209 lines
10 KiB
Text
209 lines
10 KiB
Text
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# NumPy and Matplotlib examples"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First import NumPy and Matplotlib:"
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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": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"Welcome to pylab, a matplotlib-based Python environment [backend: module://ipykernel.pylab.backend_inline].\n",
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"For more information, type 'help(pylab)'.\n"
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]
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}
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],
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"source": [
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"%pylab inline"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now we show some very basic examples of how they can be used."
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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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"a = np.random.uniform(size=(100,100))"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(100, 100)"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a.shape"
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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": 8,
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"metadata": {
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"tags": [
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"remove_cell"
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]
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},
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"outputs": [],
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"source": [
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"evs = np.linalg.eigvals(a)"
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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": 10,
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"metadata": {
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"tags": [
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"remove_output"
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]
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(100,)"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"evs.shape"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Here is a cell that has both text and PNG output:"
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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": 14,
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"metadata": {
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"tags": [
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"remove_input"
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]
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(array([95, 4, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
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" array([ -2.93566063, 2.35937011, 7.65440086, 12.9494316 ,\n",
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" 18.24446235, 23.53949309, 28.83452384, 34.12955458,\n",
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" 39.42458533, 44.71961607, 50.01464682]),\n",
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" <a list of 10 Patch objects>)"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": 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1zjvvaMuWLerr6/PM/JK0efNmlZWVpS+M8NLslmUpGo3q0KFDisfjkrw1/7p162Tbtrq6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\n",
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"text/plain": [
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"<matplotlib.figure.Figure at 0x108c8f1d0>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"hist(evs.real)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"remove_cell"
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]
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},
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"source": [
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"This cell is just markdown testing whether an ASCIIDoc quirk is caught and whether [header links are rendered](#numpy-and-matplotlib-examples) even if they [don't resolve correctly now](#NumPy-and-Matplotlib-examples).\n",
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"\n",
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"one *test* two *tests*. three *tests*"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Make sure markdown parser doesn't crash with empty Latex formulas blocks\n",
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"$$ $$\n",
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"\\[\\]\n",
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"$$"
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]
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}
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],
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"metadata": {
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"celltoolbar": "Tags",
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"kernelspec": {
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"display_name": "Python 3",
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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": "3.6.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
|