numpy中2d数组的选定元素的矢量化赋值语句

Question

I am a beginner in python. I was wondering if there is a "good" way to do this operation without using for loops. Consider the problem

u = zeros((4,2))
u_pres = array([100,200,300])
row_col_index = array([[0,0,2], [0,1,1]])

I want to assign u[0,0], u[0,1], and u[2,1] as 100,200 and 300 respectively. I wanted to do something of the form

u[row_col_index] = u_pres

If u were a 1d array such an assignment works, but am unable to figure out how to make this work for 2d arrays. Your suggestions will be most helpful. Thanks

Answer 1

You're almost there.

What you need is the following:

u[row_col_index[0], row_col_index[1]] = u_pres

Explanation:

Since you say you're a beginner in Python (I'm too!), I thought I might tell you this; it is considered unpythonic to load a module the way you did:

#BAD
from numpy import *
#GOOD
from numpy import array #or whatever it is you need
#GOOD
import numpy as np #if you need lots of things, this is better

Explanation:

In [18]: u = np.zeros(10)

In [19]: u
Out[19]: array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.])

#1D assignment
In [20]: u[0] = 1

In [21]: u[1] = 10

In [22]: u[-1] = 9 #last element

In [23]: u[-2] = np.pi #second last element

In [24]: u
Out[24]: 
array([  1.        ,  10.        ,   0.        ,   0.        ,
         0.        ,   0.        ,   0.        ,   0.        ,
         3.14159265,   9.        ])

In [25]: u.shape
Out[25]: (10,)

In [27]: u[9] #calling
Out[27]: 9.0

#2D case
In [28]: y = np.zeros((4,2))

In [29]: y
Out[29]: 
array([[ 0.,  0.],
       [ 0.,  0.],
       [ 0.,  0.],
       [ 0.,  0.]])

In [30]: y[1] = 10 #this will assign all the second row to be 10

In [31]: y
Out[31]: 
array([[  0.,   0.],
       [ 10.,  10.],
       [  0.,   0.],
       [  0.,   0.]])

In [32]: y[0,1] = 9 #now this is 2D assignment, we use 2 indices!

In [33]: y[3] = np.pi #all 4th row, similar to y[3,:], ':' means all

In [34]: y[2,1] #3rd row, 2nd column
Out[34]: 0.0


In [36]: y[2,1] = 7

In [37]: 

In [37]: y
Out[37]: 
array([[  0.        ,   9.        ],
       [ 10.        ,  10.        ],
       [  0.        ,   7.        ],
       [  3.14159265,   3.14159265]])

In your case, we had the 1st array of the row_col_index ( row_col_index[0] ) to be used for the rows and the 2nd array ( row_col_index[1] ) to be used for the columns.

Finally, if you're not using ipython , I suggest you do, it will assist you in the learning process and in many other things.

I hope this helps.