def main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/case108/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
# recipe
variables = bock20_recipe.fig2.variables
variable_additional_datasets = bock20_recipe.fig2.variable_additional_datasets
additional_datasets = bock20_recipe.fig2.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:
processor_tasks.extend(
get_tasks_for_variable(
variable=variable,
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/case107/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
exp_datasets = eyring13_recipe.exp_datasets
variables = eyring13_recipe.variables
variable_additional_datasets = eyring13_recipe.variable_additional_datasets
# get all datasets
datasets = get_datasets(
datasets=exp_datasets,
variables=variables,
variable_additional_datasets=variable_additional_datasets)
processor_tasks = []
for variable in variables:
processor_tasks.extend(
get_tasks_for_variable(
variable=variable,
datasets=datasets[variable["variable_group"]],
diagnostic={"diagnostic": diagnostic_name},
config={"data_path": eyring13_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/case110/ploto"
Path(work_dir).mkdir(parents=True, exist_ok=True)
exp_datasets = spei_recipe.exp_datasets
variables = spei_recipe.variables
datasets = get_datasets(
datasets=exp_datasets,
variables=variables,
)
processor_tasks = []
for variable in variables:
v_datasets = datasets[variable["variable_group"]]
settings = spei_recipe.processor_settings[variable["preprocessor"]]
if "multi_model_statistics" in settings:
statistics = settings["multi_model_statistics"]["statistics"]
for op in statistics:
v_datasets.append({
"alias": f"multi-model-{op}",
"variable_group": variable["variable_group"],
})
processor_tasks.extend(
get_tasks_for_variable(
variable=variable,
datasets=v_datasets,
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 main():
work_dir = "/home/hujk/ploto/esmvaltool/cases/case102/ploto"
exp_datasets = diurnal_recipe.exp_datasets
exp_datasets = [
{
**d,
"alias": f"{d['dataset']}-{d['exp']}",
"recipe_dataset_index": index
}
for index, d in enumerate(exp_datasets)
]
variables = diurnal_recipe.variables
tasks = [
{
"util_type": "combine_metadata",
"metadata_files": [
"{work_dir}" + f"/processor/preproc/{d['alias']}/{v['variable_group']}/metadata.yml"
for d in exp_datasets
],
"output_directory": "{work_dir}" + f"/processor/preproc/{v['variable_group']}"
} for v in variables
]
for task in tasks:
run_processor(
task=task,
work_dir=work_dir,
config={}
)
def main():
work_dir = f"{base_dir}/graph/processor"
variables = climwip_recipe.graph_variables
tasks = [get_task(work_dir, v) for v in variables]
for task in tasks:
run_processor(task=task, work_dir=work_dir, config={})
def main():
work_dir = f"{base_dir}/map/processor"
tasks = [
get_task(work_dir, variable)
for variable in climwip_recipe.map_variables
]
for task in tasks:
run_processor(task=task, work_dir=work_dir, config={})
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:
v_datasets = datasets[variable["variable_group"]]
preprocessor = variable.get("preprocessor", "default")
settings = bock20_recipe.processor_settings.get(preprocessor, {})
if "multi_model_statistics" in settings:
statistics = settings["multi_model_statistics"]["statistics"]
for op in statistics:
v_datasets.append({
"alias": f"multi-model-{op}",
"variable_group": variable["variable_group"],
})
processor_tasks.extend(
get_tasks_for_variable(
variable=variable,
datasets=v_datasets,
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/case103/ploto"
diagnostic_name = "miles_block"
tasks = [{
"util_type":
"combine_metadata",
"metadata_files": [
f"{work_dir}/{diagnostic_name}/processor/preproc/{d['dataset']}/{v['variable_group']}/metadata.yml"
for d, v in itertools.product(miles_recipe.exp_datasets,
miles_recipe.variables)
],
"output_directory":
f"{work_dir}/{diagnostic_name}/processor/preproc/"
}]
for task in tasks:
run_processor(task=task, work_dir=work_dir, config={})
