Functionality for large datasets.

 - Added several new options to handle data sets with many samples.
 - New options allow to specify to how many samples a dataset should
   be downsampled to, either with or without filtering. The default is
   using no filtering, which leads to much faster computing times.

RSTpicking/RST_Func.py

@@ -20,12 +20,23 @@ import nptdms
 import numpy as np
 from scipy.optimize import least_squares, curve_fit
 from scipy.stats import norm
-from scipy.signal import medfilt
+from scipy.signal import medfilt, resample
 
 
 # %%==============CONVERSION===================================================
 def convert(path, file_in, var):
     """Reads data from source files and returns a dictionary with data"""
+
+    def downsample(y, nsamples, dofilter=True):
+        """ Downsamples a filtered version of the input data. """
+        kernelsize = int((len(y)/nsamples)/2)
+        if dofilter:
+            y_filt = medfilt(y, kernel_size=kernelsize)
+        else:
+            y_filt = y
+        subset = np.linspace(0, len(y)-1, 10000).astype(int)
+        return (y_filt[subset])
+
     # possible inputs and linked helper functions
     file_convert = {'.asc': _readasc,
                     '.dat': _readdat,
@@ -33,6 +44,23 @@ def convert(path, file_in, var):
 
     (root, ext) = os.path.splitext(path+file_in)
     data = file_convert[ext](path, file_in)  # data contains basic content
+    nsamples = int(var['nsamples'])
+
+    if len(data['time']) > nsamples:
+        data['time'] = np.linspace(0, data['time'][-1], nsamples)
+        data['velocity'] = downsample(
+            data['velocity'], nsamples,
+            dofilter=var['downsample_filter']
+        )
+        data['shearforce'] = downsample(
+            data['shearforce'], nsamples,
+            dofilter=var['downsample_filter']
+        )
+        data['normalforce'] = downsample(
+            data['normalforce'], nsamples,
+            dofilter=var['downsample_filter']
+        )
+        print('Data to large... Downsampled to %i samples.' % nsamples)
 
     # Corrections
     data['time'] = data['time']-data['time'][0]

RSTpicking/RST_pick_GUI.py

@@ -3,7 +3,7 @@
 # @Author: M. Rudolf, M. Warsitzka
 # @Date:   2019-02-20 12:00:00
 # @Last Modified by:   M. Rudolf
-# @Last Modified time: 2020-07-09 17:52:48
+# @Last Modified time: 2020-09-23 10:44:14
 
 """
 RST_pick_GUI.py
@@ -485,7 +485,9 @@ class RST_pick_GUI(tk.Tk):
             'stressnoise': 0.025,
             'cellweight': 2185.3,  # weight of shear cell
             'smoothwindow': 5,  # Smoothing Factor for plots
-            'pred_norms': [500, 1000, 2000, 4000, 8000, 16000, 20000]
+            'pred_norms': [500, 1000, 2000, 4000, 8000, 16000, 20000],
+            'nsamples': 10000,  # Maximum number of samples to use
+            'downsample_filter': 0,  # Use downsampling filter or not.
         }
 
         config['units'] = {
@@ -498,7 +500,9 @@ class RST_pick_GUI(tk.Tk):
             'stressnoise': 'Pa',
             'cellweight': 'g',
             'smoothwindow': 'samples',
-            'pred_norms': 'Pa'
+            'pred_norms': 'Pa',
+            'nsamples': 'samples',
+            'downsample_filter': '(0 = No, 1 = Yes)',
         }
         self.path_cfg.set(config['paths']['path_cfg'])
         with open(self.path_cfg.get(), 'w') as f: