Visualizing Correlation

Say we have a matrix A of shape N x M , which can be viewed as a collection of N vectors of shape 1 x M . The code below gives us the correlation matrix of A :

A_corr = np.corrcoef(A)  # shape: (N, N)

To visualize it, just use plt.matshow(A_corr) .

If N is so large that the figure could not provide a clear insight, we might alternatively use histograms like this:

def corr_matrix_to_array(corr_mat):
N = corr_mat.shape[0]
return np.array([corr_mat[i][j] for i in range(1, N) for j in range(i + 1, N)])

plt.hist(corr_matrix_to_array(A_corr), bins=np.linspace(-1, 1, N_bins))

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