add test for pixel-wise interpolation
@@ -78,6 +78,12 @@ class TestInterpolation(unittest.TestCase):
result_len=68, img_min=0.0, img_max=10.0, img_mean=0.720405,
img_median=0.59765935),
+ cls.InterpolationTestCase('linear-p', LinearInterpolation('NDVI', result_interval=(0.0, 1.0),
+ mask_feature=(FeatureType.MASK, 'IS_VALID'),
+ unknown_value=10, interpolate_pixel_wise=True),
+ result_len=68, img_min=0.0, img_max=10.0, img_mean=0.720405,
+ img_median=0.59765935),
+
cls.InterpolationTestCase('linear_change_timescale',
LinearInterpolation('NDVI', result_interval=(0.0, 1.0),
mask_feature=(FeatureType.MASK, 'IS_VALID'),
@@ -107,6 +113,13 @@ class TestInterpolation(unittest.TestCase):
result_len=1, img_min=-0.032482587, img_max=0.701796, img_mean=0.42080238,
img_median=0.42889267),
+ cls.InterpolationTestCase('bspline-p', BSplineInterpolation('NDVI', unknown_value=-3,
+ mask_feature=(FeatureType.MASK, 'IS_VALID'),
+ resample_range=('2017-01-01', '2017-02-01', 50),
+ spline_degree=5, interpolate_pixel_wise=True),
+ result_len=1, img_min=-0.032482587, img_max=0.701796, img_mean=0.42080238,
+ img_median=0.42889267),
+
cls.InterpolationTestCase('akima', AkimaInterpolation('NDVI', unknown_value=0,
mask_feature=(FeatureType.MASK, 'IS_VALID')),
result_len=68, img_min=-0.13793105, img_max=0.860242, img_mean=0.53159297,
