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numpy / numpy / core / tests / test_scalarmath.py
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from __future__ import division, absolute_import, print_function

import sys

import numpy as np
from numpy.testing.utils import _gen_alignment_data
from numpy.testing import (
    TestCase, run_module_suite, assert_, assert_equal, assert_raises,
    assert_almost_equal
)

types = [np.bool_, np.byte, np.ubyte, np.short, np.ushort, np.intc, np.uintc,
         np.int_, np.uint, np.longlong, np.ulonglong,
         np.single, np.double, np.longdouble, np.csingle,
         np.cdouble, np.clongdouble]

floating_types = np.floating.__subclasses__()


# This compares scalarmath against ufuncs.

class TestTypes(TestCase):
    def test_types(self, level=1):
        for atype in types:
            a = atype(1)
            assert_(a == 1, "error with %r: got %r" % (atype, a))

    def test_type_add(self, level=1):
        # list of types
        for k, atype in enumerate(types):
            a_scalar = atype(3)
            a_array = np.array([3], dtype=atype)
            for l, btype in enumerate(types):
                b_scalar = btype(1)
                b_array = np.array([1], dtype=btype)
                c_scalar = a_scalar + b_scalar
                c_array = a_array + b_array
                # It was comparing the type numbers, but the new ufunc
                # function-finding mechanism finds the lowest function
                # to which both inputs can be cast - which produces 'l'
                # when you do 'q' + 'b'.  The old function finding mechanism
                # skipped ahead based on the first argument, but that
                # does not produce properly symmetric results...
                assert_equal(c_scalar.dtype, c_array.dtype,
                           "error with types (%d/'%c' + %d/'%c')" %
                            (k, np.dtype(atype).char, l, np.dtype(btype).char))

    def test_type_create(self, level=1):
        for k, atype in enumerate(types):
            a = np.array([1, 2, 3], atype)
            b = atype([1, 2, 3])
            assert_equal(a, b)

    def test_leak(self):
        # test leak of scalar objects
        # a leak would show up in valgrind as still-reachable of ~2.6MB
        for i in range(200000):
            np.add(1, 1)


class TestBaseMath(TestCase):
    def test_blocked(self):
        # test alignments offsets for simd instructions
        # alignments for vz + 2 * (vs - 1) + 1
        for dt, sz in [(np.float32, 11), (np.float64, 7)]:
            for out, inp1, inp2, msg in _gen_alignment_data(dtype=dt,
                                                            type='binary',
                                                            max_size=sz):
                exp1 = np.ones_like(inp1)
                inp1[...] = np.ones_like(inp1)
                inp2[...] = np.zeros_like(inp2)
                assert_almost_equal(np.add(inp1, inp2), exp1, err_msg=msg)
                assert_almost_equal(np.add(inp1, 1), exp1 + 1, err_msg=msg)
                assert_almost_equal(np.add(1, inp2), exp1, err_msg=msg)

                np.add(inp1, inp2, out=out)
                assert_almost_equal(out, exp1, err_msg=msg)

                inp2[...] += np.arange(inp2.size, dtype=dt) + 1
                assert_almost_equal(np.square(inp2),
                                    np.multiply(inp2, inp2),  err_msg=msg)
                assert_almost_equal(np.reciprocal(inp2),
                                    np.divide(1, inp2),  err_msg=msg)

                inp1[...] = np.ones_like(inp1)
                inp2[...] = np.zeros_like(inp2)
                np.add(inp1, 1, out=out)
                assert_almost_equal(out, exp1 + 1, err_msg=msg)
                np.add(1, inp2, out=out)
                assert_almost_equal(out, exp1, err_msg=msg)

    def test_lower_align(self):
        # check data that is not aligned to element size
        # i.e doubles are aligned to 4 bytes on i386
        d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64)
        o = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64)
        assert_almost_equal(d + d, d * 2)
        np.add(d, d, out=o)
        np.add(np.ones_like(d), d, out=o)
        np.add(d, np.ones_like(d), out=o)
        np.add(np.ones_like(d), d)
        np.add(d, np.ones_like(d))


class TestPower(TestCase):
    def test_small_types(self):
        for t in [np.int8, np.int16, np.float16]:
            a = t(3)
            b = a ** 4
            assert_(b == 81, "error with %r: got %r" % (t, b))

    def test_large_types(self):
        for t in [np.int32, np.int64, np.float32, np.float64, np.longdouble]:
            a = t(51)
            b = a ** 4
            msg = "error with %r: got %r" % (t, b)
            if np.issubdtype(t, np.integer):
                assert_(b == 6765201, msg)
            else:
                assert_almost_equal(b, 6765201, err_msg=msg)

    def test_mixed_types(self):
        typelist = [np.int8, np.int16, np.float16,
                    np.float32, np.float64, np.int8,
                    np.int16, np.int32, np.int64]
        for t1 in typelist:
            for t2 in typelist:
                a = t1(3)
                b = t2(2)
                result = a**b
                msg = ("error with %r and %r:"
                       "got %r, expected %r") % (t1, t2, result, 9)
                if np.issubdtype(np.dtype(result), np.integer):
                    assert_(result == 9, msg)
                else:
                    assert_almost_equal(result, 9, err_msg=msg)

class TestComplexDivision(TestCase):
    def test_zero_division(self):
        with np.errstate(all="ignore"):
            for t in [np.complex64, np.complex128]:
                a = t(0.0)
                b = t(1.0)
                assert_(np.isinf(b/a))
                b = t(complex(np.inf, np.inf))
                assert_(np.isinf(b/a))
                b = t(complex(np.inf, np.nan))
                assert_(np.isinf(b/a))
                b = t(complex(np.nan, np.inf))
                assert_(np.isinf(b/a))
                b = t(complex(np.nan, np.nan))
                assert_(np.isnan(b/a))
                b = t(0.)
                assert_(np.isnan(b/a))


class TestConversion(TestCase):
    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_longdouble_int(self):
        # gh-627
        x = np.longdouble(np.inf)
        assert_raises(OverflowError, x.__int__)
        x = np.clongdouble(np.inf)
        assert_raises(OverflowError, x.__int__)

    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))


#class TestRepr(TestCase):
#    def test_repr(self):
#        for t in types:
#            val = t(1197346475.0137341)
#            val_repr = repr(val)
#            val2 = eval(val_repr)
#            assert_equal( val, val2 )


class TestRepr(object):
    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_float_repr(self):
        # long double test cannot work, because eval goes through a python
        # float
        for t in [np.float32, np.float64]:
            yield self._test_type_repr, t


class TestSizeOf(TestCase):

    def test_equal_nbytes(self):
        for type in types:
            x = type(0)
            assert_(sys.getsizeof(x) > x.nbytes)

    def test_error(self):
        d = np.float32()
        assert_raises(TypeError, d.__sizeof__, "a")


class TestAbs(TestCase):

    def _test_abs_func(self, absfunc):
        for tp in 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)

    def test_builtin_abs(self):
        self._test_abs_func(abs)

    def test_numpy_abs(self):
        self._test_abs_func(np.abs)


if __name__ == "__main__":
    run_module_suite()