mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-23 03:58:02 +00:00
522ee709c9
* Add joint kNN CDF * add jointKNN calculation * change sub script * Update readme * update sub * Small changes * comments * update nb * Update submisison script
5107 lines
742 KiB
Text
5107 lines
742 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "5a38ed25",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-04-01T08:27:04.086911Z",
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"start_time": "2023-04-01T08:27:00.587395Z"
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},
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"not found\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\n",
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"import matplotlib.pyplot as plt\n",
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"from sklearn.neighbors import NearestNeighbors\n",
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"import joblib\n",
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"from tqdm import tqdm\n",
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"try:\n",
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" import csiborgtools\n",
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"except ModuleNotFoundError:\n",
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" print(\"not found\")\n",
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" import sys\n",
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" sys.path.append(\"../\")\n",
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" import csiborgtools\n",
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"\n",
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"\n",
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"%matplotlib notebook\n",
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"%load_ext autoreload\n",
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"%autoreload 2"
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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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"id": "4218b673",
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"metadata": {
|
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"ExecuteTime": {
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"end_time": "2023-04-01T08:27:07.868868Z",
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"start_time": "2023-04-01T08:27:04.088778Z"
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}
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},
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"outputs": [],
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"source": [
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"cat1 = csiborgtools.read.HaloCatalogue(7444, min_mass=1e13, max_dist=155 / 0.705)\n",
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"cat2 = csiborgtools.read.HaloCatalogue(7468, min_mass=1e13, max_dist=155 / 0.705)"
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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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"id": "5ff7a1b6",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-04-01T08:27:07.923418Z",
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"start_time": "2023-04-01T08:27:07.870519Z"
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}
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>NearestNeighbors()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">NearestNeighbors</label><div class=\"sk-toggleable__content\"><pre>NearestNeighbors()</pre></div></div></div></div></div>"
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],
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"text/plain": [
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"NearestNeighbors()"
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]
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},
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"execution_count": 3,
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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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"knncdf = csiborgtools.match.kNN_CDF()\n",
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"\n",
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"\n",
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"knn1 = NearestNeighbors()\n",
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"knn1.fit(cat1.positions)\n",
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"\n",
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"knn2 = NearestNeighbors()\n",
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"knn2.fit(cat2.positions)\n",
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"\n",
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"# rs, cdf = knncdf(knn, nneighbours=2, Rmax=155 / 0.705, rmin=0.01, rmax=100,\n",
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"# nsamples=int(1e6), neval=int(1e4), random_state=42, batch_size=int(1e6))"
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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": 24,
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"id": "88a31951",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-04-01T08:46:56.273595Z",
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"start_time": "2023-04-01T08:46:56.088408Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"knncdf_7444.p knncdf_7468.p knncdf_7492.p knncdf_7516.p knncdf_7540.p\r\n"
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]
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}
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],
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"source": [
|
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"!ls /mnt/extraspace/rstiskalek/csiborg/knn/cross/knncdf_7444_7468.p"
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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": 42,
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"id": "b7c2d465",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-04-01T10:05:26.294670Z",
|
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"start_time": "2023-04-01T10:05:25.954223Z"
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}
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},
|
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"outputs": [],
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"source": [
|
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"from glob import glob"
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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": 45,
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"id": "6083fcbe",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-04-01T10:05:52.758709Z",
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"start_time": "2023-04-01T10:05:52.705627Z"
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}
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},
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"outputs": [],
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"source": [
|
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"files = glob(\"/mnt/extraspace/rstiskalek/csiborg/knn/cross/*\")"
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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": 46,
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"id": "6d6b9d57",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-04-01T10:06:00.023427Z",
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"start_time": "2023-04-01T10:05:59.645149Z"
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}
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 84,
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"id": "980f74df",
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"metadata": {
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"ExecuteTime": {
|
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"end_time": "2023-04-01T10:12:49.924557Z",
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"start_time": "2023-04-01T10:12:49.714545Z"
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}
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},
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"outputs": [
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{
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"data": {
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"application/javascript": [
|
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"/* Put everything inside the global mpl namespace */\n",
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"/* global mpl */\n",
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"window.mpl = {};\n",
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"\n",
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"mpl.get_websocket_type = function () {\n",
|
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" if (typeof WebSocket !== 'undefined') {\n",
|
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" return WebSocket;\n",
|
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" } else if (typeof MozWebSocket !== 'undefined') {\n",
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" return MozWebSocket;\n",
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" } else {\n",
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" alert(\n",
|
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" 'Your browser does not have WebSocket support. ' +\n",
|
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" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
|
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" 'Firefox 4 and 5 are also supported but you ' +\n",
|
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" 'have to enable WebSockets in about:config.'\n",
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" );\n",
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" }\n",
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"};\n",
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"\n",
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"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
|
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" this.id = figure_id;\n",
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"\n",
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" this.ws = websocket;\n",
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"\n",
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" this.supports_binary = this.ws.binaryType !== undefined;\n",
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"\n",
|
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" if (!this.supports_binary) {\n",
|
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" var warnings = document.getElementById('mpl-warnings');\n",
|
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" if (warnings) {\n",
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" warnings.style.display = 'block';\n",
|
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" warnings.textContent =\n",
|
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" 'This browser does not support binary websocket messages. ' +\n",
|
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" 'Performance may be slow.';\n",
|
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" }\n",
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" }\n",
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"\n",
|
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" this.imageObj = new Image();\n",
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"\n",
|
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" this.context = undefined;\n",
|
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" this.message = undefined;\n",
|
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" this.canvas = undefined;\n",
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" this.rubberband_canvas = undefined;\n",
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" this.rubberband_context = undefined;\n",
|
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" this.format_dropdown = undefined;\n",
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"\n",
|
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" this.image_mode = 'full';\n",
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"\n",
|
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" this.root = document.createElement('div');\n",
|
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" this.root.setAttribute('style', 'display: inline-block');\n",
|
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" this._root_extra_style(this.root);\n",
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"\n",
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" parent_element.appendChild(this.root);\n",
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"\n",
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" this._init_header(this);\n",
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" this._init_canvas(this);\n",
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" this._init_toolbar(this);\n",
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"\n",
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" var fig = this;\n",
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"\n",
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" this.waiting = false;\n",
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"\n",
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" this.ws.onopen = function () {\n",
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" fig.send_message('supports_binary', { value: fig.supports_binary });\n",
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" fig.send_message('send_image_mode', {});\n",
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" if (fig.ratio !== 1) {\n",
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" fig.send_message('set_device_pixel_ratio', {\n",
|
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" device_pixel_ratio: fig.ratio,\n",
|
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" });\n",
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" }\n",
|
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" fig.send_message('refresh', {});\n",
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" };\n",
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"\n",
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" this.imageObj.onload = function () {\n",
|
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" if (fig.image_mode === 'full') {\n",
|
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" // Full images could contain transparency (where diff images\n",
|
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" // almost always do), so we need to clear the canvas so that\n",
|
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" // there is no ghosting.\n",
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" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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" }\n",
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" fig.context.drawImage(fig.imageObj, 0, 0);\n",
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" };\n",
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"\n",
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" this.imageObj.onunload = function () {\n",
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" fig.ws.close();\n",
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" };\n",
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"\n",
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" this.ws.onmessage = this._make_on_message_function(this);\n",
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"\n",
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" this.ondownload = ondownload;\n",
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"};\n",
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"\n",
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"mpl.figure.prototype._init_header = function () {\n",
|
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" var titlebar = document.createElement('div');\n",
|
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" titlebar.classList =\n",
|
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" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
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" var titletext = document.createElement('div');\n",
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" titletext.classList = 'ui-dialog-title';\n",
|
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" titletext.setAttribute(\n",
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" 'style',\n",
|
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" 'width: 100%; text-align: center; padding: 3px;'\n",
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" );\n",
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" titlebar.appendChild(titletext);\n",
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" this.root.appendChild(titlebar);\n",
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" this.header = titletext;\n",
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"};\n",
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"\n",
|
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"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
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"\n",
|
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"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
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"\n",
|
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"mpl.figure.prototype._init_canvas = function () {\n",
|
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" var fig = this;\n",
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"\n",
|
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" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
|
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" canvas_div.setAttribute(\n",
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" 'style',\n",
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" 'border: 1px solid #ddd;' +\n",
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" 'box-sizing: content-box;' +\n",
|
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" 'clear: both;' +\n",
|
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" 'min-height: 1px;' +\n",
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" 'min-width: 1px;' +\n",
|
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" 'outline: 0;' +\n",
|
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" 'overflow: hidden;' +\n",
|
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" 'position: relative;' +\n",
|
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" 'resize: both;'\n",
|
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" );\n",
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"\n",
|
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" function on_keyboard_event_closure(name) {\n",
|
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" return function (event) {\n",
|
|
" return fig.key_event(event, name);\n",
|
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" };\n",
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" }\n",
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"\n",
|
|
" canvas_div.addEventListener(\n",
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|
" 'keydown',\n",
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" on_keyboard_event_closure('key_press')\n",
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" );\n",
|
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" canvas_div.addEventListener(\n",
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" 'keyup',\n",
|
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" on_keyboard_event_closure('key_release')\n",
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" );\n",
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"\n",
|
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" this._canvas_extra_style(canvas_div);\n",
|
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" this.root.appendChild(canvas_div);\n",
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"\n",
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" var canvas = (this.canvas = document.createElement('canvas'));\n",
|
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" canvas.classList.add('mpl-canvas');\n",
|
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" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
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"\n",
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" this.context = canvas.getContext('2d');\n",
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"\n",
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" var backingStore =\n",
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" this.context.backingStorePixelRatio ||\n",
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" this.context.webkitBackingStorePixelRatio ||\n",
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" this.context.mozBackingStorePixelRatio ||\n",
|
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" this.context.msBackingStorePixelRatio ||\n",
|
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" this.context.oBackingStorePixelRatio ||\n",
|
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" this.context.backingStorePixelRatio ||\n",
|
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" 1;\n",
|
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"\n",
|
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" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
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"\n",
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" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
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" 'canvas'\n",
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" ));\n",
|
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" rubberband_canvas.setAttribute(\n",
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" 'style',\n",
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" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
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" );\n",
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"\n",
|
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" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
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" if (this.ResizeObserver === undefined) {\n",
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" if (window.ResizeObserver !== undefined) {\n",
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" this.ResizeObserver = window.ResizeObserver;\n",
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" } else {\n",
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" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
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" this.ResizeObserver = obs.ResizeObserver;\n",
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" }\n",
|
|
" }\n",
|
|
"\n",
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" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
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" var nentries = entries.length;\n",
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" for (var i = 0; i < nentries; i++) {\n",
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" var entry = entries[i];\n",
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" var width, height;\n",
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" if (entry.contentBoxSize) {\n",
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" if (entry.contentBoxSize instanceof Array) {\n",
|
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" // Chrome 84 implements new version of spec.\n",
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" width = entry.contentBoxSize[0].inlineSize;\n",
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" height = entry.contentBoxSize[0].blockSize;\n",
|
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" } 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",
|
|
" fig.rubberband_canvas.style.cursor = msg['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 https://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",
|
|
" * https://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\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
|
|
"\n",
|
|
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\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",
|
|
" // 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=\"640\">"
|
|
],
|
|
"text/plain": [
|
|
"<IPython.core.display.HTML object>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"cols = plt.rcParams[\"axes.prop_cycle\"].by_key()[\"color\"]\n",
|
|
"\n",
|
|
"plt.figure()\n",
|
|
"for file in files:\n",
|
|
" d = joblib.load(file)\n",
|
|
" mask = d[\"rs\"] > 0.1\n",
|
|
" plt.plot(d[\"rs\"][mask], d[\"corr_0\"][0, mask], c=cols[0], lw=0.4)\n",
|
|
"\n",
|
|
"plt.xscale(\"log\")\n",
|
|
"plt.axvline(2.65 / 0.705, lw=0.8, c=\"red\", ls=\"--\")\n",
|
|
"# plt.yscale(\"log\")\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "997e8f91",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"id": "25936419",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:51:11.896378Z",
|
|
"start_time": "2023-04-01T08:51:11.865150Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"550.0"
|
|
]
|
|
},
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"5500 / comb(5, 3)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"id": "043a93ff",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:50:37.181588Z",
|
|
"start_time": "2023-04-01T08:50:36.718438Z"
|
|
}
|
|
},
|
|
"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_device_pixel_ratio', {\n",
|
|
" device_pixel_ratio: fig.ratio,\n",
|
|
" });\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",
|
|
" fig.rubberband_canvas.style.cursor = msg['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 https://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",
|
|
" * https://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\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
|
|
"\n",
|
|
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\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",
|
|
" // 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": [
|
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"<IPython.core.display.Javascript object>"
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]
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},
|
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"metadata": {},
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"output_type": "display_data"
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},
|
|
{
|
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"data": {
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\" width=\"640\">"
|
|
],
|
|
"text/plain": [
|
|
"<IPython.core.display.HTML object>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.plot(d[\"rs\"], d[\"corr_0\"][1, :])\n",
|
|
"plt.plot(d[\"rs\"], d[\"corr_1\"][1, :])\n",
|
|
"plt.plot(d[\"rs\"], d[\"corr_2\"][1, :])\n",
|
|
"\n",
|
|
"# plt.yscale(\"log\")\n",
|
|
"# plt.xscale(\"log\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "279d8e58",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "d08b0dc3",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:27:19.271922Z",
|
|
"start_time": "2023-04-01T08:27:07.925222Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# rs, cdf = knncdf(knn1, nneighbours=2, Rmax=155 / 0.705, rmin=0.01, rmax=100,\n",
|
|
"# nsamples=int(1e6), neval=int(1e4), random_state=42, batch_size=int(1e6))\n",
|
|
"\n",
|
|
"rs, cdf0, cdf1, joint_cdf = knncdf.joint(knn1, knn2, nneighbours=8, Rmax=155 / 0.705,\n",
|
|
" rmin=0.01, rmax=100, nsamples=int(1e6), neval=int(1e4),\n",
|
|
" random_state=42, batch_size=int(1e6))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "0866fe23",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:27:19.436097Z",
|
|
"start_time": "2023-04-01T08:27:19.397998Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"cdf0 = knncdf.clipped_cdf(cdf0)\n",
|
|
"cdf1 = knncdf.clipped_cdf(cdf1)\n",
|
|
"joint_cdf = knncdf.clipped_cdf(joint_cdf)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"id": "b0649b7e",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:27:59.413449Z",
|
|
"start_time": "2023-04-01T08:27:59.244281Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"corr = knncdf.joint_to_corr(cdf0, cdf1, joint_cdf)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"id": "b4d28785",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:33:12.811065Z",
|
|
"start_time": "2023-04-01T08:33:12.386639Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"ics = [7444, 7468, 7492, 7516, 7540, 7564, 7588, 7612, 7636, 7660, 7684,\n",
|
|
" 7708, 7732, 7756, 7780, 7804, 7828, 7852, 7876, 7900, 7924, 7948,\n",
|
|
" 7972, 7996, 8020, 8044, 8068, 8092, 8116, 8140, 8164, 8188, 8212,\n",
|
|
" 8236, 8260, 8284, 8308, 8332, 8356, 8380, 8404, 8428, 8452, 8476,\n",
|
|
" 8500, 8524, 8548, 8572, 8596, 8620, 8644, 8668, 8692, 8716, 8740,\n",
|
|
" 8764, 8788, 8812, 8836, 8860, 8884, 8908, 8932, 8956, 8980, 9004,\n",
|
|
" 9028, 9052, 9076, 9100, 9124, 9148, 9172, 9196, 9220, 9244, 9268,\n",
|
|
" 9292, 9316, 9340, 9364, 9388, 9412, 9436, 9460, 9484, 9508, 9532,\n",
|
|
" 9556, 9580, 9604, 9628, 9652, 9676, 9700, 9724, 9748, 9772, 9796,\n",
|
|
" 9820, 9844]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "aaac3eff",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:34:00.873304Z",
|
|
"start_time": "2023-04-01T08:34:00.842613Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"from scipy.special import comb\n",
|
|
"\n",
|
|
"from itertools import combinations\n",
|
|
"# for subset in itertools.combinations(stuff, L):"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "042fe713",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:34:21.387439Z",
|
|
"start_time": "2023-04-01T08:34:21.325627Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[(7444, 7468),\n",
|
|
" (7444, 7492),\n",
|
|
" (7444, 7516),\n",
|
|
" (7444, 7540),\n",
|
|
" (7444, 7564),\n",
|
|
" (7444, 7588),\n",
|
|
" (7444, 7612),\n",
|
|
" (7444, 7636),\n",
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|
" (7444, 7660),\n",
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|
" (7444, 7684),\n",
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|
" (7444, 7708),\n",
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|
" (7444, 7732),\n",
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|
" (7444, 7756),\n",
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" (7444, 7780),\n",
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|
" (7444, 7804),\n",
|
|
" (7444, 7828),\n",
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|
" (7444, 7852),\n",
|
|
" (7444, 7876),\n",
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|
" (7444, 7900),\n",
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|
" (7444, 7924),\n",
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|
" (7444, 7948),\n",
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|
" (7444, 7972),\n",
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|
" (7444, 7996),\n",
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|
" (7444, 8020),\n",
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" (7444, 8044),\n",
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" (7444, 8068),\n",
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" (7444, 8092),\n",
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" (7444, 8140),\n",
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" (7444, 8164),\n",
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" (7444, 8188),\n",
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|
" (7444, 8212),\n",
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|
" (7444, 8236),\n",
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" (7444, 8260),\n",
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|
" (7444, 8284),\n",
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|
" (7444, 8308),\n",
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|
" (7444, 8332),\n",
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|
" (7444, 8356),\n",
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|
" (7444, 8380),\n",
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|
" (7444, 8404),\n",
|
|
" (7444, 8428),\n",
|
|
" (7444, 8452),\n",
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|
" (7444, 8476),\n",
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|
" (7444, 8500),\n",
|
|
" (7444, 8524),\n",
|
|
" (7444, 8548),\n",
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|
" (7444, 8572),\n",
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|
" (7444, 8596),\n",
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|
" (7444, 8620),\n",
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|
" (7444, 8644),\n",
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|
" (7444, 8668),\n",
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|
" (7444, 8692),\n",
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" (7444, 8716),\n",
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|
" (7444, 8740),\n",
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|
" (7444, 8764),\n",
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|
" (7444, 8788),\n",
|
|
" (7444, 8812),\n",
|
|
" (7444, 8836),\n",
|
|
" (7444, 8860),\n",
|
|
" (7444, 8884),\n",
|
|
" (7444, 8908),\n",
|
|
" (7444, 8932),\n",
|
|
" (7444, 8956),\n",
|
|
" (7444, 8980),\n",
|
|
" (7444, 9004),\n",
|
|
" (7444, 9028),\n",
|
|
" (7444, 9052),\n",
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|
" (7444, 9076),\n",
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|
" (7444, 9100),\n",
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|
" (7444, 9124),\n",
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|
" (7444, 9148),\n",
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|
" (7444, 9172),\n",
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|
" (7444, 9196),\n",
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|
" (7444, 9220),\n",
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|
" (7444, 9244),\n",
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|
" (7444, 9268),\n",
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|
" (7444, 9292),\n",
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|
" (7444, 9316),\n",
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|
" (7444, 9340),\n",
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|
" (7444, 9364),\n",
|
|
" (7444, 9388),\n",
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|
" (7444, 9412),\n",
|
|
" (7444, 9436),\n",
|
|
" (7444, 9460),\n",
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|
" (7444, 9484),\n",
|
|
" (7444, 9508),\n",
|
|
" (7444, 9532),\n",
|
|
" (7444, 9556),\n",
|
|
" (7444, 9580),\n",
|
|
" (7444, 9604),\n",
|
|
" (7444, 9628),\n",
|
|
" (7444, 9652),\n",
|
|
" (7444, 9676),\n",
|
|
" (7444, 9700),\n",
|
|
" (7444, 9724),\n",
|
|
" (7444, 9748),\n",
|
|
" (7444, 9772),\n",
|
|
" (7444, 9796),\n",
|
|
" (7444, 9820),\n",
|
|
" (7444, 9844),\n",
|
|
" (7468, 7492),\n",
|
|
" (7468, 7516),\n",
|
|
" (7468, 7540),\n",
|
|
" (7468, 7564),\n",
|
|
" (7468, 7588),\n",
|
|
" (7468, 7612),\n",
|
|
" (7468, 7636),\n",
|
|
" (7468, 7660),\n",
|
|
" (7468, 7684),\n",
|
|
" (7468, 7708),\n",
|
|
" (7468, 7732),\n",
|
|
" (7468, 7756),\n",
|
|
" (7468, 7780),\n",
|
|
" (7468, 7804),\n",
|
|
" (7468, 7828),\n",
|
|
" (7468, 7852),\n",
|
|
" (7468, 7876),\n",
|
|
" (7468, 7900),\n",
|
|
" (7468, 7924),\n",
|
|
" (7468, 7948),\n",
|
|
" (7468, 7972),\n",
|
|
" (7468, 7996),\n",
|
|
" (7468, 8020),\n",
|
|
" (7468, 8044),\n",
|
|
" (7468, 8068),\n",
|
|
" (7468, 8092),\n",
|
|
" (7468, 8116),\n",
|
|
" (7468, 8140),\n",
|
|
" (7468, 8164),\n",
|
|
" (7468, 8188),\n",
|
|
" (7468, 8212),\n",
|
|
" (7468, 8236),\n",
|
|
" (7468, 8260),\n",
|
|
" (7468, 8284),\n",
|
|
" (7468, 8308),\n",
|
|
" (7468, 8332),\n",
|
|
" (7468, 8356),\n",
|
|
" (7468, 8380),\n",
|
|
" (7468, 8404),\n",
|
|
" (7468, 8428),\n",
|
|
" (7468, 8452),\n",
|
|
" (7468, 8476),\n",
|
|
" (7468, 8500),\n",
|
|
" (7468, 8524),\n",
|
|
" (7468, 8548),\n",
|
|
" (7468, 8572),\n",
|
|
" (7468, 8596),\n",
|
|
" (7468, 8620),\n",
|
|
" (7468, 8644),\n",
|
|
" (7468, 8668),\n",
|
|
" (7468, 8692),\n",
|
|
" (7468, 8716),\n",
|
|
" (7468, 8740),\n",
|
|
" (7468, 8764),\n",
|
|
" (7468, 8788),\n",
|
|
" (7468, 8812),\n",
|
|
" (7468, 8836),\n",
|
|
" (7468, 8860),\n",
|
|
" (7468, 8884),\n",
|
|
" (7468, 8908),\n",
|
|
" (7468, 8932),\n",
|
|
" (7468, 8956),\n",
|
|
" (7468, 8980),\n",
|
|
" (7468, 9004),\n",
|
|
" (7468, 9028),\n",
|
|
" (7468, 9052),\n",
|
|
" (7468, 9076),\n",
|
|
" (7468, 9100),\n",
|
|
" (7468, 9124),\n",
|
|
" (7468, 9148),\n",
|
|
" (7468, 9172),\n",
|
|
" (7468, 9196),\n",
|
|
" (7468, 9220),\n",
|
|
" (7468, 9244),\n",
|
|
" (7468, 9268),\n",
|
|
" (7468, 9292),\n",
|
|
" (7468, 9316),\n",
|
|
" (7468, 9340),\n",
|
|
" (7468, 9364),\n",
|
|
" (7468, 9388),\n",
|
|
" (7468, 9412),\n",
|
|
" (7468, 9436),\n",
|
|
" (7468, 9460),\n",
|
|
" (7468, 9484),\n",
|
|
" (7468, 9508),\n",
|
|
" (7468, 9532),\n",
|
|
" (7468, 9556),\n",
|
|
" (7468, 9580),\n",
|
|
" (7468, 9604),\n",
|
|
" (7468, 9628),\n",
|
|
" (7468, 9652),\n",
|
|
" (7468, 9676),\n",
|
|
" (7468, 9700),\n",
|
|
" (7468, 9724),\n",
|
|
" (7468, 9748),\n",
|
|
" (7468, 9772),\n",
|
|
" (7468, 9796),\n",
|
|
" (7468, 9820),\n",
|
|
" (7468, 9844),\n",
|
|
" (7492, 7516),\n",
|
|
" (7492, 7540),\n",
|
|
" (7492, 7564),\n",
|
|
" (7492, 7588),\n",
|
|
" (7492, 7612),\n",
|
|
" (7492, 7636),\n",
|
|
" (7492, 7660),\n",
|
|
" (7492, 7684),\n",
|
|
" (7492, 7708),\n",
|
|
" (7492, 7732),\n",
|
|
" (7492, 7756),\n",
|
|
" (7492, 7780),\n",
|
|
" (7492, 7804),\n",
|
|
" (7492, 7828),\n",
|
|
" (7492, 7852),\n",
|
|
" (7492, 7876),\n",
|
|
" (7492, 7900),\n",
|
|
" (7492, 7924),\n",
|
|
" (7492, 7948),\n",
|
|
" (7492, 7972),\n",
|
|
" (7492, 7996),\n",
|
|
" (7492, 8020),\n",
|
|
" (7492, 8044),\n",
|
|
" (7492, 8068),\n",
|
|
" (7492, 8092),\n",
|
|
" (7492, 8116),\n",
|
|
" (7492, 8140),\n",
|
|
" (7492, 8164),\n",
|
|
" (7492, 8188),\n",
|
|
" (7492, 8212),\n",
|
|
" (7492, 8236),\n",
|
|
" (7492, 8260),\n",
|
|
" (7492, 8284),\n",
|
|
" (7492, 8308),\n",
|
|
" (7492, 8332),\n",
|
|
" (7492, 8356),\n",
|
|
" (7492, 8380),\n",
|
|
" (7492, 8404),\n",
|
|
" (7492, 8428),\n",
|
|
" (7492, 8452),\n",
|
|
" (7492, 8476),\n",
|
|
" (7492, 8500),\n",
|
|
" (7492, 8524),\n",
|
|
" (7492, 8548),\n",
|
|
" (7492, 8572),\n",
|
|
" (7492, 8596),\n",
|
|
" (7492, 8620),\n",
|
|
" (7492, 8644),\n",
|
|
" (7492, 8668),\n",
|
|
" (7492, 8692),\n",
|
|
" (7492, 8716),\n",
|
|
" (7492, 8740),\n",
|
|
" (7492, 8764),\n",
|
|
" (7492, 8788),\n",
|
|
" (7492, 8812),\n",
|
|
" (7492, 8836),\n",
|
|
" (7492, 8860),\n",
|
|
" (7492, 8884),\n",
|
|
" (7492, 8908),\n",
|
|
" (7492, 8932),\n",
|
|
" (7492, 8956),\n",
|
|
" (7492, 8980),\n",
|
|
" (7492, 9004),\n",
|
|
" (7492, 9028),\n",
|
|
" (7492, 9052),\n",
|
|
" (7492, 9076),\n",
|
|
" (7492, 9100),\n",
|
|
" (7492, 9124),\n",
|
|
" (7492, 9148),\n",
|
|
" (7492, 9172),\n",
|
|
" (7492, 9196),\n",
|
|
" (7492, 9220),\n",
|
|
" (7492, 9244),\n",
|
|
" (7492, 9268),\n",
|
|
" (7492, 9292),\n",
|
|
" (7492, 9316),\n",
|
|
" (7492, 9340),\n",
|
|
" (7492, 9364),\n",
|
|
" (7492, 9388),\n",
|
|
" (7492, 9412),\n",
|
|
" (7492, 9436),\n",
|
|
" (7492, 9460),\n",
|
|
" (7492, 9484),\n",
|
|
" (7492, 9508),\n",
|
|
" (7492, 9532),\n",
|
|
" (7492, 9556),\n",
|
|
" (7492, 9580),\n",
|
|
" (7492, 9604),\n",
|
|
" (7492, 9628),\n",
|
|
" (7492, 9652),\n",
|
|
" (7492, 9676),\n",
|
|
" (7492, 9700),\n",
|
|
" (7492, 9724),\n",
|
|
" (7492, 9748),\n",
|
|
" (7492, 9772),\n",
|
|
" (7492, 9796),\n",
|
|
" (7492, 9820),\n",
|
|
" (7492, 9844),\n",
|
|
" (7516, 7540),\n",
|
|
" (7516, 7564),\n",
|
|
" (7516, 7588),\n",
|
|
" (7516, 7612),\n",
|
|
" (7516, 7636),\n",
|
|
" (7516, 7660),\n",
|
|
" (7516, 7684),\n",
|
|
" (7516, 7708),\n",
|
|
" (7516, 7732),\n",
|
|
" (7516, 7756),\n",
|
|
" (7516, 7780),\n",
|
|
" (7516, 7804),\n",
|
|
" (7516, 7828),\n",
|
|
" (7516, 7852),\n",
|
|
" (7516, 7876),\n",
|
|
" (7516, 7900),\n",
|
|
" (7516, 7924),\n",
|
|
" (7516, 7948),\n",
|
|
" (7516, 7972),\n",
|
|
" (7516, 7996),\n",
|
|
" (7516, 8020),\n",
|
|
" (7516, 8044),\n",
|
|
" (7516, 8068),\n",
|
|
" (7516, 8092),\n",
|
|
" (7516, 8116),\n",
|
|
" (7516, 8140),\n",
|
|
" (7516, 8164),\n",
|
|
" (7516, 8188),\n",
|
|
" (7516, 8212),\n",
|
|
" (7516, 8236),\n",
|
|
" (7516, 8260),\n",
|
|
" (7516, 8284),\n",
|
|
" (7516, 8308),\n",
|
|
" (7516, 8332),\n",
|
|
" (7516, 8356),\n",
|
|
" (7516, 8380),\n",
|
|
" (7516, 8404),\n",
|
|
" (7516, 8428),\n",
|
|
" (7516, 8452),\n",
|
|
" (7516, 8476),\n",
|
|
" (7516, 8500),\n",
|
|
" (7516, 8524),\n",
|
|
" (7516, 8548),\n",
|
|
" (7516, 8572),\n",
|
|
" (7516, 8596),\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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|
|
" (7636, 9292),\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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|
|
" (7636, 9676),\n",
|
|
" (7636, 9700),\n",
|
|
" (7636, 9724),\n",
|
|
" (7636, 9748),\n",
|
|
" (7636, 9772),\n",
|
|
" (7636, 9796),\n",
|
|
" (7636, 9820),\n",
|
|
" (7636, 9844),\n",
|
|
" (7660, 7684),\n",
|
|
" (7660, 7708),\n",
|
|
" (7660, 7732),\n",
|
|
" (7660, 7756),\n",
|
|
" (7660, 7780),\n",
|
|
" (7660, 7804),\n",
|
|
" (7660, 7828),\n",
|
|
" (7660, 7852),\n",
|
|
" (7660, 7876),\n",
|
|
" (7660, 7900),\n",
|
|
" (7660, 7924),\n",
|
|
" (7660, 7948),\n",
|
|
" (7660, 7972),\n",
|
|
" (7660, 7996),\n",
|
|
" (7660, 8020),\n",
|
|
" (7660, 8044),\n",
|
|
" (7660, 8068),\n",
|
|
" (7660, 8092),\n",
|
|
" (7660, 8116),\n",
|
|
" (7660, 8140),\n",
|
|
" (7660, 8164),\n",
|
|
" (7660, 8188),\n",
|
|
" (7660, 8212),\n",
|
|
" (7660, 8236),\n",
|
|
" (7660, 8260),\n",
|
|
" (7660, 8284),\n",
|
|
" (7660, 8308),\n",
|
|
" (7660, 8332),\n",
|
|
" (7660, 8356),\n",
|
|
" (7660, 8380),\n",
|
|
" (7660, 8404),\n",
|
|
" (7660, 8428),\n",
|
|
" (7660, 8452),\n",
|
|
" (7660, 8476),\n",
|
|
" (7660, 8500),\n",
|
|
" (7660, 8524),\n",
|
|
" (7660, 8548),\n",
|
|
" (7660, 8572),\n",
|
|
" (7660, 8596),\n",
|
|
" (7660, 8620),\n",
|
|
" (7660, 8644),\n",
|
|
" (7660, 8668),\n",
|
|
" (7660, 8692),\n",
|
|
" (7660, 8716),\n",
|
|
" (7660, 8740),\n",
|
|
" (7660, 8764),\n",
|
|
" (7660, 8788),\n",
|
|
" (7660, 8812),\n",
|
|
" (7660, 8836),\n",
|
|
" (7660, 8860),\n",
|
|
" (7660, 8884),\n",
|
|
" (7660, 8908),\n",
|
|
" (7660, 8932),\n",
|
|
" (7660, 8956),\n",
|
|
" (7660, 8980),\n",
|
|
" (7660, 9004),\n",
|
|
" (7660, 9028),\n",
|
|
" (7660, 9052),\n",
|
|
" (7660, 9076),\n",
|
|
" (7660, 9100),\n",
|
|
" (7660, 9124),\n",
|
|
" (7660, 9148),\n",
|
|
" (7660, 9172),\n",
|
|
" (7660, 9196),\n",
|
|
" (7660, 9220),\n",
|
|
" (7660, 9244),\n",
|
|
" (7660, 9268),\n",
|
|
" (7660, 9292),\n",
|
|
" (7660, 9316),\n",
|
|
" (7660, 9340),\n",
|
|
" (7660, 9364),\n",
|
|
" (7660, 9388),\n",
|
|
" (7660, 9412),\n",
|
|
" (7660, 9436),\n",
|
|
" (7660, 9460),\n",
|
|
" (7660, 9484),\n",
|
|
" (7660, 9508),\n",
|
|
" (7660, 9532),\n",
|
|
" (7660, 9556),\n",
|
|
" (7660, 9580),\n",
|
|
" (7660, 9604),\n",
|
|
" (7660, 9628),\n",
|
|
" (7660, 9652),\n",
|
|
" (7660, 9676),\n",
|
|
" (7660, 9700),\n",
|
|
" (7660, 9724),\n",
|
|
" (7660, 9748),\n",
|
|
" (7660, 9772),\n",
|
|
" (7660, 9796),\n",
|
|
" (7660, 9820),\n",
|
|
" (7660, 9844),\n",
|
|
" (7684, 7708),\n",
|
|
" (7684, 7732),\n",
|
|
" (7684, 7756),\n",
|
|
" (7684, 7780),\n",
|
|
" (7684, 7804),\n",
|
|
" (7684, 7828),\n",
|
|
" (7684, 7852),\n",
|
|
" (7684, 7876),\n",
|
|
" (7684, 7900),\n",
|
|
" (7684, 7924),\n",
|
|
" (7684, 7948),\n",
|
|
" (7684, 7972),\n",
|
|
" (7684, 7996),\n",
|
|
" (7684, 8020),\n",
|
|
" (7684, 8044),\n",
|
|
" (7684, 8068),\n",
|
|
" (7684, 8092),\n",
|
|
" (7684, 8116),\n",
|
|
" (7684, 8140),\n",
|
|
" (7684, 8164),\n",
|
|
" (7684, 8188),\n",
|
|
" (7684, 8212),\n",
|
|
" (7684, 8236),\n",
|
|
" (7684, 8260),\n",
|
|
" (7684, 8284),\n",
|
|
" (7684, 8308),\n",
|
|
" (7684, 8332),\n",
|
|
" (7684, 8356),\n",
|
|
" (7684, 8380),\n",
|
|
" (7684, 8404),\n",
|
|
" (7684, 8428),\n",
|
|
" (7684, 8452),\n",
|
|
" (7684, 8476),\n",
|
|
" (7684, 8500),\n",
|
|
" (7684, 8524),\n",
|
|
" (7684, 8548),\n",
|
|
" (7684, 8572),\n",
|
|
" (7684, 8596),\n",
|
|
" (7684, 8620),\n",
|
|
" (7684, 8644),\n",
|
|
" (7684, 8668),\n",
|
|
" (7684, 8692),\n",
|
|
" (7684, 8716),\n",
|
|
" (7684, 8740),\n",
|
|
" (7684, 8764),\n",
|
|
" ...]"
|
|
]
|
|
},
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"list(combinations(ics, 2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "762ec153",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"id": "8c43f012",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:33:18.308219Z",
|
|
"start_time": "2023-04-01T08:33:18.275965Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<function scipy.special._basic.comb(N, k, exact=False, repetition=False)>"
|
|
]
|
|
},
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"comb()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "aaca64f3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"id": "9fb9e08e",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T08:28:35.326570Z",
|
|
"start_time": "2023-04-01T08:28:35.158664Z"
|
|
}
|
|
},
|
|
"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_device_pixel_ratio', {\n",
|
|
" device_pixel_ratio: fig.ratio,\n",
|
|
" });\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",
|
|
" fig.rubberband_canvas.style.cursor = msg['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 https://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",
|
|
" * https://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\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
|
|
"\n",
|
|
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\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",
|
|
" // 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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"<img 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\" width=\"640\">"
|
|
],
|
|
"text/plain": [
|
|
"<IPython.core.display.HTML object>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"\n",
|
|
"# plt.plot(rs, knncdf.peaked_cdf(cdf0[0, :]))\n",
|
|
"# plt.plot(rs, knncdf.peaked_cdf(cdf1[0, :]))\n",
|
|
"# plt.plot(rs, knncdf.peaked_cdf(joint_cdf[0, :]))\n",
|
|
"for i in range(8):\n",
|
|
" plt.plot(rs, corr[i, :])\n",
|
|
"\n",
|
|
"\n",
|
|
"# plt.yscale(\"log\")\n",
|
|
"# plt.xscale(\"log\")\n",
|
|
"plt.axvline(2.65 / 0.705, c=\"red\", ls=\"--\")\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f295a0f9",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0d5f3d02",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T07:20:34.202874Z",
|
|
"start_time": "2023-04-01T07:20:28.353637Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"dist1, dist2 = knncdf.joint(knn1, knn2, nneighbours=2, Rmax=155 / 0.705, rmin=0.01, rmax=100,\n",
|
|
" nsamples=int(1e6), neval=int(1e4), random_state=42, batch_size=int(1e6))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a76c8124",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T07:20:41.074933Z",
|
|
"start_time": "2023-04-01T07:20:41.041448Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "127b91a8",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "8b9a8cf0",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a1825f00",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-04-01T06:01:29.388586Z",
|
|
"start_time": "2023-04-01T06:01:29.321025Z"
|
|
},
|
|
"scrolled": false
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.plot(rs, knncdf.peaked_cdf(cdf[0, :]))\n",
|
|
"\n",
|
|
"plt.yscale(\"log\" )\n",
|
|
"plt.xscale(\"log\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "289549a0",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-31T22:55:20.690887Z",
|
|
"start_time": "2023-03-31T22:55:20.656550Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"mask"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7a8c5202",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-31T22:54:52.330633Z",
|
|
"start_time": "2023-03-31T22:54:52.299548Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "46f54897",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-31T22:54:25.138813Z",
|
|
"start_time": "2023-03-31T22:54:25.105044Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"dist"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "58806ab9",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c59b3a19",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e345945c",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-31T09:35:49.059172Z",
|
|
"start_time": "2023-03-31T09:35:42.817291Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"m1 = (rs > 1) & (rs < 35)\n",
|
|
"\n",
|
|
"fig, axs = plt.subplots(ncols=3, figsize=(6.4 * 1.5, 4.8), sharey=True)\n",
|
|
"fig.subplots_adjust(wspace=0)\n",
|
|
"for k in range(3):\n",
|
|
" for n in range(len(ics)):\n",
|
|
" m = m1 & (cdfs[n, k, :] > 1e-3)\n",
|
|
" axs[k].plot(rs[m], cdfs[n, k, m], c=\"black\", lw=0.05)\n",
|
|
"\n",
|
|
" axs[k].set_xscale(\"log\")\n",
|
|
" axs[k].set_yscale(\"log\")\n",
|
|
" axs[k].set_title(r\"$k = {}$\".format(k))\n",
|
|
" axs[k].set_xlabel(r\"$r~\\left[\\mathrm{Mpc}\\right]$\")\n",
|
|
"\n",
|
|
"axs[0].set_ylabel(r\"Peaked CDF\")\n",
|
|
"\n",
|
|
"plt.tight_layout(w_pad=0)\n",
|
|
"fig.savefig(\"../plots/peaked_cdf.png\", dpi=450)\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9f8786c0",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-31T09:50:10.103650Z",
|
|
"start_time": "2023-03-31T09:50:02.221741Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"m = (rs > 0.5) & (rs < 35)\n",
|
|
"\n",
|
|
"fig, axs = plt.subplots(ncols=3, figsize=(6.4 * 1.5, 4.8), sharey=True)\n",
|
|
"fig.subplots_adjust(wspace=0)\n",
|
|
"for k in range(3):\n",
|
|
" mu = np.nanmean(cdfs[:, k, :], axis=0)\n",
|
|
"\n",
|
|
" for n in range(len(ics)):\n",
|
|
" axs[k].plot(rs[m], (cdfs[n, k, :] / mu)[m], c=\"black\", lw=0.1)\n",
|
|
"\n",
|
|
" axs[k].set_ylim(0.5, 1.5)\n",
|
|
" axs[k].axhline(1, ls=\"--\", c=\"red\", zorder=0)\n",
|
|
" axs[k].axvline(2.65 / 0.705, ls=\"--\", c=\"red\", zorder=0)\n",
|
|
" axs[k].set_xscale(\"log\")\n",
|
|
" axs[k].set_xlabel(r\"$r~\\left[\\mathrm{Mpc}\\right]$\")\n",
|
|
" axs[k].set_title(r\"$k = {}$\".format(k))\n",
|
|
" \n",
|
|
"axs[0].set_ylabel(r\"Relative peaked CDF\")\n",
|
|
"plt.tight_layout(w_pad=0)\n",
|
|
"fig.savefig(\"../plots/peaked_cdf_ratios.png\", dpi=450)\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2f64cec1",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T15:46:31.532259Z",
|
|
"start_time": "2023-03-30T15:46:30.977449Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"k = 2\n",
|
|
"mu = np.nanmean(cdfs[:, k, :], axis=0)\n",
|
|
"# plt.plot(rs, mu, c=\"black\")\n",
|
|
"for i in range(len(ics)):\n",
|
|
" plt.plot(rs, cdfs[i, k, :] / mu)\n",
|
|
"\n",
|
|
"\n",
|
|
"plt.ylim(0.75, 1.25)\n",
|
|
"plt.axhline(1, ls=\"--\", c=\"black\")\n",
|
|
"plt.xscale(\"log\")\n",
|
|
"# plt.yscale(\"log\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a6784766",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b416efb3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e650fe2c",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1311187d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "03e49a11",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T14:58:29.937514Z",
|
|
"start_time": "2023-03-30T14:58:29.530552Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"x.shape"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "24578cba",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b0024bbf",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6dc55410",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T14:41:24.290602Z",
|
|
"start_time": "2023-03-30T14:41:16.204679Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"dist0, __ = knn0.kneighbors(X, 3)\n",
|
|
"distx, __ = knnx.kneighbors(X, 3)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "11508c3c",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T14:41:24.560538Z",
|
|
"start_time": "2023-03-30T14:41:24.292674Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"x0, y0 = knncdf.peaked_cdf_from_samples(dist0[:, 0], 0.5, 20, neval=10000)\n",
|
|
"xx, yx = knncdf.peaked_cdf_from_samples(distx[:, 0], 0.5, 20, neval=10000)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "404501ad",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T14:41:24.598933Z",
|
|
"start_time": "2023-03-30T14:41:24.562062Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"distx[:, 0].min()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "43e08969",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T14:46:10.262865Z",
|
|
"start_time": "2023-03-30T14:46:09.486658Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.plot(x0, y0)\n",
|
|
"plt.plot(xx, yx)\n",
|
|
"\n",
|
|
"plt.yscale(\"log\")\n",
|
|
"plt.xscale(\"log\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "39547a75",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9e160b38",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T13:02:02.033125Z",
|
|
"start_time": "2023-03-30T13:02:00.674878Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"\n",
|
|
"for i in range(3):\n",
|
|
" plt.plot(*knncdf.cdf_from_samples(dist0[:, i], 1, 25))\n",
|
|
" plt.plot(*knncdf.cdf_from_samples(distx[:, i], 1, 25))\n",
|
|
"\n",
|
|
"# plt.xlim(0.5, 25)\n",
|
|
"\n",
|
|
"plt.yscale(\"log\")\n",
|
|
"plt.xscale(\"log\")\n",
|
|
"plt.xlabel(r\"$r~\\left[\\mathrm{Mpc}\\right]$\")\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4bfb65d8",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4703d81c",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T12:13:35.958444Z",
|
|
"start_time": "2023-03-30T12:13:35.924241Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"x = dist[:, 0]\n",
|
|
"q = np.linspace(0, 100, int(x.size / 5))\n",
|
|
"\n",
|
|
"p = np.percentile(x, q)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b054c6df",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T12:16:50.052225Z",
|
|
"start_time": "2023-03-30T12:16:50.020395Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"y = np.sort(x)\n",
|
|
"\n",
|
|
"yy = np.arange(y.size) / y.size"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5445c964",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T12:16:53.599925Z",
|
|
"start_time": "2023-03-30T12:16:53.521266Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.plot(p, q / 100)\n",
|
|
"\n",
|
|
"plt.plot(y, yy)\n",
|
|
"\n",
|
|
"# plt.yscale(\"log\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "87fe5874",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "fb0ad6b9",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T12:03:34.387625Z",
|
|
"start_time": "2023-03-30T12:03:34.290961Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.hist(dist[:, 0], bins=\"auto\", histtype=\"step\")\n",
|
|
"plt.hist(dist[:, 1], bins=\"auto\", histtype=\"step\")\n",
|
|
"plt.hist(dist[:, 2], bins=\"auto\", histtype=\"step\")\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c2aba833",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6f70f238",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "03bcb191",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:38:04.906150Z",
|
|
"start_time": "2023-03-30T11:38:04.758107Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.hist(cat0[\"dec\"], bins=\"auto\")\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e5ad4722",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:53:23.004853Z",
|
|
"start_time": "2023-03-30T11:53:22.971967Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"gen = np.random.default_rng(22)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "785b530a",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:53:23.330397Z",
|
|
"start_time": "2023-03-30T11:53:23.296612Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"gen.normal()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b3d3b5e6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "464b606d",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:36:13.649124Z",
|
|
"start_time": "2023-03-30T11:36:12.995693Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"theta = np.linspace( t, np.pi, 100)\n",
|
|
"\n",
|
|
"plt.figure()\n",
|
|
"plt.plot(theta, np.sin(theta))\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c29049f5",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "cd2a3295",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "af9abf04",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:10:11.104389Z",
|
|
"start_time": "2023-03-30T11:10:11.070499Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"X = np.array([-3.9514747, -0.6966991, 2.97158]).reshape(1, -1)\n",
|
|
"\n",
|
|
"X"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e181b3c3",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:32:17.840355Z",
|
|
"start_time": "2023-03-30T11:32:17.351883Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"dist, indxs = knn0.kneighbors(X, n_neighbors=1)\n",
|
|
"\n",
|
|
"dist, indxs"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d38fd960",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-30T11:10:18.182326Z",
|
|
"start_time": "2023-03-30T11:10:18.145629Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"cat0.positions[indxs]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a16ddc2f",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "bbbe8fb6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "759a0149",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "312c96c9",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b097637b",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2ced23cb",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "be26cbcc",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "venv_galomatch",
|
|
"language": "python",
|
|
"name": "venv_galomatch"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.8.0"
|
|
},
|
|
"vscode": {
|
|
"interpreter": {
|
|
"hash": "f29d02a8350410abc2a9fb79641689d10bf7ab64afc03ec87ca3cf6ed2daa499"
|
|
}
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|