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Adding matrix order=None to matrix classes #495

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54e2faf
adding order=None to new()
Aug 26, 2023
e1b00d6
adding to correct classes
Aug 26, 2023
b499666
trying to implement column order
Sep 4, 2023
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2 changes: 1 addition & 1 deletion graphblas/core/infix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -271,7 +271,7 @@ class MatrixInfixExpr(InfixExprBase):
_is_transposed = False
__networkx_plugin__ = "graphblas"

def __init__(self, left, right):
def __init__(self, left, right, order=None):
super().__init__(left, right)
if left.ndim == 1:
self._nrows = right._nrows
Expand Down
2 changes: 1 addition & 1 deletion graphblas/core/mask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ def _repr_html_(self):
def _carg(self):
return self.parent.gb_obj[0]

def new(self, dtype=None, *, complement=False, mask=None, name=None, **opts):
def new(self, dtype=None, *, complement=False, mask=None, order=None, name=None, **opts):
"""Return a new object with True values determined by the mask(s).

By default, the result is True wherever the mask(s) would have been applied,
Expand Down
18 changes: 14 additions & 4 deletions graphblas/core/matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -165,6 +165,8 @@ class Matrix(BaseType):
Number of rows.
ncols : int
Number of columns.
order : str, optional
Orientation of the Matrix.
name : str, optional
Name to give the Matrix. This will be displayed in the ``__repr__``.
"""
Expand All @@ -175,7 +177,7 @@ class Matrix(BaseType):
_name_counter = itertools.count()
__networkx_plugin__ = "graphblas"

def __new__(cls, dtype=FP64, nrows=0, ncols=0, *, name=None):
def __new__(cls, dtype=FP64, nrows=0, ncols=0, order=None, *, name=None):
self = object.__new__(cls)
self.dtype = lookup_dtype(dtype)
nrows = _as_scalar(nrows, _INDEX, is_cscalar=True)
Expand All @@ -188,6 +190,8 @@ def __new__(cls, dtype=FP64, nrows=0, ncols=0, *, name=None):
self._parent = None
if backend == "suitesparse":
self.ss = ss(self)
if order is not None:
self.ss.orientation = get_order(order)
return self

@classmethod
Expand Down Expand Up @@ -3388,6 +3392,7 @@ def __init__(
expr_repr=None,
ncols=None,
nrows=None,
order=None,
):
super().__init__(
method_name,
Expand Down Expand Up @@ -3517,10 +3522,11 @@ class MatrixIndexExpr(AmbiguousAssignOrExtract):
_is_transposed = False
__networkx_plugin__ = "graphblas"

def __init__(self, parent, resolved_indexes, nrows, ncols):
def __init__(self, parent, resolved_indexes, nrows, ncols, order):
super().__init__(parent, resolved_indexes)
self._nrows = nrows
self._ncols = ncols
self.ss.orientation = order

@property
def ncols(self):
Expand Down Expand Up @@ -3633,10 +3639,14 @@ def _repr_html_(self, collapse=False):

return format_matrix_html(self, collapse=collapse)

def new(self, dtype=None, *, mask=None, name=None, **opts):
def new(self, dtype=None, *, mask=None, name=None, order=None, **opts):
if dtype is None:
dtype = self.dtype
output = Matrix(dtype, self._nrows, self._ncols, name=name)
if order is None:
order = self.ss.orientation
else:
order = get_order(order)
output = Matrix(dtype, self._nrows, self._ncols, order, name=name)
output(mask=mask, **opts) << self
return output

Expand Down
7 changes: 7 additions & 0 deletions graphblas/core/ss/matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -249,6 +249,13 @@ def orientation(self):
return "columnwise"
return "rowwise"

@orientation.setter
def orientation(self, order):
if order == "columnwise":
return "columnwise"
else:
return "rowwise"

def build_diag(self, vector, k=0, **opts):
"""
GxB_Matrix_diag.
Expand Down
74 changes: 40 additions & 34 deletions graphblas/tests/test_matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -143,7 +143,7 @@ def test_from_coo():
assert C4.isequal(C5, check_dtype=True)

with pytest.raises(
ValueError, match="`rows` and `columns` and `values` lengths must match: 1, 2, 1"
ValueError, match="`rows` and `columns` and `values` lengths must match: 1, 2, 1"
):
Matrix.from_coo([0], [1, 2], [0])

Expand Down Expand Up @@ -521,27 +521,27 @@ def test_extract_input_mask():
with pytest.raises(ValueError, match="Shape of `input_mask` does not match shape of input"):
m(input_mask=MT.S) << A[0, [0, 1]]
with pytest.raises(
ValueError, match="Size of `input_mask` Vector does not match ncols of Matrix"
ValueError, match="Size of `input_mask` Vector does not match ncols of Matrix"
):
A[0, [0]].new(input_mask=expected.S)
with pytest.raises(
ValueError, match="Size of `input_mask` Vector does not match ncols of Matrix"
ValueError, match="Size of `input_mask` Vector does not match ncols of Matrix"
):
m(input_mask=expected.S) << A[0, [0]]
with pytest.raises(
ValueError, match="Size of `input_mask` Vector does not match nrows of Matrix"
ValueError, match="Size of `input_mask` Vector does not match nrows of Matrix"
):
A[[0], 0].new(input_mask=m.S)
with pytest.raises(
ValueError, match="Size of `input_mask` Vector does not match nrows of Matrix"
ValueError, match="Size of `input_mask` Vector does not match nrows of Matrix"
):
m(input_mask=m.S) << A[[0], 0]
with pytest.raises(
TypeError, match="Got Vector `input_mask` when extracting a submatrix from a Matrix"
TypeError, match="Got Vector `input_mask` when extracting a submatrix from a Matrix"
):
A[[0], [0]].new(input_mask=expected.S)
with pytest.raises(
TypeError, match="Got Vector `input_mask` when extracting a submatrix from a Matrix"
TypeError, match="Got Vector `input_mask` when extracting a submatrix from a Matrix"
):
A(input_mask=expected.S) << A[[0], [0]]
with pytest.raises(ValueError, match="input_mask"):
Expand Down Expand Up @@ -788,11 +788,11 @@ def test_assign_row_scalar(A, v):
C[:, :](C.S) << 1

with pytest.raises(
TypeError, match="Unable to use Vector mask on Matrix assignment to a Matrix"
TypeError, match="Unable to use Vector mask on Matrix assignment to a Matrix"
):
C[:, :](v.S) << 1
with pytest.raises(
TypeError, match="Unable to use Vector mask on single element assignment to a Matrix"
TypeError, match="Unable to use Vector mask on single element assignment to a Matrix"
):
C[0, 0](v.S) << 1

Expand Down Expand Up @@ -905,7 +905,7 @@ def test_assign_row_col_matrix_mask():
assert C.isequal(result)

with pytest.raises(
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
):
C[0, :](B.S) << v2

Expand All @@ -921,7 +921,7 @@ def test_assign_row_col_matrix_mask():
assert C.isequal(result)

with pytest.raises(
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
):
C[:, 0](B.S) << v2

Expand All @@ -937,7 +937,7 @@ def test_assign_row_col_matrix_mask():
assert C.isequal(result)

with pytest.raises(
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
):
C[:, 0](B.S) << 100

Expand All @@ -953,7 +953,7 @@ def test_assign_row_col_matrix_mask():
assert C.isequal(result)

with pytest.raises(
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
TypeError, match="Indices for subassign imply Vector submask, but got Matrix mask instead"
):
C[:, 0](B.S) << 100

Expand Down Expand Up @@ -1422,7 +1422,7 @@ def test_reduce_agg(A):
assert A.reduce_scalar(agg.count_nonzero).new() == 12
assert A.reduce_scalar(agg.count_zero).new() == 0
assert A.reduce_scalar(agg.sum_of_squares).new() == 245
assert A.reduce_scalar(agg.hypot).new().isclose(245**0.5)
assert A.reduce_scalar(agg.hypot).new().isclose(245 ** 0.5)
assert A.reduce_scalar(agg.logaddexp).new().isclose(8.6071076)
assert A.reduce_scalar(agg.logaddexp2).new().isclose(9.2288187)
assert A.reduce_scalar(agg.mean).new().isclose(47 / 12)
Expand Down Expand Up @@ -1482,7 +1482,7 @@ def test_reduce_agg_argminmax(A):

# reduce_scalar
with pytest.raises(
ValueError, match="Aggregator argmin may not be used with Matrix.reduce_scalar"
ValueError, match="Aggregator argmin may not be used with Matrix.reduce_scalar"
):
A.reduce_scalar(agg.ss.argmin)

Expand Down Expand Up @@ -2422,12 +2422,12 @@ def test_ss_import_export_auto(A, do_iso, methods):
"cooc",
]:
for (
sort,
raw,
import_format,
give_ownership,
take_ownership,
import_name,
sort,
raw,
import_format,
give_ownership,
take_ownership,
import_name,
) in itertools.product(
[False, True],
[False, True],
Expand Down Expand Up @@ -2473,11 +2473,11 @@ def import_func(x, import_name, **kwargs):
C_orig = C.dup()
for format in ["fullr", "fullc"]:
for raw, import_format, give_ownership, take_ownership, import_name in itertools.product(
[False, True],
[format, None],
[False, True],
[False, True],
["any", format],
[False, True],
[format, None],
[False, True],
[False, True],
["any", format],
):
assert C.shape == (C.nrows, C.ncols)
C2 = C.dup() if give_ownership or out_method == "unpack" else C
Expand Down Expand Up @@ -2646,7 +2646,7 @@ def test_not_to_array(A):
with pytest.raises(TypeError, match="Matrix can't be directly converted to a numpy array"):
np.array(A)
with pytest.raises(
TypeError, match="TransposedMatrix can't be directly converted to a numpy array"
TypeError, match="TransposedMatrix can't be directly converted to a numpy array"
):
np.array(A.T)

Expand Down Expand Up @@ -2745,14 +2745,14 @@ def test_ss_concat(A, v):
assert B1.dtype == "FP64"
expected = Matrix(A.dtype, nrows=A.nrows, ncols=2 * A.ncols)
expected[:, : A.ncols] = A
expected[:, A.ncols :] = A
expected[:, A.ncols:] = A
assert B1.isequal(expected)

B2 = Matrix(A.dtype, nrows=2 * A.nrows, ncols=A.ncols)
B2.ss.concat([[A], [A]])
expected = Matrix(A.dtype, nrows=2 * A.nrows, ncols=A.ncols)
expected[: A.nrows, :] = A
expected[A.nrows :, :] = A
expected[A.nrows:, :] = A
assert B2.isequal(expected)

tiles = A.ss.split([4, 3])
Expand Down Expand Up @@ -2783,7 +2783,7 @@ def test_ss_concat(A, v):
B4 = gb.ss.concat([[v], [v]])
expected = Matrix(v.dtype, nrows=2 * v.size, ncols=1)
expected[: v.size, 0] = v
expected[v.size :, 0] = v
expected[v.size:, 0] = v
assert B4.isequal(expected)

B5 = gb.ss.concat([[A, v]])
Expand Down Expand Up @@ -3032,7 +3032,7 @@ def test_dup_expr(A):
result = (A + A).dup(float, clear=True)
assert result.isequal(A.dup(float, clear=True), check_dtype=True)
result = (A * A).dup(mask=A.V)
assert result.isequal((A**2).new(mask=A.V))
assert result.isequal((A ** 2).new(mask=A.V))
result = A[:, :].dup()
assert result.isequal(A)
result = A[:, :].dup(clear=True)
Expand Down Expand Up @@ -3158,8 +3158,8 @@ def test_infix_sugar(A):
if shouldhave(binary.numpy, "mod"):
assert binary.numpy.mod(A, 2).isequal(A % 2)
assert binary.numpy.mod(5, A).isequal(5 % A)
assert binary.pow(A, 2).isequal(A**2)
assert binary.pow(2, A).isequal(2**A)
assert binary.pow(A, 2).isequal(A ** 2)
assert binary.pow(2, A).isequal(2 ** A)
assert binary.pow(A, 2).isequal(pow(A, 2))
assert unary.ainv(A).isequal(-A)
assert unary.ainv(A.T).isequal(-A.T)
Expand Down Expand Up @@ -3895,7 +3895,7 @@ def test_bool_as_mask(A):
@pytest.mark.skipif("not suitesparse")
def test_ss_serialize(A):
for compression, level, nthreads in itertools.product(
[None, "none", "default", "lz4", "lz4hc", "zstd"], [None, 1, 5, 9], [None, -1, 1, 10]
[None, "none", "default", "lz4", "lz4hc", "zstd"], [None, 1, 5, 9], [None, -1, 1, 10]
):
if level is not None and compression not in {"lz4hc", "zstd"}:
with pytest.raises(TypeError, match="level argument"):
Expand Down Expand Up @@ -4393,3 +4393,9 @@ def test_power(A):
B = A[:2, :3].new()
with pytest.raises(DimensionMismatch):
B.power(2)


def test_setting_orientation(A):
A = gb.Matrix.from_csc([0, 2, 3, 3, 5], [1, 3, 7, 6, 20], [10, 20, 30, 40, 50])
B = A.T.new(order="col")
assert B.ss.orientation == "columnwise"