74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
import numpy as np
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import matplotlib.pyplot as plot
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from scipy import signal, constants
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import argparse
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import os
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def rp_raw_to_numpy(rp_raw):
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# Convert raw buffer strings to numpy arrays
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buff_string = rp_raw.split(',')
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return np.array(list(map(float, buff_string)))
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RP_IP_ADDRS = {
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"creotech-1": "192.168.1.104",
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"creotech-2": "192.168.1.105",
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"mlabs-1": "rp-f05cc9",
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"mlabs-2": "rp-f0612e",
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}
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def main():
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parser = argparse.ArgumentParser(description="Data plotting tool for Sayma DAC/TTL")
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parser.add_argument("dir", help="output directory", type=str)
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parser.add_argument("rps", metavar="NAME:CHANNEL",
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help="input <CHANNEL> of the RedPitaya at <NAME> where data is collected; "
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"CHANNEL must be 1 or 2; "
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"NAME must be any of: " + " ".join(list(RP_IP_ADDRS.keys())),
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type=str, nargs=2)
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args = parser.parse_args()
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# Must only compare 2 data
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name, channel = args.rps[0].split(':')
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y1_filename = 'rp_{}_y{}_raw.bin'.format(name, channel)
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name, channel = args.rps[1].split(':')
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y2_filename = 'rp_{}_y{}_raw.bin'.format(name, channel)
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if y1_filename == y2_filename:
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raise ValueError("Both files are the same.")
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with open(os.path.join(args.dir, y1_filename), 'rb') as f:
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y1_raw = f.read().decode('utf-8')
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with open(os.path.join(args.dir, y2_filename), 'rb') as f:
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y2_raw = f.read().decode('utf-8')
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if None in [y1_raw, y2_raw]:
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raise IOError("Raw RP string files cannot be opened.")
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y1 = rp_raw_to_numpy(y1_raw)
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y2 = rp_raw_to_numpy(y2_raw)
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# Define t as an array of timestamps (in seconds) for each sample
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# (Note that RedPitaya's oscilloscope has a sampling rate @ 125MHz)
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t = np.arange(y1.shape[0])/125e6
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# Generate matrix Y by having arrays y1 and y2 as 2 rows
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y = np.c_[y1, y2].T
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# Element-wise multiply an array of cos(2pi*9e6*t) with each row in Y;
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# Then, downsample the array by 10 as Z
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z = signal.decimate(y*np.exp(1j*2*np.pi*9e6*t), q=10, ftype="fir", zero_phase=True)[:, 10:]
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# Downsample Z by 10 again.
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z = signal.decimate(z, q=10, ftype="fir", zero_phase=True)[:, 10:]
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# Element-wise multiply Z[0] with the conjugate of Z[1] to get the phase difference (i.e. angle(z0) - angle(z1)), and use the mean value.
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angle = np.angle(np.mean(z[0]*z[1].conj()))
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print(angle)
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# Normalize y1 and y2 for plotting
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y1 /= abs(y1).max()
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y2 /= abs(y2).max()
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plot.plot(y1)
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plot.plot(y2)
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plot.show()
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if __name__ == "__main__":
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main()
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