def test_time_broadcast():
obs = '1061313128_99bl_1pol_half_time'
insfile = os.path.join(DATA_PATH, f'{obs}_SSINS.h5')
out_prefix = os.path.join(DATA_PATH, f'{obs}_test')
match_outfile = f'{out_prefix}_SSINS_match_events.yml'
ins = INS(insfile)
# Mock a simple metric_array and freq_array
ins.metric_array[:] = 1
ins.weights_array = np.copy(ins.metric_array)
ins.weights_square_array = np.copy(ins.weights_array)
ins.metric_ms = ins.mean_subtract()
ins.sig_array = np.ma.copy(ins.metric_ms)
# Arbitrarily flag enough data in channel 10
sig_thresh = {'narrow': 5}
mf = MF(ins.freq_array, sig_thresh, streak=False, tb_aggro=0.5)
ins.metric_array[4:, 9] = np.ma.masked
ins.metric_array[4:, 10] = np.ma.masked
# Put in an outlier so it gets to samp_thresh_test
ins.metric_array[2, 9] = 100
ins.metric_array[1, 10] = 100
ins.metric_ms = ins.mean_subtract()
bool_ind = np.zeros(ins.metric_array.shape, dtype=bool)
bool_ind[:, 10] = 1
bool_ind[:, 9] = 1
mf.apply_match_test(ins, event_record=True, time_broadcast=True)
print(ins.match_events)
test_match_events = [
(slice(1, 2), slice(10, 11),
'narrow_%.3fMHz' % (ins.freq_array[10] * 10**(-6))),
(slice(0, ins.Ntimes), slice(10, 11),
'time_broadcast_narrow_%.3fMHz' % (ins.freq_array[10] * 10**(-6))),
(slice(2, 3), slice(9, 10),
'narrow_%.3fMHz' % (ins.freq_array[9] * 10**(-6))),
(slice(0, ins.Ntimes), slice(9, 10),
'time_broadcast_narrow_%.3fMHz' % (ins.freq_array[9] * 10**(-6)))
]
# Test stuff
assert np.all(
ins.metric_array.mask == bool_ind), "The right flags were not applied"
for i, event in enumerate(test_match_events):
assert ins.match_events[
i][:-1] == event, "The events weren't appended correctly"
# Test that writing with samp_thresh flags is OK
ins.write(out_prefix, output_type='match_events')
test_match_events_read = ins.match_events_read(match_outfile)
os.remove(match_outfile)
assert ins.match_events == test_match_events_read
# Test that exception is raised when tb_aggro is too high
with pytest.raises(ValueError):
mf = MF(ins.freq_array, {'narrow': 5, 'streak': 5}, tb_aggro=100)
mf.apply_samp_thresh_test(ins, (slice(1, 2), slice(10, 11), 'narrow'))
def test_samp_thresh():
obs = '1061313128_99bl_1pol_half_time'
insfile = os.path.join(DATA_PATH, '%s_SSINS.h5' % obs)
out_prefix = os.path.join(DATA_PATH, '%s_test' % obs)
match_outfile = '%s_SSINS_match_events.yml' % out_prefix
ins = INS(insfile)
# Mock a simple metric_array and freq_array
ins.metric_array = np.ma.ones([10, 20, 1])
ins.weights_array = np.copy(ins.metric_array)
ins.metric_ms = ins.mean_subtract()
ins.sig_array = np.ma.copy(ins.metric_ms)
ins.freq_array = np.zeros([1, 20])
ins.freq_array = np.arange(20)
# Arbitrarily flag enough data in channel 10
sig_thresh = {'narrow': 5}
mf = MF(ins.freq_array, sig_thresh, streak=False, N_samp_thresh=5)
ins.metric_array[3:, 10] = np.ma.masked
ins.metric_array[3:, 9] = np.ma.masked
# Put in an outlier so it gets to samp_thresh_test
ins.metric_array[0, 11] = 10
ins.metric_ms = ins.mean_subtract()
bool_ind = np.zeros(ins.metric_array.shape, dtype=bool)
bool_ind[:, 10] = 1
bool_ind[:, 9] = 1
bool_ind[0, 11] = 1
mf.apply_match_test(ins, event_record=True, apply_samp_thresh=True)
test_match_events = [(0, slice(11, 12), 'narrow')]
test_match_events += [(ind, slice(9, 10), 'samp_thresh')
for ind in range(3)]
test_match_events += [(ind, slice(10, 11), 'samp_thresh')
for ind in range(3)]
# Test stuff
assert np.all(
ins.metric_array.mask == bool_ind), "The right flags were not applied"
for i, event in enumerate(test_match_events):
assert ins.match_events[
i][:-1] == event, "The events weren't appended correctly"
# Test that writing with samp_thresh flags is OK
ins.write(out_prefix, output_type='match_events')
test_match_events_read = ins.match_events_read(match_outfile)
os.remove(match_outfile)
assert ins.match_events == test_match_events_read
# Test that exception is raised when N_samp_thresh is too high
with pytest.raises(ValueError):
mf = MF(ins.freq_array, {'narrow': 5, 'streak': 5}, N_samp_thresh=100)
mf.apply_samp_thresh_test(ins)
