add fit_(function)(x,y) type functions

helperFunctions.py

@@ -1,6 +1,30 @@
 import numpy as np
 from warnings import warn
 from thunderfish.eventdetection import detect_peaks, threshold_crossing_times, threshold_crossings
+from scipy.optimize import curve_fit
+import functions as fu
+
+
+def fit_clipped_line(x, y):
+    popt, pcov = curve_fit(fu.clipped_line, x, y)
+
+    return popt
+
+
+def fit_boltzmann(x, y):
+    max_f0 = float(max(y))
+    min_f0 = 0.1  # float(min(self.f_zeros))
+    mean_int = float(np.mean(x))
+
+    total_increase = max_f0 - min_f0
+    total_change_int = max(x) - min(x)
+    start_k = float((total_increase / total_change_int * 4) / max_f0)
+
+    popt, pcov = curve_fit(fu.full_boltzmann, x, y,
+                           p0=(max_f0, min_f0, start_k, mean_int),
+                           maxfev=10000, bounds=([0, 0, -np.inf, -np.inf], [np.inf, np.inf, np.inf, np.inf]))
+
+    return popt
 
 
 def merge_similar_intensities(intensities, spiketimes, trans_amplitudes):
@@ -437,7 +461,6 @@ def detect_f_infinity_in_freq_trace(time, frequency, stimulus_start, stimulus_du
 
     start_idx = int((stimulus_end_time - length - buffer) / sampling_interval)
     end_idx = int((stimulus_end_time - buffer) / sampling_interval)
-
     return np.mean(frequency[start_idx:end_idx])