Source code for magni.cs.reconstruction._config

    Copyright (c) 2014-2017, Magni developers.
    All rights reserved.
    See LICENSE.rst for further information.

Module providing a CS reconstruction algorithm adapted configger subclass.

Routine listings
    Provide functionality to access a set of configuration options.

This module does not itself contain any configuration options and thus has no
access to any configuration options unlike the other config modules of `magni`.


import numpy as np

from magni.utils.config import Configger as _Configger
from magni.utils.validation import decorate_validation as _decorate_validation
from magni.utils.validation import validate_generic as _generic

[docs]class Configger(_Configger): """ Provide functionality to access a set of configuration options. The present class redefines the methods for retrieving configuration parameters in order to ensure the desired precision of the floating point parameter values. Parameters ---------- params : dict The configuration options and their default values. valids : dict The validation schemes of the configuration options. Attributes ---------- property See Also -------- magni.utils.config.Configger : Superclass of the present class. """ def __init__(self, params, valids): @_decorate_validation def validate_input(): _generic('params', 'mapping', has_keys=('precision_float',)) _Configger.__init__(self, params, valids) validate_input()
[docs] def __getitem__(self, name): """ Get the value of a configuration parameter. Parameters ---------- name : str The name of the parameter. Returns ------- value : None The value of the parameter. Notes ----- If the value is a floating point value then that value is typecast to the desired precision. """ value = _Configger.__getitem__(self, name) if isinstance(value, (float, np.floating)): value = self['precision_float'](value) return value