Qfyilyi

Lets say edata and tdata two 2D numpy array with shape (x,6) and (y,6) where x and y are two arbitrary number and must not be equal. Now I have to check if there is any row in edata such that both 2nd and 3rd column value of that row equals to that of some row of tdata. If there is any such row then save them in another. For now I have written the following code. But I think numpy has better way to that instead of explicitly iterating and checking for values. Can you suggest me more efficient way?

res = np.array(, dtype=np.float64).reshape(0,6)

for line in edata:

    ind = line[1] == tdata[:,1]  

    ind = line[2] == tdata[ind,2]

    if np.any(ind):

        res = np.vstack((res,line))

You can use equal and outer to see if any value in a column of edata is in a column of tdata. You check for both the 2nd and 3rd columns, then use any on axis=1 to get edata rows as required such as:

res = edata[ (np.equal.outer(edata[:,1],tdata[:,1])

              &np.equal.outer(edata[:,2],tdata[:,2])).any(1) ,:]

for example, with simple input:

edata = np.arange(4*6).reshape(4,6)

tdata = np.arange(6*6).reshape(6,6) + 12



print (res)

array([[12, 13, 14, 15, 16, 17],

       [18, 19, 20, 21, 22, 23]])

which are the last two rows of edata that have the same value in column 2 and 3 than the first two rows of tdata