GeezerVison

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		{
		"cells": [
		{
		"cell_type": "code",
		"execution_count": 1,
		"id": "6725ce7d-eea7-44f7-bedc-813e8ce5bf4f",
		"metadata": {},
		"outputs": [],
		"source": [
		"from fastplotlib import Plot\n",
		"from ipywidgets import HBox, Checkbox, Image, VBox, Layout, ToggleButton, Button\n",
		"import numpy as np"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 2,
		"id": "33bf59c4-14e5-43a8-8a16-69b6859864c5",
		"metadata": {},
		"outputs": [
		{
		"data": {
		"application/vnd.jupyter.widget-view+json": {
		"model_id": "257f4ccf14c54f1ba5a0642b2d7e82cc",
		"version_major": 2,
		"version_minor": 0
		},
		"text/plain": [
		"RFBOutputContext()"
		]
		},
		"metadata": {},
		"output_type": "display_data"
		},
		{
		"name": "stderr",
		"output_type": "stream",
		"text": [
		"/home/clewis7/repos/fastplotlib/fastplotlib/graphics/features/_base.py:33: UserWarning: converting float64 array to float32\n",
		" warn(f\"converting {array.dtype} array to float32\")\n"
		]
		},
		{
		"data": {
		"text/plain": [
		"<weakproxy at 0x7fe9c8a65ea0 to ImageGraphic at 0x7fe9f1a67d90>"
		]
		},
		"execution_count": 2,
		"metadata": {},
		"output_type": "execute_result"
		}
		],
		"source": [
		"plot = Plot()\n",
		"img = np.random.rand(512, 512)\n",
		"plot.add_image(img)"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 3,
		"id": "68ea8011-d6fd-448f-9bf6-34073164d271",
		"metadata": {},
		"outputs": [
		{
		"data": {
		"application/vnd.jupyter.widget-view+json": {
		"model_id": "832b884047e74f45b9e9307b0ced48cb",
		"version_major": 2,
		"version_minor": 0
		},
		"text/plain": [
		"VBox(children=(JupyterWgpuCanvas(), HBox(children=(Button(icon='expand-arrows-alt', layout=Layout(width='auto'…"
		]
		},
		"execution_count": 3,
		"metadata": {},
		"output_type": "execute_result"
		}
		],
		"source": [
		"plot.show()"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 5,
		"id": "0bbb459c-cb49-448e-b0b8-c541e55da313",
		"metadata": {},
		"outputs": [],
		"source": [
		"from fastplotlib import GridPlot\n",
		"from ipywidgets import Dropdown"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 7,
		"id": "91a31531-818b-46a2-9587-5d9ef5b59b93",
		"metadata": {},
		"outputs": [
		{
		"data": {
		"application/vnd.jupyter.widget-view+json": {
		"model_id": "7fedb853c0c74d10bfbb900a988f6a98",
		"version_major": 2,
		"version_minor": 0
		},
		"text/plain": [
		"RFBOutputContext()"
		]
		},
		"metadata": {},
		"output_type": "display_data"
		}
		],
		"source": [
		"gp = GridPlot(\n",
		" shape=(1,2),\n",
		" names=[[\"plot1\", \"plot2\"]])"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 9,
		"id": "e96bbda7-3693-42f2-bd52-f668f39134f6",
		"metadata": {},
		"outputs": [
		{
		"name": "stderr",
		"output_type": "stream",
		"text": [
		"/home/clewis7/repos/fastplotlib/fastplotlib/graphics/features/_base.py:33: UserWarning: converting float64 array to float32\n",
		" warn(f\"converting {array.dtype} array to float32\")\n"
		]
		}
		],
		"source": [
		"for subplot in gp:\n",
		" subplot.add_image(data=img)"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 15,
		"id": "1ff67ee5-c942-4171-9058-9dd910c99d4b",
		"metadata": {},
		"outputs": [
		{
		"data": {
		"text/plain": [
		"['plot1', 'plot2']"
		]
		},
		"execution_count": 15,
		"metadata": {},
		"output_type": "execute_result"
		}
		],
		"source": [
		"list(gp.names[0])"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 20,
		"id": "95e7f25a-d936-42da-ae51-33550cf1f944",
		"metadata": {},
		"outputs": [],
		"source": [
		"names = list(gp.names[0])\n",
		"\n",
		"dropdown = Dropdown(options=[name for name in names], disabled=False, description='Plots:')"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 21,
		"id": "f0ec8d8c-fbc8-4e83-a764-a191b2977675",
		"metadata": {},
		"outputs": [
		{
		"data": {
		"application/vnd.jupyter.widget-view+json": {
		"model_id": "c7eea34a49bf44e8a353c2ffbe436986",
		"version_major": 2,
		"version_minor": 0
		},
		"text/plain": [
		"Dropdown(description='Plots:', options=('plot1', 'plot2'), value='plot1')"
		]
		},
		"execution_count": 21,
		"metadata": {},
		"output_type": "execute_result"
		}
		],
		"source": [
		"dropdown"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 27,
		"id": "84e90ac1-8e35-4cb8-b9f2-a5ea6e0e742f",
		"metadata": {},
		"outputs": [],
		"source": [
		"tools = list()"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 28,
		"id": "52fbc321-0daf-49d6-bb61-cb6a16e585c3",
		"metadata": {},
		"outputs": [],
		"source": [
		"auto_tool = Button(value=False, disabled=False, icon='expand-arrows-alt', layout=Layout(width='auto'))\n",
		"center_tool = Button(value=False, disabled=False, icon='compress-arrows-alt', layout=Layout(width='auto'))\n",
		"panzoom_tool = ToggleButton(value=False, disabled=False, icon='hand-pointer', layout=Layout(width='auto'))\n",
		"maintain_aspect_tool = ToggleButton(value=False, disabled=False, description=\"1:1\", layout=Layout(width='auto'))\n",
		"maintain_aspect_tool.style.font_weight = \"bold\""
		]
		},
		{
		"cell_type": "code",
		"execution_count": 29,
		"id": "cf9c4930-8043-4d66-9e99-9e4b5b7c90e4",
		"metadata": {},
		"outputs": [],
		"source": [
		"tools.extend([auto_tool, center_tool, panzoom_tool, maintain_aspect_tool])\n",
		"toolbar = HBox(tools)"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 30,
		"id": "f3699979-ff0a-4490-9d15-b368f22fe5b8",
		"metadata": {},
		"outputs": [
		{
		"data": {
		"application/vnd.jupyter.widget-view+json": {
		"model_id": "0e7128ecae234179812d5e784930a131",
		"version_major": 2,
		"version_minor": 0
		},
		"text/plain": [
		"VBox(children=(JupyterWgpuCanvas(frame_feedback={'index': 5018, 'timestamp': 1684520752.8116126, 'localtime': …"
		]
		},
		"execution_count": 30,
		"metadata": {},
		"output_type": "execute_result"
		}
		],
		"source": [
		"VBox([gp.show(), HBox([toolbar, dropdown])])"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 32,
		"id": "cb64a77a-651e-4efd-8127-3a0e2dc87239",
		"metadata": {},
		"outputs": [],
		"source": [
		"def auto_scale(obj):\n",
		" current = dropdown.value\n",
		" if maintain_aspect_tool.value:\n",
		" gp[current].auto_scale(maintain_aspect=True)\n",
		" else:\n",
		" gp[current].auto_scale()\n",
		"\n",
		"def center_scene(obj):\n",
		" current = dropdown.value\n",
		" gp[current].center_scene()\n",
		"\n",
		"def panzoom_control(obj):\n",
		" current = dropdown.value\n",
		" if panzoom_tool.value:\n",
		" # toggle pan zoom controller\n",
		" gp[current].controller.enabled = False\n",
		" else:\n",
		" gp[current].controller.enabled = True"
		]
		},
		{
		"cell_type": "code",
		"execution_count": 33,
		"id": "52b779a2-17ad-4888-863f-da9883a2adb8",
		"metadata": {},
		"outputs": [],
		"source": [
		"panzoom_tool.observe(panzoom_control, 'value')\n",
		"auto_tool.on_click(auto_scale)\n",
		"center_tool.on_click(center_scene)"
		]
		},
		{
		"cell_type": "code",
		"execution_count": null,
		"id": "36f5e040-cc58-4b0a-beb1-1f66ea02ccb9",
		"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
		}

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