将函数参数间隔分解为单独部分时出错。并行Python

Question

首先，对所有代码抱歉。我很难制定一个具体的问题。我已经修好了一段时间，只是无法让它工作。该错误消息不是很有帮助。我将不胜感激一点帮助。

为了加速计算，我想对函数'EMatCreatorrx（umin，umax，vmin，vmax，stepsize，pstep，alphamax，A，rot）：'的三个实例并行执行不同的参数范围。

umin，umax和vmin，vmax分别定义了要在u和v方向分别计算的值的范围。我想通过将u范围分成三个较小的范围来划分函数。

我已经证明了我的拼接代码的功能分成三个独立的部分，然后通过运行正确地重新加入工作如下：

import pp 
import sys 

import numpy as N 
import scipy as sp 
from scipy import integrate as Int 
from scipy import special as S 
import math 

cos=sp.cos 
sin=sp.sin 
exp=sp.exp 
sqrt=sp.sqrt 
j=S.jn 
pi=N.pi 
floor=N.floor 

def EMatCreatorrx(umin,umax,vmin,vmax,stepsize,pstep,alphamax,A,rot): #pstep needs to be pi/n for n=0,1,2,3,... This is so there will be an odd number of samples when calculating the PSF. This is necessary to increase the accuracy of Simpson's method. 
    mnum=N.int(((umax-umin)/stepsize)+1) 
    nnum=N.int(((vmax-vmin)/stepsize)+1) 
    pnum=N.int((2*pi/pstep)+1) 
    gridshape=(mnum,nnum,pnum) 
    I0=N.zeros(gridshape,dtype=complex) 
    I1=N.zeros(gridshape,dtype=complex) 
    I2=N.zeros(gridshape,dtype=complex) 
    E01=N.zeros(gridshape,dtype=complex) 
    E02=N.zeros(gridshape,dtype=complex) 
    E03=N.zeros(gridshape,dtype=complex) 
    for m,u in enumerate(N.linspace(umin,umax,num=mnum)): 
     for n,v in enumerate(N.linspace(vmin,vmax,num=nnum)): 
      for i,p in enumerate(N.linspace(0,2*pi,num=pnum)):    
       vp = sqrt((v*cos(p))**2 + (v*sin(p)*cos(rot)-u*sin(rot))**2) 
       up = (v*cos(p)*sin(rot) + u*cos(rot)) 
       pp= N.arctan2(v*sin(p)*cos(rot) - u*sin(rot), v*cos(p)) 
       I0real=lambda theta: N.real((sqrt(cos(theta))*sin(theta))*(1+cos(theta))* (j(0,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I0imaginary=lambda theta: N.imag((sqrt(cos(theta))*sin(theta))*(1+cos(theta))*(j(0,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I0real_integral= Int.quad(I0real, 0, alphamax) 
       I0imag_integral= Int.quad(I0imaginary, 0, alphamax) 
       I1real=lambda theta: N.real(sqrt(cos(theta))*((sin(theta))**2)*j(1,vp*sin(theta)/(sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I1imaginary=lambda theta: N.imag(sqrt(cos(theta))*((sin(theta))**2)*j(1,vp*sin(theta)/(sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I1real_integral= Int.quad(I1real, 0, alphamax) 
       I1imag_integral= Int.quad(I1imaginary, 0, alphamax) 
       I2real=lambda theta: N.real((sqrt(cos(theta))*sin(theta))*(1-cos(theta))*(j(2,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I2imaginary=lambda theta: N.imag((sqrt(cos(theta))*sin(theta))*(1-cos(theta))*(j(2,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I2real_integral= Int.quad(I2real, 0, alphamax) 
       I2imag_integral= Int.quad(I2imaginary, 0, alphamax) 
       I0.real[m,n,i]=I0real_integral[0] 
       I0.imag[m,n,i]=I0imag_integral[0] 
       I1.real[m,n,i]=I1real_integral[0] 
       I1.imag[m,n,i]=I1imag_integral[0] 
       I2.real[m,n,i]=I2real_integral[0] 
       I2.imag[m,n,i]=I2imag_integral[0] 
       E01[m,n,i]=-A*(1j*(I0[m,n,i]+I2[m,n,i]*cos(2*pp))) 
       E02[m,n,i]=-A*(cos(rot)*1j*I2[m,n,i]*sin(2*pp) - sin(rot)*2*I1[m,n,i]*cos(pp)) 
       E03[m,n,i]=-A*(sin(rot)*1j*I2[m,n,i]*sin(2*pp) + cos(rot)*2*I1[m,n,i]*cos(pp)) 
    return E01,E02,E03,pstep 


#EMatCreatorrx(umin,umax,vmin,vmax,stepsize,pstep,alphamax,A,rot): #Enter parameters below in tuple "params." 

params=-2,2,-2,2,.2,N.pi/10,1,1,0 
############################################################################################################## 

mnum=N.int(((params[1]-params[0])/params[4])+1) 
nnum=N.int(((params[3]-params[2])/params[4])+1) 
pnum=N.int((2*N.pi/params[5])+1) 
phold=N.zeros((mnum,nnum,pnum), dtype=complex),N.zeros((mnum,nnum,pnum), dtype=complex),N.zeros((mnum,nnum,pnum), dtype=complex), params[5] 

uindarr = [(m, u) for m,u in enumerate(N.linspace(params[0],params[1],num=mnum))] 

ind_end1=floor(len(uindarr)/3) 
spa_end1=uindarr[int(ind_end1)][1] 

ind_beg2=ind_end1+1 
spa_beg2=uindarr[int(ind_beg2)][1] 
ind_end2=2*floor(len(uindarr)/3) 
spa_end2=uindarr[int(ind_end2)][1] 

ind_beg3=ind_end2+1 
spa_beg3=uindarr[int(ind_beg3)][1] 

job1 = EMatCreatorrx(params[0],spa_end1,params[2],params[3],params[4],params[5],params[6],params[7],params[8]) 
job2 = EMatCreatorrx(spa_beg2,spa_end2,params[2],params[3],params[4],params[5],params[6],params[7],params[8]) 
job3 = EMatCreatorrx(spa_beg3,params[1],params[2],params[3],params[4],params[5],params[6],params[7],params[8]) 

phold[0][:ind_end1+1,:,:]=job1[0] 
phold[0][ind_beg2:ind_end2+1,:,:]=job2[0] 
phold[0][ind_beg3:,:,:]=job3[0] 

phold[1][:ind_end1+1,:,:]=job1[1] 
phold[1][ind_beg2:ind_end2+1,:,:]=job2[1] 
phold[1][ind_beg3:,:,:]=job3[1] 

phold[2][:ind_end1+1,:,:]=job1[2] 
phold[2][ind_beg2:ind_end2+1,:,:]=job2[2] 
phold[2][ind_beg3:,:,:]=job3[2] 

后这个工作，我试图以计算实现并行蟒蛇三片并联使用此代码：

import pp 
import sys 

import numpy as N 
import scipy as sp 
from scipy import integrate as Int 
from scipy import special as S 
import math 

cos=sp.cos 
sin=sp.sin 
exp=sp.exp 
sqrt=sp.sqrt 
j=S.jn 
pi=sp.pi 
floor=N.floor 

def EMatCreatorrx(umin,umax,vmin,vmax,stepsize,pstep,alphamax,A,rot): #pstep needs to be pi/n for n=0,1,2,3,... This is so there will be an odd number of samples when calculating the PSF. This is necessary to increase the accuracy of Simpson's method. 
    cos=sp.cos 
    sin=sp.sin 
    exp=sp.exp 
    sqrt=sp.sqrt 
    j=S.jn 
    pi=sp.pi 
    mnum=N.int(((umax-umin)/stepsize)+1) 
    nnum=N.int(((vmax-vmin)/stepsize)+1) 
    pnum=N.int((2*pi/pstep)+1) 
    gridshape=(mnum,nnum,pnum) 
    I0=N.zeros(gridshape,dtype=complex) 
    I1=N.zeros(gridshape,dtype=complex) 
    I2=N.zeros(gridshape,dtype=complex) 
    E01=N.zeros(gridshape,dtype=complex) 
    E02=N.zeros(gridshape,dtype=complex) 
    E03=N.zeros(gridshape,dtype=complex) 
    for m,u in enumerate(N.linspace(umin,umax,num=mnum)): 
     for n,v in enumerate(N.linspace(vmin,vmax,num=nnum)): 
      for i,p in enumerate(N.linspace(0,2*pi,num=pnum)):    
       vp = sqrt((v*cos(p))**2 + (v*sin(p)*cos(rot)-u*sin(rot))**2) 
       up = (v*cos(p)*sin(rot) + u*cos(rot)) 
       pp= N.arctan2(v*sin(p)*cos(rot) - u*sin(rot), v*cos(p)) 
       I0real=lambda theta: N.real((sqrt(cos(theta))*sin(theta))*(1+cos(theta))*(j(0,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I0imaginary=lambda theta: N.imag((sqrt(cos(theta))*sin(theta))*(1+cos(theta))*(j(0,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I0real_integral= Int.quad(I0real, 0, alphamax) 
       I0imag_integral= Int.quad(I0imaginary, 0, alphamax) 
       I1real=lambda theta: N.real(sqrt(cos(theta))*((sin(theta))**2)*j(1,vp*sin(theta)/(sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I1imaginary=lambda theta: N.imag(sqrt(cos(theta))*((sin(theta))**2)*j(1,vp*sin(theta)/(sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I1real_integral= Int.quad(I1real, 0, alphamax) 
       I1imag_integral= Int.quad(I1imaginary, 0, alphamax) 
       I2real=lambda theta: N.real((sqrt(cos(theta))*sin(theta))*(1-cos(theta))*(j(2,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I2imaginary=lambda theta: N.imag((sqrt(cos(theta))*sin(theta))*(1-cos(theta))*(j(2,vp*sin(theta)/sin(alphamax)))*exp((1j*up*cos(theta))/((sin(alphamax))**2))) 
       I2real_integral= Int.quad(I2real, 0, alphamax) 
       I2imag_integral= Int.quad(I2imaginary, 0, alphamax) 
       I0.real[m,n,i]=I0real_integral[0] 
       I0.imag[m,n,i]=I0imag_integral[0] 
       I1.real[m,n,i]=I1real_integral[0] 
       I1.imag[m,n,i]=I1imag_integral[0] 
       I2.real[m,n,i]=I2real_integral[0] 
       I2.imag[m,n,i]=I2imag_integral[0] 
       E01[m,n,i]=-A*(1j*(I0[m,n,i]+I2[m,n,i]*cos(2*pp))) 
       E02[m,n,i]=-A*(cos(rot)*1j*I2[m,n,i]*sin(2*pp) - sin(rot)*2*I1[m,n,i]*cos(pp)) 
       E03[m,n,i]=-A*(sin(rot)*1j*I2[m,n,i]*sin(2*pp) + cos(rot)*2*I1[m,n,i]*cos(pp)) 
    return E01,E02,E03,pstep 






#EMatCreatorrx(umin,umax,vmin,vmax,stepsize,pstep,alphamax,A,rot): #Enter parameters below in tuple "params." 

params=-2,2,-2,2,.2,N.pi/10,1,1,0 
############################################################################################################## 

mnum=N.int(((params[1]-params[0])/params[4])+1) 
nnum=N.int(((params[3]-params[2])/params[4])+1) 
pnum=N.int((2*N.pi/params[5])+1) 
phold=N.zeros((mnum,nnum,pnum), dtype=complex),N.zeros((mnum,nnum,pnum), dtype=complex),N.zeros((mnum,nnum,pnum), dtype=complex), params[5] 

uindarr = [(m, u) for m,u in enumerate(N.linspace(params[0],params[1],num=mnum))] 

ind_end1=floor(len(uindarr)/3) 
spa_end1=uindarr[int(ind_end1)][1] 

ind_beg2=ind_end1+1 
spa_beg2=uindarr[int(ind_beg2)][1] 
ind_end2=2*floor(len(uindarr)/3) 
spa_end2=uindarr[int(ind_end2)][1] 

ind_beg3=ind_end2+1 
spa_beg3=uindarr[int(ind_beg3)][1] 

ppservers =() 
job_server = pp.Server() 
fn = pp.Template(job_server, EMatCreatorrx,(), ("scipy as sp", "numpy as N", "scipy.special as S", "scipy.integrate as Int",)) 
job1 = fn.submit(params[0],spa_end1,params[2],params[3],params[4],params[5],params[6],params[7],params[8]) 
job2 = fn.submit(spa_beg2,spa_end2,params[2],params[3],params[4],params[5],params[6],params[7],params[8]) 
job3 = fn.submit(spa_beg3,params[1],params[2],params[3],params[4],params[5],params[6],params[7],params[8]) 

phold[0][:ind_end1+1,:,:]=job1[0] 
phold[0][ind_beg2:ind_end2+1,:,:]=job2[0] 
phold[0][ind_beg3:,:,:]=job3[0] 

phold[1][:ind_end1+1,:,:]=job1[1] 
phold[1][ind_beg2:ind_end2+1,:,:]=job2[1] 
phold[1][ind_beg3:,:,:]=job3[1] 

phold[2][:ind_end1+1,:,:]=job1[2] 
phold[2][ind_beg2:ind_end2+1,:,:]=job2[2] 
phold[2][ind_beg3:,:,:]=job3[2] 


print "computation complete" 

当我试图运行上面的代码，我得到的文件错误的以下终结：

Traceback (most recent call last): 
    File "<stdin>", line 1, in <module> 
    File "C:\Users\tph89\Desktop\Python Path\parallel python\parallel2.py", line 104, in <module> 
    job1 = fn.submit((params[0],spa_end1,params[2],params[3],params[4],params[5],params[6],params[7],params[8])) 
    File "C:\Users\tph89\Desktop\Python Path\parallel python\pp.py", line 270, in submit 
    self.group, self.globals) 
    File "C:\Users\tph89\Desktop\Python Path\parallel python\pp.py", line 459, in submit 
    sfunc = self.__dumpsfunc((func,) + depfuncs, modules) 
    File "C:\Users\tph89\Desktop\Python Path\parallel python\pp.py", line 637, in __dumpsfunc 
    sources = [self.__get_source(func) for func in funcs] 
    File "C:\Users\tph89\Desktop\Python Path\parallel python\pp.py", line 704, in __get_source 
    sourcelines = inspect.getsourcelines(func)[0] 
    File "C:\Users\tph89\Python27\lib\inspect.py", line 693, in getsourcelines 
    else: return getblock(lines[lnum:]), lnum + 1 
    File "C:\Users\tph89\Python27\lib\inspect.py", line 677, in getblock 
    tokenize.tokenize(iter(lines).next, blockfinder.tokeneater) 
    File "C:\Users\tph89\Python27\lib\tokenize.py", line 169, in tokenize 
    tokenize_loop(readline, tokeneater) 
    File "C:\Users\tph89\Python27\lib\tokenize.py", line 175, in tokenize_loop 
    for token_info in generate_tokens(readline): 
    File "C:\Users\tph89\Python27\lib\tokenize.py", line 296, in generate_tokens 
    raise TokenError, ("EOF in multi-line string", strstart) 
tokenize.TokenError: ('EOF in multi-line string', (2, 0)) 

在这一点上，我有点失落。你有没有遇到过这个错误？如果是这样，那么问题是什么？任何输入是不胜感激。谢谢！

Answer 1

我也有这个问题以及使用并行Python，也是由于一个标记错误。在我的例子中，我的一个helper函数有双缩进（八个空格，由于复制粘贴现象，而函数声明位于零空格的正确缩进级别）--Spyder的主要解释器刚刚处理了这个，但标记化明显不。

在OP的情况下：基于上面格式化代码的方式，并基于tokenize顶部的注释，错误可能是因为空行上没有空白;这将返回“”，其中评论说是作为EOF处理。