def main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/case106/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
exp_datasets = deangelis_recipe.f2ext.exp_datasets
variables = deangelis_recipe.f2ext.variables
# get all datasets
datasets = get_datasets(
datasets=exp_datasets,
variables=variables,
)
processor_tasks = []
for variable in variables:
processor_tasks.extend(
get_processor_tasks_for_variable(
variable=variable,
datasets=datasets[variable["variable_group"]],
settings=deangelis_recipe.processor_settings[
variable["preprocessor"]],
diagnostic={"diagnostic": diagnostic_name},
config={"data_path": deangelis_config.data_path},
work_dir=work_dir,
))
for index, task in enumerate(processor_tasks):
logger.info(index)
run_processor(task, config={}, work_dir=work_dir)
def main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/case108/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
# recipe
variables = bock20_recipe.fig3.variables
variable_additional_datasets = bock20_recipe.fig3.variable_additional_datasets
additional_datasets = bock20_recipe.fig3.additional_datasets
# get all datasets
datasets = get_datasets(
variables=variables,
variable_additional_datasets=variable_additional_datasets,
additional_datasets=additional_datasets)
processor_tasks = []
for variable in variables:
preprocessor = variable.get("preprocessor", "default")
settings = bock20_recipe.processor_settings.get(preprocessor, {})
processor_tasks.extend(
get_processor_tasks_for_variable(
variable=variable,
datasets=datasets[variable["variable_group"]],
settings=settings,
diagnostic={"diagnostic": diagnostic_name},
config={"data_path": bock20_config.data_path},
work_dir=work_dir))
for task in processor_tasks:
run_processor(task, config={}, work_dir=work_dir)
def main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/land/case401/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
# recipe
variable_additional_datasets = landcover_recipe.cmip6.variable_additional_datasets
variables = landcover_recipe.cmip6.variables
# get all datasets
datasets = get_datasets(
variables=variables,
variable_additional_datasets=variable_additional_datasets)
processor_tasks = []
for variable in variables:
processor_tasks.extend(
get_processor_tasks_for_variable(
variable=variable,
datasets=datasets[variable["variable_group"]],
settings=landcover_recipe.processor_settings[
variable["preprocessor"]],
diagnostic={"diagnostic": diagnostic_name},
config={"data_path": landcover_config.data_path},
work_dir=work_dir))
for task in processor_tasks:
run_processor(task, config={}, work_dir=work_dir)
def run(
exp_dataset,
variable,
diagnostic_name
):
work_dir = "/home/hujk/ploto/esmvaltool/cases/case103/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
operations = generate_default_operations()
combined_dataset = combine_variable(
dataset=exp_dataset,
variable=variable,
)
add_variable_info(combined_dataset)
diagnostic = {
"diagnostic": "diurnal_temperature_indicator",
}
settings = miles_recipe.processor_settings[combined_dataset["preprocessor"]]
task = {
"products": [
{
"variable": combined_dataset,
"input": {
"input_data_source_file": (
"{work_dir}"
f"/{diagnostic_name}/fetcher/preproc"
"/{dataset}/{variable_group}/data_source.yml"
),
},
"output": {
"output_directory": "{dataset}/{variable_group}"
},
"settings": settings
}
],
# operations
"operations": operations,
"diagnostic": diagnostic,
"output": {
"output_directory": "{work_dir}" + f"/{diagnostic_name}/processor/preproc",
},
}
run_processor(
task=task,
work_dir=work_dir,
config={},
)
def run(
exp_dataset,
variable,
):
work_dir = "/home/hujk/ploto/esmvaltool/cases/case105/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
operations = generate_default_operations("climatological_mean")
combined_dataset = combine_variable(
dataset=exp_dataset,
variable=variable
)
add_variable_info(combined_dataset)
diagnostic = {
"diagnostic": "calculate_weights_climwip",
}
settings = climwip_recipe.processor_settings[combined_dataset["preprocessor"]]
task = {
"products": [
{
"variable": combined_dataset,
"input": {
"input_data_source_file": (
"{work_dir}" + f"/{diagnostic_name}/fetcher/preproc" + "/{dataset}/{variable_group}/data_source.yml"
),
},
"output": {
"output_directory": "{alias}/{variable_group}"
},
"settings": settings
}
],
# operations
"operations": operations,
"diagnostic": diagnostic,
"output": {
"output_directory": "{work_dir}" + f"/{diagnostic_name}/processor/preproc",
},
"step_type": "processor",
"type": "ploto_esmvaltool.processor.esmvalcore_pre_processor",
}
run_processor(
task=task,
work_dir=work_dir,
config={},
)
def main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/case1/ploto/c1"
operations = generate_default_operations()
dataset = {
"dataset": "FGOALS-g3",
"project": "CMIP6",
"mip": "day",
"exp": "1pctCO2",
"ensemble": "r1i1p1f1",
"grid": "gn",
"frequency": "day",
"start_year": 370,
"end_year": 371,
}
diag_dataset = {
"recipe_dataset_index": 0,
"alias": "FGOALS-g3",
"modeling_realm": ["atmos"],
}
variable = {
"short_name": "pr",
"variable_group": "pr",
"preprocessor": "default",
}
diag = {
"diagnostic": "dry_days",
}
task = {
# input files
"input_data_source_file":
pathlib.Path(pathlib.Path(__file__).parent, "input_meta_file.yml"),
# output
"output_directory":
"{work_dir}/preproc/pr",
# operations
"operations":
operations,
**dataset,
**diag_dataset,
**variable,
**diag,
}
run_processor(
task=task,
work_dir=work_dir,
config={},
)
def run(
exp_dataset,
variable
):
work_dir = "/home/hujk/ploto/esmvaltool/cases/case102/ploto"
operations = generate_default_preprocessor_operations()
combined_dataset = {
**exp_dataset,
**variable
}
diagnostic = {
"diagnostic": "diurnal_temperature_indicator",
}
settings = diurnal_recipe.processor_settings[variable["preprocessor"]]
task = {
"products": [
{
"variable": combined_dataset,
"input": {
"input_data_source_file": "{work_dir}/fetcher/preproc/{alias}/{variable_group}/data_source.yml",
},
"output": {
"output_directory": "{alias}/{variable_group}"
},
"settings": settings
}
],
# operations
"operations": operations,
"diagnostic": diagnostic,
"output": {
"output_directory": "{work_dir}/processor/preproc",
},
}
run_processor(
task=task,
work_dir=work_dir,
config={},
)
def get_processor(exp_dataset, variable):
work_dir = "/home/hujk/ploto/esmvaltool/cases/case101/ploto"
operations = generate_default_operations()
combined_dataset = combine_variable(
dataset=exp_dataset,
variable=variable,
)
add_variable_info(combined_dataset)
diagnostic = {
"diagnostic": "dry_days",
}
task = {
"products": [{
"variable": combined_dataset,
"input": {
"input_data_source_file":
"{work_dir}/fetcher/preproc/{dataset}/{variable_group}/data_source.yml",
},
"output": {
"output_directory": "{dataset}/{variable_group}"
}
}],
# operations
"operations":
operations,
"diagnostic":
diagnostic,
"output": {
"output_directory": "{work_dir}/processor/preproc",
},
}
run_processor(
task=task,
work_dir=work_dir,
config={},
)
def main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/case110/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
# recipe
exp_datasets = spei_recipe.exp_datasets
variables = spei_recipe.variables
# get all datasets
datasets = get_datasets(
datasets=exp_datasets,
variables=variables,
)
processor_tasks = []
for variable in variables:
processor_tasks.extend(
get_processor_tasks_for_variable(
variable=variable,
datasets=datasets[variable["variable_group"]],
settings=spei_recipe.processor_settings[variable["preprocessor"]],
diagnostic={
"diagnostic": diagnostic_name
},
config={
"data_path": spei_config.data_path
},
work_dir=work_dir
)
)
for task in processor_tasks:
run_processor(
task,
config={},
work_dir=work_dir
)
def run(
dataset,
exp,
variable,
recipe_dataset_index,
start_year,
end_year,
alias
):
work_dir = "/home/hujk/ploto/esmvaltool/cases/case105/ploto/map/processor"
Path(work_dir).mkdir(parents=True, exist_ok=True)
operations = generate_climatological_mean_operations()
dataset = {
"dataset": dataset,
"project": "CMIP6",
"mip": "Amon",
"exp": exp,
"ensemble": "r1i1p1f1",
"grid": "gn",
"frequency": "mon",
"type": "exp", #*******************
"start_year": start_year,
"end_year": end_year,
}
diag_dataset = {
"recipe_dataset_index": recipe_dataset_index,
"alias": alias,
"modeling_realm": [
"atmos"
]
}
variable = variable
diag = {
"diagnostic": "weighted_temperature_map",
}
settings = {
"mask_landsea": {
"mask_out": "sea",
},
"regrid": {
"target_grid": "2.5x2.5",
"scheme": "linear"
},
"climate_statistics": {
"operator": "mean"
}
}
task = {
"input_data_source_file": f"/home/hujk/ploto/esmvaltool/cases/case105/ploto/map/fetcher/preproc/"
f"{dataset['dataset']}/{variable['variable_group']}/data_source.yml",
# output
"output_directory": f"{work_dir}/preproc/{dataset['dataset']}/{variable['variable_group']}",
# operations
"operations": operations,
"dataset": dataset,
"diagnostic_dataset": diag_dataset,
"variable": variable,
"diagnostic": diag,
"settings": settings
}
run_processor(
task=task,
work_dir=work_dir,
config={},
)
