def read1Dv(self, fname, tname):
# open file and read column 0, 1 and 2 (variance), separator is tab
data_t = []
data_x = []
data_v = []
fp = open(fname, 'r')
for l in fp:
args = l.split('\t')
if args[0][0].isalpha() == 0:
data_t.append(float(args[0]))
data_x.append(float(args[1]))
data_v.append(float(args[2]))
fp.close()
if len(data_v)<len(data_x):
data_v = np.zeros(len(data_x))
data1 = DataArray(name=tname+" 0", shape=[len(data_t)])
data2 = DataArray(name=tname+" 1", shape=[len(data_t)])
data1.coords = [np.array(data_t)]
data1.data = np.array(data_x)
data1.shape = [len(data_x)]
data2.coords = [np.array(data_t)]
data2.data = np.array(data_v)
data2.shape = [len(data_v)]
return [data1, data2]
def read1D(self, fname, tname):
# open file and read column 0 and 1, separator is tab
data_t = []
data_x = []
fp = open(fname, 'r')
for l in fp:
args = l.split('\t')
if args[0][0].isalpha() == 0:
data_t.append(float(args[0]))
data_x.append(float(args[1]))
fp.close()
data = DataArray(name=tname, shape=[len(data_t)])
data.coords = [np.array(data_t)]
data.data = np.array(data_x)
data.shape = [len(data_x)]
return [data]
