class ThreeComponentNoIrf:
model = load_model(MODEL_3C_NO_IRF, format_name="yml_str")
initial_parameters = load_parameters(PARAMETERS_3C_NO_IRF_INITIAL,
format_name="yml_str")
wanted_parameters = load_parameters(PARAMETERS_3C_NO_IRF_WANTED,
format_name="yml_str")
time = np.arange(0, 100, 1.5)
spectral = np.arange(600, 750, 10)
axis = {"time": time, "spectral": spectral}
def test_save_model(
tmp_path: Path,
):
"""Check all files exist."""
model_path = tmp_path / "testmodel.yml"
save_model(file_name=model_path, format_name="yml", model=MODEL)
assert model_path.is_file()
assert model_path.read_text() == want
assert load_model(model_path).valid()
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 read_model_from_yaml_file(model_file: str) -> Model:
"""Parse ``model.yaml`` file to :class:`Model`.
Warning
-------
Deprecated use ``glotaran.io.load_model(model_file)`` instead.
Parameters
----------
model_file : str
File with model spec description as yaml.
Returns
-------
Model
Model described in ``model_file``.
"""
return load_model(model_file)
def read_model_from_yaml(model_yml_str: str) -> Model:
"""Parse ``yaml`` string to :class:`Model`.
Warning
-------
Deprecated use ``glotaran.io.load_model(model_yml_str, format_name="yml_str")``
instead.
Parameters
----------
model_yml_str : str
Model spec description in yaml.
Returns
-------
Model
Model described in ``model_yml_str``.
"""
return load_model(model_yml_str, format_name="yml_str")
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
},
maximum_number_function_evaluations=11,
non_negative_least_squares=True,
def load_model_file(filename, verbose=False):
return _load_file(filename,
lambda file: load_model(file, format_name="yml"),
"model", verbose)
from glotaran.analysis.simulation import simulate
from glotaran.io import load_model
from glotaran.project import Scheme
from glotaran.project.generators import generate_model_yml
from glotaran.testing.simulated_data.shared_decay import PARAMETERS
from glotaran.testing.simulated_data.shared_decay import SIMULATION_COORDINATES
from glotaran.testing.simulated_data.shared_decay import SIMULATION_PARAMETERS
SIMULATION_MODEL_YML = generate_model_yml(
generator_name="spectral_decay_parallel",
generator_arguments={
"nr_compartments": 3,
"irf": True
},
)
SIMULATION_MODEL = load_model(SIMULATION_MODEL_YML, format_name="yml_str")
MODEL_YML = generate_model_yml(
generator_name="decay_parallel",
generator_arguments={
"nr_compartments": 3,
"irf": True
},
)
MODEL = load_model(MODEL_YML, format_name="yml_str")
DATASET = simulate(
SIMULATION_MODEL,
"dataset_1",
SIMULATION_PARAMETERS,
SIMULATION_COORDINATES,
class MultiCenterIrfDispersion:
model = load_model(MODEL_MULTIPULSE_IRF_DISPERSION, format_name="yml_str")
parameters = load_parameters(PARAMETERS_MULTIPULSE_IRF_DISPERSION,
format_name="yml_str")
axis = {"time": _time_axis(), "spectral": _spectral_axis()}
class SimpleIrfDispersion:
model = load_model(MODEL_SIMPLE_IRF_DISPERSION, format_name="yml_str")
parameters = load_parameters(PARAMETERS_SIMPLE_IRF_DISPERSION,
format_name="yml_str")
axis = {"time": _time_axis(), "spectral": _spectral_axis()}
class MultiIrfDispersion:
model = load_model(MODEL_MULTI_IRF_DISPERSION, format_name="yml_str")
parameters = load_parameters(PARAMETERS_MULTI_IRF_DISPERSION, format_name="yml_str")
time = np.arange(-1, 5, 0.2)
spectral = np.arange(300, 500, 100)
axis = {"time": time, "spectral": spectral}
def model():
spec_path = join(THIS_DIR, "test_model_spec.yml")
m = load_model(spec_path)
print(m.markdown())
return m