Merge pull request #108 from Hananel-Hazan/old-hassaan

Reverting to old plotting spikes function

bindsnet/analysis/plotting.py

@@ -59,6 +59,92 @@ def plot_spikes(network: Optional[Network] = None, spikes: Optional[Dict[str, to
                 n_neurons: Optional[Dict[str, Tuple[int, int]]] = None, ims=None, axes: List[AxesImage] = None,
                 figsize: Tuple[float, float] = (8.0, 4.5)) -> Tuple[List[AxesImage], List[Axes]]:
     # language=rst
+    """
+    Plot spikes for any group(s) of neurons.
+
+    :param spikes: Mapping from layer names to spiking data.
+    :param time: Plot spiking activity of neurons in the given time range. Default is entire simulation time.
+    :param n_neurons: Plot spiking activity of neurons in the given range of neurons. Default is all neurons.
+    :param ims: Used for re-drawing the plots.
+    :param axes: Used for re-drawing the plots.
+    :param figsize: Horizontal, vertical figure size in inches.
+    :return: ``ims, axes``: Used for re-drawing the plots.
+    """
+
+    n_subplots = len(spikes.keys())
+    spikes = {k : v.view(-1, v.size(-1)) for (k, v) in spikes.items()}
+
+    if time is not None:
+        assert len(time) == 2, 'Need (start, stop) values for time argument'
+        assert time[0] < time[1], 'Need start < stop in time argument'
+    else:
+        # Set it for entire duration
+        for key in spikes.keys():
+            time = (0, spikes[key].shape[1])
+            break
+
+    if len(n_neurons.keys()) != 0:
+        assert len(n_neurons.keys()) <= n_subplots, \
+            'n_neurons argument needs fewer entries than n_subplots'
+        assert all(key in spikes.keys() for key in n_neurons.keys()), \
+            'n_neurons keys must be subset of spikes keys'
+
+    # Use all neurons if no argument provided.
+    for key, val in spikes.items():
+        if key not in n_neurons.keys():
+            n_neurons[key] = (0, val.shape[0])
+
+    if not ims:
+        fig, axes = plt.subplots(n_subplots, 1, figsize=figsize)
+        ims = []
+
+        if n_subplots == 1:
+            for datum in spikes.items():
+                ims.append(axes.imshow(spikes[datum[0]][n_neurons[datum[0]][0]:n_neurons[datum[0]][1],
+                                       time[0]:time[1]],
+                                       cmap='binary'))
+
+                args = (datum[0], n_neurons[datum[0]][0], n_neurons[datum[0]][1], time[0], time[1])
+                plt.title('%s spikes for neurons (%d - %d) from t = %d to %d ' % args)
+                plt.xlabel('Simulation time'); plt.ylabel('Neuron index')
+                axes.set_aspect('auto')
+        else:
+            for i, datum in enumerate(spikes.items()):
+                ims.append(axes[i].imshow(datum[1][n_neurons[datum[0]][0]:n_neurons[datum[0]][1],
+                                          time[0]:time[1]],
+                                          cmap='binary'))
+
+                args = (datum[0], n_neurons[datum[0]][0], n_neurons[datum[0]][1], time[0], time[1])
+                axes[i].set_title('%s spikes for neurons (%d - %d) from t = %d to %d ' % args)
+
+            for ax in axes:
+                ax.set_aspect('auto')
+
+        plt.setp(axes, xticks=[], yticks=[], xlabel='Simulation time', ylabel='Neuron index')
+        plt.tight_layout()
+
+    else:
+        if n_subplots == 1:
+            for datum in spikes.items():
+                ims[0].set_data(datum[1][n_neurons[datum[0]][0]:n_neurons[datum[0]][1], time[0]:time[1]])
+                ims[0].autoscale()
+
+                args = (datum[0], n_neurons[datum[0]][0], n_neurons[datum[0]][1], time[0], time[1])
+                axes.set_title('%s spikes for neurons (%d - %d) from t = %d to %d ' % args)
+
+        else:
+            for i, datum in enumerate(spikes.items()):
+                ims[i].set_data(datum[1][n_neurons[datum[0]][0]:n_neurons[datum[0]][1], time[0]:time[1]])
+                ims[i].autoscale()
+
+                args = (datum[0], n_neurons[datum[0]][0], n_neurons[datum[0]][1], time[0], time[1])
+                axes[i].set_title('%s spikes for neurons (%d - %d) from t = %d to %d ' % args)
+
+    plt.draw()
+    return ims, axes
+
+
+def plot_spikes_new(network=None, spikes=None, layer_to_monitor={}, layers=[], time={}, n_neurons={}, ims=None, axes=None, figsize=(8, 4.5)):
     """
     Plot spikes for any group(s) of neurons. Default behavior will plot everything.
 
@@ -78,6 +164,8 @@ def plot_spikes(network: Optional[Network] = None, spikes: Optional[Dict[str, to
     if layer_to_monitor is None:
         layer_to_monitor = {}
 
+    assert network is not None or spikes is not None, 'No plotting information'
+
     if time is None:
         time = {}