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Merged
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Jul 30, 2019
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Implementation of np.corrcoef #1071

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c2f26d7
here
yjwusf Jul 28, 2019
07a9047
Implementation of np.corrcoef
wyjw Jul 28, 2019
fd68636
Update lax_numpy_test.py
wyjw Jul 28, 2019
9740728
Merge branch 'master' of https://github.com/google/jax into corrcoef
yjwusf Jul 29, 2019
d9b7c5f
made changes to corrcoef
yjwusf Jul 29, 2019
e2bb9e3
here
yjwusf Jul 29, 2019
3b6edbb
corrcoef
yjwusf Jul 29, 2019
9856375
Merge pull request #1 from wyjw/corrcoef
wyjw Jul 29, 2019
a87627b
Revert "Corrcoef"
wyjw Jul 29, 2019
a106b01
Merge pull request #2 from wyjw/revert-1-corrcoef
wyjw Jul 29, 2019
740ba31
Accidental mistake when reverting.
wyjw Jul 29, 2019
4b42bbc
Update pxla.py
wyjw Jul 29, 2019
4e65c61
Update pxla.py
wyjw Jul 29, 2019
a06883d
Made changes based on review.
wyjw Jul 29, 2019
5487c78
added shape check
wyjw Jul 29, 2019
b89e5a7
shape_c variable taken out
wyjw Jul 29, 2019
ea8597e
Update lax_numpy_test.py
wyjw Jul 29, 2019
22a6aaf
make test more robust
wyjw Jul 29, 2019
5b75a7c
Update lax_numpy_test.py
wyjw Jul 29, 2019
4dcae5d
Update lax_numpy.py
wyjw Jul 30, 2019
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19 changes: 19 additions & 0 deletions jax/numpy/lax_numpy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2625,6 +2625,25 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None,
return true_divide(dot(X, X_T.conj()), f).squeeze()


@_wraps(onp.corrcoef)
def corrcoef(x, y=None, rowvar=True, bias=None, ddof=None):
c = cov(x, y, rowvar)
if len(shape(c)) == 0:
# scalar - this should yield nan for values (nan/nan, inf/inf, 0/0), 1 otherwise
return divide(c, c)
d = diag(c)
stddev = sqrt(real(d))
c = divide(c, stddev[:,None])
c = divide(c, stddev[None,:])

real_part = clip(real(c), -1, 1)
if iscomplexobj(c):
complex_part = clip(imag(c), -1, 1)
c = lax.complex(real_part, complex_part)
else:
c = real_part
return c

@_wraps(getattr(onp, "quantile", None))
def quantile(a, q, axis=None, out=None, overwrite_input=False,
interpolation="linear", keepdims=False):
Expand Down
21 changes: 21 additions & 0 deletions tests/lax_numpy_test.py
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Expand Up @@ -1761,5 +1761,26 @@ def testCov(self, shape, dtype, rowvar, ddof, bias, rng):
def testIssue967(self):
self.assertRaises(TypeError, lambda: lnp.zeros(1.5))

@parameterized.named_parameters(
jtu.cases_from_list(
{"testcase_name": "_shape={}_dtype={}_rowvar={}_ddof={}_bias={}".format(
shape, dtype, rowvar, ddof, bias),
"shape":shape, "dtype":dtype, "rowvar":rowvar, "ddof":ddof,
"bias":bias, "rng": rng}
for shape in [(5,), (10, 5), (3, 10)]
for dtype in number_dtypes
for rowvar in [True, False]
for bias in [True, False]
for ddof in [None, 2, 3]
for rng in [jtu.rand_default()]))
def testCorrCoef(self, shape, dtype, rowvar, ddof, bias, rng):
args_maker = self._GetArgsMaker(rng, [shape], [dtype])
mat = onp.asarray([rng(shape, dtype)])
onp_fun = partial(onp.corrcoef, rowvar=rowvar, ddof=ddof, bias=bias)
lnp_fun = partial(lnp.corrcoef, rowvar=rowvar, ddof=ddof, bias=bias)
if not onp.any(onp.isclose(onp.std(mat), 0.0)):
self._CheckAgainstNumpy(onp_fun, lnp_fun, args_maker, check_dtypes=True)
self._CompileAndCheck(lnp_fun, args_maker, check_dtypes=True)

if __name__ == "__main__":
absltest.main()