Data Containers

mouette is architectured around the concept of data containers, which are containers dedicated to the storage of one type of elements in a mesh and all of its attributes. Data structures in mouette are then defined as collections of specific data containers:

A PointCloud object only has one container named vertices such that object.vertices[i] is a 3D vector containing the position of vertex i in space.
In addition to the vertices container, a Polyline object also defines an edges container, which stores pairs of vertex indices.
A SurfaceMesh object adds the faces and face_corners containers.
Finally, a VolumeMesh objects adds a cells container and two corner containers: cell_corners and cell_faces.

The `DataContainer` class

Bases: _BaseDataContainer

A DataContainer is a container class for all elements of the same type in an instance (for example, vertices, edges or faces). It stores relevant information about the combinatorics (in the _data field) as well as various attributes onto the elements (in the _attr field)

`size` `property`

The container size. Alias for len(container)

Returns:

Name	Type	Description
`int`	`int`	number of elements in the container

`iadd(other)`

Performs several appends for a list of elements

Parameters:

Name	Type	Description	Default
`other`	`Iterable \| DataContainer`	a collection of elements to append to the container	required

Raises:

Type	Description
`Exception`	fails if `other` is not an iterable

Returns:

Name	Type	Description
`self`		self

`append(val)`

Adds the value 'val' at the end of the container. Also expands all attributes to be able to receive a value for 'val'

Parameters:

Name	Type	Description	Default
`val`	`Any`	value to append to the container	required

`clear()`

Empty the container

`create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)`

Creates an attribute with name name

Parameters:

Name	Type	Description	Default
`name`	`str`	attribute's name. If 'name' already exists in the attribute dict, the corresponding attribute will be overridden. The override warning can be disabled in the config.	required
`data_type`	`type`	The type of data stored in the attribute.	required
`elem_size`	`int`	The number of data per elements. Defaults to 1.	`1`
`dense`	`bool`	Whether to create an `Attribute` object (dictionnary storage) or an `ArrayAttribute` object (numpy array storage). Defaults to False (dictionnary mode).	`False`
`default_value`	`Any`	The default value to fill the attribute with. If not provided, will be taken as the default value of the type `data_type`. Defaults to None.	`None`
`size`	`int`	Current size of the DataContainer to be passed. Defaults to None.	`None`

Returns:

Name	Type	Description
`Attribute`	`Attribute`

`delete_attribute(name)`

Deletes the attribute associated with name name if it exists.

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name.	required

`empty()`

Returns:

Name	Type	Description
`bool`	`bool`	whether the container is empty

`get_attribute(name)`

Returns the attribute with name name. Fails if the attribute does not exist

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name	required

Raises:

Type	Description
`Exception`	no attribute has name `name` inside this data container.

Returns:

Name	Type	Description
`Attribute`	`Attribute`	the attribute

`has_attribute(name)`

Returns True is an attribute with name name is defined for this container.

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name	required

Returns:

Name	Type	Description
`bool`	`bool`

`register_array_as_attribute(name, data, default_value=None)`

Converts a numpy array as an attribute.

Parameters:

Name	Type	Description	Default
`name`	`str`	attribute's name. If 'name' already exists in the attribute dict, the corresponding attribute will be overridden. The override warning can be disabled in the config.	required
`data`	`ndarray`	the data array. Type of the attribute will be extrapolated from `data.dtype`.	required
`default_value`	`Any`	The default value to fill the attribute with. If not provided, will be taken as the default value of the type `data_type`. Defaults to None.	`None`

Bases: ABC

Base class for a data container. A container encapsulate all elements of the same type in a mesh as well as attributes defined on them.

`create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)`

Creates an attribute with name name

Parameters:

Name	Type	Description	Default
`name`	`str`	attribute's name. If 'name' already exists in the attribute dict, the corresponding attribute will be overridden. The override warning can be disabled in the config.	required
`data_type`	`type`	The type of data stored in the attribute.	required
`elem_size`	`int`	The number of data per elements. Defaults to 1.	`1`
`dense`	`bool`	Whether to create an `Attribute` object (dictionnary storage) or an `ArrayAttribute` object (numpy array storage). Defaults to False (dictionnary mode).	`False`
`default_value`	`Any`	The default value to fill the attribute with. If not provided, will be taken as the default value of the type `data_type`. Defaults to None.	`None`
`size`	`int`	Current size of the DataContainer to be passed. Defaults to None.	`None`

Returns:

Name	Type	Description
`Attribute`	`Attribute`

`delete_attribute(name)`

Deletes the attribute associated with name name if it exists.

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name.	required

`get_attribute(name)`

Returns the attribute with name name. Fails if the attribute does not exist

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name	required

Raises:

Type	Description
`Exception`	no attribute has name `name` inside this data container.

Returns:

Name	Type	Description
`Attribute`	`Attribute`	the attribute

`has_attribute(name)`

Returns True is an attribute with name name is defined for this container.

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name	required

Returns:

Name	Type	Description
`bool`	`bool`

`register_array_as_attribute(name, data, default_value=None)`

Converts a numpy array as an attribute.

Parameters:

Name	Type	Description	Default
`name`	`str`	attribute's name. If 'name' already exists in the attribute dict, the corresponding attribute will be overridden. The override warning can be disabled in the config.	required
`data`	`ndarray`	the data array. Type of the attribute will be extrapolated from `data.dtype`.	required
`default_value`	`Any`	The default value to fill the attribute with. If not provided, will be taken as the default value of the type `data_type`. Defaults to None.	`None`

The special case of corner containers

Bases: _BaseDataContainer

A CornerDataContainer is a variant of a DataContainer for corner elements. It is used for face corners, cell corners and cell faces.

Unlike a regular data container that stores a list of simplicial elements, a corner container stores two pieces of information: the associated vertex/face of the corner and the face/cell it belongs to.

`size` `property`

The container size. Alias for len(container)

Returns:

Name	Type	Description
`int`		number of elements in the container

`getitem(key)`

Shortcut for self.elem(key)

Parameters:

Name	Type	Description	Default
`key`	`int`	corner identifier	required

Returns:

Name	Type	Description
`int`	`int`	the vertex or the face this corner points to

`adj(key)`

Returns the mesh element (either face or cell) from which the corner 'key' belongs to

Parameters:

Name	Type	Description	Default
`key`	`int`	identifier of a corner	required

Returns:

Name	Type	Description
`int`	`int`	identifier of a face or a cell

`clear()`

Empty the container

`create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)`

Creates an attribute with name name

Parameters:

Name	Type	Description	Default
`name`	`str`	attribute's name. If 'name' already exists in the attribute dict, the corresponding attribute will be overridden. The override warning can be disabled in the config.	required
`data_type`	`type`	The type of data stored in the attribute.	required
`elem_size`	`int`	The number of data per elements. Defaults to 1.	`1`
`dense`	`bool`	Whether to create an `Attribute` object (dictionnary storage) or an `ArrayAttribute` object (numpy array storage). Defaults to False (dictionnary mode).	`False`
`default_value`	`Any`	The default value to fill the attribute with. If not provided, will be taken as the default value of the type `data_type`. Defaults to None.	`None`
`size`	`int`	Current size of the DataContainer to be passed. Defaults to None.	`None`

Returns:

Name	Type	Description
`Attribute`	`Attribute`

`delete_attribute(name)`

Deletes the attribute associated with name name if it exists.

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name.	required

`element(key)`

Returns the mesh element (vertex or face) associated with the corner 'key'

Parameters:

Name	Type	Description	Default
`key`	`int`	identifier of a corner	required

Returns:

Name	Type	Description
`int`	`int`	identifier of a vertex or face

`empty()`

Returns:

Name	Type	Description
`bool`		whether the container is empty

`get_attribute(name)`

Returns the attribute with name name. Fails if the attribute does not exist

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name	required

Raises:

Type	Description
`Exception`	no attribute has name `name` inside this data container.

Returns:

Name	Type	Description
`Attribute`	`Attribute`	the attribute

`has_attribute(name)`

Returns True is an attribute with name name is defined for this container.

Parameters:

Name	Type	Description	Default
`name`	`str`	the attribute's name	required

Returns:

Name	Type	Description
`bool`	`bool`

`register_array_as_attribute(name, data, default_value=None)`

Converts a numpy array as an attribute.

Parameters:

Name	Type	Description	Default
`name`	`str`	attribute's name. If 'name' already exists in the attribute dict, the corresponding attribute will be overridden. The override warning can be disabled in the config.	required
`data`	`ndarray`	the data array. Type of the attribute will be extrapolated from `data.dtype`.	required
`default_value`	`Any`	The default value to fill the attribute with. If not provided, will be taken as the default value of the type `data_type`. Defaults to None.	`None`

Attributes

`ArrayAttribute(elem_type, n_elem, elem_size=1, default_value=None)`

Bases: _BaseAttribute

init method and the whole Attribute class are not supposed to be manipulated outside of the DataContainer class. An ArrayAttribute stores its values in a numpy array. This is a less flexible but safer approach than Attribute.

Parameters:

Name	Type	Description	Default
`elem_type`		the type of the attribute (bool, int, float, complex, string)	required
`n_elem`	`int`	Total number of elements in the container. Should match the size of the DataContainer the attribute is stored in.	required
`elem_size`	`int`	Number of elem_type objects to be stored per element. Defaults to 1.	`1`
`dense`	`bool`	description. Defaults to False.	required
`default_value`	`optional)`	the default value of the attribute is n_elem is not specified. If it is not specified either, it will correspond to the default value of the type provided in elem_type.	`None`

`iter()`

Sparse attributes allow to iterate only over non-default elements

`clear()`

Empties the attribute. Frees the memory and ensures that all access return default value

`empty()`

Check if an attribute is empty. For an attribute to be empty, its number of elements should not be fixed, and the dictionnary should be empty

`Attribute(elem_type, elem_size=1, default_value=None)`

Bases: _BaseAttribute

init method and the whole Attribute class are not supposed to be manipulated outside of the DataContainer class

Parameters:

Name	Type	Description	Default
`elem_type`		the type of the attribute (bool, int, float, complex, string)	required
`elem_size`	`int`	Number of elem_type objects to be stored per element. Defaults to 1.	`1`
`default_value`	`optional)`	the default value of the attribute is n_elem is not specified. If it is not specified either, it will correspond to the default value of the type provided in elem_type.	`None`

`iter()`

Sparse attributes allow to iterate only over non-default elements

`clear()`

Empties the attribute. Frees the memory and ensures that all access return default value

`empty()`

Check if an attribute is empty. For an attribute to be empty, its number of elements should not be fixed, and the dictionnary should be empty

Data Containers

The DataContainer class

size property

__iadd__(other)

append(val)

clear()

create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)

delete_attribute(name)

empty()

get_attribute(name)

has_attribute(name)

register_array_as_attribute(name, data, default_value=None)

create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)

delete_attribute(name)

get_attribute(name)

has_attribute(name)

register_array_as_attribute(name, data, default_value=None)

The special case of corner containers

size property

__getitem__(key)

adj(key)

clear()

create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)

delete_attribute(name)

element(key)

empty()

get_attribute(name)

has_attribute(name)

register_array_as_attribute(name, data, default_value=None)

Attributes

ArrayAttribute(elem_type, n_elem, elem_size=1, default_value=None)

__iter__()

clear()

empty()

Attribute(elem_type, elem_size=1, default_value=None)

__iter__()

clear()

empty()

The `DataContainer` class

`size` `property`

`iadd(other)`

`append(val)`

`clear()`

`create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)`

`delete_attribute(name)`

`empty()`

`get_attribute(name)`

`has_attribute(name)`

`register_array_as_attribute(name, data, default_value=None)`

`create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)`

`delete_attribute(name)`

`get_attribute(name)`

`has_attribute(name)`

`register_array_as_attribute(name, data, default_value=None)`

`size` `property`

`getitem(key)`

`adj(key)`

`clear()`

`create_attribute(name, data_type, elem_size=1, dense=False, default_value=None, size=None)`

`delete_attribute(name)`

`element(key)`

`empty()`

`get_attribute(name)`

`has_attribute(name)`

`register_array_as_attribute(name, data, default_value=None)`

`ArrayAttribute(elem_type, n_elem, elem_size=1, default_value=None)`

`iter()`

`clear()`

`empty()`

`Attribute(elem_type, elem_size=1, default_value=None)`

`iter()`

`clear()`

`empty()`