nws_tools.corrcheck

nws_tools.corrcheck(*args, **kwargs)[source]

Sanity checks for statistical dependence matrices

Parameters:

Dynamic : Usage as follows

corrcheck(A) : input is NumPy 2darray

shows some statistics for the statistical dependence matrix A

corrcheck(A,label) : input is NumPy 2darray and [‘string’]

shows some statistics for the matrix A and uses label, a list containing one string, as title in figures.

corrcheck(A,B,C,...) : input are many NumPy 2darrays

shows some statistics for the statistical dependence matrices A, B, C,....

corrcheck(A,B,C,...,label) : input are many NumPy 2darrays and a list of strings

shows some statistics for the statistical dependence matrices A, B, C,.... and uses the list of strings label to generate titles in figures. Note that len(label) has to be equal to the number of input matrices.

corrcheck(T) : input is NumPy 3darray

shows some statistics for statistical dependence matrices stored in the tensor T. The storage scheme has to be

T[:,:,0] = A

T[:,:,1] = B

T[:,:,2] = C

etc.

where A, B, C,... are matrices.

corrcheck(T,label) : input is NumPy 3darray and list of strings

shows some statistics for matrices stored in the tensor T. The storage scheme has to be

T[:,:,0] = A

T[:,:,1] = B

T[:,:,2] = C

etc.

where A, B, C,... are matrices. The list of strings label is used to generate titles in figures. Note that len(label) has to be equal to T.shape[2]

corrcheck(...,title=’mytitle’) : input is any of the above

same as above and and uses the string mytitle as window name for figures.

Returns:

Nothing : None

See also

None

Notes

None