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RF+TST: make big_bad_ulp less likely to / 0 error #130

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Merged
merged 1 commit into from
Jun 9, 2012
Merged

RF+TST: make big_bad_ulp less likely to / 0 error #130

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24 changes: 21 additions & 3 deletions nibabel/tests/test_round_trip.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,8 @@

from nose.tools import assert_true

from numpy.testing import assert_array_equal, assert_almost_equal

DEBUG = True

def round_trip(arr, out_dtype):
Expand Down Expand Up @@ -48,6 +50,8 @@ def big_bad_ulp(arr):
I haven't thought about whether the vectorized log2 here could lead to
incorrect rounding; this only needs to be ballpark

This function might be used in nipy/io/tests/test_image_io.py

Parameters
----------
arr : array
Expand All @@ -60,15 +64,29 @@ def big_bad_ulp(arr):
"""
# Assumes array is floating point
arr = np.asarray(arr)
info = type_info(arr.dtype)
working_arr = np.abs(arr.astype(BFT))
# Log2 for numpy < 1.3
l2 = np.log(working_arr) / LOGe2
fl2 = np.floor(l2)
info = type_info(arr.dtype)
fl2 = np.zeros_like(working_arr) + info['minexp']
# Avoid divide by zero error for log of 0
nzs = working_arr > 0
fl2[nzs] = np.floor(np.log(working_arr[nzs]) / LOGe2)
fl2 = np.clip(fl2, info['minexp'], np.inf)
return 2**(fl2 - info['nmant'])


def test_big_bad_ulp():
for ftype in (np.float32, np.float64):
ti = type_info(ftype)
fi = np.finfo(ftype)
min_ulp = 2 ** (ti['minexp'] - ti['nmant'])
in_arr = np.zeros((10,), dtype=ftype)
in_arr = np.array([0, 0, 1, 2, 4, 5, -5, -np.inf, np.inf], dtype=ftype)
out_arr = [min_ulp, min_ulp, fi.eps, fi.eps * 2, fi.eps * 4,
fi.eps * 4, fi.eps * 4, np.inf, np.inf]
assert_array_equal(big_bad_ulp(in_arr), out_arr)


BIG_FLOAT = np.float64

def test_round_trip():
Expand Down