Fix logging to matlab/bin file

Add Python script to plot logged buffers. Modified write_file_matlab()
to add .bin extension if binary format is selected.

tools/plots/README.md

@@ -19,3 +19,16 @@ Same goes for any software modifications of `nr_ulsim` - the cache is not aware
 the data - remember to clear your cache manually if you are comparing different `nr_ulsim` versions.
 
 The script also allows to skip usage of the cache with `--rerun` option.
+
+## `dl_graph.py`
+
+This generates plots from data saved from nr_dlsim. It takes data in two formats:
+
+1. Plots frequency domain channel estimates, constellation diagram and LLRs from data read in binary format. The data is generated from `nr_dlsim -w`
+2. Plots BER (other also possible) from CSV data generated by `nr_dlsim -Z`.
+
+The plots are saved in three formats: `.png`, `.pdf` and `.svg`.
+
+### Example graphs:
+#### BER
+![image](./ber_compare.svg)

tools/plots/dl_graph.py

@@ -0,0 +1,68 @@
+#!/usr/bin/env python
+# coding: utf-8
+import numpy as np
+import matplotlib.pyplot as plt
+import argparse
+import pandas
+
+def save_fig(fig:plt.figure, figName:str):
+    fig.savefig(figName + '.pdf')
+    fig.savefig(figName + '.png')
+    fig.savefig(figName + '.svg')
+
+# Channel Frequency Response
+def channel_est(dataPath):
+    binfile = dataPath + 'chestF0_ext_s1.m.bin'
+    data = np.fromfile(binfile,dtype=np.int16)
+    dataCmp = data[0::2] + 1j*data[1::2]
+    fig = plt.gcf()
+    plt.plot(np.abs(dataCmp))
+    save_fig(fig, 'channel_est')
+    plt.close(fig)
+
+# Constellation
+def constellation(dataPath):
+    binfile = dataPath + 'rxF_comp_s1.m.bin'
+    data = np.fromfile(binfile,dtype=np.int16)
+    dataCmp = data[0::2] + 1j*data[1::2]
+    fig = plt.gcf()
+    plt.scatter(np.real(dataCmp),np.imag(dataCmp))
+    save_fig(fig, 'constellation')
+    plt.close(fig)
+
+# LLR
+def llr(dataPath):
+    binfile = dataPath + 'rxF_llr.m.bin'
+    data = np.fromfile(binfile,dtype=np.int16)
+    fig = plt.gcf()
+    plt.plot(data,'*')
+    save_fig(fig, 'llr')
+    plt.close(fig)
+
+# BER from data in CSV files generated by nr_dlsim
+def ber(dataPath, csvFiles):
+    d0 = pandas.read_csv(dataPath + csvFiles[0] + '.csv')
+    ax = d0.plot(x='SNR',y='channel_ber_0',logy=True,label=csvFiles[0])
+    plt.ylabel('BER')
+    for i in range(1,len(csvFiles)):
+        d = pandas.read_csv(dataPath + csvFiles[i] + '.csv')
+        d.plot(ax=ax,x='SNR',y='channel_ber_0',logy=True,label=csvFiles[i],grid=True)
+
+    fig = ax.figure
+    save_fig(fig, 'ber_compare')
+    plt.close(fig)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description="DL plot generator")
+    parser.add_argument('--data-path', help='Path to directory containing data', default='../../cmake_targets/ran_build/build/')
+    parser.add_argument('--csv-data', nargs='+' ,help='CSV file name without extension (generated from nr_dlsim with -Z option)')
+    parser.add_argument('--ber-compare', help='Compare BER from multiple CSV files', action='store_true')
+
+    args = parser.parse_args()
+
+    channel_est(args.data_path)
+    constellation(args.data_path)
+    llr(args.data_path)
+    if args.ber_compare:
+        ber(args.data_path, args.csv_data)