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import sparse
import pytest
import numpy as np
einsum_cases = [
"a,->a",
"ab,->ab",
",ab,->ab",
",,->",
"a,ab,abc->abc",
"a,b,ab->ab",
"ea,fb,gc,hd,abcd->efgh",
"ea,fb,abcd,gc,hd->efgh",
"abcd,ea,fb,gc,hd->efgh",
"acdf,jbje,gihb,hfac,gfac,gifabc,hfac",
"cd,bdhe,aidb,hgca,gc,hgibcd,hgac",
"abhe,hidj,jgba,hiab,gab",
"bde,cdh,agdb,hica,ibd,hgicd,hiac",
"chd,bde,agbc,hiad,hgc,hgi,hiad",
"chd,bde,agbc,hiad,bdi,cgh,agdb",
"bdhe,acad,hiab,agac,hibd",
"ab,ab,c->",
"ab,ab,c->c",
"ab,ab,cd,cd->",
"ab,ab,cd,cd->ac",
"ab,ab,cd,cd->cd",
"ab,ab,cd,cd,ef,ef->",
"ab,cd,ef->abcdef",
"ab,cd,ef->acdf",
"ab,cd,de->abcde",
"ab,cd,de->be",
"ab,bcd,cd->abcd",
"ab,bcd,cd->abd",
"eb,cb,fb->cef",
"dd,fb,be,cdb->cef",
"bca,cdb,dbf,afc->",
"dcc,fce,ea,dbf->ab",
"fdf,cdd,ccd,afe->ae",
"abcd,ad",
"ed,fcd,ff,bcf->be",
"baa,dcf,af,cde->be",
"bd,db,eac->ace",
"fff,fae,bef,def->abd",
"efc,dbc,acf,fd->abe",
"ab,ab",
"ab,ba",
"abc,abc",
"abc,bac",
"abc,cba",
"ab,bc",
"ab,cb",
"ba,bc",
"ba,cb",
"abcd,cd",
"abcd,ab",
"abcd,cdef",
"abcd,cdef->feba",
"abcd,efdc",
"aab,bc->ac",
"ab,bcc->ac",
"aab,bcc->ac",
"baa,bcc->ac",
"aab,ccb->ac",
"aab,fa,df,ecc->bde",
"ecb,fef,bad,ed->ac",
"bcf,bbb,fbf,fc->",
"bb,ff,be->e",
"bcb,bb,fc,fff->",
"fbb,dfd,fc,fc->",
"afd,ba,cc,dc->bf",
"adb,bc,fa,cfc->d",
"bbd,bda,fc,db->acf",
"dba,ead,cad->bce",
"aef,fbc,dca->bde",
"abab->ba",
"...ab,...ab",
"...ab,...b->...a",
"a...,a...",
"a...,a...",
]
@pytest.mark.parametrize("subscripts", einsum_cases)
@pytest.mark.parametrize("density", [0.1, 1.0])
def test_einsum(subscripts, density):
d = 4
terms = subscripts.split("->")[0].split(",")
arrays = [sparse.random((d,) * len(term), density=density) for term in terms]
sparse_out = sparse.einsum(subscripts, *arrays)
numpy_out = np.einsum(subscripts, *(s.todense() for s in arrays))
if not numpy_out.shape:
# scalar output
assert np.allclose(numpy_out, sparse_out)
else:
# array output
assert np.allclose(numpy_out, sparse_out.todense())
@pytest.mark.parametrize("input", [[[0, 0]], [[0, Ellipsis]], [[Ellipsis, 1], [Ellipsis]], [[0, 1], [0]]])
@pytest.mark.parametrize("density", [0.1, 1.0])
def test_einsum_nosubscript(input, density):
d = 4
arrays = [sparse.random((d, d), density=density)]
sparse_out = sparse.einsum(*arrays, *input)
numpy_out = np.einsum(*(s.todense() for s in arrays), *input)
if not numpy_out.shape:
# scalar output
assert np.allclose(numpy_out, sparse_out)
else:
# array output
assert np.allclose(numpy_out, sparse_out.todense())
def test_einsum_input_fill_value():
x = sparse.random(shape=(2,), density=0.5, format="coo", fill_value=2)
with pytest.raises(ValueError):
sparse.einsum("cba", x)
def test_einsum_no_input():
with pytest.raises(ValueError):
sparse.einsum()
@pytest.mark.parametrize("subscript", ["a+b->c", "i->&", "i->ij", "ij->jij", "a..,a...", ".i...", "a,a->->"])
def test_einsum_invalid_input(subscript):
x = sparse.random(shape=(2,), density=0.5, format="coo")
y = sparse.random(shape=(2,), density=0.5, format="coo")
with pytest.raises(ValueError):
sparse.einsum(subscript, x, y)
@pytest.mark.parametrize("subscript", [0, [0, 0]])
def test_einsum_type_error(subscript):
x = sparse.random(shape=(2,), density=0.5, format="coo")
y = sparse.random(shape=(2,), density=0.5, format="coo")
with pytest.raises(TypeError):
sparse.einsum(subscript, x, y)
format_test_cases = [
(("coo",), "coo"),
(("dok",), "dok"),
(("gcxs",), "gcxs"),
(("dense",), "dense"),
(("coo", "coo"), "coo"),
(("dok", "coo"), "coo"),
(("coo", "dok"), "coo"),
(("coo", "dense"), "coo"),
(("dense", "coo"), "coo"),
(("dok", "dense"), "dok"),
(("dense", "dok"), "dok"),
(("gcxs", "dense"), "gcxs"),
(("dense", "gcxs"), "gcxs"),
(("dense", "dense"), "dense"),
(("dense", "dok", "gcxs"), "coo"),
]
@pytest.mark.parametrize("formats,expected", format_test_cases)
def test_einsum_format(formats, expected, rng):
inputs = [
rng.standard_normal((2, 2, 2)) if format == "dense" else sparse.random((2, 2, 2), density=0.5, format=format)
for format in formats
]
if len(inputs) == 1:
eq = "abc->bc"
elif len(inputs) == 2:
eq = "abc,cda->abd"
elif len(inputs) == 3:
eq = "abc,cad,dea->abe"
out = sparse.einsum(eq, *inputs)
assert {
sparse.COO: "coo",
sparse.DOK: "dok",
sparse.GCXS: "gcxs",
np.ndarray: "dense",
}[out.__class__] == expected
def test_einsum_shape_check():
x = sparse.random((2, 3, 4), density=0.5)
with pytest.raises(ValueError):
sparse.einsum("aab", x)
y = sparse.random((2, 3, 4), density=0.5)
with pytest.raises(ValueError):
sparse.einsum("abc,acb", x, y)
@pytest.mark.parametrize("dtype", [np.int64, np.complex128])
def test_einsum_dtype(dtype):
x = sparse.random((3, 3), density=0.5) * 10.0
x = x.astype(np.float64)
y = sparse.COO.from_numpy(np.ones((3, 1), dtype=np.float64))
result = sparse.einsum("ij,i->j", x, y, dtype=dtype)
assert result.dtype == dtype
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