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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def all_features():
    ''' Returns dictionary of all features in the module

    .. note:: Some of the features (hist4, corr) are relatively expensive to compute
    '''
    features = {'mean': mean,
                'median': median,
                'gmean': gmean,
                'hmean': hmean,
                'vec_sum': vec_sum,
                'abs_sum': abs_sum,
                'abs_energy': abs_energy,
                'std': std,
                'var': var,
                'variation': variation,
                'min': minimum,
                'max': maximum,
                'skew': skew,
                'kurt': kurt,
                'mean_diff': mean_diff,
                'mean_abs_diff': means_abs_diff,
                'mse': mse,
                'mnx': mean_crossings,
                'hist4': hist(),
                'corr': corr2,
                'mean_abs_value': mean_abs,
                'zero_crossings': zero_crossing(),
                'slope_sign_changes': slope_sign_changes(),
                'waveform_length': waveform_length,
                'emg_var': emg_var,
                'root_mean_square': root_mean_square,
                'willison_amplitude': willison_amplitude()}
    return features