save redetected spikes in extra folder

Controller.py

@@ -4,6 +4,7 @@ from DatParser import DatParser
 import numpy as np
 from warnings import warn
 import os
+from redetector import detect_spiketimes
 import matplotlib.pyplot as plt
 
 
@@ -39,7 +40,6 @@ class Controller:
     def save_parameters(self, folder_path):
         header = "trial_index,threshold,min_window,step_size\n"
         for repro in self.thresholds.keys():
-            # TODO change '.' to self.data_path after testing:
             with open(folder_path + "/{}_thresholds.csv".format(repro), "w") as threshold_file:
                 threshold_file.write(header)
                 for i in range(len(self.sorting[repro])):
@@ -56,11 +56,32 @@ class Controller:
 
     def save_redetected_spikes(self, folder_path):
         # TODO save redetected spikes:
-        header = "trial_index,threshold,min_window,step_size\n"
+        redetection_folder = folder_path + "/redetected_spikes/"
+        if not os.path.exists(redetection_folder):
+            os.mkdir(redetection_folder)
+
         for repro in self.thresholds.keys():
-            # TODO change '.' to self.data_path after testing:
-            with open(folder_path + "/{}_thresholds.csv".format(repro), "w") as threshold_file:
-                threshold_file.write(header)
+            for i in range(len(self.sorting[repro])):
+                    if len(self.thresholds[repro][i]) == 0:
+                        continue  # If no params were saved, saving a redetection file makes no sense
+                    else:
+                        # format and write given thresholding parameters
+                        # i is the trial idx
+                        thresh = self.thresholds[repro][i][0]
+                        min_window = self.thresholds[repro][i][1]
+                        step = self.thresholds[repro][i][2]
+
+                        traces, spiketimes, recording_times = self.get_traces_with_spiketimes(repro)
+                        trace = traces[i]
+                        spiketimes = spiketimes[i]
+                        recording_times = recording_times
+                        sampling_interval = self.sampling_interval
+
+                        time = np.arange(len(trace)) * sampling_interval - recording_times[0]
+                        redetect = detect_spiketimes(time, trace, thresh, min_window, step)
+
+                        np.save(redetection_folder + "spikes_repro_{}_trial_{}.npy".format(repro, i), np.array(redetect))
+        print("Redetected spikes saved!")
 
     def get_repros(self):
         return self.parser.get_measured_repros()
@@ -193,4 +214,4 @@ def average_spike_height(spike_train: np.ndarray, v1: np.ndarray, sampling_rate,
 #     spike_values = [v1[i] for i in indices if 0 <= i < len(v1)]
 #     average_height = np.mean(spike_values)
 #
-#     return average_height
+#     return average_height

ReadMe.md

@@ -1,15 +1,15 @@
-# Spike redetector
+# Spike Redetector
 
-###redetection parameters:
+### Redetection Parameters:
 
-- **Threshold**: number of standard deviations between a maximum and a minimum to count as a spike.
-- **Min window size**: The minimum size of a window (as number of indices) in which spikes are detected. The voltage trace is split into parts 
+- ***Threshold***: number of standard deviations between a maximum and a minimum to count as a spike.
+- ***Min window size***: The minimum size of a window (as number of indices) in which spikes are detected. The voltage trace is split into parts 
   if the maximum or minimum of the next part are too different from the current part. 
   This makes the estimation of the STD a lot more stable between trials where the absolute voltage might wander.
-- **step size**: The number of indices that are used in each step while trying to increase the size of the window.
+- ***step size***: The number of indices that are used in each step while trying to increase the size of the window.
 
-### plot controls:
+### Plot Controls:
 
 - Drag and drop with LMB
 
-- zoom control with RMB -> press and hold; up down is zoom on y-axis while left right is zoom on x-axis
+- zoom control with RMB -> press and hold; up down is zoom on y-axis while left right is zoom on x-axis

SpikeRedetectGui.py

@@ -219,7 +219,6 @@ class SpikeRedetectGui(QWidget):
 
     @pyqtSlot()
     def save_threshold_parameters(self):
-        # TODO add question for save_path
         data_path = QFileDialog.getExistingDirectory(self, directory=self.controller.data_path, caption='Select a folder to save the parameters:')
         if data_path is None:
             return

main.py

@@ -1,12 +1,11 @@
 
 import sys
-
 from PyQt5.QtWidgets import QApplication
 
 from SpikeRedetectGui import SpikeRedetectGui
 
 
-test_file = "../neuronModel/data/final_sam/2010-11-08-al-invivo-1"
+test_file = "../neuronModel/data/final/2010-11-08-al-invivo-1"
 sam_file  = "../neuronModel/data/final_sam/2011-10-25-ad-invivo-1"
 # TODO CLI
 

testing.py

@@ -14,6 +14,11 @@ failure_to_read_sam = ["2012-06-27-an-invivo-1", "2012-12-13-ag-invivo-1"]
 
 
 def main():
+
+    test = np.load("redetected_spikes/spikes_repro_BaselineActivity_trial_0.npy")
+    print()
+
+
     for cell in sorted(os.listdir(DATA_FOLDER)):
         if cell in failure_to_read_sam:
             continue
@@ -77,4 +82,4 @@ def test_getting_repros(data_provider: Controller):
 
 
 if __name__ == '__main__':
-    main()
+    main()