mirror of
https://github.com/fairwaves/UHD-Fairwaves.git
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82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
import sys
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import csv
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import numpy as np
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import matplotlib.pyplot as plt
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def plot_csv(file_path):
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freq_vals = list()
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dc_i_vals = list()
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dc_q_vals = list()
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dc_i_vals_per_freq = dict()
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dc_q_vals_per_freq = dict()
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#extract values into the lists
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with open(file_path) as csvfile:
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reader = csv.reader(csvfile)
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for row in reader:
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if 'DATA STARTS HERE' in row[0]: break
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for i, row in enumerate(reader):
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if not i: continue #skip titles
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tx_lo, icor, qcor, meadured, delta = row
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tx_lo = float(tx_lo)/1e9
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icor = float(icor)
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qcor = float(qcor)
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freq_vals.append(tx_lo)
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dc_i_vals.append(icor)
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dc_q_vals.append(qcor)
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if tx_lo not in dc_i_vals_per_freq: dc_i_vals_per_freq[tx_lo] = list()
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if tx_lo not in dc_q_vals_per_freq: dc_q_vals_per_freq[tx_lo] = list()
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dc_i_vals_per_freq[tx_lo].append(icor)
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dc_q_vals_per_freq[tx_lo].append(qcor)
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#plot of raw correction values
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plt.figure(1)
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plt.subplot(311)
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plt.plot(freq_vals, dc_i_vals, freq_vals, dc_q_vals,)
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#plt.ylim(0, 250)
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plt.title("Freq (GHz) vs raw IQ corrections")
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#plt.xlabel('Freq (GHz)')
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plt.grid(True)
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#plot of variance
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plt.subplot(312)
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freqs = sorted(dc_i_vals_per_freq.keys())
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dc_i_std = [np.std(dc_i_vals_per_freq[f]) for f in freqs]
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dc_q_std = [np.std(dc_q_vals_per_freq[f]) for f in freqs]
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plt.plot(freqs, dc_i_std, freqs, dc_q_std)
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#plt.ylim(0, 150)
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plt.title("Freq (GHz) vs stddev IQ corrections")
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#plt.xlabel('Freq (GHz)')
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plt.grid(True)
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#plot of average values
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"""
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avg_len = 10
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def moving_average(a, n=avg_len) :
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ret = np.cumsum(a, dtype=float)
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ret[n:] = ret[n:] - ret[:-n]
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return ret[n - 1:] / n
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plt.subplot(313)
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plt.plot(freq_vals[:-avg_len+1], moving_average(dc_i_vals), freq_vals[:-avg_len+1], moving_average(dc_q_vals),)
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plt.ylim(0, 250)
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plt.title("Freq (GHz) vs averaged IQ corrections")
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#plt.xlabel('Freq (GHz)')
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plt.grid(True)
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"""
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plt.subplot(313)
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freqs = sorted(dc_i_vals_per_freq.keys())
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dc_i_avg = [np.mean(dc_i_vals_per_freq[f]) for f in freqs]
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dc_q_avg = [np.mean(dc_q_vals_per_freq[f]) for f in freqs]
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plt.plot(freqs, dc_i_avg, freqs, dc_q_avg)
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#plt.ylim(0, 250)
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plt.title("Freq (GHz) vs averaged IQ corrections")
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#plt.xlabel('Freq (GHz)')
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plt.grid(True)
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plt.show()
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if __name__ == "__main__":
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plot_csv(sys.argv[1])
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