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+""" Test printing of scalar types.
+
+"""
+import code
+import platform
+import pytest
+import sys
+
+from tempfile import TemporaryFile
+import numpy as np
+from numpy.testing import assert_, assert_equal, assert_raises, IS_MUSL
+
+class TestRealScalars:
+ def test_str(self):
+ svals = [0.0, -0.0, 1, -1, np.inf, -np.inf, np.nan]
+ styps = [np.float16, np.float32, np.float64, np.longdouble]
+ wanted = [
+ ['0.0', '0.0', '0.0', '0.0' ],
+ ['-0.0', '-0.0', '-0.0', '-0.0'],
+ ['1.0', '1.0', '1.0', '1.0' ],
+ ['-1.0', '-1.0', '-1.0', '-1.0'],
+ ['inf', 'inf', 'inf', 'inf' ],
+ ['-inf', '-inf', '-inf', '-inf'],
+ ['nan', 'nan', 'nan', 'nan']]
+
+ for wants, val in zip(wanted, svals):
+ for want, styp in zip(wants, styps):
+ msg = 'for str({}({}))'.format(np.dtype(styp).name, repr(val))
+ assert_equal(str(styp(val)), want, err_msg=msg)
+
+ def test_scalar_cutoffs(self):
+ # test that both the str and repr of np.float64 behaves
+ # like python floats in python3.
+ def check(v):
+ assert_equal(str(np.float64(v)), str(v))
+ assert_equal(str(np.float64(v)), repr(v))
+ assert_equal(repr(np.float64(v)), repr(v))
+ assert_equal(repr(np.float64(v)), str(v))
+
+ # check we use the same number of significant digits
+ check(1.12345678901234567890)
+ check(0.0112345678901234567890)
+
+ # check switch from scientific output to positional and back
+ check(1e-5)
+ check(1e-4)
+ check(1e15)
+ check(1e16)
+
+ def test_py2_float_print(self):
+ # gh-10753
+ # In python2, the python float type implements an obsolete method
+ # tp_print, which overrides tp_repr and tp_str when using "print" to
+ # output to a "real file" (ie, not a StringIO). Make sure we don't
+ # inherit it.
+ x = np.double(0.1999999999999)
+ with TemporaryFile('r+t') as f:
+ print(x, file=f)
+ f.seek(0)
+ output = f.read()
+ assert_equal(output, str(x) + '\n')
+ # In python2 the value float('0.1999999999999') prints with reduced
+ # precision as '0.2', but we want numpy's np.double('0.1999999999999')
+ # to print the unique value, '0.1999999999999'.
+
+ # gh-11031
+ # Only in the python2 interactive shell and when stdout is a "real"
+ # file, the output of the last command is printed to stdout without
+ # Py_PRINT_RAW (unlike the print statement) so `>>> x` and `>>> print
+ # x` are potentially different. Make sure they are the same. The only
+ # way I found to get prompt-like output is using an actual prompt from
+ # the 'code' module. Again, must use tempfile to get a "real" file.
+
+ # dummy user-input which enters one line and then ctrl-Ds.
+ def userinput():
+ yield 'np.sqrt(2)'
+ raise EOFError
+ gen = userinput()
+ input_func = lambda prompt="": next(gen)
+
+ with TemporaryFile('r+t') as fo, TemporaryFile('r+t') as fe:
+ orig_stdout, orig_stderr = sys.stdout, sys.stderr
+ sys.stdout, sys.stderr = fo, fe
+
+ code.interact(local={'np': np}, readfunc=input_func, banner='')
+
+ sys.stdout, sys.stderr = orig_stdout, orig_stderr
+
+ fo.seek(0)
+ capture = fo.read().strip()
+
+ assert_equal(capture, repr(np.sqrt(2)))
+
+ 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(5e-324, 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
+ f32x = np.finfo(np.float32).max
+ assert_equal(fpos32(f32x, **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.
+ assert_equal(fpos32(f32x),
+ "340282350000000000000000000000000000000.")
+
+ # Further tests of zero-padding vs rounding in different combinations
+ # of unique, fractional, precision, min_digits
+ # precision can only reduce digits, not add them.
+ # min_digits can only extend digits, not reduce them.
+ assert_equal(fpos32(f32x, unique=True, fractional=True, precision=0),
+ "340282350000000000000000000000000000000.")
+ assert_equal(fpos32(f32x, unique=True, fractional=True, precision=4),
+ "340282350000000000000000000000000000000.")
+ assert_equal(fpos32(f32x, unique=True, fractional=True, min_digits=0),
+ "340282346638528859811704183484516925440.")
+ assert_equal(fpos32(f32x, unique=True, fractional=True, min_digits=4),
+ "340282346638528859811704183484516925440.0000")
+ assert_equal(fpos32(f32x, unique=True, fractional=True,
+ min_digits=4, precision=4),
+ "340282346638528859811704183484516925440.0000")
+ assert_raises(ValueError, fpos32, f32x, unique=True, fractional=False,
+ precision=0)
+ assert_equal(fpos32(f32x, unique=True, fractional=False, precision=4),
+ "340300000000000000000000000000000000000.")
+ assert_equal(fpos32(f32x, unique=True, fractional=False, precision=20),
+ "340282350000000000000000000000000000000.")
+ assert_equal(fpos32(f32x, unique=True, fractional=False, min_digits=4),
+ "340282350000000000000000000000000000000.")
+ assert_equal(fpos32(f32x, unique=True, fractional=False,
+ min_digits=20),
+ "340282346638528859810000000000000000000.")
+ assert_equal(fpos32(f32x, unique=True, fractional=False,
+ min_digits=15),
+ "340282346638529000000000000000000000000.")
+ assert_equal(fpos32(f32x, unique=False, fractional=False, precision=4),
+ "340300000000000000000000000000000000000.")
+ # test that unique rounding is preserved when precision is supplied
+ # but no extra digits need to be printed (gh-18609)
+ a = np.float64.fromhex('-1p-97')
+ assert_equal(fsci64(a, unique=True), '-6.310887241768095e-30')
+ assert_equal(fsci64(a, unique=False, precision=15),
+ '-6.310887241768094e-30')
+ assert_equal(fsci64(a, unique=True, precision=15),
+ '-6.310887241768095e-30')
+ assert_equal(fsci64(a, unique=True, min_digits=15),
+ '-6.310887241768095e-30')
+ assert_equal(fsci64(a, unique=True, precision=15, min_digits=15),
+ '-6.310887241768095e-30')
+ # adds/remove digits in unique mode with unbiased rnding
+ assert_equal(fsci64(a, unique=True, precision=14),
+ '-6.31088724176809e-30')
+ assert_equal(fsci64(a, unique=True, min_digits=16),
+ '-6.3108872417680944e-30')
+ assert_equal(fsci64(a, unique=True, precision=16),
+ '-6.310887241768095e-30')
+ assert_equal(fsci64(a, unique=True, min_digits=14),
+ '-6.310887241768095e-30')
+ # test min_digits in unique mode with different rounding cases
+ assert_equal(fsci64('1e120', min_digits=3), '1.000e+120')
+ assert_equal(fsci64('1e100', min_digits=3), '1.000e+100')
+
+ # 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_dragon4_interface(self):
+ tps = [np.float16, np.float32, np.float64]
+ # test is flaky for musllinux on np.float128
+ if hasattr(np, 'float128') and not IS_MUSL:
+ tps.append(np.float128)
+
+ fpos = np.format_float_positional
+ fsci = np.format_float_scientific
+
+ for tp in tps:
+ # test padding
+ assert_equal(fpos(tp('1.0'), pad_left=4, pad_right=4), " 1. ")
+ assert_equal(fpos(tp('-1.0'), pad_left=4, pad_right=4), " -1. ")
+ assert_equal(fpos(tp('-10.2'),
+ pad_left=4, pad_right=4), " -10.2 ")
+
+ # test exp_digits
+ assert_equal(fsci(tp('1.23e1'), exp_digits=5), "1.23e+00001")
+
+ # test fixed (non-unique) mode
+ assert_equal(fpos(tp('1.0'), unique=False, precision=4), "1.0000")
+ assert_equal(fsci(tp('1.0'), unique=False, precision=4),
+ "1.0000e+00")
+
+ # test trimming
+ # trim of 'k' or '.' only affects non-unique mode, since unique
+ # mode will not output trailing 0s.
+ assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='k'),
+ "1.0000")
+
+ assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='.'),
+ "1.")
+ assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='.'),
+ "1.2" if tp != np.float16 else "1.2002")
+
+ assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='0'),
+ "1.0")
+ assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='0'),
+ "1.2" if tp != np.float16 else "1.2002")
+ assert_equal(fpos(tp('1.'), trim='0'), "1.0")
+
+ assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='-'),
+ "1")
+ assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='-'),
+ "1.2" if tp != np.float16 else "1.2002")
+ assert_equal(fpos(tp('1.'), trim='-'), "1")
+ assert_equal(fpos(tp('1.001'), precision=1, trim='-'), "1")
+
+ @pytest.mark.skipif(not platform.machine().startswith("ppc64"),
+ reason="only applies to ppc float128 values")
+ def test_ppc64_ibm_double_double128(self):
+ # check that the precision decreases once we get into the subnormal
+ # range. Unlike float64, this starts around 1e-292 instead of 1e-308,
+ # which happens when the first double is normal and the second is
+ # subnormal.
+ x = np.float128('2.123123123123123123123123123123123e-286')
+ got = [str(x/np.float128('2e' + str(i))) for i in range(0,40)]
+ expected = [
+ "1.06156156156156156156156156156157e-286",
+ "1.06156156156156156156156156156158e-287",
+ "1.06156156156156156156156156156159e-288",
+ "1.0615615615615615615615615615616e-289",
+ "1.06156156156156156156156156156157e-290",
+ "1.06156156156156156156156156156156e-291",
+ "1.0615615615615615615615615615616e-292",
+ "1.0615615615615615615615615615615e-293",
+ "1.061561561561561561561561561562e-294",
+ "1.06156156156156156156156156155e-295",
+ "1.0615615615615615615615615616e-296",
+ "1.06156156156156156156156156e-297",
+ "1.06156156156156156156156157e-298",
+ "1.0615615615615615615615616e-299",
+ "1.06156156156156156156156e-300",
+ "1.06156156156156156156155e-301",
+ "1.0615615615615615615616e-302",
+ "1.061561561561561561562e-303",
+ "1.06156156156156156156e-304",
+ "1.0615615615615615618e-305",
+ "1.06156156156156156e-306",
+ "1.06156156156156157e-307",
+ "1.0615615615615616e-308",
+ "1.06156156156156e-309",
+ "1.06156156156157e-310",
+ "1.0615615615616e-311",
+ "1.06156156156e-312",
+ "1.06156156154e-313",
+ "1.0615615616e-314",
+ "1.06156156e-315",
+ "1.06156155e-316",
+ "1.061562e-317",
+ "1.06156e-318",
+ "1.06155e-319",
+ "1.0617e-320",
+ "1.06e-321",
+ "1.04e-322",
+ "1e-323",
+ "0.0",
+ "0.0"]
+ assert_equal(got, expected)
+
+ # Note: we follow glibc behavior, but it (or gcc) might not be right.
+ # In particular we can get two values that print the same but are not
+ # equal:
+ a = np.float128('2')/np.float128('3')
+ b = np.float128(str(a))
+ assert_equal(str(a), str(b))
+ assert_(a != b)
+
+ def float32_roundtrip(self):
+ # gh-9360
+ x = np.float32(1024 - 2**-14)
+ y = np.float32(1024 - 2**-13)
+ assert_(repr(x) != repr(y))
+ assert_equal(np.float32(repr(x)), x)
+ assert_equal(np.float32(repr(y)), y)
+
+ def float64_vs_python(self):
+ # gh-2643, gh-6136, gh-6908
+ assert_equal(repr(np.float64(0.1)), repr(0.1))
+ assert_(repr(np.float64(0.20000000000000004)) != repr(0.2))