def print_pole_mean(mean_dictionary):
    """
    Does a pretty job printing a Fisher mean and associated statistics for
    mean paleomagnetic poles.

    Parameters
    ----------
    mean_dictionary: output dictionary of pmag.fisher_mean

    Examples
    --------
    Generate a Fisher mean using ``ipmag.fisher_mean`` and then print it nicely
    using ``ipmag.print_pole_mean``

    >>> my_mean = ipmag.fisher_mean(di_block=[[140,21],[127,23],[142,19],[136,22]])
    >>> ipmag.print_pole_mean(my_mean)
    Plon: 136.3  Plat: 21.3
    Number of directions in mean (n): 4
    Angular radius of 95% confidence (A_95): 7.3
    Precision parameter (k) estimate: 159.7
    """
    print('Plon: ' + str(round(mean_dictionary['dec'], 1)) +
          '  Plat: ' + str(round(mean_dictionary['inc'], 1)))
    print('Number of directions in mean (n): ' + str(mean_dictionary['n']))
    print('Angular radius of 95% confidence (A_95): ' +
          str(round(mean_dictionary['alpha95'], 1)))
    print('Precision parameter (k) estimate: ' +
          str(round(mean_dictionary['k'], 1)))
def print_pole_mean ( mean_dictionary ) : print ( 'Plon: ' + str ( round ( mean_dictionary [ 'dec' ] , 1 ) ) + '  Plat: ' + str ( round ( mean_dictionary [ 'inc' ] , 1 ) ) ) print ( 'Number of directions in mean (n): ' + str ( mean_dictionary [ 'n' ] ) ) print ( 'Angular radius of 95% confidence (A_95): ' + str ( round ( mean_dictionary [ 'alpha95' ] , 1 ) ) ) print ( 'Precision parameter (k) estimate: ' + str ( round ( mean_dictionary [ 'k' ] , 1 ) ) )
Does a pretty job printing a Fisher mean and associated statistics for
    mean paleomagnetic poles.

    Parameters
    ----------
    mean_dictionary: output dictionary of pmag.fisher_mean

    Examples
    --------
    Generate a Fisher mean using ``ipmag.fisher_mean`` and then print it nicely
    using ``ipmag.print_pole_mean``

    >>> my_mean = ipmag.fisher_mean(di_block=[[140,21],[127,23],[142,19],[136,22]])
    >>> ipmag.print_pole_mean(my_mean)
    Plon: 136.3  Plat: 21.3
    Number of directions in mean (n): 4
    Angular radius of 95% confidence (A_95): 7.3
    Precision parameter (k) estimate: 159.7