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0221d3fdf8
This will convert cal data files based on CSV to the new binary format.
In most cases, running
./convert_cal_data.py
is sufficient.
104 lines
3.2 KiB
Python
Executable file
104 lines
3.2 KiB
Python
Executable file
#!/usr/bin/env python3
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"""
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Copyright 2020 Ettus Research, A National Instrument Brand
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SPDX-License-Identifier: GPL-3.0-or-later
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convert_cal_data: A utility to convert CSV-based calibration data into binary
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cal data.
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"""
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import os
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import glob
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import argparse
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import uhd
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def csv_to_iq_cal(filename):
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"""
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Opens the file "filename", parses the CSV data, and returns a
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uhd.usrp.cal.IQCal class.
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"""
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def parse_metadata(handle):
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"""
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Return name, serial, and timestamp, and verify version.
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"""
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num_lines_md = 4
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metadata = {}
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for _ in range(num_lines_md):
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key, val = [x.strip() for x in handle.readline().split(",", 1)]
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if key == "version":
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if val != "0, 1":
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raise RuntimeError("Unexpected version: " + val)
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elif key == "timestamp":
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metadata[key] = int(val)
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else:
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metadata[key] = val
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if handle.readline().strip() != "DATA STARTS HERE":
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raise RuntimeError("Unexpected header!")
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handle.readline() # Flush header
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return metadata
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with open(filename, 'r') as handle:
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metadata = parse_metadata(handle)
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print("Found metadata: ")
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for key, val in metadata.items():
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print("* {k}: {v}".format(k=key, v=val))
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iq_cal = uhd.usrp.cal.IQCal(
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metadata['name'], metadata['serial'], metadata['timestamp'])
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for line in handle.readlines():
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lo_freq, corr_real, corr_imag, supp_abs, supp_delta = \
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line.split(",")
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iq_cal.set_cal_coeff(
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float(lo_freq),
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complex(float(corr_real.strip()), float(corr_imag.strip())),
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float(supp_abs.strip()),
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float(supp_delta.strip()),
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)
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return iq_cal
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def get_csv_location():
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"""
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Returns the path to the location of the CSV files
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"""
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return os.path.expandvars("$HOME/.uhd/cal")
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def get_all_files(csv_location=None):
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"""
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Returns a list of all CSV files in the standard location
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"""
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csv_path = csv_location or get_csv_location()
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return glob.glob(os.path.join(csv_path, "*.csv"))
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def parse_args():
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""" Parse args and return args object """
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parser = argparse.ArgumentParser(
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description="Convert CSV-Based cal data to binary format",
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)
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parser.add_argument(
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'files',
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help="List files to convert. If empty, will attempt to auto-detect "
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"files from the standard calibration location ($HOME/.uhd/cal)",
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nargs="*",
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)
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return parser.parse_args()
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def main():
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"""Go, go, go!"""
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args = parse_args()
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file_list = args.files or get_all_files()
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for filename in file_list:
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print("Converting {}...".format(filename))
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print("Identifying cal data type...")
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key = os.path.basename(filename).split('_cal')[0]
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if key not in ('rx_iq', 'tx_iq', 'tx_dc'):
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print("Unidentified cal data type: {}".format(key))
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continue
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iq_cal = csv_to_iq_cal(filename)
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uhd.usrp.cal.database.write_cal_data(
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key,
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iq_cal.get_serial(),
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iq_cal.serialize())
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return 0
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if __name__ == "__main__":
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exit(main())
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