aopp_deconv_tool.fit_psf_model

module documentation

Tool for fitting a PSF to a particular model

Function exec_with_args Undocumented
Function get_new_psf_model_dependency_injector Creates a new instance of the dependency injector based upon the module-wide dependency injector class. Copies the module-wide dependency injector parameters.
Function get_psf_model_dependency_injector Gets the dependecy injector instance
Function go Thin wrapper around run() to accept string inputs. As long as the names of the arguments to this function are the same as the names expected from the command line we can do this programatically
Function parse_args Undocumented
Function plot_result Plot the result of fitting a model to a PSF
Function run Undocumented
Function set_psf_model_dependency_injector Module-wide method. Sets the dependency injector class and initialises the dependency injector instance.
Function set_psf_model_dependency_injector_params Sets the parameters of the module-wide dependency injector
Constant FITTING_METHODS Undocumented
Constant PSF_MODEL_DI Undocumented
Constant PSF_MODEL_DI_CLASS Undocumented
Variable psf_models Undocumented
Variable _lgr Undocumented
def exec_with_args(argv):

Undocumented

def get_new_psf_model_dependency_injector(data):

Creates a new instance of the dependency injector based upon the module-wide dependency injector class. Copies the module-wide dependency injector parameters.

def get_psf_model_dependency_injector():

Gets the dependecy injector instance

def go(fits_spec, output_path=None, fit_result_dir=None, model=None, method=None, model_help=None, error_factor=None, **kwargs):

Thin wrapper around run() to accept string inputs. As long as the names of the arguments to this function are the same as the names expected from the command line we can do this programatically

def parse_args(argv):

Undocumented

def plot_result(result, psf_data, suptitle=None, show=True):

Plot the result of fitting a model to a PSF

def run(fits_spec, output_path, fit_result_dir: str | None = None, method: str = 'ultranest', error_factor=0.001):

Undocumented

def set_psf_model_dependency_injector(name, fits_spec):

Module-wide method. Sets the dependency injector class and initialises the dependency injector instance.

def set_psf_model_dependency_injector_params(variables=[], **kwargs):

Sets the parameters of the module-wide dependency injector

FITTING_METHODS: tuple[str, ...] =

Undocumented

Value
('ultranest', 'scipy.minimize')
PSF_MODEL_DI =

Undocumented

Value
None
PSF_MODEL_DI_CLASS =

Undocumented

Value
None
psf_models =

Undocumented

_lgr =

Undocumented