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read_data.py
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read_data.py
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import os
import sys
import numpy as np
def read_fitting_file(filename):
with open(filename, 'r') as f:
data = []
datastream = f.read()
datalines = [line.strip().split()
for line in datastream.split('\n') if line.strip() and line.strip().split()[0] != "#"]
comment_index = []
for line in datalines:
try:
comment_index.append(line.index('#'))
except ValueError:
comment_index.append(len(line))
datalines = [line[0:comment_index[i]] for i, line in enumerate(datalines)]
flags = list(zip(*datalines))[0]
values = np.array([list(map(float, line))
for line in list(zip(*datalines))[1:]]).T
n_rows = len(values[0])
n_data = len(values[:,0])
if n_rows == 3:
data = values
data_covariances = np.array([[[0.] * 3] * 3] * n_data)
data_covariances[:,0,0] = 1.
elif n_rows == 6:
data = values[:,0:3]
data_covariances = np.array([[[0.] * 3] * 3] * n_data)
data_covariances[:,0,0] = values[:,3]*values[:,3]
data_covariances[:,1,1] = values[:,4]*values[:,4]
data_covariances[:,2,2] = values[:,5]*values[:,5]
elif n_rows == 9:
data = values[:,0:3]
data_covariances = np.array([[[0.] * 3] * 3] * n_data)
data_covariances[:,0,0] = values[:,3]
data_covariances[:,1,1] = values[:,4]
data_covariances[:,2,2] = values[:,5]
data_covariances[:,0,1] = values[:,6]
data_covariances[:,1,0] = values[:,6]
data_covariances[:,0,2] = values[:,7]
data_covariances[:,2,0] = values[:,7]
data_covariances[:,1,2] = values[:,8]
data_covariances[:,2,1] = values[:,8]
else:
raise Exception('Your input file must have 4, 7, or 10 rows, where the first row is a string')
return flags, data, data_covariances