9f7e1e041a63140ddda434307cfc2d951bea4c83,neurodsp/sim/aperiodic.py,,sim_powerlaw,#Any#Any#Any#Any#,247

Before Change

        n_samples = int(n_seconds * fs) + filt_len + 1

    else:
        n_samples = int(n_seconds * fs)

    sig = _create_powerlaw(n_samples, fs, exponent)

    if f_range is not None:

After Change

    

    // Compute the number of samples for the simulated time series
    n_samples = compute_nsamples(n_seconds, fs)

    // Get the number of samples to simulate for the signal
    //   If signal is to be filtered, with FIR, add extra to compensate for edges
    if f_range and filter_kwargs.get("filter_type", None) != "iir":

Instances