I use lambdify
to compile an expression which is a function of certain parameters. Each parameter has N
points. So I need to evaluate the expression N
times. The following shows a simplified example on how this is done.
import numpy as np
from sympy.parsing.sympy_parser import parse_expr
from sympy.utilities.lambdify import lambdify, implemented_function
from sympy import S, Symbol
from sympy.utilities.autowrap import ufuncify
def CreateMagneticFieldsList(dataToSave,equationString,DSList):
expression = S(equationString)
numOfElements = len(dataToSave["MagneticFields"])
#initialize the magnetic field output array
magFieldsArray = np.empty(numOfElements)
magFieldsArray[:] = np.NaN
lam_f = lambdify(tuple(DSList),expression,modules='numpy')
try:
for i in range(numOfElements):
replacementList = np.zeros(len(DSList))
for j in range(len(DSList)):
replacementList[j] = dataToSave[DSList[j]][i]
try:
val = np.double(lam_f(*replacementList))
except:
val = np.nan
magFieldsArray[i] = val
except:
print("Error while evaluating the magnetic field expression")
return magFieldsArray
list={"MagneticFields":list(range(10000)), "Chx":list(range(10000))}
out=CreateMagneticFieldsList(list,"MagneticFields*5+Chx",["MagneticFields","Chx"])
print(out)
Is there a way to optimize this call further? Specifically, I mean is there a way to make lambdify
include that I'm calculating for a list of points, so that the loop evalulation can be optimized?
Thanks to @asmeurer, he gave the idea on how to do it.
Since lambdify
is compiled using numpy, then one could simply pass the lists as arguments! The following is a working example
#!/usr/bin/python3
import numpy as np
from sympy.parsing.sympy_parser import parse_expr
from sympy.utilities.lambdify import lambdify, implemented_function
from sympy import S, Symbol
from sympy.utilities.autowrap import ufuncify
def CreateMagneticFieldsListOpt(dataToSave,equationString,DSList):
expression = S(equationString)
numOfElements = len(dataToSave["MagneticFields"])
#initialize the magnetic field output array
magFieldsArray = np.empty(numOfElements)
magFieldsArray[:] = np.NaN
lam_f = lambdify(tuple(DSList),expression,modules='numpy')
replacementList = [None]*len(DSList)
for j in range(len(DSList)):
replacementList[j] = np.array(dataToSave[DSList[j]])
print(replacementList)
magFieldsArray = np.double(lam_f(*replacementList))
return magFieldsArray
list={"MagneticFields":[1,2,3,4,5],"ChX":[2,4,6,8,10]}
out=CreateMagneticFieldsListOpt(list,"MagneticFields*5+ChX",["MagneticFields","ChX"])
print(out)