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Merge pull request #107 from ianhi/imshow
create imshow function
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‎docs/API.rst‎

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~mpl_interactions.interactive_plot_factory
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~mpl_interactions.interactive_hist
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~mpl_interactions.interactive_scatter
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~mpl_interactions.interactive_imshow
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generic

‎examples/devlop/devlop-imshow.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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"%matplotlib ipympl\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import ipywidgets as widgets\n",
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"%load_ext autoreload\n",
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"%autoreload 2\n",
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"from mpl_interactions 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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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"import numpy as np\n",
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"parameter1 = np.linspace(-5,5)\n",
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"parameter2 = np.linspace(-5,5, 25)\n",
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"x = np.linspace(0,np.pi,200)\n",
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"y = np.linspace(0,10,200)\n",
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"X,Y = np.meshgrid(x,y)\n",
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"image_stack1 = np.sin(X)[None,:,:]+np.exp(np.cos(Y[None,:,:]*parameter1[:,None,None]))\n",
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"print(f\"image_stack1.shape : {image_stack1.shape}\")\n",
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"# image_stack1.shape : (50, 200, 200)\n",
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"\n",
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"# create another image stack with shape (50, 25, 200, 200)\n",
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"image_stack2 = np.sin(X)[None,None,:,:]*parameter2[:,None,None] + np.exp(np.cos(Y[None,:,:]*parameter1[:,None,None]))[:,None, ...]\n",
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"print(f\"image_stack2.shape : {image_stack2.shape}\")\n",
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"# image_stack2.shape : (50, 25, 200, 200)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"fig, ax = plt.subplots()\n",
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"im = ax.imshow(image_stack1[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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"metadata": {},
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"outputs": [],
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"source": [
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"im.norm.vmin=4"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"arr = image_stack1[0] + 15\n",
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"im.set_data(arr)\n",
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"# im.norm.autoscale(arr)"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"im.norm.autoscale??"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"im.norm.vmin = arr.min()\n",
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"im.norm.vmax = arr.max()\n",
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"fig.canvas.draw()"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"def f(i):\n",
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" return image_stack1[i] + i\n",
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"fig, ax, controls = interactive_imshow(f, i = np.arange(0,50),cmap='plasma')"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"im = ax._gci()"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"im.norm.vmin = 1\n",
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"im.norm.vmax = 6"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"im.norm._stale = True"
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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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"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",
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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": "3.8.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎examples/interactive_imshow.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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%matplotlib ipympl\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from mpl_interactions import interactive_imshow, ioff, callable_else_value"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"x = np.linspace(0,np.pi,200)\n",
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"y = np.linspace(0,10,200)\n",
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"X, Y = np.meshgrid(x,y)\n",
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"\n",
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"def f(param1, param2):\n",
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" return np.sin(X)*param2 + np.exp(np.cos(Y*param1)) + param2"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"fig, ax, controls = interactive_imshow(f, param1 = (-5,5), param2 = (-3,12))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Providing an axis\n",
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"\n",
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"You can also embed the interactive plot into an existing figure"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"with ioff:\n",
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" fig, (ax1, ax2) = plt.subplots(1,2,figsize=(10,5))\n",
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"\n",
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"ax1.plot(np.sin(np.linspace(0,np.pi)))\n",
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"fig2, ax2, controls2 = interactive_imshow(f, param1=(-5,5), param2=(-3, 12), ax=ax2)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Preventing colormap autoscaling\n",
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"\n",
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"The if you do not specify vmin/vmax and your function does not return an RGB(A) image then the default behavior is to rescale the colormap for each parameter change. This can disabled using this `autoscale_cmap` argument."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"fig3, ax3, controls3 = interactive_imshow(f, param1 = (-5,5), param2 = (-3,12), autoscale_cmap=False)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### vmin and vmax: thresholding an image\n",
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"\n",
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"You can also pass `vmin` and `vmax` as functions. Additionally you do not need to use a function to provide the image, you can also provide an array"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"img = plt.imread(\"https://matplotlib.org/3.3.1/_images/stinkbug.png\")\n",
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"def vmin(min_, max_):\n",
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" return min(min_, max_)\n",
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"def vmax(min_, max_):\n",
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" return max(min_, max_)\n",
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"fig4, ax4, controls4 = interactive_imshow(img, vmin=vmin, vmax = vmax, min_= (0,.7), max_= (.3,1))"
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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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"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",
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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": "3.8.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎mpl_interactions/helpers.py‎

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"broadcast_arrays",
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"broadcast_many",
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"notebook_backend",
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"callable_else_value",
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]
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elif backend == "nbAgg".lower():
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return True
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return False
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def callable_else_value(arg, params):
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if isinstance(arg, Callable):
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return arg(**params)
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return arg

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