Commit 9851a494 authored by Laura, Jason R's avatar Laura, Jason R
Browse files

Merge branch 'main' into 'main' 

Affine Update Test Fixes

See merge request astrogeology/autocnet!661
parents 05174db4 9011f095

autocnet/graph/tests/test_edge.py

+12 −2
Original line number Diff line number Diff line
@@ -348,8 +348,18 @@ class TestEdge(unittest.TestCase): 
            e = edge.Edge(s, d)

            e.matches = ['a', 'b', 'c']



    @pytest.mark.parametrize("nmatches, nstrengths", [(10,1), (10,2)])

    def test_prep_subpixel(self, nmatches, nstrengths):

    def test_prep_subpixel_1(self):

        nmatches = 10

        nstrengths = 1

        e = edge.Edge()

        arrs = e._prep_subpixel(nmatches, nstrengths=nstrengths)

        assert len(arrs) == 5

        assert arrs[2].shape == (nmatches, nstrengths)

        assert arrs[0][0] == 0



    def test_prep_subpixel_2(self):

        nmatches = 10

        nstrengths = 2

        e = edge.Edge()

        arrs = e._prep_subpixel(nmatches, nstrengths=nstrengths)

        assert len(arrs) == 5

autocnet/matcher/subpixel.py

+6 −4
Original line number Diff line number Diff line
@@ -97,8 +97,10 @@ def subpixel_phase(reference_roi, moving_roi, affine=tf.AffineTransform(), **kwa 
    : tuple

      With the RMSE error and absolute difference in phase

    """

    reference_image = reference_roi.clip()

    walking_template = moving_roi.clip(affine)

    reference_roi.clip()

    reference_image = reference_roi.clipped_array

    moving_roi.clip(affine=affine)

    walking_template = moving_roi.clipped_array



    if reference_image.shape != walking_template.shape:

        reference_size = reference_image.shape
@@ -199,7 +201,7 @@ def subpixel_template(reference_roi, 
    if (ref_clip is None) or (moving_clip is None):

        return None, None, None



    matcher_shift_x, matcher_shift_y, metrics, corrmap = func(moving_clip, ref_clip, upsampling=16, **kwargs)

    matcher_shift_x, matcher_shift_y, metrics, corrmap = func(moving_clip, ref_clip, **kwargs)

    if matcher_shift_x is None:

        return None, None, None

autocnet/matcher/tests/test_naive_template.py

+19 −20
Original line number Diff line number Diff line
@@ -79,8 +79,8 @@ class TestNaiveTemplate(unittest.TestCase): 
        result_x, result_y, result_strength, _ = naive_template.pattern_match(self._t_shape,

                                                                           self._test_image, upsampling=1)

        # Test offsets

        self.assertEqual(result_x, -3)

        self.assertEqual(result_y, -3)

        self.assertEqual(result_x, 3)

        self.assertEqual(result_y, 3)

        # Test Correlation Strength: At least 0.8

        self.assertGreaterEqual(result_strength, 0.8, "Returned Correlation Strength of %d" % result_strength)
@@ -88,8 +88,8 @@ class TestNaiveTemplate(unittest.TestCase): 
        result_x, result_y, result_strength, _ = naive_template.pattern_match(self._rect_shape,

                                                                           self._test_image, upsampling=1)

        # Test offsets

        self.assertEqual(result_x, 3)

        self.assertEqual(result_y, 4)

        self.assertEqual(result_x, -3)

        self.assertEqual(result_y, -4)

        # Test Correlation Strength: At least 0.8

        self.assertGreaterEqual(result_strength, 0.8, "Returned Correlation Strength of %d" % result_strength)
@@ -97,8 +97,8 @@ class TestNaiveTemplate(unittest.TestCase): 
        result_x, result_y, result_strength, _ = naive_template.pattern_match(self._square_shape,

                                                                           self._test_image, upsampling=1)

        # Test offsets

        self.assertEqual(result_x, -2)

        self.assertEqual(result_y, 4)

        self.assertEqual(result_x, 2)

        self.assertEqual(result_y, -4)

        # Test Correlation Strength: At least 0.8

        self.assertGreaterEqual(result_strength, 0.8, "Returned Correlation Strength of %d" % result_strength)
@@ -106,11 +106,10 @@ class TestNaiveTemplate(unittest.TestCase): 
        result_x, result_y, result_strength, _ = naive_template.pattern_match(self._vertical_line,

                                                                           self._test_image, upsampling=1)

        # Test offsets

        self.assertEqual(result_x, 3)

        self.assertEqual(result_y, -5)

        self.assertEqual(result_x, -3)

        self.assertEqual(result_y, 5)

        # Test Correlation Strength: At least 0.8

        self.assertGreaterEqual(result_strength, 0.8, "Returned Correlation Strength of %d" % result_strength)



    def tearDown(self):

        pass

autocnet/transformation/roi.py

+8 −2
Original line number Diff line number Diff line
@@ -170,7 +170,13 @@ class Roi(): 
        """

        if self.ndv == None:

            return True

        return np.isclose(self.ndv,self.array).all()

        if len(self.clipped_array) == 0:

            return False

        # Check if we have any ndv values this will return an inverted array

        # where all no data values are true, we need to then invert the array

        # and return the all result. This ensures that a valid array will return

        # True

        return np.invert(np.isclose(self.ndv, self.clipped_array)).all()





    @property

autocnet/transformation/tests/test_roi.py

+37 −21
Original line number Diff line number Diff line 
import numpy as np

import pytest



import unittest

from unittest.mock import patch, Mock



from plio.io.io_gdal import GeoDataset



from autocnet.transformation.roi import Roi



@pytest.fixture
@@ -10,26 +15,31 @@ def array_with_nodata(): 
    return arr



def test_geodata_with_ndv_is_valid(geodata_a):

    roi = Roi(geodata_a, 50, 50, size_x=2, size_y=2)

    roi = Roi(geodata_a, 7, 7, size_x=2, size_y=2)

    # Clip the ROI so that our clipped array is populated

    roi.clip()

    assert roi.is_valid == False



def test_geodata_is_valid(geodata_b):

    roi = Roi(geodata_b, 500, 500, size_x=200, size_y=200)

    roi.data.no_data_value = None  # Monkey patch in None (default on the Mock)

    roi.data.no_data_value = 2  # Monkey patch in None (default on the Mock)

    # Clip the ROI so that our clipped array is populated

    roi.clip()

    assert roi.is_valid == True



def test_center(array_with_nodata):

    roi = Roi(array_with_nodata, 5, 5, size_x=5, size_y=5, buffer=5)

    assert roi.center == (10.0,10.0)

def test_center(geodata_c):

    geodata_c.read_array.return_value = np.ones((20, 20))

    roi = Roi(geodata_c, 5, 5, size_x=5, size_y=5, buffer=5)

    assert roi.center == (5.0, 5.0)



@pytest.mark.parametrize("x, y, axr, ayr",[

                         (10.1, 10.1, .1, .1),

                         (10.5, 10.5, .5, .5),

                         (10.9, 10.9, .9, .9)

    ])

def test_roi_remainder(x, y, axr, ayr):

    gd = np.zeros((10,10))

    roi = Roi(gd, x, y)

def test_roi_remainder(x, y, axr, ayr, geodata_c):

    geodata_c.read_array.return_value = np.zeros((10,10))

    roi = Roi(geodata_c, x, y)

    pytest.approx(roi._remainder_x, axr)

    pytest.approx(roi._remainder_y, ayr)

    assert roi.x == x
@@ -40,9 +50,9 @@ def test_roi_remainder(x, y, axr, ayr): 
    (15, 15, (100, 100), (15, 15), [0, 30, 0, 30]),

    (75, 75, (100,100), (25,25), [50, 100, 50, 100])

])

def test_extent_computation(x, y, size_arr, size_roi, expected):

    gd = np.zeros(size_arr)

    roi = Roi(gd, x, y, size_x=size_roi[0], size_y=size_roi[1])

def test_extent_computation(x, y, size_arr, size_roi, expected, geodata_c):

    geodata_c.read_array.return_value = np.zeros(size_arr)

    roi = Roi(geodata_c, x, y, size_x=size_roi[0], size_y=size_roi[1])

    pixels = roi.image_extent

    assert pixels == expected
@@ -51,14 +61,14 @@ def test_extent_computation(x, y, size_arr, size_roi, expected): 
    (20, 20, (100, 100), (20, 20), 0, (0,3030)),

    (69, 69, (100,100), (30,30), 3, (4545, 9999))

])

def test_array_extent_computation(x, y, size_arr, size_roi, buffer, expected):

    gd = np.arange(size_arr[0]*size_arr[1]).reshape(size_arr)

def test_array_extent_computation(x, y, size_arr, size_roi, buffer, expected, geodata_c):

    geodata_c.read_array.return_value = np.arange(size_arr[0]*size_arr[1]).reshape(size_arr)



    roi = Roi(gd, x, y, size_x=size_roi[0], size_y=size_roi[1], buffer=buffer)

    array = roi.clip()

    roi = Roi(geodata_c, x, y, size_x=size_roi[0], size_y=size_roi[1], buffer=buffer)

    roi.clip()



    assert array.dtype == np.float32

    assert (array.shape == np.asarray(size_roi) * 2 + 1).all()

    assert roi.clipped_array.dtype == np.float32

    assert (roi.clipped_array.shape == np.asarray(size_roi) * 2 + 1).all()



@pytest.mark.parametrize("x, y, x1, y1, xs, ys, size_arr, size_roi, expected",[

    (50, 50, 50, 50, -5, -5, (100, 100), (10, 10), (45, 45)),
@@ -66,8 +76,14 @@ def test_array_extent_computation(x, y, size_arr, size_roi, buffer, expected): 
    (50, 50, 10, 10,  5,  5, (100, 100), (20, 20), (15, 15 ))

])

def test_subpixel_using_roi(x, y, x1, y1, xs, ys, size_arr, size_roi, expected):

    source = np.arange(size_arr[0]*size_arr[1]).reshape(size_arr)

    destination = np.arange(size_arr[0]*size_arr[1]).reshape(size_arr)

    source = Mock(GeoDataset)

    source_array = np.arange(size_arr[0]*size_arr[1]).reshape(size_arr)

    source.read_array.return_value = source_array



    destination = Mock(GeoDataset)

    destination_array = np.arange(size_arr[0]*size_arr[1]).reshape(size_arr)

    destination.read_array.return_value = destination_array



    s_roi = Roi(source, x, y, size_x=size_roi[0], size_y=size_roi[1])

    d_roi = Roi(destination, x1, y1, size_x=size_roi[0], size_y=size_roi[1])