def test_threshold_data():
data = np.arange(-3, 4)
# Check that an 'auto' threshold leaves at least one element
data_t, mask, thresh = html_stat_map._threshold_data(data,
threshold='auto')
gtruth_m = np.array([False, True, True, True, True, True, False])
gtruth_d = np.array([-3, 0, 0, 0, 0, 0, 3])
assert (mask == gtruth_m).all()
assert (data_t == gtruth_d).all()
# Check that threshold=None keeps everything
data_t, mask, thresh = html_stat_map._threshold_data(data, threshold=None)
assert np.all(np.logical_not(mask))
assert np.all(data_t == data)
# Check positive threshold works
data_t, mask, thresh = html_stat_map._threshold_data(data, threshold=1)
gtruth = np.array([False, False, True, True, True, False, False])
assert (mask == gtruth).all()
# Check 0 threshold works
data_t, mask, thresh = html_stat_map._threshold_data(data, threshold=0)
gtruth = np.array([False, False, False, True, False, False, False])
assert (mask == gtruth).all()
# Check that overly lenient threshold returns array
data = np.arange(3, 10)
data_t, mask, thresh = html_stat_map._threshold_data(data, threshold=2)
gtruth = np.full(7, False)
assert (mask == gtruth).all()
def test_threshold_data():
data = np.arange(-3, 4)
# Check that an 'auto' threshold leaves at least one element
data_t, thresh = html_stat_map._threshold_data(data, threshold='auto')
gtruth = np.array([False, True, True, True, True, True, False])
assert (data_t.mask == gtruth).all()
# Check that threshold=None keeps everything
data_t, thresh = html_stat_map._threshold_data(data, threshold=None)
assert ~np.ma.is_masked(data_t)
# Check positive threshold works
data_t, thresh = html_stat_map._threshold_data(data, threshold=1)
gtruth = np.array([False, False, True, True, True, False, False])
assert (data_t.mask == gtruth).all()
# Check 0 threshold works
data_t, thresh = html_stat_map._threshold_data(data, threshold=0)
gtruth = np.array([False, False, False, True, False, False, False])
assert (data_t.mask == gtruth).all()
def test_threshold_data():
data = np.arange(-3, 4)
# Check that an 'auto' threshold leaves at least one element
data_t, thresh = html_stat_map._threshold_data(data, threshold='auto')
gtruth = np.array([False, True, True, True, True, True, False])
assert (data_t.mask == gtruth).all()
# Check that threshold=None keeps everything
data_t, thresh = html_stat_map._threshold_data(data, threshold=None)
assert ~np.ma.is_masked(data_t)
# Check positive threshold works
data_t, thresh = html_stat_map._threshold_data(data, threshold=1)
gtruth = np.array([False, False, True, True, True, False, False])
assert (data_t.mask == gtruth).all()
# Check 0 threshold works
data_t, thresh = html_stat_map._threshold_data(data, threshold=0)
gtruth = np.array([False, False, False, True, False, False, False])
assert (data_t.mask == gtruth).all()
