def fit_params_to_1d_data(logX):
    """
    Fit skewed normal distributions to 1-D capactity data, 
    and return the distribution parameters.

    Args
    ----
    logX:
        Logarithm of one-dimensional capacity data, 
        indexed by module and phase resolution index

    """
    m_max = logX.shape[0]
    p_max = logX.shape[1]
    params = np.zeros((m_max, p_max, 3)) 
    for m_ in range(m_max):
        for p_ in range(p_max):
            params[m_,p_] = skewnorm.fit(logX[m_,p_])
    
    return params
def fit_params_to_1d_data ( logX ) : m_max = logX . shape [ 0 ] p_max = logX . shape [ 1 ] params = np . zeros ( ( m_max , p_max , 3 ) ) for m_ in range ( m_max ) : for p_ in range ( p_max ) : params [ m_ , p_ ] = skewnorm . fit ( logX [ m_ , p_ ] ) return params
Fit skewed normal distributions to 1-D capactity data, 
    and return the distribution parameters.

    Args
    ----
    logX:
        Logarithm of one-dimensional capacity data, 
        indexed by module and phase resolution index