# 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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