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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([[[0.0] * 3] * 3] * n_data)
data_covariances[:, 0, 0] = 1.0
elif n_rows == 6:
data = values[:, 0:3]
data_covariances = np.array([[[0.0] * 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([[[0.0] * 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