def test_values(self):
# first bin maps the ±0.5 interval error, the second the 0
bins = _histogram_bins(2)
ann = np.asarray([0, 1, 2, 3])
# A) identical detections map to the 0 error bin
hist = _error_histogram(np.asarray([0, 1, 2, 3]), ann, bins)
self.assertTrue(np.allclose(hist, [0, 4]))
# bins maps the ±0.5, -0.25, 0, 0.25 interval errors
bins = _histogram_bins(4)
# B) identical detections map to the 0 error bin
hist = _error_histogram(ann, ann, bins)
self.assertTrue(np.allclose(hist, [0, 0, 4, 0]))
# C) offbeat detections map to the ±0.5 error bin
hist = _error_histogram(np.asarray([0.5, 1.5, 2.5, 3.5]), ann, bins)
self.assertTrue(np.allclose(hist, [4, 0, 0, 0]))
# D) smaller deviations mapping to the 0 and 0.125 error bins
hist = _error_histogram(np.asarray([0.125, 0.875, 2.1, 3]), ann, bins)
self.assertTrue(np.allclose(hist, [0, 0, 3, 1]))
# E) default annotations and detections with 40 bins
bins = _histogram_bins(40)
hist = _error_histogram(DETECTIONS, ANNOTATIONS, bins)
self.assertTrue(np.allclose(hist, [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 8, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0]))
def test_values(self):
# first bin maps the ±0.5 interval error, the second the 0
bins = _histogram_bins(2)
ann = np.asarray([0, 1, 2, 3])
# A) identical detections map to the 0 error bin
hist = _error_histogram(np.asarray([0, 1, 2, 3]), ann, bins)
self.assertTrue(np.allclose(hist, [0, 4]))
# bins maps the ±0.5, -0.25, 0, 0.25 interval errors
bins = _histogram_bins(4)
# B) identical detections map to the 0 error bin
hist = _error_histogram(ann, ann, bins)
self.assertTrue(np.allclose(hist, [0, 0, 4, 0]))
# C) offbeat detections map to the ±0.5 error bin
hist = _error_histogram(np.asarray([0.5, 1.5, 2.5, 3.5]), ann, bins)
self.assertTrue(np.allclose(hist, [4, 0, 0, 0]))
# D) smaller deviations mapping to the 0 and 0.125 error bins
hist = _error_histogram(np.asarray([0.125, 0.875, 2.1, 3]), ann, bins)
self.assertTrue(np.allclose(hist, [0, 0, 3, 1]))
# E) default annotations and detections with 40 bins
bins = _histogram_bins(40)
hist = _error_histogram(DETECTIONS, ANNOTATIONS, bins)
self.assertTrue(
np.allclose(hist, [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 8,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
]))
def test_types(self):
bins = _histogram_bins(4)
hist = _error_histogram(DETECTIONS, ANNOTATIONS, bins)
ig = _information_gain(hist)
self.assertIsInstance(ig, float)
def test_types(self):
bins = _histogram_bins(4)
hist = _error_histogram(DETECTIONS, ANNOTATIONS, bins)
self.assertIsInstance(hist, np.ndarray)
self.assertTrue(hist.dtype == np.float)
def test_types(self):
bins = _histogram_bins(4)
hist = _error_histogram(DETECTIONS, ANNOTATIONS, bins)
ig = _information_gain(hist)
self.assertIsInstance(ig, float)
def test_types(self):
bins = _histogram_bins(4)
hist = _error_histogram(DETECTIONS, ANNOTATIONS, bins)
self.assertIsInstance(hist, np.ndarray)
self.assertTrue(hist.dtype == np.float)
