Python - Using 2d map() functional programing-CodePudding

Im trying to map an array to a function. Then map that that array into another function but not sure how to deal with map type object or how to map multidimensional arrays.

import numpy as np
import sympy as sp

nn = np.arange(2)
n= len(nn)
x0=0
y0=0
r=10
num=11

def func1(i):
    x1, y1 = x0   r * sp.cos(2 * sp.pi * i / n), y0   r * sp.sin(2 * sp.pi * i / n)
    return np.array([sp.N(x1),sp.N(y1)])

def func2(x1,y1):
    x, y = np.linspace(x0, x1, num), np.linspace(y0, y1, num)
    return x,y


map1=map(func1,nn)
map2=map(func2,map1[0],map1[1])

Want expect out put to be an array [[0,1,2,3,4,5,6,7,8,9,10],[0,0,0,0,0,0,0,0,0,0,0]],[[0,-1,-2,-3,-4,-5,-6,-7,-8,-9,-10],[0,0,0,0,0,0,0,0,0,0,0]]

CodePudding user response：

I'd express this as a single loop, or list comprehension. The two functions are chained, not mapped

In [60]: def func1(i):
    ...:     x1, y1 = x0   r * sp.cos(2 * sp.pi * i / n), y0   r * sp.sin(2 * sp
    ...: .pi * i / n)
    ...:     print(x1,y1)
    ...:     return np.array([int(x1),int(y1)])
    ...: 
    ...: def func2(x1,y1):
    ...:     x, y = np.linspace(x0, x1, num), np.linspace(y0, y1, num)
    ...:     return x,y
    ...: 
    ...: 
In [61]: [func2(*func1(i)) for i in range(2)]
10 0
-10 0
Out[61]: 
[(array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10.]),
  array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])),
 (array([  0.,  -1.,  -2.,  -3.,  -4.,  -5.,  -6.,  -7.,  -8.,  -9., -10.]),
  array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]))]
In [62]: np.array(_, int)
Out[62]: 
array([[[  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10],
        [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0]],

       [[  0,  -1,  -2,  -3,  -4,  -5,  -6,  -7,  -8,  -9, -10],
        [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0]]])

To use map:

np.array(list(map(lambda i: func2(*func1(i)), range(2))),int)

The use of sympy is bit obscure, but apparently it's to get "exact" sin/cos values - but they still have to be converted to int to be used by numpy. Use of sympy together with numpy has lots of pitfalls.