plot Spike-contrast synchrony measure

doc/bib/viziphant.bib

@@ -0,0 +1,9 @@
+@article{Ciba18_136,
+  title={Spike-contrast: A novel time scale independent and multivariate measure of spike train synchrony},
+  author={Ciba, M. and Isomura, T. and Jimbo, Y. and Bahmer, A. and Thielemann, C.},
+  year={2018},
+  journal={J. Neurosci. Meth.},
+  volume={293},
+  pages={136--143},
+  doi={10.1016/j.jneumeth.2017.09.008}
+}

doc/conf.py

@@ -37,6 +37,7 @@
     'sphinx.ext.viewcode',
     'sphinx.ext.mathjax',
     'matplotlib.sphinxext.plot_directive',
+    'sphinxcontrib.bibtex',
     'numpydoc',
     'sphinx_tabs.tabs',
     'sphinx.builders.linkcheck',

doc/modules.rst

@@ -15,3 +15,13 @@ Function Reference by Module
 .. automodule:: viziphant.gpfa
 
 .. automodule:: viziphant.unitary_event_analysis
+
+.. automodule:: viziphant.spike_train_synchrony
+
+
+References
+----------
+
+.. bibliography:: bib/viziphant.bib
+   :style: unsrt
+   :all:

requirements/requirements-docs.txt

@@ -1,3 +1,4 @@
-numpydoc>=0.9.2
-sphinx>=2.4.2
+numpydoc>=1.1.0
+sphinx>=3.3.0
 sphinx-tabs>=1.1.13
+sphinxcontrib-bibtex>=1.0.0

requirements/requirements.txt

@@ -1,5 +1,5 @@
 neo>=0.9.0
-elephant[extras]>=0.9.0
+elephant @ git+https://github.com/NeuralEnsemble/elephant.git#egg=elephant[extras]
 numpy>=1.18.1
 quantities>=0.12.1
 six>=1.10.0

viziphant/__init__.py

@@ -7,7 +7,7 @@
 # License: Modified BSD, see LICENSE.txt for details.
 
 from . import (events, gpfa, rasterplot, spade, spike_train_correlation,
-               statistics, unitary_event_analysis)
+               spike_train_synchrony, statistics, unitary_event_analysis)
 
 
 def _get_version():

viziphant/spike_train_synchrony.py

@@ -0,0 +1,96 @@
+"""
+Spike train synchrony plots
+---------------------------
+
+.. autosummary::
+    :toctree: toctree/spike_train_synchrony
+
+    plot_spike_contrast
+
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from viziphant.rasterplot import rasterplot
+
+
+def plot_spike_contrast(trace, spiketrains=None, title=None, lw=1.0,
+                        xscale='log', **kwargs):
+    """
+    Plot Spike-contrast synchrony measure :cite:`Ciba18_136`.
+
+    Parameters
+    ----------
+    trace : SpikeContrastTrace
+        The trace output from
+        :func:`elephant.spike_train_synchrony.spike_contrast` function.
+    spiketrains : list of neo.SpikeTrain or None
+        Input spike trains, optional. If provided, the raster plot will be
+        shown at the bottom.
+        Default: None
+    title : str or None.
+        The plot title. If None, an automatic description will be set.
+        Default: None
+    lw : float, optional
+        The curves line width.
+        Default: 1.0
+    xscale : str, optional
+        X axis scale.
+        Default: 'log'
+    **kwargs
+        Additional arguments, passed in :func:`viziphant.rasterplot.rasterplot`
+
+    Returns
+    -------
+    axes : matplotlib.Axes.axes
+
+    Examples
+    --------
+    Spike-contrast synchrony of homogenous Poisson processes.
+
+    .. plot::
+        :include-source:
+
+        import numpy as np
+        import quantities as pq
+        from elephant.spike_train_generation import homogeneous_poisson_process
+        from elephant.spike_train_synchrony import spike_contrast
+        import viziphant
+        np.random.seed(24)
+        spiketrains = [homogeneous_poisson_process(rate=20 * pq.Hz,
+                       t_stop=10 * pq.s) for _ in range(10)]
+        synchrony, trace = spike_contrast(spiketrains, return_trace=True)
+        viziphant.spike_train_synchrony.plot_spike_contrast(trace,
+             spiketrains=spiketrains, c='gray', s=1)
+        plt.show()
+
+    """
+    nrows = 2 if spiketrains is not None else 1
+    fig, axes = plt.subplots(nrows=nrows)
+    axes = np.atleast_1d(axes)
+    units = trace.bin_size.units
+    bin_sizes = trace.bin_size.magnitude
+    axes[0].plot(bin_sizes, trace.contrast, lw=lw, label=r'Contrast($\Delta$)',
+                 linestyle='dashed', color='limegreen')
+    axes[0].plot(bin_sizes, trace.active_spiketrains, lw=lw,
+                 label=r'ActiveST($\Delta$)',
+                 linestyle='dashdot', color='dodgerblue')
+    axes[0].plot(bin_sizes, trace.synchrony, lw=lw,
+                 label=r'Synchrony($\Delta$)', color='black')
+    bin_id_max = np.argmax(trace.synchrony)
+    synchrony_loc = bin_sizes[bin_id_max], trace.synchrony[bin_id_max]
+    axes[0].scatter(*synchrony_loc, s=20, c='red', marker='x')
+    axes[0].annotate('S', synchrony_loc, color='red', va='bottom', ha='left')
+    axes[0].legend()
+    axes[0].set_xscale(xscale)
+    axes[0].set_xlabel(fr"Bin size $\Delta$ ({units.dimensionality})")
+    if title is None:
+        title = "Spike-contrast synchrony measure"
+    axes[0].set_title(title)
+    if spiketrains is not None:
+        rasterplot(spiketrains, axes=axes[1], **kwargs)
+        axes[1].set_ylabel('neuron')
+        axes[1].yaxis.set_label_coords(0, 0.5)
+    plt.tight_layout()
+    return axes