simpeg/SimPEG/Model.py

from SimPEG import Utils, np, sp


class BaseModel(object):
    """SimPEG Model"""

    __metaclass__ = Utils.Save.Savable

    counter = None   #: A SimPEG.Utils.Counter object

    def __init__(self):
        pass

    def transform(self, m):
        """
            :param numpy.array m: model
            :rtype: numpy.array
            :return: transformed model

            The *transform* changes the model into the physical property.

            A common example of this is to invert for electrical conductivity
            in log space. In this case, your model will be log(sigma) and to
            get back to sigma, you can take the exponential:

        """
        return m

    def transformDeriv(self, m):
        """
            :param numpy.array m: model
            :rtype: scipy.csr_matrix
            :return: derivative of transformed model

            The *transform* changes the model into the physical property.
            The *transformDeriv* provides the derivative of the *transform*.
        """
        return sp.identity(m.size)

    def example(self, mesh, type=None):
        return np.random.rand(mesh.nC)



class LogModel(BaseModel):
    """SimPEG LogModel"""

    def __init__(self, **kwargs):
        BaseModel.__init__(self, **kwargs)

    def transform(self, m):
        """
            :param numpy.array m: model
            :rtype: numpy.array
            :return: transformed model

            The *transform* changes the model into the physical property.

            A common example of this is to invert for electrical conductivity
            in log space. In this case, your model will be log(sigma) and to
            get back to sigma, you can take the exponential:

            .. math::

                m = \log{\sigma}

                \exp{m} = \exp{\log{\sigma}} = \sigma
        """
        return np.exp(Utils.mkvc(m))

    def transformDeriv(self, m):
        """
            :param numpy.array m: model
            :rtype: scipy.csr_matrix
            :return: derivative of transformed model

            The *transform* changes the model into the physical property.
            The *transformDeriv* provides the derivative of the *transform*.

            If the model *transform* is:

            .. math::

                m = \log{\sigma}

                \exp{m} = \exp{\log{\sigma}} = \sigma

            Then the derivative is:

            .. math::

                \\frac{\partial \exp{m}}{\partial m} = \\text{sdiag}(\exp{m})
        """
        return Utils.sdiag(np.exp(Utils.mkvc(m)))