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我正在使用嵌套的scipy.integrate.quad调用来集成2维积分。被积函数由numpy函数组成 - 所以传递给它一个输入数组要比效率更高，而不是循环输入并为每个输入调用一次 - 由于numpy的数组，它的速度要快2个数量级。如何调用python scipy quad与数组输入
但是，如果我想将我的integrand只整合到一个维度上 - 但是在其他维度上输入的数据会下降 - 看起来像'scipy'quadpack软件包无法做到无论numpy如何处理阵列输入。有没有其他人看到过这种情况 - 或者找到了解决方法 - 或者我误解了它。我从四得到的错误是：
Traceback (most recent call last):
File "C:\Users\JP\Documents\Python\TestingQuad\TestingQuad_v2.py", line 159, in <module>
fnIntegrate_x(0, 1, NCALLS_SET, True)
File "C:\Users\JP\Documents\Python\TestingQuad\TestingQuad_v2.py", line 35, in fnIntegrate_x
I = Integrate_x(yarray)
File "C:\Users\JP\Documents\Python\TestingQuad\TestingQuad_v2.py", line 23, in Integrate_x
return quad(Integrand, 0, np.pi/2, args=(y))[0]
File "C:\Python27\lib\site-packages\scipy\integrate\quadpack.py", line 247, in quad
retval = _quad(func,a,b,args,full_output,epsabs,epsrel,limit,points)
File "C:\Python27\lib\site-packages\scipy\integrate\quadpack.py", line 312, in _quad
return _quadpack._qagse(func,a,b,args,full_output,epsabs,epsrel,limit)
quadpack.error: Supplied function does not return a valid float.
我已经把的我尝试下面做一个卡通版 - 什么我实际上做了一个比较复杂的积但这是gyst。
肉在顶部 - 底部正在做基准测试以显示我的观点。
import numpy as np
import time
from scipy.integrate import quad
def Integrand(x, y):
'''
Integrand
'''
return np.sin(x)*np.sin(y)
def Integrate_x(y):
'''
Integrate over x given (y)
'''
return quad(Integrand, 0, np.pi/2, args=(y))[0]
def fnIntegrate_x(ystart, yend, nsteps, ArrayInput = False):
'''
'''
yarray = np.arange(ystart,yend, (yend - ystart)/float(nsteps))
I = np.zeros(nsteps)
if ArrayInput :
I = Integrate_x(yarray)
else :
for i,y in enumerate(yarray) :
I[i] = Integrate_x(y)
return y, I
NCALLS_SET = 1000
NSETS = 10
SETS_t = np.zeros(NSETS)
for i in np.arange(NSETS) :
XInputs = np.random.rand(NCALLS_SET, 2)
t0 = time.time()
for x in XInputs :
Integrand(x[0], x[1])
t1 = time.time()
SETS_t[i] = (t1 - t0)/NCALLS_SET
print "Benchmarking Integrand - Single Values:"
print "NCALLS_SET: ", NCALLS_SET
print "NSETS: ", NSETS
print "TimePerCall(s): ", np.mean(SETS_t) , np.std(SETS_t)/ np.sqrt(SETS_t.size)
print "TotalTime: ",np.sum(SETS_t) * NCALLS_SET
'''
Benchmarking Integrand - Single Values:
NCALLS_SET: 1000
NSETS: 10
TimePerCall(s): 1.23999834061e-05 4.06987868647e-06
'''
NCALLS_SET = 1000
NSETS = 10
SETS_t = np.zeros(NSETS)
for i in np.arange(NSETS) :
XInputs = np.random.rand(NCALLS_SET, 2)
t0 = time.time()
Integrand(XInputs[:,0], XInputs[:,1])
t1 = time.time()
SETS_t[i] = (t1 - t0)/NCALLS_SET
print "Benchmarking Integrand - Array Values:"
print "NCALLS_SET: ", NCALLS_SET
print "NSETS: ", NSETS
print "TimePerCall(s): ", np.mean(SETS_t) , np.std(SETS_t)/ np.sqrt(SETS_t.size)
print "TotalTime: ",np.sum(SETS_t) * NCALLS_SET
'''
Benchmarking Integrand - Array Values:
NCALLS_SET: 1000
NSETS: 10
TimePerCall(s): 2.00009346008e-07 1.26497018465e-07
'''
NCALLS_SET = 1000
NSETS = 100
SETS_t = np.zeros(NSETS)
for i in np.arange(NSETS) :
t0 = time.time()
fnIntegrate_x(0, 1, NCALLS_SET, False)
t1 = time.time()
SETS_t[i] = (t1 - t0)/NCALLS_SET
print "Benchmarking fnIntegrate_x - Single Values:"
print "NCALLS_SET: ", NCALLS_SET
print "NSETS: ", NSETS
print "TimePerCall(s): ", np.mean(SETS_t) , np.std(SETS_t)/ np.sqrt(SETS_t.size)
print "TotalTime: ",np.sum(SETS_t) * NCALLS_SET
'''
NCALLS_SET: 1000
NSETS: 100
TimePerCall(s): 0.000165750000477 8.61204306241e-07
TotalTime: 16.5750000477
'''
NCALLS_SET = 1000
NSETS = 100
SETS_t = np.zeros(NSETS)
for i in np.arange(NSETS) :
t0 = time.time()
fnIntegrate_x(0, 1, NCALLS_SET, True)
t1 = time.time()
SETS_t[i] = (t1 - t0)/NCALLS_SET
print "Benchmarking fnIntegrate_x - Array Values:"
print "NCALLS_SET: ", NCALLS_SET
print "NSETS: ", NSETS
print "TimePerCall(s): ", np.mean(SETS_t) , np.std(SETS_t)/ np.sqrt(SETS_t.size)
'''
**** Doesn't work!!!! *****
Traceback (most recent call last):
File "C:\Users\JP\Documents\Python\TestingQuad\TestingQuad_v2.py", line 159, in <module>
fnIntegrate_x(0, 1, NCALLS_SET, True)
File "C:\Users\JP\Documents\Python\TestingQuad\TestingQuad_v2.py", line 35, in fnIntegrate_x
I = Integrate_x(yarray)
File "C:\Users\JP\Documents\Python\TestingQuad\TestingQuad_v2.py", line 23, in Integrate_x
return quad(Integrand, 0, np.pi/2, args=(y))[0]
File "C:\Python27\lib\site-packages\scipy\integrate\quadpack.py", line 247, in quad
retval = _quad(func,a,b,args,full_output,epsabs,epsrel,limit,points)
File "C:\Python27\lib\site-packages\scipy\integrate\quadpack.py", line 312, in _quad
return _quadpack._qagse(func,a,b,args,full_output,epsabs,epsrel,limit)
quadpack.error: Supplied function does not return a valid float.
'''
酷派，将在某个时候尝试这一点 - 它是自一会我看了这段代码 - 但可能在未来会有用。 – JPH 2015-07-08 19:09:19