def point_in_polygon(
test_points_x,
test_points_y,
poly_offsets,
poly_ring_offsets,
poly_points_x,
poly_points_y,
):
""" Compute from a set of points and a set of polygons which points fall
within which polygons. Note that `polygons_(x,y)` must be specified as
closed polygons: the first and last coordinate of each polygon must be
the same.
Parameters
----------
test_points_x
x-coordinate of test points
test_points_y
y-coordinate of test points
poly_offsets
beginning index of the first ring in each polygon
poly_ring_offsets
beginning index of the first point in each ring
poly_points_x
x closed-coordinate of polygon points
poly_points_y
y closed-coordinate of polygon points
Examples
--------
Test whether 3 points fall within either of two polygons
>>> result = cuspatial.point_in_polygon(
[0, -8, 6.0], # test_points_x
[0, -8, 6.0], # test_points_y
cudf.Series([0, 1], index=['nyc', 'hudson river']), # poly_offsets
[0, 3], # ring_offsets
[-10, 5, 5, -10, 0, 10, 10, 0], # poly_points_x
[-10, -10, 5, 5, 0, 0, 10, 10], # poly_points_y
)
# The result of point_in_polygon is a DataFrame of Boolean
# values indicating whether each point (rows) falls within
# each polygon (columns).
>>> print(result)
nyc hudson river
0 True True
1 True False
2 False True
# Point 0: (0, 0) falls in both polygons
# Point 1: (-8, -8) falls in the first polygon
# Point 2: (6.0, 6.0) falls in the second polygon
note
input Series x and y will not be index aligned, but computed as
sequential arrays.
Returns
-------
result : cudf.DataFrame
A DataFrame of boolean values indicating whether each point falls
within each polygon.
"""
if len(poly_offsets) == 0:
return DataFrame()
(
test_points_x,
test_points_y,
poly_points_x,
poly_points_y,
) = normalize_point_columns(
as_column(test_points_x),
as_column(test_points_y),
as_column(poly_points_x),
as_column(poly_points_y),
)
result = cpp_point_in_polygon(
test_points_x,
test_points_y,
as_column(poly_offsets, dtype="int32"),
as_column(poly_ring_offsets, dtype="int32"),
poly_points_x,
poly_points_y,
)
result = gis_utils.pip_bitmap_column_to_binary_array(
polygon_bitmap_column=result, width=len(poly_offsets))
result = DataFrame(result)
result = result._apply_support_method("astype", dtype="bool")
result.columns = [x for x in list(reversed(poly_offsets.index))]
result = result[list(reversed(result.columns))]
return result
