10000 ENH/BUG: Allow multinomial to check pvals with other float types by bashtage · Pull Request #16732 · numpy/numpy · GitHub
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ENH/BUG: Allow multinomial to check pvals with other float types #16732

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ENH/BUG: Allow multinomial to check pvals with other float types #16732

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c1e3e11
ENH/BUG: Allow multinomial to check pvals with other float types
bashtage Jul 2, 2020
9a8e3fc
BUG/ENH: Use a kahan-based approach to handle float32
bashtage Jul 2, 2020
359d04f
ENH: Improve error message in multinomial
bashtage Jul 2, 2020
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13 changes: 12 additions & 1 deletion numpy/random/_generator.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -3737,7 +3737,18 @@ cdef class Generator:
pix = <double*>np.PyArray_DATA(parr)
check_array_constraint(parr, 'pvals', CONS_BOUNDED_0_1)
if kahan_sum(pix, d-1) > (1.0 + 1e-12):
raise ValueError("sum(pvals[:-1]) > 1.0")
msg = "sum(pvals[:-1]) > 1.0"
# When floating, but not float dtype, and close, improve the error
# 1.0001 works for float16 and float32
if (isinstance(pvals, np.ndarray) and
pvals.dtype != float and
np.issubdtype(pvals.dtype, np.floating) and
pvals.sum() < 1.0001):
msg += (". pvals has been cast to double before checking "
"the sum. Changes in precision when casting may "
"produce violations even if pvals.sum() <= 1 when "
"evaluated in its original dtype.")
raise ValueError(msg)

if np.PyArray_NDIM(on) != 0: # vector
check_array_constraint(on, 'n', CONS_NON_NEGATIVE)
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8 changes: 8 additions & 0 deletions numpy/random/tests/test_generator_mt19937.py
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Expand Up @@ -142,6 +142,14 @@ def test_multidimensional_pvals(self):
assert_raises(ValueError, random.multinomial, 10, [[[0], [1]], [[1], [0]]])
assert_raises(ValueError, random.multinomial, 10, np.array([[0, 1], [1, 0]]))

def test_multinomial_pvals_float32(self):
x = np.array([9.9e-01, 9.9e-01, 1.0e-09, 1.0e-09, 1.0e-09, 1.0e-09,
1.0e-09, 1.0e-09, 1.0e-09, 1.0e-09], dtype=np.float32)
pvals = x / x.sum()
random = Generator(MT19937(1432985819))
match = r"[\w\s]*pvals has been cast to double"
with pytest.raises(ValueError, match=match):
random.multinomial(1, pvals)

class TestMultivariateHypergeometric:

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