range(0, window):
        idx_range = np.minimum(n_times - 1,
                               np.arange(k, n_times + k - 2, window))
        U = U + np.reshape(data[idx_range].reshape([-1, 1, n_ch]) *
                           data[idx_range].reshape(-1, n_ch, 1), U.shape)

    return np.array(U)</code></pre>
</details>
</section>
<section>
</section>
<section>
</section>
<section>
<h2 class="section-title" id="header-functions">Functions</h2>
<dl>
<dt id="asrpy.asr_utils.fit_eeg_distribution"><code class="