def setup():
# %% Load in data, model and parameters
dataset1 = load_dataset(script_folder.joinpath(DATA_PATH1))
dataset2 = load_dataset(script_folder.joinpath(DATA_PATH2))
model = load_model(script_folder.joinpath(MODEL_PATH))
parameters = load_parameters(script_folder.joinpath(PARAMETERS_FILE_PATH))
return model, parameters, dataset1, dataset2
def setup(self):
dataset1 = load_dataset(SCRIPT_DIR / "data/data1.ascii")
dataset2 = load_dataset(SCRIPT_DIR / "data/data2.ascii")
model = load_model(str(SCRIPT_DIR / "models/model.yml"))
parameters = load_parameters(str(SCRIPT_DIR / "models/parameters.yml"))
self.scheme = Scheme(
model,
parameters,
{
"dataset1": dataset1,
"dataset2": dataset2
},
maximum_number_function_evaluations=11,
non_negative_least_squares=True,
optimization_method="TrustRegionReflection",
)
def load_data(result: DatasetConvertible,
dataset_name: str | None = None) -> xr.Dataset:
"""Extract a single dataset from a :class:`DatasetConvertible` object.
Parameters
----------
result : DatasetConvertible
Result class instance, xarray Dataset or path to a dataset file.
dataset_name : str, optional
Name of a specific dataset contained in ``result``, if not provided
the first dataset will be extracted. Defaults to None.
Returns
-------
xr.Dataset
Extracted dataset.
Raises
------
TypeError
If ``result`` isn't a :class:`DatasetConvertible` object.
"""
if isinstance(result, xr.Dataset):
return result
if isinstance(result, xr.DataArray):
return result.to_dataset(name="data")
if isinstance(result, Result):
if dataset_name is not None:
return result.data[dataset_name]
keys = list(result.data)
return result.data[keys[0]]
if isinstance(result, (str, Path)):
return load_data(load_dataset(result))
raise TypeError(
f"Result needs to be of type {DatasetConvertible!r}, but was {result!r}."
)
from glotaran.project.scheme import Scheme
DATA_PATH1 = "data/data1.ascii"
DATA_PATH2 = "data/data2.ascii"
MODEL_PATH = "models/model.yml"
PARAMETERS_FILE_PATH = "models/parameters.yml"
# %% Setup necessary (output) paths
results_folder, script_folder = setup_case_study(Path(__file__))
output_folder = results_folder.joinpath("target_analysis")
print(f"- Using folder {output_folder.name} to read/write files for this run")
# %% Load in data, model and parameters
# dataset1 = ExplicitFile(script_folder.joinpath(DATA_PATH1)).read()
# dataset2 = ExplicitFile(script_folder.joinpath(DATA_PATH2)).read()
dataset1 = load_dataset(script_folder.joinpath(DATA_PATH1))
dataset2 = load_dataset(script_folder.joinpath(DATA_PATH2))
model = load_model(script_folder.joinpath(MODEL_PATH))
parameters = load_parameters(script_folder.joinpath(PARAMETERS_FILE_PATH))
# %% Validate model and parameters
print(model.validate(parameters=parameters))
# %% Construct the analysis scheme
scheme = Scheme(
model,
parameters,
{
"dataset1": dataset1,
"dataset2": dataset2
},
def loader(filename):
return load_dataset(filename, format_name=fmt)