text: # -*- coding: utf-8 -*-
  import sys
  import gc
  import pytest
  
  import numpy as np
  from numpy.testing import (
      assert_, assert_equal, assert_raises, assert_warns, HAS_REFCOUNT,
      assert_raises_regex,
      )
  import textwrap
  
  class TestArrayRepr:
      def test_nan_inf(self):
          x = np.array([np.nan, np.inf])
          assert_equal(repr(x), 'array([nan, inf])')
  
      def test_subclass(self):
          class sub(np.ndarray): pass
  
          # one dimensional
          x1d = np.array([1, 2]).view(sub)
          assert_equal(repr(x1d), 'sub([1, 2])')
  
          # two dimensional
          x2d = np.array([[1, 2], [3, 4]]).view(sub)
          assert_equal(repr(x2d),
              'sub([[1, 2],\n'
              '     [3, 4]])')
  
          # two dimensional with flexible dtype
          xstruct = np.ones((2,2), dtype=[('a', '<i4')]).view(sub)
          assert_equal(repr(xstruct),
              "sub([[(1,), (1,)],\n"
              "     [(1,), (1,)]], dtype=[('a', '<i4')])"
          )
  
      @pytest.mark.xfail(reason="See gh-10544")
      def test_object_subclass(self):
          class sub(np.ndarray):
              def __new__(cls, inp):
                  obj = np.asarray(inp).view(cls)
                  return obj
  
              def __getitem__(self, ind):
                  ret = super(sub, self).__getitem__(ind)
                  return sub(ret)
  
          # test that object + subclass is OK:
          x = sub([None, None])
          assert_equal(repr(x), 'sub([None, None], dtype=object)')
          assert_equal(str(x), '[None None]')
  
          x = sub([None, sub([None, None])])
          assert_equal(repr(x),
              'sub([None, sub([None, None], dtype=object)], dtype=object)')
          assert_equal(str(x), '[None sub([None, None], dtype=object)]')
  
      def test_0d_object_subclass(self):
          # make sure that subclasses which return 0ds instead
          # of scalars don't cause infinite recursion in str
          class sub(np.ndarray):
              def __new__(cls, inp):
                  obj = np.asarray(inp).view(cls)
                  return obj
  
              def __getitem__(self, ind):
                  ret = super(sub, self).__getitem__(ind)
                  return sub(ret)
  
          x = sub(1)
          assert_equal(repr(x), 'sub(1)')
          assert_equal(str(x), '1')
  
          x = sub([1, 1])
          assert_equal(repr(x), 'sub([1, 1])')
          assert_equal(str(x), '[1 1]')
  
          # check it works properly with object arrays too
          x = sub(None)
          assert_equal(repr(x), 'sub(None, dtype=object)')
          assert_equal(str(x), 'None')
  
          # plus recursive object arrays (even depth > 1)
          y = sub(None)
          x[()] = y
          y[()] = x
          assert_equal(repr(x),
              'sub(sub(sub(..., dtype=object), dtype=object), dtype=object)')
          assert_equal(str(x), '...')
          x[()] = 0  # resolve circular references for garbage collector
  
          # nested 0d-subclass-object
          x = sub(None)
          x[()] = sub(None)
          assert_equal(repr(x), 'sub(sub(None, dtype=object), dtype=object)')
          assert_equal(str(x), 'None')
  
          # gh-10663
          class DuckCounter(np.ndarray):
              def __getitem__(self, item):
                  result = super(DuckCounter, self).__getitem__(item)
                  if not isinstance(result, DuckCounter):
                      result = result[...].view(DuckCounter)
                  return result
  
              def to_string(self):
                  return {0: 'zero', 1: 'one', 2: 'two'}.get(self.item(), 'many')
  
              def __str__(self):
                  if self.shape == ():
                      return self.to_string()
                  else:
                      fmt = {'all': lambda x: x.to_string()}
                      return np.array2string(self, formatter=fmt)
  
          dc = np.arange(5).view(DuckCounter)
          assert_equal(str(dc), "[zero one two many many]")
          assert_equal(str(dc[0]), "zero")
  
      def test_self_containing(self):
          arr0d = np.array(None)
          arr0d[()] = arr0d
          assert_equal(repr(arr0d),
              'array(array(..., dtype=object), dtype=object)')
          arr0d[()] = 0  # resolve recursion for garbage collector
  
          arr1d = np.array([None, None])
          arr1d[1] = arr1d
          assert_equal(repr(arr1d),
              'array([None, array(..., dtype=object)], dtype=object)')
          arr1d[1] = 0  # resolve recursion for garbage collector
  
          first = np.array(None)
          second = np.array(None)
          first[()] = second
          second[()] = first
          assert_equal(repr(first),
              'array(array(array(..., dtype=object), dtype=object), dtype=object)')
          first[()] = 0  # resolve circular references for garbage collector
  
      def test_containing_list(self):
          # printing square brackets directly would be ambiguuous
          arr1d = np.array([None, None])
          arr1d[0] = [1, 2]
          arr1d[1] = [3]
          assert_equal(repr(arr1d),
              'array([list([1, 2]), list([3])], dtype=object)')
  
      def test_void_scalar_recursion(self):
          # gh-9345
          repr(np.void(b'test'))  # RecursionError ?
  
      def test_fieldless_structured(self):
          # gh-10366
          no_fields = np.dtype([])
          arr_no_fields = np.empty(4, dtype=no_fields)
          assert_equal(repr(arr_no_fields), 'array([(), (), (), ()], dtype=[])')
  
  
  class TestComplexArray:
      def test_str(self):
          rvals = [0, 1, -1, np.inf, -np.inf, np.nan]
          cvals = [complex(rp, ip) for rp in rvals for ip in rvals]
          dtypes = [np.complex64, np.cdouble, np.clongdouble]
          actual = [str(np.array([c], dt)) for c in cvals for dt in dtypes]
          wanted = [
              '[0.+0.j]',    '[0.+0.j]',    '[0.+0.j]',
              '[0.+1.j]',    '[0.+1.j]',    '[0.+1.j]',
              '[0.-1.j]',    '[0.-1.j]',    '[0.-1.j]',
              '[0.+infj]',   '[0.+infj]',   '[0.+infj]',
              '[0.-infj]',   '[0.-infj]',   '[0.-infj]',
              '[0.+nanj]',   '[0.+nanj]',   '[0.+nanj]',
              '[1.+0.j]',    '[1.+0.j]',    '[1.+0.j]',
              '[1.+1.j]',    '[1.+1.j]',    '[1.+1.j]',
              '[1.-1.j]',    '[1.-1.j]',    '[1.-1.j]',
              '[1.+infj]',   '[1.+infj]',   '[1.+infj]',
              '[1.-infj]',   '[1.-infj]',   '[1.-infj]',
              '[1.+nanj]',   '[1.+nanj]',   '[1.+nanj]',
              '[-1.+0.j]',   '[-1.+0.j]',   '[-1.+0.j]',
              '[-1.+1.j]',   '[-1.+1.j]',   '[-1.+1.j]',
              '[-1.-1.j]',   '[-1.-1.j]',   '[-1.-1.j]',
              '[-1.+infj]',  '[-1.+infj]',  '[-1.+infj]',
              '[-1.-infj]',  '[-1.-infj]',  '[-1.-infj]',
              '[-1.+nanj]',  '[-1.+nanj]',  '[-1.+nanj]',
              '[inf+0.j]',   '[inf+0.j]',   '[inf+0.j]',
              '[inf+1.j]',   '[inf+1.j]',   '[inf+1.j]',
              '[inf-1.j]',   '[inf-1.j]',   '[inf-1.j]',
              '[inf+infj]',  '[inf+infj]',  '[inf+infj]',
              '[inf-infj]',  '[inf-infj]',  '[inf-infj]',
              '[inf+nanj]',  '[inf+nanj]',  '[inf+nanj]',
              '[-inf+0.j]',  '[-inf+0.j]',  '[-inf+0.j]',
              '[-inf+1.j]',  '[-inf+1.j]',  '[-inf+1.j]',
              '[-inf-1.j]',  '[-inf-1.j]',  '[-inf-1.j]',
              '[-inf+infj]', '[-inf+infj]', '[-inf+infj]',
              '[-inf-infj]', '[-inf-infj]', '[-inf-infj]',
              '[-inf+nanj]', '[-inf+nanj]', '[-inf+nanj]',
              '[nan+0.j]',   '[nan+0.j]',   '[nan+0.j]',
              '[nan+1.j]',   '[nan+1.j]',   '[nan+1.j]',
              '[nan-1.j]',   '[nan-1.j]',   '[nan-1.j]',
              '[nan+infj]',  '[nan+infj]',  '[nan+infj]',
              '[nan-infj]',  '[nan-infj]',  '[nan-infj]',
              '[nan+nanj]',  '[nan+nanj]',  '[nan+nanj]']
  
          for res, val in zip(actual, wanted):
              assert_equal(res, val)
  
  class TestArray2String:
      def test_basic(self):
          """Basic test of array2string."""
          a = np.arange(3)
          assert_(np.array2string(a) == '[0 1 2]')
          assert_(np.array2string(a, max_line_width=4, legacy='1.13') == '[0 1\n 2]')
          assert_(np.array2string(a, max_line_width=4) == '[0\n 1\n 2]')
  
      def test_unexpected_kwarg(self):
          # ensure than an appropriate TypeError
          # is raised when array2string receives
          # an unexpected kwarg
  
          with assert_raises_regex(TypeError, 'nonsense'):
              np.array2string(np.array([1, 2, 3]),
                              nonsense=None)
  
      def test_format_function(self):
          """Test custom format function for each element in array."""
          def _format_function(x):
              if np.abs(x) < 1:
                  return '.'
              elif np.abs(x) < 2:
                  return 'o'
              else:
                  return 'O'
  
          x = np.arange(3)
          x_hex = "[0x0 0x1 0x2]"
          x_oct = "[0o0 0o1 0o2]"
          assert_(np.array2string(x, formatter={'all':_format_function}) ==
                  "[. o O]")
          assert_(np.array2string(x, formatter={'int_kind':_format_function}) ==
                  "[. o O]")
          assert_(np.array2string(x, formatter={'all':lambda x: "%.4f" % x}) ==
                  "[0.0000 1.0000 2.0000]")
          assert_equal(np.array2string(x, formatter={'int':lambda x: hex(x)}),
                  x_hex)
          assert_equal(np.array2string(x, formatter={'int':lambda x: oct(x)}),
                  x_oct)
  
          x = np.arange(3.)
          assert_(np.array2string(x, formatter={'float_kind':lambda x: "%.2f" % x}) ==
                  "[0.00 1.00 2.00]")
          assert_(np.array2string(x, formatter={'float':lambda x: "%.2f" % x}) ==
                  "[0.00 1.00 2.00]")
  
          s = np.array(['abc', 'def'])
          assert_(np.array2string(s, formatter={'numpystr':lambda s: s*2}) ==
                  '[abcabc defdef]')
  
  
      def test_structure_format(self):
          dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])
          x = np.array([('Sarah', (8.0, 7.0)), ('John', (6.0, 7.0))], dtype=dt)
          assert_equal(np.array2string(x),
                  "[('Sarah', [8., 7.]) ('John', [6., 7.])]")
  
          np.set_printoptions(legacy='1.13')
          try:
              # for issue #5692
              A = np.zeros(shape=10, dtype=[("A", "M8[s]")])
              A[5:].fill(np.datetime64('NaT'))
              assert_equal(
                  np.array2string(A),
                  textwrap.dedent("""\
                  [('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',)
                   ('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) ('NaT',) ('NaT',)
                   ('NaT',) ('NaT',) ('NaT',)]""")
              )
          finally:
              np.set_printoptions(legacy=False)
  
          # same again, but with non-legacy behavior
          assert_equal(
              np.array2string(A),
              textwrap.dedent("""\
              [('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',)
               ('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',)
               ('1970-01-01T00:00:00',) (                'NaT',)
               (                'NaT',) (                'NaT',)
               (                'NaT',) (                'NaT',)]""")
          )
  
          # and again, with timedeltas
          A = np.full(10, 123456, dtype=[("A", "m8[s]")])
          A[5:].fill(np.datetime64('NaT'))
          assert_equal(
              np.array2string(A),
              textwrap.dedent("""\
              [(123456,) (123456,) (123456,) (123456,) (123456,) ( 'NaT',) ( 'NaT',)
               ( 'NaT',) ( 'NaT',) ( 'NaT',)]""")
          )
  
          # See #8160
          struct_int = np.array([([1, -1],), ([123, 1],)], dtype=[('B', 'i4', 2)])
          assert_equal(np.array2string(struct_int),
                  "[([  1,  -1],) ([123,   1],)]")
          struct_2dint = np.array([([[0, 1], [2, 3]],), ([[12, 0], [0, 0]],)],
                  dtype=[('B', 'i4', (2, 2))])
          assert_equal(np.array2string(struct_2dint),
                  "[([[ 0,  1], [ 2,  3]],) ([[12,  0], [ 0,  0]],)]")
  
          # See #8172
          array_scalar = np.array(
                  (1., 2.1234567890123456789, 3.), dtype=('f8,f8,f8'))
          assert_equal(np.array2string(array_scalar), "(1., 2.12345679, 3.)")
  
      def test_unstructured_void_repr(self):
          a = np.array([27, 91, 50, 75,  7, 65, 10,  8,
                        27, 91, 51, 49,109, 82,101,100], dtype='u1').view('V8')
          assert_equal(repr(a[0]), r"void(b'\x1B\x5B\x32\x4B\x07\x41\x0A\x08')")
          assert_equal(str(a[0]), r"b'\x1B\x5B\x32\x4B\x07\x41\x0A\x08'")
          assert_equal(repr(a),
              r"array([b'\x1B\x5B\x32\x4B\x07\x41\x0A\x08'," "\n"
              r"       b'\x1B\x5B\x33\x31\x6D\x52\x65\x64'], dtype='|V8')")
  
          assert_equal(eval(repr(a), vars(np)), a)
          assert_equal(eval(repr(a[0]), vars(np)), a[0])
  
      def test_edgeitems_kwarg(self):
          # previously the global print options would be taken over the kwarg
          arr = np.zeros(3, int)
          assert_equal(
              np.array2string(arr, edgeitems=1, threshold=0),
              "[0 ... 0]"
          )
  
      def test_summarize_1d(self):
          A = np.arange(1001)
          strA = '[   0    1    2 ...  998  999 1000]'
          assert_equal(str(A), strA)
  
          reprA = 'array([   0,    1,    2, ...,  998,  999, 1000])'
          assert_equal(repr(A), reprA)
  
      def test_summarize_2d(self):
          A = np.arange(1002).reshape(2, 501)
          strA = '[[   0    1    2 ...  498  499  500]\n' \
                 ' [ 501  502  503 ...  999 1000 1001]]'
          assert_equal(str(A), strA)
  
          reprA = 'array([[   0,    1,    2, ...,  498,  499,  500],\n' \
                  '       [ 501,  502,  503, ...,  999, 1000, 1001]])'
          assert_equal(repr(A), reprA)
  
      def test_linewidth(self):
          a = np.full(6, 1)
  
          def make_str(a, width, **kw):
              return np.array2string(a, separator="", max_line_width=width, **kw)
  
          assert_equal(make_str(a, 8, legacy='1.13'), '[111111]')
          assert_equal(make_str(a, 7, legacy='1.13'), '[111111]')
          assert_equal(make_str(a, 5, legacy='1.13'), '[1111\n'
                                                      ' 11]')
  
          assert_equal(make_str(a, 8), '[111111]')
          assert_equal(make_str(a, 7), '[11111\n'
                                       ' 1]')
          assert_equal(make_str(a, 5), '[111\n'
                                       ' 111]')
  
          b = a[None,None,:]
  
          assert_equal(make_str(b, 12, legacy='1.13'), '[[[111111]]]')
          assert_equal(make_str(b,  9, legacy='1.13'), '[[[111111]]]')
          assert_equal(make_str(b,  8, legacy='1.13'), '[[[11111\n'
                                                       '   1]]]')
  
          assert_equal(make_str(b, 12), '[[[111111]]]')
          assert_equal(make_str(b,  9), '[[[111\n'
                                        '   111]]]')
          assert_equal(make_str(b,  8), '[[[11\n'
                                        '   11\n'
                                        '   11]]]')
  
      def test_wide_element(self):
          a = np.array(['xxxxx'])
          assert_equal(
              np.array2string(a, max_line_width=5),
              "['xxxxx']"
          )
          assert_equal(
              np.array2string(a, max_line_width=5, legacy='1.13'),
              "[ 'xxxxx']"
          )
  
      @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
      def test_refcount(self):
          # make sure we do not hold references to the array due to a recursive
          # closure (gh-10620)
          gc.disable()
          a = np.arange(2)
          r1 = sys.getrefcount(a)
          np.array2string(a)
          np.array2string(a)
          r2 = sys.getrefcount(a)
          gc.collect()
          gc.enable()
          assert_(r1 == r2)
  
  class TestPrintOptions:
      """Test getting and setting global print options."""
  
      def setup(self):
          self.oldopts = np.get_printoptions()
  
      def teardown(self):
          np.set_printoptions(**self.oldopts)
  
      def test_basic(self):
          x = np.array([1.5, 0, 1.234567890])
          assert_equal(repr(x), "array([1.5       , 0.        , 1.23456789])")
          np.set_printoptions(precision=4)
          assert_equal(repr(x), "array([1.5   , 0.    , 1.2346])")
  
      def test_precision_zero(self):
          np.set_printoptions(precision=0)
          for values, string in (
                  ([0.], "0."), ([.3], "0."), ([-.3], "-0."), ([.7], "1."),
                  ([1.5], "2."), ([-1.5], "-2."), ([-15.34], "-15."),
                  ([100.], "100."), ([.2, -1, 122.51], "  0.,  -1., 123."),
                  ([0], "0"), ([-12], "-12"), ([complex(.3, -.7)], "0.-1.j")):
              x = np.array(values)
              assert_equal(repr(x), "array([%s])" % string)
  
      def test_formatter(self):
          x = np.arange(3)
          np.set_printoptions(formatter={'all':lambda x: str(x-1)})
          assert_equal(repr(x), "array([-1, 0, 1])")
  
      def test_formatter_reset(self):
          x = np.arange(3)
          np.set_printoptions(formatter={'all':lambda x: str(x-1)})
          assert_equal(repr(x), "array([-1, 0, 1])")
          np.set_printoptions(formatter={'int':None})
          assert_equal(repr(x), "array([0, 1, 2])")
  
          np.set_printoptions(formatter={'all':lambda x: str(x-1)})
          assert_equal(repr(x), "array([-1, 0, 1])")
          np.set_printoptions(formatter={'all':None})
          assert_equal(repr(x), "array([0, 1, 2])")
  
          np.set_printoptions(formatter={'int':lambda x: str(x-1)})
          assert_equal(repr(x), "array([-1, 0, 1])")
          np.set_printoptions(formatter={'int_kind':None})
          assert_equal(repr(x), "array([0, 1, 2])")
  
          x = np.arange(3.)
          np.set_printoptions(formatter={'float':lambda x: str(x-1)})
          assert_equal(repr(x), "array([-1.0, 0.0, 1.0])")
          np.set_printoptions(formatter={'float_kind':None})
          assert_equal(repr(x), "array([0., 1., 2.])")
  
      def test_0d_arrays(self):
          unicode = type(u'')
  
          assert_equal(unicode(np.array(u'café', '<U4')), u'café')
  
          assert_equal(repr(np.array('café', '<U4')),
                       "array('café', dtype='<U4')")
          assert_equal(str(np.array('test', np.str_)), 'test')
  
          a = np.zeros(1, dtype=[('a', '<i4', (3,))])
          assert_equal(str(a[0]), '([0, 0, 0],)')
  
          assert_equal(repr(np.datetime64('2005-02-25')[...]),
                       "array('2005-02-25', dtype='datetime64[D]')")
  
          assert_equal(repr(np.timedelta64('10', 'Y')[...]),
                       "array(10, dtype='timedelta64[Y]')")
  
          # repr of 0d arrays is affected by printoptions
          x = np.array(1)
          np.set_printoptions(formatter={'all':lambda x: "test"})
          assert_equal(repr(x), "array(test)")
          # str is unaffected
          assert_equal(str(x), "1")
  
          # check `style` arg raises
          assert_warns(DeprecationWarning, np.array2string,
                                           np.array(1.), style=repr)
          # but not in legacy mode
          np.array2string(np.array(1.), style=repr, legacy='1.13')
          # gh-10934 style was broken in legacy mode, check it works
          np.array2string(np.array(1.), legacy='1.13')
  
      def test_float_spacing(self):
          x = np.array([1., 2., 3.])
          y = np.array([1., 2., -10.])
          z = np.array([100., 2., -1.])
          w = np.array([-100., 2., 1.])
  
          assert_equal(repr(x), 'array([1., 2., 3.])')
          assert_equal(repr(y), 'array([  1.,   2., -10.])')
          assert_equal(repr(np.array(y[0])), 'array(1.)')
          assert_equal(repr(np.array(y[-1])), 'array(-10.)')
          assert_equal(repr(z), 'array([100.,   2.,  -1.])')
          assert_equal(repr(w), 'array([-100.,    2.,    1.])')
  
          assert_equal(repr(np.array([np.nan, np.inf])), 'array([nan, inf])')
          assert_equal(repr(np.array([np.nan, -np.inf])), 'array([ nan, -inf])')
  
          x = np.array([np.inf, 100000, 1.1234])
          y = np.array([np.inf, 100000, -1.1234])
          z = np.array([np.inf, 1.1234, -1e120])
          np.set_printoptions(precision=2)
          assert_equal(repr(x), 'array([     inf, 1.00e+05, 1.12e+00])')
          assert_equal(repr(y), 'array([      inf,  1.00e+05, -1.12e+00])')
          assert_equal(repr(z), 'array([       inf,  1.12e+000, -1.00e+120])')
  
      def test_bool_spacing(self):
          assert_equal(repr(np.array([True,  True])),
                       'array([ True,  True])')
          assert_equal(repr(np.array([True, False])),
                       'array([ True, False])')
          assert_equal(repr(np.array([True])),
                       'array([ True])')
          assert_equal(repr(np.array(True)),
                       'array(True)')
          assert_equal(repr(np.array(False)),
                       'array(False)')
  
      def test_sign_spacing(self):
          a = np.arange(4.)
          b = np.array([1.234e9])
          c = np.array([1.0 + 1.0j, 1.123456789 + 1.123456789j], dtype='c16')
  
          assert_equal(repr(a), 'array([0., 1., 2., 3.])')
          assert_equal(repr(np.array(1.)), 'array(1.)')
          assert_equal(repr(b), 'array([1.234e+09])')
          assert_equal(repr(np.array([0.])), 'array([0.])')
          assert_equal(repr(c),
              "array([1.        +1.j        , 1.12345679+1.12345679j])")
          assert_equal(repr(np.array([0., -0.])), 'array([ 0., -0.])')
  
          np.set_printoptions(sign=' ')
          assert_equal(repr(a), 'array([ 0.,  1.,  2.,  3.])')
          assert_equal(repr(np.array(1.)), 'array( 1.)')
          assert_equal(repr(b), 'array([ 1.234e+09])')
          assert_equal(repr(c),
              "array([ 1.        +1.j        ,  1.12345679+1.12345679j])")
          assert_equal(repr(np.array([0., -0.])), 'array([ 0., -0.])')
  
          np.set_printoptions(sign='+')
          assert_equal(repr(a), 'array([+0., +1., +2., +3.])')
          assert_equal(repr(np.array(1.)), 'array(+1.)')
          assert_equal(repr(b), 'array([+1.234e+09])')
          assert_equal(repr(c),
              "array([+1.        +1.j        , +1.12345679+1.12345679j])")
  
          np.set_printoptions(legacy='1.13')
          assert_equal(repr(a), 'array([ 0.,  1.,  2.,  3.])')
          assert_equal(repr(b),  'array([  1.23400000e+09])')
          assert_equal(repr(-b), 'array([ -1.23400000e+09])')
          assert_equal(repr(np.array(1.)), 'array(1.0)')
          assert_equal(repr(np.array([0.])), 'array([ 0.])')
          assert_equal(repr(c),
              "array([ 1.00000000+1.j        ,  1.12345679+1.12345679j])")
          # gh-10383
          assert_equal(str(np.array([-1., 10])), "[ -1.  10.]")
  
          assert_raises(TypeError, np.set_printoptions, wrongarg=True)
  
      def test_float_overflow_nowarn(self):
          # make sure internal computations in FloatingFormat don't
          # warn about overflow
          repr(np.array([1e4, 0.1], dtype='f2'))
  
      def test_sign_spacing_structured(self):
          a = np.ones(2, dtype='<f,<f')
          assert_equal(repr(a),
              "array([(1., 1.), (1., 1.)], dtype=[('f0', '<f4'), ('f1', '<f4')])")
          assert_equal(repr(a[0]), "(1., 1.)")
  
      def test_floatmode(self):
          x = np.array([0.6104, 0.922, 0.457, 0.0906, 0.3733, 0.007244,
                        0.5933, 0.947, 0.2383, 0.4226], dtype=np.float16)
          y = np.array([0.2918820979355541, 0.5064172631089138,
                        0.2848750619642916, 0.4342965294660567,
                        0.7326538397312751, 0.3459503329096204,
                        0.0862072768214508, 0.39112753029631175],
                        dtype=np.float64)
          z = np.arange(6, dtype=np.float16)/10
          c = np.array([1.0 + 1.0j, 1.123456789 + 1.123456789j], dtype='c16')
  
          # also make sure 1e23 is right (is between two fp numbers)
          w = np.array(['1e{}'.format(i) for i in range(25)], dtype=np.float64)
          # note: we construct w from the strings `1eXX` instead of doing
          # `10.**arange(24)` because it turns out the two are not equivalent in
          # python. On some architectures `1e23 != 10.**23`.
          wp = np.array([1.234e1, 1e2, 1e123])
  
          # unique mode
          np.set_printoptions(floatmode='unique')
          assert_equal(repr(x),
              "array([0.6104  , 0.922   , 0.457   , 0.0906  , 0.3733  , 0.007244,\n"
              "       0.5933  , 0.947   , 0.2383  , 0.4226  ], dtype=float16)")
          assert_equal(repr(y),
              "array([0.2918820979355541 , 0.5064172631089138 , 0.2848750619642916 ,\n"
              "       0.4342965294660567 , 0.7326538397312751 , 0.3459503329096204 ,\n"
              "       0.0862072768214508 , 0.39112753029631175])")
          assert_equal(repr(z),
              "array([0. , 0.1, 0.2, 0.3, 0.4, 0.5], dtype=float16)")
          assert_equal(repr(w),
              "array([1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04, 1.e+05, 1.e+06, 1.e+07,\n"
              "       1.e+08, 1.e+09, 1.e+10, 1.e+11, 1.e+12, 1.e+13, 1.e+14, 1.e+15,\n"
              "       1.e+16, 1.e+17, 1.e+18, 1.e+19, 1.e+20, 1.e+21, 1.e+22, 1.e+23,\n"
              "       1.e+24])")
          assert_equal(repr(wp), "array([1.234e+001, 1.000e+002, 1.000e+123])")
          assert_equal(repr(c),
              "array([1.         +1.j         , 1.123456789+1.123456789j])")
  
          # maxprec mode, precision=8
          np.set_printoptions(floatmode='maxprec', precision=8)
          assert_equal(repr(x),
              "array([0.6104  , 0.922   , 0.457   , 0.0906  , 0.3733  , 0.007244,\n"
              "       0.5933  , 0.947   , 0.2383  , 0.4226  ], dtype=float16)")
          assert_equal(repr(y),
              "array([0.2918821 , 0.50641726, 0.28487506, 0.43429653, 0.73265384,\n"
              "       0.34595033, 0.08620728, 0.39112753])")
          assert_equal(repr(z),
              "array([0. , 0.1, 0.2, 0.3, 0.4, 0.5], dtype=float16)")
          assert_equal(repr(w[::5]),
              "array([1.e+00, 1.e+05, 1.e+10, 1.e+15, 1.e+20])")
          assert_equal(repr(wp), "array([1.234e+001, 1.000e+002, 1.000e+123])")
          assert_equal(repr(c),
              "array([1.        +1.j        , 1.12345679+1.12345679j])")
  
          # fixed mode, precision=4
          np.set_printoptions(floatmode='fixed', precision=4)
          assert_equal(repr(x),
              "array([0.6104, 0.9219, 0.4570, 0.0906, 0.3733, 0.0072, 0.5933, 0.9468,\n"
              "       0.2383, 0.4226], dtype=float16)")
          assert_equal(repr(y),
              "array([0.2919, 0.5064, 0.2849, 0.4343, 0.7327, 0.3460, 0.0862, 0.3911])")
          assert_equal(repr(z),
              "array([0.0000, 0.1000, 0.2000, 0.3000, 0.3999, 0.5000], dtype=float16)")
          assert_equal(repr(w[::5]),
              "array([1.0000e+00, 1.0000e+05, 1.0000e+10, 1.0000e+15, 1.0000e+20])")
          assert_equal(repr(wp), "array([1.2340e+001, 1.0000e+002, 1.0000e+123])")
          assert_equal(repr(np.zeros(3)), "array([0.0000, 0.0000, 0.0000])")
          assert_equal(repr(c),
              "array([1.0000+1.0000j, 1.1235+1.1235j])")
          # for larger precision, representation error becomes more apparent:
          np.set_printoptions(floatmode='fixed', precision=8)
          assert_equal(repr(z),
              "array([0.00000000, 0.09997559, 0.19995117, 0.30004883, 0.39990234,\n"
              "       0.50000000], dtype=float16)")
  
          # maxprec_equal  mode, precision=8
          np.set_printoptions(floatmode='maxprec_equal', precision=8)
          assert_equal(repr(x),
              "array([0.610352, 0.921875, 0.457031, 0.090576, 0.373291, 0.007244,\n"
              "       0.593262, 0.946777, 0.238281, 0.422607], dtype=float16)")
          assert_equal(repr(y),
              "array([0.29188210, 0.50641726, 0.28487506, 0.43429653, 0.73265384,\n"
              "       0.34595033, 0.08620728, 0.39112753])")
          assert_equal(repr(z),
              "array([0.0, 0.1, 0.2, 0.3, 0.4, 0.5], dtype=float16)")
          assert_equal(repr(w[::5]),
              "array([1.e+00, 1.e+05, 1.e+10, 1.e+15, 1.e+20])")
          assert_equal(repr(wp), "array([1.234e+001, 1.000e+002, 1.000e+123])")
          assert_equal(repr(c),
              "array([1.00000000+1.00000000j, 1.12345679+1.12345679j])")
  
      def test_legacy_mode_scalars(self):
          # in legacy mode, str of floats get truncated, and complex scalars
          # use * for non-finite imaginary part
          np.set_printoptions(legacy='1.13')
          assert_equal(str(np.float64(1.123456789123456789)), '1.12345678912')
          assert_equal(str(np.complex128(complex(1, np.nan))), '(1+nan*j)')
  
          np.set_printoptions(legacy=False)
          assert_equal(str(np.float64(1.123456789123456789)),
                       '1.1234567891234568')
          assert_equal(str(np.complex128(complex(1, np.nan))), '(1+nanj)')
  
      def test_legacy_stray_comma(self):
          np.set_printoptions(legacy='1.13')
          assert_equal(str(np.arange(10000)), '[   0    1    2 ..., 9997 9998 9999]')
  
          np.set_printoptions(legacy=False)
          assert_equal(str(np.arange(10000)), '[   0    1    2 ... 9997 9998 9999]')
  
      def test_dtype_linewidth_wrapping(self):
          np.set_printoptions(linewidth=75)
          assert_equal(repr(np.arange(10,20., dtype='f4')),
              "array([10., 11., 12., 13., 14., 15., 16., 17., 18., 19.], dtype=float32)")
          assert_equal(repr(np.arange(10,23., dtype='f4')), textwrap.dedent("""\
              array([10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22.],
                    dtype=float32)"""))
  
          styp = '<U4'
          assert_equal(repr(np.ones(3, dtype=styp)),
              "array(['1', '1', '1'], dtype='{}')".format(styp))
          assert_equal(repr(np.ones(12, dtype=styp)), textwrap.dedent("""\
              array(['1', '1', '1', '1', '1', '1', '1', '1', '1', '1', '1', '1'],
                    dtype='{}')""".format(styp)))
  
      def test_linewidth_repr(self):
          a = np.full(7, fill_value=2)
          np.set_printoptions(linewidth=17)
          assert_equal(
              repr(a),
              textwrap.dedent("""\
              array([2, 2, 2,
                     2, 2, 2,
                     2])""")
          )
          np.set_printoptions(linewidth=17, legacy='1.13')
          assert_equal(
              repr(a),
              textwrap.dedent("""\
              array([2, 2, 2,
                     2, 2, 2, 2])""")
          )
  
          a = np.full(8, fill_value=2)
  
          np.set_printoptions(linewidth=18, legacy=False)
          assert_equal(
              repr(a),
              textwrap.dedent("""\
              array([2, 2, 2,
                     2, 2, 2,
                     2, 2])""")
          )
  
          np.set_printoptions(linewidth=18, legacy='1.13')
          assert_equal(
              repr(a),
              textwrap.dedent("""\
              array([2, 2, 2, 2,
                     2, 2, 2, 2])""")
          )
  
      def test_linewidth_str(self):
          a = np.full(18, fill_value=2)
          np.set_printoptions(linewidth=18)
          assert_equal(
              str(a),
              textwrap.dedent("""\
              [2 2 2 2 2 2 2 2
               2 2 2 2 2 2 2 2
               2 2]""")
          )
          np.set_printoptions(linewidth=18, legacy='1.13')
          assert_equal(
              str(a),
              textwrap.dedent("""\
              [2 2 2 2 2 2 2 2 2
               2 2 2 2 2 2 2 2 2]""")
          )
  
      def test_edgeitems(self):
          np.set_printoptions(edgeitems=1, threshold=1)
          a = np.arange(27).reshape((3, 3, 3))
          assert_equal(
              repr(a),
              textwrap.dedent("""\
              array([[[ 0, ...,  2],
                      ...,
                      [ 6, ...,  8]],
  
                     ...,
  
                     [[18, ..., 20],
                      ...,
                      [24, ..., 26]]])""")
          )
  
          b = np.zeros((3, 3, 1, 1))
          assert_equal(
              repr(b),
              textwrap.dedent("""\
              array([[[[0.]],
  
                      ...,
  
                      [[0.]]],
  
  
                     ...,
  
  
                     [[[0.]],
  
                      ...,
  
                      [[0.]]]])""")
          )
  
          # 1.13 had extra trailing spaces, and was missing newlines
          np.set_printoptions(legacy='1.13')
  
          assert_equal(
              repr(a),
              textwrap.dedent("""\
              array([[[ 0, ...,  2],
                      ..., 
                      [ 6, ...,  8]],
  
                     ..., 
                     [[18, ..., 20],
                      ..., 
                      [24, ..., 26]]])""")
          )
  
          assert_equal(
              repr(b),
              textwrap.dedent("""\
              array([[[[ 0.]],
  
                      ..., 
                      [[ 0.]]],
  
  
                     ..., 
                     [[[ 0.]],
  
                      ..., 
                      [[ 0.]]]])""")
          )
  
      def test_bad_args(self):
          assert_raises(ValueError, np.set_printoptions, threshold=float('nan'))
          assert_raises(TypeError, np.set_printoptions, threshold='1')
          assert_raises(TypeError, np.set_printoptions, threshold=b'1')
  
  def test_unicode_object_array():
      import sys
      expected = "array(['é'], dtype=object)"
      x = np.array([u'\xe9'], dtype=object)
      assert_equal(repr(x), expected)
  
  
  class TestContextManager:
      def test_ctx_mgr(self):
          # test that context manager actually works
          with np.printoptions(precision=2):
              s = str(np.array([2.0]) / 3)
          assert_equal(s, '[0.67]')
  
      def test_ctx_mgr_restores(self):
          # test that print options are actually restrored
          opts = np.get_printoptions()
          with np.printoptions(precision=opts['precision'] - 1,
                               linewidth=opts['linewidth'] - 4):
              pass
          assert_equal(np.get_printoptions(), opts)
  
      def test_ctx_mgr_exceptions(self):
          # test that print options are restored even if an exception is raised
          opts = np.get_printoptions()
          try:
              with np.printoptions(precision=2, linewidth=11):
                  raise ValueError
          except ValueError:
              pass
          assert_equal(np.get_printoptions(), opts)
  
      def test_ctx_mgr_as_smth(self):
          opts = {"precision": 2}
          with np.printoptions(**opts) as ctx:
              saved_opts = ctx.copy()
          assert_equal({k: saved_opts[k] for k in opts}, opts)
  