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kushalkolarkushalkolar
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Merge pull request #93 from kushalkolar/interactivity-rebase
interactivity using `Graphic.link()`, works with pygfx click events, and GraphicFeatures, tested with colors only so far.
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‎examples/collection.ipynb‎

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‎examples/line_collection_event.ipynb‎

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{
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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": "f02f7349-ac1a-49b7-b304-d5b701723e0f",
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"metadata": {},
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"outputs": [],
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"source": [
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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": 1,
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"id": "d9f54448-7718-4212-ac6d-163a2d3be146",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from fastplotlib.graphics import LineGraphic, LineCollection, ImageGraphic\n",
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"from fastplotlib.plot import Plot\n",
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"import pickle"
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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": "b683c6d1-d926-43e3-a221-4ec6450e3677",
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"metadata": {},
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"outputs": [],
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"source": [
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"contours = pickle.load(open(\"/home/caitlin/Downloads/contours.pickle\", \"rb\"))"
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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": "26ced005-c52f-4696-903d-a6974ae6cefc",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "2bc75fa52d484cd1b03006a6530f10b3",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"RFBOutputContext()"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"MESA-INTEL: warning: Performance support disabled, consider sysctl dev.i915.perf_stream_paranoid=0\n",
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"\n"
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]
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}
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],
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"source": [
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"plot = Plot()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "1aea0a61-db63-41e1-b330-5a922da4bac5",
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"metadata": {},
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"outputs": [],
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"source": [
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"line_collection = LineCollection(contours, cmap=\"Oranges\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "310fd5b3-49f2-4dbb-831e-cb9f369d58c8",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot.add_graphic(line_collection)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "661a5991-0de3-44d7-a626-2ae72704dcec",
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"metadata": {},
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"outputs": [],
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"source": [
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"image = ImageGraphic(data=np.ones((180, 180)))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "816f6382-f4ea-4cd4-b9f3-2dc5c232b0a5",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot.add_graphic(image)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8187fd25-18e1-451f-b2fe-8cd2e7785c8b",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d5ddd3c4-84e2-44a3-a14f-74871aa0bb8f",
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"metadata": {},
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"outputs": [],
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"source": [
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"black = np.array([0.0, 0.0, 0.0, 1.0])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6ac64f1c-21e0-4c21-b968-3953e7858848",
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d0d0c971-aac9-4c77-b88c-de9d79c7d74e",
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"metadata": {},
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"outputs": [],
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"source": [
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"def callback_function(source: Any, target: Any, event, new_data: Any):\n",
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" # calculate coms of line collection\n",
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" indices = np.array(event.pick_info[\"index\"])\n",
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" \n",
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" coms = list()\n",
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"\n",
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" for contour in target.items:\n",
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" coors = contour.data.feature_data[~np.isnan(contour.data.feature_data).any(axis=1)]\n",
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" com = coors.mean(axis=0)\n",
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" coms.append(com)\n",
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"\n",
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" # euclidean distance to find closest index of com \n",
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" indices = np.append(indices, [0])\n",
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" \n",
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" ix = np.linalg.norm((coms - indices), axis=1).argsort()[0]\n",
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" \n",
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" ix = int(ix)\n",
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" \n",
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" print(ix)\n",
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" \n",
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" target._set_feature(feature=\"colors\", new_data=new_data, indices=ix)\n",
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" \n",
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" return None"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1a46d148-3007-4c7a-bf2b-91057eba855d",
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"metadata": {},
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"outputs": [],
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"source": [
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"image.link(event_type=\"click\", target=line_collection, feature=\"colors\", new_data=black, callback_function=callback_function)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8040456e-24a5-423b-8822-99a20e7ea470",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎examples/single_contour_event.ipynb‎

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