Add tests.

Author: feilong

tests/test_plotting.py

@@ -0,0 +1,124 @@
+import os
+import numpy as np
+import importlib.util
+from brainplotlib import brain_plot
+
+
+class TestPlotting:
+    def test_icoorder5_masked(self, tmp_path):
+        values = np.arange(9372), np.arange(9370)
+        img = brain_plot(*values, vmax=18741, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder5_masked.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder5_masked_random(self, tmp_path):
+        rng = np.random.default_rng()
+        values = rng.random((9372, )), rng.random((9370, ))
+        img = brain_plot(*values, vmax=1, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder5_masked_random.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder5_nonmasked(self, tmp_path):
+        values = np.arange(10242), np.arange(10242)
+        img = brain_plot(*values, vmax=20483, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder5_nonmasked.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder5_nonmasked_random(self, tmp_path):
+        rng = np.random.default_rng()
+        values = rng.random((10242, )), rng.random((10242, ))
+        img = brain_plot(*values, vmax=1, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder5_nonmasked_random.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder3_masked(self, tmp_path):
+        values = np.arange(588), np.arange(587)
+        img = brain_plot(*values, vmax=1174, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder3_masked.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder3_masked_random(self, tmp_path):
+        rng = np.random.default_rng()
+        values = rng.random((588, )), rng.random((587, ))
+        img = brain_plot(*values, vmax=1, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder3_masked_random.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder3_nonmasked(self, tmp_path):
+        values = np.arange(642), np.arange(642)
+        img = brain_plot(*values, vmax=1283, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder3_nonmasked.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_icoorder3_nonmasked(self, tmp_path):
+        rng = np.random.default_rng()
+        values = rng.random((642, )), rng.random((642, ))
+        img = brain_plot(*values, vmax=1, vmin=0, cmap=None)
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_icoorder3_nonmasked_random.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+
+class TestColormaps:
+    def test_bwr_cmap(self, tmp_path):
+        rng = np.random.default_rng()
+        values = rng.random((588, )), rng.random((587, ))
+        img = brain_plot(*values, vmax=1, vmin=0, cmap='bwr')
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_bwr_cmap.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])
+
+    def test_jet_cmap(self, tmp_path):
+        rng = np.random.default_rng()
+        values = rng.random((588, )), rng.random((587, ))
+        img = brain_plot(*values, vmax=1, vmin=0, cmap='jet')
+        assert img.shape in [(1560, 1728, 4), (1560, 1728, 3)]
+        assert img.dtype == np.float64
+        assert np.all(img <= 1)
+        assert np.all(img >= 0)
+        if importlib.util.find_spec('cv2'):
+            import cv2
+            cv2.imwrite(os.path.join(tmp_path, 'test_jet_cmap.png'), np.round(img * 255).astype(np.uint8)[:, :, [2, 1, 0, 3]])

tests/test_unmask_upsample.py

@@ -0,0 +1,46 @@
+import numpy as np
+from brainplotlib import prepare_data, unmask_and_upsample
+
+
+class TestUnmaskUpsample:
+    def test_icoorder5_masked(self):
+        lh = np.arange(9372)
+        rh = np.arange(9370) + 9372
+        values = unmask_and_upsample(lh, rh, 'fsaverage', 5, True)
+        assert np.nanmin(values) == 0
+        assert np.nanmax(values) == 18741
+        assert np.any(np.isnan(values))
+
+    def test_icoorder5_nonmasked(self):
+        lh = np.arange(10242)
+        rh = np.arange(10242) + 10242
+        values = unmask_and_upsample(lh, rh, 'fsaverage', 5, False)
+        assert values.min() == 0
+        assert values.max() == 20483
+        assert np.all(np.isfinite(values))
+
+
+class TestPrepareData:
+    def test_tuple_input(self):
+        lh = np.arange(9372)
+        rh = np.arange(9370) + 9372
+        values = prepare_data((lh, rh))
+        assert values.shape == (327684, )
+
+    def test_list_input(self):
+        lh = np.arange(9372)
+        rh = np.arange(9370) + 9372
+        values = prepare_data([lh, rh])
+        assert values.shape == (327684, )
+
+    def test_serial_input(self):
+        lh = np.arange(9372)
+        rh = np.arange(9370) + 9372
+        values = prepare_data(lh, rh)
+        assert values.shape == (327684, )
+
+    def test_concatenated_input(self):
+        lh = np.arange(9372)
+        rh = np.arange(9370) + 9372
+        values = prepare_data(np.concatenate([lh, rh], axis=0))
+        assert values.shape == (327684, )