def func_pwc_mr_fd(ds_single):
# print(ds_single)
ds_res = CARDAMOMlib.compute_ds_pwc_mr_fd_greg(ds_single, comp_dict)
write_to_logfile("finished single,", "lat:", ds_single.lat.data, "lon:",
ds_single.lon.data, "prob:", ds_single.prob.data)
return ds_res
def func_pwc_mr_fd(ds_single):
# print(ds_single)
ds_res = CARDAMOMlib.compute_ds_pwc_mr_fd_greg(
ds_single,
# integration_method='solve_ivp',
integration_method='trapezoidal',
nr_nodes=51)
write_to_logfile("finished single,", "lat:", ds_single.lat.data, "lon:",
ds_single.lon.data, "prob:", ds_single.prob.data)
return ds_res
def func_start_values(*args):
v_names = args[-1]
d = {v_names[i]: args[i].reshape((-1, )) for i in range(len(args[:-1]))}
# print([v.shape for v in d.values()])
print('lat:', d['lat'], 'lon:', d['lon'], 'prob:', d['prob'], flush=True)
# print('time:', d['time'], flush=True)
# print([v.shape for v in d.values()], flush=True)
start_values = CARDAMOMlib.load_start_values_greg_dict(d)
ds_res = CARDAMOMlib.compute_ds_pwc_mr_fd_greg(
ds_single, integration_method='trapezoidal', nr_nodes=51)
# print(start_values, flush=True)
# start_values = da.from_array(1.1 * np.ones((1, 1, 1, 6), dtype=np.float64, chunks=(1,1,6))
# start_values.to_dask()
return start_values.reshape(1, 1, 1, 6)
def func_pwc_mr_fd(ds_single):
# print(ds_single)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
ds_res = CARDAMOMlib.compute_ds_pwc_mr_fd_greg(
ds_single,
# integration_method='solve_ivp',
integration_method='trapezoidal',
nr_nodes=151,
errors=errors)
write_to_logfile("finished single,", "lat:", ds_single.lat.data, "lon:",
ds_single.lon.data, "prob:", ds_single.prob.data)
return ds_res