def __init__(self, file: str = "", *, dir: str = ""):
"""
Args:
file: name of hdf5 file
"""
self.filepath = DPath.from_path(file).prepend_path(
DPath.from_path(dir, dir=True))
def __init__(self, file: str = "", dir: str = "", format: str = "csv"):
"""
Args:
file: name of file to which the dataframe is stored
(in native pandas pickle format), if it is None the dataframe is returned by apply
method as main result (i.e operator is final consumer in pipeline)
"""
self.filepath = DPath.from_path(file).prepend_path(
DPath.from_path(dir, dir=True))
assert format in ["csv", "xlsx"], "Unsupported format"
self.format = format
def __init__(self, filename: str, *, dir: str = "", shortname = None, channels = None):
self._filepath = DPath.from_path(filename).prepend_path(DPath.from_path(dir, dir=True))
with open(str(self._filepath), "rt", encoding="utf-16le") as f:
longline = None
cline = False
data = defaultdict(list)
gsize = 0
channel = 0
for line in f:
line = line.rstrip()
if cline:
longline += line.rstrip("/")
else:
longline = line.rstrip("/")
if line.endswith("/"):
longline += ","
cline = True
continue
else:
cline = False
m = match(r"Sampling Frequency\(kHz\)=(\d+,\d+)", longline)
if m:
self.fs = 1000 * float(m.group(1).replace(",","."))
continue
m = match(r"Channel\s+Number=(\d+)", longline)
if m:
channel = int(m.group(1))-1
continue
m = match(r"(?:Sweep|LivePlay)\s+Data\(mV\)<(\d+)>=(.*)", longline)
if m:
gsize += int(m.group(1))
dataline = m.group(2)
for subm in finditer(r"(-?)(\d+),(\d+),?", dataline):
value = int(subm.group(2)) + int(subm.group(3)) / 100
if subm.group(1) == "-":
value = -value
data[channel].append(value)
self.data = data
self.channels = channels
if shortname is None:
self.shortpath = self._filepath
elif isinstance(shortname, Pattern):
stem = self._filepath.stem
m = shortname.search(stem)
if m:
stem = m.group(0)
self.shortpath = self._filepath.restem(stem)
def __init__(self,
file: str = "",
*,
dir: str = "",
dialect="excel",
time_unit: TimeUnit = TimeUnit.SECOND,
gzipped=False):
"""
Args:
file: name of CSV file
"""
self.filepath = DPath.from_path(file).prepend_path(
DPath.from_path(dir, dir=True))
if gzipped:
self.filepath.add_suffix(".gz")
self.dialect = dialect
self.time_unit = time_unit
self.gzipped = gzipped
def __init__(self,
filename: str,
*,
dir: str = "",
shortname=None,
channels=None):
self._filepath = DPath.from_path(filename).prepend_path(
DPath.from_path(dir, dir=True))
self.channels = channels
if shortname is None:
self.shortpath = self._filepath
elif isinstance(shortname, Pattern):
stem = self._filepath.stem
m = shortname.search(stem)
if m:
stem = m.group(0)
self.shortpath = self._filepath.restem(stem)
def __init__(self,
filename: str,
fs,
*,
dir: str = "",
dialect: str = "excel",
header: bool = True,
default_unit: str = "unit",
transpose: bool = False,
annotation: Union[str, Sequence[str]] = None):
self._filepath = DPath.from_path(filename).prepend_path(
DPath.from_path(dir, dir=True))
self.dialect = dialect
self.header = header
self.default_unit = default_unit
self.fs = fs
self.transpose = transpose
self.annotation = annotation