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)