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我有一個函數，它使用一個生成器來循環大型二維python浮點座標列表，以便創建表示座標之間距離的整數平面列表。Cython - 計算二維座標之間的距離數組
point_input = {"x": -8081441.0, "y": 5685214.0}
output = [-8081441, 5685214]
polyline_input = {"paths" : [[-8081441.0, 5685214.0], [-8081446.0, 5685216.0], [-8081442.0, 5685219.0], [-8081440.0, 5685211.0], [-8081441.0, 5685214.0]]}
output = [[-8081441, 5685214, 5, -2, -4, -3, -2, 8, 1, -3]]
polygon_input = {"rings" : [[-8081441.0, 5685214.0], [-8081446.0, 5685216.0], [-8081442.0, 5685219.0], [-8081440.0, 5685211.0], [-8081441.0, 5685214.0]]}
output = [[-8081441, 5685214, 5, -2, -4, -3, -2, 8, 1, -3]]
純Python：
def geometry_to_distance(geometry, geometry_type):
def calculate_distance(coords):
iterator = iter(coords)
previous_x, previous_y = iterator.next()
yield int(previous_x)
yield int(previous_y)
for current_x, current_y in iterator:
yield int(previous_x - current_x)
yield int(previous_y - current_y)
previous_x, previous_y = current_x, current_y
if geometry_type == "POINT":
distance_array = [int(geometry["x"]), int(geometry["y"])]
elif geometry_type == "POLYLINE":
distance_array = [list(calculate_distance(path)) for path in geometry["paths"]]
elif geometry_type == "POLYGON":
distance_array = [list(calculate_distance(ring)) for ring in geometry["rings"]]
else:
raise Exception("{} geometry type not supported".format(geometry_type))
return distance_array
對於速度的表現，我想用同樣的功能的實現用Cython。我在calculate_distance函數中使用整型變量的類型聲明。
用Cython實現：
def geometry_to_distance(geometry, geometry_type):
def calculate_distance(coords):
cdef int previous_x, previous_y, current_x, current_y
iterator = iter(coords)
previous_x, previous_y = iterator.next()
yield previous_x
yield previous_y
for current_x, current_y in iterator:
yield previous_x - current_x
yield previous_y - current_y
previous_x, previous_y = current_x, current_y
if geometry_type == "POINT":
distance_array = [geometry["x"], geometry["y"]]
elif geometry_type == "POLYLINE":
distance_array = [list(calculate_distance(path)) for path in geometry["paths"]]
elif geometry_type == "POLYGON":
distance_array = [list(calculate_distance(ring)) for ring in geometry["rings"]]
else:
raise Exception("{} geometry type not supported".format(geometry_type))
return distance_array
這裏可以用來基準功能的腳本：
import time
from functools import wraps
import numpy as np
import geometry_converter as gc
def timethis(func):
'''Decorator that reports the execution time.'''
@wraps(func)
def wrapper(*args, **kwargs):
start = time.time()
result = func(*args, **kwargs)
end = time.time()
print(func.__name__, end-start)
return result
return wrapper
def prepare_data(featCount, size):
''' Create arrays of polygon geometry (see polygon_input above)'''
input = []
for i in xrange(0, featCount):
polygon = {"rings" : []}
#random x,y coordinates inside a quadrant of the world bounding box in a spherical mercator (epsg:3857) projection
ys = np.random.uniform(-20037507.0,0,size).tolist()
xs = np.random.uniform(0,20037507.0,size).tolist()
polygon["rings"].append(zip(xs,ys))
input.append(polygon)
return input
@timethis
def process_data(data):
output = [gc.esriJson_to_CV(x, "POLYGON") for x in data]
return output
data = prepare_data(100, 100000)
process_data(data)
是否有改進，可在用Cython實現提高性能？也許通過使用2D cython數組或carrays？
爲什麼不使用'numpy.diff'來獲取X和Y座標的第一個差值？ – pbreach
因爲看起來從巨大的2D Python列表創建numpy.array太慢了。 –
你也會遇到和cython或c數組一樣的問題。列表不存儲在連續的內存中，而（同類）numpy，cython和c數組。因此，不管這些方法如何，轉換都需要一些時間。我很驚訝'numpy.diff'並不比使用生成器和列表的cython實現快。 – pbreach