Python numba.jitclass() Examples

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Example #1
Source File: geojson.py    From cate with MIT License 4 votes vote down vote up 
def simplify_geometry(x_data: np.ndarray, y_data: np.ndarray, conservation_ratio: float) \
        -> Tuple[np.ndarray, np.ndarray]:
    """
    Simplify a ring or line-string given by its coordinates *x_data* and *y_data* from *x_data.size* points to
    int(*conservation_ratio* * *x_data*.size + 0.5) points.
    A ring is detected by same start and end points. The first and last coordinates will always be
    maintained therefore the minimum number of resulting points is 3 for rings and 2 for line-strings.

    :param x_data: The x coordinates.
    :param y_data: The x coordinates.
    :param conservation_ratio: The ratio of coordinates to be conserved, 0 <= *conservation_ratio* <= 1.
    :return: A pair comprising the simplified *x_data* and *y_data*.
    """
    is_ring = x_data[0] == x_data[-1] and y_data[0] == y_data[-1]
    old_point_count = int(x_data.size)
    new_point_count = int(conservation_ratio * old_point_count + 0.5)
    min_point_count = 4 if is_ring else 2
    if new_point_count < min_point_count:
        new_point_count = min_point_count
    if old_point_count <= new_point_count:
        return x_data, y_data

    point_heap = PointHeap(x_data, y_data)
    while point_heap.size > new_point_count:
        point_heap.pop()

    new_x_data = np.zeros(new_point_count, dtype=x_data.dtype)
    new_y_data = np.zeros(new_point_count, dtype=y_data.dtype)
    point = point_heap.first_point
    i = 0
    while point is not None:
        index = point[1]
        new_x_data[i] = x_data[index]
        new_y_data[i] = y_data[index]
        point = point[3]
        i += 1

    return new_x_data, new_y_data


# TODO (forman): Optimize me!
# This is an non-optimised version of PointHeap for testing only.
# It uses the pure Python heapq implementation of a min-heap.
# We should ASAP replace heapq by the jit-compiled cate.webapi.minheap implementation
# so that we can compile the PointHeap class using @numba.jitclass().
# See http://numba.pydata.org/numba-doc/dev/user/jitclass.html

# PointHeapSpec = [
#     ('_x_data', np.float64[:]),
#     ('_y_data', np.float64[:]),
#     ('_point_heap', np.int64[:]),
#     ('_size', np.int64),
# ]
# @numba.jitclass(PointHeapSpec)