I have two data sets, one,q,with the shape, 25,100,100 and another one,p,with shape -25,1. q is a gridded with 100 x 100 points in the horizontal(x,y), where (xi,yi) represents each grid and 25 is the number of observations at each (xi,yi). I tried both numpy.correlate(p,q) and pearsonr(p,q) but both output error.

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ValueError Traceback (most recent call last)

<ipython-input-833-917b57fc9876> in <module>()

----> 1 correl=np.corrcoef(pcs1[:,3],sstano[:,:,:])

/home/nuncio/anaconda2/lib/python2.7/site-packages/numpy/lib/function_base.pyc in corrcoef(x, y, rowvar, bias, ddof)

2143 warnings.warn('bias and ddof have no affect and are deprecated',

2144 DeprecationWarning)

-> 2145 c = cov(x, y, rowvar)

2146 try:

2147 d = diag(c)

/home/nuncio/anaconda2/lib/python2.7/site-packages/numpy/lib/function_base.pyc in cov(m, y, rowvar, bias, ddof, fweights, aweights)

2022 if rowvar == 0 and y.shape[0] != 1:

2023 y = y.T

-> 2024 X = np.vstack((X, y))

2025

2026 if ddof is None:

/home/nuncio/anaconda2/lib/python2.7/site-packages/numpy/core/shape_base.pyc in vstack(tup)

228

229 """

--> 230 return _nx.concatenate([atleast_2d(_m) for _m in tup], 0)

231

232 def hstack(tup):

ValueError: all the input arrays must have same number of dimensions

ANy solutions

THanks

nuncio