def _ReadSelFile(self):
"""
Some title
==========
Using docstrings formatted according to the reStructuredText specs
can be used for automated documentation generation with for instance
Sphinx: http://sphinx.pocoo.org/.
Parameters
----------
signal : ndarray
some description
Returns
-------
output : int
describe variable
"""
# read *.sel hawc2 output file for result info
if self.FileName.lower().endswith('.sel'):
self.FileName = self.FileName[:-4]
fid = opent(self.FileName + '.sel', 'r')
Lines = fid.readlines()
fid.close()
# findes general result info (number of scans, number of channels,
# simulation time and file format)
temp = Lines[8].split()
self.NrSc = int(temp[0])
self.NrCh = int(temp[1])
self.Time = float(temp[2])
self.Freq = self.NrSc / self.Time
self.t = np.linspace(0, self.Time, self.NrSc + 1)[1:]
Format = temp[3]
# reads channel info (name, unit and description)
Name = []
Unit = []
Description = []
for i in range(0, self.NrCh):
temp = str(Lines[i + 12][12:43])
Name.append(temp.strip())
temp = str(Lines[i + 12][43:54])
Unit.append(temp.strip())
temp = str(Lines[i + 12][54:-1])
Description.append(temp.strip())
self.ChInfo = [Name, Unit, Description]
# if binary file format, scaling factors are read
if Format.lower() == 'binary':
self.ScaleFactor = np.zeros(self.NrCh)
self.FileFormat = 'HAWC2_BINARY'
for i in range(0, self.NrCh):
self.ScaleFactor[i] = float(Lines[i + 12 + self.NrCh + 2])
else:
self.FileFormat = 'HAWC2_ASCII'
def _ReadSensorFile(self):
# read sensor file used if results are saved in FLEX format
DirName = os.path.dirname(self.FileName)
try:
fid = opent(DirName + r"\sensor ", 'r')
except IOError:
print("can't finde sensor file for FLEX format")
return
Lines = fid.readlines()
fid.close()
# reads channel info (name, unit and description)
self.NrCh = 0
Name = []
Unit = []
Description = []
for i in range(2, len(Lines)):
temp = Lines[i]
if not temp.strip():
break
self.NrCh += 1
temp = str(Lines[i][38:45])
Unit.append(temp.strip())
temp = str(Lines[i][45:53])
Name.append(temp.strip())
temp = str(Lines[i][53:])
Description.append(temp.strip())
self.ChInfo = [Name, Unit, Description]
# read general info from *.int file
fid = open(self.FileName, 'rb')
fid.seek(4 * 19)
if not np.fromfile(fid, 'int32', 1) == self.NrCh:
print(
"number of sensors in sensor file and data file are not consisten"
)
fid.seek(4 * (self.NrCh) + 4, 1)
self.Version = np.fromfile(fid, 'int32', 1)[0]
temp = np.fromfile(fid, 'f', 2)
self.Freq = 1 / temp[1]
self.ScaleFactor = np.fromfile(fid, 'f', self.NrCh)
fid.seek(2 * 4 * self.NrCh + 48 * 2)
self.NrSc = int(len(np.fromfile(fid, 'int16')) / self.NrCh)
self.Time = self.NrSc * temp[1]
self.t = np.arange(0, self.Time, temp[1])
fid.close()
def _ReadSelFile(self):
"""
Some title
==========
Using docstrings formatted according to the reStructuredText specs
can be used for automated documentation generation with for instance
Sphinx: http://sphinx.pocoo.org/.
Parameters
----------
signal : ndarray
some description
Returns
-------
output : int
describe variable
"""
# read *.sel hawc2 output file for result info
if self.FileName.lower().endswith('.sel'):
self.FileName = self.FileName[:-4]
fid = opent(self.FileName + '.sel', 'r')
Lines = fid.readlines()
fid.close()
if Lines[0].lower().find('bhawc') >= 0:
# --- Find line with scan info
iLine = 0
for i in np.arange(5, 10):
if Lines[i].lower().find('scans') >= 0:
iLine = i + 1
if iLine == 0:
raise Exception('Cannot find the keyword "scans"')
temp = Lines[iLine].split()
self.NrSc = int(temp[0])
self.NrCh = int(temp[1])
self.Time = float(temp[2])
self.Freq = self.NrSc / self.Time
self.t = np.linspace(0, self.Time, self.NrSc + 1)[1:]
# --- Find line with channel info
iLine = 0
for i in np.arange(5, 13):
if Lines[i].lower().find('channel') >= 0:
iLine = i + 1
if iLine == 0:
raise Exception('Cannot find the keyword "Channel"')
# reads channel info (name, unit and description)
Name = []
Unit = []
Description = []
for i in range(0, self.NrCh + 1):
if (i + iLine) >= len(Lines):
break
line = Lines[i + iLine].strip()
if len(line) == 0:
continue
# --- removing number and unit
sp = [sp.strip() for sp in line.split() if len(sp.strip()) > 0]
num = sp[0]
iNum = line.find(num)
line = line[iNum + len(num) + 1:]
unit = sp[-1]
iUnit = line.find(unit)
line = line[:iUnit]
# --- Splitting to find label and description
sp = [
sp.strip() for sp in line.split('\t')
if len(sp.strip()) > 0
]
if len(sp) != 2:
for nSpaces in np.arange(2, 15):
sp = [
sp.strip() for sp in line.split(' ' * nSpaces)
if len(sp.strip()) > 0
]
if len(sp) == 2:
break
if len(sp) != 2:
raise Exception(
'Dont know how to split the input of the sel file into 4 columns'
)
Unit.append(unit)
Description.append(sp[0])
Name.append(sp[1])
self.ChInfo = [Name, Unit, Description]
self.FileFormat = 'BHAWC_ASCII'
else:
# findes general result info (number of scans, number of channels,
# simulation time and file format)
temp = Lines[8].split()
self.NrSc = int(temp[0])
self.NrCh = int(temp[1])
self.Time = float(temp[2])
self.Freq = self.NrSc / self.Time
self.t = np.linspace(0, self.Time, self.NrSc + 1)[1:]
Format = temp[3]
# reads channel info (name, unit and description)
Name = []
Unit = []
Description = []
for i in range(0, self.NrCh):
temp = str(Lines[i + 12][12:43])
Name.append(temp.strip())
temp = str(Lines[i + 12][43:54])
Unit.append(temp.strip())
temp = str(Lines[i + 12][54:-1])
Description.append(temp.strip())
self.ChInfo = [Name, Unit, Description]
# if binary file format, scaling factors are read
if Format.lower() == 'binary':
self.ScaleFactor = np.zeros(self.NrCh)
self.FileFormat = 'HAWC2_BINARY'
for i in range(0, self.NrCh):
self.ScaleFactor[i] = float(Lines[i + 12 + self.NrCh + 2])
else:
self.FileFormat = 'HAWC2_ASCII'