grig.grid package

Submodules

grig.grid.base_grid module

class grig.grid.base_grid.BaseGrid(*grid, scale_factor=None, scale_offset=None, build_tree=False, tree_shape=None, dtype=None, **kwargs)

Bases: object

Attributes:

features

Return the number of grid dimensions.

regular

Return whether the grid contains feature aligned grid coordinates.

scale_factor

Return the scaling factor between actual and grid coordinates.

scale_offset

Return the scaling offset between actual and grid coordinates.

shape

Return the shape of the grid.

singular

Return whether the grid consists of only a single output coordinate.

size

Return the number of grid vertices.

tree_class

Return the relevant tree class for this grid.

Methods

__call__()	Returns the grid.
get_class_for(thing)	Return a Grid class specific to a given tree, resampler, or name.
get_class_for_name(name)	Return a Grid class of the given name.
get_tree_class()	Return the relevant tree class for the grid.
rescale()	Re-apply the previous scaling factors and offsets if removed.
reshape_data(data)	Reshape data to the grid dimensions.
scale(factor, offset)	Apply a scaling factor and offset to the grid coordinates.
set_indexer([shape, build_tree, build_type])	Calculate the indexing mapping the grid coordinates to the tree.
unscale()	Unscale the grid coordinates.

property features

Return the number of grid dimensions.

Returns:

int

static get_class_for(thing)

Return a Grid class specific to a given tree, resampler, or name.

Parameters:

thingBaseTree or ResampleBase or str

Either a sub-class of a BaseTree, ResampleBase, or a string.

Returns:

BaseTree subclass

static get_class_for_name(name)

Return a Grid class of the given name.

Parameters:

namestr

The name of the grid.

Returns:

BaseGrid subclass

get_tree_class()

Return the relevant tree class for the grid.

Returns:

BaseGrid subclass

property regular

Return whether the grid contains feature aligned grid coordinates.

Returns:

bool

rescale()

Re-apply the previous scaling factors and offsets if removed.

Returns:

None

reshape_data(data)

Reshape data to the grid dimensions.

Note that this will only reshape data if the grid is regular.

Parameters:

datanumpy.ndarray

Data of the shape (n_sets, grid.size) or (grid.size,).

Returns:

reshaped_datanumpy.ndarray

Data of shape (grid.shape).

scale(factor, offset)

Apply a scaling factor and offset to the grid coordinates.

Parameters:

factornumpy.ndarray

A scaling factor of shape (n_features,).

offsetnumpy.ndarray

A scaling offset of shape (n_features,).

Returns:

None

property scale_factor

Return the scaling factor between actual and grid coordinates.

Returns:

numpy.ndarray (float)

property scale_offset

Return the scaling offset between actual and grid coordinates.

Returns:

numpy.ndarray (float)

set_indexer(shape=None, build_tree=False, build_type='hood', **kwargs)

Calculate the indexing mapping the grid coordinates to the tree.

Parameters:

shapetuple (int), optional

The shape of the grid. If not supplied, uses the maximum internal grid coordinates + 1 in each dimension.

build_treebool, optional

If True, builds a neighborhood tree of the type build_type.

build_typestr, optional

Must be one of {‘hood’, ‘balltree’, ‘all’, None}. Please see BaseTree for further details. The default type necessary for resampling is ‘hood’.

kwargsdict, optional

Optional keyword arguments passed into the tree initialization.

Returns:

None

property shape

Return the shape of the grid.

Returns:

tuple (int)

property singular

Return whether the grid consists of only a single output coordinate.

Returns:

bool

property size

Return the number of grid vertices.

Returns:

int

property tree_class

Return the relevant tree class for this grid.

Returns:

BaseTree subclass

unscale()

Unscale the grid coordinates.

Remove a scaling factor and offset if previously applied.

Returns:

None

grig.grid.kernel_grid module

class grig.grid.kernel_grid.KernelGrid(*grid, scale_factor=None, scale_offset=None, build_tree=False, tree_shape=None, dtype=None, **kwargs)

Bases: BaseGrid

The polynomial grid contains a KernelTree instead of the BaseTree object.

Attributes:

features

Return the number of grid dimensions.

regular

Return whether the grid contains feature aligned grid coordinates.

scale_factor

Return the scaling factor between actual and grid coordinates.

scale_offset

Return the scaling offset between actual and grid coordinates.

shape

Return the shape of the grid.

singular

Return whether the grid consists of only a single output coordinate.

size

Return the number of grid vertices.

tree_class

Return the relevant tree class for this grid.

Methods

__call__()	Returns the grid.
get_class_for(thing)	Return a Grid class specific to a given tree, resampler, or name.
get_class_for_name(name)	Return a Grid class of the given name.
get_tree_class()	Return the relevant tree class for the grid.
rescale()	Re-apply the previous scaling factors and offsets if removed.
reshape_data(data)	Reshape data to the grid dimensions.
scale(factor, offset)	Apply a scaling factor and offset to the grid coordinates.
set_indexer([shape, build_tree, build_type])	Calculate the indexing mapping the grid coordinates to the tree.
unscale()	Unscale the grid coordinates.

grig.grid.polynomial_grid module

class grig.grid.polynomial_grid.PolynomialGrid(*grid, scale_factor=None, scale_offset=None, build_tree=False, tree_shape=None, dtype=None, **kwargs)

Bases: BaseGrid

The polynomial grid contains a PolynomialTree instead of the BaseTree object.

Attributes:

features

Return the number of grid dimensions.

regular

Return whether the grid contains feature aligned grid coordinates.

scale_factor

Return the scaling factor between actual and grid coordinates.

scale_offset

Return the scaling offset between actual and grid coordinates.

shape

Return the shape of the grid.

singular

Return whether the grid consists of only a single output coordinate.

size

Return the number of grid vertices.

tree_class

Return the relevant tree class for this grid.

Methods

__call__()	Returns the grid.
get_class_for(thing)	Return a Grid class specific to a given tree, resampler, or name.
get_class_for_name(name)	Return a Grid class of the given name.
get_tree_class()	Return the relevant tree class for the grid.
rescale()	Re-apply the previous scaling factors and offsets if removed.
reshape_data(data)	Reshape data to the grid dimensions.
scale(factor, offset)	Apply a scaling factor and offset to the grid coordinates.
set_indexer([shape, build_tree, build_type])	Calculate the indexing mapping the grid coordinates to the tree.
unscale()	Unscale the grid coordinates.