def _read_data_array( self ):
''' Read the experiment data.
'''
if exists( self.data_file ):
print 'READ FILE'
# change the file name dat with asc
file_split = self.data_file.split( '.' )
file_name = file_split[0] + '.csv'
if not os.path.exists( file_name ):
file_name = file_split[0] + '.ASC'
if not os.path.exists( file_name ):
raise IOException, 'file %s does not exist' % file_name
print 'file_name', file_name
# try to use loadtxt to read data file
try:
_data_array = loadtxt( file_name,
delimiter = ';' )
# loadtxt returns an error if the data file contains
# 'NOVALUE' entries. In this case use the special
# method 'loadtxt_novalue'
except ValueError:
_data_array = loadtxt_novalue( file_name )
self.data_array = _data_array
def _read_data_array(self):
''' Read the experiment data.
'''
if os.path.exists(self.data_file):
print 'READ FILE'
# change the file name dat with asc
file_split = self.data_file.split('.')
file_name = file_split[0] + '.csv'
# for data exported into a single csv-file
if os.path.exists(file_name):
print 'check csv-file'
file_ = open(file_name, 'r')
header_line_1 = file_.readline().split()
if header_line_1[0].split(';')[0] == 'Datum/Uhrzeit':
print 'read csv-file'
# for data exported into down sampled data array
try:
_data_array = np.loadtxt(file_name,
delimiter=';',
skiprows=2)
# reset time[sec] in order to start at 0.
_data_array[:0] -= _data_array[0:0]
except ValueError:
# for first column use converter method 'time2sec';
converters = {0: time2sec}
# for all other columns use converter method
# 'comma2dot'
for i in range(len(header_line_1[0].split(';')) - 1):
converters[i + 1] = comma2dot
_data_array = np.loadtxt(
file_name, delimiter=";", skiprows=2, converters=converters)
# reset time[sec] in order to start at 0.
_data_array[:0] -= _data_array[0:0]
else:
# for data exported into DAT and ASC-files
# try to use loadtxt to read data file
try:
_data_array = np.loadtxt(file_name,
delimiter=';')
# loadtxt returns an error if the data file contains
# 'NOVALUE' entries. In this case use the special
# method 'loadtxt_novalue'
except ValueError:
_data_array = loadtxt_novalue(file_name)
if not os.path.exists(file_name):
file_name = file_split[0] + '.ASC'
if not os.path.exists(file_name):
raise IOError, 'file %s does not exist' % file_name
# for data exported into DAT and ASC-files
# try to use loadtxt to read data file
try:
_data_array = np.loadtxt(file_name,
delimiter=';')
# loadtxt returns an error if the data file contains
# 'NOVALUE' entries. In this case use the special
# method 'loadtxt_novalue'
except ValueError:
_data_array = loadtxt_novalue(file_name)
self.data_array = _data_array
def _read_data_array(self):
''' Read the experiment data.
'''
if os.path.exists(self.data_file):
print 'READ FILE'
# change the file name dat with asc
file_split = self.data_file.split('.')
file_name = file_split[0] + '.csv'
# for data exported into a single csv-file
if os.path.exists(file_name):
print 'check csv-file'
file_ = open(file_name, 'r')
header_line_1 = file_.readline().split()
if header_line_1[0].split(';')[0] == 'Datum/Uhrzeit':
print 'read csv-file'
# for data exported into down sampled data array
try:
_data_array = np.loadtxt(file_name,
delimiter=';',
skiprows=2)
# reset time[sec] in order to start at 0.
_data_array[:0] -= _data_array[0:0]
except ValueError:
# for first column use converter method 'time2sec';
converters = {0: time2sec}
# for all other columns use converter method
# 'comma2dot'
for i in range(len(header_line_1[0].split(';')) - 1):
converters[i + 1] = comma2dot
_data_array = np.loadtxt(
file_name, delimiter=";", skiprows=2, converters=converters)
# reset time[sec] in order to start at 0.
_data_array[:0] -= _data_array[0:0]
else:
# for data exported into DAT and ASC-files
# try to use loadtxt to read data file
try:
_data_array = np.loadtxt(file_name,
delimiter=';')
# loadtxt returns an error if the data file contains
# 'NOVALUE' entries. In this case use the special
# method 'loadtxt_novalue'
except ValueError:
_data_array = loadtxt_novalue(file_name)
if not os.path.exists(file_name):
file_name = file_split[0] + '.ASC'
if not os.path.exists(file_name):
raise IOError, 'file %s does not exist' % file_name
# for data exported into DAT and ASC-files
# try to use loadtxt to read data file
try:
_data_array = np.loadtxt(file_name,
delimiter=';')
# loadtxt returns an error if the data file contains
# 'NOVALUE' entries. In this case use the special
# method 'loadtxt_novalue'
except ValueError:
_data_array = loadtxt_novalue(file_name)
self.data_array = _data_array
