pyPDAF.PDAF.omi_prodRinvA_cb

pyPDAF.PDAF.omi_prodRinvA_cb()

This function is an internal PDAF-OMI function that is used as a call-back function to perform the matrix multiplication inverse of observation errro covariance and a matrix A. This could be used to modify the observation variance when OMI is used with pyPDAF.PDAF.assimilate_xxx instead of pyPDAF.PDAF.omi_assimilate_xxx.

Parameters:

• step (int) – Current time step

• dim_obs_p (int) – Dimension of PE-local observation vector

• ncol (int) – Number of columns in A_p and C_p

• obs_p (ndarray[tuple[dim_obs_p], np.float64]) –

  PE-local vector of observations

  The array dimension dim_obs_p is Dimension of PE-local observation vector.

• A_p (ndarray[tuple[dim_obs_p, ncol], np.float64]) –

  Input matrix

  The1st-th dimension dim_obs_p is Dimension of PE-local observation vector; the2nd-th dimension ncol is Number of columns in A_p and C_p.

• C_p (ndarray[tuple[dim_obs_p, ncol], np.float64]) –

  Output matrix

  The1st-th dimension dim_obs_p is Dimension of PE-local observation vector; the2nd-th dimension ncol is Number of columns in A_p and C_p.

Returns:

C_p – Output matrix

The 1st-th dimension dim_obs_p is Dimension of PE-local observation vector The 2nd-th dimension ncol is Number of columns in A_p and C_p

Return type:

ndarray[tuple[dim_obs_p, ncol], np.float64]