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4adadedeb9
Add Python script to plot logged buffers. Modified write_file_matlab() to add .bin extension if binary format is selected.
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
#!/usr/bin/env python
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# coding: utf-8
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import numpy as np
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import matplotlib.pyplot as plt
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import argparse
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import pandas
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def save_fig(fig:plt.figure, figName:str):
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fig.savefig(figName + '.pdf')
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fig.savefig(figName + '.png')
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fig.savefig(figName + '.svg')
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# Channel Frequency Response
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def channel_est(dataPath):
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binfile = dataPath + 'chestF0_ext_s1.m.bin'
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data = np.fromfile(binfile,dtype=np.int16)
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dataCmp = data[0::2] + 1j*data[1::2]
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fig = plt.gcf()
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plt.plot(np.abs(dataCmp))
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save_fig(fig, 'channel_est')
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plt.close(fig)
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# Constellation
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def constellation(dataPath):
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binfile = dataPath + 'rxF_comp_s1.m.bin'
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data = np.fromfile(binfile,dtype=np.int16)
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dataCmp = data[0::2] + 1j*data[1::2]
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fig = plt.gcf()
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plt.scatter(np.real(dataCmp),np.imag(dataCmp))
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save_fig(fig, 'constellation')
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plt.close(fig)
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# LLR
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def llr(dataPath):
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binfile = dataPath + 'rxF_llr.m.bin'
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data = np.fromfile(binfile,dtype=np.int16)
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fig = plt.gcf()
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plt.plot(data,'*')
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save_fig(fig, 'llr')
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plt.close(fig)
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# BER from data in CSV files generated by nr_dlsim
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def ber(dataPath, csvFiles):
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d0 = pandas.read_csv(dataPath + csvFiles[0] + '.csv')
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ax = d0.plot(x='SNR',y='channel_ber_0',logy=True,label=csvFiles[0])
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plt.ylabel('BER')
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for i in range(1,len(csvFiles)):
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d = pandas.read_csv(dataPath + csvFiles[i] + '.csv')
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d.plot(ax=ax,x='SNR',y='channel_ber_0',logy=True,label=csvFiles[i],grid=True)
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fig = ax.figure
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save_fig(fig, 'ber_compare')
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plt.close(fig)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description="DL plot generator")
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parser.add_argument('--data-path', help='Path to directory containing data', default='../../cmake_targets/ran_build/build/')
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parser.add_argument('--csv-data', nargs='+' ,help='CSV file name without extension (generated from nr_dlsim with -Z option)')
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parser.add_argument('--ber-compare', help='Compare BER from multiple CSV files', action='store_true')
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args = parser.parse_args()
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channel_est(args.data_path)
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constellation(args.data_path)
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llr(args.data_path)
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if args.ber_compare:
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ber(args.data_path, args.csv_data)
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