def confRegions2PPlanes(majorAxis, minorAxis, theta, want2plot=True,
    confLvl=0.95):
    """Determines the :math:`\\mathbb{R}^2` coordinates of each confidence
    ellipse in the local Cartesyan System of the :math:`\\mathscr{P}-` planes
    that contain them. It is donde from their geometric parameters obtained
    from the ``eigVectsRegions`` function. If it is wanted,
    plots them too.

    Parameters:
        majorAxis (`numpy.ndarray`): Array with the three lengths of the
            ellipses' major axis that define the confidence region. The order
            is acording to the principal values returned from the
            ``getEigSorted`` function.
        minorAxis (`list`): list with the three couples of
            :math:`\\boldsymbol{\\mathrm{W}_i}`'s eigenvalues obtained with
            the ``getEigSorted`` function. The order is acording to the
            principal values returned from the ``getEigSorted`` function.
        theta (`list`): list with the three ellipse inclinations in radians
            measured from the horizontal axis of the local Cartesian System of
            each ellipse to the respective major axis counter clockwise.
        want2plot (`bool`): Logical variable to indicate if is wanted to plot
            the ellipes. ``True`` is the default value.
        confLvl (`float`): Confidence level of the limits of the
            variabilities of :math:`\\boldsymbol{k}`'s principal vectors and
            values. ``0.95`` is the default value.

    Returns:
        Three elements are returned; they are described below.

            - **x** (`list`): List of three arrays that contain the abscises                of the each ellipse.
            - **y** (`list`): List of three arrays that contain the ordinates                of the each ellipse.
            - **fig** (`list`): ``matplotlib`` object. use ``fig.show()`` for                displaying the plot

    Examples:
        >>> from numpy import array
        >>> from jelinekstat.tools import confRegions2PPlanes
        >>> majorAxis = array([ 0.66888885,  0.66949335,  0.13745895])
        >>> minorAxis = array([ 0.09950548,  0.09615434,  0.04640122])
        >>> theta = array([-0.01949436, -1.51693959, -0.81162812])
        >>> x, y, fig = confRegions2PPlanes(majorAxis, minorAxis, theta,
        >>>                                 want2plot=True, confLvl=0.95)
        >>> fig.show()

    .. figure:: https://rawgit.com/eamontoyaa/jelinekstat/master/examples/figures/tools_confRegions2PPlanes_example.svg
        :alt: tools_confRegions2PPlanes_example

    .. only:: html

       :download:`example script<../examples/figuresScripts/tools_confRegions2PPlanes_example.py>`.

    """
    import numpy as np
    import matplotlib.pyplot as plt
    numPoints = 500
    confLvl = round(confLvl * 100, 1)
    phi = np.linspace(0, 2 * np.pi, numPoints)
    x, y = list(), list()
    for i in range(3):
        rotMatrix = np.array([[np.cos(theta[i]), -np.sin(theta[i])], [np.
            sin(theta[i]), np.cos(theta[i])]])
        rotMatrix = [rotMatrix] * numPoints
        xyNoRot = np.array([np.cos(phi) * majorAxis[i], np.sin(phi) *
            minorAxis[i]]).T
        xyRot = np.array(list(map(np.dot, rotMatrix, xyNoRot)))
        x.append(xyRot[:, (0)])
        y.append(xyRot[:, (1)])
        plt.ioff()
        fig = plt.figure(num='Confidence regions')
        eigenVectName = ['major', 'intermediate', 'minor']
        xLabel = ['$p_2$', '$p_3$', '$p_1$']
        yLabel = ['$p_3$', '$p_1$', '$p_2$']
        if want2plot:
            ax = fig.add_subplot(1, 3, i + 1)
            ax.plot(x[i], y[i], '-k')
            ax.axis('equal')
            ax.grid(True, ls='--', lw=0.5)
            ax.set_xlabel(xLabel[i])
            ax.set_ylabel(yLabel[i])
            ax.set_title(str(confLvl) + '% confidence ellipse \nof ' +
                eigenVectName[i] + ' eigenvector', fontweight='bold',
                fontsize=9)
            ax.tick_params(labelsize=7)
            fig.subplots_adjust(wspace=0.7)
    return x, y, fig
