Duda con kwargs.pop()

[Bael_Balzac]

En la línea 15 quiero que los limites sean 0 < umbral < 1, como se usa kwargs.pop(), para evitar ValueError: cannot convert float NaN to integer debido a log(0.0). log(-0.1), ..., log(-0.9999), el intervalo actual seria -0.9999 < umbral < 0.9999.

Código:

from __future__ import unicode_literals

import numpy as np
from numpy import ma
from matplotlib import scale as mscale
from matplotlib import transforms as mtransforms
from matplotlib.ticker import Formatter, FixedLocator

class EscalaAcumuladaGumbel(mscale.ScaleBase):

    name = 'gumbel'

    def __init__(self, axis, **kwargs):
        mscale.ScaleBase.__init__(self)
        umbral = kwargs.pop("umbral", 0.9999)
        if umbral >= 1.0:
            raise ValueError("umbral debe ser mayor que 0.0 o menor que 1.0")
        self.umbral = umbral

    def get_transform(self):
        return self.TransformacionAcumuladaGumbel(self.umbral)

    def set_default_locators_and_formatters(self, axis):
        class TresDecimales(Formatter):
            def __call__(self, x, pos=None):
                return '%.3f' % x
        axis.set_major_locator(FixedLocator(np.arange(0.0, 1.0, 0.05)))
        axis.set_major_formatter(TresDecimales())
        axis.set_minor_formatter(TresDecimales())

    def limit_range_for_scale(self, vmin, vmax, minpos):
        return max(vmin, -self.umbral), min(vmax, self.umbral)

    class TransformacionAcumuladaGumbel(mtransforms.Transform):
        input_dims = 1
        output_dims = 1
        is_separable = True

        def __init__(self, umbral):
            mtransforms.Transform.__init__(self)
            self.umbral = umbral

        def transform(self, a):
            masked = ma.masked_where((a < -self.umbral) | (a > self.umbral), a)
            if masked.mask.any():
                return 0.156516164484 + (0.0915834783405*(-ma.log(-ma.log(a))))
            else:
                return 0.156516164484 + (0.0915834783405*(-np.log(-np.log(a))))

        def inverted(self):
            return EscalaAcumuladaGumbel.TransformacionInversaAcumuladaGumbel(self.umbral)

    class TransformacionInversaAcumuladaGumbel(mtransforms.Transform):
        input_dims = 1
        output_dims = 1
        is_separable = True

        def __init__(self, umbral):
            mtransforms.Transform.__init__(self)
            self.umbral = umbral

        def transform(self, a):
            return np.exp(-np.exp(-a))

        def inverted(self):
            return EscalaAcumuladaGumbel.TransformacionAcumuladaGumbel(self.umbral)

mscale.register_scale(EscalaAcumuladaGumbel)


if __name__ == '__main__':
    import matplotlib.pyplot as plt

    Datos = np.array([ 2690.0, 2700.0, 2700.667, 2701.333, 2702.0, 3196.0, 2372.0, 2395.0, 2128.0, 2727.0, 2431.0, 2850.0, 2216.0, 2057.0, 2269.0, 2208.0, 2628.0, 2729.0, 2588.0, 3448.0, 2508.0, 3081.0, 2417.0, 2770.0, 2283.0, 2455.0, 1963.0, 2786.0, 2885.0, 2357.0, 3422.0, 2423.0, 2148.0, 1305.0, 2472.0, 2186.0, 2720.0, 2430.0, 2304.0, 2556.0, 2625.0, 2164.0, 2585.0, ])
    DatosOrdenados = np.sort(Datos)
    mu = 2353.157
    sigma = 297.961

    y1 = ( DatosOrdenados - mu) / sigma
    x1 = np.exp(-np.exp(-y1))

    plt.plot(x1, y1, 'ro', lw=2)
    plt.gca().set_xscale('gumbel')

    plt.xlabel('F(z)')
    plt.ylabel('z')
    plt.title('Papel de probabilidad de Gumbel')
    plt.xticks(rotation='vertical', fontsize=7)
    plt.grid(True)

    plt.show()