gin commit from platypus

Modified files: 5

code/analyses/heterogeneous_populations.py

@@ -74,7 +74,7 @@ def mutual_info_heterogeneous_population(df, data_location, stim_location, popul
     Parameters
     ----------
     df : pandas.DataFrame
-        The DataFrame holding information about the white noise dirven responses recorded in the neurons.
+        The DataFrame holding information about the white noise driven responses recorded in the neurons.
     data_location : _type_
         The folder containing the raw data.
     stim_location : _type_

code/plots/lif_results.py

@@ -168,7 +168,7 @@ def lif_simulations(args):
         if i < 1:
             plot_info_per_band(axes[0], axes[1], axes[2], pop_size, info_no_delay, info_slow, info_squid, info_efish, colors=colors, ls=line_styles[i], labels=lbls)
         else:
-            plot_info_per_band(axes[0], axes[1], axes[2], pop_size, None, info_slow, info_squid, info_efish, colors=colors, ls=line_styles[i], labels=lbls)
+            plot_info_per_band(axes[0], axes[1], axes[2], pop_size, info_no_delay, info_slow, info_squid, info_efish, colors=colors, ls=line_styles[i], labels=lbls)
 
     for i, a in enumerate(axes):
         pimp_lif_sim_axes(a, i == 0, i==1)

code/plots/property_correlations.py

@@ -367,7 +367,7 @@ def layout_figure():
     driven_axes = list(range(12))
     baseline_axes = list(range(12))
 
-    fig = plt.figure(figsize=(4.3, 5.0))
+    fig = plt.figure(figsize=(5.7, 5.0))
     subfigs = fig.subfigures(1, 2, wspace=0.07)
     gr = gridspec.GridSpec(25, 2, width_ratios=[3, 1], wspace=0.0)
 

code/util.py

@@ -340,11 +340,11 @@ def mutual_info(spike_responses, artificial_delay, inversion_needed, stimulus, f
     stimulus : np.ndarray
         The stimulus waveform.
     freq_bin_edges : list of float
-        The edges of the frequency bands to be analysed.
+        The edges of the frequency bands to be analyzed.
     kernel_sigma : float, optional
         Standard deviation of the Gaussian kernel used for firing rate estimation, by default 0.00125
-    delay_type : DealyType, optional
-        Type of destribution of the delays, by default DelayType.Equal
+    delay_type : DelayType, optional
+        Type of distribution of the delays, by default DelayType.Equal
     stepsize : float, optional
         Temporal stepsize of the stimulus trace, by default 1./20000
     trial_duration : float, optional

plot_figures.py

@@ -9,6 +9,8 @@ from code.plots.info_surface import command_line_parser as infosurface_parser
 from code.plots.supp_figure4 import command_line_parser as supfig4_parser
 from code.plots.supp_figure5 import command_line_parser as supfig5_parser
 from code.plots.intro_figure import command_line_parser as introfig_parser
+from code.plots.populations_method import command_line_parser as popmethods_parser
+
 
 def create_parser():
     parser = argparse.ArgumentParser(description="Tool for plotting figures of the Hladnik & Grewe population coding project.")
@@ -26,7 +28,7 @@ def create_parser():
 
     supfig4_parser(subparsers)
     supfig5_parser(subparsers)
-
+    popmethods_parser(subparsers)
     return parser