updated data and figures to new analysis with the right units

noisesplit.py

@@ -120,13 +120,13 @@ def plot_chi2_data(ax, s, cell_name, run):
     eodf = float(data['eodf'])
     ratebase = float(data['ratebase/Hz'])
     cvbase = float(data['cvbase'])
-    data_file = data_path / f'{cell_name}-spectral-all-s{run:02d}.npz'
+    data_file = data_path / f'{cell_name}-spectral-100-s{run:02d}.npz'
     data = np.load(data_file)
-    nsegs = data['n']
+    nsegs = data['nsegs']
     fcutoff = data['fcutoff']
     nfft = data['nfft']
     deltat = data['deltat']
-    alpha = data['alpha']
+    alpha = data['contrast']
     freqs = data['freqs']
     pss = data['pss']
     prss = data['prss']
@@ -135,7 +135,7 @@ def plot_chi2_data(ax, s, cell_name, run):
     print()
     ax.text(1, 1.1, f'$N={nsegs}$',
             ha='right', transform=ax.transAxes)
-    plot_chi2(ax, s, freqs, chi2, fcutoff, ratebase)
+    plot_chi2(ax, s, freqs, chi2, fcutoff, ratebase, 15)
     return alpha, ratebase, eodf
 
     
@@ -216,8 +216,8 @@ if __name__ == '__main__':
     wtime = np.arange(len(wnoise))*wdt
                  
     s = plot_style()
-    fig, axs = plt.subplots(4, 4, cmsize=(s.plot_width, 0.83*s.plot_width),
-                            width_ratios=[1, 0, 1, 1, 0.15, 1])
+    fig, axs = plt.subplots(4, 4, cmsize=(s.plot_width, 0.85*s.plot_width),
+                            width_ratios=[1, 0, 1, 1, 0.15, 0.9])
     fig.subplots_adjust(leftm=8, rightm=1.5, topm=3.5, bottomm=4,
                         wspace=0.25, hspace=0.6)
     axs[0, 2].set_visible(False)