cleaned up for new data

modelsusceptlown.py

@@ -3,7 +3,7 @@ import matplotlib.pyplot as plt
 from scipy.stats import pearsonr, linregress, gaussian_kde
 from thunderlab.tabledata import TableData
 from pathlib import Path
-from spectral import whitenoise, diag_projection, peakedness
+from spectral import whitenoise, diag_projection, peak_size
 from plotstyle import plot_style, labels_params, significance_str
 
 
@@ -64,8 +64,8 @@ def plot_chi2(ax, s, data_file, rate):
     ax.set_xlabel('$f_1$', 'Hz')
     ax.set_ylabel('$f_2$', 'Hz')
     dfreqs, diag = diag_projection(freqs, chi2, 2*fcutoff)
-    nli, nlif = peakedness(dfreqs, diag, rate, median=False)
-    ax.text(0.95, 0.88, f'SI($r$)={nli:.1f}', ha='right', zorder=50,
+    sinorm, sirel, sif = peak_size(dfreqs, diag, rate, median=False)
+    ax.text(0.95, 0.88, f'SI($r$)={sinorm:.1f}', ha='right', zorder=50,
             color='white', fontsize='medium', transform=ax.transAxes)
     cax = ax.inset_axes([1.04, 0, 0.05, 1])
     cax.set_spines_outward('lrbt', 0)