Commit 8452b82e authored by Gavin's avatar Gavin
Browse files

updated test's to test for correct data and pass

parent 3db2570f

autocnet/matcher/mutual_information.py

+5 −5
Original line number Diff line number Diff line
@@ -37,6 +37,8 @@ def mutual_information(reference_roi, moving_roi, affine=AffineTransform(), **kw 
    reference_image = reference_roi.clip()

    walking_template = moving_roi.clip()



    # print(f"\nShape's \n{reference_image.shape}\n{walking_template.shape}\n--------")

    

    # if reference_roi.ndv == None or moving_roi.ndv == None:

    if np.isnan(reference_image).any() or np.isnan(walking_template).any():

        raise Exception('Unable to process due to NaN values in the input data')
@@ -99,8 +101,8 @@ def mutual_information_match(d_template, s_image, subpixel_size=3, 
        func = mutual_information





    image_size = (s_image.size_x * 2, s_image.size_y * 2)

    template_size = (d_template.size_x * 2, d_template.size_y * 2)

    image_size = ((s_image.size_x * 2) + 1, (s_image.size_y * 2) + 1)

    template_size = ((d_template.size_x * 2) + 1, (d_template.size_y * 2) + 1)



    y_diff = image_size[0] - template_size[0]

    x_diff = image_size[1] - template_size[1]
@@ -119,7 +121,6 @@ def mutual_information_match(d_template, s_image, subpixel_size=3, 


    for i in range(starting_y, ending_y):

        for j in range(starting_x, ending_x):



            s_image.x = (j)

            s_image.y = (i)
@@ -154,4 +155,3 @@ def mutual_information_match(d_template, s_image, subpixel_size=3, 
    x += subpixel_x_shift

    new_affine = AffineTransform(translation=(-x, -y))

    return new_affine, float(max_corr), corr_map
 
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    # return float(x), float(y), float(max_corr), corr_map
 
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autocnet/matcher/tests/test_mutual_information.py

+5 −20
Original line number Diff line number Diff line
@@ -21,31 +21,16 @@ def test_bad_mi(): 
    assert corrilation == pytest.approx(0)



def test_mutual_information():

    d_template = np.array([[i for i in range(50, 100)] for j in range(50)])

    s_image = np.ones((100, 100))



    s_image[25:75, 25:75] = d_template



    d_template = Roi(d_template, 25, 25, 25, 25, ndv=22222222)

    s_image = Roi(s_image, 50, 50, 25, 25, ndv=22222222)

    affine, max_corr, corr_map = mutual_information.mutual_information_match(d_template, s_image, bins=20)



    assert max_corr == 2.9755967600033015

    assert corr_map.shape == (50, 50)

    assert np.min(corr_map) >= 0.0

    #TODO add assert test for affine and odd sized s_image 



def test_mutual_information_odd_sized_s_image():

    d_template = np.array([[i for i in range(50, 101)] for j in range(51)])

    s_image = np.ones((101, 101))



    s_image[25:76, 25:76] = d_template



    d_template = Roi(d_template, 26, 26, 26, 26, ndv=22222222)

    s_image = Roi(s_image, 51, 51, 26, 26, ndv=22222222)

    d_template = Roi(d_template, 25, 25, 25, 25, ndv=22222222)

    s_image = Roi(s_image, 50, 50, 25, 25, ndv=22222222)

    affine, max_corr, corr_map = mutual_information.mutual_information_match(d_template, s_image, bins=20)



    assert max_corr == 2.9755967600033015

    assert affine.params[0][2] == -0.45017566300973355

    assert affine.params[1][2] == -0.5000000000000002

    assert max_corr == 2.9763186763296856

    assert corr_map.shape == (51, 51)

    assert np.min(corr_map) >= 0.0
 
    
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autocnet/transformation/roi.py

+1 −1
Original line number Diff line number Diff line
@@ -162,7 +162,7 @@ class Roi(): 
        """

        pixels = self.image_extent

        if isinstance(self.data, np.ndarray):

            data = self.data[pixels[2]:pixels[3],pixels[0]:pixels[1]]

            data = self.data[pixels[2]:pixels[3]+1,pixels[0]:pixels[1]+1]

        else:

            # Have to reformat to [xstart, ystart, xnumberpixels, ynumberpixels]

            # TODO: I think this will result in an incorrect obj.center when the passed data is a GeoDataset