Merge branch 'main' into issue_3704

Author: nikhilchandra

doc/how_to/customize_a_plot.rst

@@ -0,0 +1,136 @@
+Customize a plot
+================
+
+The ``SpikeInterface`` widgets are designed to have reasonable default
+plotting options, but sometimes you’ll want to make adjustments to the
+plots. The plotting functions all return a ``Widget`` object. These
+contain and give you access to the underlying matplotlib figure and
+axis, which you can apply any matplotlib machinery to. Let’s see how to
+do this in an example, by first making some synthetic data and computing
+extensions which can be used for plotting.
+
+.. code::
+
+    import spikeinterface.full as si
+    import matplotlib.pyplot as plt
+
+    recording, sorting = si.generate_ground_truth_recording(seed=1205)
+    sorting_analyzer = si.create_sorting_analyzer(sorting=sorting, recording=recording)
+    sorting_analyzer.compute({"random_spikes": {'seed': 1205}, "templates": {}, "unit_locations": {}})
+
+    unit_locations = sorting_analyzer.get_extension("unit_locations").get_data()
+
+
+
+.. parsed-literal::
+
+    estimate_sparsity (no parallelization):   0%|          | 0/10 [00:00<?, ?it/s]
+
+
+
+.. parsed-literal::
+
+    estimate_templates_with_accumulator (no parallelization):   0%|          | 0/10 [00:00<?, ?it/s]
+
+
+Now we can plot the ``unit_locations`` and ``unit_templates`` using the
+appropriate widgets (see the `full list of
+widgets <https://spikeinterface.readthedocs.io/en/stable/modules/widgets.html#available-plotting-functions>`__
+for more!). These functions output a ``Widget object``. We’ll assign the
+unit locations widget to ``fig_units``.
+
+.. code::
+
+    fig_units = si.plot_unit_locations(sorting_analyzer)
+
+    # Each widget contains a `matplotlib` figure and axis:
+    print(type(fig_units.figure))
+    print(type(fig_units.ax))
+
+
+.. parsed-literal::
+
+    <class 'matplotlib.figure.Figure'>
+    <class 'matplotlib.axes._axes.Axes'>
+
+
+
+.. image:: customize_a_plot_files/customize_a_plot_4_1.png
+
+
+By gaining access to the matplotlib objects, we are able to utilize the
+full ``matplotlib`` machinery: adding custom titles, axis labels, ticks,
+more plots etc. Let’s customize our unit locations plot. (Note: the
+``SpikeInterface`` Team does not endorse the following style
+conventions):
+
+.. code::
+
+    # Get the widget
+    fig_units = si.plot_unit_locations(sorting_analyzer)
+
+    # Modify the widget's `axis`` to set the title and axes labels
+    fig_units.ax.set_title("My favorite units", fontname = "Comic Sans MS")
+    fig_units.ax.set_xlabel("x probe location (um)")
+    fig_units.ax.set_ylabel("y probe location (um)")
+
+    # You can also set custom ticks
+    fig_units.ax.set_xticks([-60,-30,unit_locations[0,0],30,60])
+    fig_units.ax.set_xticklabels([-60,-30,"unit_0_x",30,60])
+    fig_units.ax.set_yticks([-40,-20,0,unit_locations[0,1],40])
+    fig_units.ax.set_yticklabels([-40,-20,0,"unit_0_y",40])
+
+    # Change the limits of the plot
+    fig_units.ax.set_xlim((-30,50))
+    fig_units.ax.set_ylim((-50,50))
+
+    # And add extra information on the plot
+    fig_units.ax.text(unit_locations[6,0], unit_locations[6,1]+5, s="UNIT 6!!!", fontname="Courier")
+
+    fig_units
+
+
+
+
+.. parsed-literal::
+
+    <spikeinterface.widgets.unit_locations.UnitLocationsWidget at 0x147a81520>
+
+
+
+
+.. image:: customize_a_plot_files/customize_a_plot_6_1.png
+
+
+Beautiful!!!
+
+You can also combine figures into a multi-figure plot. The easiest way
+to do this is to set up your figure and axes first, then tell
+``SpikeInterface`` which axes it should attach the widget plot to.
+Here’s an example of making a unit summary plot.
+
+.. code::
+
+    import matplotlib.pyplot as plt
+    fig, axs = plt.subplots(ncols=2, nrows=1)
+
+    unit_id=8
+    si.plot_unit_locations(sorting_analyzer=sorting_analyzer, ax=axs[0])
+    si.plot_unit_templates(sorting_analyzer, axes=[axs[1]], unit_ids=[f'{unit_id}'])
+
+    axs[0].plot([unit_locations[8,0], unit_locations[8,0]+50], [unit_locations[8,1], unit_locations[8,1]+50])
+    axs[0].text(unit_locations[8,0]+52, unit_locations[8,1]+52, s=f"Unit {unit_id}")
+    axs[0].set_title("Unit location", fontsize=10)
+
+    fig.suptitle(f"Unit {unit_id} summary", fontfamily="Comic Sans MS", fontsize=20)
+
+    fig.tight_layout()
+
+
+
+
+.. image:: customize_a_plot_files/customize_a_plot_8_1.png
+
+
+For more details on what you can do using matplotlib, check out their
+`extensive documentation <https://matplotlib.org/stable/>`__

doc/how_to/customize_a_plot_files/customize_a_plot_4_1.png

@@ -17,3 +17,4 @@ Guides on how to solve specific, short problems in SpikeInterface. Learn how to.
     drift_with_lfp
     auto_curation_training
     auto_curation_prediction
+    customize_a_plot

doc/how_to/customize_a_plot_files/customize_a_plot_6_1.png

@@ -14,7 +14,7 @@ with `nbconvert`. Here are the steps (in this example for the `get_started`):
 
 ```
 >>>  jupytext --to notebook get_started.py
->>>  jupytext --set-formats ipynb,py get_started.ipynb
+>>>  jupytext --set-formats ipynb.py get_started.ipynb
 ```
 
 2. Run the notebook

doc/how_to/customize_a_plot_files/customize_a_plot_8_1.png

@@ -0,0 +1,100 @@
+# ---
+# jupyter:
+#   jupytext:
+#     cell_metadata_filter: -all
+#     formats: py:light,ipynb
+#     text_representation:
+#       extension: .py
+#       format_name: light
+#       format_version: '1.5'
+#       jupytext_version: 1.17.0
+#   kernelspec:
+#     display_name: .venv
+#     language: python
+#     name: python3
+# ---
+
+# # Customize a plot
+
+# The `SpikeInterface` widgets are designed to have reasonable default plotting options, but
+# sometimes you'll want to make adjustments to the plots. The plotting functions all return
+# a `Widget` object. These contain and give you access to the underlying matplotlib figure
+# and axis, which you can apply any matplotlib machinery to. Let's see how to do this in an
+# example, by first making some synthetic data and computing extensions which can be used for plotting.
+
+# +
+import spikeinterface.full as si
+import matplotlib.pyplot as plt
+
+recording, sorting = si.generate_ground_truth_recording(seed=1205)
+sorting_analyzer = si.create_sorting_analyzer(sorting=sorting, recording=recording)
+sorting_analyzer.compute({"random_spikes": {'seed': 1205}, "templates": {}, "unit_locations": {}})
+
+unit_locations = sorting_analyzer.get_extension("unit_locations").get_data()
+# -
+
+# Now we can plot the `unit_locations` and `unit_templates` using the appropriate widgets
+# (see the  [full list of widgets](https://spikeinterface.readthedocs.io/en/stable/modules/widgets.html#available-plotting-functions)
+# for more!). These functions output a `Widget object`.  We'll assign the unit locations widget to `fig_units`.
+
+# +
+fig_units = si.plot_unit_locations(sorting_analyzer)
+
+# Each widget contains a `matplotlib` figure and axis:
+print(type(fig_units.figure))
+print(type(fig_units.ax))
+# -
+
+# By gaining access to the matplotlib objects, we are able to utilize the full `matplotlib`
+# machinery: adding custom titles, axis labels, ticks, more plots etc. Let's customize
+# our unit locations plot. (Note: the `SpikeInterface` Team does not endorse the following style conventions):
+
+# +
+# Get the widget
+fig_units = si.plot_unit_locations(sorting_analyzer)
+
+# Modify the widget's `axis`` to set the title and axes labels
+fig_units.ax.set_title("My favorite units", fontname = "Comic Sans MS")
+fig_units.ax.set_xlabel("x probe location (um)")
+fig_units.ax.set_ylabel("y probe location (um)")
+
+# You can also set custom ticks
+fig_units.ax.set_xticks([-60,-30,unit_locations[0,0],30,60])
+fig_units.ax.set_xticklabels([-60,-30,"unit_0_x",30,60])
+fig_units.ax.set_yticks([-40,-20,0,unit_locations[0,1],40])
+fig_units.ax.set_yticklabels([-40,-20,0,"unit_0_y",40])
+
+# Change the limits of the plot
+fig_units.ax.set_xlim((-30,50))
+fig_units.ax.set_ylim((-50,50))
+
+# And add extra information on the plot
+fig_units.ax.text(unit_locations[6,0], unit_locations[6,1]+5, s="UNIT 6!!!", fontname="Courier")
+
+fig_units
+# -
+
+# Beautiful!!!
+#
+# You can also combine figures into a multi-figure plot. The easiest way to do this is to set up your
+# figure and axes first, then tell `SpikeInterface` which axes it should attach the widget plot to.
+# Here's an example of making a unit summary plot.
+
+# +
+import matplotlib.pyplot as plt
+fig, axs = plt.subplots(ncols=2, nrows=1)
+
+unit_id=8
+si.plot_unit_locations(sorting_analyzer=sorting_analyzer, ax=axs[0])
+si.plot_unit_templates(sorting_analyzer, axes=[axs[1]], unit_ids=[f'{unit_id}'])
+
+axs[0].plot([unit_locations[8,0], unit_locations[8,0]+50], [unit_locations[8,1], unit_locations[8,1]+50])
+axs[0].text(unit_locations[8,0]+52, unit_locations[8,1]+52, s=f"Unit {unit_id}")
+axs[0].set_title("Unit location", fontsize=10)
+
+fig.suptitle(f"Unit {unit_id} summary", fontfamily="Comic Sans MS", fontsize=20)
+
+fig.tight_layout()
+# -
+
+# For more details on what you can do using matplotlib, check out their [extensive documentation](https://matplotlib.org/stable/)

doc/how_to/index.rst

@@ -264,6 +264,7 @@ def __init__(
             "cache_folder": cache_folder,
             "remove_cached": remove_cached,
             "stream": stream,
+            "stream_type": stream_type,
         }