pyPDAF.PDAF.omi_set_id_obs_p

pyPDAF.PDAF.omi_set_id_obs_p()

Setting the id_obs_p attribute of obs_f.

The function is typically used in user-supplied function py__init_dim_obs_pdaf.

Here, id_obs_p(nrows, dim_obs_p) is a 2D array of integers. The value of nrows depends on the observation operator used for an observation.

Examples:

• nrows=1: observations are located on model grid point. In this case, id_obs_p stores the index of the state vector (starting from 1) corresponds to the observations, e.g. id_obs_p[0, j] = i means that the location and variable of the i-th element of the state vector is the same as the j-th observation.

• nrows=4: each observation corresponds to 4 indices of elements in the state vector. In this case, the location of these elements is used to perform bi-linear interpolation from model grid to observation location. This information is used in the pyPDAF.PDAF.omi_obs_op_gridavg() and pyPDAF.PDAF.omi_obs_op_interp_lin() functions. When interpolation is needed, the weighting of the interpolation is done in the pyPDAF.PDAF.omi_get_interp_coeff_lin(), pyPDAF.PDAF.omi_get_interp_coeff_lin1D(), and pyPDAF.PDAF.omi_get_interp_coeff_tri() functions. The details of interpolation setup can be found at PDAF wiki page.

Parameters:

• i_obs (int) – index of observations

• id_obs_p (ndarray[tuple[nrows, dim_obs_p], np.intc]) –

  indice corresponds to observations in the state vector

  The1st-th dimension nrows is Number of values to be averaged or used for interpolation; the2nd-th dimension dim_obs_p is dimension of PE local obs.