Пример #1
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def spatial_poly_select(xvals, yvals, geometry):
    try:
        from shapely.geometry import Polygon
        boxes = (Polygon(np.column_stack([xs, ys]))
                 for xs, ys in zip(xvals, yvals))
        poly = Polygon(geometry)
        return np.array([poly.contains(p) for p in boxes])
    except ImportError:
        raise ImportError("Lasso selection on geometry data requires "
                          "shapely to be available.")
Пример #2
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def spatial_select_columnar(xvals, yvals, geometry):
    try:
        from spatialpandas.geometry import Polygon, PointArray
        points = PointArray((xvals.astype('float'), yvals.astype('float')))
        poly = Polygon([np.concatenate([geometry, geometry[:1]]).flatten()])
        return points.intersects(poly)
    except Exception:
        pass
    try:
        from shapely.geometry import Point, Polygon
        points = (Point(x, y) for x, y in zip(xvals, yvals))
        poly = Polygon(geometry)
        return np.array([poly.contains(p) for p in points])
    except ImportError:
        raise ImportError("Lasso selection on tabular data requires "
                          "either spatialpandas or shapely to be available.")
Пример #3
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def spatial_geom_select(x0vals, y0vals, x1vals, y1vals, geometry):
    try:
        from shapely.geometry import box, Polygon
        boxes = (box(x0, y0, x1, y1)
                 for x0, y0, x1, y1 in zip(x0vals, y0vals, x1vals, y1vals))
        poly = Polygon(geometry)
        return np.array([poly.contains(p) for p in boxes])
    except ImportError:
        raise ImportError("Lasso selection on geometry data requires "
                          "shapely to be available.")
Пример #4
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def spatial_select_columnar(xvals, yvals, geometry):
    if 'cudf' in sys.modules:
        import cudf
        if isinstance(xvals, cudf.Series):
            xvals = xvals.values.astype('float')
            yvals = yvals.values.astype('float')
            try:
                import cuspatial
                result = cuspatial.point_in_polygon(
                    xvals,
                    yvals,
                    cudf.Series([0], index=["selection"]),
                    [0],
                    geometry[:, 0],
                    geometry[:, 1],
                )
                return result.values
            except Exception:
                xvals = np.asarray(xvals)
                yvals = np.asarray(yvals)
    x0, x1 = geometry[:, 0].min(), geometry[:, 0].max()
    y0, y1 = geometry[:, 1].min(), geometry[:, 1].max()
    mask = (xvals >= x0) & (xvals <= x1) & (yvals >= y0) & (yvals <= y1)
    masked_xvals = xvals[mask]
    masked_yvals = yvals[mask]
    try:
        from spatialpandas.geometry import Polygon, PointArray
        points = PointArray(
            (masked_xvals.astype('float'), masked_yvals.astype('float')))
        poly = Polygon([np.concatenate([geometry, geometry[:1]]).flatten()])
        geom_mask = points.intersects(poly)
    except Exception:
        pass
    try:
        from shapely.geometry import Point, Polygon
        points = (Point(x, y) for x, y in zip(masked_xvals, masked_yvals))
        poly = Polygon(geometry)
        geom_mask = np.array([poly.contains(p) for p in points])
    except ImportError:
        raise ImportError("Lasso selection on tabular data requires "
                          "either spatialpandas or shapely to be available.")
    mask[np.where(mask)[0]] = geom_mask
    return mask
Пример #5
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def test_polygon():
    polygon = Polygon([large_square_ccw, unit_square_cw])
    assert polygon.length == 16.0
    assert polygon.area == 8.0