def test_nan(self):
# Test that nan is 'far' from small, tiny, inf, max and min
for dt in [np.float32, np.float64]:
if dt == np.float32:
maxulp = 1e6
else:
maxulp = 1e12
inf = np.array([np.inf]).astype(dt)
nan = np.array([np.nan]).astype(dt)
big = np.array([np.finfo(dt).max])
tiny = np.array([np.finfo(dt).tiny])
zero = np.array([np.PZERO]).astype(dt)
nzero = np.array([np.NZERO]).astype(dt)
assert_raises(
AssertionError,
lambda: assert_array_max_ulp(nan, inf, maxulp=maxulp))
assert_raises(
AssertionError,
lambda: assert_array_max_ulp(nan, big, maxulp=maxulp))
assert_raises(
AssertionError,
lambda: assert_array_max_ulp(nan, tiny, maxulp=maxulp))
assert_raises(
AssertionError,
lambda: assert_array_max_ulp(nan, zero, maxulp=maxulp))
assert_raises(
AssertionError,
lambda: assert_array_max_ulp(nan, nzero, maxulp=maxulp))
def test_complex64_fail(self):
nulp = 5
x = np.linspace(-20, 20, 50, dtype=np.float32)
x = 10**x
x = np.r_[-x, x]
xi = x + x * 1j
eps = np.finfo(x.dtype).eps
y = x + x * eps * nulp * 2.
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
x + y * 1j, nulp)
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + x * 1j, nulp)
y = x + x * eps * nulp
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + y * 1j, nulp)
epsneg = np.finfo(x.dtype).epsneg
y = x - x * epsneg * nulp * 2.
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
x + y * 1j, nulp)
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + x * 1j, nulp)
y = x - x * epsneg * nulp
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + y * 1j, nulp)
def test_complex128_fail(self):
nulp = 5
x = np.linspace(-20, 20, 50, dtype=np.float64)
x = 10**x
x = np.r_[-x, x]
xi = x + x * 1j
eps = np.finfo(x.dtype).eps
y = x + x * eps * nulp * 2.
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
x + y * 1j, nulp)
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + x * 1j, nulp)
# The test condition needs to be at least a factor of sqrt(2) smaller
# because the real and imaginary parts both change
y = x + x * eps * nulp
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + y * 1j, nulp)
epsneg = np.finfo(x.dtype).epsneg
y = x - x * epsneg * nulp * 2.
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
x + y * 1j, nulp)
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + x * 1j, nulp)
y = x - x * epsneg * nulp
assert_raises(AssertionError, assert_array_almost_equal_nulp, xi,
y + y * 1j, nulp)
def test_float16_pass(self):
nulp = 5
x = np.linspace(-4, 4, 10, dtype=np.float16)
x = 10**x
x = np.r_[-x, x]
eps = np.finfo(x.dtype).eps
y = x + x * eps * nulp / 2.
assert_array_almost_equal_nulp(x, y, nulp)
epsneg = np.finfo(x.dtype).epsneg
y = x - x * epsneg * nulp / 2.
assert_array_almost_equal_nulp(x, y, nulp)
def test_float16_fail(self):
nulp = 5
x = np.linspace(-4, 4, 10, dtype=np.float16)
x = 10**x
x = np.r_[-x, x]
eps = np.finfo(x.dtype).eps
y = x + x * eps * nulp * 2.
assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y,
nulp)
epsneg = np.finfo(x.dtype).epsneg
y = x - x * epsneg * nulp * 2.
assert_raises(AssertionError, assert_array_almost_equal_nulp, x, y,
nulp)
def test_plausible_finfo():
# Assert that finfo returns reasonable results for all types
for ftype in np.sctypes['float'] + np.sctypes['complex']:
info = np.finfo(ftype)
assert_(info.nmant > 1)
assert_(info.minexp < -1)
assert_(info.maxexp > 1)
def test_int_from_huge_longdouble(self):
# Produce a longdouble that would overflow a double,
# use exponent that avoids bug in Darwin pow function.
exp = np.finfo(np.double).maxexp - 1
huge_ld = 2 * 1234 * np.longdouble(2)**exp
huge_i = 2 * 1234 * 2**exp
assert_(huge_ld != np.inf)
assert_equal(int(huge_ld), huge_i)
def test_float64_pass(self):
# The number of units of least precision
# In this case, use a few places above the lowest level (ie nulp=1)
nulp = 5
x = np.linspace(-20, 20, 50, dtype=np.float64)
x = 10**x
x = np.r_[-x, x]
# Addition
eps = np.finfo(x.dtype).eps
y = x + x * eps * nulp / 2.
assert_array_almost_equal_nulp(x, y, nulp)
# Subtraction
epsneg = np.finfo(x.dtype).epsneg
y = x - x * epsneg * nulp / 2.
assert_array_almost_equal_nulp(x, y, nulp)
def _test_abs_func(self, absfunc):
for tp in floating_types + complex_floating_types:
x = tp(-1.5)
assert_equal(absfunc(x), 1.5)
x = tp(0.0)
res = absfunc(x)
# assert_equal() checks zero signedness
assert_equal(res, 0.0)
x = tp(-0.0)
res = absfunc(x)
assert_equal(res, 0.0)
x = tp(np.finfo(tp).max)
assert_equal(absfunc(x), x.real)
x = tp(np.finfo(tp).tiny)
assert_equal(absfunc(x), x.real)
x = tp(np.finfo(tp).min)
assert_equal(absfunc(x), -x.real)
def test_complex64_pass(self):
nulp = 5
x = np.linspace(-20, 20, 50, dtype=np.float32)
x = 10**x
x = np.r_[-x, x]
xi = x + x * 1j
eps = np.finfo(x.dtype).eps
y = x + x * eps * nulp / 2.
assert_array_almost_equal_nulp(xi, x + y * 1j, nulp)
assert_array_almost_equal_nulp(xi, y + x * 1j, nulp)
y = x + x * eps * nulp / 4.
assert_array_almost_equal_nulp(xi, y + y * 1j, nulp)
epsneg = np.finfo(x.dtype).epsneg
y = x - x * epsneg * nulp / 2.
assert_array_almost_equal_nulp(xi, x + y * 1j, nulp)
assert_array_almost_equal_nulp(xi, y + x * 1j, nulp)
y = x - x * epsneg * nulp / 4.
assert_array_almost_equal_nulp(xi, y + y * 1j, nulp)
def do_precision_upper_bound(self, float_small, float_large):
eps = np.finfo(float_large).eps
arr = np.array([1.0], float_small)
range = np.array([0.0, 1.0 - eps], float_large)
# test is looking for behavior when the bounds change between dtypes
if range.astype(float_small)[-1] != 1:
return
# previously crashed
count, x_loc = np.histogram(arr, bins=1, range=range)
assert_equal(count, [1])
# gh-10322 means that the type comes from arr - this may change
assert_equal(x_loc.dtype, float_small)
def _test_type_repr(self, t):
finfo = np.finfo(t)
last_fraction_bit_idx = finfo.nexp + finfo.nmant
last_exponent_bit_idx = finfo.nexp
storage_bytes = np.dtype(t).itemsize * 8
# could add some more types to the list below
for which in ['small denorm', 'small norm']:
# Values from http://en.wikipedia.org/wiki/IEEE_754
constr = np.array([0x00] * storage_bytes, dtype=np.uint8)
if which == 'small denorm':
byte = last_fraction_bit_idx // 8
bytebit = 7 - (last_fraction_bit_idx % 8)
constr[byte] = 1 << bytebit
elif which == 'small norm':
byte = last_exponent_bit_idx // 8
bytebit = 7 - (last_exponent_bit_idx % 8)
constr[byte] = 1 << bytebit
else:
raise ValueError('hmm')
val = constr.view(t)[0]
val_repr = repr(val)
val2 = t(eval(val_repr))
if not (val2 == 0 and val < 1e-100):
assert_equal(val, val2)
def test_dragon4(self):
# these tests are adapted from Ryan Juckett's dragon4 implementation,
# see dragon4.c for details.
fpos32 = lambda x, **k: np.format_float_positional(np.float32(x), **k)
fsci32 = lambda x, **k: np.format_float_scientific(np.float32(x), **k)
fpos64 = lambda x, **k: np.format_float_positional(np.float64(x), **k)
fsci64 = lambda x, **k: np.format_float_scientific(np.float64(x), **k)
preckwd = lambda prec: {'unique': False, 'precision': prec}
assert_equal(fpos32('1.0'), "1.")
assert_equal(fsci32('1.0'), "1.e+00")
assert_equal(fpos32('10.234'), "10.234")
assert_equal(fpos32('-10.234'), "-10.234")
assert_equal(fsci32('10.234'), "1.0234e+01")
assert_equal(fsci32('-10.234'), "-1.0234e+01")
assert_equal(fpos32('1000.0'), "1000.")
assert_equal(fpos32('1.0', precision=0), "1.")
assert_equal(fsci32('1.0', precision=0), "1.e+00")
assert_equal(fpos32('10.234', precision=0), "10.")
assert_equal(fpos32('-10.234', precision=0), "-10.")
assert_equal(fsci32('10.234', precision=0), "1.e+01")
assert_equal(fsci32('-10.234', precision=0), "-1.e+01")
assert_equal(fpos32('10.234', precision=2), "10.23")
assert_equal(fsci32('-10.234', precision=2), "-1.02e+01")
assert_equal(fsci64('9.9999999999999995e-08', **preckwd(16)),
'9.9999999999999995e-08')
assert_equal(fsci64('9.8813129168249309e-324', **preckwd(16)),
'9.8813129168249309e-324')
assert_equal(fsci64('9.9999999999999694e-311', **preckwd(16)),
'9.9999999999999694e-311')
# test rounding
# 3.1415927410 is closest float32 to np.pi
assert_equal(fpos32('3.14159265358979323846', **preckwd(10)),
"3.1415927410")
assert_equal(fsci32('3.14159265358979323846', **preckwd(10)),
"3.1415927410e+00")
assert_equal(fpos64('3.14159265358979323846', **preckwd(10)),
"3.1415926536")
assert_equal(fsci64('3.14159265358979323846', **preckwd(10)),
"3.1415926536e+00")
# 299792448 is closest float32 to 299792458
assert_equal(fpos32('299792458.0', **preckwd(5)), "299792448.00000")
assert_equal(fsci32('299792458.0', **preckwd(5)), "2.99792e+08")
assert_equal(fpos64('299792458.0', **preckwd(5)), "299792458.00000")
assert_equal(fsci64('299792458.0', **preckwd(5)), "2.99792e+08")
assert_equal(fpos32('3.14159265358979323846', **preckwd(25)),
"3.1415927410125732421875000")
assert_equal(fpos64('3.14159265358979323846', **preckwd(50)),
"3.14159265358979311599796346854418516159057617187500")
assert_equal(fpos64('3.14159265358979323846'), "3.141592653589793")
# smallest numbers
assert_equal(
fpos32(0.5**(126 + 23), unique=False, precision=149),
"0.00000000000000000000000000000000000000000000140129846432"
"4817070923729583289916131280261941876515771757068283889791"
"08268586060148663818836212158203125")
assert_equal(
fpos64(0.5**(1022 + 52), unique=False, precision=1074),
"0.00000000000000000000000000000000000000000000000000000000"
"0000000000000000000000000000000000000000000000000000000000"
"0000000000000000000000000000000000000000000000000000000000"
"0000000000000000000000000000000000000000000000000000000000"
"0000000000000000000000000000000000000000000000000000000000"
"0000000000000000000000000000000000049406564584124654417656"
"8792868221372365059802614324764425585682500675507270208751"
"8652998363616359923797965646954457177309266567103559397963"
"9877479601078187812630071319031140452784581716784898210368"
"8718636056998730723050006387409153564984387312473397273169"
"6151400317153853980741262385655911710266585566867681870395"
"6031062493194527159149245532930545654440112748012970999954"
"1931989409080416563324524757147869014726780159355238611550"
"1348035264934720193790268107107491703332226844753335720832"
"4319360923828934583680601060115061698097530783422773183292"
"4790498252473077637592724787465608477820373446969953364701"
"7972677717585125660551199131504891101451037862738167250955"
"8373897335989936648099411642057026370902792427675445652290"
"87538682506419718265533447265625")
# largest numbers
assert_equal(fpos32(np.finfo(np.float32).max, **preckwd(0)),
"340282346638528859811704183484516925440.")
assert_equal(
fpos64(np.finfo(np.float64).max, **preckwd(0)),
"1797693134862315708145274237317043567980705675258449965989"
"1747680315726078002853876058955863276687817154045895351438"
"2464234321326889464182768467546703537516986049910576551282"
"0762454900903893289440758685084551339423045832369032229481"
"6580855933212334827479782620414472316873817718091929988125"
"0404026184124858368.")
# Warning: In unique mode only the integer digits necessary for
# uniqueness are computed, the rest are 0. Should we change this?
assert_equal(fpos32(np.finfo(np.float32).max, precision=0),
"340282350000000000000000000000000000000.")
# test trailing zeros
assert_equal(fpos32('1.0', unique=False, precision=3), "1.000")
assert_equal(fpos64('1.0', unique=False, precision=3), "1.000")
assert_equal(fsci32('1.0', unique=False, precision=3), "1.000e+00")
assert_equal(fsci64('1.0', unique=False, precision=3), "1.000e+00")
assert_equal(fpos32('1.5', unique=False, precision=3), "1.500")
assert_equal(fpos64('1.5', unique=False, precision=3), "1.500")
assert_equal(fsci32('1.5', unique=False, precision=3), "1.500e+00")
assert_equal(fsci64('1.5', unique=False, precision=3), "1.500e+00")
# gh-10713
assert_equal(
fpos64('324', unique=False, precision=5, fractional=False),
"324.00")
def test_double(self):
# Generate 1 + small deviation, check that adding eps gives a few UNL
x = np.ones(10).astype(np.float64)
x += 0.01 * np.random.randn(10).astype(np.float64)
eps = np.finfo(np.float64).eps
assert_array_max_ulp(x, x + eps, maxulp=200)
def test_finfo_repr(self):
expected = "finfo(resolution=1e-06, min=-3.4028235e+38," + \
" max=3.4028235e+38, dtype=float32)"
assert_equal(repr(np.finfo(np.float32)), expected)
class TestConversion(object):
def test_int_from_long(self):
l = [1e6, 1e12, 1e18, -1e6, -1e12, -1e18]
li = [10**6, 10**12, 10**18, -10**6, -10**12, -10**18]
for T in [None, np.float64, np.int64]:
a = np.array(l, dtype=T)
assert_equal([int(_m) for _m in a], li)
a = np.array(l[:3], dtype=np.uint64)
assert_equal([int(_m) for _m in a], li[:3])
def test_iinfo_long_values(self):
for code in 'bBhH':
res = np.array(np.iinfo(code).max + 1, dtype=code)
tgt = np.iinfo(code).min
assert_(res == tgt)
for code in np.typecodes['AllInteger']:
res = np.array(np.iinfo(code).max, dtype=code)
tgt = np.iinfo(code).max
assert_(res == tgt)
for code in np.typecodes['AllInteger']:
res = np.typeDict[code](np.iinfo(code).max)
tgt = np.iinfo(code).max
assert_(res == tgt)
def test_int_raise_behaviour(self):
def overflow_error_func(dtype):
np.typeDict[dtype](np.iinfo(dtype).max + 1)
for code in 'lLqQ':
assert_raises(OverflowError, overflow_error_func, code)
def test_int_from_infinite_longdouble(self):
# gh-627
x = np.longdouble(np.inf)
assert_raises(OverflowError, int, x)
with suppress_warnings() as sup:
sup.record(np.ComplexWarning)
x = np.clongdouble(np.inf)
assert_raises(OverflowError, int, x)
assert_equal(len(sup.log), 1)
@pytest.mark.skipif(not IS_PYPY, reason="Test is PyPy only (gh-9972)")
def test_int_from_infinite_longdouble___int__(self):
x = np.longdouble(np.inf)
assert_raises(OverflowError, x.__int__)
with suppress_warnings() as sup:
sup.record(np.ComplexWarning)
x = np.clongdouble(np.inf)
assert_raises(OverflowError, x.__int__)
assert_equal(len(sup.log), 1)
@pytest.mark.skipif(np.finfo(np.double) == np.finfo(np.longdouble),
reason="long double is same as double")
@pytest.mark.skipif(platform.machine().startswith("ppc64"),
reason="IBM double double")
def test_int_from_huge_longdouble(self):
# Produce a longdouble that would overflow a double,
# use exponent that avoids bug in Darwin pow function.
exp = np.finfo(np.double).maxexp - 1
huge_ld = 2 * 1234 * np.longdouble(2)**exp
huge_i = 2 * 1234 * 2**exp
assert_(huge_ld != np.inf)
assert_equal(int(huge_ld), huge_i)
def test_int_from_longdouble(self):
x = np.longdouble(1.5)
assert_equal(int(x), 1)
x = np.longdouble(-10.5)
assert_equal(int(x), -10)
def test_numpy_scalar_relational_operators(self):
# All integer
for dt1 in np.typecodes['AllInteger']:
assert_(1 > np.array(0, dtype=dt1)[()], "type %s failed" % (dt1, ))
assert_(not 1 < np.array(0, dtype=dt1)[()],
"type %s failed" % (dt1, ))
for dt2 in np.typecodes['AllInteger']:
assert_(
np.array(1, dtype=dt1)[()] > np.array(0, dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
assert_(
not np.array(1, dtype=dt1)[()] < np.array(0,
dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
#Unsigned integers
for dt1 in 'BHILQP':
assert_(-1 < np.array(1, dtype=dt1)[()],
"type %s failed" % (dt1, ))
assert_(not -1 > np.array(1, dtype=dt1)[()],
"type %s failed" % (dt1, ))
assert_(-1 != np.array(1, dtype=dt1)[()],
"type %s failed" % (dt1, ))
#unsigned vs signed
for dt2 in 'bhilqp':
assert_(
np.array(1, dtype=dt1)[()] > np.array(-1, dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
assert_(
not np.array(1, dtype=dt1)[()] < np.array(-1,
dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
assert_(
np.array(1, dtype=dt1)[()] != np.array(-1, dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
#Signed integers and floats
for dt1 in 'bhlqp' + np.typecodes['Float']:
assert_(1 > np.array(-1, dtype=dt1)[()],
"type %s failed" % (dt1, ))
assert_(not 1 < np.array(-1, dtype=dt1)[()],
"type %s failed" % (dt1, ))
assert_(-1 == np.array(-1, dtype=dt1)[()],
"type %s failed" % (dt1, ))
for dt2 in 'bhlqp' + np.typecodes['Float']:
assert_(
np.array(1, dtype=dt1)[()] > np.array(-1, dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
assert_(
not np.array(1, dtype=dt1)[()] < np.array(-1,
dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
assert_(
np.array(-1, dtype=dt1)[()] == np.array(-1, dtype=dt2)[()],
"type %s and %s failed" % (dt1, dt2))
def test_scalar_comparison_to_none(self):
# Scalars should just return False and not give a warnings.
# The comparisons are flagged by pep8, ignore that.
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', FutureWarning)
assert_(not np.float32(1) == None)
assert_(not np.str_('test') == None)
# This is dubious (see below):
assert_(not np.datetime64('NaT') == None)
assert_(np.float32(1) != None)
assert_(np.str_('test') != None)
# This is dubious (see below):
assert_(np.datetime64('NaT') != None)
assert_(len(w) == 0)
# For documentation purposes, this is why the datetime is dubious.
# At the time of deprecation this was no behaviour change, but
# it has to be considered when the deprecations are done.
assert_(np.equal(np.datetime64('NaT'), None))
from __future__ import division, absolute_import, print_function
import pytest
import numpy1 as np
from numpy1.testing import (
assert_,
assert_equal,
assert_raises,
assert_array_equal,
temppath,
)
from numpy1.core.tests._locales import CommaDecimalPointLocale
LD_INFO = np.finfo(np.longdouble)
longdouble_longer_than_double = (LD_INFO.eps < np.finfo(np.double).eps)
_o = 1 + LD_INFO.eps
string_to_longdouble_inaccurate = (_o != np.longdouble(repr(_o)))
del _o
def test_scalar_extraction():
"""Confirm that extracting a value doesn't convert to python float"""
o = 1 + LD_INFO.eps
a = np.array([o, o, o])
assert_equal(a[1], o)
# Conversions string -> long double
def test_inf(self):
for dt in [np.float32, np.float64]:
inf = np.array([np.inf]).astype(dt)
big = np.array([np.finfo(dt).max])
assert_array_max_ulp(inf, big, maxulp=200)