SimpleMART

class esis.data.inversion.mart.simple_mart.SimpleMART(track_cube_history=False, anti_aliasing=None, rotation_kwargs=<factory>, verbose=False)

Bases: object

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

Initialize self. See help(type(self)) for accurate signature.

Parameters

• track_cube_history (bool) –

• anti_aliasing (str) –

• 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”.

Methods

__init__([track_cube_history, …])	Initialize self.
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

static channel_is_not_converged(goodness_of_fit)

Return type

bool

Parameters

goodness_of_fit (numpy.ndarray) –

static chisq(goodness_of_fit)

Return type

float

Parameters

goodness_of_fit (numpy.ndarray) –

static correction_exponent(goodness_of_fit)

Return type

numpy.ndarray

Parameters

goodness_of_fit (numpy.ndarray) –

anti_aliasing: str = None

rotation_kwargs: Dict[str, Any]

track_cube_history: bool = False

type_int: ClassVar[int] = 0

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)