Merge pull request #1426 from NeuralEnsemble/black-formatting

Black formatting

neo/rawio/neuralynxrawio/ncssections.py

@@ -33,6 +33,7 @@
 The challenge addressed by the NcsSectionsFactory of this module is to separate those intended
 gaps from those introduced by a quirk of the hardware, recording software, or file format.
 """
+
 import math
 import numpy as np
 
@@ -87,12 +88,12 @@ class NcsSection:
     _RECORD_SIZE = 512  # nb sample per signal record
 
     def __init__(self, startRec, startTime, endRec, endTime, n_samples):
-        self.startRec = startRec # index of starting record
-        self.startTime = startTime # starttime of first record
-        self.endRec = endRec # index of last record (inclusive)
-        self.endTime = endTime # end time of last record, that is, the end time of the last
-                          # sampling period contained in the last record of the section
-        self.n_samples = n_samples # number of samples in record which are valid
+        self.startRec = startRec  # index of starting record
+        self.startTime = startTime  # starttime of first record
+        self.endRec = endRec  # index of last record (inclusive)
+        self.endTime = endTime  # end time of last record, that is, the end time of the last
+        # sampling period contained in the last record of the section
+        self.n_samples = n_samples  # number of samples in record which are valid
 
     def __eq__(self, other):
         return (
@@ -200,7 +201,7 @@ def _parseGivenActualFrequency(ncsMemMap, ncsSects, chanNum, reqFreq, blkOnePred
         delta_prediction = ((ncsMemMap["nb_valid"][:-1] / ncsSects.sampFreqUsed) * 1e6).astype(np.int64)
         gap_inds = np.flatnonzero((delta - delta_prediction) != 0)
         gap_inds += 1
-        sections_limits = [ 0 ] + gap_inds.tolist() + [len(ncsMemMap)]
+        sections_limits = [0] + gap_inds.tolist() + [len(ncsMemMap)]
 
         for i in range(len(gap_inds) + 1):
             start = sections_limits[i]
@@ -209,9 +210,10 @@ def _parseGivenActualFrequency(ncsMemMap, ncsSects, chanNum, reqFreq, blkOnePred
                 NcsSection(
                     startRec=start,
                     startTime=ncsMemMap["timestamp"][start],
-                    endRec=stop-1,
-                    endTime=ncsMemMap["timestamp"][stop-1] + np.uint64(ncsMemMap["nb_valid"][stop-1] / ncsSects.sampFreqUsed * 1e6),
-                    n_samples=np.sum(ncsMemMap["nb_valid"][start:stop])
+                    endRec=stop - 1,
+                    endTime=ncsMemMap["timestamp"][stop - 1]
+                    + np.uint64(ncsMemMap["nb_valid"][stop - 1] / ncsSects.sampFreqUsed * 1e6),
+                    n_samples=np.sum(ncsMemMap["nb_valid"][start:stop]),
                 )
             )
 
@@ -272,13 +274,14 @@ def _buildGivenActualFrequency(ncsMemMap, actualSampFreq, reqFreq):
             ncsSects.sects.append(curBlock)
             return ncsSects
 
-
         else:
             # otherwise need to scan looking for data gaps
             blkOnePredTime = NcsSectionsFactory.calc_sample_time(actualSampFreq, ts0, nb0)
             # curBlock = NcsSection(0, ts0, -1, -1, -1)
             # ncsSects.sects.append(curBlock)
-            ncsSects = NcsSectionsFactory._parseGivenActualFrequency(ncsMemMap, ncsSects, chanNum, reqFreq, blkOnePredTime)
+            ncsSects = NcsSectionsFactory._parseGivenActualFrequency(
+                ncsMemMap, ncsSects, chanNum, reqFreq, blkOnePredTime
+            )
             return ncsSects
 
     @staticmethod

neo/rawio/neuralynxrawio/neuralynxrawio.py

@@ -319,7 +319,7 @@ def _parse_header(self):
                         internal_ids = []
                     else:
                         data = self._get_file_map(filename)
-                        if data.shape[0] == 0: # empty file
+                        if data.shape[0] == 0:  # empty file
                             self._empty_nse_ntt.append(filename)
                         internal_ids = np.unique(data[["event_id", "ttl_input"]]).tolist()
                     for internal_event_id in internal_ids:

neo/rawio/neuralynxrawio/nlxheader.py

@@ -81,52 +81,53 @@ def _to_bool(txt):
         "bml": dict(
             datetime1_regex=r"## Time Opened: \(m/d/y\): (?P<date>\S+)" r"  At Time: (?P<time>\S+)",
             filename_regex=r"## File Name: (?P<filename>\S+)",
-            datetimeformat="%m/%d/%y %H:%M:%S.%f"
+            datetimeformat="%m/%d/%y %H:%M:%S.%f",
         ),
         # Cheetah after version 1 and before version 5
         "bv5": dict(
             datetime1_regex=r"## Time Opened: \(m/d/y\): (?P<date>\S+)" r"  At Time: (?P<time>\S+)",
             filename_regex=r"## File Name: (?P<filename>\S+)",
-            datetimeformat="%m/%d/%Y %H:%M:%S.%f"
+            datetimeformat="%m/%d/%Y %H:%M:%S.%f",
         ),
         # Cheetah version 5.4.0
         "v5.4.0": dict(
             datetime1_regex=r"## Time Opened \(m/d/y\): (?P<date>\S+)" r"  At Time: (?P<time>\S+)",
             datetime2_regex=r"## Time Closed \(m/d/y\): (?P<date>\S+)" r"  At Time: (?P<time>\S+)",
             filename_regex=r"## File Name: (?P<filename>\S+)",
-            datetimeformat="%m/%d/%Y %H:%M:%S.%f"
+            datetimeformat="%m/%d/%Y %H:%M:%S.%f",
         ),
         # Cheetah version 5.6.0, some range of versions in between
         "v5.6.0": dict(
             datetime1_regex=r"## Time Opened: \(m/d/y\): (?P<date>\S+)" r" At Time: (?P<time>\S+)",
             filename_regex=r"## File Name: (?P<filename>\S+)",
-            datetimeformat="%m/%d/%Y %H:%M:%S.%f"
+            datetimeformat="%m/%d/%Y %H:%M:%S.%f",
         ),
         # Cheetah version 5 before and including v 5.6.4 as well as version 1
         "bv5.6.4": dict(
             datetime1_regex=r"## Time Opened \(m/d/y\): (?P<date>\S+)" r"  \(h:m:s\.ms\) (?P<time>\S+)",
             datetime2_regex=r"## Time Closed \(m/d/y\): (?P<date>\S+)" r"  \(h:m:s\.ms\) (?P<time>\S+)",
             filename_regex=r"## File Name (?P<filename>\S+)",
-            datetimeformat="%m/%d/%Y %H:%M:%S.%f"
+            datetimeformat="%m/%d/%Y %H:%M:%S.%f",
         ),
         "neuraview2": dict(
             datetime1_regex=r"## Date Opened: \(mm/dd/yyy\): (?P<date>\S+)" r" At Time: (?P<time>\S+)",
             datetime2_regex=r"## Date Closed: \(mm/dd/yyy\): (?P<date>\S+)" r" At Time: (?P<time>\S+)",
             filename_regex=r"## File Name: (?P<filename>\S+)",
-            datetimeformat="%m/%d/%Y %H:%M:%S"
+            datetimeformat="%m/%d/%Y %H:%M:%S",
         ),
-        'peg': dict(
-            datetime1_regex=r'-TimeCreated (?P<date>\S+) (?P<time>\S+)',
-            datetime2_regex=r'-TimeClosed (?P<date>\S+) (?P<time>\S+)',
+        "peg": dict(
+            datetime1_regex=r"-TimeCreated (?P<date>\S+) (?P<time>\S+)",
+            datetime2_regex=r"-TimeClosed (?P<date>\S+) (?P<time>\S+)",
             filename_regex=r'-OriginalFileName "?(?P<filename>\S+)"?',
-            datetimeformat=r'%Y/%m/%d %H:%M:%S',
-            datetime2format=r'%Y/%m/%d %H:%M:%S.f'),
+            datetimeformat=r"%Y/%m/%d %H:%M:%S",
+            datetime2format=r"%Y/%m/%d %H:%M:%S.f",
+        ),
         # Cheetah after v 5.6.4 and default for others such as Pegasus
         "def": dict(
             datetime1_regex=r"-TimeCreated (?P<date>\S+) (?P<time>\S+)",
             datetime2_regex=r"-TimeClosed (?P<date>\S+) (?P<time>\S+)",
             filename_regex=r'-OriginalFileName "?(?P<filename>\S+)"?',
-            datetimeformat="%Y/%m/%d %H:%M:%S"
+            datetimeformat="%Y/%m/%d %H:%M:%S",
         ),
     }
 
@@ -144,7 +145,7 @@ def __init__(self, filename, props_only=False):
 
         # must start with 8 # characters
         if not props_only and not txt_header.startswith("########"):
-           ValueError("Neuralynx files must start with 8 # characters.")
+            ValueError("Neuralynx files must start with 8 # characters.")
 
         self.read_properties(filename, txt_header)
 
@@ -163,7 +164,6 @@ def build_with_properties_only(filename):
         """
         res = OrderedDict()
 
-
     def read_properties(self, filename, txt_header):
         """
         Read properties from header and place in OrderedDictionary which this object is.
@@ -272,8 +272,8 @@ def readTimeDate(self, txt_header):
         elif an == "Neuraview":
             hpd = NlxHeader.header_pattern_dicts["neuraview2"]
             av = Version("2")
-        elif an == 'Pegasus':
-            hpd = NlxHeader.header_pattern_dicts['peg']
+        elif an == "Pegasus":
+            hpd = NlxHeader.header_pattern_dicts["peg"]
             av = Version("2")
         else:
             an = "Unknown"
@@ -289,15 +289,16 @@ def readTimeDate(self, txt_header):
             dt1 = sr.groupdict()
             try:  # allow two possible formats for date and time
                 self["recording_opened"] = datetime.datetime.strptime(
-                    dt1["date"] + " " + dt1["time"], hpd["datetimeformat"])
+                    dt1["date"] + " " + dt1["time"], hpd["datetimeformat"]
+                )
             except:
                 try:
                     self["recording_opened"] = datetime.datetime.strptime(
-                        dt1["date"] + " " + dt1["time"], hpd["datetime2format"])
+                        dt1["date"] + " " + dt1["time"], hpd["datetime2format"]
+                    )
                 except:
                     self["recording_opened"] = None
 
-
         # close time, if available
         if "datetime2_regex" in hpd:
             sr = re.search(hpd["datetime2_regex"], txt_header)

neo/test/rawiotest/test_neuralynxrawio.py

@@ -27,7 +27,7 @@ class TestNeuralynxRawIO(
         "neuralynx/Cheetah_v5.5.1/original_data",
         "neuralynx/Cheetah_v5.6.3/original_data",
         "neuralynx/Cheetah_v5.7.4/original_data",
-        "neuralynx/Cheetah_v6.3.2/incomplete_blocks"
+        "neuralynx/Cheetah_v6.3.2/incomplete_blocks",
     ]
 
     def test_scan_ncs_files(self):