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book/features/widgets.ipynb
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"source": [
"# Widgets\n",
"\n",
"If you publish widgets in a jupyter book they might (depending on your implementation) require an active python kernel for the output to be interactive. Using the [thebe-integration](live_code.md), this is possible. Note: You can circumvent the use of a kernel by using packages which don't need such a kernel, for example the [non-kernel-based widgets using Plotly](interactive_element)."
"If you publish widgets in a jupyter book they might (depending on your implementation) require an active python kernel for the output to be interactive. Using the [thebe-integration](live_code.md), this is possible. Note: You can circumvent the use of a kernel by using packages which don't need such a kernel, for example the [non-kernel-based widgets using Plotly](interactive_element).\n",
"\n",
"## `matplotlib` widgets\n",
"When you'd like to use `ipywidgets` in combinations with a `matplotlib` figure, import the following packages:\n",
"```{python}\n",
"import ipywidgets as widgets\n",
"import micropip\n",
"await micropip.install(\"ipympl\")\n",
"```\n",
"Activate the correct output format:\n",
"```{python}\n",
"%matplotlib widget\n",
"```\n",
"\n",
"Write the code which generates your plot in a function:\n",
"```{python}\n",
"fig = plt.figure() # Define the figure once\n",
"ax = fig.add_subplot(1,1,1) # Define the axis once\n",
"\n",
"def update_plot(input_variables_from_widget):\n",
" ax.clear() # Clear the existing plot\n",
" ax.plot(x,y) # Plot your actual data\n",
" plt.draw() # Update the plot whenever this function is executed\n",
"```\n",
"Initiate the widget:\n",
"```{python}\n",
"input_slider = widgets.FloatSlider(value=0, min=0, max=10, step=1, description='Input variable:') # Defines a widget, more options than just FloatSlider\n",
"widgets.interact(update_plot, input_variable_from_widget = input_slider);\n",
"```\n"
]
},
{