place random numbers for nan values numpy array

I have a numpy array X that has `nan` values in it. ``` X = np.array([[ 1., 2., 3.], [ 4., nan, 54.], [ 90., 32., nan], [ 55., 42., 86.]]) ``` I'd like to replace all nan values with a different random number. I can generate the random number easily with `np.random.randn()`. I can use a mask to locate and count the nans. ``` mx = ma.masked_array(X,mask=np.isnan(X)) //locate nans mx.mask.sum() // count nans so I know how many random values to generate ``` My issue is I don't know how to input them in quickly and efficiently. The example I gave above is a very small dataset, but I have one that is much much larger. Therefore efficiency is key. If I try ``` X[mx.mask] = np.random.randn() //or X[mx.mask]=np.random.randn(mx.mask.sum()) ``` I replace each nan with the same random number which is not what I want or I get a broadcast error in the second example. Any suggestions?