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Add pyadi helpers with doc and tests (#63)
* Add pyadi helper functions with example Signed-off-by: Travis F. Collins <[email protected]> * Add test for pyadi helper Signed-off-by: Travis F. Collins <[email protected]> * Add doc for pyadi helpers Signed-off-by: Travis F. Collins <[email protected]> * Rename helpers module Signed-off-by: Travis F. Collins <[email protected]> * Remove IIO dependency and add licensing Signed-off-by: Travis F. Collins <[email protected]> * Add helper to example to ignore cases when pyadi-iio is not installed Signed-off-by: Travis F. Collins <[email protected]> --------- Signed-off-by: Travis F. Collins <[email protected]>
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‎bindings/python/examples/fft_analysis_pyadi.py‎

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# Example of Fourier analysis using Genalyzer and an ADI SDR
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# Requires: genalyzer, pyadi-iio, matplotlib, numpy
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def main():
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import time
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import numpy as np
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import genalyzer as gn
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from importlib.util import find_spec
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if find_spec("adi") is None or find_spec("iio") is None:
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print("pyadi-iio must be installed to run this example")
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return
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import adi
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#
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# Setup Example parameters
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#
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plot = True
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navg = 8
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nfft = 2**16
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fshift = 0e6
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tone_freq = 70e6
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uri = "ip:192.168.86.35"
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axis_fmt = gn.FreqAxisFormat.FREQ
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axis_type = gn.FreqAxisType.DC_CENTER
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window = gn.Window.BLACKMAN_HARRIS
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# Single sideband parameters (width in bins)
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ssb_fund = 4
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ssb_rest = 3
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if gn.Window.NO_WINDOW == window:
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ssb_fund = 0
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ssb_rest = 0
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# Setup SDR
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sdr = adi.adrv9009_zu11eg(uri)
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fs = int(sdr.rx_sample_rate)
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sdr.rx_lo = int(1e9)
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sdr.tx_lo = int(1e9)
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sdr.rx_buffer_size = nfft * navg
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sdr.rx_enabled_channels = [0]
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# Start transmission
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sdr.dds_single_tone(tone_freq, 0.9, 0)
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time.sleep(2)
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# Acquisition and processing
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for i in range(16):
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x = sdr.rx()
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fft_cplx, fft_db, fft_freq_out = gn.pai.fft(sdr, x, navg, window)
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#
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# Fourier analysis configuration
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#
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key = "fa"
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gn.mgr_remove(key)
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gn.fa_create(key)
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gn.fa_analysis_band(key, "fdata*0.0", "fdata*1.0")
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gn.fa_fixed_tone(key, "A", gn.FaCompTag.SIGNAL, tone_freq, ssb_fund)
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gn.fa_conv_offset(key, 0.0 != fshift)
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gn.fa_hd(key, 3)
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gn.fa_ssb(key, gn.FaSsb.DEFAULT, ssb_rest)
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gn.fa_ssb(key, gn.FaSsb.DC, -1)
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gn.fa_ssb(key, gn.FaSsb.SIGNAL, -1)
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gn.fa_ssb(key, gn.FaSsb.WO, -1)
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gn.fa_fdata(key, fs)
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gn.fa_fsample(key, fs)
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gn.fa_fshift(key, fshift)
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print(gn.fa_preview(key, True))
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#
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# Fourier analysis execution
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#
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results = gn.fft_analysis(key, fft_cplx, nfft, axis_type)
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carrier = gn.fa_result_string(results, "carrierindex")
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maxspur = gn.fa_result_string(results, "maxspurindex")
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#
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# Print results
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#
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for k in [
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"fsnr",
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"sfdr",
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"dc:mag_dbfs",
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"A:freq",
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"A:ffinal",
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"A:mag_dbfs",
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"A:phase",
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"-3A:mag_dbc",
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]:
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print("{:20s}{:20.6f}".format(k, results[k]))
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print("{:20s}{:20s}".format("Carrier", carrier))
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print("{:20s}{:20s}".format("MaxSpur", maxspur))
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#
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# Plot
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#
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if plot:
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import matplotlib.pyplot as pl
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from matplotlib.patches import Rectangle as MPRect
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# freq_axis = gn.freq_axis(nfft, axis_type, fs, axis_fmt)
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# fft_db = gn.db(fft_cplx)
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fig = pl.figure(1)
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fig.clf()
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pl.plot(fft_freq_out, fft_db)
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pl.grid(True)
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pl.xlim(fft_freq_out[0], fft_freq_out[-1])
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pl.ylim(-140.0, 20.0)
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annots = gn.fa_annotations(results, axis_type, axis_fmt)
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for x, y, label in annots["labels"]:
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pl.annotate(label, xy=(x, y), ha="center", va="bottom")
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for line in annots["lines"]:
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pl.axline((line[0], line[1]), (line[2], line[3]), c="pink")
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for box in annots["ab_boxes"]:
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fig.axes[0].add_patch(
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MPRect(
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(box[0], box[1]),
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box[2],
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box[3],
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ec="lightgray",
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fc="gainsboro",
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fill=True,
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hatch="x",
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)
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)
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for box in annots["tone_boxes"]:
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fig.axes[0].add_patch(
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MPRect(
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(box[0], box[1]),
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box[2],
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box[3],
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ec="pink",
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fc="pink",
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fill=True,
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hatch="x",
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)
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)
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pl.show()
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if __name__ == "__main__":
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main()

‎bindings/python/genalyzer/__init__.py‎

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import genalyzer.simplified_beta as simplified_beta
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import genalyzer.helpers as helpers
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import genalyzer.pai_inf as pai

‎bindings/python/genalyzer/pai_inf.py‎

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# Copyright (C) 2025 Analog Devices, Inc.
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#
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# SPDX short identifier: ADIBSD OR GPL-2.0-or-later
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"""Helper functions for pyadi-iio devices."""
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import numpy as np
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import genalyzer as gn
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def fft(
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interface,
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data,
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navg=1,
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window=gn.Window.NO_WINDOW,
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axis_type=gn.FreqAxisType.DC_CENTER,
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axis_fmt=gn.FreqAxisFormat.FREQ,
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):
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"""Perform FFT based off pyadi-iio interface.
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This function performs an FFT on data acquired from a pyadi-iio device and
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generate the scaled FFT result in dB along with the corresponding frequency axis.
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The dB scaled data is shifted if the axis_type is set to DC_CENTER.
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The function supports both real and complex data. For complex data, the input
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numpy array should have a complex dtype (np.complex64 or np.complex128).
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For real data, the input numpy array should have an integer dtype (e.g., np.int16,
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np.int32, etc.) matching the data format of the device channel.
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The function also supports multiple channels if the pyadi-iio device has more
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than one enabled channel. In this case, the input data should be a list of numpy
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arrays, one for each enabled channel.
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Args:
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``interface``: pyadi-iio device instance.
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``data``: numpy array or list of numpy arrays (for multiple channels).
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``navg``: number of averages.
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``window``: window type from gn.Window enum.
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``axis_type``: frequency axis type from gn.FreqAxisType enum.
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``axis_fmt``: frequency axis format from gn.FreqAxisFormat enum.
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Returns:
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``fft_out``: FFT output as a numpy array or list of numpy arrays (for multiple channels).
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``fft_out_db``: dB scaled FFT output as a numpy array or list of numpy arrays (for multiple channels).
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``fft_freq_out``: frequency axis as a numpy array or list of numpy arrays (for multiple channels).
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"""
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# Checks
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assert hasattr(
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interface, "_rxadc"
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), "Non standard pyadi-iio device. interface must have _rxadc attribute"
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# assert isinstance(
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# interface._rxadc, iio.Device
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# ), "interface must be an iio.Device as _rxadc attribute"
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if not isinstance(data, (np.ndarray, list)) and not all(
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isinstance(d, np.ndarray) for d in data
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):
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raise ValueError("data must be a numpy array or a list of numpy arrays")
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assert navg > 0 and isinstance(navg, int), "navg must be a positive integer"
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# Check data meets channels
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if len(interface.rx_enabled_channels) > 1:
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if not isinstance(data, list):
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raise ValueError("data must be a list when multiple channels are enabled")
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if len(data) != len(interface.rx_enabled_channels):
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raise ValueError("data length must match number of enabled channels")
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elif isinstance(data, list):
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raise ValueError("data must be a numpy array when a single channel is enabled")
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elif len(interface.rx_enabled_channels) == 0:
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raise ValueError("No enabled channels found in interface")
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if hasattr(interface, "rx_sample_rate"):
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fs = int(interface.rx_sample_rate)
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elif hasattr(interface, "sample_rate"):
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fs = int(interface.sample_rate)
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else:
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raise ValueError("Sample rate not found in interface")
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fft_out = {}
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fft_out_db = {}
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fft_freq_out = {}
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for i, rx_ch in enumerate(interface.rx_enabled_channels):
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if isinstance(rx_ch, int):
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channel = interface._rxadc.channels[rx_ch]
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elif isinstance(rx_ch, str):
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channel = interface._rxadc.find_channel(rx_ch, False)
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else:
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raise ValueError("rx_channel must be int or str")
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if not channel:
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raise ValueError(
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f"Channel {rx_ch} not found in device {interface._rxadc.name}"
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)
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df = channel.data_format
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fmt = ("i" if df.is_signed is True else "u") + str(df.length // 8)
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fmt = f">{fmt}" if df.is_be else fmt
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qres = df.bits
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fmt = np.dtype(fmt)
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assert fmt in [
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np.dtype("int16"),
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np.dtype("int32"),
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], "Unsupported data format"
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code_fmt = gn.CodeFormat.TWOS_COMPLEMENT # Binary scaling not supported for now
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rx_data = data[i] if isinstance(data, list) else data
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is_complex = rx_data.dtype in [np.complex64, np.complex128]
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nfft = len(rx_data) // (navg)
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assert navg * nfft == len(rx_data), "data length must be multiple of navg"
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if is_complex:
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x_re = np.array(rx_data.real).astype(fmt)
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x_im = np.array(rx_data.imag).astype(fmt)
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fft_cplx = gn.fft(x_re, x_im, qres, navg, nfft, window, code_fmt)
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else:
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x = np.array(rx_data).astype(fmt)
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fft_cplx = gn.fft_real(x, qres, navg, nfft, window, code_fmt)
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# Frequency axis and dB
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freq_axis = gn.freq_axis(nfft, axis_type, fs, axis_fmt)
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fft_db = gn.db(fft_cplx)
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if gn.FreqAxisType.DC_CENTER == axis_type:
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fft_db = gn.fftshift(fft_db)
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fft_out[rx_ch] = fft_cplx
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fft_out_db[rx_ch] = fft_db
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fft_freq_out[rx_ch] = freq_axis
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if len(fft_out) == 1:
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first = list(fft_out.keys())[0]
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fft_out = fft_out[first]
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fft_out_db = fft_out_db[first]
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fft_freq_out = fft_freq_out[first]
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return fft_out, fft_out_db, fft_freq_out

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