diff options
Diffstat (limited to 'numpy/testing/utils.py')
| -rw-r--r-- | numpy/testing/utils.py | 35 |
1 files changed, 2 insertions, 33 deletions
diff --git a/numpy/testing/utils.py b/numpy/testing/utils.py index 0cd8ccada..7009d532c 100644 --- a/numpy/testing/utils.py +++ b/numpy/testing/utils.py @@ -14,7 +14,7 @@ __all__ = ['assert_equal', 'assert_almost_equal','assert_approx_equal', 'assert_array_almost_equal', 'assert_raises', 'build_err_msg', 'decorate_methods', 'jiffies', 'memusage', 'print_assert_equal', 'raises', 'rand', 'rundocs', 'runstring', 'verbose', 'measure', - 'assert_', 'spacing', 'assert_array_almost_equal_nulp', + 'assert_', 'assert_array_almost_equal_nulp', 'assert_array_max_ulp'] verbose = 0 @@ -1105,7 +1105,7 @@ def assert_array_almost_equal_nulp(x, y, nulp=1): import numpy as np ax = np.abs(x) ay = np.abs(y) - ref = nulp * spacing(np.where(ax > ay, ax, ay)) + ref = nulp * np.spacing(np.where(ax > ay, ax, ay)) if not np.all(np.abs(x-y) <= ref): max_nulp = np.max(nulp_diff(x, y)) raise AssertionError("X and Y are not equal to %d ULP "\ @@ -1196,34 +1196,3 @@ def integer_repr(x): return _integer_repr(x, np.int64, np.int64(-2**63)) else: raise ValueError("Unsupported dtype %s" % x.dtype) - -def spacing(x, dtype=None): - """Return the spacing for each item in x. - - spacing(x) is defined as the space between x and the next representable - floating point number > x. For example, spacing(1) == EPS - - This aims at being equivalent to the Fortran 95 spacing intrinsic. - """ - import numpy as np - if dtype: - x = np.atleast_1d(np.array(x, dtype=dtype)) - else: - x = np.atleast_1d(np.array(x)) - - if np.iscomplexobj(x): - raise NotImplementerError("_compute_spacing not implemented for complex array") - - t = x.dtype - - res = integer_repr(x) - return (res + 1).view(t) - res.view(t) - # XXX: alternative implementation, the one used in gfortran: much simpler, - # but I am not sure I understand it, and it does not work for Nan - #p = np.finfo(t).nmant + 1 - #emin = np.finfo(t).minexp - # - #e = np.frexp(x)[1] - p - #e[e<=emin] = emin - - #return np.ldexp(np.array(1., dtype=t), e) |