pyface.data_view.data_models.array_data_model module

Provides an N-dimensional array data model implementation.

This module provides a concrete implementation of a data model for an n-dim numpy array.

class pyface.data_view.data_models.array_data_model.ArrayDataModel(**traits)

Bases: AbstractDataModel, HasRequiredTraits

A data model for an n-dim array.

This data model presents the data from a multidimensional array hierarchically by dimension. The underlying array must be at least 2 dimensional.

Values are adapted by the value_type trait. This provides sensible default values for integer, float and text dtypes, but other dtypes may need the user of the class to supply an appropriate value type class to adapt values.

There are additional value types which provide data sources for row headers, column headers, and the label of the row header column. The defaults are likely suitable for most cases, but can be overriden if required.

data = _AtLeastTwoDArray()

The array being displayed. This must have dimension at least 2.

index_manager = Instance(TupleIndexManager, args=())

The index manager that helps convert toolkit indices to data view indices.

label_header_type = Instance( …

The value type of the row index column header.

column_header_type = Instance( …

The value type of the column titles.

row_header_type = Instance( …

The value type of the row titles.

value_type = Instance(AbstractValueType, allow_none=False, required=True)

The type of value being displayed in the data model.

get_column_count()

How many columns in the data view model.

The number of columns is the size of the last dimension of the array.

Returns

column_count – The number of columns in the data view model, which is the size of the last dimension of the array.

Return type

non-negative int

can_have_children(row)

Whether or not a row can have child rows.

A row is a leaf row if the length of the index is one less than the dimension of the array: the final coordinate for the value will be supplied by the column index.

Parameters

row (sequence of int) – The indices of the row as a sequence from root to leaf.

Returns

can_have_children – Whether or not the row can ever have child rows.

Return type

bool

get_row_count(row)

Whether or not the row currently has any child rows.

The number of rows in a non-leaf row is equal to the size of the next dimension.

Parameters

row (sequence of int) – The indices of the row as a sequence from root to leaf.

Returns

has_children – Whether or not the row currently has child rows.

Return type

bool

get_value(row, column)

Return the Python value for the row and column.

Parameters

row (sequence of int) – The indices of the row as a sequence from root to leaf.

Returns

row_count – The number of child rows that the row has.

Return type

non-negative int

can_set_value(row, column)

Whether the value in the indicated row and column can be set.

This returns False for row and column headers, but True for all array values.

Parameters

• row (sequence of int) – The indices of the row as a sequence from root to leaf.

• column (sequence of int) – The indices of the column as a sequence of length 0 or 1.

Returns

can_set_value – Whether or not the value can be set.

Return type

bool

set_value(row, column, value)

Return the Python value for the row and column.

Parameters

• row (sequence of int) – The indices of the row as a sequence from root to leaf.

• column (sequence of int) – The indices of the column as a sequence of length 1.

Returns

value – The value represented by the given row and column.

Return type

Any

get_value_type(row, column)

Return the value type of the given row and column.

This method returns the value of column_header_type for column headers, the value of row_header_type for row headers, the value of label_header_type for the top-left corner value, the value of value_type for all array values, and no_value for everything else.

Parameters

• row (sequence of int) – The indices of the row as a sequence from root to leaf.

• column (sequence of int) – The indices of the column as a sequence of length 0 or 1.

Returns

value_type – The value type of the given row and column.

Return type

AbstractValueType

data_updated(event)

Handle the array being replaced with a new array.

value_type_updated(event)

Handle the value type being updated.

column_header_type_updated(event)

Handle the column header type being updated.

value_header_type_updated(event)

Handle the value header type being updated.

label_header_type_updated(event)

Handle the label header type being updated.