diff --git a/bin/gamutrf b/bin/gamutrf index 49c6dab7..d254168a 100644 --- a/bin/gamutrf +++ b/bin/gamutrf @@ -9,7 +9,7 @@ Options: -h, help print this help -i, install install GamutRF repo, optionally supply a version, tag, branch, or tarball -l, logs tail GamutRF logs - -r, run specify GamutRF tool to run (and any additional args for the tools), options include: 'worker', 'scan', 'specgram' + -r, run specify GamutRF tool to run (and any additional args for the tools), options include: 'worker', 'scan' -R, restart specify 'orchestrator' or 'worker' to restart -s, start specify 'orchestrator' or 'worker' to start -S, stop specify 'orchestrator' or 'worker' to stop diff --git a/gamutrf/__main__.py b/gamutrf/__main__.py index a25916af..f098df45 100644 --- a/gamutrf/__main__.py +++ b/gamutrf/__main__.py @@ -3,7 +3,6 @@ from gamutrf.compress_dirs import main as compress_dirs_main from gamutrf.offline import main as offline_main from gamutrf.scan import main as scan_main -from gamutrf.specgram import main as specgram_main from gamutrf.worker import main as worker_main @@ -22,11 +21,6 @@ def scan(): scan_main() -def specgram(): - """Entrypoint for specgram""" - specgram_main() - - def worker(): """Entrypoint for worker""" worker_main() diff --git a/gamutrf/specgram.py b/gamutrf/specgram.py deleted file mode 100644 index 8d47bafc..00000000 --- a/gamutrf/specgram.py +++ /dev/null @@ -1,422 +0,0 @@ -import argparse -import concurrent.futures -import os -import time - -import matplotlib.pyplot as plt -import numpy as np -from matplotlib.mlab import detrend -from matplotlib.mlab import detrend_none -from matplotlib.mlab import window_hanning -from scipy.fft import fft # pylint disable=no-name-in-module -from scipy.fft import fftfreq # pylint disable=no-name-in-module - -from gamutrf.utils import get_nondot_files -from gamutrf.utils import is_fft -from gamutrf.utils import replace_ext -from gamutrf.sample_reader import read_recording, parse_filename - - -def stride_windows(x, n, noverlap=0, axis=0): - # np>=1.20 provides sliding_window_view, and we only ever use axis=0. - if hasattr(np.lib.stride_tricks, "sliding_window_view") and axis == 0: - if noverlap >= n: - raise ValueError("noverlap must be less than n") - return np.lib.stride_tricks.sliding_window_view(x, n, axis=0)[:: n - noverlap].T - - if noverlap >= n: - raise ValueError("noverlap must be less than n") - if n < 1: - raise ValueError("n cannot be less than 1") - - x = np.asarray(x) - - if n == 1 and noverlap == 0: - if axis == 0: - return x[np.newaxis] - else: - return x[np.newaxis].T - if n > x.size: - raise ValueError("n cannot be greater than the length of x") - - # np.lib.stride_tricks.as_strided easily leads to memory corruption for - # non integer shape and strides, i.e. noverlap or n. See #3845. - noverlap = int(noverlap) - n = int(n) - - step = n - noverlap - if axis == 0: - shape = (n, (x.shape[-1] - noverlap) // step) - strides = (x.strides[0], step * x.strides[0]) - else: - shape = ((x.shape[-1] - noverlap) // step, n) - strides = (step * x.strides[0], x.strides[0]) - return np.lib.stride_tricks.as_strided(x, shape=shape, strides=strides) - - -def spectral_helper( - x, - NFFT=None, - Fs=None, - detrend_func=None, - window=None, - noverlap=None, - pad_to=None, - scale_by_freq=None, - mode=None, - skip_fft=False, -): - if Fs is None: - Fs = 2 - if noverlap is None: - noverlap = 0 - if detrend_func is None: - detrend_func = detrend_none - if window is None: - window = window_hanning - - window = np.abs(window(np.ones(NFFT, np.complex64))) - if len(window) != NFFT: - raise ValueError("The window length must match the data's first dimension") - - # if NFFT is set to None use the whole signal - if NFFT is None: - NFFT = 256 - - if mode is None or mode == "default": - mode = "psd" - - if pad_to is None: - pad_to = NFFT - - if mode != "psd": - scale_by_freq = False - elif scale_by_freq is None: - scale_by_freq = True - - # For real x, ignore the negative frequencies unless told otherwise - numFreqs = pad_to - if pad_to % 2: - freqcenter = (pad_to - 1) // 2 + 1 - else: - freqcenter = pad_to // 2 - - results = [] - - for i in x: - if i is None: - break - if skip_fft: - # TODO: assume NFFT is factor of sps. - result = i.reshape(-1, int(len(i) / NFFT), order="F") - else: - result = stride_windows(i, NFFT, noverlap, axis=0) - result = detrend(result, detrend_func, axis=0) - result = fft(result, n=pad_to, axis=0)[ - :numFreqs, : - ] # pylint: disable=invalid-sequence-index - - if mode == "psd": - result *= np.conj(result) - # MATLAB divides by the sampling frequency so that density function - # has units of dB/Hz and can be integrated by the plotted frequency - # values. Perform the same scaling here. - if scale_by_freq: - result /= Fs - # Scale the spectrum by the norm of the window to compensate for - # windowing loss; see Bendat & Piersol Sec 11.5.2. - result /= (window**2).sum() - else: - # In this case, preserve power in the segment, not amplitude - result /= window.sum() ** 2 - elif mode == "magnitude": - result = np.abs(result) / window.sum() - elif mode == "complex": - result /= window.sum() - elif mode in ("angle", "phase"): - # we unwrap the phase later to handle the onesided vs. twosided case - result = np.angle(result) - if mode == "phase": - # we unwrap the phase here to handle the onesided vs. twosided case - result = np.unwrap(result, axis=0) - results.append(np.real(result)) - - if results: - lastresult = np.hstack(results) - t_x = lastresult.shape[0] * lastresult.shape[1] - t = np.arange(NFFT / 2, t_x - NFFT / 2 + 1, NFFT - noverlap) / Fs - freqs = fftfreq(pad_to, 1 / Fs)[:numFreqs] - # center the frequency range at zero - freqs = np.roll(freqs, -freqcenter, axis=0) - lastresult = np.roll(lastresult, -freqcenter, axis=0) - return lastresult, freqs, t - return (None, None, None) - - -def specgram( - x, - NFFT=None, - Fs=None, - Fc=None, - detrend=None, - window=None, - noverlap=None, - xextent=None, - pad_to=None, - scale_by_freq=None, - mode=None, - scale=None, - skip_fft=False, -): - if NFFT is None: - NFFT = 256 # same default as in mlab.specgram() - if Fc is None: - Fc = 0 # same default as in mlab._spectral_helper() - if noverlap is None: - noverlap = 128 # same default as in mlab.specgram() - if Fs is None: - Fs = 2 # same default as in mlab._spectral_helper() - - if mode == "complex": - raise ValueError("Cannot plot a complex specgram") - - if scale is None or scale == "default": - if mode in ["angle", "phase"]: - scale = "linear" - else: - scale = "dB" - elif mode in ["angle", "phase"] and scale == "dB": - raise ValueError("Cannot use dB scale with angle or phase mode") - - spec, freqs, t = spectral_helper( - x=x, - NFFT=NFFT, - Fs=Fs, - detrend_func=detrend, - window=window, - noverlap=noverlap, - pad_to=pad_to, - scale_by_freq=scale_by_freq, - mode=mode, - skip_fft=skip_fft, - ) - if scale == "linear": - Z = spec - elif scale == "dB": - if mode is None or mode == "default" or mode == "psd": - Z = 10.0 * np.log10(spec) - else: - Z = 20.0 * np.log10(spec) - else: - raise ValueError(f"Unknown scale {scale!r}") - - Z = np.flipud(Z) - - if xextent is None: - # padding is needed for first and last segment: - pad_xextent = (NFFT - noverlap) / Fs / 2 - xextent = np.min(t) - pad_xextent, np.max(t) + pad_xextent - xmin, xmax = xextent - freqs += Fc - freqs /= 1e6 - extent = xmin, xmax, freqs[0], freqs[-1] - - return Z, extent - - -def plot_spectrogram( - x, - spectrogram_filename, - nfft, - fs, - fc, - cmap, - ytics, - bare, - noverlap, - skip_fft, - width, - height, - dpi, -): - fig = plt.figure() - fig.set_size_inches(width, height) - axes = fig.add_subplot(111) - axes.set_xlabel("time (s)") - axes.set_ylabel("freq (MHz)") - Z, extent = specgram( - x, NFFT=nfft, Fs=fs, Fc=fc, noverlap=noverlap, skip_fft=skip_fft - ) - im = axes.imshow(Z, cmap=cmap, extent=extent, origin="upper") - axes.axis("auto") - axes.minorticks_on() - plt.locator_params(axis="y", nbins=ytics) - - if bare: - axes.set_axis_off() - plt.subplots_adjust(top=1, bottom=0, right=1, left=0, hspace=0, wspace=0) - plt.margins(0, 0) - axes.xaxis.set_major_locator(plt.NullLocator()) - axes.yaxis.set_major_locator(plt.NullLocator()) - - plt.sci(im) - plt.savefig(spectrogram_filename, dpi=dpi) - print(f"wrote {spectrogram_filename}") - # must call this in specific order to avoid pyplot leak - # axes.images.remove(im) - im.remove() - fig.clear() - plt.close() - plt.cla() - plt.clf() - - -def process_recording(args, recording): - meta = parse_filename(recording) - center_frequency = meta["center_frequency"] - sample_rate = int(meta["sample_rate"]) - sample_len = int(meta["sample_len"]) - sample_dtype = meta["sample_dtype"] - spectrogram_filename = replace_ext(recording, args.iext, all_ext=True) - if args.skip_exist and os.path.exists(spectrogram_filename): - print(f"skipping {recording}") - return - if is_fft(recording): - if not args.skip_fft: - print(f"skipping precomputed FFT {recording}") - return - else: - if args.skip_fft: - print(f"{recording} not a precomputed FFT, skipping") - return - print(f"processing {recording}") - samples = read_recording( - recording, - sample_rate, - sample_dtype, - sample_len, - skip_sample_secs=args.skip_sample_secs, - max_sample_secs=args.max_sample_secs, - ) - plot_spectrogram( - samples, - spectrogram_filename, - args.nfft, - sample_rate, - center_frequency, - args.cmap, - args.ytics, - args.bare, - args.noverlap, - args.skip_fft, - args.width, - args.height, - args.dpi, - ) - - -def process_all_recordings(args): - if os.path.isdir(args.recording): - recordings = get_nondot_files(args.recording) - else: - recordings = [args.recording] - if args.workers == 1: - for recording in sorted(recordings): - process_recording(args, recording) - else: - with concurrent.futures.ProcessPoolExecutor( - max_workers=args.workers - ) as executor: - for recording in sorted(recordings): - executor.submit(process_recording, args, recording) - executor.shutdown(wait=True) - - -def argument_parser(): - parser = argparse.ArgumentParser(description="draw spectrogram from recording") - parser.add_argument( - "recording", default="", type=str, help="filename of recording, or directory" - ) - parser.add_argument( - "--nfft", default=int(2048), type=int, help="number of FFT points" - ) - parser.add_argument("--ytics", default=20, type=int, help="number of y tics") - # https://ai.googleblog.com/2019/08/turbo-improved-rainbow-colormap-for.html (turbo scheme suggested for ML). - # yellow signal > blue signal. - parser.add_argument( - "--cmap", - default="turbo_r", - type=str, - help="pyplot colormap (see https://matplotlib.org/stable/tutorials/colors/colormaps.html)", - ) - parser.add_argument("--bare", dest="bare", action="store_true") - parser.add_argument("--no-bare", dest="bare", action="store_false") - parser.add_argument( - "--iext", - dest="iext", - default="png", - type=str, - help="extension (image type) to use for spectrogram", - ) - parser.add_argument( - "--noverlap", - dest="noverlap", - default=0, - type=int, - help="number of overlapping FFT windows", - ) - parser.add_argument( - "--workers", - dest="workers", - default=1, - type=int, - help="number of parallel workers", - ) - parser.add_argument( - "--skip-exist", - dest="skip_exist", - action="store_true", - help="skip existing images", - ) - parser.add_argument( - "--no-skip-exist", - dest="skip_exist", - action="store_false", - help="overwrite existing images", - ) - parser.add_argument( - "--skip-fft", dest="skip_fft", action="store_true", help="skip FFT" - ) - parser.add_argument( - "--no-skip-fft", dest="skip_fft", action="store_false", help="calculate FFT" - ) - parser.add_argument( - "--loop", dest="loop", default=0, type=int, help="if > 0, run in a loop" - ) - parser.add_argument("--width", default=11, type=int, help="plot width") - parser.add_argument("--height", default=8, type=int, help="plot height") - parser.add_argument("--dpi", default=100, type=int, help="plot DPI") - parser.add_argument( - "--skip_sample_secs", - default=0, - type=float, - help="skip n seconds worth of samples (default skip none)", - ) - parser.add_argument( - "--max_sample_secs", - default=0, - type=float, - help="max n seconds worth of samples (default all samples)", - ) - parser.set_defaults(bare=False, skip_exist=False, skip_fft=False) - return parser - - -def main(): - parser = argument_parser() - args = parser.parse_args() - while True: - process_all_recordings(args) - if not args.loop: - break - time.sleep(args.loop) diff --git a/gamutrf/waterfall_samples.py b/gamutrf/waterfall_samples.py deleted file mode 100644 index b75f12e8..00000000 --- a/gamutrf/waterfall_samples.py +++ /dev/null @@ -1,254 +0,0 @@ -import argparse -import datetime -import os -import re -import numpy as np -from scipy import signal -import matplotlib.pyplot as plt -from gamutrf.utils import is_fft -from gamutrf.sample_reader import get_reader, parse_filename - - -def read_samples(filename, sample_dtype, sample_bytes, seek_bytes=0, nfft=None, n=None): - reader = get_reader(filename) - - # with reader(filename) as infile: - # infile.seek(int(seek_bytes)) - # sample_buffer_all = infile.readall() - - with reader(filename) as infile: - infile.seek(int(seek_bytes)) - # print(f"{n=}") - # print(f"{nfft=}") - # print(f"{sample_bytes=}") - sample_buffer = infile.read(n * nfft * sample_bytes) - - # print(f"{len(sample_buffer)=}, {len(sample_buffer_all)=}") - # print(len(sample_buffer) == len(sample_buffer_all)) - buffered_samples = int(len(sample_buffer) / sample_bytes) - - if buffered_samples == 0: - print(filename) - return None - if buffered_samples / nfft != n: - print("incomplete") - # return None - - x1d = np.frombuffer(sample_buffer, dtype=sample_dtype, count=buffered_samples) - return x1d["i"] + np.csingle(1j) * x1d["q"] - - -def argument_parser(): - parser = argparse.ArgumentParser(description="Waterfall plotter from scan data") - parser.add_argument( - "--sample_dir", type=str, help="Directory with sample zst files." - ) - parser.add_argument( - "--min_freq", type=float, help="Minimum frequency for plotting." - ) - parser.add_argument( - "--max_freq", type=float, help="Maximum frequency for plotting." - ) - parser.add_argument( - "--sampling_rate", default=100e6, type=float, help="Sampling rate." - ) - parser.add_argument("--nfft", default=256, type=int, help="FFT length.") - parser.add_argument( - "--write_samples", - default=2048, - type=int, - help="Number of samples written during scan.", - ) - - return parser - - -def main(): - # ARG PARSE PARAMETERS - parser = argument_parser() - args = parser.parse_args() - sample_dir = args.sample_dir - min_freq = args.min_freq - max_freq = args.max_freq - nfft = args.nfft - n = args.write_samples - sps = args.sampling_rate - - noverlap = nfft // 8 - db_min = -220 - db_max = -70 - - cmap = plt.get_cmap("turbo") - - plot_min_freq = min_freq # freq - (sps/2) - plot_max_freq = max_freq # freq + (sps/2) - - freq_resolution = sps / nfft - max_idx = round((max_freq - min_freq) / freq_resolution) - total_time = (nfft * n) / sps - expected_time_bins = int((nfft * n) / (nfft - noverlap)) - X, Y = np.meshgrid( - np.linspace( - plot_min_freq, - plot_max_freq, - int((max_freq - min_freq) / freq_resolution + 1), - ), - np.linspace(0, total_time, expected_time_bins), - ) - freq_bin_vals = X[0] - # print(f"{freq_bin_vals.shape=}{freq_bin_vals=}") - - fig = plt.figure(figsize=(28, 10), dpi=100) - ax = fig.add_subplot(1, 1, 1) - box = ax.get_position() - ax.set_position([box.x0, box.y0, box.width * 0.95, box.height]) - title = ax.text(0.5, 1.02, "", transform=ax.transAxes, va="center", ha="center") - sm = plt.cm.ScalarMappable(cmap=cmap) - sm.set_clim(vmin=db_min, vmax=db_max) - cbar_ax = fig.add_axes([0.87, 0.250, 0.03, 0.5]) - cbar = fig.colorbar(sm, cax=cbar_ax) - cbar.set_label("dB", rotation=0) - - spec_data = np.empty(X.shape) - spec_data.fill(np.nan) - mesh = ax.pcolormesh(X, Y, spec_data, shading="nearest") - - plt.show(block=False) - plt.pause(0.1) - background = fig.canvas.copy_from_bbox(fig.bbox) - ax.draw_artist(mesh) - fig.canvas.blit(ax.bbox) - - processed_files = [] - while True: - sample_files = [ - f - for f in sorted(os.listdir(sample_dir)) - if f.startswith("sample") and f.endswith(".zst") - ] - - needs_processing = [] - processing_batch = [] - for f in sample_files: - f = os.path.join(sample_dir, f) - # center_frequency, sample_rate, sample_dtype, sample_bytes, sample_type, sample_bits, _, timestamp = parse_filename(f) - file_info = parse_filename(f) - center_frequency = file_info["center_frequency"] - sample_rate = file_info["sample_rate"] - if ( - ( - ((center_frequency + (sample_rate / 2)) >= min_freq) - and ((center_frequency + (sample_rate / 2)) <= max_freq) - ) - or ( - ((center_frequency - (sample_rate / 2)) >= min_freq) - and ((center_frequency - (sample_rate / 2)) <= max_freq) - ) - ) and f not in processed_files: - if ( - not processing_batch - or processing_batch[-1]["center_frequency"] < center_frequency - ): - processing_batch.append(file_info) - else: - needs_processing.append(processing_batch) - processing_batch = [file_info] - - # for n in needs_processing: - # print(f"{len(n)=}\n{n=}\n\n") - - # process files - if needs_processing: - # f = needs_processing[0][0]["filename"] - # print(f"{f=}") - spec_data.fill(np.nan) - for file_info in needs_processing[0]: - filename = file_info["filename"] - sample_dtype = file_info["sample_dtype"] - sample_bytes = file_info["sample_len"] - center_frequency = file_info["center_frequency"] - sample_rate = file_info["sample_rate"] - sample_type = file_info["sample_type"] - sample_bits = file_info["sample_bits"] - timestamp = file_info["timestamp"] - # filename, center_frequency, sample_rate, sample_dtype, sample_bytes, sample_type, sample_bits, _, timestamp = parse_filename(f) - - samples = read_samples( - filename, sample_dtype, sample_bytes, seek_bytes=0, nfft=nfft, n=n - ) - if samples is None: - continue - freq_bins, t_bins, S = signal.spectrogram( - samples, - sample_rate, - window=signal.hann(int(nfft), sym=True), - nperseg=nfft, - noverlap=noverlap, - detrend="constant", - return_onesided=False, - ) - freq_bins = np.fft.fftshift(freq_bins) - # print(f"{freq_bins.shape=}{center_frequency + freq_bins=}") - - idx = np.array( - [ - round((item - min_freq) / freq_resolution) - for item in freq_bins + center_frequency - ] - ).astype(int) - # print(f"{idx=}") - # print(f"{np.where(idx>=0)}") - # print(f"{(freq_bins+center_frequency)[np.where(idx>=0)]=}") - # print(f"{freq_bins.shape=}, {S.shape=}") - - S = np.fft.fftshift(S, axes=0) - S = S.T - S = 10 * np.log10(S) - # S_norm = (S-np.min(S))/(np.max(S) - np.min(S)) - print(f"{np.min(S)=}, {np.max(S)=}") - S_norm = (S - db_min) / (db_max - db_min) - # plt.figure() - # plt.pcolormesh(t_bins, freq_bins, S) - # plt.show() - # time.sleep(10) - # print(f"{filename=}, {round((max_freq-min_freq)/freq_resolution)=}") - # print(f"{np.flatnonzero(idx>=0)=}") - # print(f"{idx[np.flatnonzero(idx>=0)]=}") - spec_data[ - : S_norm.shape[0], - idx[np.flatnonzero((idx >= 0) & (idx <= max_idx))], - ] = S_norm[:, np.flatnonzero((idx >= 0) & (idx <= max_idx))] - processed_files.append(filename) - - fig.canvas.restore_region(background) - # spec_data = np.empty(X.shape) - - try: - mesh.set_array(cmap(spec_data)) - except Exception as e: - print(f"{e}") - continue - # print(f"{filename=}, {idx[np.flatnonzero(idx>=0)]=}\n") - title.set_text(str(datetime.datetime.fromtimestamp(timestamp))) - ax.draw_artist(title) - ax.draw_artist(mesh) - fig.canvas.blit(ax.title.axes.figure.bbox) - fig.canvas.blit(fig.bbox) - fig.canvas.flush_events() - # time.sleep(3) - - # print(f"{freq_bins=}") - # print(f"{freq_bins.shape=}") - # print(f"{t_bins=}") - # print(f"{t_bins.shape=}") - - # print(f"{samples.shape=}") - - # print(f"{processed_files=}") - else: - print("waiting") - quit() - - -if __name__ == "__main__": - main() diff --git a/poetry.lock b/poetry.lock index a7ca5b9b..89a6b986 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "astroid" @@ -132,13 +132,13 @@ xcb = ["xcffib (>=1.4.0)"] [[package]] name = "certifi" -version = "2024.2.2" +version = "2024.6.2" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" files = [ - {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"}, - {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"}, + {file = "certifi-2024.6.2-py3-none-any.whl", hash = "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56"}, + {file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"}, ] [[package]] @@ -394,63 +394,63 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"] [[package]] name = "coverage" -version = "7.5.1" +version = "7.5.4" description = "Code coverage measurement for Python" 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'gamutrf.__main__:scan' -gamutrf-specgram = 'gamutrf.__main__:specgram' gamutrf-waterfall = 'gamutrf.__main__:waterfall' gamutrf-worker = 'gamutrf.__main__:worker' diff --git a/specgram.yml b/specgram.yml deleted file mode 100644 index ec6ea867..00000000 --- a/specgram.yml +++ /dev/null @@ -1,27 +0,0 @@ ---- -# On Pi4/Ubuntu, also requires systemd.unified_cgroup_hierarchy=0 added to -# /boot/firmware/cmdline.txt, to fall back to cgroup v1. -version: "3.3" -networks: - gamutrf: -services: - specgram: - restart: always - image: iqtlabs/gamutrf:latest - volumes: - - '${VOL_PREFIX}:/data' - deploy: - resources: - # we would prefer "reservations", but this works only in "swarm" mode. - # see https://github.com/docker/compose/pull/5684 - limits: - cpus: '0.5' - command: - - nice - - '-n' - - '19' - - gamutrf-specgram - - '--loop=10' - - '--skip-exist' - - '--workers=1' - - '/data/gamutrf' diff --git a/tests/test_main.py b/tests/test_main.py index 7cd2548a..a0da6690 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -3,7 +3,6 @@ from gamutrf.__main__ import worker from gamutrf.__main__ import scan -from gamutrf.__main__ import specgram sys.argv.append("-h") @@ -21,10 +20,3 @@ def test_main_scan(): scan() assert pytest_wrapped_e.type == SystemExit assert pytest_wrapped_e.value.code == 0 - - -def test_main_specgram(): - with pytest.raises(SystemExit) as pytest_wrapped_e: - specgram() - assert pytest_wrapped_e.type == SystemExit - assert pytest_wrapped_e.value.code == 0 diff --git a/tests/test_specgram.py b/tests/test_specgram.py deleted file mode 100644 index fff942f3..00000000 --- a/tests/test_specgram.py +++ /dev/null @@ -1,81 +0,0 @@ -#!/usr/bin/python3 -import os -import tempfile -import unittest - -from gamutrf.specgram import process_all_recordings -from gamutrf.sample_reader import parse_filename - - -class FakeArgs: - def __init__( - self, - nfft, - cmap, - ytics, - bare, - noverlap, - iext, - skip_exist, - recording, - workers, - skip_fft, - width, - height, - dpi, - skip_sample_secs, - max_sample_secs, - ): - self.nfft = nfft - self.cmap = cmap - self.ytics = ytics - self.bare = bare - self.noverlap = noverlap - self.iext = iext - self.skip_exist = skip_exist - self.recording = recording - self.workers = workers - self.skip_fft = skip_fft - self.width = width - self.height = height - self.dpi = dpi - self.skip_sample_secs = 0 - self.max_sample_secs = 0 - - -class SpecgramTestCase(unittest.TestCase): - def test_process_recordings(self): - with tempfile.TemporaryDirectory() as tempdir: - recording = os.path.join( - str(tempdir), "testrecording_123_100Hz_1000sps.raw" - ) - meta = parse_filename(recording) - samples = chr(0) * int(meta["sample_len"] * meta["sample_rate"]) - with open(recording, "wb") as f: - f.write(samples.encode("utf8")) - fakeargs = FakeArgs( - 256, - "turbo", - 1, - True, - 0, - "png", - False, - recording, - 2, - True, - 11, - 8, - 100, - 0, - 0, - ) - process_all_recordings(fakeargs) - fakeargs.workers = 1 - fakeargs.skip_exist = False - fakeargs.skip_fft = False - process_all_recordings(fakeargs) - - -if __name__ == "__main__": # pragma: no cover - unittest.main()