.. role:: red .. role:: blue .. role:: navy TransferFunction ================ :navy:`period` ~~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **period** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :red:`True` | periods for estimates | 0.01 0.1 1.0 | | | | | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.float64]] | None | | | | **Units**: second | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`z` ~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **z** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Estimates of the impedance tensor. | 1.0+0.0j | | | | 0.5+0.5j | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.complex128]] | | | | | **Units**: [mV/km]/[nT] | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`z_var` ~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **z_var** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Variance estimates for the impedance tensor. | 0.01 0.1 1.0 | | | | | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.float64]] | None | | | | **Units**: None | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`z_invsigcov` ~~~~~~~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **z_invsigcov** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Inverse of the covariance matrix for the | 1.0+0.0j | | | impedance tensor. | 0.5+0.5j | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.complex128]] | | | | | **Units**: None | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`z_residcov` ~~~~~~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **z_residcov** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Residual covariance matrix for the impedance | 1.0+0.0j | | | tensor. | 0.5+0.5j | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.complex128]] | | | | | **Units**: None | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`t` ~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **t** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Estimates of the tipper tensor. | 1.0+0.0j | | | | 0.5+0.5j | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.complex128]] | | | | | **Units**: [] | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`t_var` ~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **t_var** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Variance estimates for the tipper tensor. | 0.01 0.1 1.0 | | | | | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.float64]] | None | | | | **Units**: None | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`t_invsigcov` ~~~~~~~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **t_invsigcov** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Inverse of the covariance matrix for the | 1.0+0.0j | | | tipper tensor. | 0.5+0.5j | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.complex128]] | | | | | **Units**: None | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+ :navy:`t_residcov` ~~~~~~~~~~~~~~~~~~ .. container:: .. table:: :class: tight-table :widths: 45 45 15 +----------------------------------------------+-----------------------------------------------+----------------+ | **t_residcov** | **Description** | **Example** | +==============================================+===============================================+================+ | **Required**: :blue:`False` | Residual covariance matrix for the tipper | 1.0+0.0j | | | tensor. | 0.5+0.5j | | **Type**: numpy.ndarray[tuple[int, ...], | | | | numpy.dtype[numpy.complex128]] | | | | | **Units**: None | | | | | | | | | | | | | | | | | | | | | | | | | | | +----------------------------------------------+-----------------------------------------------+----------------+