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'''
Runs unit tests for various SPy spatial functions.
To run the unit tests, type the following from the system command line:
# python -m spectral.tests.spatial
'''
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
from numpy.testing import assert_allclose
from warnings import warn
import spectral as spy
from spectral.algorithms.spatial import (get_window_bounds,
get_window_bounds_clipped,
map_class_ids, map_classes,
map_window)
from spectral.tests.spytest import SpyTest
class SpatialWindowTest(SpyTest):
'''Tests various spatial functions.'''
def setup(self):
self.data = spy.open_image('92AV3C.lan').load()
def test_get_window_bounds(self):
assert(get_window_bounds(90, 90, 3, 7, 30, 40) == (29, 32, 37, 44))
def test_get_window_bounds_border(self):
assert(get_window_bounds(90, 90, 3, 7, 0, 2) == (0, 3, 0, 7))
def test_get_window_bounds_clipped(self):
assert(get_window_bounds_clipped(90, 90, 3, 7, 30, 40) \
== (29, 32, 37, 44))
def test_get_window_bounds_clipped_border(self):
assert(get_window_bounds_clipped(90, 90, 3, 7, 0, 2) == (0, 2, 0, 6))
def test_map_window(self):
'''Test computing spectra average over local window.'''
f = lambda X, ij: np.mean(X.reshape((-1, X.shape[-1])), axis=0)
X = self.data
y = map_window(f, X, (3, 5), (10, 50), (20, 40))
t = np.mean(X[9:12, 18:23].reshape((-1, X.shape[-1])), axis=0)
assert_allclose(y[0, 0], t)
def test_map_window_clipped(self):
'''Test spatial averaging near border with clipped window.'''
f = lambda X, ij: np.mean(X.reshape((-1, X.shape[-1])), axis=0)
X = self.data
y = map_window(f, X, (3, 5), (100, None), (100, None), border='clip')
t = np.mean(X[-2:, -3:].reshape((-1, X.shape[-1])), axis=0)
assert_allclose(y[-1, -1], t)
def test_map_window_shifted(self):
'''Test spatial averaging near border with shifted window.'''
f = lambda X, ij: np.mean(X.reshape((-1, X.shape[-1])), axis=0)
X = self.data
y = map_window(f, X, (3, 5), (100, None), (100, None), border='shift')
t = np.mean(X[-3:, -5:].reshape((-1, X.shape[-1])), axis=0)
assert_allclose(y[-1, -1], t)
def test_map_window_stepped(self):
'''Test spatial averaging with non-unity row/column step sizes.'''
f = lambda X, ij: np.mean(X.reshape((-1, X.shape[-1])), axis=0)
X = self.data
y = map_window(f, X, (3, 5), (30, 60, 3), (70, 100, 4), border='shift')
t = np.mean(X[32:35, 72:77].reshape((-1, X.shape[-1])), axis=0)
assert_allclose(y[1, 1], t)
class MapClassesTest(SpyTest):
'''Test mapping of class indices between classification images.'''
def setup(self):
self.gt = spy.open_image('92AV3GT.GIS').read_band(0)
def test_map_class_ids_identity(self):
'''Mapping a class image back to itself should yield identity map.'''
gt = np.array(self.gt)
d = map_class_ids(gt, gt)
for i in set(gt.ravel()):
assert(i in d)
for (i, j) in d.items():
assert(j == i)
def test_map_class_ids_identity_unlabeled(self):
'''Mapping a class image back to itself with an unlabeled class.'''
gt = np.array(self.gt)
d = map_class_ids(gt, gt, unlabeled=0)
for i in set(gt.ravel()):
assert(i in d)
for (i, j) in d.items():
assert(j == i)
def test_map_class_ids_identity_multiple_unlabeled(self):
'''Mapping a class image back to itself with unlabeled classes.'''
gt = np.array(self.gt)
d = map_class_ids(gt, gt, unlabeled=[2, 4])
for i in set(gt.ravel()):
assert(i in d)
for (i, j) in d.items():
assert(j == i)
def test_map_class_ids_isomorphic(self):
'''Test map_class_ids with isomorphic classes.'''
gt = np.array(self.gt)
gt2 = gt + 1
d = map_class_ids(gt, gt2)
for (i, j) in d.items():
assert(j == i + 1)
def test_map_class_ids_isomorphic_background(self):
'''Test map_class_ids with isomorphic classes and background arg.'''
gt = np.array(self.gt)
gt2 = gt + 1
d = map_class_ids(gt, gt2, unlabeled=0)
assert(d[0] == 0)
d.pop(0)
for (i, j) in d.items():
assert(j == i + 1)
def test_map_class_ids_src_gt_dest(self):
'''Test map_class_ids with more classes in source image.'''
gt = np.array(self.gt)
(i, j) = (100, 30)
old_label = gt[i, j]
new_label = max(set(gt.ravel())) + 10
gt2 = np.array(gt)
gt2[i, j] = new_label
d = map_class_ids(gt2, gt)
# There are enough pixels for each class that a new single-pixel class
# should not be mapped to one of the existing classes.
assert(d[new_label] not in gt)
d.pop(new_label)
for (i, j) in d.items():
assert(j == i)
def test_map_class_ids_dest_gt_src(self):
'''Test map_class_ids with more classes in dest image.'''
gt = np.array(self.gt)
(i, j) = (100, 30)
old_label = gt[i, j]
new_label = max(set(gt.ravel())) + 10
gt2 = np.array(gt)
gt2[i, j] = new_label
d = map_class_ids(gt, gt2)
for (i, j) in d.items():
assert(j == i)
def test_map_classes_isomorphic(self):
'''map_classes should map isomorphic class image back to original.'''
gt = np.array(self.gt)
gt2 = gt + 1
d = map_class_ids(gt2, gt)
result = map_classes(gt2, d)
assert(np.alltrue(result == gt))
def test_map_fails_allow_unmapped_false(self):
'''map_classes should raise ValueError if image has unmapped value.'''
gt = np.array(self.gt)
gt2 = gt + 1
d = map_class_ids(gt2, gt)
d.pop(1)
try:
result = map_classes(gt2, d)
except ValueError:
pass
else:
assert(False)
def test_map_allow_unmapped_true(self):
'''map_classes should raise ValueError if image has unmapped value.'''
gt = np.array(self.gt)
gt2 = gt + 1
d = map_class_ids(gt2, gt)
d.pop(1)
result = map_classes(gt2, d, allow_unmapped=True)
assert(np.alltrue(result[gt2 == 1] == 1))
def run():
print('\n' + '-' * 72)
print('Running spatial tests.')
print('-' * 72)
for T in [SpatialWindowTest, MapClassesTest]:
T().run()
if __name__ == '__main__':
from spectral.tests.run import parse_args, reset_stats, print_summary
parse_args()
reset_stats()
run()
print_summary()
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