mercaderd / pynoci Goto Github PK

Dear @mercaderd,

First of all I want to say thank you for your realisation of ICA-by blocks in Python! This was very useful for my work.
Secondly I want to ask you for advice regarding function ICA_by_two_blocks. Is it possible to use 3 blocks there for the correlation calculation?
In this part I changed nblocks to 3 and inserted calculation of B3 and Y3 but I am stuck with the CMat calculation:

nblocks=2
blocks = np.empty([block_length, T, nblocks])
for i in range(nblocks):
blocks[:,:, i]=X[(i * block_length):((i+1) * block_length),:]
correlation_data = []
for i in arange(maxICs):
B1 = jadeR(blocks[:, :, 0], m=i + 1
B2 = jadeR(blocks[:, :, 1], m=i + 1)
Y1 = B1 * matrix(blocks[:, :, 0])
Y2 = B2 * matrix(blocks[:, :, 1])
CMat = np.sort(np.nanmax(np.abs(np.corrcoef(Y1, Y2)[:i + 1, i + 1:]), axis=1))

If it is possible could you please give me advice how correctly extrapolate this algorythm inlo 3-blocks sutuation?
Thank you very much in advance!

Best regards,
Polina