def test_rasterization_function():
sq1 = GeoFeature(
GeoVector.from_bounds(xmin=0, ymin=2, xmax=1, ymax=3, crs=WGS84_CRS),
{'value': 1.0}
)
sq2 = GeoFeature(
GeoVector.from_bounds(xmin=1, ymin=0, xmax=3, ymax=2, crs=WGS84_CRS),
{'value': 2.0}
)
fc = FeatureCollection([sq1, sq2])
def func(feat):
return feat['value']
expected_image = np.ma.masked_array(
[[
[1.0, 0.0, 0.0],
[0.0, 2.0, 2.0],
[0.0, 2.0, 2.0]
]],
[
[False, True, True],
[True, False, False],
[True, False, False],
]
)
result = fc.rasterize(1.0, fill_value=func, crs=WGS84_CRS, dtype=np.float32)
assert_array_equal(result.image.mask, expected_image.mask)
assert_array_equal(result.image.data, expected_image.data)
def test_groupby_agg_returns_expected_result():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(3, 3)), {
'prop1': 'a',
'b': 1
}),
GeoFeature(GeoVector(Point(1, 1)), {
'prop1': 'a',
'b': 2
}),
GeoFeature(GeoVector(Point(2, 2)), {
'prop1': 'b',
'b': 3
})
])
def first(collection):
return collection[0]
expected_result = FeatureCollection([
GeoFeature(GeoVector(Point(3, 3)), {'b': 1}),
GeoFeature(GeoVector(Point(2, 2)), {'b': 3})
])
assert list(fc.groupby('prop1')['b'].agg(first)) == expected_result
def test_rasterization_of_line_has_correct_pixel_width(resolution):
xmax, ymax = 11, 5
pixels_width = 1
line = GeoFeature.from_shape(
LineString([(xmax / 2, 0), (xmax / 2, ymax * 4 / 5)]))
roi = GeoVector.from_bounds(xmin=0,
ymin=0,
xmax=xmax,
ymax=ymax,
crs=DEFAULT_CRS)
fc = FeatureCollection([line])
expected_image = np.zeros(
(int(ymax // resolution), int(xmax // resolution)), dtype=np.uint8)
expected_image[int(1 // resolution):, expected_image.shape[1] // 2] = 1
expected_affine = Affine(resolution, 0.0, 0.0, 0.0, -resolution, 5.0)
expected_crs = DEFAULT_CRS
expected_result = GeoRaster2(expected_image,
expected_affine,
expected_crs,
nodata=0)
result = fc.rasterize(resolution,
polygonize_width=pixels_width,
crs=DEFAULT_CRS,
bounds=roi)
assert result == expected_result
def test_rasterization_of_line_simple():
resolution = 1
pixels_width = 1
line = GeoFeature.from_shape(LineString([(2.5, 0), (2.5, 3)]))
roi = GeoVector.from_bounds(xmin=0,
ymin=0,
xmax=5,
ymax=5,
crs=DEFAULT_CRS)
fc = FeatureCollection([line])
expected_image = np.zeros((5, 5), dtype=np.uint8)
expected_image[2:, 2] = 1
expected_affine = Affine(1.0, 0.0, 0.0, 0.0, -1.0, 5.0)
expected_crs = DEFAULT_CRS
expected_result = GeoRaster2(expected_image,
expected_affine,
expected_crs,
nodata=0)
result = fc.rasterize(resolution,
polygonize_width=pixels_width,
crs=DEFAULT_CRS,
bounds=roi)
assert result == expected_result
def test_rasterization_raise_error_for_too_big_image():
shape = Polygon([(0, 0), (1, 0), (1, -1), (0, -1)])
fcol = FeatureCollection([GeoFeature(GeoVector(shape), {})])
with pytest.raises(ScaleError) as excinfo:
fcol.rasterize(1e-50)
assert "Scale is too fine, increase it for a smaller image" in excinfo.exconly()
def test_feature_collection_schema_of_empty_set():
fc = FeatureCollection([])
assert fc.schema == {"geometry": None, "properties": {}}
with tempfile.NamedTemporaryFile(suffix=".json") as target:
fc.save(target.name)
fc2 = FileCollection.open(target.name)
assert fc == fc2
def test_get_tile_merge_tiles(tile):
raster1_path = './tests/data/raster/overlap1.tif'
raster2_path = './tests/data/raster/overlap2.tif'
raster1 = GeoRaster2.open(raster1_path)
raster2 = GeoRaster2.open(raster2_path)
features = [
GeoFeature(raster1.footprint().reproject(new_crs=WGS84_CRS),
{'raster_url': raster1_path, 'created': datetime.now()}),
GeoFeature(raster2.footprint().reproject(new_crs=WGS84_CRS),
{'raster_url': raster2_path, 'created': datetime.now()}),
]
fc = FeatureCollection(features)
bounds = mercantile.xy_bounds(*tile)
eroi = GeoVector.from_bounds(xmin=bounds.left, xmax=bounds.right,
ymin=bounds.bottom, ymax=bounds.top,
crs=WEB_MERCATOR_CRS)
expected_tile = merge_all([raster1.get_tile(*tile), raster2.get_tile(*tile)], roi=eroi)
merged = fc.get_tile(*tile, sort_by='created')
if merged is not None:
assert merged == expected_tile
else:
assert expected_tile.image.mask.all()
assert (expected_tile.image.data == 0).all()
def test_groupby_can_extract_property():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(3, 3)), {
'prop1': 'a',
'b': 1
}),
GeoFeature(GeoVector(Point(1, 1)), {
'prop1': 'a',
'b': 2
}),
GeoFeature(GeoVector(Point(2, 2)), {
'prop1': 'b',
'b': 3
})
])
expected_groups = [
('a',
FeatureCollection([
GeoFeature(GeoVector(Point(3, 3)), {'b': 1}),
GeoFeature(GeoVector(Point(1, 1)), {'b': 2}),
])),
('b', FeatureCollection([GeoFeature(GeoVector(Point(2, 2)),
{'b': 3})]))
]
assert list(fc.groupby('prop1')['b']) == expected_groups
def test_get_values():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(0, 0)), {'prop1': 1}),
GeoFeature(GeoVector(Point(0, 0)), {'prop1': 2}),
GeoFeature(GeoVector(Point(0, 0)), {'prop1': 3}),
GeoFeature(GeoVector(Point(0, 0)), {'prop2': 1}),
])
assert list(fc.get_values('prop1')) == [1, 2, 3, None]
def test_feature_collection_to_record_from_record():
num_features = 3
gen_features = (GeoFeature.from_shape(
Polygon([(0 + d_x, 0), (0 + d_x, 1), (1 + d_x, 1), (1 + d_x, 0)]))
for d_x in range(num_features))
fc = FeatureCollection(gen_features)
assert mapping(fc) == mapping(
FeatureCollection.from_record(fc.to_record(WGS84_CRS), WGS84_CRS))
def test_groupby_has_proper_groups():
gfa1 = GeoFeature(GeoVector(Point(3, 3)), {'prop1': 'a'})
gfa2 = GeoFeature(GeoVector(Point(1, 1)), {'prop1': 'a'})
gfb1 = GeoFeature(GeoVector(Point(2, 2)), {'prop1': 'b'})
fc = FeatureCollection([gfa1, gfa2, gfb1])
expected_groups = [('a', FeatureCollection([gfa1, gfa2])),
('b', FeatureCollection([gfb1]))]
assert list(fc.groupby('prop1')) == expected_groups
def test_featurecollection_save_has_no_side_effects():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(0, 0)), {'attr1': 1}),
GeoFeature(GeoVector(Point(0, 0)), {'attr2': 1})
])
with tempfile.NamedTemporaryFile(suffix=".json") as fp:
fc.save(fp.name)
assert fc[0].attributes == {'attr1': 1}
assert fc[1].attributes == {'attr2': 1}
def test_collection_add():
gv1 = GeoVector.from_bounds(xmin=0, ymin=0, xmax=2, ymax=1)
gv2 = GeoVector.from_bounds(xmin=1, ymin=0, xmax=3, ymax=1)
gv3 = GeoVector.from_bounds(xmin=2, ymin=0, xmax=4, ymax=1)
gv4 = GeoVector.from_bounds(xmin=3, ymin=0, xmax=5, ymax=1)
assert (gv1 + gv2) == FeatureCollection.from_geovectors([gv1, gv2])
assert (gv1 + gv2 + gv3) == FeatureCollection.from_geovectors(
[gv1, gv2, gv3])
assert (((gv1 + gv2) + (gv3 + gv4)) == (gv1 + gv2 + gv3 + gv4) ==
FeatureCollection.from_geovectors([gv1, gv2, gv3, gv4]))
def test_feature_collection_filter_returns_proper_elements():
num_features = 3
gen_features = (GeoFeature.from_shape(
Polygon([(0 + d_x, 0), (0 + d_x, 1), (1 + d_x, 1), (1 + d_x, 0)]))
for d_x in range(num_features))
filter_gv = GeoVector(Point(1.5, 0.5))
fcol = FeatureCollection(gen_features)
res = fcol.filter(intersects=filter_gv)
assert len(list(res)) == 1
def test_groupby_with_dissolve():
fc = FeatureCollection([
GeoFeature(GeoVector.from_bounds(xmin=0, ymin=0, xmax=2, ymax=1, crs=DEFAULT_CRS), {'prop1': 'a', 'b': 1}),
GeoFeature(GeoVector.from_bounds(xmin=1, ymin=0, xmax=3, ymax=1, crs=DEFAULT_CRS), {'prop1': 'a', 'b': 2}),
GeoFeature(GeoVector.from_bounds(xmin=0, ymin=0, xmax=2, ymax=1, crs=DEFAULT_CRS), {'prop1': 'b', 'b': 3}),
])
expected_result = FeatureCollection([
GeoFeature(GeoVector.from_bounds(xmin=0, ymin=0, xmax=3, ymax=1, crs=DEFAULT_CRS), {'b': 3}),
GeoFeature(GeoVector.from_bounds(xmin=0, ymin=0, xmax=2, ymax=1, crs=DEFAULT_CRS), {'b': 3}),
])
assert fc.dissolve('prop1', sum) == fc.groupby('prop1').agg(partial(dissolve, aggfunc=sum)) == expected_result
def test_rasterization_function_raises_error_if_no_dtype_is_given():
sq1 = GeoFeature(
GeoVector.from_bounds(xmin=0, ymin=2, xmax=1, ymax=3, crs=WGS84_CRS),
{'value': 1.0})
sq2 = GeoFeature(
GeoVector.from_bounds(xmin=1, ymin=0, xmax=3, ymax=2, crs=WGS84_CRS),
{'value': 2.0})
fc = FeatureCollection([sq1, sq2])
with pytest.raises(ValueError) as excinfo:
fc.rasterize(1.0, fill_value=lambda x: 1, crs=WGS84_CRS)
assert "dtype must be specified for multivalue rasterization" in excinfo.exconly(
)
def test_sort():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(3, 3)), {'prop1': 3}),
GeoFeature(GeoVector(Point(1, 1)), {'prop1': 1}),
GeoFeature(GeoVector(Point(2, 2)), {'prop1': 2})
])
expected_fc = FeatureCollection([
GeoFeature(GeoVector(Point(1, 1)), {'prop1': 1}),
GeoFeature(GeoVector(Point(2, 2)), {'prop1': 2}),
GeoFeature(GeoVector(Point(3, 3)), {'prop1': 3})
])
assert fc.sort("prop1") == expected_fc
def test_featurecollection_apply_multiple_statements():
fc = fc_generator(5)
new_fc = fc.apply(prop1=3)
new_fc_2 = new_fc.apply(prop2=lambda f: f['prop1'] + 2, prop3='aaa')
assert new_fc_2 == FeatureCollection([GeoFeature(feat.geometry, {'prop1': 3, 'prop2': 5, 'prop3': 'aaa'})
for feat in fc])
def test_feature_collection_with_invalid_schema():
fc = FileCollection.open("tests/data/vector/bsas_barrios_lla.geojson")
schema = fc.schema.copy()
schema["properties"] = {}
with pytest.raises(ValueError) as exception:
fc2 = FeatureCollection(list(fc), schema=schema)
assert exception.message.startswith("Record does not match collection schema")
def test_feature_collection_from_rasters():
rasters_list = [
GeoRaster2.open("./tests/data/raster/overlap1.tif"),
GeoRaster2.open("./tests/data/raster/overlap2.tif")
]
fc = FeatureCollection.from_georasters(rasters_list)
assert fc.is_rasters_collection()
def test_featurecollection_schema_for_property_types_with_none_values():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(0, 0)), {
'prop1': None,
'prop2': 1.0,
'prop3': 'A'
}),
GeoFeature(GeoVector(Point(0, 0)), {
'prop1': 2,
'prop2': None,
'prop3': 'B'
}),
GeoFeature(GeoVector(Point(0, 0)), {
'prop1': 3,
'prop2': 3.0,
'prop3': None
})
])
expected_schema = {
'geometry': 'Point',
'properties': {
'prop1': 'int',
'prop2': 'float',
'prop3': 'str'
}
}
assert fc.schema == expected_schema
def test_featurecollection_apply_on_rasters_collection():
rasters_list = [
GeoRaster2.open("./tests/data/raster/overlap1.tif"),
GeoRaster2.open("./tests/data/raster/overlap2.tif")
]
fc = FeatureCollection.from_georasters(rasters_list)
new_fc = fc.apply(prop1=3)
assert new_fc.is_rasters_collection()
def fc_generator(num_features):
gen_features = (
GeoFeature.from_shape(
Polygon([(0 + d_x, 0), (0 + d_x, 1), (1 + d_x, 1), (1 + d_x, 0)])
)
for d_x in range(num_features)
)
return FeatureCollection(gen_features)
def test_rasterization_has_expected_affine_and_crs():
shape = Polygon([(0, 0), (1, 0), (1, -1), (0, -1)])
crs = CRS({'init': 'epsg:32631'})
fcol = FeatureCollection([GeoFeature(GeoVector(shape, crs), {})])
expected_affine = ~Affine(1.0, 0.0, 0.0, 0.0, -1.0, 0.0)
georaster = fcol.rasterize(1, crs=crs)
assert georaster.crs == crs
assert georaster.affine.a == pytest.approx(expected_affine.a)
assert georaster.affine.b == pytest.approx(expected_affine.b, abs=1e-10)
assert georaster.affine.c == pytest.approx(expected_affine.c, abs=1e-10)
assert georaster.affine.d == pytest.approx(expected_affine.d, abs=1e-10)
assert georaster.affine.e == pytest.approx(expected_affine.e)
assert georaster.affine.f == pytest.approx(expected_affine.f, abs=1e-10)
def test_featurecollection_property_names_includes_all():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(0, 0)), {'prop1': 1}),
GeoFeature(GeoVector(Point(0, 0)), {'prop2': 1})
])
expected_property_names = ['prop1', 'prop2']
assert sorted(fc.property_names) == expected_property_names
def test_featurecollection_map():
fc = fc_generator(5)
def func(feat):
return GeoFeature(feat.geometry, {'attr1': 1})
new_fc = fc.map(func)
assert new_fc == FeatureCollection([func(feat) for feat in fc])
def test_featurecollection_attribute_names_includes_all():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(0, 0)), {'attr1': 1}),
GeoFeature(GeoVector(Point(0, 0)), {'attr2': 1})
])
expected_attribute_names = ['attr1', 'attr2']
assert sorted(fc.attribute_names) == expected_attribute_names
def test_featurecollection_schema_raises_error_for_heterogeneous_property_types():
fc = FeatureCollection([
GeoFeature(GeoVector(Point(0, 0)), {'prop1': 1}),
GeoFeature(GeoVector(Point(0, 0)), {'prop1': 1.0})
])
with pytest.raises(FeatureCollectionIOError) as excinfo:
fc.schema
assert "Cannot generate a schema for a heterogeneous FeatureCollection. " in excinfo.exconly()
def test_featurecollection_schema_raises_error_for_heterogeneous_types():
fc = FeatureCollection.from_geovectors([
GeoVector(Polygon.from_bounds(0, 0, 1, 1)),
GeoVector(Point(0, 0))
])
with pytest.raises(FeatureCollectionIOError) as excinfo:
fc.schema
assert "Cannot generate a schema for a heterogeneous FeatureCollection. " in excinfo.exconly()
def test_convex_hull_and_envelope():
fc = FeatureCollection.from_geovectors([
GeoVector.from_bounds(xmin=0, ymin=0, xmax=1, ymax=1),
GeoVector.from_bounds(xmin=1, ymin=0, xmax=2, ymax=1),
GeoVector.from_bounds(xmin=1, ymin=1, xmax=2, ymax=2),
])
expected_convex_hull = GeoVector(Polygon([(0, 0), (2, 0), (2, 2), (1, 2), (0, 1), (0, 0)]))
expected_envelope = GeoVector.from_bounds(xmin=0, ymin=0, xmax=2, ymax=2)
assert fc.convex_hull.equals(expected_convex_hull)
assert fc.envelope.equals(expected_envelope)
