我试图通过计算身体两侧的影响来计算埋藏物体的重力效应,然后总结贡献以在一个站点获得一次测量,重复多个站点。代码如下(正文是一个正方形,代码围绕它顺时针计算,这就是它从-x返回到-x坐标的原因)
grav = []
x=si.arange(-30.0,30.0,0.5)
#-9.79742526 9.78716693 22.32153704 27.07382349 2138.27146193
xcorn = (-9.79742526,9.78716693 ,9.78716693 ,-9.79742526,-9.79742526)
zcorn = (22.32153704,22.32153704,27.07382349,27.07382349,22.32153704)
gamma = (6.672*(10**-11))#'N m^2 / Kg^2'
rho = 2138.27146193#'Kg / m^3'
grav = []
iter_time=[]
def procedure():
for i in si.arange(len(x)):# cycles position
t0=time.clock()
sum_lines = 0.0
for n in si.arange(len(xcorn)-1):#cycles corners
x1 = xcorn[n]-x[i]
x2 = xcorn[n+1]-x[i]
z1 = zcorn[n]-0.0 #just depth to corner since all observations are on the surface.
z2 = zcorn[n+1]-0.0
r1 = ((z1**2) + (x1**2))**0.5
r2 = ((z2**2) + (x2**2))**0.5
O1 = si.arctan2(z1,x1)
O2 = si.arctan2(z2,x2)
denom = z2-z1
if denom == 0.0:
denom = 1.0e-6
alpha = (x2-x1)/denom
beta = ((x1*z2)-(x2*z1))/denom
factor = (beta/(1.0+(alpha**2)))
term1 = si.log(r2/r1)#log base 10
term2 = alpha*(O2-O1)
sum_lines = sum_lines + (factor*(term1-term2))
sum_lines = sum_lines*2*gamma*rho
grav.append(sum_lines)
t1 = time.clock()
dt = t1-t0
iter_time.append(dt)
任何有关加快此循环的帮助都将不胜感激。
答案 0 :(得分:1)
你的xcorn和zcorn值重复,所以请考虑缓存一些计算的结果。
查看timeit和profile模块,以获取有关计算时间最多的信息。
答案 1 :(得分:1)
在Python循环中访问numpy数组的各个元素是非常低效的。例如,这个Python循环:
for i in xrange(0, len(a), 2):
a[i] = i
会慢得多:
a[::2] = np.arange(0, len(a), 2)
您可以使用更好的算法(更少的时间复杂度)或在numpy
数组上使用向量运算,如上例所示。但更快的方法可能只是使用Cython编译代码:
#cython: boundscheck=False, wraparound=False
#procedure_module.pyx
import numpy as np
cimport numpy as np
ctypedef np.float64_t dtype_t
def procedure(np.ndarray[dtype_t,ndim=1] x,
np.ndarray[dtype_t,ndim=1] xcorn):
cdef:
Py_ssize_t i, j
dtype_t x1, x2, z1, z2, r1, r2, O1, O2
np.ndarray[dtype_t,ndim=1] grav = np.empty_like(x)
for i in range(x.shape[0]):
for j in range(xcorn.shape[0]-1):
x1 = xcorn[j]-x[i]
x2 = xcorn[j+1]-x[i]
...
grav[i] = ...
return grav
没有必要定义所有类型,但如果你需要比Python更快的速度,你应该至少定义数组和循环索引的类型。
您可以使用cProfile
(Cython支持),而不是手动调用time.clock()
。
致电procedure()
:
#!/usr/bin/env python
import pyximport; pyximport.install() # pip install cython
import numpy as np
from procedure_module import procedure
x = np.arange(-30.0,30.0,0.5)
xcorn = np.array((-9.79742526,9.78716693 ,9.78716693 ,-9.79742526,-9.79742526))
grav = procedure(x, xcorn)