[SOLVED] how to call python scipy quad with array inputs

I am using nested scipy.integrate.quad calls to integrate a 2 dimensional integrand. The integrand is made of numpy functions - so it is much more efficient to pass it an array of inputs - than to loop through the inputs and call it once for each one - it is ~2 orders of magnitude faster because of numpy's arrays.

However.... if I want to integrate my integrand over only one dimension - but with an array of inputs over the other dimension things fall down - it seems like the 'scipy' quadpack package isn't able to do whatever it is that numpy does to handle arrayed inputs. Has anyone else seen this - and or found a way of fixing it - or am i misunderstanding it. The error i get from quad is :

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.

I have put a cartoon version of what i'm trying to do below - what i'm actually doing has a more complicated integrand but this is the gyst.

The meat is at the top - the bottom is doing benchmarking to show my point.

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.

'''