parsing of stimuli.dat file

util.py

@@ -1,6 +1,7 @@
 from functools import reduce
 import numpy as np
 import nixio as nix
+import re
 import os
 import glob
 import datetime as dt
@@ -31,6 +32,104 @@ def read_info_file(file_name):
     return root
 
 
+def parse_metadata_line(line):
+    if not line.startswith("#"):
+        return None, None
+
+    line = line.strip("#").strip()
+    parts = line.split(":")
+    if len(parts) == 0:
+        return None, None
+    if len(parts) == 1 or len(parts[-1].strip()) == 0:
+        return parts[0].strip(), None
+    else:
+        return parts[0].strip(), parts[-1].strip()
+
+
+def has_signal(line, col_names):
+    """
+    Checks whether a signal/stimulus was given in the line.
+    :param line: the current line of the data table
+    :param col_names: The names of the table header columns
+    :return: whether or not any of the signal entries is not empty ("-")
+    """
+    values = line.split()
+    for i, n in enumerate(col_names):
+        if n.lower() == "signal" and i < len(values):
+            if len(values[i].strip()) > 0 and values[i].strip()[0] != "-":
+                return True
+            else:
+                print(i, values[i])
+    return False
+
+
+def parse_table(lines, start_index):
+    """
+
+    :param lines:
+    :param start_index:
+    :return:
+    """
+    data_indices = {}
+    stim_count = 0
+    names = re.split(r'\s{2,}', lines[start_index + 3][1:].strip())
+    while start_index < len(lines):
+        l = lines[start_index].strip()
+        if l.startswith("#"):  # ignore
+            start_index += 1
+        elif len(l) > 0:
+            if stim_count == 0 and (has_signal(l, names)):
+                data_indices[stim_count] = l.split()[0]
+                stim_count += 1
+            elif stim_count > 0:
+                data_indices[stim_count] = l.split()[0]
+                stim_count += 1
+            start_index += 1
+        else:
+            start_index += 1
+            break
+    return data_indices, start_index
+
+
+def read_stimuli_file(file_name):
+    repro_settings = []
+    settings = {}
+    with open(file_name, 'r') as f:
+        lines = f.readlines()
+        index = 0
+        current_section = None
+        current_section_name = ""
+        while index < len(lines):
+            l = lines[index].strip()
+            if len(l) == 0:
+                index += 1
+            elif l.startswith("#") and "key" not in l.lower():
+                name, value = parse_metadata_line(l)
+                if not name:
+                    continue
+                if name and not value:
+                    if current_section:
+                        settings[current_section_name] = current_section.copy()
+
+                    current_section = {}
+                    current_section_name = name
+                else:
+                    current_section[name] = value
+                index += 1
+            elif l.lower().startswith("#key"):  # table data coming
+                data, index = parse_table(lines, index)
+                settings["stim_data"]  = data
+                # we are done with this repro run
+                settings[current_section_name] = current_section.copy()
+                repro_settings.append(settings.copy())
+                current_section = None
+                settings = {}
+            else:
+                # data lines, ignore them here
+                index += 1
+    return repro_settings
+
+
 def find_key_recursive(dictionary, key, path=[]):
     assert(isinstance(dictionary, dict))
     if key in dictionary.keys():
@@ -155,6 +254,7 @@ def mtag_settings_to_yaml(mtag, pos_index):
 
 
 if __name__ == "__main__":
+    """
     nix_file = "../../science/high_freq_chirps/data/2018-11-09-aa-invivo-1/2018-11-09-aa-invivo-1.nix"
     f = nix.File.open(nix_file, nix.FileMode.ReadOnly)
     b = f.blocks[0]
@@ -164,4 +264,7 @@ if __name__ == "__main__":
     print(nix_metadata_to_yaml(b.metadata))
     embed()
     f.close()
-
+    """
+    dataset = "/Users/jan/zwischenlager/2012-03-23-ad"
+    settings = read_stimuli_file(os.path.join(dataset, "stimuli.dat"))
+    embed()