def test_mean_hologram_value(self):
accumulator = Accumulator()
data = _load_example_data_backgrounds()
for holo in data:
accumulator.push(holo)
numpy_mean = np.mean([holo.values for holo in data], axis=0)
self.assertTrue(np.allclose(numpy_mean, accumulator.mean().values))
def test_mean_hologram_type(self):
import xarray
expected_type = xarray.core.dataarray.DataArray
accumulator = Accumulator()
data = _load_example_data_backgrounds()
for holo in data:
accumulator.push(holo)
self.assertTrue(isinstance(accumulator.mean(), expected_type))
def test_calculate_hologram_noise_sd(self):
accumulator = Accumulator()
refimg = _load_raw_example_data()
paths = get_example_data_path(['bg01.jpg', 'bg02.jpg', 'bg03.jpg'])
bg = load_average(paths, refimg)
# This value is from the legacy version of load_average
self.assertTrue(np.allclose(bg.noise_sd, 0.00709834))
def test_cv_no_data(self):
accumulator = Accumulator()
self.assertTrue(accumulator.cv() is None)
def test_cv(self):
accumulator = Accumulator()
data = np.arange(10)
for point in data:
accumulator.push(point)
self.assertTrue(accumulator.cv() == np.std(data) / np.mean(data))
def test_std_no_data(self):
accumulator = Accumulator()
self.assertTrue(accumulator._std() is None)
def test_push_hologram(self):
accumulator = Accumulator()
data = _load_example_data_backgrounds()
for holo in data:
accumulator.push(holo)
self.assertTrue(accumulator._n == 3)
def test_push(self):
accumulator = Accumulator()
data = np.arange(10)
for point in data:
accumulator.push(point)
self.assertTrue(accumulator._n == 10)