simpeg.maps.Weighting.deriv#

Weighting.deriv(m, v=None)[source]#

Derivative of mapping with respect to the input parameters.

For a weighting mapping $\mathbf{u}(\mathbf{m})$ that scales the input parameters in the model $\mathbf{m}$ by their corresponding weights $\mathbf{w}$; i.e.:

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the derivative of the mapping with respect to the model is a diagonal matrix of the form:

$$\frac{\partial \mathbf{u}}{\partial \mathbf{m}}=diag(\mathbf{w})$$

Parameters:

m(nP) numpy.ndarray

A vector representing a set of model parameters

v(nP) numpy.ndarray

If not None, the method returns the derivative times the vector v

Returns:

scipy.sparse.csr_matrix

Derivative of the mapping with respect to the model parameters. If the input argument v is not None, the method returns the derivative times the vector v.