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Merged
kushalkolar merged 13 commits into from
Dec 29, 2022
Merged

Interactivity attempt 4 #93

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6f63f64
beginning base logic for interactivity impl
Dec 12, 2022
2ccb19b
further changes and ideas
Dec 12, 2022
835197a
oops
Dec 15, 2022
0dd74aa
accidentally deleted heatmap file
Dec 19, 2022
cfa0aa9
rebase
Dec 28, 2022
a39ceaa
further rebase
Dec 28, 2022
557c611
single contour example
Dec 28, 2022
76a82f1
interactivity modification
Dec 28, 2022
af8cd2e
refactoring classes
Dec 28, 2022
0517d5c
single contour updates/fixes
Dec 29, 2022
e2eb1c8
line collection, fixing feature event names
Dec 29, 2022
fa208ca
minor changes
Dec 29, 2022
118b3a8
interactivity works, image -> lines -> lines with colors
kushalkolar Dec 29, 2022
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377 changes: 0 additions & 377 deletions examples/collection.ipynb
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212 changes: 212 additions & 0 deletions examples/line_collection_event.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "f02f7349-ac1a-49b7-b304-d5b701723e0f",
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d9f54448-7718-4212-ac6d-163a2d3be146",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from fastplotlib.graphics import LineGraphic, LineCollection, ImageGraphic\n",
"from fastplotlib.plot import Plot\n",
"import pickle"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "b683c6d1-d926-43e3-a221-4ec6450e3677",
"metadata": {},
"outputs": [],
"source": [
"contours = pickle.load(open(\"/home/caitlin/Downloads/contours.pickle\", \"rb\"))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "26ced005-c52f-4696-903d-a6974ae6cefc",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2bc75fa52d484cd1b03006a6530f10b3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"RFBOutputContext()"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"MESA-INTEL: warning: Performance support disabled, consider sysctl dev.i915.perf_stream_paranoid=0\n",
"\n"
]
}
],
"source": [
"plot = Plot()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "1aea0a61-db63-41e1-b330-5a922da4bac5",
"metadata": {},
"outputs": [],
"source": [
"line_collection = LineCollection(contours, cmap=\"Oranges\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "310fd5b3-49f2-4dbb-831e-cb9f369d58c8",
"metadata": {},
"outputs": [],
"source": [
"plot.add_graphic(line_collection)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "661a5991-0de3-44d7-a626-2ae72704dcec",
"metadata": {},
"outputs": [],
"source": [
"image = ImageGraphic(data=np.ones((180, 180)))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "816f6382-f4ea-4cd4-b9f3-2dc5c232b0a5",
"metadata": {},
"outputs": [],
"source": [
"plot.add_graphic(image)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8187fd25-18e1-451f-b2fe-8cd2e7785c8b",
"metadata": {},
"outputs": [],
"source": [
"plot.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d5ddd3c4-84e2-44a3-a14f-74871aa0bb8f",
"metadata": {},
"outputs": [],
"source": [
"black = np.array([0.0, 0.0, 0.0, 1.0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6ac64f1c-21e0-4c21-b968-3953e7858848",
"metadata": {},
"outputs": [],
"source": [
"from typing import *"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d0d0c971-aac9-4c77-b88c-de9d79c7d74e",
"metadata": {},
"outputs": [],
"source": [
"def callback_function(source: Any, target: Any, event, new_data: Any):\n",
" # calculate coms of line collection\n",
" indices = np.array(event.pick_info[\"index\"])\n",
" \n",
" coms = list()\n",
"\n",
" for contour in target.items:\n",
" coors = contour.data.feature_data[~np.isnan(contour.data.feature_data).any(axis=1)]\n",
" com = coors.mean(axis=0)\n",
" coms.append(com)\n",
"\n",
" # euclidean distance to find closest index of com \n",
" indices = np.append(indices, [0])\n",
" \n",
" ix = np.linalg.norm((coms - indices), axis=1).argsort()[0]\n",
" \n",
" ix = int(ix)\n",
" \n",
" print(ix)\n",
" \n",
" target._set_feature(feature=\"colors\", new_data=new_data, indices=ix)\n",
" \n",
" return None"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1a46d148-3007-4c7a-bf2b-91057eba855d",
"metadata": {},
"outputs": [],
"source": [
"image.link(event_type=\"click\", target=line_collection, feature=\"colors\", new_data=black, callback_function=callback_function)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8040456e-24a5-423b-8822-99a20e7ea470",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
225 changes: 225 additions & 0 deletions examples/single_contour_event.ipynb
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