Last active
July 26, 2024 18:29
-
-
Save snmishra/27dcc624b639c2626137 to your computer and use it in GitHub Desktop.
Short python script to read ngspice raw binary files
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# MIT license: https://opensource.org/licenses/MIT | |
# See https://github.com/Isotel/mixedsim/blob/master/python/ngspice_read.py | |
# for a more complete library. Isotel's version is GPL licensed | |
from __future__ import division | |
import numpy as np | |
BSIZE_SP = 512 # Max size of a line of data; we don't want to read the | |
# whole file to find a line, in case file does not have | |
# expected structure. | |
MDATA_LIST = [b'title', b'date', b'plotname', b'flags', b'no. variables', | |
b'no. points', b'dimensions', b'command', b'option'] | |
def rawread(fname: str): | |
"""Read ngspice binary raw files. Return tuple of the data, and the | |
plot metadata. The dtype of the data contains field names. This is | |
not very robust yet, and only supports ngspice. | |
>>> darr, mdata = rawread('test.py') | |
>>> darr.dtype.names | |
>>> plot(np.real(darr['frequency']), np.abs(darr['v(out)'])) | |
""" | |
# Example header of raw file | |
# Title: rc band pass example circuit | |
# Date: Sun Feb 21 11:29:14 2016 | |
# Plotname: AC Analysis | |
# Flags: complex | |
# No. Variables: 3 | |
# No. Points: 41 | |
# Variables: | |
# 0 frequency frequency grid=3 | |
# 1 v(out) voltage | |
# 2 v(in) voltage | |
# Binary: | |
fp = open(fname, 'rb') | |
count = 0 | |
arrs = [] | |
plots = [] | |
plot = {} | |
while (True): | |
try: | |
mdata = fp.readline(BSIZE_SP).split(b':', maxsplit=1) | |
except: | |
raise | |
if len(mdata) == 2: | |
if mdata[0].lower() in MDATA_LIST: | |
plot[mdata[0].lower()] = mdata[1].strip() | |
if mdata[0].lower() == b'variables': | |
nvars = int(plot[b'no. variables']) | |
npoints = int(plot[b'no. points']) | |
plot['varnames'] = [] | |
plot['varunits'] = [] | |
for varn in range(nvars): | |
varspec = (fp.readline(BSIZE_SP).strip() | |
.decode('ascii').split()) | |
assert(varn == int(varspec[0])) | |
plot['varnames'].append(varspec[1]) | |
plot['varunits'].append(varspec[2]) | |
if mdata[0].lower() == b'binary': | |
rowdtype = np.dtype({'names': plot['varnames'], | |
'formats': [np.complex_ if b'complex' | |
in plot[b'flags'] | |
else np.float_]*nvars}) | |
# We should have all the metadata by now | |
arrs.append(np.fromfile(fp, dtype=rowdtype, count=npoints)) | |
plots.append(plot) | |
plot = {} # reset the plot dict | |
fp.readline() # Read to the end of line | |
else: | |
break | |
return (arrs, plots) | |
if __name__ == '__main__': | |
arrs, plots = rawread('test.raw') | |
print(arrs) | |
# Local Variables: | |
# mode: python | |
# End: |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
That's exactly it, thanks.