CODEWITHSUNDEEP
pythonnumpy
FooBar
FooBar

Reputation: 16488

How to vectorize this cumulative operation?

Let W be some matrix of dimension (x, nP) [see end of question]

Right now, I'm doing the following code:

uUpperDraw = np.zeros(W.shape)
for p in np.arange(0, nP):
    uUpperDraw[s, p] = (W[s+1,:(p+1)]).sum()

I want to vectorize this for efficiency gains. Given a pGrid = [0, 1, ...], how can I reproduce the following?

uUpperDraw = np.array([sum(W[x, 0]), sum(W[x,0] + W[x, 1]), sum(W[x,0] + W[x, 1] + W[x, 2]) ...

Here is some reproducible example. 

>>> s, nP
(3, 10)
>>> W

array([[ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
         0.        ,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
         0.        ,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
         0.        ,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
         0.        ,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 2.        ,  1.63636364,  1.38461538,  1.2       ,  1.05882353,
         0.94736842,  0.85714286,  0.7826087 ,  0.72      ,  0.66666667]])
>>> uUpperDraw
array([[  0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ],
       [  0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ],
       [  0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ],
       [  2.        ,   3.63636364,   5.02097902,   6.22097902,
          7.27980255,   8.22717097,   9.08431383,   9.86692252,
         10.58692252,  11.25358919],
       [  0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ,   0.        ,   0.        ,
          0.        ,   0.        ]])

Upvotes: 2

Views: 126

Answers (1)

plonser
plonser

Reputation: 3363

This looks like the cumulative sum. When you want to have the cumulative sum for each row seperately this here works

uUpperDraw = np.cumsum(W,axis=1)

Upvotes: 4

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