def compute(self, inputs):
self.make_storage_data_input_vars(inputs)
inputs["jm"] = 1
for name, value in tuple(inputs.items()):
if hasattr(
value,
"shape") and len(value.shape) > 1 and value.shape[1] == 1:
inputs[name] = self.make_storage_data(
pad_field_in_j(value, self.grid.njd))
for name, value in tuple(inputs["tracers"].items()):
if hasattr(
value,
"shape") and len(value.shape) > 1 and value.shape[1] == 1:
inputs["tracers"][name] = self.make_storage_data(
pad_field_in_j(value, self.grid.njd))
run_fillz = fillz.FillNegativeTracerValues(
self.grid.stencil_factory,
inputs.pop("im"),
inputs.pop("jm"),
inputs.pop("km"),
inputs.pop("nq"),
)
run_fillz(**inputs)
ds = self.grid.default_domain_dict()
ds.update(self.out_vars["q2tracers"])
tracers = np.zeros(
(self.grid.nic, self.grid.npz, len(inputs["tracers"])))
for varname, data in inputs["tracers"].items():
index = utils.tracer_variables.index(varname)
tracers[:, :, index] = np.squeeze(data[self.grid.slice_dict(ds)])
out = {"q2tracers": tracers}
return out
def compute(self, inputs):
self.setup(inputs)
inputs["j_2d"] = self.grid.global_to_local_y(
inputs["j_2d"] + TranslateGrid.fpy_model_index_offset)
inputs["i1"] = self.is_
inputs["i2"] = self.ie
inputs["j1"] = inputs["j_2d"]
inputs["j2"] = inputs["j_2d"]
del inputs["j_2d"]
inputs["kord"] = abs(spec.namelist.kord_tm)
inputs["qmin"] = 184.0
# these are sometimes 3D and sometimes singleton in J
if inputs["pe1"].shape[1] == 1:
inputs["pe1"] = self.make_storage_data(
pad_field_in_j(inputs["pe1"], self.nj))
if inputs["pe2"].shape[1] == 1:
inputs["pe2"] = self.make_storage_data(
pad_field_in_j(inputs["pe2"], self.nj))
qs_field = utils.make_storage_from_shape(self.maxshape[0:2],
origin=(0, 0))
qs_field[:, :] = inputs["qs"][:, :, 0]
inputs["qs"] = qs_field
if inputs["qs"].shape[1] == 1:
inputs["qs"] = utils.tile(inputs["qs"][:, 0],
[self.nj, 1]).transpose(1, 0)
var_inout = self.compute_func(**inputs)
return self.slice_output(inputs, {"pt": var_inout})
def compute(self, inputs):
self.setup(inputs)
inputs["j_2d"] = self.grid.global_to_local_y(
inputs["j_2d"] + TranslateGrid.fpy_model_index_offset)
inputs["i1"] = self.is_
inputs["i2"] = self.ie
inputs["j1"] = inputs["j_2d"]
inputs["j2"] = inputs["j_2d"]
del inputs["j_2d"]
inputs["pe1"] = self.make_storage_data(
pad_field_in_j(inputs["pe1"], self.grid.njd))
inputs["pe2"] = self.make_storage_data(
pad_field_in_j(inputs["pe2"], self.grid.njd))
inputs["dp2"] = self.make_storage_data(
pad_field_in_j(inputs["dp2"], self.grid.njd))
inputs["kord"] = abs(spec.namelist.kord_tr)
self.compute_func = MapN_Tracer.MapNTracer(
self.grid.stencil_factory,
inputs.pop("kord"),
inputs.pop("nq"),
inputs.pop("i1"),
inputs.pop("i2"),
inputs.pop("j1"),
inputs.pop("j2"),
fill=spec.namelist.fill,
)
self.compute_func(**inputs)
return self.slice_output(inputs)
def compute_from_storage(self, inputs):
for name, value in inputs.items():
if hasattr(
value,
"shape") and len(value.shape) > 1 and value.shape[1] == 1:
inputs[name] = self.make_storage_data(
pad_field_in_j(value, self.grid.njd))
self.compute_func(**inputs)
return inputs
def compute(self, inputs):
self.make_storage_data_input_vars(inputs)
if "qs" in inputs:
qs_field = utils.make_storage_from_shape(self.maxshape[0:2], origin=(0, 0))
qs_field[:, :] = inputs["qs"][:, :, 0]
inputs["qs"] = qs_field
if inputs["qs"].shape[1] == 1:
inputs["qs"] = utils.tile(inputs["qs"][:, 0], [self.nj, 1]).transpose(
1, 0
)
inputs["i1"] = self.grid.global_to_local_x(
inputs["i1"] + TranslateGrid.fpy_model_index_offset
)
inputs["i2"] = self.grid.global_to_local_x(
inputs["i2"] + TranslateGrid.fpy_model_index_offset
)
inputs["qmin"] = 0.0
inputs["j_2d"] = self.grid.global_to_local_y(
inputs["j_2d"] + TranslateGrid.fpy_model_index_offset
)
if inputs["q1"].shape[1] == 1:
# some test cases are on singleton j-slices,
# so for those calls these are zero and not n_halo
inputs["j1"] = 0
inputs["j2"] = 0
else:
inputs["j1"] = inputs["j_2d"]
inputs["j2"] = inputs["j_2d"]
if inputs["pe1"].shape[1] == 1:
inputs["pe1"] = self.make_storage_data(
pad_field_in_j(inputs["pe1"], self.nj)
)
if inputs["pe2"].shape[1] == 1:
inputs["pe2"] = self.make_storage_data(
pad_field_in_j(inputs["pe2"], self.nj)
)
del inputs["j_2d"]
var_inout = self.compute_func(**inputs)
return self.slice_output(inputs, {"var_inout": var_inout})