interregnum.bidimensional package¶

A bi-dimensional structure useful for graph or table operations.

class interregnum.bidimensional.Bidimensional¶

Bases: Generic[_Row, _Col, AnyValue]

Bi-dimensional structure.

__getitem__(idx)¶

Return the value at position idx (row index, col index).

Parameters:: idx (tuple[_Row, _Col])
Return type:: AnyValue

col_size()¶

Return the number of columns.

Return type:: int

empty()¶

Return True if the object is empty.

Return type:: bool

iter_col(col, sparse=False)¶

Iterate column _Col elements.

Parameters:

col (_Col)
sparse (bool)

Return type:

Iterator[tuple[_Row, AnyValue]]

iter_col_keys()¶

Iterate column keys.

Return type:: Iterator[_Col]

iter_row(row, sparse=False)¶

Iterate row _Row elements.

Parameters:

row (_Row)
sparse (bool)

Return type:

Iterator[tuple[_Col, AnyValue]]

iter_row_keys()¶

Iterate row keys.

Return type:: Iterator[_Row]

remove_row(row)¶

Remove row _Row.

Parameters:: row (_Row)
Return type:: None

row_size()¶

Return the number of rows.

Return type:: int

Submodules¶

interregnum.bidimensional.dataframe module¶

A poor man’s data frame.

class interregnum.bidimensional.dataframe.DataFrame¶

Bases: Bidimensional[AnyKey, int, AnyValue]

Table for series of data.

Create an empty data frame.

__getitem__(idx)¶

Return the value at position idx (row index, col index).

Parameters:: idx (tuple[AnyKey, int])
Return type:: AnyValue

col_size()¶

Return the number of columns.

Return type:: int

empty()¶

Return True if the object is empty.

Return type:: bool

insert_row(row, series)¶

Insert or replace a row.

Parameters:

row (AnyKey)
series (list[AnyValue])

Return type:

None

iter_col(col, sparse=False)¶

Iterate column _Col elements.

Parameters:

col (int)
sparse (bool)

Return type:

Iterator[tuple[AnyKey, AnyValue]]

iter_col_keys()¶

Iterate column keys.

Return type:: Iterator[int]

iter_row(row, sparse=False)¶

Iterate row _Row elements.

Parameters:

row (AnyKey)
sparse (bool)

Return type:

Iterator[tuple[int, AnyValue]]

iter_row_keys()¶

Iterate row keys.

Return type:: Iterator[AnyKey]

remove_row(row)¶

Remove row _Row.

Parameters:: row (AnyKey)
Return type:: None

row_size()¶

Return the number of rows.

Return type:: int

interregnum.bidimensional.matrix module¶

Matrix structure with indices of a hashable type and values of any type.

class interregnum.bidimensional.matrix.AbstractMatrix¶

Bases: Bidimensional[_Row, _Col, AnyValue]

Abstract matrix.

__getitem__(idx)¶

Return the value at position idx (row index, col index).

Parameters:: idx (tuple[_Row, _Col])
Return type:: AnyValue

__str__()¶

Return str(self).

Return type:: str

col(idx)¶

Return col.

Parameters:: idx (_Col)
Return type:: dict[_Row, AnyValue]

col_size()¶

Return the number of columns.

Return type:: int

empty()¶

Return True if the object is empty.

Return type:: bool

iter_col(col, sparse=False)¶

Iterate column _Col elements.

Parameters:

col (_Col)
sparse (bool)

Return type:

Iterator[tuple[_Row, AnyValue]]

iter_col_keys()¶

Return col keys.

Return type:: Iterator[_Col]

iter_cols()¶

Iterate cols.

Return type:: ItemsView[_Col, dict[_Row, AnyValue]]

iter_row(row, sparse=False)¶

Iterate row _Row elements.

Parameters:

row (_Row)
sparse (bool)

Return type:

Iterator[tuple[_Col, AnyValue]]

iter_row_keys()¶

Return row keys.

Return type:: Iterator[_Row]

iter_rows()¶

Iterate rows.

Return type:: ItemsView[_Row, dict[_Col, AnyValue]]

remove_col(col)¶

Remove column col.

Parameters:: col (_Col)
Return type:: None

remove_row(row)¶

Remove row _Row.

Parameters:: row (_Row)
Return type:: None

row(idx)¶

Return row.

Parameters:: idx (_Row)
Return type:: dict[_Col, AnyValue]

row_size()¶

Return the number of rows.

Return type:: int

transpose()¶

Transpose matrix.

Return type:: AbstractMatrix[_Col, _Row, AnyValue]

class interregnum.bidimensional.matrix.Matrix(default_value_f, row_keys, col_keys)¶

Bases: TransposableMatrix[_Row, _Col, AnyValue]

Dict based matrix.

Parameters:

default_value_f (Callable[[_Row, _Col], AnyValue])
row_keys (Iterable[_Row])
col_keys (Iterable[_Col])

transpose()¶

Return a transposed matrix from this one.

Return type:: TransposableMatrix[_Col, _Row, AnyValue]

class interregnum.bidimensional.matrix.TransposableMatrix¶

Bases: AbstractMatrix[_Row, _Col, AnyValue]

A matrix that can be transposed.

transpose()¶

Return a transposed matrix from this one.

Return type:: TransposableMatrix[_Col, _Row, AnyValue]

class interregnum.bidimensional.matrix.TransposedMatrix(matrix)¶

Bases: TransposableMatrix[_Row, _Col, AnyValue]

Transposed view of a matrix.

Parameters:: matrix (TransposableMatrix[_Col, _Row, AnyValue])

transpose()¶

Return a transposed matrix from this one.

Return type:: TransposableMatrix[_Col, _Row, AnyValue]

interregnum.bidimensional.sparse module¶

A sparse bi-dimensional table.

class interregnum.bidimensional.sparse.SparseTable(default)¶

Bases: Bidimensional[_Row, _Col, AnyValue]

Bi-dimensional table which initialises missing values.

Rows and cols keys are added dynamically.

Create a sparse table with a default value for empty cells.

Parameters:: default (AnyValue)

__getitem__(idx)¶

Return the element at idx.

Parameters:

idx (tuple[_Row, _Col]) – a row-column tuple

Returns:

the element at idx
>>> t = SparseTable(0)
>>> a = t[0, 3]

Return type:

AnyValue

__str__()¶

Return str(self).

Return type:: str

col_size()¶

Return the number of columns.

Return type:: int

empty()¶

Return True if the object is empty.

Return type:: bool

iter_col(col, sparse=False)¶

Iterate existing elements in a column.

If an element does not exist and not sparse, yield default value

Parameters:

col (_Col) – column index
sparse (bool) – if True, return only non-default values
SparseTable(0) (>>> t =)
t[2 (>>>)
1 (3] =)
t[5 (>>>)
2 (3] =)
t.iter_col(3) (>>> for x in)
print(x) (>>>)

Return type:

Iterator[tuple[_Row, AnyValue]]

iter_col_keys()¶

Return keys from existing columns.

>>> t = SparseTable(0)
>>> t['Alice', 'Bob'] = 5
>>> t['Bob', 'Charles'] = 3
>>> # 'Bob', 'Charles'
>>> print(t.col_keys())

Return type:: Iterator[_Col]

iter_row(row, sparse=False)¶

Iterate row _Row elements.

Parameters:

row (_Row)
sparse (bool)

Return type:

Iterator[tuple[_Col, AnyValue]]

iter_row_keys()¶

Iterate row keys.

Return type:: Iterator[_Row]

keys()¶

Return different existing keys in table.

>>> t = SparseTable(0)
>>> t['Alice', 'Bob'] = 5
>>> t['Bob', 'Charles'] = 3
>>> # 'Alice', 'Bob', 'Charles'
>>> print(t.keys())

Return type:: Iterator[_Row | _Col]

remove_col(col)¶

Remove elements from col.

Parameters:: col (_Col)
Return type:: None

remove_row(row)¶

Remove elements from row.

Parameters:: row (_Row)
Return type:: None

row(idx)¶

Get items in row (non-empty columns).

Parameters:

idx (_Row) – row index

Returns:

row at idx
>>> t = SparseTable(0)
>>> t[5, 2] = 2
>>> r5 = t.row(5)

Return type:

dict[_Col, AnyValue]

row_keys()¶

Return keys from existing rows.

>>> t = SparseTable(0)
>>> t['Alice', 'Bob'] = 5
>>> t['Bob', 'Charles'] = 3
>>> # 'Alice', 'Bob'
>>> print(t.row_keys())

Return type:: KeysView[_Row]

row_size()¶

Return the number of rows.

Return type:: int

rows()¶

Iterate existing rows.

Returns:: iterator of (row key, row defaultdict)
Return type:: ItemsView[_Row, dict[_Col, AnyValue]]

interregnum.bidimensional package¶

Submodules¶

interregnum.bidimensional.dataframe module¶

interregnum.bidimensional.matrix module¶

interregnum.bidimensional.sparse module¶

interregnum

Navigation

Related Topics