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327 lines
15 KiB
Python
327 lines
15 KiB
Python
# -*- coding: utf-8 -*-
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""" Test printing of scalar types.
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"""
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from __future__ import division, absolute_import, print_function
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import code, sys
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import platform
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import pytest
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from tempfile import TemporaryFile
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import numpy as np
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from numpy.testing import assert_, assert_equal, suppress_warnings
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class TestRealScalars(object):
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def test_str(self):
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svals = [0.0, -0.0, 1, -1, np.inf, -np.inf, np.nan]
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styps = [np.float16, np.float32, np.float64, np.longdouble]
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wanted = [
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['0.0', '0.0', '0.0', '0.0' ],
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['-0.0', '-0.0', '-0.0', '-0.0'],
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['1.0', '1.0', '1.0', '1.0' ],
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['-1.0', '-1.0', '-1.0', '-1.0'],
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['inf', 'inf', 'inf', 'inf' ],
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['-inf', '-inf', '-inf', '-inf'],
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['nan', 'nan', 'nan', 'nan']]
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for wants, val in zip(wanted, svals):
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for want, styp in zip(wants, styps):
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msg = 'for str({}({}))'.format(np.dtype(styp).name, repr(val))
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assert_equal(str(styp(val)), want, err_msg=msg)
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def test_scalar_cutoffs(self):
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# test that both the str and repr of np.float64 behaves
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# like python floats in python3. Note that in python2
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# the str has truncated digits, but we do not do this
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def check(v):
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# we compare str to repr, to avoid python2 truncation behavior
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assert_equal(str(np.float64(v)), repr(v))
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assert_equal(repr(np.float64(v)), repr(v))
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# check we use the same number of significant digits
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check(1.12345678901234567890)
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check(0.0112345678901234567890)
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# check switch from scientific output to positional and back
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check(1e-5)
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check(1e-4)
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check(1e15)
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check(1e16)
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def test_py2_float_print(self):
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# gh-10753
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# In python2, the python float type implements an obsolte method
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# tp_print, which overrides tp_repr and tp_str when using "print" to
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# output to a "real file" (ie, not a StringIO). Make sure we don't
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# inherit it.
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x = np.double(0.1999999999999)
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with TemporaryFile('r+t') as f:
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print(x, file=f)
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f.seek(0)
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output = f.read()
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assert_equal(output, str(x) + '\n')
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# In python2 the value float('0.1999999999999') prints with reduced
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# precision as '0.2', but we want numpy's np.double('0.1999999999999')
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# to print the unique value, '0.1999999999999'.
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# gh-11031
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# Only in the python2 interactive shell and when stdout is a "real"
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# file, the output of the last command is printed to stdout without
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# Py_PRINT_RAW (unlike the print statement) so `>>> x` and `>>> print
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# x` are potentially different. Make sure they are the same. The only
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# way I found to get prompt-like output is using an actual prompt from
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# the 'code' module. Again, must use tempfile to get a "real" file.
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# dummy user-input which enters one line and then ctrl-Ds.
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def userinput():
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yield 'np.sqrt(2)'
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raise EOFError
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gen = userinput()
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input_func = lambda prompt="": next(gen)
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with TemporaryFile('r+t') as fo, TemporaryFile('r+t') as fe:
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orig_stdout, orig_stderr = sys.stdout, sys.stderr
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sys.stdout, sys.stderr = fo, fe
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# py2 code.interact sends irrelevant internal DeprecationWarnings
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with suppress_warnings() as sup:
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sup.filter(DeprecationWarning)
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code.interact(local={'np': np}, readfunc=input_func, banner='')
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sys.stdout, sys.stderr = orig_stdout, orig_stderr
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fo.seek(0)
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capture = fo.read().strip()
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assert_equal(capture, repr(np.sqrt(2)))
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def test_dragon4(self):
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# these tests are adapted from Ryan Juckett's dragon4 implementation,
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# see dragon4.c for details.
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fpos32 = lambda x, **k: np.format_float_positional(np.float32(x), **k)
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fsci32 = lambda x, **k: np.format_float_scientific(np.float32(x), **k)
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fpos64 = lambda x, **k: np.format_float_positional(np.float64(x), **k)
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fsci64 = lambda x, **k: np.format_float_scientific(np.float64(x), **k)
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preckwd = lambda prec: {'unique': False, 'precision': prec}
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assert_equal(fpos32('1.0'), "1.")
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assert_equal(fsci32('1.0'), "1.e+00")
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assert_equal(fpos32('10.234'), "10.234")
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assert_equal(fpos32('-10.234'), "-10.234")
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assert_equal(fsci32('10.234'), "1.0234e+01")
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assert_equal(fsci32('-10.234'), "-1.0234e+01")
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assert_equal(fpos32('1000.0'), "1000.")
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assert_equal(fpos32('1.0', precision=0), "1.")
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assert_equal(fsci32('1.0', precision=0), "1.e+00")
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assert_equal(fpos32('10.234', precision=0), "10.")
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assert_equal(fpos32('-10.234', precision=0), "-10.")
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assert_equal(fsci32('10.234', precision=0), "1.e+01")
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assert_equal(fsci32('-10.234', precision=0), "-1.e+01")
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assert_equal(fpos32('10.234', precision=2), "10.23")
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assert_equal(fsci32('-10.234', precision=2), "-1.02e+01")
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assert_equal(fsci64('9.9999999999999995e-08', **preckwd(16)),
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'9.9999999999999995e-08')
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assert_equal(fsci64('9.8813129168249309e-324', **preckwd(16)),
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'9.8813129168249309e-324')
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assert_equal(fsci64('9.9999999999999694e-311', **preckwd(16)),
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'9.9999999999999694e-311')
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# test rounding
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# 3.1415927410 is closest float32 to np.pi
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assert_equal(fpos32('3.14159265358979323846', **preckwd(10)),
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"3.1415927410")
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assert_equal(fsci32('3.14159265358979323846', **preckwd(10)),
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"3.1415927410e+00")
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assert_equal(fpos64('3.14159265358979323846', **preckwd(10)),
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"3.1415926536")
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assert_equal(fsci64('3.14159265358979323846', **preckwd(10)),
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"3.1415926536e+00")
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# 299792448 is closest float32 to 299792458
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assert_equal(fpos32('299792458.0', **preckwd(5)), "299792448.00000")
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assert_equal(fsci32('299792458.0', **preckwd(5)), "2.99792e+08")
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assert_equal(fpos64('299792458.0', **preckwd(5)), "299792458.00000")
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assert_equal(fsci64('299792458.0', **preckwd(5)), "2.99792e+08")
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assert_equal(fpos32('3.14159265358979323846', **preckwd(25)),
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"3.1415927410125732421875000")
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assert_equal(fpos64('3.14159265358979323846', **preckwd(50)),
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"3.14159265358979311599796346854418516159057617187500")
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assert_equal(fpos64('3.14159265358979323846'), "3.141592653589793")
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# smallest numbers
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assert_equal(fpos32(0.5**(126 + 23), unique=False, precision=149),
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"0.00000000000000000000000000000000000000000000140129846432"
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"4817070923729583289916131280261941876515771757068283889791"
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"08268586060148663818836212158203125")
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assert_equal(fpos64(0.5**(1022 + 52), unique=False, precision=1074),
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"0.00000000000000000000000000000000000000000000000000000000"
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"0000000000000000000000000000000000000000000000000000000000"
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"0000000000000000000000000000000000000000000000000000000000"
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"0000000000000000000000000000000000000000000000000000000000"
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"0000000000000000000000000000000000000000000000000000000000"
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"0000000000000000000000000000000000049406564584124654417656"
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"8792868221372365059802614324764425585682500675507270208751"
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"8652998363616359923797965646954457177309266567103559397963"
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"9877479601078187812630071319031140452784581716784898210368"
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"8718636056998730723050006387409153564984387312473397273169"
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"6151400317153853980741262385655911710266585566867681870395"
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"6031062493194527159149245532930545654440112748012970999954"
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"1931989409080416563324524757147869014726780159355238611550"
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"1348035264934720193790268107107491703332226844753335720832"
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"4319360923828934583680601060115061698097530783422773183292"
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"4790498252473077637592724787465608477820373446969953364701"
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"7972677717585125660551199131504891101451037862738167250955"
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"8373897335989936648099411642057026370902792427675445652290"
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"87538682506419718265533447265625")
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# largest numbers
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assert_equal(fpos32(np.finfo(np.float32).max, **preckwd(0)),
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"340282346638528859811704183484516925440.")
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assert_equal(fpos64(np.finfo(np.float64).max, **preckwd(0)),
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"1797693134862315708145274237317043567980705675258449965989"
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"1747680315726078002853876058955863276687817154045895351438"
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"2464234321326889464182768467546703537516986049910576551282"
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"0762454900903893289440758685084551339423045832369032229481"
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"6580855933212334827479782620414472316873817718091929988125"
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"0404026184124858368.")
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# Warning: In unique mode only the integer digits necessary for
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# uniqueness are computed, the rest are 0. Should we change this?
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assert_equal(fpos32(np.finfo(np.float32).max, precision=0),
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"340282350000000000000000000000000000000.")
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# test trailing zeros
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assert_equal(fpos32('1.0', unique=False, precision=3), "1.000")
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assert_equal(fpos64('1.0', unique=False, precision=3), "1.000")
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assert_equal(fsci32('1.0', unique=False, precision=3), "1.000e+00")
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assert_equal(fsci64('1.0', unique=False, precision=3), "1.000e+00")
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assert_equal(fpos32('1.5', unique=False, precision=3), "1.500")
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assert_equal(fpos64('1.5', unique=False, precision=3), "1.500")
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assert_equal(fsci32('1.5', unique=False, precision=3), "1.500e+00")
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assert_equal(fsci64('1.5', unique=False, precision=3), "1.500e+00")
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# gh-10713
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assert_equal(fpos64('324', unique=False, precision=5, fractional=False), "324.00")
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def test_dragon4_interface(self):
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tps = [np.float16, np.float32, np.float64]
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if hasattr(np, 'float128'):
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tps.append(np.float128)
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fpos = np.format_float_positional
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fsci = np.format_float_scientific
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for tp in tps:
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# test padding
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assert_equal(fpos(tp('1.0'), pad_left=4, pad_right=4), " 1. ")
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assert_equal(fpos(tp('-1.0'), pad_left=4, pad_right=4), " -1. ")
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assert_equal(fpos(tp('-10.2'),
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pad_left=4, pad_right=4), " -10.2 ")
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# test exp_digits
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assert_equal(fsci(tp('1.23e1'), exp_digits=5), "1.23e+00001")
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# test fixed (non-unique) mode
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assert_equal(fpos(tp('1.0'), unique=False, precision=4), "1.0000")
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assert_equal(fsci(tp('1.0'), unique=False, precision=4),
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"1.0000e+00")
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# test trimming
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# trim of 'k' or '.' only affects non-unique mode, since unique
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# mode will not output trailing 0s.
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assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='k'),
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"1.0000")
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assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='.'),
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"1.")
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assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='.'),
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"1.2" if tp != np.float16 else "1.2002")
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assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='0'),
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"1.0")
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assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='0'),
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"1.2" if tp != np.float16 else "1.2002")
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assert_equal(fpos(tp('1.'), trim='0'), "1.0")
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assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='-'),
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"1")
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assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='-'),
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"1.2" if tp != np.float16 else "1.2002")
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assert_equal(fpos(tp('1.'), trim='-'), "1")
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@pytest.mark.skipif(not platform.machine().startswith("ppc64"),
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reason="only applies to ppc float128 values")
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def test_ppc64_ibm_double_double128(self):
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# check that the precision decreases once we get into the subnormal
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# range. Unlike float64, this starts around 1e-292 instead of 1e-308,
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# which happens when the first double is normal and the second is
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# subnormal.
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x = np.float128('2.123123123123123123123123123123123e-286')
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got = [str(x/np.float128('2e' + str(i))) for i in range(0,40)]
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expected = [
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"1.06156156156156156156156156156157e-286",
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"1.06156156156156156156156156156158e-287",
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"1.06156156156156156156156156156159e-288",
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"1.0615615615615615615615615615616e-289",
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"1.06156156156156156156156156156157e-290",
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"1.06156156156156156156156156156156e-291",
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"1.0615615615615615615615615615616e-292",
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"1.0615615615615615615615615615615e-293",
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"1.061561561561561561561561561562e-294",
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"1.06156156156156156156156156155e-295",
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"1.0615615615615615615615615616e-296",
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"1.06156156156156156156156156e-297",
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"1.06156156156156156156156157e-298",
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"1.0615615615615615615615616e-299",
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"1.06156156156156156156156e-300",
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"1.06156156156156156156155e-301",
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"1.0615615615615615615616e-302",
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"1.061561561561561561562e-303",
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"1.06156156156156156156e-304",
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"1.0615615615615615618e-305",
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"1.06156156156156156e-306",
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"1.06156156156156157e-307",
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"1.0615615615615616e-308",
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"1.06156156156156e-309",
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"1.06156156156157e-310",
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"1.0615615615616e-311",
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"1.06156156156e-312",
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"1.06156156154e-313",
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"1.0615615616e-314",
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"1.06156156e-315",
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"1.06156155e-316",
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"1.061562e-317",
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"1.06156e-318",
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"1.06155e-319",
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"1.0617e-320",
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"1.06e-321",
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"1.04e-322",
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"1e-323",
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"0.0",
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"0.0"]
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assert_equal(got, expected)
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# Note: we follow glibc behavior, but it (or gcc) might not be right.
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# In particular we can get two values that print the same but are not
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# equal:
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a = np.float128('2')/np.float128('3')
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b = np.float128(str(a))
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assert_equal(str(a), str(b))
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assert_(a != b)
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def float32_roundtrip(self):
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# gh-9360
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x = np.float32(1024 - 2**-14)
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y = np.float32(1024 - 2**-13)
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assert_(repr(x) != repr(y))
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assert_equal(np.float32(repr(x)), x)
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assert_equal(np.float32(repr(y)), y)
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def float64_vs_python(self):
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# gh-2643, gh-6136, gh-6908
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assert_equal(repr(np.float64(0.1)), repr(0.1))
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assert_(repr(np.float64(0.20000000000000004)) != repr(0.2))
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