Issue
I have a text file containing data in form of blocks. Something like:
File description
Used units
Additional info
T[K]
50 75 100
125 150 175
200 225 250
Field_1
0.1 0.2 0.3
0.4 0.5 0.6
0.7 0.8 0.9
Field_2
1.0 2.0 3.0
4.0 5.0 6.0
7.0 8.0 9.0
I need to skip the lines without data, and read and convert the three blocks with data into three arrays. Ideally, I want to use a generator that can identify the lines with T[K], Field_1, Field_2, and separately collect whatever is in the following block of three lines.
Something that starts like this:
def npgenfromtxtgenerator(file_name):
with open(file_name) as fp:
for line_no, line in enumerate(fp):
if line.startswith('Te[eV]'):
# Make first array
if line.startswith('Field_1'):
# Make second array
if line.startswith('Field_2'):
# Make third array
Many thanks
Solution
Try:
s = """\
File description
Used units
Additional info
T[K]
50 75 100
125 150 175
200 225 250
Field_1
0.1 0.2 0.3
0.4 0.5 0.6
0.7 0.8 0.9
Field_2
1.0 2.0 3.0
4.0 5.0 6.0
7.0 8.0 9.0"""
import re
import numpy as np
from io import StringIO
fields = ["T[K]", "Field_1", "Field_2"]
pat = "|".join(map(re.escape, fields))
pat = re.compile(fr"^({pat})([\s\d.-]+)", flags=re.M | re.S)
out = {n: np.loadtxt(StringIO(a)) for n, a in pat.findall(s)}
# pretty print the dictionary:
for k, v in out.items():
print(k)
print(v)
print("-" * 80)
Prints:
T[K]
[[ 50. 75. 100.]
[125. 150. 175.]
[200. 225. 250.]]
--------------------------------------------------------------------------------
Field_1
[[0.1 0.2 0.3]
[0.4 0.5 0.6]
[0.7 0.8 0.9]]
--------------------------------------------------------------------------------
Field_2
[[1. 2. 3.]
[4. 5. 6.]
[7. 8. 9.]]
--------------------------------------------------------------------------------
Answered By - Andrej Kesely
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