5352 lines
689 KiB
Plaintext
5352 lines
689 KiB
Plaintext
{
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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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"# Demo Jupyter\n",
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"\n",
|
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"## Sous titre\n",
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"\n",
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"- une\n",
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"- liste\n",
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"- comme ça\n",
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"\n",
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"Les liens, [Ma page](https://mdk.fr)\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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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
|
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" and should_run_async(code)\n",
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"Executing <Handle IOLoop.add_future.<locals>.<lambda>(<Future finis...queues.py:248>) at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/ioloop.py:688 created at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/concurrent.py:184> took 0.751 seconds\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import pandas as pd\n"
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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 des données"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
|
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" and should_run_async(code)\n"
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]
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}
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],
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"source": [
|
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"%matplotlib notebook\n",
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"# %matplotlib 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": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"a = np.array(range(10))"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"a = np.zeros((4, 5))"
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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": 9,
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||
"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result"
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"a"
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"outputs": [],
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||
"source": [
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"a[0, 0] = 5"
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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 + 5"
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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": 11,
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"metadata": {},
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"outputs": [
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"data": {
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"a * 2.5"
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"2"
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"output_type": "execute_result"
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"source": [
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"1 + 1"
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"cell_type": "code",
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"execution_count": 28,
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"outputs": [
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{
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" 15.5, 16. , 16.5, 17. , 17.5, 18. , 18.5, 19. , 19.5])"
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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": [
|
||
"np.arange(10, 20, .5)"
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||
]
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||
},
|
||
{
|
||
"cell_type": "code",
|
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"execution_count": 12,
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" 16.32653061, 18.36734694, 20.40816327, 22.44897959,\n",
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" 32.65306122, 34.69387755, 36.73469388, 38.7755102 ,\n",
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"source": [
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"np.linspace(0, 100, 50)"
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{
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"cell_type": "code",
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"execution_count": 30,
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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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"np.zeros((3, 3))"
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{
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"cell_type": "code",
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"execution_count": 31,
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"np.zeros((3, 5))"
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],
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"source": [
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"np.zeros((2, 3, 4, 5))"
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{
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"execution_count": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"b = np.random.rand(4, 4)"
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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": 58,
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{
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]
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"execution_count": 58,
|
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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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"np.random.rand(4, 4)"
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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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{
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"metadata": {},
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"b"
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{
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"cell_type": "code",
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"execution_count": 15,
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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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"array([[ True, False, True, True],\n",
|
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" [False, False, True, False],\n",
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" [ True, False, True, True],\n",
|
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" [ True, False, False, False]])"
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|
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},
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"execution_count": 15,
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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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"b > 0.5"
|
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|
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},
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{
|
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"cell_type": "code",
|
||
"execution_count": 17,
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||
"metadata": {},
|
||
"outputs": [],
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"source": [
|
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"mask = b > .5"
|
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]
|
||
},
|
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{
|
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"cell_type": "code",
|
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"execution_count": 21,
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"metadata": {},
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"outputs": [
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"data": {
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"execution_count": 21,
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"metadata": {},
|
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"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"b[b < .5].mean()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 63,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
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"data": {
|
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"text/plain": [
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"array([0.32798554, 0.12009786, 0.15686044, 0.1508741 , 0.19020511,\n",
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" 0.42079271, 0.4914277 ])"
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]
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},
|
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"execution_count": 63,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
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}
|
||
],
|
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"source": [
|
||
"b[~mask]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
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"text/plain": [
|
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"array([0.50888646])"
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]
|
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},
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"b[(b > .5) & (b < .7)]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Executing <Handle IOLoop.add_future.<locals>.<lambda>(<Future finis...queues.py:248>) at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/ioloop.py:688 created at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/concurrent.py:184> took 0.190 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"iris = pd.read_excel('https://mdk.fr/iris.xls', index_col=0)\n",
|
||
"\n",
|
||
"# python -m pip install xlrd # Doit marcher\n",
|
||
"# py -m pip install xlrd # Doit marcher aussi !"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"pandas.core.frame.DataFrame"
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"type(iris)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" vertical-align: middle;\n",
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||
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|
||
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|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>sepal length (cm)</th>\n",
|
||
" <th>sepal width (cm)</th>\n",
|
||
" <th>petal length (cm)</th>\n",
|
||
" <th>petal width (cm)</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td>5.843333</td>\n",
|
||
" <td>3.054000</td>\n",
|
||
" <td>3.758667</td>\n",
|
||
" <td>1.198667</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td>0.828066</td>\n",
|
||
" <td>0.433594</td>\n",
|
||
" <td>1.764420</td>\n",
|
||
" <td>0.763161</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td>4.300000</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>0.100000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td>5.100000</td>\n",
|
||
" <td>2.800000</td>\n",
|
||
" <td>1.600000</td>\n",
|
||
" <td>0.300000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td>5.800000</td>\n",
|
||
" <td>3.000000</td>\n",
|
||
" <td>4.350000</td>\n",
|
||
" <td>1.300000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td>6.400000</td>\n",
|
||
" <td>3.300000</td>\n",
|
||
" <td>5.100000</td>\n",
|
||
" <td>1.800000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td>7.900000</td>\n",
|
||
" <td>4.400000</td>\n",
|
||
" <td>6.900000</td>\n",
|
||
" <td>2.500000</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" sepal length (cm) sepal width (cm) petal length (cm) \\\n",
|
||
"count 150.000000 150.000000 150.000000 \n",
|
||
"mean 5.843333 3.054000 3.758667 \n",
|
||
"std 0.828066 0.433594 1.764420 \n",
|
||
"min 4.300000 2.000000 1.000000 \n",
|
||
"25% 5.100000 2.800000 1.600000 \n",
|
||
"50% 5.800000 3.000000 4.350000 \n",
|
||
"75% 6.400000 3.300000 5.100000 \n",
|
||
"max 7.900000 4.400000 6.900000 \n",
|
||
"\n",
|
||
" petal width (cm) \n",
|
||
"count 150.000000 \n",
|
||
"mean 1.198667 \n",
|
||
"std 0.763161 \n",
|
||
"min 0.100000 \n",
|
||
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|
||
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|
||
"75% 1.800000 \n",
|
||
"max 2.500000 "
|
||
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|
||
},
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"source": [
|
||
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|
||
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|
||
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|
||
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|
||
"cell_type": "code",
|
||
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|
||
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|
||
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|
||
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|
||
"data": {
|
||
"text/plain": [
|
||
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|
||
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|
||
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|
||
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|
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|
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|
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|
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|
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"name": "stderr",
|
||
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|
||
"text": [
|
||
"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
|
||
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|
||
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|
||
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|
||
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|
||
"data": {
|
||
"text/plain": [
|
||
"sepal length (cm) 4.6\n",
|
||
"sepal width (cm) 3.1\n",
|
||
"petal length (cm) 1.5\n",
|
||
"petal width (cm) 0.2\n",
|
||
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|
||
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|
||
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|
||
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|
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|
||
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|
||
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|
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|
||
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|
||
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|
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|
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|
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|
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|
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|
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|
||
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|
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|
||
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|
||
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|
||
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|
||
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|
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|
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|
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|
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|
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|
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|
||
"data": {
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|
||
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|
||
"1 4.9\n",
|
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|
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|
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|
||
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|
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|
||
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|
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|
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|
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|
||
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|
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|
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|
||
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|
||
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||
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|
||
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|
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|
||
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|
||
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|
||
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|
||
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|
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|
||
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|
||
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|
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|
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|
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|
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|
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|
||
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|
||
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|
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|
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|
||
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|
||
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|
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
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|
||
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||
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|
||
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|
||
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|
||
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|
||
{
|
||
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|
||
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|
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"0 5.1\n",
|
||
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|
||
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|
||
"3 4.6\n",
|
||
"4 5.0\n",
|
||
" ... \n",
|
||
"145 6.7\n",
|
||
"146 6.3\n",
|
||
"147 6.5\n",
|
||
"148 6.2\n",
|
||
"149 5.9\n",
|
||
"Name: sepal length (cm), Length: 150, dtype: float64"
|
||
]
|
||
},
|
||
"execution_count": 86,
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
{
|
||
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|
||
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|
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" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>sepal length (cm)</th>\n",
|
||
" <th>petal length (cm)</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>5.1</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>4.9</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>4.7</td>\n",
|
||
" <td>1.3</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>4.6</td>\n",
|
||
" <td>1.5</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>5.0</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>145</th>\n",
|
||
" <td>6.7</td>\n",
|
||
" <td>5.2</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>146</th>\n",
|
||
" <td>6.3</td>\n",
|
||
" <td>5.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>147</th>\n",
|
||
" <td>6.5</td>\n",
|
||
" <td>5.2</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>148</th>\n",
|
||
" <td>6.2</td>\n",
|
||
" <td>5.4</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>149</th>\n",
|
||
" <td>5.9</td>\n",
|
||
" <td>5.1</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>150 rows × 2 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" sepal length (cm) petal length (cm)\n",
|
||
"0 5.1 1.4\n",
|
||
"1 4.9 1.4\n",
|
||
"2 4.7 1.3\n",
|
||
"3 4.6 1.5\n",
|
||
"4 5.0 1.4\n",
|
||
".. ... ...\n",
|
||
"145 6.7 5.2\n",
|
||
"146 6.3 5.0\n",
|
||
"147 6.5 5.2\n",
|
||
"148 6.2 5.4\n",
|
||
"149 5.9 5.1\n",
|
||
"\n",
|
||
"[150 rows x 2 columns]"
|
||
]
|
||
},
|
||
"execution_count": 96,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"iris.loc[:, lengths]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
|
||
" and should_run_async(code)\n",
|
||
"Executing <Handle IOLoop.add_future.<locals>.<lambda>(<Future finis...queues.py:248>) at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/ioloop.py:688 created at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/concurrent.py:184> took 0.128 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"pd.read_csv"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"pd.read_excel # Shift tab, Shift tab, Shift tab, Shift tab"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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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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||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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|
||
" return fig.toolbar_button_onmouseover(tooltip);\n",
|
||
" }\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.buttons = {};\n",
|
||
" var buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'mpl-button-group';\n",
|
||
" for (var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" /* Instead of a spacer, we start a new button group. */\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
" buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'mpl-button-group';\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var button = (fig.buttons[name] = document.createElement('button'));\n",
|
||
" button.classList = 'mpl-widget';\n",
|
||
" button.setAttribute('role', 'button');\n",
|
||
" button.setAttribute('aria-disabled', 'false');\n",
|
||
" button.addEventListener('click', on_click_closure(method_name));\n",
|
||
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
|
||
"\n",
|
||
" var icon_img = document.createElement('img');\n",
|
||
" icon_img.src = '_images/' + image + '.png';\n",
|
||
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
|
||
" icon_img.alt = tooltip;\n",
|
||
" button.appendChild(icon_img);\n",
|
||
"\n",
|
||
" buttonGroup.appendChild(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fmt_picker = document.createElement('select');\n",
|
||
" fmt_picker.classList = 'mpl-widget';\n",
|
||
" toolbar.appendChild(fmt_picker);\n",
|
||
" this.format_dropdown = fmt_picker;\n",
|
||
"\n",
|
||
" for (var ind in mpl.extensions) {\n",
|
||
" var fmt = mpl.extensions[ind];\n",
|
||
" var option = document.createElement('option');\n",
|
||
" option.selected = fmt === mpl.default_extension;\n",
|
||
" option.innerHTML = fmt;\n",
|
||
" fmt_picker.appendChild(option);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var status_bar = document.createElement('span');\n",
|
||
" status_bar.classList = 'mpl-message';\n",
|
||
" toolbar.appendChild(status_bar);\n",
|
||
" this.message = status_bar;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
|
||
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
|
||
" // which will in turn request a refresh of the image.\n",
|
||
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_message = function (type, properties) {\n",
|
||
" properties['type'] = type;\n",
|
||
" properties['figure_id'] = this.id;\n",
|
||
" this.ws.send(JSON.stringify(properties));\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_draw_message = function () {\n",
|
||
" if (!this.waiting) {\n",
|
||
" this.waiting = true;\n",
|
||
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
|
||
" var format_dropdown = fig.format_dropdown;\n",
|
||
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
|
||
" fig.ondownload(fig, format);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
|
||
" var size = msg['size'];\n",
|
||
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
|
||
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
|
||
" fig.send_message('refresh', {});\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
|
||
" var x0 = msg['x0'] / fig.ratio;\n",
|
||
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
|
||
" var x1 = msg['x1'] / fig.ratio;\n",
|
||
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
|
||
" x0 = Math.floor(x0) + 0.5;\n",
|
||
" y0 = Math.floor(y0) + 0.5;\n",
|
||
" x1 = Math.floor(x1) + 0.5;\n",
|
||
" y1 = Math.floor(y1) + 0.5;\n",
|
||
" var min_x = Math.min(x0, x1);\n",
|
||
" var min_y = Math.min(y0, y1);\n",
|
||
" var width = Math.abs(x1 - x0);\n",
|
||
" var height = Math.abs(y1 - y0);\n",
|
||
"\n",
|
||
" fig.rubberband_context.clearRect(\n",
|
||
" 0,\n",
|
||
" 0,\n",
|
||
" fig.canvas.width / fig.ratio,\n",
|
||
" fig.canvas.height / fig.ratio\n",
|
||
" );\n",
|
||
"\n",
|
||
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
|
||
" // Updates the figure title.\n",
|
||
" fig.header.textContent = msg['label'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
|
||
" var cursor = msg['cursor'];\n",
|
||
" switch (cursor) {\n",
|
||
" case 0:\n",
|
||
" cursor = 'pointer';\n",
|
||
" break;\n",
|
||
" case 1:\n",
|
||
" cursor = 'default';\n",
|
||
" break;\n",
|
||
" case 2:\n",
|
||
" cursor = 'crosshair';\n",
|
||
" break;\n",
|
||
" case 3:\n",
|
||
" cursor = 'move';\n",
|
||
" break;\n",
|
||
" }\n",
|
||
" fig.rubberband_canvas.style.cursor = cursor;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
|
||
" fig.message.textContent = msg['message'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
|
||
" // Request the server to send over a new figure.\n",
|
||
" fig.send_draw_message();\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
|
||
" fig.image_mode = msg['mode'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
|
||
" for (var key in msg) {\n",
|
||
" if (!(key in fig.buttons)) {\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
" fig.buttons[key].disabled = !msg[key];\n",
|
||
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
|
||
" if (msg['mode'] === 'PAN') {\n",
|
||
" fig.buttons['Pan'].classList.add('active');\n",
|
||
" fig.buttons['Zoom'].classList.remove('active');\n",
|
||
" } else if (msg['mode'] === 'ZOOM') {\n",
|
||
" fig.buttons['Pan'].classList.remove('active');\n",
|
||
" fig.buttons['Zoom'].classList.add('active');\n",
|
||
" } else {\n",
|
||
" fig.buttons['Pan'].classList.remove('active');\n",
|
||
" fig.buttons['Zoom'].classList.remove('active');\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function () {\n",
|
||
" // Called whenever the canvas gets updated.\n",
|
||
" this.send_message('ack', {});\n",
|
||
"};\n",
|
||
"\n",
|
||
"// A function to construct a web socket function for onmessage handling.\n",
|
||
"// Called in the figure constructor.\n",
|
||
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
|
||
" return function socket_on_message(evt) {\n",
|
||
" if (evt.data instanceof Blob) {\n",
|
||
" var img = evt.data;\n",
|
||
" if (img.type !== 'image/png') {\n",
|
||
" /* FIXME: We get \"Resource interpreted as Image but\n",
|
||
" * transferred with MIME type text/plain:\" errors on\n",
|
||
" * Chrome. But how to set the MIME type? It doesn't seem\n",
|
||
" * to be part of the websocket stream */\n",
|
||
" img.type = 'image/png';\n",
|
||
" }\n",
|
||
"\n",
|
||
" /* Free the memory for the previous frames */\n",
|
||
" if (fig.imageObj.src) {\n",
|
||
" (window.URL || window.webkitURL).revokeObjectURL(\n",
|
||
" fig.imageObj.src\n",
|
||
" );\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
|
||
" img\n",
|
||
" );\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" } else if (\n",
|
||
" typeof evt.data === 'string' &&\n",
|
||
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
|
||
" ) {\n",
|
||
" fig.imageObj.src = evt.data;\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var msg = JSON.parse(evt.data);\n",
|
||
" var msg_type = msg['type'];\n",
|
||
"\n",
|
||
" // Call the \"handle_{type}\" callback, which takes\n",
|
||
" // the figure and JSON message as its only arguments.\n",
|
||
" try {\n",
|
||
" var callback = fig['handle_' + msg_type];\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\n",
|
||
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
|
||
" msg\n",
|
||
" );\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (callback) {\n",
|
||
" try {\n",
|
||
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
|
||
" callback(fig, msg);\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\n",
|
||
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
|
||
" e,\n",
|
||
" e.stack,\n",
|
||
" msg\n",
|
||
" );\n",
|
||
" }\n",
|
||
" }\n",
|
||
" };\n",
|
||
"};\n",
|
||
"\n",
|
||
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
|
||
"mpl.findpos = function (e) {\n",
|
||
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
|
||
" var targ;\n",
|
||
" if (!e) {\n",
|
||
" e = window.event;\n",
|
||
" }\n",
|
||
" if (e.target) {\n",
|
||
" targ = e.target;\n",
|
||
" } else if (e.srcElement) {\n",
|
||
" targ = e.srcElement;\n",
|
||
" }\n",
|
||
" if (targ.nodeType === 3) {\n",
|
||
" // defeat Safari bug\n",
|
||
" targ = targ.parentNode;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // pageX,Y are the mouse positions relative to the document\n",
|
||
" var boundingRect = targ.getBoundingClientRect();\n",
|
||
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
|
||
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
|
||
"\n",
|
||
" return { x: x, y: y };\n",
|
||
"};\n",
|
||
"\n",
|
||
"/*\n",
|
||
" * return a copy of an object with only non-object keys\n",
|
||
" * we need this to avoid circular references\n",
|
||
" * http://stackoverflow.com/a/24161582/3208463\n",
|
||
" */\n",
|
||
"function simpleKeys(original) {\n",
|
||
" return Object.keys(original).reduce(function (obj, key) {\n",
|
||
" if (typeof original[key] !== 'object') {\n",
|
||
" obj[key] = original[key];\n",
|
||
" }\n",
|
||
" return obj;\n",
|
||
" }, {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
|
||
" var canvas_pos = mpl.findpos(event);\n",
|
||
"\n",
|
||
" if (name === 'button_press') {\n",
|
||
" this.canvas.focus();\n",
|
||
" this.canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" var x = canvas_pos.x * this.ratio;\n",
|
||
" var y = canvas_pos.y * this.ratio;\n",
|
||
"\n",
|
||
" this.send_message(name, {\n",
|
||
" x: x,\n",
|
||
" y: y,\n",
|
||
" button: event.button,\n",
|
||
" step: event.step,\n",
|
||
" guiEvent: simpleKeys(event),\n",
|
||
" });\n",
|
||
"\n",
|
||
" /* This prevents the web browser from automatically changing to\n",
|
||
" * the text insertion cursor when the button is pressed. We want\n",
|
||
" * to control all of the cursor setting manually through the\n",
|
||
" * 'cursor' event from matplotlib */\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
|
||
" // Handle any extra behaviour associated with a key event\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.key_event = function (event, name) {\n",
|
||
" // Prevent repeat events\n",
|
||
" if (name === 'key_press') {\n",
|
||
" if (event.key === this._key) {\n",
|
||
" return;\n",
|
||
" } else {\n",
|
||
" this._key = event.key;\n",
|
||
" }\n",
|
||
" }\n",
|
||
" if (name === 'key_release') {\n",
|
||
" this._key = null;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var value = '';\n",
|
||
" if (event.ctrlKey && event.key !== 'Control') {\n",
|
||
" value += 'ctrl+';\n",
|
||
" }\n",
|
||
" else if (event.altKey && event.key !== 'Alt') {\n",
|
||
" value += 'alt+';\n",
|
||
" }\n",
|
||
" else if (event.shiftKey && event.key !== 'Shift') {\n",
|
||
" value += 'shift+';\n",
|
||
" }\n",
|
||
"\n",
|
||
" value += 'k' + event.key;\n",
|
||
"\n",
|
||
" this._key_event_extra(event, name);\n",
|
||
"\n",
|
||
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
|
||
" return false;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
|
||
" if (name === 'download') {\n",
|
||
" this.handle_save(this, null);\n",
|
||
" } else {\n",
|
||
" this.send_message('toolbar_button', { name: name });\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
|
||
" this.message.textContent = tooltip;\n",
|
||
"};\n",
|
||
"\n",
|
||
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
|
||
"// prettier-ignore\n",
|
||
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
|
||
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
|
||
"\n",
|
||
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
|
||
"\n",
|
||
"mpl.default_extension = \"png\";/* global mpl */\n",
|
||
"\n",
|
||
"var comm_websocket_adapter = function (comm) {\n",
|
||
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
|
||
" // object with the appropriate methods. Currently this is a non binary\n",
|
||
" // socket, so there is still some room for performance tuning.\n",
|
||
" var ws = {};\n",
|
||
"\n",
|
||
" ws.binaryType = comm.kernel.ws.binaryType;\n",
|
||
" ws.readyState = comm.kernel.ws.readyState;\n",
|
||
" function updateReadyState(_event) {\n",
|
||
" if (comm.kernel.ws) {\n",
|
||
" ws.readyState = comm.kernel.ws.readyState;\n",
|
||
" } else {\n",
|
||
" ws.readyState = 3; // Closed state.\n",
|
||
" }\n",
|
||
" }\n",
|
||
" comm.kernel.ws.addEventListener('open', updateReadyState);\n",
|
||
" comm.kernel.ws.addEventListener('close', updateReadyState);\n",
|
||
" comm.kernel.ws.addEventListener('error', updateReadyState);\n",
|
||
"\n",
|
||
" ws.close = function () {\n",
|
||
" comm.close();\n",
|
||
" };\n",
|
||
" ws.send = function (m) {\n",
|
||
" //console.log('sending', m);\n",
|
||
" comm.send(m);\n",
|
||
" };\n",
|
||
" // Register the callback with on_msg.\n",
|
||
" comm.on_msg(function (msg) {\n",
|
||
" //console.log('receiving', msg['content']['data'], msg);\n",
|
||
" var data = msg['content']['data'];\n",
|
||
" if (data['blob'] !== undefined) {\n",
|
||
" data = {\n",
|
||
" data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
|
||
" };\n",
|
||
" }\n",
|
||
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
|
||
" ws.onmessage(data);\n",
|
||
" });\n",
|
||
" return ws;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.mpl_figure_comm = function (comm, msg) {\n",
|
||
" // This is the function which gets called when the mpl process\n",
|
||
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
|
||
"\n",
|
||
" var id = msg.content.data.id;\n",
|
||
" // Get hold of the div created by the display call when the Comm\n",
|
||
" // socket was opened in Python.\n",
|
||
" var element = document.getElementById(id);\n",
|
||
" var ws_proxy = comm_websocket_adapter(comm);\n",
|
||
"\n",
|
||
" function ondownload(figure, _format) {\n",
|
||
" window.open(figure.canvas.toDataURL());\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
|
||
"\n",
|
||
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
|
||
" // web socket which is closed, not our websocket->open comm proxy.\n",
|
||
" ws_proxy.onopen();\n",
|
||
"\n",
|
||
" fig.parent_element = element;\n",
|
||
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
|
||
" if (!fig.cell_info) {\n",
|
||
" console.error('Failed to find cell for figure', id, fig);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" fig.cell_info[0].output_area.element.on(\n",
|
||
" 'cleared',\n",
|
||
" { fig: fig },\n",
|
||
" fig._remove_fig_handler\n",
|
||
" );\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_close = function (fig, msg) {\n",
|
||
" var width = fig.canvas.width / fig.ratio;\n",
|
||
" fig.cell_info[0].output_area.element.off(\n",
|
||
" 'cleared',\n",
|
||
" fig._remove_fig_handler\n",
|
||
" );\n",
|
||
" fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
|
||
"\n",
|
||
" // Update the output cell to use the data from the current canvas.\n",
|
||
" fig.push_to_output();\n",
|
||
" var dataURL = fig.canvas.toDataURL();\n",
|
||
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
|
||
" // the notebook keyboard shortcuts fail.\n",
|
||
" IPython.keyboard_manager.enable();\n",
|
||
" fig.parent_element.innerHTML =\n",
|
||
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
" fig.close_ws(fig, msg);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
|
||
" fig.send_message('closing', msg);\n",
|
||
" // fig.ws.close()\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
|
||
" // Turn the data on the canvas into data in the output cell.\n",
|
||
" var width = this.canvas.width / this.ratio;\n",
|
||
" var dataURL = this.canvas.toDataURL();\n",
|
||
" this.cell_info[1]['text/html'] =\n",
|
||
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function () {\n",
|
||
" // Tell IPython that the notebook contents must change.\n",
|
||
" IPython.notebook.set_dirty(true);\n",
|
||
" this.send_message('ack', {});\n",
|
||
" var fig = this;\n",
|
||
" // Wait a second, then push the new image to the DOM so\n",
|
||
" // that it is saved nicely (might be nice to debounce this).\n",
|
||
" setTimeout(function () {\n",
|
||
" fig.push_to_output();\n",
|
||
" }, 1000);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var toolbar = document.createElement('div');\n",
|
||
" toolbar.classList = 'btn-toolbar';\n",
|
||
" this.root.appendChild(toolbar);\n",
|
||
"\n",
|
||
" function on_click_closure(name) {\n",
|
||
" return function (_event) {\n",
|
||
" return fig.toolbar_button_onclick(name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" function on_mouseover_closure(tooltip) {\n",
|
||
" return function (event) {\n",
|
||
" if (!event.currentTarget.disabled) {\n",
|
||
" return fig.toolbar_button_onmouseover(tooltip);\n",
|
||
" }\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.buttons = {};\n",
|
||
" var buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'btn-group';\n",
|
||
" var button;\n",
|
||
" for (var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" /* Instead of a spacer, we start a new button group. */\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
" buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'btn-group';\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
"\n",
|
||
" button = fig.buttons[name] = document.createElement('button');\n",
|
||
" button.classList = 'btn btn-default';\n",
|
||
" button.href = '#';\n",
|
||
" button.title = name;\n",
|
||
" button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
|
||
" button.addEventListener('click', on_click_closure(method_name));\n",
|
||
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
|
||
" buttonGroup.appendChild(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add the status bar.\n",
|
||
" var status_bar = document.createElement('span');\n",
|
||
" status_bar.classList = 'mpl-message pull-right';\n",
|
||
" toolbar.appendChild(status_bar);\n",
|
||
" this.message = status_bar;\n",
|
||
"\n",
|
||
" // Add the close button to the window.\n",
|
||
" var buttongrp = document.createElement('div');\n",
|
||
" buttongrp.classList = 'btn-group inline pull-right';\n",
|
||
" button = document.createElement('button');\n",
|
||
" button.classList = 'btn btn-mini btn-primary';\n",
|
||
" button.href = '#';\n",
|
||
" button.title = 'Stop Interaction';\n",
|
||
" button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
|
||
" button.addEventListener('click', function (_evt) {\n",
|
||
" fig.handle_close(fig, {});\n",
|
||
" });\n",
|
||
" button.addEventListener(\n",
|
||
" 'mouseover',\n",
|
||
" on_mouseover_closure('Stop Interaction')\n",
|
||
" );\n",
|
||
" buttongrp.appendChild(button);\n",
|
||
" var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
|
||
" titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._remove_fig_handler = function (event) {\n",
|
||
" var fig = event.data.fig;\n",
|
||
" if (event.target !== this) {\n",
|
||
" // Ignore bubbled events from children.\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" fig.close_ws(fig, {});\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function (el) {\n",
|
||
" el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function (el) {\n",
|
||
" // this is important to make the div 'focusable\n",
|
||
" el.setAttribute('tabindex', 0);\n",
|
||
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
|
||
" // off when our div gets focus\n",
|
||
"\n",
|
||
" // location in version 3\n",
|
||
" if (IPython.notebook.keyboard_manager) {\n",
|
||
" IPython.notebook.keyboard_manager.register_events(el);\n",
|
||
" } else {\n",
|
||
" // location in version 2\n",
|
||
" IPython.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
|
||
" var manager = IPython.notebook.keyboard_manager;\n",
|
||
" if (!manager) {\n",
|
||
" manager = IPython.keyboard_manager;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Check for shift+enter\n",
|
||
" if (event.shiftKey && event.which === 13) {\n",
|
||
" this.canvas_div.blur();\n",
|
||
" // select the cell after this one\n",
|
||
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
|
||
" IPython.notebook.select(index + 1);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
|
||
" fig.ondownload(fig, null);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.find_output_cell = function (html_output) {\n",
|
||
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
|
||
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
|
||
" // IPython event is triggered only after the cells have been serialised, which for\n",
|
||
" // our purposes (turning an active figure into a static one), is too late.\n",
|
||
" var cells = IPython.notebook.get_cells();\n",
|
||
" var ncells = cells.length;\n",
|
||
" for (var i = 0; i < ncells; i++) {\n",
|
||
" var cell = cells[i];\n",
|
||
" if (cell.cell_type === 'code') {\n",
|
||
" for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
|
||
" var data = cell.output_area.outputs[j];\n",
|
||
" if (data.data) {\n",
|
||
" // IPython >= 3 moved mimebundle to data attribute of output\n",
|
||
" data = data.data;\n",
|
||
" }\n",
|
||
" if (data['text/html'] === html_output) {\n",
|
||
" return [cell, data, j];\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"// Register the function which deals with the matplotlib target/channel.\n",
|
||
"// The kernel may be null if the page has been refreshed.\n",
|
||
"if (IPython.notebook.kernel !== null) {\n",
|
||
" IPython.notebook.kernel.comm_manager.register_target(\n",
|
||
" 'matplotlib',\n",
|
||
" mpl.mpl_figure_comm\n",
|
||
" );\n",
|
||
"}\n"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.Javascript object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<img 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\" width=\"639.65\">"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Executing <Handle IOLoop._run_callback(functools.par...7f52f77a4190>)) created at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/platform/asyncio.py:227> took 0.410 seconds\n",
|
||
"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/pandas/plotting/_matplotlib/tools.py:400: MatplotlibDeprecationWarning: \n",
|
||
"The is_first_col function was deprecated in Matplotlib 3.4 and will be removed two minor releases later. Use ax.get_subplotspec().is_first_col() instead.\n",
|
||
" if ax.is_first_col():\n",
|
||
"Executing <Handle IOLoop.add_future.<locals>.<lambda>(<Future finis...queues.py:248>) at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/ioloop.py:688 created at /home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/tornado/concurrent.py:184> took 10.611 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from pandas.plotting import scatter_matrix\n",
|
||
"plot = scatter_matrix(iris)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"x = np.linspace(0, 10, 100)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
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|
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|
||
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|
||
},
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"x"
|
||
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|
||
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|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"y = np.sin(x)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
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|
||
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|
||
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|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"y"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
|
||
" and should_run_async(code)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/javascript": [
|
||
"/* Put everything inside the global mpl namespace */\n",
|
||
"/* global mpl */\n",
|
||
"window.mpl = {};\n",
|
||
"\n",
|
||
"mpl.get_websocket_type = function () {\n",
|
||
" if (typeof WebSocket !== 'undefined') {\n",
|
||
" return WebSocket;\n",
|
||
" } else if (typeof MozWebSocket !== 'undefined') {\n",
|
||
" return MozWebSocket;\n",
|
||
" } else {\n",
|
||
" alert(\n",
|
||
" 'Your browser does not have WebSocket support. ' +\n",
|
||
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
|
||
" 'Firefox 4 and 5 are also supported but you ' +\n",
|
||
" 'have to enable WebSockets in about:config.'\n",
|
||
" );\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\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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|
||
" warnings.style.display = 'block';\n",
|
||
" warnings.textContent =\n",
|
||
" 'This browser does not support binary websocket messages. ' +\n",
|
||
" 'Performance may be slow.';\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj = new Image();\n",
|
||
"\n",
|
||
" this.context = undefined;\n",
|
||
" this.message = undefined;\n",
|
||
" this.canvas = undefined;\n",
|
||
" this.rubberband_canvas = undefined;\n",
|
||
" this.rubberband_context = undefined;\n",
|
||
" this.format_dropdown = undefined;\n",
|
||
"\n",
|
||
" this.image_mode = 'full';\n",
|
||
"\n",
|
||
" this.root = document.createElement('div');\n",
|
||
" this.root.setAttribute('style', 'display: inline-block');\n",
|
||
" this._root_extra_style(this.root);\n",
|
||
"\n",
|
||
" parent_element.appendChild(this.root);\n",
|
||
"\n",
|
||
" this._init_header(this);\n",
|
||
" this._init_canvas(this);\n",
|
||
" this._init_toolbar(this);\n",
|
||
"\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" this.waiting = false;\n",
|
||
"\n",
|
||
" this.ws.onopen = function () {\n",
|
||
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|
||
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|
||
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|
||
" fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
|
||
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|
||
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|
||
"\n",
|
||
" this.imageObj.onload = function () {\n",
|
||
" if (fig.image_mode === 'full') {\n",
|
||
" // Full images could contain transparency (where diff images\n",
|
||
" // almost always do), so we need to clear the canvas so that\n",
|
||
" // there is no ghosting.\n",
|
||
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
" }\n",
|
||
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.imageObj.onunload = function () {\n",
|
||
" fig.ws.close();\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.ws.onmessage = this._make_on_message_function(this);\n",
|
||
"\n",
|
||
" this.ondownload = ondownload;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_header = function () {\n",
|
||
" var titlebar = document.createElement('div');\n",
|
||
" titlebar.classList =\n",
|
||
" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
|
||
" var titletext = document.createElement('div');\n",
|
||
" titletext.classList = 'ui-dialog-title';\n",
|
||
" titletext.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'width: 100%; text-align: center; padding: 3px;'\n",
|
||
" );\n",
|
||
" titlebar.appendChild(titletext);\n",
|
||
" this.root.appendChild(titlebar);\n",
|
||
" this.header = titletext;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_canvas = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
|
||
" canvas_div.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'border: 1px solid #ddd;' +\n",
|
||
" 'box-sizing: content-box;' +\n",
|
||
" 'clear: both;' +\n",
|
||
" 'min-height: 1px;' +\n",
|
||
" 'min-width: 1px;' +\n",
|
||
" 'outline: 0;' +\n",
|
||
" 'overflow: hidden;' +\n",
|
||
" 'position: relative;' +\n",
|
||
" 'resize: both;'\n",
|
||
" );\n",
|
||
"\n",
|
||
" function on_keyboard_event_closure(name) {\n",
|
||
" return function (event) {\n",
|
||
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|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" canvas_div.addEventListener(\n",
|
||
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|
||
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|
||
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|
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|
||
" 'keyup',\n",
|
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" on_keyboard_event_closure('key_release')\n",
|
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|
||
"\n",
|
||
" this._canvas_extra_style(canvas_div);\n",
|
||
" this.root.appendChild(canvas_div);\n",
|
||
"\n",
|
||
" var canvas = (this.canvas = document.createElement('canvas'));\n",
|
||
" canvas.classList.add('mpl-canvas');\n",
|
||
" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
|
||
"\n",
|
||
" this.context = canvas.getContext('2d');\n",
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"\n",
|
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|
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|
||
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|
||
" 1;\n",
|
||
"\n",
|
||
" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
|
||
"\n",
|
||
" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
|
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" 'canvas'\n",
|
||
" ));\n",
|
||
" rubberband_canvas.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
|
||
" );\n",
|
||
"\n",
|
||
" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
|
||
" if (this.ResizeObserver === undefined) {\n",
|
||
" if (window.ResizeObserver !== undefined) {\n",
|
||
" this.ResizeObserver = window.ResizeObserver;\n",
|
||
" } else {\n",
|
||
" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
|
||
" this.ResizeObserver = obs.ResizeObserver;\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
|
||
" var nentries = entries.length;\n",
|
||
" for (var i = 0; i < nentries; i++) {\n",
|
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|
||
" var width, height;\n",
|
||
" if (entry.contentBoxSize) {\n",
|
||
" if (entry.contentBoxSize instanceof Array) {\n",
|
||
" // Chrome 84 implements new version of spec.\n",
|
||
" width = entry.contentBoxSize[0].inlineSize;\n",
|
||
" height = entry.contentBoxSize[0].blockSize;\n",
|
||
" } else {\n",
|
||
" // Firefox implements old version of spec.\n",
|
||
" width = entry.contentBoxSize.inlineSize;\n",
|
||
" height = entry.contentBoxSize.blockSize;\n",
|
||
" }\n",
|
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|
||
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|
||
" width = entry.contentRect.width;\n",
|
||
" height = entry.contentRect.height;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Keep the size of the canvas and rubber band canvas in sync with\n",
|
||
" // the canvas container.\n",
|
||
" if (entry.devicePixelContentBoxSize) {\n",
|
||
" // Chrome 84 implements new version of spec.\n",
|
||
" canvas.setAttribute(\n",
|
||
" 'width',\n",
|
||
" entry.devicePixelContentBoxSize[0].inlineSize\n",
|
||
" );\n",
|
||
" canvas.setAttribute(\n",
|
||
" 'height',\n",
|
||
" entry.devicePixelContentBoxSize[0].blockSize\n",
|
||
" );\n",
|
||
" } else {\n",
|
||
" canvas.setAttribute('width', width * fig.ratio);\n",
|
||
" canvas.setAttribute('height', height * fig.ratio);\n",
|
||
" }\n",
|
||
" canvas.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'width: ' + width + 'px; height: ' + height + 'px;'\n",
|
||
" );\n",
|
||
"\n",
|
||
" rubberband_canvas.setAttribute('width', width);\n",
|
||
" rubberband_canvas.setAttribute('height', height);\n",
|
||
"\n",
|
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|
||
" // that occurs as the element is placed into the DOM, which should\n",
|
||
" // otherwise not happen due to the minimum size styling.\n",
|
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" if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
|
||
" fig.request_resize(width, height);\n",
|
||
" }\n",
|
||
" }\n",
|
||
" });\n",
|
||
" this.resizeObserverInstance.observe(canvas_div);\n",
|
||
"\n",
|
||
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|
||
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|
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|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" rubberband_canvas.addEventListener(\n",
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" 'mousedown',\n",
|
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|
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|
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" 'dblclick',\n",
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|
||
"\n",
|
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|
||
" 'mouseenter',\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" );\n",
|
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"\n",
|
||
" canvas_div.addEventListener('wheel', function (event) {\n",
|
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|
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" event.step = 1;\n",
|
||
" } else {\n",
|
||
" event.step = -1;\n",
|
||
" }\n",
|
||
" on_mouse_event_closure('scroll')(event);\n",
|
||
" });\n",
|
||
"\n",
|
||
" canvas_div.appendChild(canvas);\n",
|
||
" canvas_div.appendChild(rubberband_canvas);\n",
|
||
"\n",
|
||
" this.rubberband_context = rubberband_canvas.getContext('2d');\n",
|
||
" this.rubberband_context.strokeStyle = '#000000';\n",
|
||
"\n",
|
||
" this._resize_canvas = function (width, height, forward) {\n",
|
||
" if (forward) {\n",
|
||
" canvas_div.style.width = width + 'px';\n",
|
||
" canvas_div.style.height = height + 'px';\n",
|
||
" }\n",
|
||
" };\n",
|
||
"\n",
|
||
" // Disable right mouse context menu.\n",
|
||
" this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
" });\n",
|
||
"\n",
|
||
" function set_focus() {\n",
|
||
" canvas.focus();\n",
|
||
" canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" window.setTimeout(set_focus, 100);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var toolbar = document.createElement('div');\n",
|
||
" toolbar.classList = 'mpl-toolbar';\n",
|
||
" this.root.appendChild(toolbar);\n",
|
||
"\n",
|
||
" function on_click_closure(name) {\n",
|
||
" return function (_event) {\n",
|
||
" return fig.toolbar_button_onclick(name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" function on_mouseover_closure(tooltip) {\n",
|
||
" return function (event) {\n",
|
||
" if (!event.currentTarget.disabled) {\n",
|
||
" return fig.toolbar_button_onmouseover(tooltip);\n",
|
||
" }\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.buttons = {};\n",
|
||
" var buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'mpl-button-group';\n",
|
||
" for (var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" /* Instead of a spacer, we start a new button group. */\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
" buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'mpl-button-group';\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var button = (fig.buttons[name] = document.createElement('button'));\n",
|
||
" button.classList = 'mpl-widget';\n",
|
||
" button.setAttribute('role', 'button');\n",
|
||
" button.setAttribute('aria-disabled', 'false');\n",
|
||
" button.addEventListener('click', on_click_closure(method_name));\n",
|
||
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
|
||
"\n",
|
||
" var icon_img = document.createElement('img');\n",
|
||
" icon_img.src = '_images/' + image + '.png';\n",
|
||
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
|
||
" icon_img.alt = tooltip;\n",
|
||
" button.appendChild(icon_img);\n",
|
||
"\n",
|
||
" buttonGroup.appendChild(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fmt_picker = document.createElement('select');\n",
|
||
" fmt_picker.classList = 'mpl-widget';\n",
|
||
" toolbar.appendChild(fmt_picker);\n",
|
||
" this.format_dropdown = fmt_picker;\n",
|
||
"\n",
|
||
" for (var ind in mpl.extensions) {\n",
|
||
" var fmt = mpl.extensions[ind];\n",
|
||
" var option = document.createElement('option');\n",
|
||
" option.selected = fmt === mpl.default_extension;\n",
|
||
" option.innerHTML = fmt;\n",
|
||
" fmt_picker.appendChild(option);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var status_bar = document.createElement('span');\n",
|
||
" status_bar.classList = 'mpl-message';\n",
|
||
" toolbar.appendChild(status_bar);\n",
|
||
" this.message = status_bar;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
|
||
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
|
||
" // which will in turn request a refresh of the image.\n",
|
||
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_message = function (type, properties) {\n",
|
||
" properties['type'] = type;\n",
|
||
" properties['figure_id'] = this.id;\n",
|
||
" this.ws.send(JSON.stringify(properties));\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_draw_message = function () {\n",
|
||
" if (!this.waiting) {\n",
|
||
" this.waiting = true;\n",
|
||
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
|
||
" var format_dropdown = fig.format_dropdown;\n",
|
||
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
|
||
" fig.ondownload(fig, format);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
|
||
" var size = msg['size'];\n",
|
||
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
|
||
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
|
||
" fig.send_message('refresh', {});\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
|
||
" var x0 = msg['x0'] / fig.ratio;\n",
|
||
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
|
||
" var x1 = msg['x1'] / fig.ratio;\n",
|
||
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
|
||
" x0 = Math.floor(x0) + 0.5;\n",
|
||
" y0 = Math.floor(y0) + 0.5;\n",
|
||
" x1 = Math.floor(x1) + 0.5;\n",
|
||
" y1 = Math.floor(y1) + 0.5;\n",
|
||
" var min_x = Math.min(x0, x1);\n",
|
||
" var min_y = Math.min(y0, y1);\n",
|
||
" var width = Math.abs(x1 - x0);\n",
|
||
" var height = Math.abs(y1 - y0);\n",
|
||
"\n",
|
||
" fig.rubberband_context.clearRect(\n",
|
||
" 0,\n",
|
||
" 0,\n",
|
||
" fig.canvas.width / fig.ratio,\n",
|
||
" fig.canvas.height / fig.ratio\n",
|
||
" );\n",
|
||
"\n",
|
||
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
|
||
" // Updates the figure title.\n",
|
||
" fig.header.textContent = msg['label'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
|
||
" var cursor = msg['cursor'];\n",
|
||
" switch (cursor) {\n",
|
||
" case 0:\n",
|
||
" cursor = 'pointer';\n",
|
||
" break;\n",
|
||
" case 1:\n",
|
||
" cursor = 'default';\n",
|
||
" break;\n",
|
||
" case 2:\n",
|
||
" cursor = 'crosshair';\n",
|
||
" break;\n",
|
||
" case 3:\n",
|
||
" cursor = 'move';\n",
|
||
" break;\n",
|
||
" }\n",
|
||
" fig.rubberband_canvas.style.cursor = cursor;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
|
||
" fig.message.textContent = msg['message'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
|
||
" // Request the server to send over a new figure.\n",
|
||
" fig.send_draw_message();\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
|
||
" fig.image_mode = msg['mode'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
|
||
" for (var key in msg) {\n",
|
||
" if (!(key in fig.buttons)) {\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
" fig.buttons[key].disabled = !msg[key];\n",
|
||
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
|
||
" if (msg['mode'] === 'PAN') {\n",
|
||
" fig.buttons['Pan'].classList.add('active');\n",
|
||
" fig.buttons['Zoom'].classList.remove('active');\n",
|
||
" } else if (msg['mode'] === 'ZOOM') {\n",
|
||
" fig.buttons['Pan'].classList.remove('active');\n",
|
||
" fig.buttons['Zoom'].classList.add('active');\n",
|
||
" } else {\n",
|
||
" fig.buttons['Pan'].classList.remove('active');\n",
|
||
" fig.buttons['Zoom'].classList.remove('active');\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function () {\n",
|
||
" // Called whenever the canvas gets updated.\n",
|
||
" this.send_message('ack', {});\n",
|
||
"};\n",
|
||
"\n",
|
||
"// A function to construct a web socket function for onmessage handling.\n",
|
||
"// Called in the figure constructor.\n",
|
||
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
|
||
" return function socket_on_message(evt) {\n",
|
||
" if (evt.data instanceof Blob) {\n",
|
||
" var img = evt.data;\n",
|
||
" if (img.type !== 'image/png') {\n",
|
||
" /* FIXME: We get \"Resource interpreted as Image but\n",
|
||
" * transferred with MIME type text/plain:\" errors on\n",
|
||
" * Chrome. But how to set the MIME type? It doesn't seem\n",
|
||
" * to be part of the websocket stream */\n",
|
||
" img.type = 'image/png';\n",
|
||
" }\n",
|
||
"\n",
|
||
" /* Free the memory for the previous frames */\n",
|
||
" if (fig.imageObj.src) {\n",
|
||
" (window.URL || window.webkitURL).revokeObjectURL(\n",
|
||
" fig.imageObj.src\n",
|
||
" );\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
|
||
" img\n",
|
||
" );\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" } else if (\n",
|
||
" typeof evt.data === 'string' &&\n",
|
||
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
|
||
" ) {\n",
|
||
" fig.imageObj.src = evt.data;\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var msg = JSON.parse(evt.data);\n",
|
||
" var msg_type = msg['type'];\n",
|
||
"\n",
|
||
" // Call the \"handle_{type}\" callback, which takes\n",
|
||
" // the figure and JSON message as its only arguments.\n",
|
||
" try {\n",
|
||
" var callback = fig['handle_' + msg_type];\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\n",
|
||
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
|
||
" msg\n",
|
||
" );\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (callback) {\n",
|
||
" try {\n",
|
||
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
|
||
" callback(fig, msg);\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\n",
|
||
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
|
||
" e,\n",
|
||
" e.stack,\n",
|
||
" msg\n",
|
||
" );\n",
|
||
" }\n",
|
||
" }\n",
|
||
" };\n",
|
||
"};\n",
|
||
"\n",
|
||
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
|
||
"mpl.findpos = function (e) {\n",
|
||
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
|
||
" var targ;\n",
|
||
" if (!e) {\n",
|
||
" e = window.event;\n",
|
||
" }\n",
|
||
" if (e.target) {\n",
|
||
" targ = e.target;\n",
|
||
" } else if (e.srcElement) {\n",
|
||
" targ = e.srcElement;\n",
|
||
" }\n",
|
||
" if (targ.nodeType === 3) {\n",
|
||
" // defeat Safari bug\n",
|
||
" targ = targ.parentNode;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // pageX,Y are the mouse positions relative to the document\n",
|
||
" var boundingRect = targ.getBoundingClientRect();\n",
|
||
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
|
||
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
|
||
"\n",
|
||
" return { x: x, y: y };\n",
|
||
"};\n",
|
||
"\n",
|
||
"/*\n",
|
||
" * return a copy of an object with only non-object keys\n",
|
||
" * we need this to avoid circular references\n",
|
||
" * http://stackoverflow.com/a/24161582/3208463\n",
|
||
" */\n",
|
||
"function simpleKeys(original) {\n",
|
||
" return Object.keys(original).reduce(function (obj, key) {\n",
|
||
" if (typeof original[key] !== 'object') {\n",
|
||
" obj[key] = original[key];\n",
|
||
" }\n",
|
||
" return obj;\n",
|
||
" }, {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
|
||
" var canvas_pos = mpl.findpos(event);\n",
|
||
"\n",
|
||
" if (name === 'button_press') {\n",
|
||
" this.canvas.focus();\n",
|
||
" this.canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" var x = canvas_pos.x * this.ratio;\n",
|
||
" var y = canvas_pos.y * this.ratio;\n",
|
||
"\n",
|
||
" this.send_message(name, {\n",
|
||
" x: x,\n",
|
||
" y: y,\n",
|
||
" button: event.button,\n",
|
||
" step: event.step,\n",
|
||
" guiEvent: simpleKeys(event),\n",
|
||
" });\n",
|
||
"\n",
|
||
" /* This prevents the web browser from automatically changing to\n",
|
||
" * the text insertion cursor when the button is pressed. We want\n",
|
||
" * to control all of the cursor setting manually through the\n",
|
||
" * 'cursor' event from matplotlib */\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
|
||
" // Handle any extra behaviour associated with a key event\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.key_event = function (event, name) {\n",
|
||
" // Prevent repeat events\n",
|
||
" if (name === 'key_press') {\n",
|
||
" if (event.key === this._key) {\n",
|
||
" return;\n",
|
||
" } else {\n",
|
||
" this._key = event.key;\n",
|
||
" }\n",
|
||
" }\n",
|
||
" if (name === 'key_release') {\n",
|
||
" this._key = null;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var value = '';\n",
|
||
" if (event.ctrlKey && event.key !== 'Control') {\n",
|
||
" value += 'ctrl+';\n",
|
||
" }\n",
|
||
" else if (event.altKey && event.key !== 'Alt') {\n",
|
||
" value += 'alt+';\n",
|
||
" }\n",
|
||
" else if (event.shiftKey && event.key !== 'Shift') {\n",
|
||
" value += 'shift+';\n",
|
||
" }\n",
|
||
"\n",
|
||
" value += 'k' + event.key;\n",
|
||
"\n",
|
||
" this._key_event_extra(event, name);\n",
|
||
"\n",
|
||
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
|
||
" return false;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
|
||
" if (name === 'download') {\n",
|
||
" this.handle_save(this, null);\n",
|
||
" } else {\n",
|
||
" this.send_message('toolbar_button', { name: name });\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
|
||
" this.message.textContent = tooltip;\n",
|
||
"};\n",
|
||
"\n",
|
||
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
|
||
"// prettier-ignore\n",
|
||
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
|
||
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
|
||
"\n",
|
||
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
|
||
"\n",
|
||
"mpl.default_extension = \"png\";/* global mpl */\n",
|
||
"\n",
|
||
"var comm_websocket_adapter = function (comm) {\n",
|
||
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
|
||
" // object with the appropriate methods. Currently this is a non binary\n",
|
||
" // socket, so there is still some room for performance tuning.\n",
|
||
" var ws = {};\n",
|
||
"\n",
|
||
" ws.binaryType = comm.kernel.ws.binaryType;\n",
|
||
" ws.readyState = comm.kernel.ws.readyState;\n",
|
||
" function updateReadyState(_event) {\n",
|
||
" if (comm.kernel.ws) {\n",
|
||
" ws.readyState = comm.kernel.ws.readyState;\n",
|
||
" } else {\n",
|
||
" ws.readyState = 3; // Closed state.\n",
|
||
" }\n",
|
||
" }\n",
|
||
" comm.kernel.ws.addEventListener('open', updateReadyState);\n",
|
||
" comm.kernel.ws.addEventListener('close', updateReadyState);\n",
|
||
" comm.kernel.ws.addEventListener('error', updateReadyState);\n",
|
||
"\n",
|
||
" ws.close = function () {\n",
|
||
" comm.close();\n",
|
||
" };\n",
|
||
" ws.send = function (m) {\n",
|
||
" //console.log('sending', m);\n",
|
||
" comm.send(m);\n",
|
||
" };\n",
|
||
" // Register the callback with on_msg.\n",
|
||
" comm.on_msg(function (msg) {\n",
|
||
" //console.log('receiving', msg['content']['data'], msg);\n",
|
||
" var data = msg['content']['data'];\n",
|
||
" if (data['blob'] !== undefined) {\n",
|
||
" data = {\n",
|
||
" data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
|
||
" };\n",
|
||
" }\n",
|
||
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
|
||
" ws.onmessage(data);\n",
|
||
" });\n",
|
||
" return ws;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.mpl_figure_comm = function (comm, msg) {\n",
|
||
" // This is the function which gets called when the mpl process\n",
|
||
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
|
||
"\n",
|
||
" var id = msg.content.data.id;\n",
|
||
" // Get hold of the div created by the display call when the Comm\n",
|
||
" // socket was opened in Python.\n",
|
||
" var element = document.getElementById(id);\n",
|
||
" var ws_proxy = comm_websocket_adapter(comm);\n",
|
||
"\n",
|
||
" function ondownload(figure, _format) {\n",
|
||
" window.open(figure.canvas.toDataURL());\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
|
||
"\n",
|
||
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
|
||
" // web socket which is closed, not our websocket->open comm proxy.\n",
|
||
" ws_proxy.onopen();\n",
|
||
"\n",
|
||
" fig.parent_element = element;\n",
|
||
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
|
||
" if (!fig.cell_info) {\n",
|
||
" console.error('Failed to find cell for figure', id, fig);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" fig.cell_info[0].output_area.element.on(\n",
|
||
" 'cleared',\n",
|
||
" { fig: fig },\n",
|
||
" fig._remove_fig_handler\n",
|
||
" );\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_close = function (fig, msg) {\n",
|
||
" var width = fig.canvas.width / fig.ratio;\n",
|
||
" fig.cell_info[0].output_area.element.off(\n",
|
||
" 'cleared',\n",
|
||
" fig._remove_fig_handler\n",
|
||
" );\n",
|
||
" fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
|
||
"\n",
|
||
" // Update the output cell to use the data from the current canvas.\n",
|
||
" fig.push_to_output();\n",
|
||
" var dataURL = fig.canvas.toDataURL();\n",
|
||
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
|
||
" // the notebook keyboard shortcuts fail.\n",
|
||
" IPython.keyboard_manager.enable();\n",
|
||
" fig.parent_element.innerHTML =\n",
|
||
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
" fig.close_ws(fig, msg);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
|
||
" fig.send_message('closing', msg);\n",
|
||
" // fig.ws.close()\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
|
||
" // Turn the data on the canvas into data in the output cell.\n",
|
||
" var width = this.canvas.width / this.ratio;\n",
|
||
" var dataURL = this.canvas.toDataURL();\n",
|
||
" this.cell_info[1]['text/html'] =\n",
|
||
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function () {\n",
|
||
" // Tell IPython that the notebook contents must change.\n",
|
||
" IPython.notebook.set_dirty(true);\n",
|
||
" this.send_message('ack', {});\n",
|
||
" var fig = this;\n",
|
||
" // Wait a second, then push the new image to the DOM so\n",
|
||
" // that it is saved nicely (might be nice to debounce this).\n",
|
||
" setTimeout(function () {\n",
|
||
" fig.push_to_output();\n",
|
||
" }, 1000);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var toolbar = document.createElement('div');\n",
|
||
" toolbar.classList = 'btn-toolbar';\n",
|
||
" this.root.appendChild(toolbar);\n",
|
||
"\n",
|
||
" function on_click_closure(name) {\n",
|
||
" return function (_event) {\n",
|
||
" return fig.toolbar_button_onclick(name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" function on_mouseover_closure(tooltip) {\n",
|
||
" return function (event) {\n",
|
||
" if (!event.currentTarget.disabled) {\n",
|
||
" return fig.toolbar_button_onmouseover(tooltip);\n",
|
||
" }\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.buttons = {};\n",
|
||
" var buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'btn-group';\n",
|
||
" var button;\n",
|
||
" for (var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" /* Instead of a spacer, we start a new button group. */\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
" buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'btn-group';\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
"\n",
|
||
" button = fig.buttons[name] = document.createElement('button');\n",
|
||
" button.classList = 'btn btn-default';\n",
|
||
" button.href = '#';\n",
|
||
" button.title = name;\n",
|
||
" button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
|
||
" button.addEventListener('click', on_click_closure(method_name));\n",
|
||
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
|
||
" buttonGroup.appendChild(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add the status bar.\n",
|
||
" var status_bar = document.createElement('span');\n",
|
||
" status_bar.classList = 'mpl-message pull-right';\n",
|
||
" toolbar.appendChild(status_bar);\n",
|
||
" this.message = status_bar;\n",
|
||
"\n",
|
||
" // Add the close button to the window.\n",
|
||
" var buttongrp = document.createElement('div');\n",
|
||
" buttongrp.classList = 'btn-group inline pull-right';\n",
|
||
" button = document.createElement('button');\n",
|
||
" button.classList = 'btn btn-mini btn-primary';\n",
|
||
" button.href = '#';\n",
|
||
" button.title = 'Stop Interaction';\n",
|
||
" button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
|
||
" button.addEventListener('click', function (_evt) {\n",
|
||
" fig.handle_close(fig, {});\n",
|
||
" });\n",
|
||
" button.addEventListener(\n",
|
||
" 'mouseover',\n",
|
||
" on_mouseover_closure('Stop Interaction')\n",
|
||
" );\n",
|
||
" buttongrp.appendChild(button);\n",
|
||
" var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
|
||
" titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._remove_fig_handler = function (event) {\n",
|
||
" var fig = event.data.fig;\n",
|
||
" if (event.target !== this) {\n",
|
||
" // Ignore bubbled events from children.\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" fig.close_ws(fig, {});\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function (el) {\n",
|
||
" el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function (el) {\n",
|
||
" // this is important to make the div 'focusable\n",
|
||
" el.setAttribute('tabindex', 0);\n",
|
||
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
|
||
" // off when our div gets focus\n",
|
||
"\n",
|
||
" // location in version 3\n",
|
||
" if (IPython.notebook.keyboard_manager) {\n",
|
||
" IPython.notebook.keyboard_manager.register_events(el);\n",
|
||
" } else {\n",
|
||
" // location in version 2\n",
|
||
" IPython.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
|
||
" var manager = IPython.notebook.keyboard_manager;\n",
|
||
" if (!manager) {\n",
|
||
" manager = IPython.keyboard_manager;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Check for shift+enter\n",
|
||
" if (event.shiftKey && event.which === 13) {\n",
|
||
" this.canvas_div.blur();\n",
|
||
" // select the cell after this one\n",
|
||
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
|
||
" IPython.notebook.select(index + 1);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
|
||
" fig.ondownload(fig, null);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.find_output_cell = function (html_output) {\n",
|
||
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
|
||
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
|
||
" // IPython event is triggered only after the cells have been serialised, which for\n",
|
||
" // our purposes (turning an active figure into a static one), is too late.\n",
|
||
" var cells = IPython.notebook.get_cells();\n",
|
||
" var ncells = cells.length;\n",
|
||
" for (var i = 0; i < ncells; i++) {\n",
|
||
" var cell = cells[i];\n",
|
||
" if (cell.cell_type === 'code') {\n",
|
||
" for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
|
||
" var data = cell.output_area.outputs[j];\n",
|
||
" if (data.data) {\n",
|
||
" // IPython >= 3 moved mimebundle to data attribute of output\n",
|
||
" data = data.data;\n",
|
||
" }\n",
|
||
" if (data['text/html'] === html_output) {\n",
|
||
" return [cell, data, j];\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"// Register the function which deals with the matplotlib target/channel.\n",
|
||
"// The kernel may be null if the page has been refreshed.\n",
|
||
"if (IPython.notebook.kernel !== null) {\n",
|
||
" IPython.notebook.kernel.comm_manager.register_target(\n",
|
||
" 'matplotlib',\n",
|
||
" mpl.mpl_figure_comm\n",
|
||
" );\n",
|
||
"}\n"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.Javascript object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<img 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width=\"754.6\">"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot = plt.plot(x, y)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/mdk/clones/JulienPalard/formations-python/initiation/.venv/lib/python3.9/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
|
||
" and should_run_async(code)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([-2.61610422e-02, 1.42921306e-02, -5.20813328e-02, -2.23127660e-02,\n",
|
||
" -1.56407798e-02, -1.94671092e-02, -2.70240020e-02, 9.87301705e-02,\n",
|
||
" 4.58401368e-02, 8.05074020e-02, -3.95228828e-02, -4.70438339e-02,\n",
|
||
" -2.31054010e-02, -3.07576425e-02, -3.02841464e-02, 6.33642997e-02,\n",
|
||
" 7.65929203e-04, 8.93655449e-02, -6.57685961e-02, -2.09331262e-02,\n",
|
||
" -7.95423933e-03, 5.15033111e-02, -1.47139641e-02, 3.71333473e-03,\n",
|
||
" 7.94331957e-02, 5.17917532e-02, -1.58413857e-02, -2.63330478e-02,\n",
|
||
" -7.13012799e-02, 7.30895506e-02, -6.87598799e-02, -4.36450681e-02,\n",
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||
" 6.89196086e-02, 2.01622940e-03, 3.38498568e-02, 8.47395945e-02,\n",
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||
" 6.27180069e-02, 9.47183223e-02, 7.17339572e-02, -2.74824583e-02,\n",
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||
" 9.66808815e-02, -4.60344335e-02, 7.89062287e-02, 5.57193000e-02,\n",
|
||
" -4.91076187e-02, 4.03865918e-02, -7.01319832e-02, -1.13030002e-02,\n",
|
||
" 5.19137561e-02, -7.96988896e-02, 4.06396940e-02, 3.77251497e-02,\n",
|
||
" -3.75263419e-02, 6.48161238e-02, -2.92075623e-02, -6.81009776e-03,\n",
|
||
" -7.91310902e-02, -7.36745412e-02, -7.48249834e-02, -6.13511927e-02,\n",
|
||
" 9.23331090e-02, -9.85932332e-02, -1.57357572e-02, -5.69554023e-02,\n",
|
||
" 2.36748510e-03, 7.05788979e-02, 3.89702976e-05, 1.37697807e-02,\n",
|
||
" 8.98334742e-04, 4.84575504e-03, 4.16759833e-02, -9.09785292e-02,\n",
|
||
" -4.54826040e-02, -2.14110992e-02, 7.81935603e-02, 6.27486750e-02,\n",
|
||
" -1.94231946e-02, -2.00489944e-02, 3.81097433e-02, -5.20383845e-02,\n",
|
||
" 4.95988748e-02, 5.29600519e-02, -2.73029453e-02, 9.46090838e-04,\n",
|
||
" -9.29933730e-02, 5.14507006e-02, -7.06237049e-02, 6.17418415e-02,\n",
|
||
" -4.82639424e-02, 9.93905438e-03, 9.90594354e-02, -5.38109982e-02,\n",
|
||
" -5.67998727e-02, 3.74765457e-02, 1.61534149e-03, -7.95271732e-02,\n",
|
||
" -3.11100791e-02, 1.92887943e-02, 8.76050520e-02, -9.95234837e-02])"
|
||
]
|
||
},
|
||
"execution_count": 36,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"noise = np.random.uniform(-1/10, 1/10, 100)\n",
|
||
"noise"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 106,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/javascript": [
|
||
"/* Put everything inside the global mpl namespace */\n",
|
||
"window.mpl = {};\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.get_websocket_type = function() {\n",
|
||
" if (typeof(WebSocket) !== 'undefined') {\n",
|
||
" return WebSocket;\n",
|
||
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
|
||
" return MozWebSocket;\n",
|
||
" } else {\n",
|
||
" alert('Your browser does not have WebSocket support. ' +\n",
|
||
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
|
||
" 'Firefox 4 and 5 are also supported but you ' +\n",
|
||
" 'have to enable WebSockets in about:config.');\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
|
||
" this.id = figure_id;\n",
|
||
"\n",
|
||
" this.ws = websocket;\n",
|
||
"\n",
|
||
" this.supports_binary = (this.ws.binaryType != undefined);\n",
|
||
"\n",
|
||
" if (!this.supports_binary) {\n",
|
||
" var warnings = document.getElementById(\"mpl-warnings\");\n",
|
||
" if (warnings) {\n",
|
||
" warnings.style.display = 'block';\n",
|
||
" warnings.textContent = (\n",
|
||
" \"This browser does not support binary websocket messages. \" +\n",
|
||
" \"Performance may be slow.\");\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj = new Image();\n",
|
||
"\n",
|
||
" this.context = undefined;\n",
|
||
" this.message = undefined;\n",
|
||
" this.canvas = undefined;\n",
|
||
" this.rubberband_canvas = undefined;\n",
|
||
" this.rubberband_context = undefined;\n",
|
||
" this.format_dropdown = undefined;\n",
|
||
"\n",
|
||
" this.image_mode = 'full';\n",
|
||
"\n",
|
||
" this.root = $('<div/>');\n",
|
||
" this._root_extra_style(this.root)\n",
|
||
" this.root.attr('style', 'display: inline-block');\n",
|
||
"\n",
|
||
" $(parent_element).append(this.root);\n",
|
||
"\n",
|
||
" this._init_header(this);\n",
|
||
" this._init_canvas(this);\n",
|
||
" this._init_toolbar(this);\n",
|
||
"\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" this.waiting = false;\n",
|
||
"\n",
|
||
" this.ws.onopen = function () {\n",
|
||
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
|
||
" fig.send_message(\"send_image_mode\", {});\n",
|
||
" if (mpl.ratio != 1) {\n",
|
||
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
|
||
" }\n",
|
||
" fig.send_message(\"refresh\", {});\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj.onload = function() {\n",
|
||
" if (fig.image_mode == 'full') {\n",
|
||
" // Full images could contain transparency (where diff images\n",
|
||
" // almost always do), so we need to clear the canvas so that\n",
|
||
" // there is no ghosting.\n",
|
||
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
" }\n",
|
||
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.imageObj.onunload = function() {\n",
|
||
" fig.ws.close();\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.ws.onmessage = this._make_on_message_function(this);\n",
|
||
"\n",
|
||
" this.ondownload = ondownload;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_header = function() {\n",
|
||
" var titlebar = $(\n",
|
||
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
|
||
" 'ui-helper-clearfix\"/>');\n",
|
||
" var titletext = $(\n",
|
||
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
|
||
" 'text-align: center; padding: 3px;\"/>');\n",
|
||
" titlebar.append(titletext)\n",
|
||
" this.root.append(titlebar);\n",
|
||
" this.header = titletext[0];\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_canvas = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var canvas_div = $('<div/>');\n",
|
||
"\n",
|
||
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
|
||
"\n",
|
||
" function canvas_keyboard_event(event) {\n",
|
||
" return fig.key_event(event, event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
|
||
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
|
||
" this.canvas_div = canvas_div\n",
|
||
" this._canvas_extra_style(canvas_div)\n",
|
||
" this.root.append(canvas_div);\n",
|
||
"\n",
|
||
" var canvas = $('<canvas/>');\n",
|
||
" canvas.addClass('mpl-canvas');\n",
|
||
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
|
||
"\n",
|
||
" this.canvas = canvas[0];\n",
|
||
" this.context = canvas[0].getContext(\"2d\");\n",
|
||
"\n",
|
||
" var backingStore = this.context.backingStorePixelRatio ||\n",
|
||
"\tthis.context.webkitBackingStorePixelRatio ||\n",
|
||
"\tthis.context.mozBackingStorePixelRatio ||\n",
|
||
"\tthis.context.msBackingStorePixelRatio ||\n",
|
||
"\tthis.context.oBackingStorePixelRatio ||\n",
|
||
"\tthis.context.backingStorePixelRatio || 1;\n",
|
||
"\n",
|
||
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
|
||
"\n",
|
||
" var rubberband = $('<canvas/>');\n",
|
||
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
|
||
"\n",
|
||
" var pass_mouse_events = true;\n",
|
||
"\n",
|
||
" canvas_div.resizable({\n",
|
||
" start: function(event, ui) {\n",
|
||
" pass_mouse_events = false;\n",
|
||
" },\n",
|
||
" resize: function(event, ui) {\n",
|
||
" fig.request_resize(ui.size.width, ui.size.height);\n",
|
||
" },\n",
|
||
" stop: function(event, ui) {\n",
|
||
" pass_mouse_events = true;\n",
|
||
" fig.request_resize(ui.size.width, ui.size.height);\n",
|
||
" },\n",
|
||
" });\n",
|
||
"\n",
|
||
" function mouse_event_fn(event) {\n",
|
||
" if (pass_mouse_events)\n",
|
||
" return fig.mouse_event(event, event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" rubberband.mousedown('button_press', mouse_event_fn);\n",
|
||
" rubberband.mouseup('button_release', mouse_event_fn);\n",
|
||
" // Throttle sequential mouse events to 1 every 20ms.\n",
|
||
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
|
||
"\n",
|
||
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
|
||
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
|
||
"\n",
|
||
" canvas_div.on(\"wheel\", function (event) {\n",
|
||
" event = event.originalEvent;\n",
|
||
" event['data'] = 'scroll'\n",
|
||
" if (event.deltaY < 0) {\n",
|
||
" event.step = 1;\n",
|
||
" } else {\n",
|
||
" event.step = -1;\n",
|
||
" }\n",
|
||
" mouse_event_fn(event);\n",
|
||
" });\n",
|
||
"\n",
|
||
" canvas_div.append(canvas);\n",
|
||
" canvas_div.append(rubberband);\n",
|
||
"\n",
|
||
" this.rubberband = rubberband;\n",
|
||
" this.rubberband_canvas = rubberband[0];\n",
|
||
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
|
||
" this.rubberband_context.strokeStyle = \"#000000\";\n",
|
||
"\n",
|
||
" this._resize_canvas = function(width, height) {\n",
|
||
" // Keep the size of the canvas, canvas container, and rubber band\n",
|
||
" // canvas in synch.\n",
|
||
" canvas_div.css('width', width)\n",
|
||
" canvas_div.css('height', height)\n",
|
||
"\n",
|
||
" canvas.attr('width', width * mpl.ratio);\n",
|
||
" canvas.attr('height', height * mpl.ratio);\n",
|
||
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
|
||
"\n",
|
||
" rubberband.attr('width', width);\n",
|
||
" rubberband.attr('height', height);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
|
||
" // upon first draw.\n",
|
||
" this._resize_canvas(600, 600);\n",
|
||
"\n",
|
||
" // Disable right mouse context menu.\n",
|
||
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
|
||
" return false;\n",
|
||
" });\n",
|
||
"\n",
|
||
" function set_focus () {\n",
|
||
" canvas.focus();\n",
|
||
" canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" window.setTimeout(set_focus, 100);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var nav_element = $('<div/>');\n",
|
||
" nav_element.attr('style', 'width: 100%');\n",
|
||
" this.root.append(nav_element);\n",
|
||
"\n",
|
||
" // Define a callback function for later on.\n",
|
||
" function toolbar_event(event) {\n",
|
||
" return fig.toolbar_button_onclick(event['data']);\n",
|
||
" }\n",
|
||
" function toolbar_mouse_event(event) {\n",
|
||
" return fig.toolbar_button_onmouseover(event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" for(var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" // put a spacer in here.\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
" var button = $('<button/>');\n",
|
||
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
|
||
" 'ui-button-icon-only');\n",
|
||
" button.attr('role', 'button');\n",
|
||
" button.attr('aria-disabled', 'false');\n",
|
||
" button.click(method_name, toolbar_event);\n",
|
||
" button.mouseover(tooltip, toolbar_mouse_event);\n",
|
||
"\n",
|
||
" var icon_img = $('<span/>');\n",
|
||
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
|
||
" icon_img.addClass(image);\n",
|
||
" icon_img.addClass('ui-corner-all');\n",
|
||
"\n",
|
||
" var tooltip_span = $('<span/>');\n",
|
||
" tooltip_span.addClass('ui-button-text');\n",
|
||
" tooltip_span.html(tooltip);\n",
|
||
"\n",
|
||
" button.append(icon_img);\n",
|
||
" button.append(tooltip_span);\n",
|
||
"\n",
|
||
" nav_element.append(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fmt_picker_span = $('<span/>');\n",
|
||
"\n",
|
||
" var fmt_picker = $('<select/>');\n",
|
||
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
|
||
" fmt_picker_span.append(fmt_picker);\n",
|
||
" nav_element.append(fmt_picker_span);\n",
|
||
" this.format_dropdown = fmt_picker[0];\n",
|
||
"\n",
|
||
" for (var ind in mpl.extensions) {\n",
|
||
" var fmt = mpl.extensions[ind];\n",
|
||
" var option = $(\n",
|
||
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
|
||
" fmt_picker.append(option);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add hover states to the ui-buttons\n",
|
||
" $( \".ui-button\" ).hover(\n",
|
||
" function() { $(this).addClass(\"ui-state-hover\");},\n",
|
||
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
|
||
" );\n",
|
||
"\n",
|
||
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
|
||
" nav_element.append(status_bar);\n",
|
||
" this.message = status_bar[0];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
|
||
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
|
||
" // which will in turn request a refresh of the image.\n",
|
||
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_message = function(type, properties) {\n",
|
||
" properties['type'] = type;\n",
|
||
" properties['figure_id'] = this.id;\n",
|
||
" this.ws.send(JSON.stringify(properties));\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_draw_message = function() {\n",
|
||
" if (!this.waiting) {\n",
|
||
" this.waiting = true;\n",
|
||
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
|
||
" var format_dropdown = fig.format_dropdown;\n",
|
||
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
|
||
" fig.ondownload(fig, format);\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
|
||
" var size = msg['size'];\n",
|
||
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
|
||
" fig._resize_canvas(size[0], size[1]);\n",
|
||
" fig.send_message(\"refresh\", {});\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
|
||
" var x0 = msg['x0'] / mpl.ratio;\n",
|
||
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
|
||
" var x1 = msg['x1'] / mpl.ratio;\n",
|
||
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
|
||
" x0 = Math.floor(x0) + 0.5;\n",
|
||
" y0 = Math.floor(y0) + 0.5;\n",
|
||
" x1 = Math.floor(x1) + 0.5;\n",
|
||
" y1 = Math.floor(y1) + 0.5;\n",
|
||
" var min_x = Math.min(x0, x1);\n",
|
||
" var min_y = Math.min(y0, y1);\n",
|
||
" var width = Math.abs(x1 - x0);\n",
|
||
" var height = Math.abs(y1 - y0);\n",
|
||
"\n",
|
||
" fig.rubberband_context.clearRect(\n",
|
||
" 0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
|
||
"\n",
|
||
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
|
||
" // Updates the figure title.\n",
|
||
" fig.header.textContent = msg['label'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
|
||
" var cursor = msg['cursor'];\n",
|
||
" switch(cursor)\n",
|
||
" {\n",
|
||
" case 0:\n",
|
||
" cursor = 'pointer';\n",
|
||
" break;\n",
|
||
" case 1:\n",
|
||
" cursor = 'default';\n",
|
||
" break;\n",
|
||
" case 2:\n",
|
||
" cursor = 'crosshair';\n",
|
||
" break;\n",
|
||
" case 3:\n",
|
||
" cursor = 'move';\n",
|
||
" break;\n",
|
||
" }\n",
|
||
" fig.rubberband_canvas.style.cursor = cursor;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
|
||
" fig.message.textContent = msg['message'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
|
||
" // Request the server to send over a new figure.\n",
|
||
" fig.send_draw_message();\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
|
||
" fig.image_mode = msg['mode'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function() {\n",
|
||
" // Called whenever the canvas gets updated.\n",
|
||
" this.send_message(\"ack\", {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"// A function to construct a web socket function for onmessage handling.\n",
|
||
"// Called in the figure constructor.\n",
|
||
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
|
||
" return function socket_on_message(evt) {\n",
|
||
" if (evt.data instanceof Blob) {\n",
|
||
" /* FIXME: We get \"Resource interpreted as Image but\n",
|
||
" * transferred with MIME type text/plain:\" errors on\n",
|
||
" * Chrome. But how to set the MIME type? It doesn't seem\n",
|
||
" * to be part of the websocket stream */\n",
|
||
" evt.data.type = \"image/png\";\n",
|
||
"\n",
|
||
" /* Free the memory for the previous frames */\n",
|
||
" if (fig.imageObj.src) {\n",
|
||
" (window.URL || window.webkitURL).revokeObjectURL(\n",
|
||
" fig.imageObj.src);\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
|
||
" evt.data);\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
|
||
" fig.imageObj.src = evt.data;\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var msg = JSON.parse(evt.data);\n",
|
||
" var msg_type = msg['type'];\n",
|
||
"\n",
|
||
" // Call the \"handle_{type}\" callback, which takes\n",
|
||
" // the figure and JSON message as its only arguments.\n",
|
||
" try {\n",
|
||
" var callback = fig[\"handle_\" + msg_type];\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (callback) {\n",
|
||
" try {\n",
|
||
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
|
||
" callback(fig, msg);\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
|
||
" }\n",
|
||
" }\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
|
||
"mpl.findpos = function(e) {\n",
|
||
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
|
||
" var targ;\n",
|
||
" if (!e)\n",
|
||
" e = window.event;\n",
|
||
" if (e.target)\n",
|
||
" targ = e.target;\n",
|
||
" else if (e.srcElement)\n",
|
||
" targ = e.srcElement;\n",
|
||
" if (targ.nodeType == 3) // defeat Safari bug\n",
|
||
" targ = targ.parentNode;\n",
|
||
"\n",
|
||
" // jQuery normalizes the pageX and pageY\n",
|
||
" // pageX,Y are the mouse positions relative to the document\n",
|
||
" // offset() returns the position of the element relative to the document\n",
|
||
" var x = e.pageX - $(targ).offset().left;\n",
|
||
" var y = e.pageY - $(targ).offset().top;\n",
|
||
"\n",
|
||
" return {\"x\": x, \"y\": y};\n",
|
||
"};\n",
|
||
"\n",
|
||
"/*\n",
|
||
" * return a copy of an object with only non-object keys\n",
|
||
" * we need this to avoid circular references\n",
|
||
" * http://stackoverflow.com/a/24161582/3208463\n",
|
||
" */\n",
|
||
"function simpleKeys (original) {\n",
|
||
" return Object.keys(original).reduce(function (obj, key) {\n",
|
||
" if (typeof original[key] !== 'object')\n",
|
||
" obj[key] = original[key]\n",
|
||
" return obj;\n",
|
||
" }, {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
|
||
" var canvas_pos = mpl.findpos(event)\n",
|
||
"\n",
|
||
" if (name === 'button_press')\n",
|
||
" {\n",
|
||
" this.canvas.focus();\n",
|
||
" this.canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" var x = canvas_pos.x * mpl.ratio;\n",
|
||
" var y = canvas_pos.y * mpl.ratio;\n",
|
||
"\n",
|
||
" this.send_message(name, {x: x, y: y, button: event.button,\n",
|
||
" step: event.step,\n",
|
||
" guiEvent: simpleKeys(event)});\n",
|
||
"\n",
|
||
" /* This prevents the web browser from automatically changing to\n",
|
||
" * the text insertion cursor when the button is pressed. We want\n",
|
||
" * to control all of the cursor setting manually through the\n",
|
||
" * 'cursor' event from matplotlib */\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
|
||
" // Handle any extra behaviour associated with a key event\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.key_event = function(event, name) {\n",
|
||
"\n",
|
||
" // Prevent repeat events\n",
|
||
" if (name == 'key_press')\n",
|
||
" {\n",
|
||
" if (event.which === this._key)\n",
|
||
" return;\n",
|
||
" else\n",
|
||
" this._key = event.which;\n",
|
||
" }\n",
|
||
" if (name == 'key_release')\n",
|
||
" this._key = null;\n",
|
||
"\n",
|
||
" var value = '';\n",
|
||
" if (event.ctrlKey && event.which != 17)\n",
|
||
" value += \"ctrl+\";\n",
|
||
" if (event.altKey && event.which != 18)\n",
|
||
" value += \"alt+\";\n",
|
||
" if (event.shiftKey && event.which != 16)\n",
|
||
" value += \"shift+\";\n",
|
||
"\n",
|
||
" value += 'k';\n",
|
||
" value += event.which.toString();\n",
|
||
"\n",
|
||
" this._key_event_extra(event, name);\n",
|
||
"\n",
|
||
" this.send_message(name, {key: value,\n",
|
||
" guiEvent: simpleKeys(event)});\n",
|
||
" return false;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
|
||
" if (name == 'download') {\n",
|
||
" this.handle_save(this, null);\n",
|
||
" } else {\n",
|
||
" this.send_message(\"toolbar_button\", {name: name});\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
|
||
" this.message.textContent = tooltip;\n",
|
||
"};\n",
|
||
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
|
||
"\n",
|
||
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
|
||
"\n",
|
||
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
|
||
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
|
||
" // object with the appropriate methods. Currently this is a non binary\n",
|
||
" // socket, so there is still some room for performance tuning.\n",
|
||
" var ws = {};\n",
|
||
"\n",
|
||
" ws.close = function() {\n",
|
||
" comm.close()\n",
|
||
" };\n",
|
||
" ws.send = function(m) {\n",
|
||
" //console.log('sending', m);\n",
|
||
" comm.send(m);\n",
|
||
" };\n",
|
||
" // Register the callback with on_msg.\n",
|
||
" comm.on_msg(function(msg) {\n",
|
||
" //console.log('receiving', msg['content']['data'], msg);\n",
|
||
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
|
||
" ws.onmessage(msg['content']['data'])\n",
|
||
" });\n",
|
||
" return ws;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.mpl_figure_comm = function(comm, msg) {\n",
|
||
" // This is the function which gets called when the mpl process\n",
|
||
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
|
||
"\n",
|
||
" var id = msg.content.data.id;\n",
|
||
" // Get hold of the div created by the display call when the Comm\n",
|
||
" // socket was opened in Python.\n",
|
||
" var element = $(\"#\" + id);\n",
|
||
" var ws_proxy = comm_websocket_adapter(comm)\n",
|
||
"\n",
|
||
" function ondownload(figure, format) {\n",
|
||
" window.open(figure.imageObj.src);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fig = new mpl.figure(id, ws_proxy,\n",
|
||
" ondownload,\n",
|
||
" element.get(0));\n",
|
||
"\n",
|
||
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
|
||
" // web socket which is closed, not our websocket->open comm proxy.\n",
|
||
" ws_proxy.onopen();\n",
|
||
"\n",
|
||
" fig.parent_element = element.get(0);\n",
|
||
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
|
||
" if (!fig.cell_info) {\n",
|
||
" console.error(\"Failed to find cell for figure\", id, fig);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var output_index = fig.cell_info[2]\n",
|
||
" var cell = fig.cell_info[0];\n",
|
||
"\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
|
||
" var width = fig.canvas.width/mpl.ratio\n",
|
||
" fig.root.unbind('remove')\n",
|
||
"\n",
|
||
" // Update the output cell to use the data from the current canvas.\n",
|
||
" fig.push_to_output();\n",
|
||
" var dataURL = fig.canvas.toDataURL();\n",
|
||
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
|
||
" // the notebook keyboard shortcuts fail.\n",
|
||
" IPython.keyboard_manager.enable()\n",
|
||
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
|
||
" fig.close_ws(fig, msg);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
|
||
" fig.send_message('closing', msg);\n",
|
||
" // fig.ws.close()\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
|
||
" // Turn the data on the canvas into data in the output cell.\n",
|
||
" var width = this.canvas.width/mpl.ratio\n",
|
||
" var dataURL = this.canvas.toDataURL();\n",
|
||
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function() {\n",
|
||
" // Tell IPython that the notebook contents must change.\n",
|
||
" IPython.notebook.set_dirty(true);\n",
|
||
" this.send_message(\"ack\", {});\n",
|
||
" var fig = this;\n",
|
||
" // Wait a second, then push the new image to the DOM so\n",
|
||
" // that it is saved nicely (might be nice to debounce this).\n",
|
||
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var nav_element = $('<div/>');\n",
|
||
" nav_element.attr('style', 'width: 100%');\n",
|
||
" this.root.append(nav_element);\n",
|
||
"\n",
|
||
" // Define a callback function for later on.\n",
|
||
" function toolbar_event(event) {\n",
|
||
" return fig.toolbar_button_onclick(event['data']);\n",
|
||
" }\n",
|
||
" function toolbar_mouse_event(event) {\n",
|
||
" return fig.toolbar_button_onmouseover(event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" for(var toolbar_ind in mpl.toolbar_items){\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) { continue; };\n",
|
||
"\n",
|
||
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
|
||
" button.click(method_name, toolbar_event);\n",
|
||
" button.mouseover(tooltip, toolbar_mouse_event);\n",
|
||
" nav_element.append(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add the status bar.\n",
|
||
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
|
||
" nav_element.append(status_bar);\n",
|
||
" this.message = status_bar[0];\n",
|
||
"\n",
|
||
" // Add the close button to the window.\n",
|
||
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
|
||
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
|
||
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
|
||
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
|
||
" buttongrp.append(button);\n",
|
||
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
|
||
" titlebar.prepend(buttongrp);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function(el){\n",
|
||
" var fig = this\n",
|
||
" el.on(\"remove\", function(){\n",
|
||
"\tfig.close_ws(fig, {});\n",
|
||
" });\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
|
||
" // this is important to make the div 'focusable\n",
|
||
" el.attr('tabindex', 0)\n",
|
||
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
|
||
" // off when our div gets focus\n",
|
||
"\n",
|
||
" // location in version 3\n",
|
||
" if (IPython.notebook.keyboard_manager) {\n",
|
||
" IPython.notebook.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
" else {\n",
|
||
" // location in version 2\n",
|
||
" IPython.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
|
||
" var manager = IPython.notebook.keyboard_manager;\n",
|
||
" if (!manager)\n",
|
||
" manager = IPython.keyboard_manager;\n",
|
||
"\n",
|
||
" // Check for shift+enter\n",
|
||
" if (event.shiftKey && event.which == 13) {\n",
|
||
" this.canvas_div.blur();\n",
|
||
" // select the cell after this one\n",
|
||
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
|
||
" IPython.notebook.select(index + 1);\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
|
||
" fig.ondownload(fig, null);\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.find_output_cell = function(html_output) {\n",
|
||
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
|
||
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
|
||
" // IPython event is triggered only after the cells have been serialised, which for\n",
|
||
" // our purposes (turning an active figure into a static one), is too late.\n",
|
||
" var cells = IPython.notebook.get_cells();\n",
|
||
" var ncells = cells.length;\n",
|
||
" for (var i=0; i<ncells; i++) {\n",
|
||
" var cell = cells[i];\n",
|
||
" if (cell.cell_type === 'code'){\n",
|
||
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
|
||
" var data = cell.output_area.outputs[j];\n",
|
||
" if (data.data) {\n",
|
||
" // IPython >= 3 moved mimebundle to data attribute of output\n",
|
||
" data = data.data;\n",
|
||
" }\n",
|
||
" if (data['text/html'] == html_output) {\n",
|
||
" return [cell, data, j];\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"// Register the function which deals with the matplotlib target/channel.\n",
|
||
"// The kernel may be null if the page has been refreshed.\n",
|
||
"if (IPython.notebook.kernel != null) {\n",
|
||
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
|
||
"}\n"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.Javascript object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<img 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\" width=\"639.9166666666667\">"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot = plt.plot(x, np.sin(x) + noise)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 39,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from matplotlib.colors import Normalize\n",
|
||
"\n",
|
||
"\n",
|
||
"def show(np_array):\n",
|
||
" fig, ax = plt.subplots(figsize=(9, np_array.shape[0]))\n",
|
||
" if len(np_array.shape) == 1:\n",
|
||
" np_array = [np_array]\n",
|
||
" for y, line in enumerate(np_array):\n",
|
||
" for x, value in enumerate(line):\n",
|
||
" offset = .1 if value < 10 else .2\n",
|
||
" ax.text(x - offset, y + .15, str(value), c=\"white\", fontsize=20)\n",
|
||
" ax.imshow(np_array, cmap=\"hsv\", norm=Normalize(1, 50), aspect='equal')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 37,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"a1 = np.arange(1, 13)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 40,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/javascript": [
|
||
"/* Put everything inside the global mpl namespace */\n",
|
||
"/* global mpl */\n",
|
||
"window.mpl = {};\n",
|
||
"\n",
|
||
"mpl.get_websocket_type = function () {\n",
|
||
" if (typeof WebSocket !== 'undefined') {\n",
|
||
" return WebSocket;\n",
|
||
" } else if (typeof MozWebSocket !== 'undefined') {\n",
|
||
" return MozWebSocket;\n",
|
||
" } else {\n",
|
||
" alert(\n",
|
||
" 'Your browser does not have WebSocket support. ' +\n",
|
||
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
|
||
" 'Firefox 4 and 5 are also supported but you ' +\n",
|
||
" 'have to enable WebSockets in about:config.'\n",
|
||
" );\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
|
||
" this.id = figure_id;\n",
|
||
"\n",
|
||
" this.ws = websocket;\n",
|
||
"\n",
|
||
" this.supports_binary = this.ws.binaryType !== undefined;\n",
|
||
"\n",
|
||
" if (!this.supports_binary) {\n",
|
||
" var warnings = document.getElementById('mpl-warnings');\n",
|
||
" if (warnings) {\n",
|
||
" warnings.style.display = 'block';\n",
|
||
" warnings.textContent =\n",
|
||
" 'This browser does not support binary websocket messages. ' +\n",
|
||
" 'Performance may be slow.';\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj = new Image();\n",
|
||
"\n",
|
||
" this.context = undefined;\n",
|
||
" this.message = undefined;\n",
|
||
" this.canvas = undefined;\n",
|
||
" this.rubberband_canvas = undefined;\n",
|
||
" this.rubberband_context = undefined;\n",
|
||
" this.format_dropdown = undefined;\n",
|
||
"\n",
|
||
" this.image_mode = 'full';\n",
|
||
"\n",
|
||
" this.root = document.createElement('div');\n",
|
||
" this.root.setAttribute('style', 'display: inline-block');\n",
|
||
" this._root_extra_style(this.root);\n",
|
||
"\n",
|
||
" parent_element.appendChild(this.root);\n",
|
||
"\n",
|
||
" this._init_header(this);\n",
|
||
" this._init_canvas(this);\n",
|
||
" this._init_toolbar(this);\n",
|
||
"\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" this.waiting = false;\n",
|
||
"\n",
|
||
" this.ws.onopen = function () {\n",
|
||
" fig.send_message('supports_binary', { value: fig.supports_binary });\n",
|
||
" fig.send_message('send_image_mode', {});\n",
|
||
" if (fig.ratio !== 1) {\n",
|
||
" fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
|
||
" }\n",
|
||
" fig.send_message('refresh', {});\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.imageObj.onload = function () {\n",
|
||
" if (fig.image_mode === 'full') {\n",
|
||
" // Full images could contain transparency (where diff images\n",
|
||
" // almost always do), so we need to clear the canvas so that\n",
|
||
" // there is no ghosting.\n",
|
||
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
" }\n",
|
||
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.imageObj.onunload = function () {\n",
|
||
" fig.ws.close();\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.ws.onmessage = this._make_on_message_function(this);\n",
|
||
"\n",
|
||
" this.ondownload = ondownload;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_header = function () {\n",
|
||
" var titlebar = document.createElement('div');\n",
|
||
" titlebar.classList =\n",
|
||
" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
|
||
" var titletext = document.createElement('div');\n",
|
||
" titletext.classList = 'ui-dialog-title';\n",
|
||
" titletext.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'width: 100%; text-align: center; padding: 3px;'\n",
|
||
" );\n",
|
||
" titlebar.appendChild(titletext);\n",
|
||
" this.root.appendChild(titlebar);\n",
|
||
" this.header = titletext;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_canvas = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
|
||
" canvas_div.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'border: 1px solid #ddd;' +\n",
|
||
" 'box-sizing: content-box;' +\n",
|
||
" 'clear: both;' +\n",
|
||
" 'min-height: 1px;' +\n",
|
||
" 'min-width: 1px;' +\n",
|
||
" 'outline: 0;' +\n",
|
||
" 'overflow: hidden;' +\n",
|
||
" 'position: relative;' +\n",
|
||
" 'resize: both;'\n",
|
||
" );\n",
|
||
"\n",
|
||
" function on_keyboard_event_closure(name) {\n",
|
||
" return function (event) {\n",
|
||
" return fig.key_event(event, name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" canvas_div.addEventListener(\n",
|
||
" 'keydown',\n",
|
||
" on_keyboard_event_closure('key_press')\n",
|
||
" );\n",
|
||
" canvas_div.addEventListener(\n",
|
||
" 'keyup',\n",
|
||
" on_keyboard_event_closure('key_release')\n",
|
||
" );\n",
|
||
"\n",
|
||
" this._canvas_extra_style(canvas_div);\n",
|
||
" this.root.appendChild(canvas_div);\n",
|
||
"\n",
|
||
" var canvas = (this.canvas = document.createElement('canvas'));\n",
|
||
" canvas.classList.add('mpl-canvas');\n",
|
||
" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
|
||
"\n",
|
||
" this.context = canvas.getContext('2d');\n",
|
||
"\n",
|
||
" var backingStore =\n",
|
||
" this.context.backingStorePixelRatio ||\n",
|
||
" this.context.webkitBackingStorePixelRatio ||\n",
|
||
" this.context.mozBackingStorePixelRatio ||\n",
|
||
" this.context.msBackingStorePixelRatio ||\n",
|
||
" this.context.oBackingStorePixelRatio ||\n",
|
||
" this.context.backingStorePixelRatio ||\n",
|
||
" 1;\n",
|
||
"\n",
|
||
" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
|
||
"\n",
|
||
" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
|
||
" 'canvas'\n",
|
||
" ));\n",
|
||
" rubberband_canvas.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
|
||
" );\n",
|
||
"\n",
|
||
" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
|
||
" if (this.ResizeObserver === undefined) {\n",
|
||
" if (window.ResizeObserver !== undefined) {\n",
|
||
" this.ResizeObserver = window.ResizeObserver;\n",
|
||
" } else {\n",
|
||
" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
|
||
" this.ResizeObserver = obs.ResizeObserver;\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
|
||
" var nentries = entries.length;\n",
|
||
" for (var i = 0; i < nentries; i++) {\n",
|
||
" var entry = entries[i];\n",
|
||
" var width, height;\n",
|
||
" if (entry.contentBoxSize) {\n",
|
||
" if (entry.contentBoxSize instanceof Array) {\n",
|
||
" // Chrome 84 implements new version of spec.\n",
|
||
" width = entry.contentBoxSize[0].inlineSize;\n",
|
||
" height = entry.contentBoxSize[0].blockSize;\n",
|
||
" } else {\n",
|
||
" // Firefox implements old version of spec.\n",
|
||
" width = entry.contentBoxSize.inlineSize;\n",
|
||
" height = entry.contentBoxSize.blockSize;\n",
|
||
" }\n",
|
||
" } else {\n",
|
||
" // Chrome <84 implements even older version of spec.\n",
|
||
" width = entry.contentRect.width;\n",
|
||
" height = entry.contentRect.height;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Keep the size of the canvas and rubber band canvas in sync with\n",
|
||
" // the canvas container.\n",
|
||
" if (entry.devicePixelContentBoxSize) {\n",
|
||
" // Chrome 84 implements new version of spec.\n",
|
||
" canvas.setAttribute(\n",
|
||
" 'width',\n",
|
||
" entry.devicePixelContentBoxSize[0].inlineSize\n",
|
||
" );\n",
|
||
" canvas.setAttribute(\n",
|
||
" 'height',\n",
|
||
" entry.devicePixelContentBoxSize[0].blockSize\n",
|
||
" );\n",
|
||
" } else {\n",
|
||
" canvas.setAttribute('width', width * fig.ratio);\n",
|
||
" canvas.setAttribute('height', height * fig.ratio);\n",
|
||
" }\n",
|
||
" canvas.setAttribute(\n",
|
||
" 'style',\n",
|
||
" 'width: ' + width + 'px; height: ' + height + 'px;'\n",
|
||
" );\n",
|
||
"\n",
|
||
" rubberband_canvas.setAttribute('width', width);\n",
|
||
" rubberband_canvas.setAttribute('height', height);\n",
|
||
"\n",
|
||
" // And update the size in Python. We ignore the initial 0/0 size\n",
|
||
" // that occurs as the element is placed into the DOM, which should\n",
|
||
" // otherwise not happen due to the minimum size styling.\n",
|
||
" if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
|
||
" fig.request_resize(width, height);\n",
|
||
" }\n",
|
||
" }\n",
|
||
" });\n",
|
||
" this.resizeObserverInstance.observe(canvas_div);\n",
|
||
"\n",
|
||
" function on_mouse_event_closure(name) {\n",
|
||
" return function (event) {\n",
|
||
" return fig.mouse_event(event, name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" rubberband_canvas.addEventListener(\n",
|
||
" 'mousedown',\n",
|
||
" on_mouse_event_closure('button_press')\n",
|
||
" );\n",
|
||
" rubberband_canvas.addEventListener(\n",
|
||
" 'mouseup',\n",
|
||
" on_mouse_event_closure('button_release')\n",
|
||
" );\n",
|
||
" rubberband_canvas.addEventListener(\n",
|
||
" 'dblclick',\n",
|
||
" on_mouse_event_closure('dblclick')\n",
|
||
" );\n",
|
||
" // Throttle sequential mouse events to 1 every 20ms.\n",
|
||
" rubberband_canvas.addEventListener(\n",
|
||
" 'mousemove',\n",
|
||
" on_mouse_event_closure('motion_notify')\n",
|
||
" );\n",
|
||
"\n",
|
||
" rubberband_canvas.addEventListener(\n",
|
||
" 'mouseenter',\n",
|
||
" on_mouse_event_closure('figure_enter')\n",
|
||
" );\n",
|
||
" rubberband_canvas.addEventListener(\n",
|
||
" 'mouseleave',\n",
|
||
" on_mouse_event_closure('figure_leave')\n",
|
||
" );\n",
|
||
"\n",
|
||
" canvas_div.addEventListener('wheel', function (event) {\n",
|
||
" if (event.deltaY < 0) {\n",
|
||
" event.step = 1;\n",
|
||
" } else {\n",
|
||
" event.step = -1;\n",
|
||
" }\n",
|
||
" on_mouse_event_closure('scroll')(event);\n",
|
||
" });\n",
|
||
"\n",
|
||
" canvas_div.appendChild(canvas);\n",
|
||
" canvas_div.appendChild(rubberband_canvas);\n",
|
||
"\n",
|
||
" this.rubberband_context = rubberband_canvas.getContext('2d');\n",
|
||
" this.rubberband_context.strokeStyle = '#000000';\n",
|
||
"\n",
|
||
" this._resize_canvas = function (width, height, forward) {\n",
|
||
" if (forward) {\n",
|
||
" canvas_div.style.width = width + 'px';\n",
|
||
" canvas_div.style.height = height + 'px';\n",
|
||
" }\n",
|
||
" };\n",
|
||
"\n",
|
||
" // Disable right mouse context menu.\n",
|
||
" this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
" });\n",
|
||
"\n",
|
||
" function set_focus() {\n",
|
||
" canvas.focus();\n",
|
||
" canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" window.setTimeout(set_focus, 100);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var toolbar = document.createElement('div');\n",
|
||
" toolbar.classList = 'mpl-toolbar';\n",
|
||
" this.root.appendChild(toolbar);\n",
|
||
"\n",
|
||
" function on_click_closure(name) {\n",
|
||
" return function (_event) {\n",
|
||
" return fig.toolbar_button_onclick(name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" function on_mouseover_closure(tooltip) {\n",
|
||
" return function (event) {\n",
|
||
" if (!event.currentTarget.disabled) {\n",
|
||
" return fig.toolbar_button_onmouseover(tooltip);\n",
|
||
" }\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.buttons = {};\n",
|
||
" var buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'mpl-button-group';\n",
|
||
" for (var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" /* Instead of a spacer, we start a new button group. */\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
" buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'mpl-button-group';\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var button = (fig.buttons[name] = document.createElement('button'));\n",
|
||
" button.classList = 'mpl-widget';\n",
|
||
" button.setAttribute('role', 'button');\n",
|
||
" button.setAttribute('aria-disabled', 'false');\n",
|
||
" button.addEventListener('click', on_click_closure(method_name));\n",
|
||
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
|
||
"\n",
|
||
" var icon_img = document.createElement('img');\n",
|
||
" icon_img.src = '_images/' + image + '.png';\n",
|
||
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
|
||
" icon_img.alt = tooltip;\n",
|
||
" button.appendChild(icon_img);\n",
|
||
"\n",
|
||
" buttonGroup.appendChild(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fmt_picker = document.createElement('select');\n",
|
||
" fmt_picker.classList = 'mpl-widget';\n",
|
||
" toolbar.appendChild(fmt_picker);\n",
|
||
" this.format_dropdown = fmt_picker;\n",
|
||
"\n",
|
||
" for (var ind in mpl.extensions) {\n",
|
||
" var fmt = mpl.extensions[ind];\n",
|
||
" var option = document.createElement('option');\n",
|
||
" option.selected = fmt === mpl.default_extension;\n",
|
||
" option.innerHTML = fmt;\n",
|
||
" fmt_picker.appendChild(option);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var status_bar = document.createElement('span');\n",
|
||
" status_bar.classList = 'mpl-message';\n",
|
||
" toolbar.appendChild(status_bar);\n",
|
||
" this.message = status_bar;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
|
||
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
|
||
" // which will in turn request a refresh of the image.\n",
|
||
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_message = function (type, properties) {\n",
|
||
" properties['type'] = type;\n",
|
||
" properties['figure_id'] = this.id;\n",
|
||
" this.ws.send(JSON.stringify(properties));\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_draw_message = function () {\n",
|
||
" if (!this.waiting) {\n",
|
||
" this.waiting = true;\n",
|
||
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
|
||
" var format_dropdown = fig.format_dropdown;\n",
|
||
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
|
||
" fig.ondownload(fig, format);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
|
||
" var size = msg['size'];\n",
|
||
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
|
||
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
|
||
" fig.send_message('refresh', {});\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
|
||
" var x0 = msg['x0'] / fig.ratio;\n",
|
||
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
|
||
" var x1 = msg['x1'] / fig.ratio;\n",
|
||
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
|
||
" x0 = Math.floor(x0) + 0.5;\n",
|
||
" y0 = Math.floor(y0) + 0.5;\n",
|
||
" x1 = Math.floor(x1) + 0.5;\n",
|
||
" y1 = Math.floor(y1) + 0.5;\n",
|
||
" var min_x = Math.min(x0, x1);\n",
|
||
" var min_y = Math.min(y0, y1);\n",
|
||
" var width = Math.abs(x1 - x0);\n",
|
||
" var height = Math.abs(y1 - y0);\n",
|
||
"\n",
|
||
" fig.rubberband_context.clearRect(\n",
|
||
" 0,\n",
|
||
" 0,\n",
|
||
" fig.canvas.width / fig.ratio,\n",
|
||
" fig.canvas.height / fig.ratio\n",
|
||
" );\n",
|
||
"\n",
|
||
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
|
||
" // Updates the figure title.\n",
|
||
" fig.header.textContent = msg['label'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
|
||
" var cursor = msg['cursor'];\n",
|
||
" switch (cursor) {\n",
|
||
" case 0:\n",
|
||
" cursor = 'pointer';\n",
|
||
" break;\n",
|
||
" case 1:\n",
|
||
" cursor = 'default';\n",
|
||
" break;\n",
|
||
" case 2:\n",
|
||
" cursor = 'crosshair';\n",
|
||
" break;\n",
|
||
" case 3:\n",
|
||
" cursor = 'move';\n",
|
||
" break;\n",
|
||
" }\n",
|
||
" fig.rubberband_canvas.style.cursor = cursor;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
|
||
" fig.message.textContent = msg['message'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
|
||
" // Request the server to send over a new figure.\n",
|
||
" fig.send_draw_message();\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
|
||
" fig.image_mode = msg['mode'];\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
|
||
" for (var key in msg) {\n",
|
||
" if (!(key in fig.buttons)) {\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
" fig.buttons[key].disabled = !msg[key];\n",
|
||
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
|
||
" if (msg['mode'] === 'PAN') {\n",
|
||
" fig.buttons['Pan'].classList.add('active');\n",
|
||
" fig.buttons['Zoom'].classList.remove('active');\n",
|
||
" } else if (msg['mode'] === 'ZOOM') {\n",
|
||
" fig.buttons['Pan'].classList.remove('active');\n",
|
||
" fig.buttons['Zoom'].classList.add('active');\n",
|
||
" } else {\n",
|
||
" fig.buttons['Pan'].classList.remove('active');\n",
|
||
" fig.buttons['Zoom'].classList.remove('active');\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function () {\n",
|
||
" // Called whenever the canvas gets updated.\n",
|
||
" this.send_message('ack', {});\n",
|
||
"};\n",
|
||
"\n",
|
||
"// A function to construct a web socket function for onmessage handling.\n",
|
||
"// Called in the figure constructor.\n",
|
||
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
|
||
" return function socket_on_message(evt) {\n",
|
||
" if (evt.data instanceof Blob) {\n",
|
||
" var img = evt.data;\n",
|
||
" if (img.type !== 'image/png') {\n",
|
||
" /* FIXME: We get \"Resource interpreted as Image but\n",
|
||
" * transferred with MIME type text/plain:\" errors on\n",
|
||
" * Chrome. But how to set the MIME type? It doesn't seem\n",
|
||
" * to be part of the websocket stream */\n",
|
||
" img.type = 'image/png';\n",
|
||
" }\n",
|
||
"\n",
|
||
" /* Free the memory for the previous frames */\n",
|
||
" if (fig.imageObj.src) {\n",
|
||
" (window.URL || window.webkitURL).revokeObjectURL(\n",
|
||
" fig.imageObj.src\n",
|
||
" );\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
|
||
" img\n",
|
||
" );\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" } else if (\n",
|
||
" typeof evt.data === 'string' &&\n",
|
||
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
|
||
" ) {\n",
|
||
" fig.imageObj.src = evt.data;\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var msg = JSON.parse(evt.data);\n",
|
||
" var msg_type = msg['type'];\n",
|
||
"\n",
|
||
" // Call the \"handle_{type}\" callback, which takes\n",
|
||
" // the figure and JSON message as its only arguments.\n",
|
||
" try {\n",
|
||
" var callback = fig['handle_' + msg_type];\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\n",
|
||
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
|
||
" msg\n",
|
||
" );\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (callback) {\n",
|
||
" try {\n",
|
||
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
|
||
" callback(fig, msg);\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\n",
|
||
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
|
||
" e,\n",
|
||
" e.stack,\n",
|
||
" msg\n",
|
||
" );\n",
|
||
" }\n",
|
||
" }\n",
|
||
" };\n",
|
||
"};\n",
|
||
"\n",
|
||
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
|
||
"mpl.findpos = function (e) {\n",
|
||
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
|
||
" var targ;\n",
|
||
" if (!e) {\n",
|
||
" e = window.event;\n",
|
||
" }\n",
|
||
" if (e.target) {\n",
|
||
" targ = e.target;\n",
|
||
" } else if (e.srcElement) {\n",
|
||
" targ = e.srcElement;\n",
|
||
" }\n",
|
||
" if (targ.nodeType === 3) {\n",
|
||
" // defeat Safari bug\n",
|
||
" targ = targ.parentNode;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // pageX,Y are the mouse positions relative to the document\n",
|
||
" var boundingRect = targ.getBoundingClientRect();\n",
|
||
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
|
||
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
|
||
"\n",
|
||
" return { x: x, y: y };\n",
|
||
"};\n",
|
||
"\n",
|
||
"/*\n",
|
||
" * return a copy of an object with only non-object keys\n",
|
||
" * we need this to avoid circular references\n",
|
||
" * http://stackoverflow.com/a/24161582/3208463\n",
|
||
" */\n",
|
||
"function simpleKeys(original) {\n",
|
||
" return Object.keys(original).reduce(function (obj, key) {\n",
|
||
" if (typeof original[key] !== 'object') {\n",
|
||
" obj[key] = original[key];\n",
|
||
" }\n",
|
||
" return obj;\n",
|
||
" }, {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
|
||
" var canvas_pos = mpl.findpos(event);\n",
|
||
"\n",
|
||
" if (name === 'button_press') {\n",
|
||
" this.canvas.focus();\n",
|
||
" this.canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" var x = canvas_pos.x * this.ratio;\n",
|
||
" var y = canvas_pos.y * this.ratio;\n",
|
||
"\n",
|
||
" this.send_message(name, {\n",
|
||
" x: x,\n",
|
||
" y: y,\n",
|
||
" button: event.button,\n",
|
||
" step: event.step,\n",
|
||
" guiEvent: simpleKeys(event),\n",
|
||
" });\n",
|
||
"\n",
|
||
" /* This prevents the web browser from automatically changing to\n",
|
||
" * the text insertion cursor when the button is pressed. We want\n",
|
||
" * to control all of the cursor setting manually through the\n",
|
||
" * 'cursor' event from matplotlib */\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
|
||
" // Handle any extra behaviour associated with a key event\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.key_event = function (event, name) {\n",
|
||
" // Prevent repeat events\n",
|
||
" if (name === 'key_press') {\n",
|
||
" if (event.key === this._key) {\n",
|
||
" return;\n",
|
||
" } else {\n",
|
||
" this._key = event.key;\n",
|
||
" }\n",
|
||
" }\n",
|
||
" if (name === 'key_release') {\n",
|
||
" this._key = null;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var value = '';\n",
|
||
" if (event.ctrlKey && event.key !== 'Control') {\n",
|
||
" value += 'ctrl+';\n",
|
||
" }\n",
|
||
" else if (event.altKey && event.key !== 'Alt') {\n",
|
||
" value += 'alt+';\n",
|
||
" }\n",
|
||
" else if (event.shiftKey && event.key !== 'Shift') {\n",
|
||
" value += 'shift+';\n",
|
||
" }\n",
|
||
"\n",
|
||
" value += 'k' + event.key;\n",
|
||
"\n",
|
||
" this._key_event_extra(event, name);\n",
|
||
"\n",
|
||
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
|
||
" return false;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
|
||
" if (name === 'download') {\n",
|
||
" this.handle_save(this, null);\n",
|
||
" } else {\n",
|
||
" this.send_message('toolbar_button', { name: name });\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
|
||
" this.message.textContent = tooltip;\n",
|
||
"};\n",
|
||
"\n",
|
||
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
|
||
"// prettier-ignore\n",
|
||
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
|
||
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
|
||
"\n",
|
||
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
|
||
"\n",
|
||
"mpl.default_extension = \"png\";/* global mpl */\n",
|
||
"\n",
|
||
"var comm_websocket_adapter = function (comm) {\n",
|
||
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
|
||
" // object with the appropriate methods. Currently this is a non binary\n",
|
||
" // socket, so there is still some room for performance tuning.\n",
|
||
" var ws = {};\n",
|
||
"\n",
|
||
" ws.binaryType = comm.kernel.ws.binaryType;\n",
|
||
" ws.readyState = comm.kernel.ws.readyState;\n",
|
||
" function updateReadyState(_event) {\n",
|
||
" if (comm.kernel.ws) {\n",
|
||
" ws.readyState = comm.kernel.ws.readyState;\n",
|
||
" } else {\n",
|
||
" ws.readyState = 3; // Closed state.\n",
|
||
" }\n",
|
||
" }\n",
|
||
" comm.kernel.ws.addEventListener('open', updateReadyState);\n",
|
||
" comm.kernel.ws.addEventListener('close', updateReadyState);\n",
|
||
" comm.kernel.ws.addEventListener('error', updateReadyState);\n",
|
||
"\n",
|
||
" ws.close = function () {\n",
|
||
" comm.close();\n",
|
||
" };\n",
|
||
" ws.send = function (m) {\n",
|
||
" //console.log('sending', m);\n",
|
||
" comm.send(m);\n",
|
||
" };\n",
|
||
" // Register the callback with on_msg.\n",
|
||
" comm.on_msg(function (msg) {\n",
|
||
" //console.log('receiving', msg['content']['data'], msg);\n",
|
||
" var data = msg['content']['data'];\n",
|
||
" if (data['blob'] !== undefined) {\n",
|
||
" data = {\n",
|
||
" data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
|
||
" };\n",
|
||
" }\n",
|
||
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
|
||
" ws.onmessage(data);\n",
|
||
" });\n",
|
||
" return ws;\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.mpl_figure_comm = function (comm, msg) {\n",
|
||
" // This is the function which gets called when the mpl process\n",
|
||
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
|
||
"\n",
|
||
" var id = msg.content.data.id;\n",
|
||
" // Get hold of the div created by the display call when the Comm\n",
|
||
" // socket was opened in Python.\n",
|
||
" var element = document.getElementById(id);\n",
|
||
" var ws_proxy = comm_websocket_adapter(comm);\n",
|
||
"\n",
|
||
" function ondownload(figure, _format) {\n",
|
||
" window.open(figure.canvas.toDataURL());\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
|
||
"\n",
|
||
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
|
||
" // web socket which is closed, not our websocket->open comm proxy.\n",
|
||
" ws_proxy.onopen();\n",
|
||
"\n",
|
||
" fig.parent_element = element;\n",
|
||
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
|
||
" if (!fig.cell_info) {\n",
|
||
" console.error('Failed to find cell for figure', id, fig);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" fig.cell_info[0].output_area.element.on(\n",
|
||
" 'cleared',\n",
|
||
" { fig: fig },\n",
|
||
" fig._remove_fig_handler\n",
|
||
" );\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_close = function (fig, msg) {\n",
|
||
" var width = fig.canvas.width / fig.ratio;\n",
|
||
" fig.cell_info[0].output_area.element.off(\n",
|
||
" 'cleared',\n",
|
||
" fig._remove_fig_handler\n",
|
||
" );\n",
|
||
" fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
|
||
"\n",
|
||
" // Update the output cell to use the data from the current canvas.\n",
|
||
" fig.push_to_output();\n",
|
||
" var dataURL = fig.canvas.toDataURL();\n",
|
||
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
|
||
" // the notebook keyboard shortcuts fail.\n",
|
||
" IPython.keyboard_manager.enable();\n",
|
||
" fig.parent_element.innerHTML =\n",
|
||
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
" fig.close_ws(fig, msg);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
|
||
" fig.send_message('closing', msg);\n",
|
||
" // fig.ws.close()\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
|
||
" // Turn the data on the canvas into data in the output cell.\n",
|
||
" var width = this.canvas.width / this.ratio;\n",
|
||
" var dataURL = this.canvas.toDataURL();\n",
|
||
" this.cell_info[1]['text/html'] =\n",
|
||
" '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function () {\n",
|
||
" // Tell IPython that the notebook contents must change.\n",
|
||
" IPython.notebook.set_dirty(true);\n",
|
||
" this.send_message('ack', {});\n",
|
||
" var fig = this;\n",
|
||
" // Wait a second, then push the new image to the DOM so\n",
|
||
" // that it is saved nicely (might be nice to debounce this).\n",
|
||
" setTimeout(function () {\n",
|
||
" fig.push_to_output();\n",
|
||
" }, 1000);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function () {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var toolbar = document.createElement('div');\n",
|
||
" toolbar.classList = 'btn-toolbar';\n",
|
||
" this.root.appendChild(toolbar);\n",
|
||
"\n",
|
||
" function on_click_closure(name) {\n",
|
||
" return function (_event) {\n",
|
||
" return fig.toolbar_button_onclick(name);\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" function on_mouseover_closure(tooltip) {\n",
|
||
" return function (event) {\n",
|
||
" if (!event.currentTarget.disabled) {\n",
|
||
" return fig.toolbar_button_onmouseover(tooltip);\n",
|
||
" }\n",
|
||
" };\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.buttons = {};\n",
|
||
" var buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'btn-group';\n",
|
||
" var button;\n",
|
||
" for (var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" /* Instead of a spacer, we start a new button group. */\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
" buttonGroup = document.createElement('div');\n",
|
||
" buttonGroup.classList = 'btn-group';\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
"\n",
|
||
" button = fig.buttons[name] = document.createElement('button');\n",
|
||
" button.classList = 'btn btn-default';\n",
|
||
" button.href = '#';\n",
|
||
" button.title = name;\n",
|
||
" button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
|
||
" button.addEventListener('click', on_click_closure(method_name));\n",
|
||
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
|
||
" buttonGroup.appendChild(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (buttonGroup.hasChildNodes()) {\n",
|
||
" toolbar.appendChild(buttonGroup);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add the status bar.\n",
|
||
" var status_bar = document.createElement('span');\n",
|
||
" status_bar.classList = 'mpl-message pull-right';\n",
|
||
" toolbar.appendChild(status_bar);\n",
|
||
" this.message = status_bar;\n",
|
||
"\n",
|
||
" // Add the close button to the window.\n",
|
||
" var buttongrp = document.createElement('div');\n",
|
||
" buttongrp.classList = 'btn-group inline pull-right';\n",
|
||
" button = document.createElement('button');\n",
|
||
" button.classList = 'btn btn-mini btn-primary';\n",
|
||
" button.href = '#';\n",
|
||
" button.title = 'Stop Interaction';\n",
|
||
" button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
|
||
" button.addEventListener('click', function (_evt) {\n",
|
||
" fig.handle_close(fig, {});\n",
|
||
" });\n",
|
||
" button.addEventListener(\n",
|
||
" 'mouseover',\n",
|
||
" on_mouseover_closure('Stop Interaction')\n",
|
||
" );\n",
|
||
" buttongrp.appendChild(button);\n",
|
||
" var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
|
||
" titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._remove_fig_handler = function (event) {\n",
|
||
" var fig = event.data.fig;\n",
|
||
" if (event.target !== this) {\n",
|
||
" // Ignore bubbled events from children.\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" fig.close_ws(fig, {});\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function (el) {\n",
|
||
" el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function (el) {\n",
|
||
" // this is important to make the div 'focusable\n",
|
||
" el.setAttribute('tabindex', 0);\n",
|
||
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
|
||
" // off when our div gets focus\n",
|
||
"\n",
|
||
" // location in version 3\n",
|
||
" if (IPython.notebook.keyboard_manager) {\n",
|
||
" IPython.notebook.keyboard_manager.register_events(el);\n",
|
||
" } else {\n",
|
||
" // location in version 2\n",
|
||
" IPython.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
|
||
" var manager = IPython.notebook.keyboard_manager;\n",
|
||
" if (!manager) {\n",
|
||
" manager = IPython.keyboard_manager;\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Check for shift+enter\n",
|
||
" if (event.shiftKey && event.which === 13) {\n",
|
||
" this.canvas_div.blur();\n",
|
||
" // select the cell after this one\n",
|
||
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
|
||
" IPython.notebook.select(index + 1);\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
|
||
" fig.ondownload(fig, null);\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.find_output_cell = function (html_output) {\n",
|
||
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
|
||
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
|
||
" // IPython event is triggered only after the cells have been serialised, which for\n",
|
||
" // our purposes (turning an active figure into a static one), is too late.\n",
|
||
" var cells = IPython.notebook.get_cells();\n",
|
||
" var ncells = cells.length;\n",
|
||
" for (var i = 0; i < ncells; i++) {\n",
|
||
" var cell = cells[i];\n",
|
||
" if (cell.cell_type === 'code') {\n",
|
||
" for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
|
||
" var data = cell.output_area.outputs[j];\n",
|
||
" if (data.data) {\n",
|
||
" // IPython >= 3 moved mimebundle to data attribute of output\n",
|
||
" data = data.data;\n",
|
||
" }\n",
|
||
" if (data['text/html'] === html_output) {\n",
|
||
" return [cell, data, j];\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"// Register the function which deals with the matplotlib target/channel.\n",
|
||
"// The kernel may be null if the page has been refreshed.\n",
|
||
"if (IPython.notebook.kernel !== null) {\n",
|
||
" IPython.notebook.kernel.comm_manager.register_target(\n",
|
||
" 'matplotlib',\n",
|
||
" mpl.mpl_figure_comm\n",
|
||
" );\n",
|
||
"}\n"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.Javascript object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
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width=\"899.8000000000001\">"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(a1)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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\n",
|
||
"text/plain": [
|
||
"<Figure size 648x144 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(a1.reshape(2, 6))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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\n",
|
||
"text/plain": [
|
||
"<Figure size 648x432 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(a1.reshape(6, 2))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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\n",
|
||
"text/plain": [
|
||
"<Figure size 648x864 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(a1.reshape(3, 4).ravel())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"a2 = np.arange(13, 25)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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\n",
|
||
"text/plain": [
|
||
"<Figure size 648x864 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(a2)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 648x144 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(np.stack((a1, a2)))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 648x864 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"show(np.stack((a1, a2), axis=1))"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"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": "3.9.2"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|