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