def test_exporters(data_files, tmpdir): from wwb_scanner.scan_objects import Spectrum for fkey, d in data_files.items(): p = tmpdir.mkdir('-'.join((str(f) for f in fkey))) for skey, fn in d.items(): src_spectrum = Spectrum.import_from_file(fn) assert not np.any(np.isnan(src_spectrum.sample_data['magnitude'])) assert not np.any(np.isnan(src_spectrum.sample_data['dbFS'])) for ext in ['csv', 'sdb2']: exp_fn = p.join('{}_src.{}'.format(skey, ext)) src_spectrum.export_to_file(filename=str(exp_fn)) imp_spectrum = Spectrum.import_from_file(str(exp_fn)) # Account for frequency units in KHz for sdb2 assert np.allclose(src_spectrum.sample_data['frequency'], imp_spectrum.sample_data['frequency']) assert np.array_equal(src_spectrum.sample_data['magnitude'], imp_spectrum.sample_data['magnitude'])
def test_exporters(data_files, tmpdir): from wwb_scanner.scan_objects import Spectrum for fkey, d in data_files.items(): p = tmpdir.mkdir('-'.join((str(f) for f in fkey))) for skey, fn in d.items(): src_spectrum = Spectrum.import_from_file(fn) assert not np.any(np.isnan(src_spectrum.sample_data['magnitude'])) assert not np.any(np.isnan(src_spectrum.sample_data['dbFS'])) for ext in ['csv', 'sdb2']: exp_fn = p.join('{}_src.{}'.format(skey, ext)) src_spectrum.export_to_file(filename=str(exp_fn)) imp_spectrum = Spectrum.import_from_file(str(exp_fn)) # Account for frequency units in KHz for sdb2 assert np.allclose(src_spectrum.sample_data['frequency'], imp_spectrum.sample_data['frequency']) # sdb2 stores dB values rounded to the first decimal assert np.array_equal( np.around(src_spectrum.sample_data['dbFS'], 1), np.around(imp_spectrum.sample_data['dbFS'], 1), )
def test_io(tmpdir, random_samples): from wwb_scanner.scan_objects import Spectrum rs = 1.024e6 nsamp = 256 step_size = 0.5e6 freq_range = [572e6, 636e6] def build_data(fc): freqs, sig, Pxx = random_samples(n=nsamp, rs=rs, fc=fc) return freqs, Pxx spectrum = Spectrum(step_size=step_size) spectrum.color['r'] = 1. fc = freq_range[0] while True: freqs, ff = build_data(fc) spectrum.add_sample_set(frequency=freqs, iq=ff) if spectrum.sample_data['frequency'].max() >= freq_range[1] / 1e6: break fc += step_size dB = np.around(spectrum.sample_data['dbFS'], decimals=1) p = tmpdir.mkdir('test_io') for ext in ['csv', 'sdb2']: fn = p.join('foo.{}'.format(ext)) spectrum.export_to_file(filename=str(fn)) imp_spectrum = Spectrum.import_from_file(str(fn)) assert np.allclose(spectrum.sample_data['frequency'], imp_spectrum.sample_data['frequency']) imp_dB = np.around(imp_spectrum.sample_data['dbFS'], decimals=1) assert np.allclose(dB, imp_dB)
def test_io(tmpdir, random_samples): from wwb_scanner.scan_objects import Spectrum rs = 1.024e6 nsamp = 256 step_size = 0.5e6 freq_range = [572e6, 636e6] def build_data(fc): freqs, sig, Pxx = random_samples(n=nsamp, rs=rs, fc=fc) return freqs, Pxx spectrum = Spectrum(step_size=step_size) spectrum.color['r'] = 1. fc = freq_range[0] while True: freqs, ff = build_data(fc) spectrum.add_sample_set(frequency=freqs, iq=ff) if spectrum.sample_data['frequency'].max() >= freq_range[1] / 1e6: break fc += step_size dB = np.around(spectrum.sample_data['dbFS'], decimals=1) p = tmpdir.mkdir('test_io') for ext in ['csv', 'sdb2']: fn = p.join('foo.{}'.format(ext)) spectrum.export_to_file(filename=str(fn)) imp_spectrum = Spectrum.import_from_file(str(fn)) assert np.allclose(spectrum.sample_data['frequency'], imp_spectrum.sample_data['frequency']) imp_dB = np.around(imp_spectrum.sample_data['dbFS'], decimals=1) assert np.allclose(dB, imp_dB)