7cd15d13d91e2de78d53a5cdac661e63f64d59e8,prody/dynamics/adaptive.py,,calcStep,#Any#Any#Any#Any#Any#Any#Any#Any#,73

Before Change

        Fmin = Fmin_max

    overlaps = np.abs(np.dot(d, anm.getEigvecs())) 
    sorted_indices = overlaps.argsort()[::-1]
    overlaps = overlaps[sorted_indices]

    sorted_mode_indices = np.arange(anm.numModes())[sorted_indices]

    normalised_overlaps = overlaps / norm(d)
    c_sq = np.cumsum(np.power(normalised_overlaps, 2), axis=0)

    torf_Fmin = c_sq <= Fmin
    if not np.any(torf_Fmin):
        torf_Fmin[0] = True

    selected_mode_indices = sorted_mode_indices[torf_Fmin]

    n_sel_modes = len(selected_mode_indices)

    modes = ModeSet(anm, selected_mode_indices)

After Change

    if not np.any(torf_Fmin):
        torf_Fmin[0] = True
    
    if not np.all(torf_Fmin):
        i = np.where(torf_Fmin)[0].max()
        torf_Fmin[i+1] = True

    selected_mode_indices = np.arange(anm.numModes())[torf_Fmin]

    n_sel_modes = len(selected_mode_indices)

Instances