Exercise 3

class_materials/walker/Step_3_break_out_the_context_map_initialization/.ipynb_checkpoints/Step_3_break_out_the_context_map_initialization-checkpoint.ipynb

@@ -0,0 +1,204 @@
+{
+ "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": true,
+     "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. Propose modifications to the code that calls the walker (above) 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": [
+    "%matplotlib inline\n",
+    "\n",
+    "from plotting import plot_trajectory, plot_trajectory_hexbin\n",
+    "from walker import Walker\n",
+    "from context_map import create_context_map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "context_map = create_context_map(size=200, map_type='hills')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a Walker instance\n",
+    "walker = Walker(sigma_i=3, sigma_j=4, context_map)\n",
+    "\n",
+    "# Sample a next step 1000 times\n",
+    "initial_position = (100, 50)\n",
+    "N_steps = 1000\n",
+    "trajectory = np.array((N_steps, 2), dtype=np.int8)\n",
+    "\n",
+    "for step in range(N_steps):\n",
+    "    i,j = walker.sample_next_step(i, j)\n",
+    "    trajectory[step] = np.array([i,j], dtype = np.int8)\n",
+    "\n",
+    "plot_trajectory(trajectory, context_map)"
+   ]
+  },
+  {
+   "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\n",
+    "\n",
+    "When you have a working implementation: PR! You can link the issue in the commit message (by writing \"issue #3\")."
+   ]
+  },
+  {
+   "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": "3.13.6"
+  },
+  "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": 4
+}

class_materials/walker/Step_3_break_out_the_context_map_initialization/.ipynb_checkpoints/plotting-checkpoint.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')

class_materials/walker/Step_3_break_out_the_context_map_initialization/Step_3_break_out_the_context_map_initialization.ipynb

@@ -47,7 +47,7 @@
    "metadata": {
     "collapsed": true,
     "jupyter": {
-     "outputs_hidden": false,
+     "outputs_hidden": true,
      "source_hidden": false
     },
     "nteract": {
@@ -95,14 +95,43 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "%matplotlib inline\n",
+    "\n",
+    "from plotting import plot_trajectory, plot_trajectory_hexbin\n",
+    "from walker import Walker\n",
+    "from context_map import create_context_map"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "context_map = create_context_map(size=200, map_type='hills')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a Walker instance\n",
+    "walker = Walker(sigma_i=3, sigma_j=4, context_map)\n",
+    "\n",
+    "# Sample a next step 1000 times\n",
+    "initial_position = (100, 50)\n",
+    "N_steps = 1000\n",
+    "trajectory = np.array((N_steps, 2), dtype=np.int8)\n",
+    "\n",
+    "for step in range(N_steps):\n",
+    "    i,j = walker.sample_next_step(i, j)\n",
+    "    trajectory[step] = np.array([i,j], dtype = np.int8)\n",
+    "\n",
+    "plot_trajectory(trajectory, context_map)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -151,7 +180,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.13.6"
   },
   "nteract": {
    "version": "0.28.0"
@@ -171,5 +200,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }