Multi-Block Structures

Vector

Constructor

Vector(data[, name, index, dtype, copy])

State or observation vector composed of one or more Block objects.

Attributes and underlying data

Vector.name	The name of the underlying Series.
Vector.data	The underlying data, which must be numeric and non-NaN.
Vector.index	Return the index of the underlying data.
Vector.shape	Return the shape of the underlying data.
Vector.values	Return the values as a numpy array.
Vector.blocks	Accessor for retrieving Block instances from the Vector.

Conversion

Vector.copy([deep])	Create a copy of the structure.
Vector.to_series()	Get the underlying Series data.
Vector.to_numpy()	Get the underlying data as a NumPy array.
Vector.to_xarray()	Convert the Vector to xarray.

Reindexing / selection / label manipulation

Vector.__getitem__(block)	Get block by name.
Vector.xs(key[, axis, level, drop_level])	Cross-select data based on index/column values.
Vector.reindex(index[, columns, ...])	Return a new instance with data reindexed to the specified index and columns.
Vector.round_index(decimals[, axis, inplace])	Round float indices on the specified axis to given decimals.

Serialization

Vector.from_file(path)	Load object from a pickle file.
Vector.to_file(path)	Save object to a pickle file.

Matrix

Constructor

Matrix(data[, name, index, columns, dtype, ...])

Base class for all matrix-like objects in the inversion framework.

Attributes and underlying data

Matrix.name	Name of the structure, used for error messages and block naming.
Matrix.data	The underlying data, which must be numeric and non-NaN.
Matrix.index	Return the index of the underlying data.
Matrix.columns	Return the columns of the underlying DataFrame.
Matrix.shape	Return the shape of the underlying data.
Matrix.values	Return values as numpy array or sparse matrix.

Conversion

Matrix.copy([deep])	Create a copy of the structure.
Matrix.to_frame()	Get the underlying DataFrame data.
Matrix.to_numpy()	Get the underlying data as a NumPy array.

Reindexing / selection / label manipulation

Matrix.__getitem__(block)	Get the submatrix DataFrame for the given (row_block, col_block) tuple.
Matrix.xs(key[, axis, level, drop_level])	Cross-select data based on index/column values.
Matrix.reindex(index[, columns, ...])	Return a new instance with data reindexed to the specified index and columns.
Matrix.round_index(decimals[, axis, inplace])	Round float indices on the specified axis to given decimals.

Computations

Matrix.scale(factor)

Scale the matrix by a scalar factor.

Binary operations

Matrix.__add__(other)

Add two Matrix instances.

Serialization

Matrix.from_file(path)	Load object from a pickle file.
Matrix.to_file(path)	Save object to a pickle file.

Sparse support

Matrix.is_sparse	True if the internal DataFrame uses pandas sparse storage.
Matrix.to_sparse([threshold])	Return a copy with sparse internal storage.
Matrix.to_dense()	Return a copy with dense internal storage.