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22 changes: 20 additions & 2 deletions docs/user_guide/operations.rst
Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,7 @@ a Vector is treated as an nx1 column matrix.
[2., 5., 1.5, 4.25, 0.5], nrows=4, ncols=4)
B = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2, 3, 3], [1, 2, 0, 1, 1, 2, 0, 1],
[3., 2., 9., 6., 3., 1., 0., 5.])
C = gb.Matrix(float, A.nrows, B.ncols)

# These are equivalent
C << A.mxm(B, op='min_plus') # method style
Expand Down Expand Up @@ -69,6 +70,7 @@ a Vector is treated as an nx1 column matrix.
A = gb.Matrix.from_coo([0, 0, 1, 1, 2], [1, 2, 2, 3, 3],
[2., 5., 1.5, 4.25, 0.5], nrows=4, ncols=4)
v = gb.Vector.from_coo([0, 1, 3], [10., 20., 40.])
w = gb.Vector(float, A.nrows)

# These are equivalent
w << A.mxv(v, op='plus_times') # method style
Expand Down Expand Up @@ -102,6 +104,7 @@ a Vector is treated as an nx1 column matrix.
v = gb.Vector.from_coo([0, 1, 3], [10., 20., 40.])
B = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2, 3, 3], [1, 2, 0, 1, 1, 2, 0, 1],
[3., 2., 9., 6., 3., 1., 0., 5.])
u = gb.Vector(float, B.ncols)

# These are equivalent
u << v.vxm(B, op='plus_plus') # method style
Expand Down Expand Up @@ -149,6 +152,7 @@ Example usage:
[2.0, 5.0, 1.5, 4.0, 0.5])
B = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 2, 0, 1, 1, 2],
[3., -2., 0., 6., 3., 1.])
C = gb.Matrix(float, A.nrows, A.ncols)

# These are equivalent
C << A.ewise_mult(B, op='min') # method style
Expand Down Expand Up @@ -221,10 +225,11 @@ should be used with the functional syntax, ``left_default`` and ``right_default`

.. code-block:: python

A = gb.Matrix.from_coo([0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 2],
A = gb.Matrix.from_coo([0, 0, 0, 1, 1], [0, 1, 2, 0, 2],
[9.0, 2.0, 5.0, 1.5, 4.0], nrows=3)
B = gb.Matrix.from_coo([0, 0, 0, 2, 2, 2], [0, 1, 2, 0, 1, 2],
[4., 0., -2., 6., 3., 1.])
C = gb.Matrix(float, A.nrows, A.ncols)

# These are equivalent
C << A.ewise_add(B, op='minus') # method style
Expand Down Expand Up @@ -258,10 +263,11 @@ should be used with the functional syntax, ``left_default`` and ``right_default`

.. code-block:: python

A = gb.Matrix.from_coo([0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 2],
A = gb.Matrix.from_coo([0, 0, 0, 1, 1], [0, 1, 2, 0, 2],
[9.0, 2.0, 5.0, 1.5, 4.0], nrows=3)
B = gb.Matrix.from_coo([0, 0, 0, 2, 2, 2], [0, 1, 2, 0, 1, 2],
[4., 0., -2., 6., 3., 1.])
C = gb.Matrix(float, A.nrows, A.ncols)

# These are equivalent
C << A.ewise_union(B, op='minus', left_default=0, right_default=0) # method style
Expand Down Expand Up @@ -315,6 +321,7 @@ Vector Slice Example:
.. code-block:: python

v = gb.Vector.from_coo([0, 1, 3, 4, 6], [10., 2., 40., -5., 24.])
w = gb.Vector(float, 4)

w << v[:4]

Expand All @@ -336,6 +343,7 @@ Matrix List Example:

A = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 2, 0, 1, 0, 2],
[2.0, 5.0, 1.5, 4.0, 0.5, -7.0])
C = gb.Matrix(float, 2, A.ncols)

C << A[[0, 2], :]

Expand Down Expand Up @@ -473,6 +481,7 @@ function with the collection as the argument.
.. code-block:: python

v = gb.Vector.from_coo([0, 1, 3], [10., 20., 40.])
w = gb.Vector(float, v.size)

# These are equivalent
w << v.apply(gb.unary.minv)
Expand All @@ -495,6 +504,7 @@ function with the collection as the argument.
.. code-block:: python

v = gb.Vector.from_coo([0, 1, 3], [10., 20., 40.])
w = gb.Vector(int, v.size)

# These are equivalent
w << v.apply(gb.indexunary.index)
Expand All @@ -517,6 +527,7 @@ function with the collection as the argument.
.. code-block:: python

v = gb.Vector.from_coo([0, 1, 3], [10., 20., 40.])
w = gb.Vector(float, v.size)

# These are all equivalent
w << v.apply('minus', right=15)
Expand Down Expand Up @@ -548,6 +559,7 @@ Upper Triangle Example:

A = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 2, 0, 2, 1, 2],
[2.0, 5.0, 1.5, 4.0, 0.5, -7.0])
C = gb.Matrix(float, A.nrows, A.ncols)

# These are equivalent
C << A.select('triu')
Expand All @@ -574,6 +586,7 @@ Select by Value Example:
.. code-block:: python

v = gb.Vector.from_coo([0, 1, 3, 4, 6], [10., 2., 40., -5., 24.])
w = gb.Vector(float, v.size)

# These are equivalent
w << v.select('>=', 5)
Expand Down Expand Up @@ -607,6 +620,7 @@ A monoid or aggregator is used to perform the reduction.

A = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 3, 0, 1, 0, 1],
[2.0, 5.0, 1.5, 4.0, 0.5, -7.0])
w = gb.Vector(float, A.ncols)

w << A.reduce_columnwise('times')

Expand All @@ -630,6 +644,7 @@ A monoid or aggregator is used to perform the reduction.

A = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 3, 0, 1, 0, 1],
[2.0, 5.0, 1.5, 4.0, 0.5, -7.0])
s = gb.Scalar(float)

s << A.reduce_scalar('max')

Expand All @@ -652,6 +667,7 @@ A monoid or aggregator is used to perform the reduction.
.. code-block:: python

v = gb.Vector.from_coo([0, 1, 3, 4, 6], [10., 2., 40., -5., 24.])
s = gb.Scalar(int)

# These are equivalent
s << v.reduce('argmin')
Expand Down Expand Up @@ -681,6 +697,7 @@ To force the transpose to be computed by itself, use it by itself as the right-h

A = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 3, 0, 1, 0, 2],
[2.0, 5.0, 1.5, 4.0, 0.5, -7.0])
C = gb.Matrix(float, A.ncols, A.nrows)

C << A.T

Expand Down Expand Up @@ -714,6 +731,7 @@ The Kronecker product uses a binary operator.
A = gb.Matrix.from_coo([0, 0, 1], [0, 1, 0], [1., -2., 3.])
B = gb.Matrix.from_coo([0, 0, 1, 1, 2, 2], [1, 2, 0, 1, 0, 2],
[2.0, 5.0, 1.5, 4.0, 0.5, -7.0])
C = gb.Matrix(float, A.nrows * B.nrows, A.ncols * B.ncols)

C << A.kronecker(B, 'times')

Expand Down