV5ACqsZ0u7ImAyiThKNWcgUO1Hhqsp7APkpVm8oRlSFc+sGzg0qFAcMpgpxBplwOvgSqeyaQAr3Pv0FbKQK86s2jOOlV8DSu77hOVgLasDcLEQJhPEFZVf/I2yR7YwjA8nC4aUN/ZxxsgMGz9hq6o/FR1omF/8Q1o3KWehVViz9Hvq2LkbK/EwaaJ+PqqnihPSMHkq/qg26ydGP3pevRduB0DFxdj4OJi7M1KwdIBbdB/sSOFs8FqU9scvH76UEwZ3hP1CSGnn9mTlwlbWZY7/VApbR0jPzsPCRUCHrpsLF6/6w0AwKfH9sYbZwxFYUE2WuyvwPAlhdhZkIFlvQowcEUxxny/Dhu7NceTt3zAr/X89SORXl2L816ywgEdqcGqNiOEpHKr7mvTQ0iqiGL8Xavx47mxlwIBgEXj2uC9Pw3C/txUkAMmXhr7Jt93/PR1GDVzAyIhDeFo/Oqsw4EdmU2xqmUrrM1vgUc/nIRTly/1PO7hcROQEDUwpGgzQqaJozZtwFGbNuCezz5CTTiMrc2ysSMrC+n20h79i4pw9bczAAJUJSbi0yH9sLZlC76iNENpRhpOWbQcAPDeqIHYlZPhfF+J/J39wxffo0lNHda1zcXMoV2kb+aYH9bindMGW/3wEFxKG/WAFSBAY8Lw96w5L9Mv7ob65BBgAEZIw6LR7TD3mI5ovqMCoz7fgDFT1qLZvmqMmeYdwbpj0R7c+8Rk3PLCN9jZPBM7cjKxs3kmtudkYoewrbDXGzpULOzZlv/usmU39qen4O/PTcU5U6xI6u8VDcD0o7ti4IpinPH5MmS97rjKr+yVj8ln9Ebv1dtx3k+6u4O6JjoSK42GD/TBgQ4pyFtagdqMEDacnIteb+8AoUDvd63YhuUtklGfrCOnUPacXDSuDV6/bzhqbGact81Rve5omYGWO8oRMn6dgepvZ52NDwcNxmsvvoCRGzfg+06d8cyxx+O/b76GHjt3+J73wMfvY2nrNgAsF/lnRx+P8atWoPvOnUirq0PPnTvQUzg/vbYWt37prNV15czZaLVvv+u6CZEohq3fgnpdx7MnH+N57yZVtfj7G1Nx1rfWYPrsuceAakQi+hO+XYl3Tht8SHUBNHKVYMEj94Kk254tQpBVvnKtjyowQZmwGtZMrgrkoXYUZhVS3dobMK4Dbvf2qKnzlWq5qo/KqkGW76gM7bShO04cwiRSQAigqy5ZIq6/paoGGQ7BrV1lVuLSK5oS2srLyQIQHCpCUY8JwrYK0FYNJtssiakGU7R67mTBVYNEVhFy5wt7m0AMX1XgoQS/rYc8YZirAqk8cbiWhvnvajOR70usiOCvR30DjQJ3TT0ZFTnJfGJxjRHmk4trjRD0qIG+c7aj65oSrOjRCosHtUHPpTtx4tcrkbv7IFrsLkfWgYY97CpSErHDHtDK05JBY0QXEBkXATBxxnLfYze0b47SnDQctcA96fTZG4/BqkEtUJ2diGcnTkJKlTtiebyIJmoI1R3egaEiPxHFI7PQ871dKG+RhOXnFOCYJzdKx+zLS8G/Jp+IaiQif3M57jw3fnfvXwKr8/OxLasZxq1a6XvMppzm+Ou5F2D02jW4cbrb4WPkbXdgZ1ZTvPTKSxi9ThaEvuzTGweTk5BSX49Tli6Pu1wz+3TGHZefipLmGQAs7cpRyzfi1fvfdB07e2An3HDX2Vh+8n08b/BXt1kqwao6LDnjyd+/SjBAgMaC1kv3QaPAnrZNUJGTHPNYI6Rj7tEdMffojjwq/MJB7bBwUDtEbKFErzKQU1KJ/N0HkLe7Ai1LD6DF7nK0LD2A/NJyZJdXIb26DulFu9GtyDuMz09F58JSdC4s9dx37ZOzf9a1K7MTsPnYHLSevw9Niw9fENwtY5ph3dl52DK8GXLWVKLne9aSJ+vG5vIBa0fXDGTtqEZWSTXuPf5zVDRNQouiCs/rPf7X47GhS3OM/WINJn6+/LCV0ws9du5Ej53+UxYmDRmG+086BS3KD3gOVgAw58F/YUNuLjrvdveF9nv2oLB5Do5dHd+aVAyjV2zA3BsewdJOBZjTuyP6byrGyBXekTOOWbwRA1duxRsTh+DijxdgW4vMQ7oXQ+MesLzsLhp1L+PQQJglXTP5JNKGmFUspwsmjTP2xZ0ubONPSDNcNizmMMHKZCoTi1mIKEpN7q6sPpfBCBF3c3cmEjMW5CxNwhiXnearPYKfw6HasFwLDzr39Vs6Qw0a7EzINnk9sWPDysKKTj5jv0KYJbsimX1K3YpLiThOF+zc2HZIaXoCY2OMLTOXdzC7msXemK3LgMaXE2H3ixAdbRdbkQK2DMoW+hJz8NERUeqN9TtDaXNWsvrkMIrbNENxm2bcQccQnHuSa+uRV2oNZC13H0Bqjfd8Ht7EEsOiuPFNtyF/9rBOWNU1n0+mP/uTxcg6zEvVNymrR97aClTnJCBlX/3PUgmKaDdtL5L31eP4G9aiNtNiwATAwTaO2rTlunL+O7W8Hqnl/ra3mx6bfljK9XPx/DGjsbBde0z4cRlyDh6MeazXYAUA3XbuQredu35yGfpv3Ib+G7c1eNyzd76DUR/fhE0dcrCsdwEIodAJdabPxIHGPWAFCNBI0HqR5epcNLDZr3K/mqQEFBbkoLAgx29+LwD3+lvEXsjxio/mIa1aHuTuv2EcDmSmIKyZGDt9NTJ91JLvXz4AZ7/y05e6z10Z+8P7U5G3xLpu2H6u9F21uH5QfBN4Dye2Z2eiVdmBw3Ktq2bPxFWz3cJFQ/jvscfi0jlzPBeZPFx4/qyjMOTHLei73rKVJUQNzDvlEZz2ytUozYmt+vND4x6wCFz2Flnad/K8tqLHnyucjnoM1P2mR/BUVd8uMy52npWnhGiCu0yAM3mXECpIw/JdiEqaBGZEOWNjxyhUSmVWEsOS69HXe5BQoa7Zc3rXp5jWfBiVugyH7mFzUhdjZF577V4tQ/PpB7Hxnzmo7pQIHabLZqWWxWXLUidbAzDthMGvZR3EbFo8zBMVly+xtskH65C31lItbR3YzN23iOl6ZlYnXn2V5av9nPcZqGjYdiUyuJBhYn9GCtKq61CdFEZKrfVR++APL6IuMYScvbKTQk1SGMm1zoePDVb7clLw6LNjkVJZj/KCZDxy/EfSeXsLUtFsm39sw18DCdVuBlfZNBE/ntAS9SSEUe/4h5cCgM3tslGwfT8SIvEzwRfGjcRHRw3Abe9+hYtm/bzVjWNhZctW6LXDHXGkrEkqnhp7PPampeLKmbORW+Gt9vy56LplNza2zeUDFsOnlz+HySf0wmvnDcPu/IwGl/kR0bgHrAABFLR9ZS+Sd0bR7ISt+GFmW0TbHvnoY62W7Aex7VeVOUluueY3huvenoXWu/ajMjkBf/rXeUg0o3j2b5OQXlkLeIQiFAcrEev65aG0VRqa7qnGyf91Lyx5pAcrPzTZX4fh7xbGdWxqVR3+8OJF+O81byO1Jj62cs9bk61z6+Jz95/RvRuOWxOffWlp6zY4mJSMsBFFv2LviclFOTlY8o+7flF2BVh2Kz+cPHUlxk9bha/H9MTLp/eP+5q/6wFLnWuiwmtk9/P+U6V/r6UpWJ6heN6pNi2v66p2qFhzwFWpGApbo86BnmxBvliMG/FjvE/2nGPsmt8jP49nnftcX/f4squhkVSUnJiOdi9Z6reBpxej9Ow07D0vBXXtwh7X8ruvw9r5gpuKLYtNJGbHRvi57nIxdeDWQVnQiel5DENDzFTM95Ppebso53oGOlYwcvFGXPGxNVH5rhtOxqquLaFrJk577RqMXLIJf/u3O5LFW5cMRs8fd/Jl7hmGf1OI4d8UIhrSEPqV5yv9WsgrPYg3Ln0Nt959OnbmZSJrdxVOmL0GIxdsQnqVvJLu1EHdsblFDq79fDbueWsypvbr7nvdW84/G49Meh8VSUm4+opLYRAdGVXVmPz4E65lSET09xmkRAzcUhT38/nhQGoySpumIWSYaL+rzLW/IiUR/7noWPRdtw0TZntHuw+ZFBOmrsTwaavwaZz3PfLiZ4AAhxFbL3aWaw8fMNHyhXL0Hr0LXc7fjaaTq0Hq41c/HC60XmR9YLYO+nXsVz8VeXvKcd+TnwEA3pkwEDNGdOX7SnPSsaldc8/zEuuiuPeek3yvG4qaqE/U8c2l7rWavFDaowmiiY3r03T/vZ9ha0EW5g3qgLtuPhkjJt2CYZNuwS3Xn44ZA7qgNhzClrxsPHrOGDxjz186YdkaAMDiDm1c13tk0vsArPlRN379Dbru3IncinJ816Wr69ifg2969vhJ583t2QHvHTsQnw/v7bk/vboOLfaU49Pj+vK8a+87V/IOXN6jFfZlpsDQ4pGaLTTueViP3QuSZq+UaYdm0sIGDwvEtmE7HJA6JyiRLyliCFEXmHeg4iUIKuUD/gsA8kUZqeO1BViRLvg8KyrPu2Luy7HmYzlhm+zrMu+wGPOxuFR9KOF6GFQblsf8Kytt8kX91PlXYY/5V4AVjonNu0oJyaGY2BIiLCQTC3ibotW7QjHxtDD/aujELchcUYu9x6RA0ygyZ9VwshFppmHfWSnYe14TGG1dIUIAgC8pYlLCfxuKzYrNv/Kaj1XF5l/RMBIqIvjj0O9BKPDIjLGozEniCzxWC/OwnMUdrW29MC8LcPcPgxLnt9LuBo9wIbexF8NiDDhsRPHq7W+g37rtWNMhD5c8cgki4RB0jUpRX0IRA8lGBNGQhhGLN+Oeuyz1Vll2KrLLfpsqvsONBSPb4oWrR+LlC+T5Rl+O6Yk7bzgZIIQvwBmJ6ohGWUg1K8+MALd8+A3+NNmaAvDhsP448wfviBWNCf8+dzRueDe2A8iqLi1QsHM/Mg7W4smrj8WHEwfAOFiL+Wc8Fdc8rMYlxgQIEAdKxludXqunWPtKHpbNaYnt12egPldHeK+J3Ocq0f2YErQ7rwzpX9b4LpNxOJC/pJwPlpXZsZdvOJK47u1Z6LduOw6mJOKvt5yBSNjbWhAN66hJSUAkIYS5Izvio4n9AOB/ZrACgCFzilyDFQCcNG0V/vRGHPPQCMEjZ47FwxNPwOrWLdBy74HDX8gjAKYCLctIxfW3nY0f+rRDfUgWCosKmuHZyyyG+Yc3vkfWvkrQQ2BYv58Bi1p/lBL+x3cJeeKf6fUH+0/JZzCp5gRHpcTzjx3jfU1ln8997Mfh+ZQSnud+Lth/xC1F83qxv8uU2H/w/+PnEpmJKcfxw4UyOPUklFsou/y83nXBYECz/qjGF1NkeWp7mHD+dp6YAQDIXFADbY+B+lYhbL8pEyvm5mPjC9koH50ESoAm8+rQ5tp9aPF/5TBMO3agYpljeew+6v3ZfqeMctlaLnDm9gyZtEV6Lnc9COfafcYPUt0q/VmFu5/I+45avAl/YHar6yZge4ss4ZpCW0LuHiYleO6PR3uW70BW7MnRhxNfft0D6y5rjrpMb8b8a+Ly9+fhnM8XyXVlv0fqO7ghvzl6FO/CsA3xOXgcCjbleKtvfykc/fRN6LjNWuZm6ojumD6kG/54z4UY9fpN/JiDqYl46orRKCzIRlTX0KS6Hid/+aNnn/XD79rpIsD/JmpbJqC8TxIyVtQie2o1yi6yolMjRHBgbAoOjk1GwvYoct6pRPP/HkT2JIsdbL8/8ycteRAL/V93VqE9+sUNWDqxNZCYcFjv8XOQW1aBB//9CQDg7RMHYdoIf0cAFW2LynDxm95Lq7MI9D8XhWOaYefRmTjqH94RFADgpHENL9n+a+BAejIyK2pw8wvTsC8lBVtaZqPrxt0I1xh47cThaFJdi5s/mIZLvvFfjr4qMSFu78FY6LjHOxJJvFjTqgW6b49/MvF31z0OAIhqGt4ZN4jndyt0rvHMxcfgqjfnYOKU5QCs+po/qP0hlatxD1ji8hlMbKSOZOMssyBv1Rh/TFqV8sDsT7aHnzLZyaR6g5ESvGIKqnnqfcWlSNSy82N97FE8KcQSdOpHmXcVSwsmOx/y+xDI9xWDZKhl09gKJ7y+3M/D60LZMvueSaPyfoGFsCXqWTQJFpORRU3fNT4dGStq0ezLKuy60NaLE8f+WNMqjB23ZKKmYxhtbtqH7ElVKL0sDbWdwpLdSlxqhJUBcGxXhrLfoITbuRL3yB+eJvvq0e/9Ynx7YTfpWiIzUtufX9/DPsXqlqrtr7QFlHzrt7U9f8pCND1Yg9XtW+DhS8e6pF1iMwOxTAWF+3DZ23Nx7Jz1MQNtl+WmInv3z1MVtp+2FwtuayflbTsmEwWzD/ys6/4SyKywBmmNAg8+8Zm07443vvI6RcL0nt1w/KpDC4/0U1GRlIT/nDAWb44YjvqEEM5csBCPvPM+pvfshj9cczmoTpFaW4s1N97pef7SjgU4984r0XPLDjz/+NvIKbfmO4RME+kHawCD4sTZK/HQk5/yc656ew6a2nU0eWwvPHXFKBzMTAatin9V5cY9YIm8m33EhYCvTMPCnRNsXanmSmt8BWDCvgJMO6N444oTOP2orNeACFgfYh70ljtfyGn2OPwDZTofQnUAZmk+GCj7QYXgt+p6WLEGLB9XeHYq382XHRHrXHYAMJnbvl2vrJ51TYOuOpYQ60PPwl9FNNtwzRwOiI5ohKDfO9tQ0S0JOwdnOhN32ZIh9kCy88QMdH2wFJkLa6DtMRHJCTnChjAJuOT0NLS6cz9CBykiIKhXVHos6K0zUOrSlg1c4papBU+7bjm/1r5WKcjaXo2jX92Ibyd2RSQ5hAgf/DTeD9h91IFL7TeGqbmcLLizjTqQ8S0vDieSqdXWoDpzYGfU6WHe/yd89yPSquvw0Qn9YCRYByfVG7jzyS8x5ru1fKCaeVRnrOnVAvk7D2D4/EJsb90UWztkYUeHTMwe3xm55RV45qR38XNw3nGLpfTMx7ug52s70f+phsMBAcD6ic3R5eOfxzh+DXgNVhFNQ9j8aVMCPu/TDz906IQHPn5fyp/WvQf+78yzsddexp6YSlhk01qipjohGUvat8GAQrer/C1XnImIpmNZ+wKsbtsCo1Y4c64m3f4qdmZnIL+sXDqnaUUNtrTKwn3Xjsfyvq0BAJpJeb+NB417wArwP4d+72zDsQ+uByXAD39tj3V/yPVU49W2TMCBPsnIXFGDnKlV2Hlhhuf1tEoToYPW17c+7/C9Dmk7apC/0nlhs7ZbYYzS9tUhf1M5tvb67bq4X/v+bPz53VkAgDOmLcVdfzkZG9rlYtiSQpww2/qozhvUHs9fMRKb2zfnHqHP/+UY9F+0FfffYrGLgfOKsXJ4/mEv35AHt2DXEO/29MK+Lqk/6T7LR7ZC3znuSBG/Bl4deRRyDh7EiSucCddf9eqN/P370We7NVBP7dELJ6z2juB+9UWXoWlVFW76xs3sjl6/Dn+e/g3+e9xx2J0Rux4vuuEKrLnBzbLefeBFPD9hJGoTwhi1YiPqQjouu/1inPbdCpw9c6lrsKoP6Xjp7BF47ayhlvdpAysl+KFRD1jEJCBstV32zRIYFpfybanRT+rXCIVm7+NqPiVILWMzIUGt1KBKkMosyqTExazUFYdVV2XHhV2QqPkKw7I7u7PiMGNVxMVAHb1RHLYarvOzj2WBdJ1pwOzijsrUvjdbRNCP1RqmxgPG1ttu3mwKgbMEi8OsAIDWAINfKuJFG/5oIZptqsLsezqhPlG3i+hIo9vGN0Xmiho0+6IKhedn88C4hjAJOHmXlRdNI6htEgYoOEMybUcPwH+lYWe5EWdbZ4Yx7gHHrjL9mq4ACCJUQ3lOMgq75YCahD9f1HSYd73J+oN3/+D9x9BczIozbpcqHL4Q2ZhpElz34Wz8+b1ZAKwVjbtt2Y23//IKXjj7KLx36gAUtcxC2x37YIBgxLzNeP3q132vPWxmIYbNjO1Q8PXVPZC/4QB6f+u/tpOKLh+UossHbsb0/pT+0KsoOn++G73edKKbD3tgS9zXFnGkBisAuOT7udDsxvmqV288fdwYrG+Rj/y9+zB880Z80bs/Rm5c5zlgvT9gMK6fPhXdd1l1sKVZNh488RTsaNoUd37+CQYXFeLieXNxzoL5WNamLQxdw4iNFkM6ftVaJNVGUZts9e+qhCTP8uVUVOKOSc5g+OQZx2FB1w5Y0LUD1rfJwz9ek1djvvb28zC/fztrKpAJiIvMGjRgWAF+hxj4YRGalNXhQH4yll1cgGMe3oAun+5GenENZj/dCbXN5GgWJGK98Il73ct8MyTusvbVHUZ21W7OHnSaUQojRPDiByNR3N5iU2yuFTXjEBaOAP70wSxc/741j+axC4/DJ8f2xV0vfIkx89fhT+98h+MWrMfLZ4/AHU9PwchFmzFykb8jRLxIrInGPViJKwh7ocfbu7BzQAbq0n6Zz1pJizTk7fIOzFvcoila7/KPQCFiTasWWNWmJc6eu9j3GI1SfNWrN5463hqomOy4s2kWPhw4BIQC33XynkR89pKFACw71VPHjsXbQ0cgEgqBEuD8P16LoUWbcf20qRi8pRBDC91tOP+ue/Dv8WMwrVcPXPXtrLie6cWTjkJaVQ1ueXcaLphu3f9Ak2RkVlo2qys+mYv5/drGF1knBhr1xOE29/8LaGJJANRetBEhCti/+UKObFFBeyIxW9CRqTJCuriAo7wECbOn6OoCjjHCPvnZsAxh4rBqRFeZlTpJ2DA0F7MyFUbl2KuErZ/tKp5WJ+pWse/pzkRiYtexZuexBR1jLZ7JJhO7F3K0PkqpbCFHvR7h2ij+eepkpJfV4vM7+2DtOXloO7cMp/11BRIPRnEwPxFf/bcnqrtag0LzwgqccOpa6PUUa/6Wi7zpB5G0W46dRgAkb3fyalrJAx7VgMJLsrHl0mYO41EmCvOJxPaijZE6HRedMh9ZxdX4/uIOmHpzT1TbK9eyCcNsJVtnsnCITxhm/aCOTxi2mVfUSkcNp9+wCeMqw3I54yhOGSLueflzXDh9IbblZKJgzwEAwMPnj8FLpx8FwApJdeIPq/CPF6ag6cEaRHQNu7PT0Wq3dWxJTjo2t8sGAIxYePjds2PBCBHsHJCJggXxDRS/BRiE4PLrLsMJy1bh/O8Xeh7zVa/eeOo4eaDiKxnZW0KBxEgEl38/G3/5Vlb77choivcHDMW7g4Zhf2oT/t5ypYoGgFL02VGMgn17QQEkmFE8/P57h/w85clJGHf/9RiwsRh3vf0Fd7744Jj+ePjCMUivqsUXtz6L5PoI7rrqJHw4foBVBOE7alTXYfW5jwQLOAb4/WDEx5uRXlaL/fnJWH5qARIRQdGIbLz3zkCccu0KZBbX4LTzluO7xzpix9GZGPK3Iuj1FCWj0pFUGkXWkobXbRIHL4bsHyqx5dL47U0DXtmKrOJqHMxJxMxruhzSMx5JiIPVC6eOdGJqEoKvj+qJRT3b4s4XvsSYH9bxwYrhnltOQteNJb/6gPXFU72xr30qLjthHs/b3SsNezumorpZIlJ316Hb5JJftUwNQacUrz/1iue+kox0XPbHP2B9bkvRodWFjqUlOGfRfJy2fDEya9zTB8658nqUpjdg4yMEy1u3wfLWbaxpYTqQGI3i3o8/in2egEWd2uAvV56DB179FKN+tKLab26RjX/84RQs6N4eRDOxPz0VT5x/HP7vta9x6+vTMK9/B+zMzYz7Hioa9YBFogQ8AqgmeAZyuxazWdnH2BFmCZEXxfMCZ0f2dUM2zRCD4/qdz734FBd2wxQYlodNAhC8wwRmZW2J4wWmMCpqMEMbe07HS5B/d1w2LN9Hd8BO0ZyPl9e5lkRvl1sx/hlKeKcobwOdEzd1kUy+iKFtz0msA45/zTL2f3tFV1TrCbxedrXLwOvvDMXEm5ajYMF+HHftetRmhpG8P4K6NB3Lrm+FMedZ5y65vwAVXZJA7AfQiYnet+9Extpa7B7VBBuub46U4nr0uW0HQrUUB9snYtE/26LWDLtsWZxRCaGakvfVY8gLlr3kq7/2REVyCmC6mVWd/Vz1fBuKm1lFBTblMCzFpsnaRVU9erS5mPXQuSfg+ZNH2tNFbKmcUlBKUZqWjhtuORvj5q7mbAsA8vZU4I6HpyDjoPzhnDm6Mz44ZwBufWgq2m7Z576xD9781xBcdIf3khsz/tIV7eftQbsFe7F5ZA4ihoZBT8v2qdyVB3+x9bR+aexNbYKNOS1ADIdRqdvz58/D3V/GHlT+9dkHuPq8PziMihBxAypMAUqpq0PX3TvQc+d29N9axK/x97PORI8dO3DhvB+ka2/Ma46HTx2HF59/A4M2bsX3tz4MAKgL6XjmlFF47qRjEEnSLU9D+xvw+tghuPCrBWi9ez9uem06/nLz2fybYhLKv4HxoFEPWAH+N3D0JxuRubcGe1ukYOkpbVz7azMT8OkLfTHqvg3o9f4OJO+3mNLim9ug3ed7EaqjKOuXiq1nZQGE8EjvOjFhpNgD3wnpqG8awoDrtvHBas5bHVGbY69OG6UIVxqIZPi/MpnF1QjXmihvnoSV41vGJxQcYSzp3AZnzFmGJ884Di9NGImYhbbZ1pLerXHHc19hzA/rAMBly3r50uF496JB6LN8e8zBytAJdEO+X58ZbkeHgzmJSNtTh+OeWMfzOszZgw5z9sTxhL9dXPCnK/Hqc68gwbCk7h47d+KCH+bhraFH+Z4TMg2YhHCHDC+M2rjGM18zTfTbVoTuJdvQc8d29Ny5He3LSl3Ximoa9qSn4c5hZ7gGrE4lpXjx+TekvHUtc3HNny7EllaWJoIIfahn4Q7c8+pktN5tqW2jSqimQ0WjHrCICYdNsEGaANROUFss4R5s9pwa1WxLdeKas8KXcleYkLiAnh/8JigbgpegGrA0qtghuPQs2Cn4hGBDZlqcQhoyAyKSDUvIkwrr8QACQbPOsfPtOuaMS1gE0rmMyrT8Oyiry7poyDNfMyj0qIET3rA87r68rDcO6t7rSZm6hi/+0Qu93ncM+CPuclRUS68rQBVNAltgUas3MWHcSjTZbtnJIvUhDL2gCCk7IzjYJhGL/9EaTb+rRvtVZchaXYWstdUI1ZqY8VAXbDw1lzOrOtMJeltrM6hIoo5amsBtVIxhMWZVqwS6rYuGONtqiFk5jFvjfYP3XdY/XPZK/3lYnw7pj8kD+8AIaUAUsJUPfAI2oRTUvjC17Xilaem4/uazcdIPq3D7819xtgUAf/u/0/HdMZ3QsuQAHv2rzASqUhPw1ek9kFwdwcD5W5G7082Ees+UHTBqmoSwNz8VaXvin1wqYk/bJlg9Nh9Hv7hBmuRc1jIVd352GvrOKMYV//e9a+D8pfF5/77YmNMCVYmJSKh21NX//OQTfN2tD/alpAEANP6OW5u3Bh6NT3oNRsge5MTP0PzH/8F/E0OcLwmAUvznw9cwZr17qY/daelY1bIVVrVshZUFBVjZsgBlGWkgUaD9o4+gS0kJxv+4Atd/M93zWb7v1gmFOc2BKHc5RUZlNW75eCrO/3YRNEpRmZSAf595HN4cPxjRqOYEziaAEQ0YVoDfCfr9sA1Ny2pwICsZ8ya0R0Ks1Q8Jwfyr22Hoc2435kEPbcWmwuYoPqEpIlk6jrl6Ix+sAGDQXU4IpbStdRh9mffic83WVeFgQTm29W162MM4HSkYuo5DpoOE4OuRPbCoVxvMvuQJAMBVD56PJb3bIAwDtUlhrO+Uiy4bd+OrE3vgrT8Mwf5mqUjQLHHxDTIM3ZftwnFfrsVRX/t7GyZXRtF2RfwqRRG7uqTjlZdHoNWP+/HhvQMw9uk1yCyxBtfsHVW4/prpmH1OF8w9qSOO/nwj1vbLQ7dlh9fmtaBzW2RU1qLrTvm6pyxdjlOWLufpJW3aYMBWa4LunZM/wY3nXOx7zarEJEcAFZpt3DV/x+Mfv4Gp3fq4zhmydRPGrF+Fek3HnE5dsbpFK6xqWYDVLVohva4aezLSUJ6SAtXDvNPu3bht8hcYXOgIfweTEjG/UwfUh3V0274LG/Jz+T5imjj7+8W47f2vkVVpDcSfDe+DBy4Yhz1ZaSDaz1sXrVF7Cba/4z6QNMtL0AzZOtEwLE9BADQkeA4CIHZaCzFPNktK0XXqeBJq6pZKaXXJci/4hV0yTOIbnUC1R5iqfcIQolYYKqOypWFFGoNJHHakdvBY87G4a5JyiMqwWFqnfI4W8xxkW43VOVt+hHkNhkwk2EuNJChLkDCvwcRQFP93+xQMn1OIz87rjQ9uGCgsQWIfY38A2XIjiSSK5AP1OO7ptej73i83j+ajp/ph07HNJYZVsGIvrrn4O+xp1QT//Oxkl83Ki1kBlt1KZVZseQrDw5YJ2IxbtWWaSoN52Ss5bVb6L29j2eYIjfK2432fvSvKltkiQ7qJEFtORpc9ctVlfBL0KFIO1uGYGRtxyRM/uBZ6XDs4D5sH5kAzKU58znshwF8DH5/SFxM/X/6zr7M/JQXbs5qiaVW1tBDjwcQkpNU5Cz6ec8X1WF7QljtfNPgee4FTLIrX334Gg7YV4q0BR+G+cROtbA1ovW8PvnnmAexPScUtE8/H7K6Wq3zn0p348j+PSZdb1ro1nhw3Ft917QIaIvwdp/a257ZtuHfSp+i/xZrYvL5lLu688BQs6NHOKo5GOYMXF6E1q2ux5fL7Ai/BAI0b6QdqMHheEQBg1onxe9zVZCYgmvjTdeX1TXQkVMpuWkaYYF+HVOSss9x2a5q6VzBuYIHrAD6oTkvEjIndMGNiN/RYuQO3/9Fx0+62sATdFh4661k3IhcFq/cj9YAcz7GoRxbarvZmbDsKMtByWzkAoD5BxzvnD8Ilr1mBag91sDr7b3/EwE1bMWDDVhy30rG9Na2uRtNqt8eqOFgBwHsv/wfd7nyUmzdiQTNNjNiyHgAwv00nRELyZ31w8SYM2laIel3Hi8OPlfblHiy3y1WFl956EbM6d8OoDe4QUa+MPBr/OuUUUI8RI6m+Hnd8+CUumDPfUv8lJuCJU8fgtbHDEA3pkk3r56JRD1gkSmCv2wdNCIDHl2VQVDbUz75CTWfGv53lsCLGsJinDWNY/uVyBSUVbFh+UQk4o6IOo7K2gr1KtVkxDyIlX/IsUvIgkycfyPN2mFTEhXPOrNgDA9DZszp6bKGIwi9xIInd/UZ8swkhw8SGrs2xsU0ukgy327nLTmhH3e0y5dA/cm9NHoz9HVPR8atSjLltLUL1JnZ3S8PHz/ZDRfNkdPy2FGf8eRkqcpOwoWceqEEQMXXoERN9Py3G8S9bL3okpKMqmshtV2wRRhbRQ2RW1lbnjIrNv4saCrOy95sCm3LZMP08QT2jmih5nFUzb1vGogmPFMPm2lG74anSh2nIaQv1HeDtpCtpxZN2Zc9WuPCHyzDmg7W45HH/qOaAt9MGw8bezfHCgyMx8r1NOP3p5Tz/0SdOwDn/XoSRX27C12d2h25QjPnE/kAL9ZRQb+Ci12Pf3w9tXnsAiGhY0LEDQqNNLLn1HmRW1+CGC89HVmUVJixbgQGCR969J52Gg4lJOHfRfPTf5uSfv2AeJg2wHDBUb0FQa6Aat245rvnhG7TfZ0X+qEhMwswOPfFNlz6Y16YLIrqOP303FQDwQZ9hKEvOdFzmKVzu816DFQDM6dQFmklgx6O2vUet+rrt469w0XeWc8ang/rivjNPQmlmhvUNiDgMjGqUL/7KviEghH/74kGjHrC0qO3aDifcEgHhrucm11nZFcbCgSiR2GlIeLHsl4+toKvZag6mmhGprPoZUF8dd3R14j9AqZOAWSOKaj42+CgqQd6ZufrAOUdVHbhVgnBDGe+ZMZ8PVGpAXd0x6IsR3K0fynMyA750Q+9uePzX1svz9dgeqImGpajmPOyVHSDX1NnEXis95/xOOPE/lgrpo/v7wQhpOPvWJZ73AYC5V7fHjlZNMeS5LRj1b2tOyYZRzfHRQ/0RSbHczjt+bXml/Xh8K1TRROi1Jvp9VowTXl6NrBJLat6fnYx3rxyEGiPsHqgMecCqN9gqwpqz0jRTBSoDlqcAo6qIGfjkUmUA84Kq9mVbdm1CuWBCbdUmH7h0xelDGJR49/JwPGLHiPujGmtPAyFNx2cT+2J1n3yMnrweSbUR9J2/HU3LZGbiN1iVtUjF3GM7YX9CE3x6UT98c2p3/HfMJJTmN0FZaio2dWmOkV9uwtAZW5C533EYabn9gHQdjQL7MlKQVd7wHD6Gksx0dCsswdoWLQEAR63ehMzqGuxJS8OUnv1gahreHHI08soPYNyPP6L5wQq833cY6sNhfN59MDqV7sKbbzyNzNoa3DBrCr7p0Af7UtOcd9weqE5YtxxXL/gG7fdbA1V5YjLqQmE0r6rAqWsW49Q1i1GRkITKxGTkH9yPel3HKwOOhRblryQoAbIrKn2f5crzrsSNs6agx64dgAGLHHAh1XLoyi0vx/nfWwP7NZddhK/69QF0ChIVBVq7L+mUC0KO8Eudb10caNQDVoDfLzoV7kaXTaWoD+uYOfrQJ+BGbJVgUd8s/DihAKAUe59dh2ZF7uUuVpzREvOu6oBx96xGn08su9fCi9pi2l+7w7A/yqE6A11mWaxt9egWGPpRIY57aS0fqA5kJ+OrS3pgxindUBn2jr8W4NBQ3KkZXr9pOHTTwNtHeU+2VbHs6AK8cucIVKYlQY+aOO6j9bjwcWteV/OdlUg9WIf1vSwnAXGwEhHVNdz40NnY2CoHBzKSsWD8w3xf/zf/D1XJiXjssQ8w4YdVeGncCDx87lhcOuUH3PDZt8g7UIEv7/0P3jhmOB4/eSxOXGYFr/26d0+YmvNhLsnIxBvDrMUviSBwbGzeAiNuvBcfvPoEuu/egb989yX+Mf5cADajWr8cV893GFV5YjLe6D8Kk/qMRHVCAvruLMLYjcsxZtOPaF5VgfR6S9X4Ya9hKE3L5PdpVnUQly6aicsWz5KefVbH7sipLEePkh148Z0XUReKPURc/e0MJBoGFnRoj6/69o557OFAox6wtCi4ShAeKkGHadlMhLm7M2ZlssmRDm0lbAKyKacZ29AE31jVtV1d7ZevIyQYw30ZVTwOFYxBMWalMCpX+BYTLnd2X2Ot4qku/uaCukLnqcC4eF0qaikuZXEVEVPLOtML3PVGMO4bay7Jd0M6YU9qmmsugkvFZBc2wdZZ9JxquUcvHtMWlYa1NP38ie1x0uMe0a1rCCZetQwdFpbB1IDJt/XBgnPaI2l/PbrO3IUBX2xFUkUESVXWtc+6fQmydjuMasrFvTD9lK6IJFkhlrjjhClPBlaZFVP7RQzdYVZRJdxS1IdxG8TVtqKzDXCIhnnWwZXwW1SDy1HDCbosG92p0LcdtmUVquX2Pbj+rZl8cUI+PQSKQ4f9OxrS8Nm5fbGtbRbePrnhwSoa0jDpusGYclZP6AbF0Z9uwFUPzJGOWT6oFfakpGNPh3Q89I8T8Ld7LVVZRVoSHrh1HB74x6eoC+s4/dWrUdYszVLTRoHv+nfE0Us3AQDS9tWivHkKbr3iDMzt3hHTevVAHU3E82NG47MB/XDH+1/i5CU/4rJZc3H6wqXIrLYGxa969uXvqxaR31/bb0h4fzXcd+wZePud/2DiqoX4uMdQUBDc+807EqN6o98ovNNrJKoSkkCoxWpWNG+HFc3b4cmhJ2PR83/jz/5q32Nh+yXh7JVzcdP3nyM5KqvY57TrCs00cTDBWS06MWoV7qU3XsL3HbrI3wQCDN9kedP+5/gTuAu+lwYGsL+HSj+jGgGNBAwrQCNGKGrgpFnWwDL5+F6HfH7T3VXo8GMZAGDFca14/pKTW3sOWH2mWKyqLkXH5Dv6gNRRXH/GDORtqvC8ftbuapQ3S8LXl/XEjJOtgSpyCBGn/xdx1JLNOGHuoS1O2GPVLtQku51bVJS2aIKn7j0WRV2yMfqL9Tj9tWVovktWdd37yIlYNqw1/4hWp1rXNQlw279Ow9UvfAcA+Oykvihrliade9OtZ2LxuQ8CAL698Ql0nnQvapIS8O7oQTAjjk22JCsT1/3hQrwzYiPuffdTdCh1JjZ337EDC9t2jPvZV+S3xSc9BuP01Qvxr6nvILu6Ak3q65yBqrc1UPkJI4N2bOK/3+s5HKVNMnn6/BVzXIMVAIzcss6Vx6BTimM2ee+f36ED5nfoENdz/Vw06gFLiwDEFbyZgLUiFVgXIEjysl8AQDUuLTJXTUPzZlgmOQSGxbYC63C5IPsYzlUXdWIQh1Gp+9StaNui8j6v+RtSYYVH4II1Z1iMZrI0k7BF6doumo/hX7Qjmso+hlFLtyCrvBplmamY3bszd3WWVubVnCVAAGG5Fk3HyOmW1Lehd3PszGqKsGEgVG+g89TdiIXEagNn/t/SmMfUJ+pIqDPwyWV9Mf3M7pZ9ynAm9tYaYW6P4qGXWNrHZT0a1RynCtVWFfXuJ8QgQvt79wfOzmMwLKeNVacL+wCNOFMWmPbBWYLYSvPle/xtwh+M6o8xc9di4Fprvtu7Jw3A6k753EYc0hzG1bpkHy5+awHSy2uRXi57zx1MSwShQJNKayLxyr75ePSeMRg0dyuu+8dM5CrR1Ff1aoH77j0R+zNTgahV52kVtbjukZkAgPfOGAitiqL36p2oC+t4eeJw1EXs8Fh2u1XrCVjSpQAD1m/7//bePN62o6oT/1btc+59U+ZAJl5CgACBhKHD+GMIYTSMzWBsR0BEbGwUifoT0AYHoMUBtW2xtdEwiBEnPiIqMhgQ0kwxKGNIIAlJSMicl+G9e8/ZVf3HrrVq1aqqfc4NCXAetT6f9+rW3vvsXbuGXeu7RnTe4/87/yv4yIlBTD1Lx+dH3/8x/NBHz8X6LP0w/eLf/x28s3j7Ix6LR1x4EX76nH/Erz75ObjgiGNgeV3H0vTA7z7yaXjCRZ/F3W8cNr5PHnMvnPnkF+CW9e2D0cXMV1H0qz4cnbbf8qAnws48r+3/+vQfx0OvuAjexPUcpSjgYwBw11tuwu4br8Wnj73H8D3t4nXeePTW4iP3vc8wH2kKseQlLWHjfRPjnnm6/sdopTesRvsnPftfPgMAeM/jHoC+s5iMOQsX6OEfuhgA8MknHo/JZo/H/v2X8T1/+jkW422F9u6c4J9eeBIe8r5LsfvCG7C2MXxVvnG3cX+RRindtn0dP/7qH8Qfv/4dOOULl+Fp53wO73n8A3DBiUcCiH5a2zc38Ruv+Rv+3f995D1wxe6D8Lx3nY//+6jj8ftnnobXvvI9OOGC4SN+8me+jrc+863FZ779xx6Os3/woQOjFa1A8HP/4324y3W34tK7HYo/fv6j8ab//y8BAH9z+oMHdCUs5ybzHj/xlx/GAy6KETj+x1v+Bk/+1Z/BLdtzXeVjvnRBgqwk/dI/vBvvfOij8Cvv/Uvc/fpr8OPnfhBnPrvuIHz9jgPw2496Bl77oXfhE8fcCz/91Bdho1urXs9tdj3udvNgun/hIUfimp0HJeevOuAQvOe+D2UG1Fsh3u9UqcX/k3jedT659ltBK+04fP+XvB5mZ3AcDpIDN5F/hw6lOg0CHacOn/i482sHWO1IKZxqFyEsRnLSoVPpGWom6qMIq2IVmJ2XCGuRtaCkiuVYjQsrTd5YRq57KEWfB6diQ47cU4dD99yK//uT/wPT3uEZb/qvuPDYIzDllCR95pC6HlKR0AfvqGtvxFue+3YAwF89/8E47R+/jMOuHgwtbrjLDrz3R07GD/1WObjqMvS3P/wgnPPUe+Oy3YcCiBaAhLA2+hjINjoDkzVg3RLQzQlRFXRVkJah4LpRc0lakg03U2WJ9BjTcYGi8/FO149ON4PORyd9ZW17wGwv/vh178BDvvQ17Nmxjh//lR/C5084GpOuxwkXX413vez/ZE38vZeeho8+6l645ohdgDE46Oa9eMIHvoiX/f45xVe67rCd+MTDj8dT/2Hc0fiHfvcFOPCWffiDV5+NjWmH7/nfL8M1hx3A43Kvi67Br//B3+B+lwzGNh8++QSc8uVLsWtjE3/8pMfg17736TA0XgElHHLTbXjxOefgR/71Y9i1mYeTeteDH4Ezzh+s6m6bruEx/+1XsGmGTShFWKHfeuCut9yIq7cfBBiz1Dp+2kWfwi9/9Ozh7+/9RVx1wCHh4nCp3oRslJ5kG1W2nofSdSNrXd1fzhs+JvTibu8+XPbzv7SU43ATvDf6jqJnnPvvmPYO/3GPo3HhsUcs/oGiR344hpB53lvPx2FX34rr77IDbz3zEfj5v34OPnjGifjkk+5+u9u3tjnHlccdfLt//91Ot21fx4tf/UM4/z53w4G3beCPXvMO3P/Cr+PRn7qouFkBwE/9wb/g1H/9MnONNx+4DX/3rAfi60cdlF17xTEH4y/POGXhZgUAZ73ibfiDVw8f9vVZj+d84Hw841/+A6d84VK89C/Owd+88g9xv0uuwvW7duCnXnYGXvaT/wXXH7ALALBtM9cBAcBNO3bgN5/6VDzuF16FPzjtCbhlbT05T5sVAOyYbeIxX12s17t618HYShiwrx48oNZ/OfYkfGPXIUv/bhVopRHWyT/6Opidg0ULo6ppRFJ0zMuwTcg5AjdBDDOiwg4x4iogrIWOWCVHzpEwSsNxJOe57kfOacQl9VYVrvt2IawCZ0Zlxm0xig2vp49PPPw0RbNm6vD3//1/4qRLv47//vxn4J2nP2w4LRJvEpKicE4UDmg9hHn6zZ//K5xy3qAnufbwnfjrH/xP+NAz74PZ+iSmMYFHN3foJxZ3ufJmHPvV63G3i2/A0RffiLtdfAOOueRGbNtXzmx7y651/Jd/eDEjqplL0dPMRZ+qGTkDs64qtQSUPlZeceoaWWVjnuiwQkljmY35yMdOJ/fTKNoUxluLgjLE5WM4NBrbYC1oOg/jHN71K3+MUy64rNqsm3Ztw0G37MNlRx2M3VfeCAD43R8/DWc/96G87I685ib81qv+Csd/7br6+1VoNrGYzheLmt/30Pvh1T/yLFx74C68+XffidP/7fO47LBD8LRX/gz27NgOQxZ/YbrYMH5kvXzYTbfihR/7MF5y7geT+3758CNx72uvwj/e+0H4haf8SLhHRFU0hlat8aiTDv1a+Xp3rh/0vMaI9az0k/QJ6sDfO16nGnEVSrcQjRUQlwpCAOvh9u3Dpa/6xRaaqdFq0ckXX46TLv06NiYd3vPI2+fT8cX7HYVDr7sV//is++N9T7s//DaLie2z6/rJsHKuOeoAXHf0Lpz/6GPZoMM4j8OvuhnHXHwj7vbVYRN73D8NzsSk7G+0RfIeD/rKZThgYx9e8E8fH92sAOC2bWs46JZ9eM+THoDpvMeL3/kx/PQf/QuOuGYPpnOHk754Be751WswceUv9hdPOALvOOPh+OyJx+Caw3fhja/5GzzmE1/BpUcfgh/5vRfiluka/u7Fb8YxV9+EG3dtx1uf+Qgc/Y2bcMzVN+KYq2+EMwa/87wn4D2PfABcb/H8fz4Xp//b57HZdXjpj/8Q9uzYXnyupht27sKbHv80/OkjTsX/etef4pTLB/3qva8dxIynfvUL2DbbxL7pYt3UVqi3Xc5Q7we00huWnQFmpszbPABlCZtZBxLiCqjGOsktkuWMsozSSQyXIY1qnOSKK7qrzOIvns+PhdKrehKaSV2jmco7AmF1uUUQh+0h/RRbZobjHjj4llvx8K98FQ+/6Ct4xJe/ivtdcSUA4AMPOhHXb9sFO3fJb7xHFlWhD5w7RVD4wx9+LP7whx/LSGwyd+hCNAydINKOKHduves6Lr7rXeAeNtyXNiwA2DufRoTVpyhq1tvF4ZUogC2jKpvrqohTH0HVVT+8MRSdWYOapCjpGDK9Blu6+qQe/W5M5uv4/R/5JN7wtr/FsrR93wBR7nLVzfi1n3wqemfxE2f/K/7L36bRSq46/AB89r7H4PP3ORp3v+w6POlfv4idezdx4oXfwKM+9hV88j53x/e+69/wmE98BRvTDmf+3PNw/XQnHnb+JTjm6puwMe3wtN/8SVx96IEx+owcnxlw8kVfx6v/fIhv+PpnPx2fvduxMJuErMI3hHypCGnN4nE7B26e7sLzv+9lOPi2W/CCT30Y3//vH8XO2QZ2zDfxoMsvxifvdu/4W5nAkRKe1tD0MgIyFW5L66JNb3iMaU6x9Emt52Sd098d8nPyN9KqWOu3jImWlkvQSm9YjVaLDrn1Fjzk0q/iEV/5Ch7+1a/gvldemV3zpWOOxP96xmnfhtY1ujPp/Hvuxk3bt+GgvfuK568/YAcOvTlacZKO6JirbwKMwZu//7G4bccUj/3kRfjSvY7EZ+97DD57v6Nx9eGpCOn3XnQaXvrWD+N5/3A+nnrO5/HUcz7P59744ifjgnscCXiPl559DgDg7x77AFx9aF0MdeCte/EHf/hnWOt7/NODTsJZj3vU7e0CAMCNO3bh9x71NLztP52KHz7vI7jn9VfhokOP+qbu+d1EK71hDQgrVDjoar5bsxuA4vJjGvAC16h8jqA4z1G4nVlpRQ64atk1gqyoXkVUJWRFJXNkKae2lOUYXcpy57RPSIaNXsiz2TISOPi2W3DKFV/Fwy65CA+79Cu47zfyDerLRxyBj9/7Hvj4CffEJ+5zPK498IBB/zErxx+UaAuIyIoSYmrE1RnPqWG2grCAIXoGJ9Y0cf7snU35/hpNzZ1lRDWnqBW98rEq6KsMI6pUJ5Ihb4m4K+OuX6uItPQYE9BS6NpYA6+47shRF7huKunv8MwvHnUM/uzUR+Cl/3QONN3nLb+M2fbhU/Sfzz0fv/37f4Vtm0MHHPWNm9jK8i3PfDTe8sxHs3Xu9o0Zjr3wOuy+8gYcd+X1OPbK6/Hw/7gEu6+6IXsGALzzCQ+Fn1scduMtOOVLg0jyez94Pk4970J87vhj8NnjjsFnjz8G/757N64+5EBgBvz6W/4Gx157PS477BD8/A+cwVaBWbSK8B1ixEVBuXt5Lhybe+yZ7MSbTzmdj9tNoa/qfaa7Yp1VhqLFoGboORyuoueIvBhJ2XRMeRwZTVPdiHOhLHwD5HO9NbkPpxHf8CVotTesuRcbFsQfesRCEUoSe1t2dhViDzqmYbNWFi6xYWWGDlIkqER0VRP1oggI1WuGMk7uLFzTVkyd6VKe6KkSlY1KbLz/Qbfeghd/4oN4xNe+jPtck29QF97lCHzy+Hvh4/e8Jz5xz3vgugMOYOMLNxkmr+eVEAoOoAsegBj2KpyjjcpRGTYsm29YrO9dkA/EecMb00+88QfxRz/3Z3jpr30/NuaTKO6jDbOQCZiNKshkXYn7WAw4zzeskjOpPF9kYPSGNSYarHzUtFLcW7GJ6Q3Kph8xJ0WDqi3HXXcdXvjBj6FEb/v1P8UvPf9ZuPSuh+FLR6WWoUdfcyPmGwbeWjz4oq/heR86H3e/6jocd+X1OPL6ciSSEt2wazv6TYseE1yzfgB+79mn4cmf/gJOuPxq3PXGW/D48y/A48+/gK+/+sAD8LXDD8VDvnopNrsOP/nCH8bN0x1xo+LNJ5S143O5Yfns3FCGeUmbnzBrz9Y0jzktDvGSlQ1LhkEaSmSlYfFdKgqk405vTs7z+i8yLPL+9G0VBjwcAs8gOscvQSu9YTX6zqJDb7sZ/+ev34wTroupPS46/Ah88th74RP3uCc+ddw9ce1BQ9gbP/ERoa0Afeak3XjYP/4CR6dotDV6yr9/DttnM1y3ayde9mM/gP/+l+/Bfa8Y5snDv3wJ/vnVvwsA2LMjdcZdn/d4zoc/g117N/BLb/3H7L4lum19ip/7qediz85tePtrzwIAHHLLXjz3nPPxrsc9FH3X4Xe+94l403OfiG0bmzjxkm/gpIuvwMkXX4GTL7kCJ3z9atx1z824654hasbrnv10/MdxuwtRdRp9q2mlzdof+qxfhQ3WOv2UlPzSxD0eA8DOq054a1MZza8JfoVzNWS1BZEgX+pQENuliEqbKktOu46wKopZibAqRhemMPws+lPioZpDoOuAQzZuwR+/+8241/VX4Rs7D8RvPO5Z+NTuew0iPhT6fAI4QlbK5J3GD8rBGxPHTsbsmBo4wloWXCtEgjqXmXb8zvpB5HValCm6lAnYaSfgUNeGFXaeIidAcOqZOXsoS4j7TkJYuclzKGtmzJ24JozXwXtvxbM/dR7ee8rJuOqQg3HCVVfiBz/6cbzgnHNxe+jaA3fiirscjBMvuQpr/dAR597/HvifzzsNnzrx7iwpedgXvoo//9U/4d/d822/CmctfG+rAae3753hfpd/HSdffAVuW1vDXz/koYAZULAOYJsZWzDiinUbDMNy9BXmY5/WTS/+5gmIpB5dGJb4fDOySqVH8Rtn4CYKfVFQ6cxh2HA9c1kR55IycVBOjwFAv7EPF/7Wq+4cx+GPfOQjeMYznoGjjz4axhi8+93vTs577/Ha174WRx99NLZv347HPe5x+PznP59cs7GxgZe97GU4/PDDsXPnTjzzmc/E5ZffeenMG925dMhtNyeb1Y8996V4330ejOt3HLD4x42+K+iGXTvxJ6c9FlcdcjAA4MvHHInXfN9/xnH/+4146Bt/Ef/8oPtt6X6H77kVD/zKFVjre5x7/3vg+1/zIvzIL70Qnzrx7sl1n7jfPfDiM3+Q6wfcVjb6kLRvbQ3/do+7462nPhp/+ciHYUuWwY3uVNqySPDWW2/FAx/4QLzwhS/Ec5/73Oz8G9/4Rvz2b/82zjrrLNz73vfGr/3ar+FJT3oSLrjgAhxwwPABe/nLX473vOc9OPvss3HYYYfhzDPPxNOf/nScd9556Lrl5UTdpoeZag5DTq7UEIONL+is1GkRsHIpl5CHZhK31PO4puwW+qPcnD2UFaMLK5CX1YiqGqoplhlHNsZ1q4bXzdojN3bI3pvx5vf9Ie51w1W4eseBePGzXorLdt0lcpPqOV4wjJwlmrMTB661FqwYNppL0zHi6ukxKguutZ6zEFN4ID1sWpfFxh6iDTFDtE3rfVr3vYmpQEg2Tyh6rsvhtDSgsNrYQqWeSBC31k9WkFYJRRMRms7md4ErtsuaMTvPiJonkWorD1gHXLPrILz4Jc/HL/3V3+PHPpimBCF63fedjnc/6kE44oY9uNt1N+CgW/fCwOOC3UfgM/c6drhIiOzk3Hn/A++Px/36mThszy24Yf0AYBbaUQooDDE+jHYFEq6ZsWtkxQjL8zWdOJbcg8IwzUXJ4+2Ta7TjMNG4pMQn9SSwMQaE1FEAY0Jaai45NhLzXPdqLIuGGeJ5CfIWKI+MepahLW9Yp59+Ok4//fTiOe89fud3fgevfvWr8ZznPAcA8Na3vhVHHHEE3vnOd+IlL3kJbrrpJrzlLW/B29/+djzxiU8EALzjHe/A7t278YEPfABPecpTttqkRt9Guv+1l+H4G78xbFbPeCm+dvBdvt1NarRitDab47+97wN4wb+UjTJ+69lPxB+d/lgY63HNwQfgc/cYsvkuEulKuuTIw3HJkYfHDbPRStIdanRx8cUX46qrrsKTn/xkPra+vo5TTz0V5557Ll7ykpfgvPPOw2w2S645+uijcdJJJ+Hcc88tblgbGxvY2IgRBvbsGayDzNyj2yxChKTQ5jO5taDg2Nk5kurCEg4Q5r8ji0WndZD6o4oD4EILwF5wW7fDSrCGtEaJuW1tORl1FecedSJeeeqP4MLDjsLlO+/CXGN0GUjxjES53P86DQwIEedmT7HZwfKO0JlGXISMrGM9lwmmnjR2S+mwiEtUiTcdJzEM18rU9Tpwbc1knbj1PufqdVI/6VQ6NCD9e7j2zkHTmc6qYsYs08WwCwnpIemUsvK8/6WX4zf+7Gzc98rBAOM/jj0GD/hajIz++6efhv/1PY8H5hZeJ5dU75CQQuc6yLQMRL0QWYn6MjqroYx6qxqy4jrpuASa0josRlS9HmPx7mq58KphZKW+ZTbOS0JWGYrOJCRRKuLFeJd+w2lnOkJnBR2WAfy3y6z9qquGSXfEEalp6hFHHIFLL72Ur1lbW8MhhxySXUO/1/SGN7wBv/zLv3xHNrXRHUj/ctwDVsrir9G3lnbt24ddsyHzLn2opm6O1/zt3+JxXxpMya/dtRMfv/e9cOoXhiSB1+3aiZ/50e/Dh0+6z+3QtDfaX+lOMWs3Sknpvc+OaRq75pWvfCVe8YpXcH3Pnj3YvXs3upljHZaVO3ZkLfRTAEhdCT1bcIcqpbthpEXvFuoj71NL72Accp+Zgm5Cnpf6Kq3XqoVvied99h5F/43qi4RLS5ZjENyy9dD+UXR/QklWjcWgwwp/M+OXIiujkFeCtDLOzyYnerYeNJxYkHVVjLDKry05Ry/0WYCQy+t04BJV6YC1Wnelx1Fy7hX/q+y8y8d9sUVo4V1ZYqDqwsEzH2+qD6WUVNBxOnfiFVfgz9/ye9g2H7cJ/+zu3Xj6v/07AOAT9zweP/WjP4irDj1wSKcSoVT6IowKxUDqd1QoIAmNpp2yR8YHIB0W+O9iqSwCu9kSyIqtBWPd9qFRPMYKaWVoujC4hKx4TDXSCu/bmehvRZZ+niQYdH9k9TwAg5FN4wVu6bwVzxTflK24C9yhvMuRRw5h7TVSuvrqqxl1HXnkkdjc3MQNN9xQvUbT+vo6DjzwwORfo0aNvvPptrU1bE4W88WnfXFAVr//5CfgB376JfjGwQfd2U1rtIJ0hyKs448/HkceeSTe//7348EPfjAAYHNzEx/+8Ifx67/+6wCAU045BdPpFO9///txxhlnAACuvPJKfO5zn8Mb3/jGLT1vCGEStnOSg0qEVeLAAGikBZ9yh0BB1qoYmFHAqK8d02HVLPxEAjc6r6+xmbVgznEv5SGvSb1b7hlPXJiP9czSL6US0iIAoPuSkDYhIpcgLYXe1R/MAZKPiI/cXJ9ZxC2AmT5aQjE3qRAWNMJyW0NWQMq589gqRKUtypbxw8p1WfF92TqQDmj0LJSN1H+Oft/FdQPEtZMAunDs0kPuiif/t1fhBZ/4MH74Ex/FzpDU8PNHH4P33+8kvOBjH8HBe/fiup07ceb3/wA+fP/7AD70RyUsmteTq7QWM+lGAWEpHVYm5ShYBFo9Hlym60yO10JkNQs+gwJhmYCw4vqlTiazvXD/RIdFL5stqKEkXRIhL0JTzgBdsKTldTQ8gCxm+bjQAbILL0tXVF0h8cHi1CfnjAF8v2AdCtryhnXLLbfgoosu4vrFF1+Mz3zmMzj00ENx7LHH4uUvfzle//rX44QTTsAJJ5yA17/+9dixYwd+4Ad+AABw0EEH4UUvehHOPPNMHHbYYTj00EPxsz/7szj55JPZarBRo0b7D924Yxfe9MSn4axHnornf/zD+OGPfxT3//oVuP/Xo3HFM37mFbjq4IOxnKy60XcrbXnD+vSnP43TTjuN66Rbev7zn4+zzjoLP//zP4+9e/fipS99KW644QY8/OEPxz//8z+zDxYAvOlNb8JkMsEZZ5yBvXv34glPeALOOuusLflgAQNnQtyJJwuwuUn0WcM50lmkHLbVSAuI66Wiy/rm/bDSY9rSK0dN4Lo+ZzWyKtSZA1NWicT2aJCRGPVRR9H9NNKiW3e5pd8ipGWM4YgTSJlfPk73YGu+3gAFfRZQ+MwJ/RpxdUalV4C+P/1UWpgp60CdcFNbnw3REFJEVUNWSUr0ZZFV4Td5qfUbyMioMCys51DWsVIfFbnvMMZdOgaJTpi+LGw1Cty4vgu/84Sn4R0Peww+9puvTX77R3/yJ/i9Jz0ZH7z//TkiTaYXpXVMfZ7MVfWuWan0VRIJj1jmJqUTiEpFp9DIy7JvlZCWVHRWElkN93Ywc4WwKNkkwxW9rvNBZhStlMU+fCANDbo1ua4PGnGFW/h4VvtNcp0kLyTlkKmf1PfU29iXy9BKh2Z63ENfBbt9JwDArYUQOWsWbi0o/4Kppg7RxMdlmCDOg4XkXJYh83ZsWFJUk4sClRivYnxhe59/+LSxRSGcSy2US/VjJvdunrupsjYTDYr+45Au1NeqTh+jfmqyUFk6I3Q87vm3OuQPfxh11ltuu4+rTgXx5VfWIlC5eLnf1IZVyRwtw/fojSuKkXIRoVbm6w9iafOrRfKuigYLVJzXSMe4lP9Mlq4QkicLxcXjBjz7M5/EG/7ubDhj8OcPfSSe9ZnzsEuICl/9vOfhs7uPzcRHOixaylyl4qgxw6ehHMkvp9wPIqNRMF+feVWn88PxbhZN1O2mT85pkSCLAecu/k3iMtrA9IaV+RQIijHIktLzt87GevjbTWx6DYdoCsfp2zkxYq2r8RcOyfp4yYCr39yH/3jbq++c0EyNGjVqdHupcz1+4l/fDwD4P486Decddzw+fffj+fz9v34FfuG9f//tal6j73Ba6WjtxvlMKWl7z2KI6BhXFgkyZ90XYG04xdx2hcsrtmuEu6tyxRUFuhQDZiLAEWRF9QzBbcHogqUsCp1BiYIwN7H/6LfEpSoxjhfv5ZTIgrOdUp2vDRyb8ZG7dunYkrMxt5mQlhNt1dJEkx7OyIvfa9GSRlZCvKQzANcyA6fi3vxYqS6vWzYb7VjwW+4vhaYZsAgHUad/RD/hsY/nqZ1O9LXxDq9+37tx3A3XAQB+/KMfSu5zy/o6Pnqve+N/n/b44V20869Kb5NKdjVMTn6CLP+cRxYuqpTVWdZHMwGrtZmMk3YC529VjqyoziJAfg7VK6JB+bdJ52Y0ukhFgdyPPko7CCk6csznW4S/6L1Ed7PEUcllo5uKaB+LIenZuHNDMzVq1KjRsnTQ3lvx6Iu/hEdf/CWc+pUv4KB9e5PzFxxxFD5yr/vinPvcF+cfe3dsrk+a3KdRlVZ7w5LmnxJNcSiQlLvP0Y3gGBl1lTl2Iu1oWSTN3SUIq8IVL1Hmv60jK2Doi1wRn147Spn5sNJsyzpxp2yuWut78PNr46O5cxmIk//WSFfpNdh013oB+1S7x8aQXtOpi5wuTVavpZCpujS40rlF88QXjyWvqce4BCVV/9H8YOdSeWk4dL9rv4a3/f3vZuev37YT1+44EC78dup6HH/91cXMzq978n/GP9/3ARy9nfQcxvnI1UfWPW1ApiwuvJdGxBp9unx8Fq3BcnqgWinXYLpOszBL+nzv68iKMymqe4lj+uPEY8nWMwFp0XlY8d0jlBdOsk9Iqhs2vXiOSeeqHqc0IIQSc5jCPB2h1d6wGjVq9C2nB37jkuLxQ/fdikP33Vo8994TH4ynffF8AMBvPP7pePvDHntnNa/RfkwrvWEZGVNJ6GYip6K4/sxSKPzEIrMiYnm54tBKOiyvGHhun7LWKpl16nQLVQ47+W3Ua6W/TfV5CSrTyKpi1i7fh+X+7CGqLqB0AsbkbbCaay3osvQ7a7F81lcmcpSZqa66P3F9MHwOSsae6bR0X0gzNI2WKnPJiPfSrgTV0Ek+5fzTd07vUQ7zVUFWjPRL0IouUbo/PhH7M5q8D8f+4sRHY6Ob4tFXfAG791yL3XuuxcSPs8m0WV2/fSfOftCjcr2aXl8Q60pdGsdYNzpSTY8spR81q8qlJCTZ3B1BxHTtgjBLjGKci2NWQ1ZalyVJIa3kOyfvBbrMwNMx04Vjqm1cj79J1j8kKlPHnWgPj7dA8vXpmdFKb1iNGjX61pM3Fn97n0fir+/3yKEexHkdehx1yw24283X4tibr8HuG6/FcTddi903XotjbroeE+/wPx/zPdi7tv5tbH2jVabV3rC8j5yO4CYN+2IoFMHXqPPOZMiJmRTJCcTTqcGVRlY1rs75QlvKv8nvUfqtL/4m7YsFyKrAoVHQWdYmaEdNxSUZEZpJI9IM3UoOVyOqDBmo8wJl1rhhjc6S34g3TIl+XFCGqDmTOViW6tUxLB9PuHA1PqNjvvA5CkkWiK9RVoJgrtxn7+4rfT7vOlx24OH42iGH46OTE4dzYjPbtbEXNxywa7AMqyKgOJcyZKDbXn+tvC9Kx7MxTN+ruK6qa7v8WynxydBkYb3y+Yq/lckkSsvDk6w/+XlOICsXruF4XEPJ8bdIauWjPlnpyHzNF04CO9GGMQmApmaP06hRozud5l2HG3fs+nY3o9GK08ojrJwTkefTy03hkhopx/k7jmoP11xWqT2Km0vOlZ6R9MViZJVdS0hLWZBFFZDgrBSy8stE2ao0Yalxqr0z1yMcZL+TWsiH2iAX0VnaxqXOac597DeLnucLxxY8l88X1EwZeqHflAy7+DnjnLQXxxYyz4V3qP2ER1RfMNJWfVy2den+K92z+pz0xFLoYUwPtezxYqSL2gMLFqA0pgtNZ7dAy3xoR9ZYiRrCatSoUaNGK0GrjbAalUnq47bAveyvVEVWi+jb0X93NKJv9N1HBR+6/YVWe8MyBlmcJTlWatxYx6rH0+TH4rUjg79Ad58peg2gjTv0vWKeovRL6cWr6tBF2fOKbU0NKYwU59WuzfrEJGVyvWrbIlFqMXhwbXxKVPltrJfeq3avEflvxXR6rM+zc6ZyXJzPTLhr9YLZd+78W2570XhBz/PsniZrsL62tK6yttWosu7034AYgrF7V8Yrdyxf3OdLPUe3VTnNemPEmNXkvaV5V+k4/gioe5U2qezbWJhEoe5r574ZKvRR6du7FSatiQQbNWrUqNFK0MojLM3deWNi2gsOz1NGYV4iCc0lVkp5XnMLFcAVmaIhAujo/Y1+jgxQyXm90vZzWJUR7tgos9QMacl2a26xFvjXxv6rcej5+MTzS/e1TG+hrymkK8jutQh9GXWcle1GtIX6XsEY7iPRv6otxVxqQMwv5haPafG8Hic1t6JTcF2uuQgtSa64lookHzdTHctaqpAk9UuWz672nOpr5WtRDdcwL9RBPT6FttdCgo29Z9Z+zqRskt9wSDnZ6To1CAf+1el865IS1L6DnUj7y+tIXaN/I9POdGmb4v3pXmkp12Lyvd4CqmsIq1GjRo0arQStNMLynYEnLqGLuzvv3pQ4rMY9Sk4u49gVt1BJ5Ji0h44pEJVw2jVuS+sZlHOzN/FazojbpabqecBSL16AHpsqOIoRdap9EH7DnFXkunTytlIiwOT9TH6sxoXHPveFcdCIlRwd6V4+PzcyhslxL2ysqa0KmWYOsDLMF7+PT+6R6R6NmCMCdSV1bTouzYEXzKnMQVZeqy/hvhfrqTKGtRK2cD89xiNrsoqodALOEcbcq3fnNSLRbtZP4VRhfKge57dP2hSlOQrldohpc2jd6GDMlPZDhDDyjLYUpnDk2Ju2dUz3FNepTa+VOmk6l411pTRAhkyr8yT+Jo6z+O3yAKshrEaNGjVqtBq00ggL1mTp293EFLiEUOeUzflxpxGCSu09Kj9XyIpJB9WUXMkie+miaJq4+tSqzXHytZLzX3ot60B0SJ78MTnCUsgqTaOu+3QJbryWer3AsVd/w78tICtqOyOcyjvXhsQjDrRLURIjrQzF+NjXmnPX70VD04m/tX5DO8TzvDB5g3XiviVCM2l9ZVEHU0FW+VjE66pjKZBHUlqBWPR9GTlWdLXFFwuXsJMz/cTI05AndWLDZHwwoJlsrrpKvdQX6pwhqZCWkHSGdVRZskq6JgS/HXXZWKCP4vBLExvXa0B7XFakKr4zhXGvICvRZyUJjFsmyECghrAaNWrUqNFK0EojLNdZmEkuY3V0rIaoChx9FVnVuL0luLuMc0/0RSmnUUpyN/zExPO+cEzci5BWDPOPyE1xWoIRnyOUT/lOc2bp8YFzCm3L0Ksei3jdImQVr/XZc7w4BiCOEyMtgbg0slLWljXyHnnaCx7DFGlFEshH6Y7oPWwpmKx65/pYx2ZYPcG07kUhPcmMF/1hkM/zAT2nbcvGqzDG1bHV42V9fp0+V9GDjca60no7Hreog8wFIiPjgwEJ0FQiPRTPQ0ZaYS2KgLesE6NMIQrGWkrtMZH4ISRSJKRFOk1OpCgQPf8klQIwaUTF/UloKtoCxDL8ZpLW47fVFI6FZuj5kEhi1DEjxncJagirUaNGjRqtBK00wvKdgQscgZtKbiHs/FyiWE+4/Rr3WOXuxhpWKYVFjLZAIk6a/G80J+EQPeZt4LKy3/TMWg9lb5BFceCIF9S2uv9G5neTodBY11xVra9lSYiwxoVrFDXoAxSy4rpCVkKnxT5oyrrMjHHo1AHE5esUKzz+JaSlud90smgdpPfglUhAwKqmlZBWNBCjeRDqWm8jVVnlJpWtt4BUx8AoOpyrouexMaVrCsiK6gpZxTWokTLqpPpAJ/xE76sQuzg+ANDFvzVaIgs/NvTj/Iom5ktUUzRmE7FJE4cKjUP4ca/qOm1QaF+RNKJiP6wolWIkRWt6BFlRuQhZZdIWW/6eLhUoW71Ko0aNGjVq9B1Nq42wJhZe7/LTws4/SXU8fpIe9x0S7hDAQt3VqJd90cIPIcV2/Ht4YHpf4qSc0rMYA9ieflJGVgwC+vgbBhXkC0JWRxXuXxL7lnTppWyRKZBWhqyyvqbS8HHd514hrgyBTTwfY2Q1qSGr0H+d534iKz3WYdXeW1zGKEUhLd/beBHA45bOC6Vj0ladiEjZzsOlGmmpRsqx57x5Oi07c/3p+xTVpHo+a12W4IpLyFqWchwzPSSPZQ1ZRVQV9VxCDwlEi7hlEBYRIx4aH7I0NEIfFK6d18eHmqFUYRG4qWkY9VR+/GMh70FIywKYx3YCgLEE6RR65zHPB5eRFM/7iKgARB9WaeVL38pMhxUeJ5CWRtoZ8laIHHIu8ZgaOLfMQA600huWmxiAOngaJ5v+ONY2KvlBzERWauFuRSSYKbnF3qAd/rhUIkJaYNEi1ccNSV3DH2CVATTZIJWp7jIBzL0ysqhvWIVJO7JR0fHapkabkNyo+DyfUxsUOVF3QVktNiyr0vfGvi53ghcfGN6glMmzM+kHhH/Si33B6D/SzY03Jfi4EfV0LLl9FIWYeMKpcYeSFmX5r273hqU2qJoRRkkkqMawulFJ83Zl6r7Q8XvMmkRJxCHWnxd9mVxcGJ+hzgGRcomc3KCS55t43wU7bAz7ZCOTRZsqjQFl+eYGSHlv2hQmFapOuwINJuqVDYs3LmTHS6oVWR81bhPfFE9GYktQEwk2atSoUaOVoNVGWFMLrA07dk8IS4gE++lwXRVZCYTlFFdQc1AFixTq7YoiQZPWBeLRnKzV9T69zhkTUQNxiSzmM8lvSAE8ICy6cdq2MaS1yJk0cwyU/ae5rgKyorKGrGp1THxEVpPQkYysgniUShuRlqV+M7rM3z3pBx/HkMQWjpGvTeqxr2wdtYRrGPGRO4JokzUpd6+DrcqxZyStxr021vLYYrP2CO3qRhfqN9KsvVNjucCgJjGeYTSk5GxapFscP2VsoZEPi3TF/WgdjYzP8PiIhMHH1O2LXuj6mGo4dfWMmmh4Pps5reUUWfme6vnTiLIxJgSkRYMWwugi/HYJk/XcyAJJPRMhV4wuXENYjRo1atRof6PVRlhrQoclSkJWjhFWiqwyhGVLXEFUAstyGYVv5O5SLggC8Wgdlhajs6xdlCbI1uMxMroY6mwHIJ4Rn6PaskARPFwcLlVcd1E2nSllqR6uYRl4rPN4TCs6KzpOhhWdZx2WCQiLkRX1RdBhdaG01ke0FV7LKqRVI+8NejZtThFWTxwuIS8yGbaeHTS5v2KOmOFaZYZuRToOp5AW2NAGyW+G+RD/lm2pIqwS06/qJd3t0g7ewrAi12/5Sl2hp85nyMooXZZRNv8lpJUFCyZkxUpBk+kf2cVE1Rn1GjlnyusntoVu4vOT1bQmAeHNvRhbWstKp9XRraTyqty0TBddCKWkXRS0DmsZV6Ca0UWqw6I2UNsQzf6XoIawGjVq1KjRStBKI6x+auDXUoTVTyOyIsvBkv4EKMvcMy6S2XJVXyIsjDZvNx7RykdbCarUE8zlSYSlLQyVxY0p3Dv+XeG+682P9cxKMJQlK8EFpulSP5VbCYYxKCErAJh4RlaWSkuIyocy1G0sO6XD2hLCckFXRTqKUJ+He2rE5YyFY0vClIPPTN8FR6+df1lPw+Ov9FV9YT4oB9XbhbAK834spNlQz/VVuXVgigxqjt5GICyjS2qqTVnycYQV5iUhZYm06G+FOKLT7lBExGX4lONOTh+etcUYxAGhJqXzgMOziX62YpwBMbacdkS/6Jh+UiEsHuuCPkrrsKqm6yU0hrQcQ1ji3ZsOq1GjRo0a7Xe00gjLT42wDgSXrM/SVoIVH6FE5q51VjoAp+KKSqRD4ySJ4Qh9EedE54jD1LJr6QRMcmutu+DjWj/mt8Z18wukZS0Zo7QaG/PJAQooaoLMGtArhAVlEWgnjq0Au8nQCZ3SWU0C9z0RSKtTyKqzywnNvTfMmZMuixDXhJBWnyKu3npGWzRApA9181QxKZEWW4cGB2LWcyl9Jc8LK8ZZcajRgZheZImXrSEsU0dUdY7a1xGWdvAuWHlGR++oh5TlMlaeMXN8WQfpnWG07DTC0uMj1n6M0KV1VAohQx5OEVX0C0TyXD+n9xQJHJWulL4tPOajHyK6v6prXbTUYfGa1jotJPUBYZX1W6M+rQXr66bDatSoUaNG+x2tNMLqJwZGWQS6qYl/V6wCJZcPEIdR1mHpgJteWihVmJuos0r1RtIPi54TuWTFUWvE1ZsEbQ3XIL1G151J0Z1oSymUS/Ye1RTY6TskOgs6V/OxEpw39/9UceFkATglZEXcd4/JJEVU02542YmqE6qadn1EVqETrEJcmpzQezBnHjphHrjyWd+F54bjoT63FjM7/E2IoOdBpT4K7zsX1oQUPUQjq3nKuccIHmLOqLnkNcIiGkHTtUgXgw6rot+tIS7pL0f32YLfnLTwTM5RkzJ/uvhiXiEOrxAyoypnoqWn0UirMD6hpGupDU5Z/kmLQmq01lFBPYdQNSOtXiArQlpa501f7hGddC2cXCkhp45mUkdNEVVVEdXYdyILtwX2KVuGGsJq1KhRo0YrQSuNsNwaONKF1GHl3D2dU1z+CEfIdWW1leh3NFujuTuOPGCyY8Qdk9VSCVEBKeLKzmV+OHRteJi0Esx0V8raqPQaFa67VOYRLip6DhG9wk9TrhthfLQlIOunJj0jqbUJIauhXCdkFbjxaTCzmliHiSH91nBMIyvmltX4OaHDmocXIIS1Fu61GSbTjPVjlhFBRFrDb8x8qPeh7iTHS9w8sZDMdQ9laez1nNGBXpfSYWUIK9fZZrqIik9VYgFYi/GorDmtQlNd53g8aGw5czwhrQUIGRBWgcpKsOeIJRbzEPy171UpfOqA6GOHmYUPc4nQWLTqJBSWIi0YeU1aGqVLsvPY94SsdPQaXrc1FC1oEcJiK8iujIaGeoq8tpJCRgY0puMlJL8VK8GV3rD6NQOzNvwtxYDZBlWI+i2Po5MblhJlaCdGvYGVSOfRoVFyEKa0dC5c1KcTw2iz1t6MigsBIfaTZu3qo7WVgKj1EENI2lo2Yw5N0cdlyRuV2qBUOQmb07TreaNa6+IxIG5QdHwtyFnkhmVDyUYYC6wRHAxm4QWcH+43DwNHG9c0TCLanDZdh0n4m8zpZyYVEc5p4zJkqGFzcY3KWcTzQ5q1a6aGDQ3oj/T4mFl75r6BWM9Egpq5K0TM5zk6UeI9ZSRTMpaRLglDF/ikvkikC6RiXQDCPSGKdtlwJmxItIHF8VGiXAP4OY1Pek6avg9/xI+1rYjWaR80FKmfDa0icxpVB2qNj4gCNWXO4AUGdOlI/KU1X3UOLzy/YMTWRIKNGjVq1Gi/o5VGWG6CaHTBqEqG9EnPFbl8YNj1tQgjc14MD12QSwkQ3KlCWomzIrFkpCi3ilUj7iThqOlvpWwnDiXcy7K4UXBgd4Cpc+44HLml3OhCoVht3jxxMGRMQQiLDCgCVz4lNMXlXCCoIAqczEN9nhwn8d+67RlZTRXSWmx0Ydm8t2fOfHjRjfBia2GANgOqmroJNuwktGF4zkYoNwPnTs+dC1FhT5wnpbYg9rtXHD2jGBPnRs1xmOYa0uMJLRIJSkU5j3GOqGRpJ06EzCKUPO5+MBHGMmxIwwirjKxsASnr4LQSUQFALxCyNpwZGx9gcFngEFzcb4SeyojLmpgGhhGUEveyw7BY3xz8WodWq4r4kVNVJEglNTIX620lwHHd6MLnxws5zly/vF17Q1iNGjVq1GglaLUR1hoKZu0+N6UO56rJ/wRHyAFlGVmRohehjLosHdonN6kNbXKRxclCxLDuSusqtA4jRVtJqcI69V3kxiLXXVHEb4kzU9xRIgNX3FS1r0Pbpi4zqphOlV4qIKttAUWtT+asq9rWzUIZznUp0poKQ4tp6CgqNbLqlGKPuHDnDXqkOivSVa0HndZGH5BWYJP39VFntsm6rEl4jg/HSScTTKStz/QmxLA70pkQayl1WdSnjNqR1I3SZRWpgrAguWQlXRhz+h3ex0U9pAqVpY1lpmQkQ6jKuORvIDeWKSErTYS0tC6LEPLc20TvCMTxmXcKEQvdI6mbCDW5IOYgY4yYIVgaXaR6LaNcF9gIQ+ivs7VeM6RhXVbeF9otZcx4atkAx6mhmr7GF+uJIVtpns2bDqtRo0aNGu1ntNIIq58Clq0EA8fTgR1Ri+kpgGKKCm3FpJ0Ws7AwI+1i5qcQFkYnAqRUFFwnM1JCWKzDMAnaGq4ZyixApkwvEhuTXqMbK2mBdSAKMupqcNNCeCVg4MYnU9JZpchqfUqoiUzWI8KKyGoo11lXFa6xs6Q+FQiLOPJO6bJq5LxltEXc+Myn5VpAT5sB1k+Nw0Zo074+1WVFxDAc3wj3NMZnehNCXOzUStwrIywb54Z2n1ChwbQD+3AwfVevkBWT9eUAtcidfqUFoHbsnird1VTpIqfCujPvL0LIWpdVHz8nUDIAzLg+lJuu477Wlp6EmvOEnzFs1HxGcCg8T0apRhyKIbBxaBQjq3A/bR04j5dlYdcqeso4piNfpGWsBBchqkJghaXcG4AUTRWsrs286bAaNWrUqNF+RiuNsPwk97VyU5+np5iUuXzpxKj9QnSgVMP1yKZqXYh2POWwMISeREJAChHDaSkIeQXnRQ6BInVaEm0BOeJSwVBTK8GKDByqLl8hQ1ZKRk3sTsmPrZJokYLWTiYuQ1bbArJaU8hqx2RzON/NsZ2QVTi33Q7nIsIiHRbpSOaZDqvDclaCPSxz5BpZUbktcOX7gqJ0zU4wCRlESd+2N1hBMcJjP6Oo2yK9lq35bCnrQW99RONOsPOyJOA1FobL6DJFWkYgLK3frflUTbs+C5WlrTunyl9uTeit1tmHTiMrtTYL46jXII1THMehXHcdW3pOQvTVzRDvqDQ+Q91jg7qJnjkjJByer6wHvbERhSm/K9ZtKUvkJAxbZvkZym9KF62Ol3RYtXRL4vjClDEamVtftrqeL+853BBWo0aNGjVaCVpphOXWvPDDCju/QFgcRFVx+8wRinrHfiEU4kdxwxUfkGK7dNK4cLx3lj3u+8DVURgY9sQPbaMwMTIwZ/RCL+i3hj/CedJXmYi6yN9rjCMj0voNbSWmrYAMMl0V6zkK4ZWAwf+GLMbWhRUgUEZWALC9m2F7t8l/A8A20lkFtpXroZyaHmvhnIWKnMCJ58vUwzKH3iuktc9Pk3pEcVP+e2+/Fp47PI90MqTbknNJI/qaTxAjchvTY2Tp33mMCdmndQDQIRLyxJGRE+ZQSFoKodaItAAk6z8aU45EwhFJUr85RsjdHBOFiNkfK4zX1KYceclakKwE9bhJa09t6bmXdGYu7fvSOG3MSM81PG82S/vPCV2WZ7iKcMwk9y2lktGWv9XAxmPrmGgZHZa28FuAuIpSlZovq6hbPb+MRz9pCKtRo0aNGu1ntNIIy0+iRWCitxpJTwFEr3vm9q2rpqdg5EWWUEgth4rtUikpZDyz6HEfjwExESDVOTUFlb2J+osstTc57YQ2Sb8cpccgf47Y2MILZLJvXzwuOSrmmFTsOKmzAlIfq20LkdXAtm4X5Y6gs9rRke4qIC0zV/Xh/JqJVoJsHchIawHC8hazEC6lB1mbDfVtfngO6a6knmwaYL+2Zpu4PqknnDvptxR3P1M+WzJgq9Z/ekJc9AIZwhIvp6ZB7mcouGIRmHZoS8W3SlgALopEov3mpA4y6h9TpBX96Ahx1ddgz2svRVgk0dhwEz42YSRHyFiPXyjhM8mK/g6wFWGoiww/wi8qtI2QFR3uY53Xk0JYHL3km0JYOZqSkU2AugVg4lu1IMCx9mW1Yi5Jq2uKdLMMNYTVqFGjRo1WglYaYbmJZ/2UF5aAjKymdf0JUJa5ay/7GsJaygdEIay5s0ksMyAiqhlx0CG+Gem45hwNQXDUfdRrAcIfKotTaITlGMK11WbXSSWxhJJNw/rok0MINdS1JaCMtk7c9/ZJ6ltF5a6AtMgSUCIs0lXtsBtJfZtJdVtTM8cUKcLqFowhjR8MsElWZoG321Q6LOb+XUQBMSq80r0Yhd6LCEtZwlF0jGA9SHEjO+Mxp/QX7NsX5gEB7QxNF3x1ROSWoUw54IErTtcA6Xd1tAqpr9K6qmX95lKElVp80rhN2YEJSV9JkpaeQG7dOTV9pn/UfZ7preGriCpS+kmdg5deFuE9S+MjUY6IBwpEnVVMM4KklM3IhllLTKy6zgLViPw1C0AZkT9DVkrKInSeJevrfpKO5xit9IblJ55zKEkxIIkA9UZFH8up/ogKEQaLOVQQ1WXEA9qkllJRsBGGNZxXabNPRRQdbVwkUgj10gcqiglJsZuaypMjqXdGKOJTp1KtmE+oIgIkMUXJzFkr5CdKTKTTgqxP5tlGtXOSGlTIjQoAdthN7Og2+G8giv52hjp9zGjjGkSC5Q8fEdV7flFwfRs5moaVOyWH4eC1TRsXbUqdd/FvxLkC1A11LOKGZQsGGbIk0eCs72CJqQlzyYe+53nA4uC6U6mpbViinHRl5m3M+bcWMos2Jm00Q2Ozbmf8N40htaVmPFMidh8BieDVxmUm2OfJbD1lEvaSubwav61R/LT2qvRKsJU76JsoEuQguMSchkvVhlVsobLBqYoGRT4ssPGFEP2J41L8p0V/NTcHmd+MmB25cc23sGE1kWCjRo0aNVoJWnmEFRPFhZ174oWiv4ysdPK/9W4uHBfTa8aS/y1CWCQSjEkADeaews4M96eQPl0QFzBn21Pg1OH6Wd8x2tKKceKoEc6T6MFbgbZ0eB5WyOe8WZakUiEso7gkW3C81iF5JLICBjGgFgGOISsAOKDbxyKknUEUSCWLAk0UBQ5ljzUWyaWcM5Hm1HthNNOHzpgGRDULSGuTxEgkwiMxiHeMAJYJIVRqj/ytvsaQaBBAH0TCxLVyNl2aF8qtokQsFVJzSrp1aNeORUkz12yfOXjTuR3K0bvkhqDHkJ9LdRViq0SEqLTxxSaLBntYX0bCRGOuK0R5wGuNZuMnlu4WRYThWso2zQ/2LBLkTMaUXoQQlRL3lpqaBTQumLPz8zJXlRRRlcJyafF/FP3VRchazNpZx/dZhhrCatSoUaNGK0ErjbDQeeEcHHd31qOoclpAVgDpsMoJAGWaCiBFWDWKTotDSSht7i1sxSmRwsLo45RkTh5jpEXPYxNRCqRLyMtEtIWo10I4ApQ5M6TMHV+knf6kUlU7XteQleS4NbJaU/qNaMI+oKh1O1uIrGIZ04xMtbFFeK1OM8P8/gGx+MgNb5LynpJB+lTn2flYso6MfnwHsIV67K3xPDfinCFjnBRVOzHGdEwbC1A2jCwUmckTKi7jBLwodJZGVtJYJpqxh/uqehzHEcMnkyIsQlzToLfa530cM0bENSOciLiztCVQpQ4a4PuqLpH0az6bKCZ3JaFLODNkqrwaxYIV3VUxhUwl0HHJsEIjq9o3QCL0khGbtQ1hNWrUqFGj/YxWHmFpS5VuIhFWn5Q6qCrVt3WzaOlkU3n8WODNRTqsmPwvWJjBJGgLADaQIqvNypAY4zErnhE6LL6WuGgLR4nlPJ8M9bp+g4EVc3nKGkgjLOuqyCrTdxCH3c0zE2dtsp6ZqpvNKqJi83bixgNLumYcpuGFKI9nZ9Jx0lwbMbM9PFt2WWX5N+a0Sjdkq8NwQ3IUJQdwnc69dqz6GGVR2jMy1Fz+YitBRnDheNQ/uMzFY5nwSjVkRWhZO3qvCetOthIM99Dm7IvcEoZ3VwgrDAq7GnjHTt88AWicbJ2PZ4f/TiEqVe9F3+tx4LVIvwnVBGmRG0o4Qmuarff0q2/B2pfvId1UlDVgDKtUNlnvOp9ZAlu2Hk1RlLQq1RaZE+tgW2imRo0aNWq0v9FKIyzTSYfVaKU2UTv91JZ3fOL2J8ZVkdVEhYfRqQ3SBg0FcXPWRwQCBB8Qxc0hcKkI/jdc3wL1RtdFiBeNqDi5n+L25GsonxzOgqAcAqV/heaquqq+IyKuLCUIc+pKvyHKbex/lSIstgQM5TbSNRlgjYKNhvfrwkBZM45mHDx6hahiuZgrpHT39GD2CUKuXyEncD4Xxmd9BHFtRviXkFUISyJ/5tjVvbRDJ49tIWX9GLIajsckjFpnleunUr+5QYcV5kPo46oOawxh6T4OY0F6q+EGfHFS1+NDvncyYC4huHnoA5aihDr5V7quj9abXboW2SsY5K8ZDstU8oF4CMmRmANe8xV5J+h7aGQldVlbQFZDGSVMNWSldZ+dcVlyTmscvGkIq1GjRo0a7We00ggL1hdCybjMM7+mR2EusJtnyIq4e53aIIZvcZmlIOkfiDPU3vXWe0Zd/FunkFVAWm7Ecqamf2JrMNJpWQfiSWrIajmEpfpYceOdza1/orVlilSZS7fzDL2uq4gUutxmZty3MaJF4O75moisgAFdTWlcyNdN8Wlap9WHTnHJGJNSIeVS+3A86kp65tAJNRC3P8veJ3Dr1sa5E6wPCXGxLib0VbRG6zlsztylc4r0oyaMtd2CDkvObyAEhjblMZwqi1qZFiRHVGn0irFQWtEPiyKTOFVfrEckfZ4N/dWpcUuvTZFvaXyAoe9JXzhX706ok/qevjlzZ/l7FANbB70yhT0iy002CHYxGgZPP0JDFf/JUWW0Oq4TLNoCsqJPSOH7CpT11lqCJZEVMEhXJkpSNbEOpvlhNWrUqFGj/Y1WGmEZ40Xo+mjrL31IgJx7lPJ5YOBMO97xy7oq4iY5SGlBfk4MUs8Bv9JrZugYIZDFGCejC5fmnDTpWyw/M3LfpFxyaT2aO/G5HFmliEvSovhyEllRXadjMaqPtQ9PZ3yWRqIzKSe9xohrzufXFMeeByxF+C2hXZMhq451WmV+jXySHAwj4silpkiLdFyEtAZfnRAVw5B1KL1HiENouuS8NS5DIvxbmg+kj5JzQFkf0lhnVokjCCu+czqvk1iCC9DyVI3b1PS8TnQA2xiLU1nfsg6yFwhKzQct5RhBWBFZkQ6LJv5QONgoCQnzi1CyHh9uO3zsA5/6aW6q+T5DRBCEyjq1Th3po2jNBMjlTUQ8EUiRzopeQI3p2BBXrAUTXZbSb8n0MkDBQth4XifV74Na+zI6kNRl+QWRYCSt+IYlP6pU+kxxzB2nO1CIOiYV8UNtoxo2ubSjaaOyJt10JFFoH7q/49/QINPHNR1Y5x1/gPTGGze1MMnJ0MJ4FgvlHsLUtnzRV0WCqi6PZ8yA1R+kVGw1MX0SSFj2CYtflSn5FCISOh+jDx3VEX4bSmN4Y6INw6pxoT4n6qUy3KiPDDES4RZaPDUEso0fXyDm0NIOr3KuzZR7A/XFHNo5mPrVZozXnJT3dG3NwkKQzu+Wf1DyceqytuSbnBbf0TVryhlYl51x1WDFeqNaKiitmuY9ba6Y8wYVAxen45MxD6bPVAMZ86tcAIzzgokLolplrOCCwUbcJHI3lLh+K+t5C2btWiRohGpFZgJeVOqQXfq7m38T+mLWi0WhyyQ1kWCjRo0aNVoJWmmEBSH+K2UAHssKDORBT4HIDeTXppxBUSQYjvUq6ZRlsVFOzF34FFlxO7y8NuUsa7l5pEhPozCvri2x39l91HESBUhnU6PalrVZlYDgbFVf5mI+l/9mAXfdMfdsMqMKvsaU+TU+7qPRih6XaDxDz4vcv26bznCsRdXw8pzuC8W5KwReIh5zqrMYLPZD7fel+V9KrVN6Dy3RSNo9EkZJUmlcSyhWPr9I6pTj+TCcmBXuq8en1EVZUOLK3C3VWYSm7jn6nWKUpMzYtYBkwbdu4TVZo+I3JCnp9Mi9srWyRHDnZakhrEaNGjVqtBK02girQKM7/1ZkpbeTA1hExGnOFa9AXN3W3YZjW/sllOvUP2PhevZ3qiGrVaMaN18zsrh9iQhvH42l/gByY4s7m/Qa6VAPdUY0huaXRYy3m2rLk9HfEuu3Ztb+HUSdic75y9D+sXIbNWrUqNF+T6uNsLwR5toq7AlyFOFYt7TYUY241GoKittJfYVH6JUV2lib9DXLmC0TD1Pqp+xadU6jMkchp8S9bw9iq/XFMu/TL2AbiWubls75VB9UOw8ArsJJj/HXum1uCb5Q6z2z55EDseibLGHogmSCpbmVOb8ri9PkvsLcX7alNF70Przm1CV03Jnl1yT1K+uEeY0u5tA5KC3SstTm+Dxbv3bJubvU2ixdU3ul2v3k8aoOrmYxPPK8b4L0vClR783oN09TQ1iNGjVq1GglaKURlvd5iCEvUFe8TvnQeM0h2sjxsaNhGsCWOVFl1VeiyIGmaSScSDVAHJrTnCjdQwcwhcmO6RBNJbSZpzagstp8QdGfSz7XqHYY8ZxaIru8tGIcyqkgenXeGZtxvTGBHsLxgaZc98L5V/hXASL4aEpOsJscpokcg8lhmI/TcyLnrsdUJxHUyMR5m88Zca5YxxJ9vgwSJ4tPtiRMr3Ww/M6ldVNqY+8t+wzmY0qpUHQ9Xs8O3tTX2ulXW30W5rKDfn7a5h42OxfHKR8fumdpHo/V5Rp0CvhkzvzyfThArlE/0mUJneljvlwV9+Ylos7FAAN527Xlsf7OmsL8zOdm/PYuQw1hNWrUqFGjlaCVRliSE/GC86EgkzEkSoh0oLgjTglgHO/4MlAtEDkBilBB9bFIF0T82/CcHjbj0GaKI6NrKYgmtdEJ5BjbrzhbSuTnYr2WPG5MlxUtLUMf6KCd/DzSd5isTdQ3c0/v45L3XRfcKvW55tgpQsQshMHZ9B2nelijKBIcxYLun/rWAE74rAStG0WvCIeJo9f6qt57Pjaj9iufupmn0nJJnPpmeJ4OghzfaxLuZbJrCJHMBHc/9E3sZ05xoedBxvUvoSPQSIt+K8eWfAUZccVwVLLt1vsYxFe9F0f3CGk6CFnpaCCAsDTkcQu9ztFhaCzy96vprCTS0uOg551G8zPfZXN1rsengJR53dI4cZmiKO9i6cX0HUqNtFS9RDzv+Y+0HiCfN0LtpcafnhujdAyHe0i/TJs8TgfLnvP3wzNaJyvpCdxy8zNQQ1iNGjVq1GglaKURViIfdpGbZIShkAenBjBpfLaZt7ABydAWbpWSh3RY0opK6wgyhJUhCMN/b4S0IoSgZopj47aKOv3NSGoEWdHzqF9qOqwywqKSuCvqC+ocEVwXQwJJ5qromKV2B47KpH2/0U84fuOE0VdXLAmpTP0koi0OSEocO1mjKd8Z78FsKjOW6Tvz2GqEhcgRErLapHq4/aZAVtRm5tyRIqrNyvvN3IT/5nEnpE3zo4C89Xyg+Uj30Ii8RKyf1NE3aIi9ieag4ViM9hE4Z0cxGgndOo6/RwkTrU/Hhcaxy9aZjGpCOixCWkjq+reScp1ViuQ2fcfjocvS+AxlJ85ZPgbIcUvLXkh8ev2tcun4SITFiEqXRDSllxjb+JlKkZUMX+HVJXwPjk9J8RANl06s/+FY+g2Yq7k0N17MIfojzullaLU3rN7C9yS6oA9lDMQ678OioY3JpRsVddqmqXcDR1WnYLUc6dvz5M1+oz4UJFqYuy5uTGqj2gyLYrOnD1O6EGauw6ynBZR+qOa9+nCJhaHFD7zGxya6Mn+1ZKOgDTZCHhz0ccIxE9CnH7G5zUWDtGlT3+4z0+Q3HHzUx5I+KtYN11LAzX15drD4Dspwglrb8erMNyoiEjFqEeA++mCFu21y2WGfn4ZrJ+HatB7LsHn7CfeFZmji/Agf1ZAvbe4t93G2cSnjCO6RwpjL8FqyThkBJtbFzMacjiC7TfgtbU4drNMbUdjMgpiI+kRn+y056VK0e3IPoDo5/pZ+o409tDh205fGaS2pb4Q5tiHGi9Ytrde5Wr8s/qd123e8PrO1SIxFX9ic9DG2G9KiQVUC0Xo9/pGUvD/I6VCxhGfJI22uYsPizOZKbMhMT5ifct7EeRXu11vM+hb8tlGjRo0a7We00ggLvYEn7iVsvX3vo7KvJ64u7Py9Rlh1kQJzqcQJMPeQhtAf+61TCtmZEONoEQ8hK+bcXHrdrO8YWRFyJBEgK90VBzcgLMXNUSOXUsQrTSw7EKd8jrexL4xJUSfVTZ+6B1gTc5BtqD7lvFiBs2Vxknf8N1FXMU2P5BgxxeCpSOqaJIAgREVPIRHgBomRwt2IW9/npsnfSUnHiaMX5wlRxTKdD4SsNgUHv6m4eW2OTceJxgxsdOqYxCzbpr/TdaIxB142oNDDRU0USCu6LKTiPBYR6vQwYwiLkXCOsGZqHDZcfXyG8xEJb/SpRIRKLQWZ9zaKB+lb1Suk1Suk1UuR4FAYVaf1a0YQFtJLY0BbGluZf6Zi+S7CGGOr5KxTdYNJlufPc/8sQ1tuxUc+8hE84xnPwNFHHw1jDN797ncn51/wghfAGJP8e8QjHpFcs7GxgZe97GU4/PDDsXPnTjzzmc/E5ZdfvtWmNGrUqFGj7yLaMsK69dZb8cAHPhAvfOEL8dznPrd4zfd8z/fgT//0T7m+traWnH/5y1+O97znPTj77LNx2GGH4cwzz8TTn/50nHfeeei6sl6oSL2JOiwb5ahzxS2aeZogjZBWiRgdqcy/cx0y37iMo8x1BqnhRO9NVKYzskpl4TNGWkoW7iwjK5KJzxWi6jXn5myud9LGFiWmmJWo4b1IVm35x8k9uk5wUktG77XGZUkds0SAqnFJwNECZy6Js8d6FzPiVoKZaq5NOgPTmM5YF5LqRCJqimWOqIbyNjesg9v69aQuOfe9/XAtIat9c6qnxhezvksU+0BufLNMGK48Gedw3JMLA3KdrPfjYZRGgzArAw4mkpA4i22UKTlINTY5U3N0bwDGA+xGp32b1KUhD+msNLKi8clR70SMTxj/UOdxCWOwOY86aFqX/TxFWn5eQFbDi8PwsaHQuqvs1UfWsbA3Hy7V9+gKcRCU4zC5MPguNehJfqINu7q0PhEm/mSENWRkXv6bv+UN6/TTT8fpp58+es36+jqOPPLI4rmbbroJb3nLW/D2t78dT3ziEwEA73jHO7B792584AMfwFOe8pStNqlRo0aNGn0X0J2iwzrnnHNw17veFQcffDBOPfVUvO51r8Nd73pXAMB5552H2WyGJz/5yXz90UcfjZNOOgnnnntuccPa2NjAxsYG1/fs2QMAAxcyD7u4IfNLz9Yqc2VuSUiLSFpN0d9r7PAYOAGVWHFio8nUVhGW80aYq6ey714hLG0JOOut0F2VkRVb8pC+yglOaJGVoBBn8yGVxI1k3lQaEbZFc1U1IvREnGnpnKZOm6onPwolGSyGsV/j9OZzTlW/5pWurKrDiohCOo0CgxWgrGtLwH1uilvdenJsDFkBA6oizp36hZD3vj61PpPzQyMqpxDX7UFYdGUXoFZnbUyFrp30s5BQYTDEV6UWeozcHnQIpanp2RJtFsZwaoJVoCHnYpXUUobSUgocdgJmF5No8Ufjs1HQVQFxnGhs9vZTHg8aJ9JlbcyDTiuULA2Zd5jPUx0zISpGVvN0jZo+Wgka1mEhvWbMSpBISUpoGhhex/GbwDlLZURrUUa9tXC6D99TLWnR7hSTcE/no8SCnb6dxXy+OPAx0R1uJXj66afjz/7sz/ChD30Iv/Vbv4VPfepTePzjH88bzlVXXYW1tTUccsghye+OOOIIXHXVVcV7vuENb8BBBx3E/3bv3n1HN7tRo0aNGn2H0x2OsL7v+76P/z7ppJPwkIc8BMcddxze+9734jnPeU71d957dkrT9MpXvhKveMUruL5nz55h05pHToR94oopI8qvKdGA61I9wDTIaicu5eas8OXSiKCWWoDDKyEiLHpOSVcFlC0BWRaurY18yrEVHRA1slqCM2OZN70nKTgU0kJnQIFktS+nDg01RsskzdT+NfwcQtiWrMIGrnzquwRtAQVnVaUQkM6mY348AHKLQL9W1YnkHDshrY459oiwooM1EJHVXCBujahynzuFqgsUncTLVoK98wnaAgDXpVIIWjtJoGY+ls5RosxXMVw3NT2PIfnh2eCfR3VOrLiEDisGmS4gLOVnRXUaH61X3NdP68iKdM8BdcxIhzW3cOGcm5HuipBVmMOEoghV9YajULEuK/V9z3SAxYwhSofFSIv9pkK984y2+HtQQVyEtLzzq753fgAAOGtJREFUwIT0nKmExxLSEsgKGPRVZHVNj+usQz9iU6DpTvfDOuqoo3DcccfhwgsvBAAceeSR2NzcxA033JBcd/XVV+OII44o3mN9fR0HHnhg8q9Ro0aNGn130Z3uh3Xdddfhsssuw1FHHQUAOOWUUzCdTvH+978fZ5xxBgDgyiuvxOc+9zm88Y1v3NK9bQ+AuBZhLsbMR8bUD68bOc/IKRKXOrUUtDUgLJKTW2XBtpQfVs5FaoTFsnWNqJS+qu8tekZQ2o8jRVaJx7zy2xhFVpoU0mI/LGaPAjfuPHNTmaXQyAyrhQwaCyWUh78KSNWmyGebHeIgrJme0VbnKZKG4tArfdF7y/470cpMR68ISEtYBhLCirorrbNKkda+fhKtzTSyYqsz0o3EedPXIigoNK3T0EiKQ5z62pEvo7We9U20BjgEWOCke4W0kpBp3TAOOq2Etrakct3O+W9CVFMbxk9FQCHSCHl4XurDlYVZEoFs9bjkyCrqrWhc9s4UEp6l48N6q76rIiujdFgSVfHf2qLPpcelLprdJlOhk1i3oco6abqnYetNHW+YkRXX6ceex9Q4QlSp9TDNx46+E9bAkk+sCJzbb0GHteUN65ZbbsFFF13E9Ysvvhif+cxncOihh+LQQw/Fa1/7Wjz3uc/FUUcdhUsuuQSvetWrcPjhh+PZz342AOCggw7Ci170Ipx55pk47LDDcOihh+Jnf/ZncfLJJ7PVYKNGjRo1aqRpyxvWpz/9aZx22mlcJ93S85//fLz5zW/GZz/7WbztbW/DjTfeiKOOOgqnnXYa/uIv/gIHHHAA/+ZNb3oTJpMJzjjjDOzduxdPeMITcNZZZ23NBwuAmRkEtQRbFslYBsx3Kd8jHfi1dy7jGtkyiizKvgmExb4HzlZ9ZghRMRor6KuYc9FWRoSoCvHHsthjmf9GAc3ooJmaI1P38p2QbSsfrSydCf200H2LEJfzNupGiHMmCzLioG2qa5qaOeuwtFXZmA4EGFCVDpoa/XjSeHP7RD3XhaT1EudOVoBaJzIjjn0JxL3Q504c09IH1mGRWsXFeU46CfJ1dMq/RluF9dYmlrEAMA/WtexvSLElqewi0mJkRSWPJQU8Xjx+Onmq9sPaEAGHN1X0itL40Hkan2gVmOusAKAnC7q5hZ+Rk1lAJHNVEpqiuhPWgdoPK0NY+btnq4i+jTa9IFr9inVq0udk6U0YRcVzPP8oXUm4xtI8cTS3TILch6Z57qtlyHg/ppL9zqQ9e/bgoIMOwj1+6XXArm0AAD8NsHPq4SfhlVRpgpLQhpLMMLvO8d8T2phow7LlDWvMhCB+lNMF3TtbjKgO5E6/Tot7RLiWkqPhUA6FnNy1YJljE54ndG3DImMLVsz6eCxMVtOlfc59HeqTSY+1ybDZrE2GVbkelPnbJoMYaVs3T+rbuxm2BxHTdrs5/CaIi6gkUeB6KKemryrrbbZ7p+RgR3JZpaJAqbivOQHzh3CefhA3+kl0GO/VB1CF9ZEMjJPGNUDddUGOcWXDYsW8TSeIsZ7Hkpm1Ll8/QFw7k85hGsZyjcqwYfHxMF5rqr5ue0zDtRO1cdH9o1n7YqYxN7qImxQzCSoMVml8gGFsNmsb1SwwFDQ+tEnNbRT51cqwKVkWCYqAsiQt0+btgcbslDL+T69rWr9WiPOUsYWXa1we7zyLEelc7RtAx431PL+sEEG72/bh4he+HjfddNNC+4Q73eiiUaNGjRo1uiNopYPfJiJBygTsBbJhzBoKFlOEG/jIoTKyCTBWKwcJYekQNiVy/DyFsHye7iNDVNpEXQbGrCEqdTxxNtSOhppDK7SfmXCNsDRnJtNNKPjPZUU8lTgbV0zfSw6qLFLtlDK9UkqEpUWCJWW9pCErbeCcOYBxOQ1ILHOEtY8D16biJDaN7rsYykeF38oDpkbEXUxLAeSGNUu4FGQGNUJRT4GLPYkGvZqzATU7MsIQInYpJgREPi+u92nd9uycTyG1uK5dTLYQgDpm9h7KDSdThSjRYGF8gAFVseN2MLLgcEtkZEGm6kIMaGYporKZKHAobR+PM7JSRhc8ZbWkZISydaskJsZElM6IyilExd9KcMlxp7Whhku/BdINxmiXGAO4LYgEG8Jq1KhRo0YrQSuNsOwMMJvELoSdGwbEfrAhwJTqKddP2WR9Jzgycn5TykHiELWDZYlq2X2dy/UOVUSlDSl6U0dUrJhNzxuPjENbxqzdqD8yc1ilmDW2wG3xcxRyJAdjjCAqXQqEpZ2x50GnJZX2QEQ863Ye05UsqbSXCnutvI96jzLS2pQBUvs0QKp2At4scO7zOelCaD6mnHuCqipJ/rJkf0iPJ8QoOoyPdhI30amUHU4riIvaPJnITOABgQQ9Za8QV68Q16Z1rM9inZhCVmQIJVPVEGUOymrcZAZvncpnbHzo+FzprMgAyoU6Zum6NTOL8Dq5zqpy3Lioz9K6qyrCuh266KiTFsiJEVaKqMgIBxJFLTLMYE+jcNz6xNCDXoBR6RLUEFajRo0aNVoJWm2ENQcM5cnmpG8eljn0cIrKKVWVGebEROc3Nt3NrVkAJKFsdCQpbW8Z5b4RcWWy4DFENbzQ8DzBUeuwLZr7kk6GRuuwataCst2KIyuZwSbvYAvcFuvMtG4rHPbxQWxSS1nTC7o/Ok7cMFkQzpWOYj2YSZOl2YabVK3MiGohtnrYzLqMkF1MXa8syVwnki6mTsCRY08tzYYAoKk5NCPxkRQUteR+1TTqJcrGOnLDQ2mivoGkAMxB0/wjx1EaawsXEBWHPGNLWdJBBgd9CjVF49b1jLbYYlcFnv5mnPfnPI62GFAYyJ20I/q1jLAY8bI1IOmpgiSG9VZSd4VQxnNASUKSWgzKcxE9649NoRO0REQhLK6L9CKss+LvU7iUxpbCLXU+rlu2Xk7vQXpt1mF1yJX/1kd93xLUEFajRo0aNVoJWm2ENYtcCpHxhnVTRF4jLuIe6O2didwh+RAEOb0TPgSAtJxb7ACRWcg5Uw6fBETOmTgoxVEPlkMVRKU5tMQPK23DAsO44Rr1B4d6IV2GkoH7Erel+5jOE7r1JiaF01ab017+hMfNeYN1lUBO6iQAYFP59UyNY868I2fYLVgJ1nQgM21hJhCWdgLWSf20vmo+t7muiuT6NcTdmzwwqgrDNZqCQjG6GkUnzqYqFJfX66jgOBrD8wSkxdax5AhNPlvknxURF6EtssyN4dFi4GlZligLi0bPp/EUCTBlQGE6B6TjA2AIs0TpjKSfFQq+VQFh2T5KgTSy0ijKCsQV13T47lR0WMuFWNN6IyR135uIrBRKigFsw2/D860zcY1rHy0tVaHkur1A69wWA9MQVqNGjRo12t9o9RHWZqgQFw7AMgsRjgUrQauQD1sUCYTAXGMllcbtQ1iCE674zGSISqOn3tQRlfqN5Liz4Jlb4szCpZozE7JvQHFoOgBmhcsf/LAs/52eM9VShrkCgHUfdFnKr4fTqnf9QiszTU7AD0JLOqEnISpGXH1EXDGsUhoNgQMcF1KmZ7oqndRvHrnU0MgccWdWgurFlrAkM2wtGOpW6C61NIB1WaTjIp2wZ6uy6LcTJBbK3zFaEw4XzqxjtKXDo1lloVtCWrU0JjrYdO8sIyrn0jEcS2mfBbDViIp0V4SaZrkOK7cSDHVe674gNUnLUStBhZ4XWQl66wWyUhKSiq+V9MPKEJVGWuJ5Rj0bJvbPMtQQVqNGjRo1WglaaYTVzTwwy4+z+T9zHcShBy4vsBxW6lnoR8RhKFl+JgcWx5h0RAFlKScbZxS3WkJU8hGJXLvyG3qe9OFYFmHp1ATDwbTMODPhu6G5LdIjUjfG4/H5y/hqDXUqI8IiKzO6Rvv1dIYQj2MdyLJWZlL/UbIuAyLHrhHWzNlq1IroY5WiKTe3MZmfSOI3/Cjl2I3UaeqxVXNr1EeHSCEsPc8HrlhbgSnEpdeO98IqlLhv0lea5HgpwgyhLR3Ps4aw5JTVr5rF7OTn2tE4jUMpxgcoxwUkZKX1U1SKaDxWoC5AjCmf93y8jrDCNRpNF8Y4Q1a8jnPkk0W4YCvB8F6kywo7xhDwGum1mbWgQlwWbLEoU5xQHy5DK71h2RlgZjRS+UvXzMyhHIi9FwpE+tiTaaZQDgJiIxPH4gN0A8JlUvynwyepaMzZJkRKziQLKdJrnb421pffsEKfyHdaKEoIZWHyxrBXoUqBiIW41OnxAH3U6CMznCa7mmHDGv6Opu6hrsyk2YTdui0r7UsbFju4qg1rpuvzLvsQSqU9gKi474VJtI7k3acfwBKTUjKykdcsE74nigKR/JF+zMJHko4VwvTIEg65iJ03jvQjVnLYr4VH0xtWKUyatvZ2asOSzxsLewUgGr6QyKoUZikTASrx31yas9M14VzYoLSocDBrLxtbxLEtb1wJZcxI+g1Lx5j6JRxjZjTdwOS6jkYXQ0l9rzMby3sVDT+U4dwYNZFgo0aNGjVaCVpxhOWF43COtDTCirEYU7GVRD5Z5k3FESRbfA3JKmMLGXh2EVecIa4k5UBoQoa+6nVCTstz3fFEKUjmUA+cU0kBS8hUGFcMTQmcZzjhYGC9T84ZNnn38hYir1lEWMQNR/Pp4SpGWmQSbR1mW8xpJrnxLNcTORKPZIiOiCpX2gPIDSt6U0g5EfpLo2oxP2qpJ2pc91bERlJko8cbpTA9oh1D3K3wtxATJmXF6dhZXw2PFpEVVF3M2Vq4Ly2CdDEQdTHQNJCMDzCMzUJkpcR9dpYjLDNPkVVmjJEYXVSQlvx2iePJu9eMpTJJSTQ3p/uw4zoHv0Xyh5dm7RXDDL2AjTXZs43x8AW1To0awmrUqFGjRitBK42wTA/Yeap7GVJHBC4qXMe7suL6E3mscopk5aAw/QSQmf0W26U5XEJaQqeUI6uKbkvoq8bOpXWf/abGiY1x3UZxZlB9EVGVyczXSdWnDWCkHlGjrow7ZsQV7uWF+4FyOtYhgCYBFfTWxtQwLtWJLFL1ehTMooXSHignWNRKe+bctUm04OSjqXOOrOW1JcS9FZNnbVzDfaC4b1nPjGw0aiIunB4ndMJOtWWR07HpYrBdp40tKkirRFmma9axkr7KCCOBFEmVxgcIoeC0iTojrlBXhhV2Lv8O7dY6rUyX5YU0xSf35ZBMY7qrQAvHVhhDOGWKbpQbQoainM+MLaAQV5YE0qbIfXiQietiCWoIq1GjRo0arQStNMLqCjqsHkYErC0jLV2XyQRJrxUtouhHKUs6xt1lAWbpuCtxxSnnrJFXkja7hqhGLIrq3PcIa0aXKouxzFqQuTIPnZ490x+qe1uRBiY66uZ6yOFo4MKDWzgw5IwcnmPKJSEu59FRaBhlVTaWIobu1bv0vux4qizLZDqQLBXIApN1ybnzeOmkftqSzBfmwwI0nSAt9UdJdzU0IK4Fp/W7OgUFDXoXb2hZd0U3DgXrOSLiHgqfOetr/Yoet9I48jygukrrAxkmLQuDlo8PEHRYffw7OaecgaVFYBVZaV2WQFP8G45LhqQeJTWqjoL0h3SQKklnoqen/rJ6vFLJk7Ty1WmadGCGEtLieSXnYrMSbNSoUaNG+xutNMIyvWeuBFK3xJZPKcdeQ1rSqom5BOYwFeLie480rKJDGBBPKu/N0JJX9cQ3I214Lt/OS21ltCXfHNItZQiL0Gg4bpFZ/HF/qntLpp9DaBn1W+IESY/ITbfsq0V3duxAnOq7iEO01rEeyijd1Vjw1OH9oh+WtjbrVVqYYur6JZAVoDj3BbosOQeqSf4yHSodj+/rlYhAIyvJfdMx1kNqKzAeayGl4KznCj0rpAWl/4KXa88kD/YmXYtZ4yVpnWmGsOIxHf6KxquUYDG3+EvrueWfX4ysqE7reS6lJp7vM9TDfZWVoDymxxYKWTHS4vQf+djWwqVBIOZodU2nwjqm9UbInOaf1IeKbwr7vi5BDWE1atSoUaOVoJVGWHbmhZVgOGaRoi1EKzTWaUXGYqjLXlCcn1Fe/caI52nGTjHsMcpE5CpLAWqTssBJU91oRKWQlVWWREUrQeacctk3vwajyPTdo/xZyaw7iV61XoqOp+QARH1gioAYgeh7Gc+oRUfFsKHu2JQx/NYa4c/j5GuxHkzrQHwip0+RVbSasmldWgRuQScChHFaElmNWQlW9RyFMTY8IcIl1MU81gIJqbnj1BrRZL2B0w/lSZVKPTwI9Qr9h+bueXJR34ffjEg5ssDTrPPJEZYOPB3RkdIr9inaAgrjUvC14pBMSyCr4V5eHFNIK4Z6Sd5XTmGWjKh1bFgnqNb1REomkJyLOitfqKeSqyilIgRH9fid0PpVb2PfLUMNYTVq1KhRo5WglUZYxgn5cGLrTxx1iqiIw7CKM1jK4k9zK+I3zJ1qTragUxhLZw+MRTbwda6bOUAl55Y6rEyfod5PUPS/SjnZzKdF6K0yC8xML5Xe2xoxLjw+SK5lhCKsPjkmYZ8OmjdplAxKfWG8j8F0AxrLRPyEmrMoCeKdOXhvWtdREtCbHFnVfKoE524LflbAyHzoC+OuuNelUsmoMYhAKM6l6HcV2hQuKQRXYLJsoasezj43CmlR20VcymztqfqYL6T2gcwQls+R1aLg0lbqGms+kYVx08fY70ohq2hN6ITUJPyhxhgacZVIBe6OCy78lqKLSCWWklDEsc6lHiy5kggKhXnhxcAVxnQrCGulNyw795mYzIpQMjyJSJFMUYSV+MP2I4tPd7DApJnzJV2qNwfxAdEflbrzL5Xx/ZbdqBLRoH5eQVkrz8to9PEjlipc9cdgMIWgvweKm1G6WKJJdOGDwAxGKq6Km7qJzonMQIR6n1TjxtlF8V38KmqRUr5R0UMyc/nMpFuImKjUIjq9gWVi4JHAxqMbVs6gyHIrBjY60DE7+lpxo4qYN1s7BrxJM3OoxjQyHEocy8LBKC5k4wuW4VbK/Hb5xiXdSSobFbK+F6LbyrjozUgyoNVAtplbSrwu26hcWmbm7IWNKwtywEYsJI4NVbgo+qaGT+ijmbYdUnyvRfkFZj4lD6Gn4UNNJNioUaNGjfY7WmmEZZwXCCTs7l0BnejUHZyTInIgNa7Ap4wGJArOfqNRS0EMVzO6yLnuknhv/Jqy0UWKihY5EBsnEBVzZmUOO97E5FyWapNjVEMKYPHOhJLU+3nJDSMo2/uUi6sGbw2HHT0LgOOxTDnMqtGFuGEVWTFXHkujzaUXiIGNQGUZAq+WfuE1yyCsGlopj7gS4ylxoryHHhdGLxppKTFVcl9lmJF7O9deqtBk7teIoqr9x2K39PjYb6pGVHKcWBpURk3JcX1tQFwZoorRpXNS4eRq/eUhho6unbOMIvxPokBxXTb+JEY0ybX500RbrBmfn4oawmrUqFGjRitBq4+wiAMhJXvCBY1zuImTpOYSFXugQ4oY8XdGFaSVcNKaC1acWqZ7St4rlV/He2kdk7gPOyaXdVhpeyscrea7RV+NOZ4m7yPazKazKuQPIxNOZSDOq0CsmSKFmUkhX6dXVuG12KFSa+9FnZEVK+8VosrqKHDmKYer3R2K7gfVeRDHfiGyUnO4qKDXaFp3hTjk1drQyEqOtVHjkY2bBuvCQIARtTJ5j8/RCyx/rTFkRfXYXzTf6Fz6m2QNVscnRTrFdVtZ6yUnYW3GHlGfS39bioWm/DaiDov6M8cpmbSB9F/KnD2Za0pqUnORKH1T43civusy1BBWo0aNGjVaCVpphCVTwEuOipmEwjl53AjuITOl1feoIIYx2krbdJvGflt/n1CW5Ocl9FVoa8lUOHJASt9AnLDxrBeiaxPHU3n/kb6ojgFVvSmjSNnwTMYfU12w4yS/TVlxKduRhfaptJHIeJO1ZdGYy3ssQlrJ8Vp/1ca8QOxkykk083v6rL3pZPG6rVY8col3TupOzEEVDojbLOZdRqXxSNoh6ov6uNTWGvIdG+vKnK1/p7zoD7U4ashK9hEPSDqmXusLheWfHluvUKee94O7SPkaU5kfpW+Yl++9BDWE1ahRo0aNVoJWG2EVKOE86RijljqXXEMv0udtuEc4XrEqlNcUObWtcpzyugoqyji40n0qdc2kGj/+bsvSIvQkVEs5CtNtlb+pcNAe5T7wPor0mSNkVHE7KNN3VUrkfbvMbxb+tnBNxqkvuB6QKCacoz7RFmWFObuQ/NhYKtRUundt7tTmZbH/Cu+x4DfZudpaXeZ+hXkQv0MFVJScL0laKr8dcxzOFkva90aMBSFsaGkE19Pfem/E+FS+r/xe1J7CdwDLzXWihrAaNWrUqNFK0H6HsBrdiVThVkvIZ0v3+06mO6KNW0BLK0Wr2ObvRGr9uDQ1hNWoUaNGjVaC9juE5S0yWbfXMbUyH5CCaqJ27TJtUK4twiwtHiy0oUjCt6Eao8sohcQYLbh0VH9V89UxlWMjtKXfmPr5zFJsTLeooyzwcXVPectlu7bYtvL9s9+YfM7U4lSW7l+LA1i9vtCGPOmfKBe1f9lnycZV2p62afFzsrbUxkmf38o8l2tQX7NEvd4X6YB5WVfn4rxQ1pz8kJIirzIB1fcwGXtbOFZsuxwf9X3VTZPjWVjzW9GZr/aGZcuLVvt4liZeVh87V6rL+xJphb/+kIy0CWrws4+r/KjV3k+HkTKI2WEppJFqZCVNUfI3b/hqMssJu2xfj4XvqX4ouD0+ygSya7UFAjct/6Dr3yiKIYFif+Vt1TuMOK+dL7Pnony88F5jvy2FREquYVP1+m6rw3DpteML/VdlAEsbTOV9atbmKVNX3tx8bdNL3it86J06KcdmUf8tMT6j/cbvo9dP2pZ8jE1sJxs7pB7yZKI++q3ncQpX2fQ439vIdqt5zVmKqRningvW+Ni3eSmGqEBNJNioUaNGjVaCVhpheWsAytWT7PxljiZDS4LDiMfSa5ZCWkjPZc5xgjnKuGLtiKwyYSScO58zyUURUdF7xx+xI69CWrGtuZgs47o515jqV1Fm16j3079J3icbF59fG0p93xrHS2a5sJ7/1siqythJDj6DoKpWGGs2F2ZHWjIRTjldHhtj8nFnc2J1XIx95mJRm1Mazshr9SUjfc7nKmOalNncye+blnHMqxy7zedqRvq9rEJasj9VBm0thzVKVGdM4ZtCY1mZl/J9uFShyDjfmDQpZ+douh/NYXoPNafGRHg8bjZthxQZdmrN629kYRxr38TsO1FAU1Jas1D8WHiVRo0aNWrU6DuaVh9h0W4euBbf1RHBGGdYvWYB8iq2q+Jw6MfYg8zxMEdRyoeQr6GsrvH2EhUo7lp7dGoZP/J3zXRYhf4dQ1/62vib2rXh+aXjjL5U59pyaSTCotda0tPWeKH9sbJPI3mNXrxoG3PwClmp+WBs/L2vIitdmmzca6iv5JS7LMLyVqytZdeTKV3js2uKvxVjrH9b1W2VKCo+h2oIji3TuHi9Nirr1ci20TnqEw7Zlko35LwvHZP1iM7Ddd7wl5myEXvqDJrLvWpsiRRyYSSndFhDG+PfybVZm8fWfPkbIOeJvlZKWpahhrAaNWrUqNFK0GojrM4I7idyAI45QrpuKPk4cQ8SlalrlpbBFxtWKWW6h2XuIy5wkccqWLCmSCuKpmNiRZ1KIdOv1R9d4IpV/5XQEvdn3tdUapk+ccH5vTyXzClTv1Gd0stQGThRaz2MDcnvlG6imrRTQBXHqU5CH2c/ClZbCe8XrqH3oiZLDlqcd97D6mPhTnzXElqqjLuebxpcS6rri2JZGm9ZZkirk9f68m/1mNO6s2KMec1VrAJLSCuTVISSOzS8S8RX0ZrS18dnaJrJ1k2GtFx+nP/m0EX0nPQ1fEhL7+DiuNMXmtLI0/1N2mbIFB02naO5TpreL0dYbqIQVqePh8d1prrG+Rtq0/ogEaO/qW0xseoy1BBWo0aNGjVaCVpphOWsAbKdv4yghtLwNfq8RmV16zayHKq3K1oJav0RIjfo0ksyziG7f0FnoX+rnA2lDwhzV9qycIQySyHFfTsh5+b+DzOqhKhk6bqRazJkFRrUiZetICtLJaEq62HZSlCXlfcWfWMChOdEdo5QDSk46EqBtJSaMGZzGC62fEHk5Pn+Sq+iDA1Fw+Tf6bir7BLixZDRIksvSPS8UHIRSz12C5GVQNHR2lHpJfVxanphHItWtoCQcpjoq0WJDrVFqEJa3ns+VkJSQxnmh0wHovTRuRNaeC1hKuxAUoGApGgSke5K38smkxaSMgdfbVltc0Q1hqyoXkNW+ZhLvRe/IreN58AS1BBWo0aNGjVaCVpphOUnhjkAWTrF7TvmFuh3oSxx+xk3WZafl8KMZJy1UxyvRbTKUzJpkUttKMN5iaasIT1Kyhk69Rsj/EYYTShYVk1rot9R1ivWQCW0lHNm6Xlv5Tj49JrJCPdNyGoSOFBCVKFuDSGtUBcIi1GXel36jVOw2YffA4i6rNCRJigFCWlF9aTQNpKFF1l80X01xw0jdFYKEoR70Nxl9UQvbkgIIZxk/x62SvT8PpqyyAZ6rA1G1oaqC/TEa62GrCaEkOk6gaY0iuY5nK5FMyYm0H1Mc5bT03v2SczvopWBpHuKh1Q+xRwtCX0Vr+1Mh2XSewSy8PBhnllCVNkYq4YUlOF5FJN03VKfuC7qlnjdWr1+x3RYSM5piVai21T6cFjA07dwCWoIq1GjRo0arQStNMJyUwPDyApcev477PAVvYrkDBZZqrHMlR4+osPSUSukpRJ73puUG2Y2i7iNcH+JnqJTe0RQwz0CgiBOinxNHNjDP08qqeCgJMWR1SwmJedUswbUqDaiKMARktLjw7/R3LhnZGU1wgroqQv1jhGWQ6d0V12mECqT85EL7gPH6xTi6hnthvPGwhllOUjccfYEycmn3HaGtAhN01ET545WXfL4MxM+NlnTx4z7YakyW08RGfM1Ci2zBaCuWzHGwocuLaltXjaxSF7pobQO0vcmR6jqhjT/aSycN/Fv0kdqxJVJLgys9+k5heCMVsKZgvREJVBkacrI2EYUY9J65ldp4ppj1BXqmd4/1vPxL38DUh87dcwIq8IlqCGsRo0aNWq0ErTaCGtiYApoqp+myMpN6ZqhLKGAhciKuZMoR9fMjRaps+7KRY4metErTol1JEiPM4cl9FpK38CWa9rnyuXcdkRYJqnHlxDtr+qwVCnk2TVrQafQk5v6HHVNU0TFyIrQ1MTDEHIiJDUZOoUQFZeky7KOEVVnUz1X4ZWH54bSeRMRVmCPe0ZWpMsK14ZnzOeeoQBZoTmTTibNaHtjRJtoLEON3kPrmvrY/3R749JS+/mUqBojU/ph6fEv6KySuq0jKx5TiahEaazPfelUZBLtTyePxczxJqlzVBgZ3YF0WKaMhHlshXWntvTUeiga6VQvpXVi1CSj3i9+JyyNaeg/injB348uXb9b87FTSMia3PJXoaNMhzWRY5uiMO1/ldQL82wrOqwV37AAEzYnuSkt2qicFjmVjC50ANbaxiWIjyjDBjYld4hpAdSHgcxV6XmWdiUazD5vC3+oaHNTSne4KC7kNaGcSe8IowtfFA+k9SimjWLATCQ4slENpYsb0kRtUGEzmnRDZ0zFcd68lGhQb1ya5IY1D96NPW9gQ30eRIF03hiPPoxlT3IvEhFq5XcYSAO5QQ2lnacblFNiMWMNj7sen5w5SevyN0RZaCbEus8+PPkGldQ7H3/Da6y8UfHm1EURL4+TcP4eyrIDeIn0huXC+NDjXW/F5kVrjxiNfHyAYePSIkHqVJuJdJHUIe+k3Sp07iuRuoOZEMWU8Njq9VygYjgkdTwPtqBFgWnpCkxq7RuQiJcL31M3H2m8oiYSbNSoUaNGK0GrjbCmBkahKDc1EVlROcLlA8RFlrnGLBDnUoE3U4WvDGzKHJES37AhBXGAIxx1VMSqUt0TJaMLFhGOcKdaCazQZcm8ucplKfQkTde5/6eKC58SsiIDi8DFdj0m4dgkiAInjKyGckoIy0aENTHEmafIahmERUhq2imkFcpZ4Mq7fnixufGYq3Qm/ZwMMsJ9Sxlflciv6qrAY+4zRK1FgbcHYWWSBCsQiB5jan9B/OeVqG9ZR2/bOYGo0nPaeGY5hBUQcVhwXLcx7JZjgxqEemF8hgfyOUZQKh6WNqAoJ38kKUv6LWERoehzXr/6e1EY0yzdjHquTv2ThN9SJuiLTNWXc/wvPCf7ngK+H1+HkhrCatSoUaNGK0ErjrAAKB2WnxR0VxVk5Uoydza+SDmBagDOEindVYK0lBk767SYowq3L3HUpBKhdPesu0L62wRhpc2XoWmS47L5VWVtvawp4jNDl0k87gOSis7AoQ+mqek66akmk56R1BohLIWoIsKKCIwQluVyeYRFzsTz8AIaYXVhEs3YZN7C9lGfBQA2oLD5nAYwRVze2MzcV3PFPD9o7E1hzqgAx1GHSsfFy1W5cC9vMSAsjai0NKJkqm7VmAodFSDQkzaW6RyPS8coOa0vo4N0CmE51j2G8TRdPBbu33PKjsL4hD7SuTkjglKoiYwzTLbkon5KmZfbedRjm4BkLBtlpYhrzNhCUz11THx+NWBtzV1lLNjCmItQZgsQv8fLUENYjRo1atRoJWilEVYvdViijIiKjimOUMvcJyNpKyrJ44xBzt7o0D6MaiJX5KMiI5TEnQZOhjhozT1bI/72fCy5hrkxasCIzHuEQ1uIsAq6rNx8Ob3GKQtAP/UZsrLT4QW0yTrprdYm84iwApJanwwmRoSo6PjE5AhrEq7p1EtbZWNFFmC9N3DhBebB9pYQ1jywoJ2jew/lrO/QkV4rjNMsQGNt3cbRuayHnysLNZVkL5bc6IjOMxTt0/oYF84oolKXOizFSSchs4DEAtBUkFXmftCl/WetSyw8RZP4mm8KYVHZOczIwjOMjw6STG4ivbAi9DMap/AgtZztzCS/hcn1WoywCLiRlRyt597HgLwsPUlRM69xolJX1Ma2JCFR1oF11BTet6jDKs+TJI1QAcE7NzZBU2oIq1GjRo0arQStNMIa/LDC34kOy6fH2GJNcfnsxIiiA+NwLq1H34kRriBzWgyFMwWERcgKyfM5MKdAXKy/YKdC0mtQPZR875J+o97s6utksu9Qsgzb17mtZcIsTRXXHY5PpwE9BdS0NumxTsiqU+fsUF9T9alxGbIiRGUzNjUl5y1m4WUj0hrKjX54sbVQ3wz1TdvxOe3/xZZwNujD2NnYxulAeoU5KTaGIvNf6eK4a4vTaoDjES48R1aRW+Zn1/S7hYDE2vpvWb+5iXWMpPgaZeVJ54lKSMtluqt0/HpnMSHdYnj25pyQltY5EuKKyImRlkozw9ads4iqojUgjW1ot00OC/9Kk6/x2joWr77ISrCOsMxCfVQpKe6Y43h6bZwvuW0A4OcNYTVq1KhRo/2MVhthreUIKwn5o7l7FfpHWjKxrJ2QVJdyx6WwMFo0rV2b2BeEUJSInMAJ34IcnUOtcLgYpG3sDKMwRlQacTEXFn5T8sP6pnRYBaufUC5MH6G58KlL/KsAYDoly7/UEnBtEtETIattHR2j+gwAsG6VlaDpMRX6rKFJ4xw6c+Ww/PeMrQSHkhDcZphkrCdzHT9nI8QNi9ZugYOnOUTPt34I6QSgDzCZ/PBYtyVCCg0XGO5TDv21wB+rSAsQVsIVa/1uIUoFvU8tZNa0gKhkOe16dCbVUxIiJqS8jJWnRlgla88ZWXgGHzoap825QsiEiOee9V1O9Vf01UoxgJM6LBVmS0c3oTVkemEdSGs8i3ChPzaFTsjaFupaYtKVpCaqzBCXz/TU1cSr7Mfnc4hkPfx8XNKRXL70lY0aNWrUqNG3kVYbYU0Bsxb+ZhQV/ybUlcUz0zHqOpelqci97VMLoq142ct4Zo654cBlETdCyIqtBQMvwbosJGiLjyG3Dkx0WCKO4fAjVZZII0fNkSmOEFKHpfta+1iJ9CDMdU+J6w76qWmqjyJLwPVuzkiKENa6jeeAiHzWWYcVERZx7sSxdwt0WL23jKzIcpC48o2ArGakO7NBh+Um2OhTS8WuHybiREVsiBx9B6Ms1eYUHYPSmSikBWfi3FBjy7ErK6nYh5PqZRWKTqxila6qJo2QaEojqlokEu03t2Z7RlITpcMineNUjduoDkuNm7T2JLS8GRCU1j3S8bjmO0ZDZNjnWL81XOs5biRJPwzikBFKpm/KcNzMyTow1IW/kgpHWddTAnF89fpVOrLML0v6Yam1XUodQ7+t6bCquk7rs8hBMB7YAsJa7Q1rAhgysBBhfpwW/U0qH00OD9NzHqWYV2k8HIw1+aal8w6xZM6R4t7FhURRvymPEuWhcfRhokkgNrA+3ajyDYzEB3GT8otEgsiJ32qBSBBCBCAVqwCYKaDJa1WfT6Y9h1fSG5U2rNg+CZvUZMYb0vawcW1nUWAQDdqhTpuU3LCo1MYWWkTYUxZhb9HTB8+Tg/AkeR5tXFTf269lZvT04d0XNi7eMIVxQRdEgpvZxkUfxFB2oW29ieMuGJRw8XBcO66XqOYQL4yOsrxUC3KQddZVHbszNwR2RxiOT4zjcad+pGu1scxyIsHQX53euCxvUJNwjMaJNqrOKpHu3GNDfQfmM9pRwnNVvDRvctEfiwRFUAAASUCAaM6uyjtEtJ+eTxx6hSFVUleiQjcpBFtY4BpkZK4zkQndNJFgo0aNGjXa32ilEZaf5gFU3dTz3xFZRTEUkDumShFGNKnNuWBAMKDLOC2qeu8sh4YhJNWH5zLSorxLBcTF6Q+0gYY2iZdK+Io5LJvAVt+iLkpIlKh0vhKKRxtWyOC1hKy2aRFg4LB3TDaH811EVRFZDec0sloP5TZDIsF5QSSYouca9d5gFiYYoa4ZiY+CvHlbqO8L9anpcZsb5NRTl4qYGHkpUaE1PjKlQkwI5CbWFD7IWhPnBhlZKEsAnQtq3KydON9QF6gqpvlIxeVjBhUTJfJjka12Q7DqvJ2zyI8QakTGPqkTlUS7PbsjKIRMBhSuywxn9vY0PmQc45PSICKDDeo2mkOz1Dk8xgqwuZOxchg2FNZJBLym9EJZkOwR95SqWTtfEM4XXCWckpDkZu4acRWkKhXXoChClsiKXBUAM1k+IVZDWI0aNWrUaCVopRGWmwJYCzv/VJS0w6s0FdoxVaaoIKUwydyZK1YIi7muEWxCit6S86JOAMgOjRQGxhMXG873pMOwuYFGDXE5wWo5xXaxYh5JPaGq7FvJqGUonoqJswxcC6Qm62xMMUkNJ0rIaig3+e8dNlyTIatZcnzQYQ336ZSxhUXOmUtysMypE4e+GUp6zj4fkdVQTlnncls/IC0OExUshDTnbo1n9EV6FeJEKW0Jzcd5R/PCwoWwUK5P0UTNcX04ZpL7M7FVtpdVGOuq+t2x1C4Zsqo4dpMbAhvP2FlEZ0r3mCHlEaMZ0l0x0lK6yH1uymG2Nhj5DuVeE5GvLvWxjVn6CZ0rdOOMrzoZR8OMcE/6sQV6HRSgmiYoPksv5QxpZbqriJC+qQDHI8k4AYFQrS8m4+yn4+uw8AqNGjVq1KjRdzatOMLybCUY9VaOzdUp5I92TC3J3InzIyRFsnUdDqaEsIjTc4qbKyEs5vQo4V/g8iaUIFAkAgRi+B7XuajnUgnnWIdBiEsG1l1kMTaGsLiuZNU6bFUhFI9lZKX6mpyBux7bpwEdKedfQljaEnCH3cSOoLsihEXIaqcdtArEhRMCmpo51kgHEtjSNaUD0eNH1MNEhBVYS9JpEdKaumg+T+U0XENzROtgrEIIE+uwL3D12hpVpi0BwKlLSukxvLJAzXRYJSo4xMu6tS6zmNXSiJKJunbsXlNIKlp3zrgPgAEZ15CVtvLU1p2SpKXnUE8R1rqZY8OSlWB4H5fef6qsPK3xwlIxXTi63+KJiONLCSHDzYa20uFeuKbwGg/3H0FYmqpWglo3LZzDswS2IwGOl0nGOdSjtIUlByJcWR++A8tQQ1iNGjVq1GglaKURlp94QCArADATH4OpcnqK8ZA/UuauuSqZpgL45nRYc9dx8E2SwzMHr3QVGUfdd8yp6IRz7ISsEZcMtusF6pJU4r4rvjm1gMDW+mIiPiANXAukzsDsX9Wl5S5CWDZFWgPC2uC/AWCbSXVZrMMK5VpBhxU59LIeh6hHTC+yyQgrRVqE1tYCd77PzDENFoMdI6xUJ9IpK8W9va/6GMm0JUCcFzPrMQ9zg67VKTUYVIsxrumwYrLJFOF1xvO64WC0ClERepKBiGmcaey0Q7cupS6yhqzWwjguY+VJumKHVJfFOiwzxdRrdEzjRrqs/P5j675ExnjhZDyUMiEkgNwx35roS6l0WGw1SEhomeZoZFXwqyyGUQLqFoBJsAVCWOVvgEzIWUrG2XfNSrBRo0aNGu1ntPIIiy1ThN5KIyvi7qcFLh8YUJW2XlomLEzNF0uHhekLCIsTAXpCVoGTJq97SsFe4Kg1N0y6LeLKyGrM26i7ikiLOo/YrREWTSEtHfFA+uUsQlY6esX6JIZZ2ql1VgE97ZqkaGqH3cSOoKvapnRXGlkRqtpm5gLpkHVgKkfX1Ivx64OeYVvgxjcDd8zWgcylh9L1jAC0zoqIrdzIpwo+49zptzo6BoVw6ozHjCxJ2eI09d1zCj2PqSvZkou5YckVk04nRVo6aSatnW3dPAuZtd2mfnM1/7mp6bMxXMt0VzR+ubWnUzx4zcpz6nseQ0be+r59eryErsZCtA0UP7GEI2I4p9BWCrtFF1ofLX45SWsYH5KeqHU8HukiXce5H5YX/lcFXRXKFoBjkU5kKRG6tr42xmM+IQy6mBrCatSoUaNGK0ErjbAw8UJ3FS0Cl0VW68KCSVszxfQUKTe5TPI/bS3ICMs4TghIaQrmPuX6tc6COGoDIQsO3Na8T7lix7qsWI/6Le2js1j4nVuOpQirE1ZAbF2pYsiVkBUw6Ku2KSvAks4qLTcYUe3QyCrTYYVxhMMac+IDkdtalVuj/gQwC91ESGtKOsgwXmQ9yFy/9cyhd0pfyNeESBglYlTWp3ovtiLsSY9pYZVFKUVH8Z6sHlOdlmyOTcFXlnaeuWTjM8tZDmjLaUDyFC/RGnC5iCSxvsmIKuqWgg6S1iJSncdopIuAYiKyCkGLfZ/psBjBueX9goh0HNGU9GeWFEZO/I+44HrD6IgRldBLAwJRkQSF/0PByjdcmvlRiuOVpJyl1DHAoK/SUhXtl6d1nhOB1mVSzq5bHmGt9obVeQ631Akz6mh2SwuqvFHRAlvr+syRUeZTAkqmySNGF9qcHbRJOUx8/BsAb2B0v80+DQtDHyhrPH+gZnoDoY8Ym7vHDYvEQ2Yrps5EmSIeoa6Uq0Ixv8xGReVWNipgEP/pjSqKBEkESOMVzKSNBwXt78IL8Joshv4FeiH6mYW/e96gUsZlRpuhFyV9gW6H/EIzQlk9PHfurQiim4oGed5lwZjz95Vhh2Rdfmx0fipaEzUn4O3dZib6W97Re54YzNAxoGQ0kxvP9Cy/pvrQJ1M2lhnuuek7WBIJKuYtM8YpkFNzhw2tCgZX3qcbrHwS/RqIxhjegOWH2gS9mutMNrmyYY0GAKiIAGum6qVwdtqBnMR/ksHRm5iFx6wZXTRq1KhRo/2NVhphmYkTgWwJYfXM5bPZeiHnDpByiDpEjA68qRHWWC4lHXiTuLwODpPw9yahF5easxPXvKnNz8WzNdKi4zMK40RKeGMEKhrKWq4uSTVRIIsDNBfeuXqeo1qwU9tXU4OQ6Tpz4aJchKyoXA/vsGYMpoGVpLQOU+Zsx8nBYUp968sK/32lDiQ2cAHS6llkbKGbpJ2Y+dYCiUcUHgx1QpvYdUKN9RhlDvIiBcoau3qk66eWg2zdzreMrGJ9k0V+GmFxaCZq2wgS4r4N5Vq45yatYzeNY0hrbQH73ntbN6gKC4zSmKQIKz3GzrkKPjkxYfgUW2qE32hbqTEwqB2H+bh6XxuN12AXIysqx0JzyTr188S6YuqdbtIchxs1atSo0X5GK42wSg6rE+swpR1fKYsZUWWcYQ8ZfJPuA4wE3hxzHDaCc4YIvImO0Ra/A8nlKxy1pHkBdQE5A9WzwtYwgxZ1tLcfYclwKkA0fZ52/UgG2XJoHsmF676PhhObqj4THPk4stpGaMpYRlRRhxX0hhUdFpGDZ663A3H3Wm9CZS6HZ7NlusJE5DucJ4MYyxx0b1N0PkZWzQf6DZlAe4UG5DVaB6uTSrLjsnFJckVgHFlRuU2h42WQFdXZURhaypH2/TLO+z3rlpQJvAU6H/8OFw2/UeOzHixUZr7LpCbrlK4kzG9XQFzsJhGaq9cikZcNoezEKmBuzFlE9ZF5UgkAoBGWsT5JAQKMIysgDRi+KIu0DMKQuwt5ztK8DK3khkUWbm7vBlywSqOIv/1kzp7TZN9PViiW81/NktKYHiZ0LsJC6kPHurBYnLIkWi7ShdqwnOOJTiK/uSPjCxOOO752KLv4Wxf9uQARd1BFfqeNsneGj90RGxZNdG9poZPVYB/z24S+p/6cdekYdHbG9UkQBdAxSx/G8OEzVJp4T3o2TfK5KjdD22fhJSYGLBLURhdb2bBIJEhWnWSMQSLBjdCf+7zhv28L0S82wnhQfW+wTtvrKHJ4h32hSzfCGG+E6bjpqKR2xPlA405zJcasVNaBW9iwqH9pDnjjYMK4UJ/TuIDHqU/qsHNeRzYcc5buEUo6HjYlF+7Rm543phnSj9s3tWFRXqxwfp93bAFK47OvMj48tv0MGz2t01CGCOuz0AWzkFOLMkXP+x79PLxb36Vl8L/iaPvkP9lHMaIPx7IN6o7esGjceXGEdRY2pRjpgq5zYpPr+RiQfwM4oobJ1681HrNbB2ZlKctlv8xV32F0+eWXY/fu3d/uZjRq1KhRozuILrvsMtztbncbvWYlNyznHC644ALc7373w2WXXYYDDzzw292k7wras2cPdu/e3fr8W0itz7/11Pr8W0vee9x88804+uijOQ9gjVZSJGitxTHHHAMAOPDAA9uk+hZT6/NvPbU+/9ZT6/NvHR100EFLXdesBBs1atSo0UpQ27AaNWrUqNFK0MpuWOvr63jNa16D9fX1b3dTvmuo9fm3nlqff+up9fl3Lq2k0UWjRo0aNfruo5VFWI0aNWrU6LuL2obVqFGjRo1WgtqG1ahRo0aNVoLahtWoUaNGjVaC2obVqFGjRo1WgtqG1ahRo0aNVoLahtWoUaNGjVaC2obVqFGjRo1Wgv4f+iilNTKtCR0AAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using a square next step proposal" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:55.307Z", + "iopub.status.busy": "2022-08-20T06:27:55.303Z", + "iopub.status.idle": "2022-08-20T06:27:56.162Z", + "shell.execute_reply": "2022-08-20T06:27:56.165Z" + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "context_map = hills_context_map(size=200)\n", + "walker = Walker(\n", + " context_map=context_map, \n", + " next_step_proposal=square_next_step_proposal,\n", + " next_step_proposal_arguments={'width': 20}\n", + ")\n", + "\n", + "# Sample a next step 1000 times\n", + "i, j = 100, 50\n", + "trajectory = []\n", + "for _ in range(1000):\n", + " i, j = walker.sample_next_step(i, j)\n", + " trajectory.append((i, j))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-08-20T06:27:56.177Z", + "iopub.status.busy": "2022-08-20T06:27:56.172Z", + "iopub.status.idle": "2022-08-20T06:27:56.321Z", + "shell.execute_reply": "2022-08-20T06:27:56.344Z" + }, + "pycharm": { + "name": "#%%\n" + }, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_trajectory(trajectory, walker.context_map)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "nteract": { + "version": "0.28.0" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/context_maps.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/context_maps.py new file mode 100644 index 0000000..773867d --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/context_maps.py @@ -0,0 +1,37 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + +def flat_context_map(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/next_step_proposals.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/next_step_proposals.py new file mode 100644 index 0000000..840d224 --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/next_step_proposals.py @@ -0,0 +1,25 @@ +""" Functions to compute next step proposal maps. """ + +import numpy as np + + +def gaussian_next_step_proposal(current_i, current_j, size, sigma_i, sigma_j): + """ Gaussian next step proposal. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + +def square_next_step_proposal(current_i, current_j, size, width): + """ Square next step proposal. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + inside_mask = (np.abs(grid_ii - current_i) <= width // 2) & (np.abs(grid_jj - current_j) <= width // 2) + p_next_step = inside_mask / inside_mask.sum() + return p_next_step + diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/plotting.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/walker.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/walker.py new file mode 100644 index 0000000..affc6ae --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/solution/walker.py @@ -0,0 +1,59 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, context_map, next_step_proposal, next_step_proposal_arguments): + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + self.next_step_proposal = next_step_proposal + self.next_step_proposal_arguments = next_step_proposal_arguments + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self.next_step_proposal( + current_i, current_j, self.size, **self.next_step_proposal_arguments) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_4_break_out_the_next_step_probability/walker.py b/notebooks/walker/Step_4_break_out_the_next_step_probability/walker.py new file mode 100644 index 0000000..39c9afd --- /dev/null +++ b/notebooks/walker/Step_4_break_out_the_next_step_probability/walker.py @@ -0,0 +1,60 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, context_map): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:self.size, 0:self.size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_5_reproducibility/Step_5_reproducibility.ipynb b/notebooks/walker/Step_5_reproducibility/Step_5_reproducibility.ipynb new file mode 100644 index 0000000..98da886 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/Step_5_reproducibility.ipynb @@ -0,0 +1,204 @@ +{ + "cells": [ + { + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "from plotting import plot_trajectory\n", + "from walker import Walker" + ], + "outputs": [], + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "collapsed": false, + "pycharm": { + "name": "#%%\n" + }, + "execution": { + "iopub.status.busy": "2023-06-28T17:23:15.993Z", + "iopub.execute_input": "2023-06-28T17:23:16.002Z", + "shell.execute_reply": "2023-06-28T17:23:16.081Z", + "iopub.status.idle": "2023-06-28T17:23:16.018Z" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "For this Exercise let's go back to the version of the walker with only one \"next step proposal\". " + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "markdown", + "source": [ + "# 1. Complete the run.py script\n", + "- In the file, at the top we give the desired parameters for the run\n", + "- create a context map and walker (see previous exercises for reference)\n", + "- simulate a trajectory (see previous exercises for reference)\n", + "- save the trajectory using `np.save()` and some metadata" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "markdown", + "source": [ + "# 2. Run the run.py script twice and compare that the outcome is identical by plotting the result below" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "trajectory = np.load(\"sim_20230628-192022.npy\") # change the name of the file here!" + ], + "outputs": [], + "execution_count": 5, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2023-06-28T17:23:19.216Z", + "iopub.execute_input": "2023-06-28T17:23:19.227Z", + "iopub.status.idle": "2023-06-28T17:23:19.236Z", + "shell.execute_reply": "2023-06-28T17:23:19.239Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "plt.plot(trajectory[:,0], trajectory[:,1])" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 6, + "data": { + "text/plain": "[]" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 6, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2023-06-28T17:23:21.468Z", + "iopub.execute_input": "2023-06-28T17:23:21.471Z", + "iopub.status.idle": "2023-06-28T17:23:21.552Z", + "shell.execute_reply": "2023-06-28T17:23:21.558Z" + } + } + }, + { + "cell_type": "code", + "source": [], + "outputs": [], + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + } + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python [default]", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.10.3", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + }, + "nteract": { + "version": "0.28.0" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git a/notebooks/walker/Step_5_reproducibility/context_maps.py b/notebooks/walker/Step_5_reproducibility/context_maps.py new file mode 100644 index 0000000..1aafc63 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/context_maps.py @@ -0,0 +1,39 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + + +def flat_context_map_builder(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map_builder(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map_builder(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map + diff --git a/notebooks/walker/Step_5_reproducibility/exercise b/notebooks/walker/Step_5_reproducibility/exercise new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/exercise @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_5_reproducibility/plotting.py b/notebooks/walker/Step_5_reproducibility/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_5_reproducibility/run.py b/notebooks/walker/Step_5_reproducibility/run.py new file mode 100644 index 0000000..32b57b4 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/run.py @@ -0,0 +1,42 @@ +import json +import time + +import git +import numpy as np + +import context_maps +from walker import Walker + +# Use the following parameters to simulate and save a trajectory of the walker + +seed = 42 +sigma_i = 3 +sigma_j = 4 +size = 200 +i, j = (50, 100) +n_iterations = 1000 +# USE map_type hills +random_state = np.random.RandomState(seed) + +# STEP 1: Create a context map + + +# STEP 2: Create a Walker + + +# STEP 3: Simulate the walk + + +# STEP 4: Save the trajectory +curr_time = time.strftime("%Y%m%d-%H%M%S") +# save the npy file here! + +# STEP 5: Save the metadata +# lookup git repository +repo = git.Repo(search_parent_directories=True) +sha = repo.head.object.hexsha + +with open('meta.txt', 'w') as f: + f.write(f'I estimated parameters at {curr_time}.\n') + f.write(f'The git repo was at commit {sha}') + # you can add any other information you want here! diff --git a/notebooks/walker/Step_5_reproducibility/solution/Step_5_reproducibility.ipynb b/notebooks/walker/Step_5_reproducibility/solution/Step_5_reproducibility.ipynb new file mode 100644 index 0000000..98da886 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/solution/Step_5_reproducibility.ipynb @@ -0,0 +1,204 @@ +{ + "cells": [ + { + "cell_type": "code", + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "from plotting import plot_trajectory\n", + "from walker import Walker" + ], + "outputs": [], + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2022-08-18T09:50:40.616906Z", + "start_time": "2022-08-18T11:50:40.181358+02:00" + }, + "collapsed": false, + "pycharm": { + "name": "#%%\n" + }, + "execution": { + "iopub.status.busy": "2023-06-28T17:23:15.993Z", + "iopub.execute_input": "2023-06-28T17:23:16.002Z", + "shell.execute_reply": "2023-06-28T17:23:16.081Z", + "iopub.status.idle": "2023-06-28T17:23:16.018Z" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "For this Exercise let's go back to the version of the walker with only one \"next step proposal\". " + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "markdown", + "source": [ + "# 1. Complete the run.py script\n", + "- In the file, at the top we give the desired parameters for the run\n", + "- create a context map and walker (see previous exercises for reference)\n", + "- simulate a trajectory (see previous exercises for reference)\n", + "- save the trajectory using `np.save()` and some metadata" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "markdown", + "source": [ + "# 2. Run the run.py script twice and compare that the outcome is identical by plotting the result below" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "trajectory = np.load(\"sim_20230628-192022.npy\") # change the name of the file here!" + ], + "outputs": [], + "execution_count": 5, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2023-06-28T17:23:19.216Z", + "iopub.execute_input": "2023-06-28T17:23:19.227Z", + "iopub.status.idle": "2023-06-28T17:23:19.236Z", + "shell.execute_reply": "2023-06-28T17:23:19.239Z" + } + } + }, + { + "cell_type": "code", + "source": [ + "plt.plot(trajectory[:,0], trajectory[:,1])" + ], + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 6, + "data": { + "text/plain": "[]" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "execution_count": 6, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + }, + "execution": { + "iopub.status.busy": "2023-06-28T17:23:21.468Z", + "iopub.execute_input": "2023-06-28T17:23:21.471Z", + "iopub.status.idle": "2023-06-28T17:23:21.552Z", + "shell.execute_reply": "2023-06-28T17:23:21.558Z" + } + } + }, + { + "cell_type": "code", + "source": [], + "outputs": [], + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + } + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python [default]", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.10.3", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + }, + "toc": { + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false + }, + "nteract": { + "version": "0.28.0" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git a/notebooks/walker/Step_5_reproducibility/solution/context_maps.py b/notebooks/walker/Step_5_reproducibility/solution/context_maps.py new file mode 100644 index 0000000..f24b3bd --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/solution/context_maps.py @@ -0,0 +1,40 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + + +def flat_context_map_builder(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map_builder(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map_builder(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map + + diff --git a/notebooks/walker/Step_5_reproducibility/solution/meta.txt b/notebooks/walker/Step_5_reproducibility/solution/meta.txt new file mode 100644 index 0000000..dab942c --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/solution/meta.txt @@ -0,0 +1,2 @@ +I estimated parameters at 20230628-192022. +The git repo was at commit 6a26566a46593a650ebfc86ebdbb28ee78ace079 \ No newline at end of file diff --git a/notebooks/walker/Step_5_reproducibility/solution/plotting.py b/notebooks/walker/Step_5_reproducibility/solution/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/solution/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_5_reproducibility/solution/run.py b/notebooks/walker/Step_5_reproducibility/solution/run.py new file mode 100644 index 0000000..8416b9a --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/solution/run.py @@ -0,0 +1,46 @@ +import json +import time + +import git +import numpy as np + +import context_maps +from walker import Walker + +# Use the following parameters to simulate and save a trajectory of the walker + +seed = 42 +sigma_i = 3 +sigma_j = 4 +size = 200 +i, j = (50, 100) +n_iterations = 1000 +# USE map_type hills +random_state = np.random.RandomState(seed) + +# STEP 1: Create a context map +context_map = context_maps.hills_context_map_builder(size) + +# STEP 2: Create a Walker +walker = Walker(sigma_i, sigma_j, context_map) + +# STEP 3: Simulate the walk + +trajectory = [] +for _ in range(n_iterations): + i, j = walker.sample_next_step(i, j, random_state) + trajectory.append((i, j)) + +# STEP 4: Save the trajectory +curr_time = time.strftime("%Y%m%d-%H%M%S") +np.save(f"sim_{curr_time}", trajectory) + + +# STEP 5: Save the metadata +# lookup git repository +repo = git.Repo(search_parent_directories=True) +sha = repo.head.object.hexsha + +with open('meta.txt', 'w') as f: + f.write(f'I estimated parameters at {curr_time}.\n') + f.write(f'The git repo was at commit {sha}') diff --git a/notebooks/walker/Step_5_reproducibility/solution/sim_20230628-192022.npy b/notebooks/walker/Step_5_reproducibility/solution/sim_20230628-192022.npy new file mode 100644 index 0000000..14a24e8 Binary files /dev/null and b/notebooks/walker/Step_5_reproducibility/solution/sim_20230628-192022.npy differ diff --git a/notebooks/walker/Step_5_reproducibility/solution/walker.py b/notebooks/walker/Step_5_reproducibility/solution/walker.py new file mode 100644 index 0000000..39c9afd --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/solution/walker.py @@ -0,0 +1,60 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, context_map): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:self.size, 0:self.size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_5_reproducibility/walker.py b/notebooks/walker/Step_5_reproducibility/walker.py new file mode 100644 index 0000000..39c9afd --- /dev/null +++ b/notebooks/walker/Step_5_reproducibility/walker.py @@ -0,0 +1,60 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, context_map): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:self.size, 0:self.size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/context_maps.py b/notebooks/walker/Step_6_loading_parameters_from_file/context_maps.py new file mode 100644 index 0000000..1aafc63 --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/context_maps.py @@ -0,0 +1,39 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + + +def flat_context_map_builder(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map_builder(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map_builder(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map + diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/plotting.py b/notebooks/walker/Step_6_loading_parameters_from_file/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/run.py b/notebooks/walker/Step_6_loading_parameters_from_file/run.py new file mode 100644 index 0000000..8416b9a --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/run.py @@ -0,0 +1,46 @@ +import json +import time + +import git +import numpy as np + +import context_maps +from walker import Walker + +# Use the following parameters to simulate and save a trajectory of the walker + +seed = 42 +sigma_i = 3 +sigma_j = 4 +size = 200 +i, j = (50, 100) +n_iterations = 1000 +# USE map_type hills +random_state = np.random.RandomState(seed) + +# STEP 1: Create a context map +context_map = context_maps.hills_context_map_builder(size) + +# STEP 2: Create a Walker +walker = Walker(sigma_i, sigma_j, context_map) + +# STEP 3: Simulate the walk + +trajectory = [] +for _ in range(n_iterations): + i, j = walker.sample_next_step(i, j, random_state) + trajectory.append((i, j)) + +# STEP 4: Save the trajectory +curr_time = time.strftime("%Y%m%d-%H%M%S") +np.save(f"sim_{curr_time}", trajectory) + + +# STEP 5: Save the metadata +# lookup git repository +repo = git.Repo(search_parent_directories=True) +sha = repo.head.object.hexsha + +with open('meta.txt', 'w') as f: + f.write(f'I estimated parameters at {curr_time}.\n') + f.write(f'The git repo was at commit {sha}') diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/solution/context_maps.py b/notebooks/walker/Step_6_loading_parameters_from_file/solution/context_maps.py new file mode 100644 index 0000000..1ac8fbe --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/solution/context_maps.py @@ -0,0 +1,46 @@ +""" CONTEXT MAP BUILDERS """ +import numpy as np + + + +def flat_context_map_builder(size): + """ A context map where all positions are equally likely. """ + return np.ones((size, size)) + + +def hills_context_map_builder(size): + """ A context map with bumps and valleys. """ + grid_ii, grid_jj = np.mgrid[0:size, 0:size] + i_waves = np.sin(grid_ii / 130) + np.sin(grid_ii / 10) + i_waves /= i_waves.max() + j_waves = np.sin(grid_jj / 100) + np.sin(grid_jj / 50) + \ + np.sin(grid_jj / 10) + j_waves /= j_waves.max() + context_map = j_waves + i_waves + return context_map + + +def labyrinth_context_map_builder(size): + """ A context map that looks like a labyrinth. """ + context_map = np.ones((size, size)) + context_map[50:100, 50:60] = 0 + context_map[20:89, 80:90] = 0 + context_map[90:120, 0:10] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + context_map[50:60, 50:200] = 0 + context_map[179:189, 80:130] = 0 + context_map[110:120, 0:190] = 0 + context_map[120:size, 30:40] = 0 + context_map[180:190, 50:60] = 0 + + return context_map + + +# Register map builders +map_builders = { + "flat": flat_context_map_builder, + "hills": hills_context_map_builder, + "labyrinth": labyrinth_context_map_builder, +} diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/solution/inputs.json b/notebooks/walker/Step_6_loading_parameters_from_file/solution/inputs.json new file mode 100644 index 0000000..f737f3d --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/solution/inputs.json @@ -0,0 +1,10 @@ +{ + "seed": 42, + "sigma_i": 3, + "sigma_j": 4, + "size": 200, + "map_type": "hills", + "start_i": 50, + "start_j": 100, + "n_iterations": 1000 +} \ No newline at end of file diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/solution/plotting.py b/notebooks/walker/Step_6_loading_parameters_from_file/solution/plotting.py new file mode 100644 index 0000000..b07ea67 --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/solution/plotting.py @@ -0,0 +1,22 @@ +import matplotlib.pyplot as plt +import numpy as np + + +def plot_trajectory(trajectory, context_map): + """ Plot a trajectory over a context map. """ + trajectory = np.asarray(trajectory) + plt.matshow(context_map) + plt.plot(trajectory[:, 1], trajectory[:, 0], color='r') + plt.show() + + +def plot_trajectory_hexbin(trajectory): + """ Plot an hexagonal density map of a trajectory. """ + trajectory = np.asarray(trajectory) + with plt.rc_context({'figure.figsize': (4, 4), 'axes.labelsize': 16, + 'xtick.labelsize': 14, 'ytick.labelsize': 14}): + plt.hexbin(trajectory[:, 1], trajectory[:, 0], gridsize=30, + extent=(0, 200, 0, 200), edgecolors='none', cmap='Reds') + plt.gca().invert_yaxis() + plt.xlabel('X') + plt.ylabel('Y') diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/solution/run.py b/notebooks/walker/Step_6_loading_parameters_from_file/solution/run.py new file mode 100644 index 0000000..ffa0949 --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/solution/run.py @@ -0,0 +1,42 @@ +import json +import time + +import git +import numpy as np + +from walker import Walker +from context_maps import map_builders + + +with open("inputs.json", 'r') as f: + inputs = json.load(f) + +random_state = np.random.RandomState(inputs["seed"]) +n_iterations = inputs["n_iterations"] + + + +context_map_builder = map_builders[inputs["map_type"]] +context_map = context_map_builder(inputs["size"]) +walker = Walker(inputs["sigma_i"], inputs["sigma_j"], context_map) + + +trajectory = [] +for _ in range(n_iterations): + i, j = walker.sample_next_step(inputs["start_i"], inputs["start_j"], + random_state) + trajectory.append((i, j)) + +# STEP 4: Save the trajectory +curr_time = time.strftime("%Y%m%d-%H%M%S") +np.save(f"sim_{curr_time}", trajectory) + + +# STEP 5: Save the metadata +# lookup git repository +repo = git.Repo(search_parent_directories=True) +sha = repo.head.object.hexsha + +with open('meta.txt', 'w') as f: + f.write(f'I estimated parameters at {curr_time}.\n') + f.write(f'The git repo was at commit {sha}') diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/solution/show b/notebooks/walker/Step_6_loading_parameters_from_file/solution/show new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/solution/show @@ -0,0 +1 @@ + diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/solution/walker.py b/notebooks/walker/Step_6_loading_parameters_from_file/solution/walker.py new file mode 100644 index 0000000..39c9afd --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/solution/walker.py @@ -0,0 +1,60 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, context_map): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:self.size, 0:self.size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/notebooks/walker/Step_6_loading_parameters_from_file/walker.py b/notebooks/walker/Step_6_loading_parameters_from_file/walker.py new file mode 100644 index 0000000..39c9afd --- /dev/null +++ b/notebooks/walker/Step_6_loading_parameters_from_file/walker.py @@ -0,0 +1,60 @@ +import numpy as np + + +class Walker: + """ The Walker knows how to walk at random on a context map. """ + + def __init__(self, sigma_i, sigma_j, context_map): + self.sigma_i = sigma_i + self.sigma_j = sigma_j + self.size = context_map.shape[0] + # Make sure that the context map is normalized + context_map /= context_map.sum() + self.context_map = context_map + + # Pre-compute a 2D grid of coordinates for efficiency + self._grid_ii, self._grid_jj = np.mgrid[0:self.size, 0:self.size] + + # --- Walker public interface + + def sample_next_step(self, current_i, current_j, random_state=np.random): + """ Sample a new position for the walker. """ + + # Combine the next-step proposal with the context map to get a + # next-step probability map + next_step_map = self._next_step_proposal(current_i, current_j) + selection_map = self._compute_next_step_probability(next_step_map) + + # Draw a new position from the next-step probability map + r = random_state.rand() + cumulative_map = np.cumsum(selection_map) + cumulative_map = cumulative_map.reshape(selection_map.shape) + i_next, j_next = np.argwhere(cumulative_map >= r)[0] + + return i_next, j_next + + # --- Walker non-public interface + + def _next_step_proposal(self, current_i, current_j): + """ Create the 2D proposal map for the next step of the walker. """ + + # 2D Gaussian distribution , centered at current position, + # and with different standard deviations for i and j + grid_ii, grid_jj = self._grid_ii, self._grid_jj + sigma_i, sigma_j = self.sigma_i, self.sigma_j + + rad = ( + (((grid_ii - current_i) ** 2) / (sigma_i ** 2)) + + (((grid_jj - current_j) ** 2) / (sigma_j ** 2)) + ) + + p_next_step = np.exp(-(rad / 2.0)) / (2.0 * np.pi * sigma_i * sigma_j) + return p_next_step / p_next_step.sum() + + def _compute_next_step_probability(self, next_step_map): + """ Compute the next step probability map from next step proposal and + context map. """ + next_step_probability = next_step_map * self.context_map + next_step_probability /= next_step_probability.sum() + return next_step_probability + diff --git a/scientific_programming_patterns.pdf b/scientific_programming_patterns.pdf new file mode 100644 index 0000000..3195aa6 Binary files /dev/null and b/scientific_programming_patterns.pdf differ diff --git a/scientific_programming_patterns.pptx b/scientific_programming_patterns.pptx new file mode 100644 index 0000000..c5b1091 Binary files /dev/null and b/scientific_programming_patterns.pptx differ