LGOFMART¶

class kgpy.ctis.inversion.mart.lgof_mart.LGOFMART(track_cube_history=False, anti_aliasing=None, rotation_kwargs=<factory>, verbose=False)¶

Bases: SimpleMART

Parameters:

track_cube_history (bool) –
anti_aliasing (str) –
rotation_kwargs (Dict[str, Any]) –
verbose (bool) –

__init__(track_cube_history=False, anti_aliasing=None, rotation_kwargs=<factory>, verbose=False)¶

Parameters:

track_cube_history (bool) –
anti_aliasing (str | None) –
rotation_kwargs (Dict[str, Any]) –
verbose (bool) –

Return type:

None

Attributes

`anti_aliasing`
`track_cube_history`
`type_int`
`verbose`	SimpleMART is the basic unit of mart, and encompasses a single "filtering iteration".
`rotation_kwargs`

Methods

`__init__`([track_cube_history, ...])
`channel_is_not_converged`(goodness_of_fit)	rtype: `bool`
`chisq`(goodness_of_fit)	rtype: `float`
`correction_exponent`(goodness_of_fit)	rtype: `numpy.ndarray`

Inheritance Diagram

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static channel_is_not_converged(goodness_of_fit)¶

Return type:: bool
Parameters:: goodness_of_fit (ndarray) –

static chisq(goodness_of_fit)¶

Return type:: float
Parameters:: goodness_of_fit (ndarray) –

static correction_exponent(goodness_of_fit)¶

Return type:: numpy.ndarray
Parameters:: goodness_of_fit (ndarray) –

anti_aliasing: str = None¶

rotation_kwargs: typing.Dict[str, typing.Any]¶

track_cube_history: bool = False¶

type_int: typing.ClassVar[int] = 1¶

verbose: bool = False¶

SimpleMART is the basic unit of mart, and encompasses a single “filtering iteration”.

Parameters:: track_cube_history – if ‘multiplicative’, a copy of the cube after each multiplicative iteration will be stored. Very memory intensive. if ‘filter’, a copy is saved each time MART converges (or exceeds max multiplicative iterations)

Navigation

LGOFMART¶