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