ASPP 2024 material
This commit is contained in:
Pietro Berkes
commit
1f6bc07c51
90 changed files with 91689 additions and 0 deletions
194
exercises/numpy_view_or_copy/view_or_copy.ipynb
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194
exercises/numpy_view_or_copy/view_or_copy.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "774cc021",
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"metadata": {},
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"source": [
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"# Is it a view or a copy?\n",
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"\n",
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"- For every operations on the array `x`, decide whether it returns a view of `x`, or a copy\n",
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"- If it's a view, derive the new values for the metadata (ndim, shape, strides)\n",
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"- You can verify your answers with the function `print_info` defined below"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4ccf18f3",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"\n",
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"\n",
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"def is_view(a, x):\n",
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" \"\"\" Is `a` a view of `x`? \"\"\"\n",
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" return a.base is x\n",
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"\n",
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"\n",
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"def print_info(a, x):\n",
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" txt = f\"\"\"\n",
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"Is it a view? {is_view(a, x)}\n",
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"\n",
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"dtype\\t{a.dtype}\n",
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"ndim\\t{a.ndim}\n",
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"shape\\t{a.shape}\n",
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"strides\\t{a.strides}\n",
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" \"\"\"\n",
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" print(a)\n",
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" print(txt)\n",
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"\n",
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"\n",
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"x = np.arange(12).reshape(3, 4).copy()\n",
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"print_info(x, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b68308e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x[::2, :]\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "85feedb0",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x[1, :]\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dbbb9a7f",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"y = x[1]\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4957469c",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x[[1, 2, 0], [1, 1, 2]]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aa8effeb",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Get the first and third row\n",
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"y = x[[0, 2], :]\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d1649515",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x.reshape((6, 2))\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "15b0d7ad",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x.ravel()\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "38cc1ef3",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x.T.ravel()\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b7d0cc63",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Get all the odd elements\n",
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"y = x[(x % 2) == 1]\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4474f8cf",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x + 2\n",
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"#print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "866e842a",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = np.sort(x, axis=1)\n",
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"#print_info(y ,x)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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194
exercises/numpy_view_or_copy/view_or_copy_solution.ipynb
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194
exercises/numpy_view_or_copy/view_or_copy_solution.ipynb
Normal file
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@ -0,0 +1,194 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "774cc021",
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"metadata": {},
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"source": [
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"# Is it a view or a copy?\n",
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"\n",
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"- For every operations on the array `x`, decide whether it returns a view of `x`, or a copy\n",
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"- If it's a view, derive the new values for the metadata (ndim, shape, strides)\n",
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"- You can verify your answers with the function `print_info` defined below"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4ccf18f3",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"\n",
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"\n",
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"def is_view(a, x):\n",
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" \"\"\" Is `a` a view of `x`? \"\"\"\n",
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" return a.base is x\n",
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"\n",
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"\n",
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"def print_info(a, x):\n",
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" txt = f\"\"\"\n",
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"Is it a view? {is_view(a, x)}\n",
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"\n",
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"dtype\\t{a.dtype}\n",
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"ndim\\t{a.ndim}\n",
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"shape\\t{a.shape}\n",
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"strides\\t{a.strides}\n",
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" \"\"\"\n",
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" print(a)\n",
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" print(txt)\n",
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"\n",
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"\n",
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"x = np.arange(12).reshape(3, 4).copy()\n",
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"print_info(x, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b68308e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x[::2, :]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "85feedb0",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x[1, :]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dbbb9a7f",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"y = x[1]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4957469c",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x[[1, 2, 0], [1, 1, 2]]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aa8effeb",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Get the first and third row\n",
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"y = x[[0, 2], :]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d1649515",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x.reshape((6, 2))\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "15b0d7ad",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x.ravel()\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "38cc1ef3",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x.T.ravel()\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b7d0cc63",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Get all the odd elements\n",
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"y = x[(x % 2) == 1]\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4474f8cf",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = x + 2\n",
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"print_info(y, x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "866e842a",
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"metadata": {},
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"outputs": [],
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"source": [
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"y = np.sort(x, axis=1)\n",
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"print_info(y ,x)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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