DRG tests for raw text input

phys2bids/cli/run.py

@@ -1,7 +1,6 @@
 # -*- coding: utf-8 -*-
 """Parser for phys2bids."""
 
-
 import argparse
 
 from phys2bids import __version__
@@ -134,6 +133,27 @@ def _get_parser():
         "or just one TR if it is consistent throughout the session.",
         default=None,
     )
+    optional.add_argument(
+        "-freq",
+        "--frequency",
+        dest="freq",
+        type=float,
+        help="Frequency of input data. Now specifically for GE gep files. "
+        "Units are Hertz, Hz or samples/sec "
+        "GE defaults to PPG of 100Hz, Resp at 25Hz and ECG at 1000Hz ",
+        default=None,
+    )
+
+    optional.add_argument(
+        "-pt",
+        "--pre_time",
+        dest="pretime",
+        type=float,
+        help="Pre-run time offset of input data. Now specifically for GE gep files. "
+        "Time offset in seconds. Default for GE is 30 seconds. ",
+        default=30.0,
+    )
+
     optional.add_argument(
         "-thr",
         "--threshold",

phys2bids/io.py

@@ -3,6 +3,7 @@
 """phys2bids interfaces for loading extension files."""
 
 import logging
+import pdb
 import warnings
 from copy import deepcopy
 from itertools import groupby
@@ -200,19 +201,22 @@ def read_header_and_channels(filename):
     """
     header = []
     # Read in the header until it's numbers
+
     with open(filename, "r") as f:
         for n, line in enumerate(f):
             line = line.rstrip("\n").split("\t")
             if line[-1] == "":
                 line.remove("")
             try:
-                float(line[0])
+                list(map(float, line[0].split(" ")))
+                # float(line[0])
                 break
             except ValueError:
                 header.append(line)
                 continue
+
     # Read in the rest paying attention to possible differences
-    if "Interval=" in header[0]:
+    if "Interval=" in str(header[0]):
         # Not specifying delimiters will ignore comments
         channel_list = np.genfromtxt(filename, skip_header=n)
     elif "acq" in header[0][0]:
@@ -261,29 +265,31 @@ def extract_header_items(header):
         If Labchart headers cannot be processed
         If files are not in acq or txt format
     """
+
     # check header is not empty and detect if it is in labchart or Acqknoledge format
     if len(header) == 0:
         raise NotImplementedError("Files without header are not supported yet")
-    elif "Interval=" in header[0]:
+    elif "Interval=" in header[0][0]:
         LGR.info("phys2bids detected that your file is in Labchart format")
 
         interval = None
         orig_names = None
         range_list = None
         for line in header:
-            if "Interval=" in line:
-                interval = line[1].split(" ")
-            if "ChannelTitle=" in line:
-                orig_names = line[1:]
-            if "Range=" in line:
-                range_list = line[1:]
+            ll = line[0]
+            if "Interval=" in ll:
+                interval = ll.split()[1:]
+            if "ChannelTitle=" in ll:
+                orig_names = ll.split()[1:]
+            if "Range=" in ll:
+                range_list = ll.split()[1:]
 
         if None in [interval, orig_names, range_list]:
             raise NotImplementedError(OPEN_ISSUE)
 
         orig_units = []
         for item in range_list:
-            orig_units.append(item.split(" ")[1])
+            orig_units.append(item.split()[0])
 
     elif "acq" in header[0][0]:
         LGR.info("phys2bids detected that your file is in AcqKnowledge format")
@@ -450,7 +456,7 @@ def load_mat(filename, chtrig=0):
         return BlueprintInput(timeseries, freq, names, units, chtrig)
 
 
-def load_gep(filename):
+def load_gep(filename, inifreq=None, pretime=30.0):
     """
     Populate object phys_input from GE physiological files.
 
@@ -491,11 +497,15 @@ def load_gep(filename):
 
     # Initiate lists of column names and units with time and trigger
     names = ["time", "trigger"]
-    units = ["s", "mV"]  # Assuming recording units are mV...
+    units = ["s", "mV", "au"]  # Assuming recording units are mV...
+
+    # start debugging here
+    # pdb.set_trace()
 
     # Add column for file given by user
     if "PPGData" in filename:
         freq = [100, 100, 100]
+        #    freq = [50, 50, 50]
         names.append("cardiac")
     elif "RESPData" in filename:
         freq = [25, 25, 25]
@@ -504,13 +514,18 @@ def load_gep(filename):
         freq = [1000, 1000, 1000]
         names.append("cardiac")
 
+    # if frequency specified in call, use that instead
+    if inifreq:
+        freq = [inifreq, inifreq, inifreq]
+
     # Load in user file data
     data = [np.loadtxt(filename)]
 
     # Calculate time in seconds for first input (starts from -30s)
     interval = 1 / freq[0]
     duration = data[0].shape[0] * interval
-    t_ch = np.ogrid[-30 : duration - 30 : interval]
+    # t_ch = np.ogrid[-30 : duration - 30 : interval]
+    t_ch = np.ogrid[0:duration:interval]
 
     # Find and add additional data files
     filename = Path(filename)
@@ -519,20 +534,33 @@ def load_gep(filename):
     if not len(fnames) == 0:
         for fname in fnames:
             if "PPGData" in fname:
-                freq.append(100)
+                if inifreq:
+                    freq.append(inifreq)
+                else:
+                    freq.append(100)
                 names.append("cardiac")
                 data.append(np.loadtxt(fname))
             elif "RESPData" in fname:
-                freq.append(25)
+                if inifreq:
+                    freq.append(inifreq)
+                else:
+                    freq.append(25)
                 names.append("respiratory")
                 data.append(np.loadtxt(fname))
             elif "ECGData" in fname:
-                freq.append(1000)
+                if inifreq:
+                    freq.append(inifreq)
+                else:
+                    freq.append(1000)
                 names.append("cardiac")
                 data.append(np.loadtxt(fname))
 
     # Create trigger channel
-    trigger = np.hstack((np.zeros(int(30 / interval)), np.ones(int((duration - 30) / interval))))
+    trigger = np.hstack(
+        (np.zeros(int(pretime / interval)), np.ones(int((duration - pretime) / interval)))
+    )
+    # trigger = np.hstack((np.zeros(int(30 / interval)), np.ones(int((duration - 30) / interval))))
+    # trigger = np.hstack( np.ones(int((duration) / interval)))
 
     # Create final list of timeseries
     timeseries = [t_ch, trigger]

phys2bids/phys2bids.py

@@ -147,6 +147,8 @@ def phys2bids(
     yml="",
     debug=False,
     quiet=False,
+    freq=None,
+    pretime=None,
 ):
     """
     Run main workflow of phys2bids.
@@ -259,7 +261,7 @@ def phys2bids(
     elif ftype == "gep":
         from phys2bids.io import load_gep
 
-        phys_in = load_gep(infile)
+        phys_in = load_gep(infile, inifreq=freq, pretime=pretime)
 
     LGR.info("Checking that units of measure are BIDS compatible")
     for index, unit in enumerate(phys_in.units):

phys2bids/physio_obj.py

@@ -518,13 +518,16 @@ def check_trigger_amount(self, thr=None, num_timepoints_expected=0, tr=0):
         if thr is None:
             # If trigger channels are binary
             # (i.e., "on" is a higher value and "off" is a lower value)
-            # and each "on" and "off" are each always approzimately the same value
+            # and each "on" and "off" are each always approximately the same value
             # then any value above the mean is "on" and every value below the mean
             # is "off".
             thr = np.mean(trigger)
             flag = 1
-        timepoints = trigger > thr
-        num_timepoints_found = np.count_nonzero(np.ediff1d(timepoints.astype(np.int8)) > 0)
+        # drg - modified to >= rather than >
+        timepoints = trigger >= thr
+        # drg - also removed threshold difference that looks at consecutive diffs
+        # num_timepoints_found = np.count_nonzero(np.ediff1d(timepoints.astype(np.int8)) > 0)
+        num_timepoints_found = np.count_nonzero(timepoints.astype(np.int8) > 0)
         if flag == 1:
             LGR.info(
                 f"The number of timepoints according to the std_thr method "