Beispiel #1
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def test_mask_wrap():

    # create a test case where the outlines and the lon coordinates 
    # are different
    
    # outline 0..359.9
    outl1 = ((359, 0), (359, 1), (0, 1.), (0, 0))
    outl2 = ((359, 1), (359, 2), (0, 2.), (0, 1))
    outlines = [outl1, outl2]

    r = Regions_cls(name, numbers, names, abbrevs, outlines) 

    # lon -180..179.9
    lon = [-1.5, -0.5]
    lat = [0.5, 1.5]

    result = r.mask(lon, lat, xarray=False)
    assert np.all(np.isnan(result))

    # this is the wron wrapping
    result = r.mask(lon, lat, xarray=False, wrap_lon=180)
    assert np.all(np.isnan(result))

    expected = expected_mask()

    # determine the wrap automatically
    result = r.mask(lon, lat, xarray=False, wrap_lon=True)
    assert np.allclose(result, expected, equal_nan=True)

    # determine the wrap by hand
    result = r.mask(lon, lat, xarray=False, wrap_lon=360)
    assert np.allclose(result, expected, equal_nan=True)
Beispiel #2
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def test_Regions_cls_deprection_warning():

    with pytest.warns(
            FutureWarning,
            match=
            "Using 'Regions_cls' is deprecated, please use 'Regions' instead.",
    ):
        Regions_cls(name, numbers, names, abbrevs, outlines)
Beispiel #3
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def test_centroids_deprection_warning():

    centroids = [[0, 0], [1, 1]]
    with pytest.warns(FutureWarning,
                      match="Specifying 'centroids' is deprecated"):
        Regions_cls(name,
                    numbers,
                    names,
                    abbrevs,
                    outlines,
                    centroids=centroids)
Beispiel #4
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def test_user_defined_centroid():

    centroids = [[0, 0], [1, 1]]

    test_regions_centroids = Regions_cls(name,
                                         numbers,
                                         names,
                                         abbrevs,
                                         outlines,
                                         centroids=centroids)

    assert test_regions_centroids.centroids == centroids
Beispiel #5
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def test_mask_wrap():

    # create a test case where the outlines and the lon coordinates
    # are different

    # outline 0..359.9
    outl1 = ((359, 0), (359, 1), (0, 1.), (0, 0))
    outl2 = ((359, 1), (359, 2), (0, 2.), (0, 1))
    outlines = [outl1, outl2]

    r = Regions_cls(name, numbers, names, abbrevs, outlines)

    # lon -180..179.9
    lon = [-1.5, -0.5]
    lat = [0.5, 1.5]

    result = r.mask(lon, lat, xarray=False)
    assert np.all(np.isnan(result))

    # this is the wron wrapping
    result = r.mask(lon, lat, xarray=False, wrap_lon=180)
    assert np.all(np.isnan(result))

    expected = expected_mask()

    # determine the wrap automatically
    result = r.mask(lon, lat, xarray=False, wrap_lon=True)
    assert np.allclose(result, expected, equal_nan=True)

    # determine the wrap by hand
    result = r.mask(lon, lat, xarray=False, wrap_lon=360)
    assert np.allclose(result, expected, equal_nan=True)
Beispiel #6
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 def crop(self, image: xa.DataArray, regions: Regions_cls ) -> xa.DataArray:
     region_mask = regions.mask( image, lat_name=image.dims[-2], lon_name=image.dims[-1] )
     return image.where( region_mask == 0 )
Beispiel #7
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from pytest import raises

import xarray as xr

# =============================================================================

name = 'Example'
numbers = [0, 1]
names = ['Unit Square1', 'Unit Square2']
abbrevs = ['uSq1', 'uSq2']

outl1 = ((0, 0), (0, 1), (1, 1.), (1, 0))
outl2 = ((0, 1), (0, 2), (1, 2.), (1, 1))
outlines = [outl1, outl2]

r1 = Regions_cls(name, numbers, names, abbrevs, outlines)

lon = [0.5, 1.5]
lat = [0.5, 1.5]

# in this example the result looks:
# a fill
# b fill


def expected_mask(a=0, b=1, fill=np.NaN):
    return np.array([[a, fill], [b, fill]])


def test_create_mask_contains():
Beispiel #8
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warnings.filterwarnings(message="Using 'Regions_cls'", action="ignore")

# =============================================================================

# set up the testing regions

name = "Example"
numbers = [0, 1]
names = ["Unit Square1", "Unit Square2"]
abbrevs = ["uSq1", "uSq2"]

outl1 = ((0, 0), (0, 1), (1, 1.0), (1, 0))
outl2 = ((0, 1), (0, 2), (1, 2.0), (1, 1))
outlines = [outl1, outl2]

r1 = Regions_cls(name, numbers, names, abbrevs, outlines)

numbers = [1, 2]
names = {1: "Unit Square1", 2: "Unit Square2"}
abbrevs = {1: "uSq1", 2: "uSq2"}
poly1 = Polygon(outl1)
poly2 = Polygon(outl2)
poly = {1: poly1, 2: poly2}

r2 = Regions_cls(name, numbers, names, abbrevs, poly)

# numbers as array
r3 = Regions_cls(name, np.array(numbers), names, abbrevs, poly)

# =============================================================================