fixed VST fitting

Fixed weird behaviour of bootstrap fitting for VST tests
Switched to scipy.optimize.curve_fit for this case.

RSTpicking/RST_Func.py

@@ -18,7 +18,8 @@ import matplotlib.gridspec as gridspec
 import matplotlib.pyplot as plt
 import nptdms
 import numpy as np
-from scipy import optimize, stats
+from scipy.optimize import least_squares, curve_fit
+from scipy.stats import norm
 from scipy.signal import medfilt
 
 
@@ -395,12 +396,12 @@ def fitfric(x, a, b):
 # %%=====================VELOCITY STEPPING ANALYSIS============================
 def vst_analysis(data):
     mu_app = data['shearstress']/data['normalstress']  # Apparent friction
-    pfit, perr = fit_bootstrap(
-        [-.1, .5],
+    pfit, pcov = curve_fit(
+        fitfric,
         np.log10(data['velocity']),
-        mu_app,
-        function=fitfric
+        mu_app
     )
+    perr = 2*np.sqrt(np.diag(pcov))
     name_fit = (
         r'y = ({:.4f}$\pm${:.5f})log10(x) +' +
         '\n\t\t' +
@@ -434,7 +435,7 @@ def fit_bootstrap(p0, datax, datay, function=None,
         return function(x, *p) - y
 
     # Fit first time
-    pfit, perr = optimize.leastsq(errfunc,
+    pfit, perr = leastsq(errfunc,
                                   p0,
                                   args=(datax, datay),
                                   full_output=0)
@@ -453,7 +454,7 @@ def fit_bootstrap(p0, datax, datay, function=None,
         randomdataY = datay + randomDelta
 
         randomfit, randomcov = \
-            optimize.leastsq(errfunc, p0, args=(datax, randomdataY),
+            leastsq(errfunc, p0, args=(datax, randomdataY),
                              full_output=0)
 
         ps.append(randomfit)
@@ -545,10 +546,10 @@ def plothist(path, name, strength, data_mut):
                       color='royalblue',
                       edgecolor='black')
         lnspc = np.linspace(np.nanmin(coef), np.nanmax(coef), len(coef))
-        histfit_coef = stats.norm.pdf(
+        histfit_coef = norm.pdf(
                        lnspc,
-                       stats.norm.fit(coef[~np.isnan(coef)])[0],
-                       stats.norm.fit(coef[~np.isnan(coef)])[1])
+                       norm.fit(coef[~np.isnan(coef)])[0],
+                       norm.fit(coef[~np.isnan(coef)])[1])
         axrow[0].plot(lnspc, histfit_coef,
                       'r--',
                       linewidth=2,
@@ -557,10 +558,10 @@ def plothist(path, name, strength, data_mut):
         axrow[0].set_xlabel('Friction coefficient $\\mu$')
         axrow[0].set_ylabel('Counts')
         text = 'Mean: ' + \
-            str(round(stats.norm.fit(coef[~np.isnan(coef)])[0], 3)) + \
+            str(round(norm.fit(coef[~np.isnan(coef)])[0], 3)) + \
             '\n' + \
             'Std.: ' + \
-            str(round(stats.norm.fit(coef[~np.isnan(coef)])[1], 3)) + \
+            str(round(norm.fit(coef[~np.isnan(coef)])[1], 3)) + \
             '\n' + \
             ' (' + \
             str(coef[~np.isnan(coef)].size) + \
@@ -575,21 +576,21 @@ def plothist(path, name, strength, data_mut):
                       density=True,
                       color='royalblue',
                       edgecolor='black')
-        statscoh = stats.norm.fit(coh[~np.isnan(coh)])
+        statscoh = norm.fit(coh[~np.isnan(coh)])
         lnspc = np.linspace(np.nanmin(coh), np.nanmax(coh), len(coh))
-        histfit_coh = stats.norm.pdf(
+        histfit_coh = norm.pdf(
                       lnspc,
-                      stats.norm.fit(coh[~np.isnan(coh)])[0],
-                      stats.norm.fit(coh[~np.isnan(coh)])[1])
+                      norm.fit(coh[~np.isnan(coh)])[0],
+                      norm.fit(coh[~np.isnan(coh)])[1])
         axrow[1].plot(lnspc, histfit_coh, 'r--', linewidth=2)
         axrow[1].set_title(tit_C)
         axrow[1].set_xlabel('Cohesion $C$ [Pa]')
         axrow[1].set_ylabel('Counts')
         text = 'Mean: ' + \
-            str(round(stats.norm.fit(coh[~np.isnan(coh)])[0], 2)) + \
+            str(round(norm.fit(coh[~np.isnan(coh)])[0], 2)) + \
             '\n' + \
             'Std.: ' + \
-            str(round(stats.norm.fit(coh[~np.isnan(coh)])[1], 2)) + \
+            str(round(norm.fit(coh[~np.isnan(coh)])[1], 2)) + \
             '\n' + \
             ' (' + \
             str(coh[~np.isnan(coh)].size) + \