code: import copy
  import sys
  import gc
  import tempfile
  import pytest
  from os import path
  from io import BytesIO
  from itertools import chain
  
  import numpy as np
  from numpy.testing import (
          assert_, assert_equal, IS_PYPY, assert_almost_equal,
          assert_array_equal, assert_array_almost_equal, assert_raises,
          assert_raises_regex, assert_warns, suppress_warnings,
          _assert_valid_refcount, HAS_REFCOUNT,
          )
  from numpy.testing._private.utils import _no_tracing
  from numpy.compat import asbytes, asunicode, pickle
  
  try:
      RecursionError
  except NameError:
      RecursionError = RuntimeError  # python < 3.5
  
  class TestRegression:
      def test_invalid_round(self):
          # Ticket #3
          v = 4.7599999999999998
          assert_array_equal(np.array([v]), np.array(v))
  
      def test_mem_empty(self):
          # Ticket #7
          np.empty((1,), dtype=[('x', np.int64)])
  
      def test_pickle_transposed(self):
          # Ticket #16
          a = np.transpose(np.array([[2, 9], [7, 0], [3, 8]]))
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              with BytesIO() as f:
                  pickle.dump(a, f, protocol=proto)
                  f.seek(0)
                  b = pickle.load(f)
              assert_array_equal(a, b)
  
      def test_dtype_names(self):
          # Ticket #35
          # Should succeed
          np.dtype([(('name', 'label'), np.int32, 3)])
  
      def test_reduce(self):
          # Ticket #40
          assert_almost_equal(np.add.reduce([1., .5], dtype=None), 1.5)
  
      def test_zeros_order(self):
          # Ticket #43
          np.zeros([3], int, 'C')
          np.zeros([3], order='C')
          np.zeros([3], int, order='C')
  
      def test_asarray_with_order(self):
          # Check that nothing is done when order='F' and array C/F-contiguous
          a = np.ones(2)
          assert_(a is np.asarray(a, order='F'))
  
      def test_ravel_with_order(self):
          # Check that ravel works when order='F' and array C/F-contiguous
          a = np.ones(2)
          assert_(not a.ravel('F').flags.owndata)
  
      def test_sort_bigendian(self):
          # Ticket #47
          a = np.linspace(0, 10, 11)
          c = a.astype(np.dtype('<f8'))
          c.sort()
          assert_array_almost_equal(c, a)
  
      def test_negative_nd_indexing(self):
          # Ticket #49
          c = np.arange(125).reshape((5, 5, 5))
          origidx = np.array([-1, 0, 1])
          idx = np.array(origidx)
          c[idx]
          assert_array_equal(idx, origidx)
  
      def test_char_dump(self):
          # Ticket #50
          ca = np.char.array(np.arange(1000, 1010), itemsize=4)
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              with BytesIO() as f:
                  pickle.dump(ca, f, protocol=proto)
                  f.seek(0)
                  ca = np.load(f, allow_pickle=True)
  
      def test_noncontiguous_fill(self):
          # Ticket #58.
          a = np.zeros((5, 3))
          b = a[:, :2,]
  
          def rs():
              b.shape = (10,)
  
          assert_raises(AttributeError, rs)
  
      def test_bool(self):
          # Ticket #60
          np.bool_(1)  # Should succeed
  
      def test_indexing1(self):
          # Ticket #64
          descr = [('x', [('y', [('z', 'c16', (2,)),]),]),]
          buffer = ((([6j, 4j],),),)
          h = np.array(buffer, dtype=descr)
          h['x']['y']['z']
  
      def test_indexing2(self):
          # Ticket #65
          descr = [('x', 'i4', (2,))]
          buffer = ([3, 2],)
          h = np.array(buffer, dtype=descr)
          h['x']
  
      def test_round(self):
          # Ticket #67
          x = np.array([1+2j])
          assert_almost_equal(x**(-1), [1/(1+2j)])
  
      def test_scalar_compare(self):
          # Trac Ticket #72
          # https://github.com/numpy/numpy/issues/565
          a = np.array(['test', 'auto'])
          assert_array_equal(a == 'auto', np.array([False, True]))
          assert_(a[1] == 'auto')
          assert_(a[0] != 'auto')
          b = np.linspace(0, 10, 11)
          # This should return true for now, but will eventually raise an error:
          with suppress_warnings() as sup:
              sup.filter(FutureWarning)
              assert_(b != 'auto')
          assert_(b[0] != 'auto')
  
      def test_unicode_swapping(self):
          # Ticket #79
          ulen = 1
          ucs_value = u'\U0010FFFF'
          ua = np.array([[[ucs_value*ulen]*2]*3]*4, dtype='U%s' % ulen)
          ua.newbyteorder()  # Should succeed.
  
      def test_object_array_fill(self):
          # Ticket #86
          x = np.zeros(1, 'O')
          x.fill([])
  
      def test_mem_dtype_align(self):
          # Ticket #93
          assert_raises(TypeError, np.dtype,
                                {'names':['a'], 'formats':['foo']}, align=1)
  
      def test_endian_bool_indexing(self):
          # Ticket #105
          a = np.arange(10., dtype='>f8')
          b = np.arange(10., dtype='<f8')
          xa = np.where((a > 2) & (a < 6))
          xb = np.where((b > 2) & (b < 6))
          ya = ((a > 2) & (a < 6))
          yb = ((b > 2) & (b < 6))
          assert_array_almost_equal(xa, ya.nonzero())
          assert_array_almost_equal(xb, yb.nonzero())
          assert_(np.all(a[ya] > 0.5))
          assert_(np.all(b[yb] > 0.5))
  
      def test_endian_where(self):
          # GitHub issue #369
          net = np.zeros(3, dtype='>f4')
          net[1] = 0.00458849
          net[2] = 0.605202
          max_net = net.max()
          test = np.where(net <= 0., max_net, net)
          correct = np.array([ 0.60520202,  0.00458849,  0.60520202])
          assert_array_almost_equal(test, correct)
  
      def test_endian_recarray(self):
          # Ticket #2185
          dt = np.dtype([
                 ('head', '>u4'),
                 ('data', '>u4', 2),
              ])
          buf = np.recarray(1, dtype=dt)
          buf[0]['head'] = 1
          buf[0]['data'][:] = [1, 1]
  
          h = buf[0]['head']
          d = buf[0]['data'][0]
          buf[0]['head'] = h
          buf[0]['data'][0] = d
          assert_(buf[0]['head'] == 1)
  
      def test_mem_dot(self):
          # Ticket #106
          x = np.random.randn(0, 1)
          y = np.random.randn(10, 1)
          # Dummy array to detect bad memory access:
          _z = np.ones(10)
          _dummy = np.empty((0, 10))
          z = np.lib.stride_tricks.as_strided(_z, _dummy.shape, _dummy.strides)
          np.dot(x, np.transpose(y), out=z)
          assert_equal(_z, np.ones(10))
          # Do the same for the built-in dot:
          np.core.multiarray.dot(x, np.transpose(y), out=z)
          assert_equal(_z, np.ones(10))
  
      def test_arange_endian(self):
          # Ticket #111
          ref = np.arange(10)
          x = np.arange(10, dtype='<f8')
          assert_array_equal(ref, x)
          x = np.arange(10, dtype='>f8')
          assert_array_equal(ref, x)
  
      def test_arange_inf_step(self):
          ref = np.arange(0, 1, 10)
          x = np.arange(0, 1, np.inf)
          assert_array_equal(ref, x)
  
          ref = np.arange(0, 1, -10)
          x = np.arange(0, 1, -np.inf)
          assert_array_equal(ref, x)
  
          ref = np.arange(0, -1, -10)
          x = np.arange(0, -1, -np.inf)
          assert_array_equal(ref, x)
  
          ref = np.arange(0, -1, 10)
          x = np.arange(0, -1, np.inf)
          assert_array_equal(ref, x)
  
      def test_arange_underflow_stop_and_step(self):
          finfo = np.finfo(np.float64)
  
          ref = np.arange(0, finfo.eps, 2 * finfo.eps)
          x = np.arange(0, finfo.eps, finfo.max)
          assert_array_equal(ref, x)
  
          ref = np.arange(0, finfo.eps, -2 * finfo.eps)
          x = np.arange(0, finfo.eps, -finfo.max)
          assert_array_equal(ref, x)
  
          ref = np.arange(0, -finfo.eps, -2 * finfo.eps)
          x = np.arange(0, -finfo.eps, -finfo.max)
          assert_array_equal(ref, x)
  
          ref = np.arange(0, -finfo.eps, 2 * finfo.eps)
          x = np.arange(0, -finfo.eps, finfo.max)
          assert_array_equal(ref, x)
  
      def test_argmax(self):
          # Ticket #119
          a = np.random.normal(0, 1, (4, 5, 6, 7, 8))
          for i in range(a.ndim):
              a.argmax(i)  # Should succeed
  
      def test_mem_divmod(self):
          # Ticket #126
          for i in range(10):
              divmod(np.array([i])[0], 10)
  
      def test_hstack_invalid_dims(self):
          # Ticket #128
          x = np.arange(9).reshape((3, 3))
          y = np.array([0, 0, 0])
          assert_raises(ValueError, np.hstack, (x, y))
  
      def test_squeeze_type(self):
          # Ticket #133
          a = np.array([3])
          b = np.array(3)
          assert_(type(a.squeeze()) is np.ndarray)
          assert_(type(b.squeeze()) is np.ndarray)
  
      def test_add_identity(self):
          # Ticket #143
          assert_equal(0, np.add.identity)
  
      def test_numpy_float_python_long_addition(self):
          # Check that numpy float and python longs can be added correctly.
          a = np.float_(23.) + 2**135
          assert_equal(a, 23. + 2**135)
  
      def test_binary_repr_0(self):
          # Ticket #151
          assert_equal('0', np.binary_repr(0))
  
      def test_rec_iterate(self):
          # Ticket #160
          descr = np.dtype([('i', int), ('f', float), ('s', '|S3')])
          x = np.rec.array([(1, 1.1, '1.0'),
                           (2, 2.2, '2.0')], dtype=descr)
          x[0].tolist()
          [i for i in x[0]]
  
      def test_unicode_string_comparison(self):
          # Ticket #190
          a = np.array('hello', np.unicode_)
          b = np.array('world')
          a == b
  
      def test_tobytes_FORTRANORDER_discontiguous(self):
          # Fix in r2836
          # Create non-contiguous Fortran ordered array
          x = np.array(np.random.rand(3, 3), order='F')[:, :2]
          assert_array_almost_equal(x.ravel(), np.frombuffer(x.tobytes()))
  
      def test_flat_assignment(self):
          # Correct behaviour of ticket #194
          x = np.empty((3, 1))
          x.flat = np.arange(3)
          assert_array_almost_equal(x, [[0], [1], [2]])
          x.flat = np.arange(3, dtype=float)
          assert_array_almost_equal(x, [[0], [1], [2]])
  
      def test_broadcast_flat_assignment(self):
          # Ticket #194
          x = np.empty((3, 1))
  
          def bfa():
              x[:] = np.arange(3)
  
          def bfb():
              x[:] = np.arange(3, dtype=float)
  
          assert_raises(ValueError, bfa)
          assert_raises(ValueError, bfb)
  
      def test_nonarray_assignment(self):
          # See also Issue gh-2870, test for non-array assignment
          # and equivalent unsafe casted array assignment
          a = np.arange(10)
          b = np.ones(10, dtype=bool)
          r = np.arange(10)
  
          def assign(a, b, c):
              a[b] = c
  
          assert_raises(ValueError, assign, a, b, np.nan)
          a[b] = np.array(np.nan)  # but not this.
          assert_raises(ValueError, assign, a, r, np.nan)
          a[r] = np.array(np.nan)
  
      def test_unpickle_dtype_with_object(self):
          # Implemented in r2840
          dt = np.dtype([('x', int), ('y', np.object_), ('z', 'O')])
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              with BytesIO() as f:
                  pickle.dump(dt, f, protocol=proto)
                  f.seek(0)
                  dt_ = pickle.load(f)
              assert_equal(dt, dt_)
  
      def test_mem_array_creation_invalid_specification(self):
          # Ticket #196
          dt = np.dtype([('x', int), ('y', np.object_)])
          # Wrong way
          assert_raises(ValueError, np.array, [1, 'object'], dt)
          # Correct way
          np.array([(1, 'object')], dt)
  
      def test_recarray_single_element(self):
          # Ticket #202
          a = np.array([1, 2, 3], dtype=np.int32)
          b = a.copy()
          r = np.rec.array(a, shape=1, formats=['3i4'], names=['d'])
          assert_array_equal(a, b)
          assert_equal(a, r[0][0])
  
      def test_zero_sized_array_indexing(self):
          # Ticket #205
          tmp = np.array([])
  
          def index_tmp():
              tmp[np.array(10)]
  
          assert_raises(IndexError, index_tmp)
  
      def test_chararray_rstrip(self):
          # Ticket #222
          x = np.chararray((1,), 5)
          x[0] = b'a   '
          x = x.rstrip()
          assert_equal(x[0], b'a')
  
      def test_object_array_shape(self):
          # Ticket #239
          assert_equal(np.array([[1, 2], 3, 4], dtype=object).shape, (3,))
          assert_equal(np.array([[1, 2], [3, 4]], dtype=object).shape, (2, 2))
          assert_equal(np.array([(1, 2), (3, 4)], dtype=object).shape, (2, 2))
          assert_equal(np.array([], dtype=object).shape, (0,))
          assert_equal(np.array([[], [], []], dtype=object).shape, (3, 0))
          assert_equal(np.array([[3, 4], [5, 6], None], dtype=object).shape, (3,))
  
      def test_mem_around(self):
          # Ticket #243
          x = np.zeros((1,))
          y = [0]
          decimal = 6
          np.around(abs(x-y), decimal) <= 10.0**(-decimal)
  
      def test_character_array_strip(self):
          # Ticket #246
          x = np.char.array(("x", "x ", "x  "))
          for c in x:
              assert_equal(c, "x")
  
      def test_lexsort(self):
          # Lexsort memory error
          v = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
          assert_equal(np.lexsort(v), 0)
  
      def test_lexsort_invalid_sequence(self):
          # Issue gh-4123
          class BuggySequence:
              def __len__(self):
                  return 4
  
              def __getitem__(self, key):
                  raise KeyError
  
          assert_raises(KeyError, np.lexsort, BuggySequence())
  
      def test_lexsort_zerolen_custom_strides(self):
          # Ticket #14228
          xs = np.array([], dtype='i8')
          assert xs.strides == (8,)
          assert np.lexsort((xs,)).shape[0] == 0 # Works
  
          xs.strides = (16,)
          assert np.lexsort((xs,)).shape[0] == 0 # Was: MemoryError
  
      def test_lexsort_zerolen_custom_strides_2d(self):
          xs = np.array([], dtype='i8')
  
          xs.shape = (0, 2)
          xs.strides = (16, 16)
          assert np.lexsort((xs,), axis=0).shape[0] == 0
  
          xs.shape = (2, 0)
          xs.strides = (16, 16)
          assert np.lexsort((xs,), axis=0).shape[0] == 2
  
      def test_lexsort_invalid_axis(self):
          assert_raises(np.AxisError, np.lexsort, (np.arange(1),), axis=2)
          assert_raises(np.AxisError, np.lexsort, (np.array([]),), axis=1)
          assert_raises(np.AxisError, np.lexsort, (np.array(1),), axis=10)
  
      def test_lexsort_zerolen_element(self):
          dt = np.dtype([])  # a void dtype with no fields
          xs = np.empty(4, dt)
  
          assert np.lexsort((xs,)).shape[0] == xs.shape[0]
  
      def test_pickle_py2_bytes_encoding(self):
          # Check that arrays and scalars pickled on Py2 are
          # unpickleable on Py3 using encoding='bytes'
  
          test_data = [
              # (original, py2_pickle)
              (np.unicode_('\u6f2c'),
               b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
               b"(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\n"
               b"I0\ntp6\nbS',o\\x00\\x00'\np7\ntp8\nRp9\n."),
  
              (np.array([9e123], dtype=np.float64),
               b"cnumpy.core.multiarray\n_reconstruct\np0\n(cnumpy\nndarray\n"
               b"p1\n(I0\ntp2\nS'b'\np3\ntp4\nRp5\n(I1\n(I1\ntp6\ncnumpy\ndtype\n"
               b"p7\n(S'f8'\np8\nI0\nI1\ntp9\nRp10\n(I3\nS'<'\np11\nNNNI-1\nI-1\n"
               b"I0\ntp12\nbI00\nS'O\\x81\\xb7Z\\xaa:\\xabY'\np13\ntp14\nb."),
  
              (np.array([(9e123,)], dtype=[('name', float)]),
               b"cnumpy.core.multiarray\n_reconstruct\np0\n(cnumpy\nndarray\np1\n"
               b"(I0\ntp2\nS'b'\np3\ntp4\nRp5\n(I1\n(I1\ntp6\ncnumpy\ndtype\np7\n"
               b"(S'V8'\np8\nI0\nI1\ntp9\nRp10\n(I3\nS'|'\np11\nN(S'name'\np12\ntp13\n"
               b"(dp14\ng12\n(g7\n(S'f8'\np15\nI0\nI1\ntp16\nRp17\n(I3\nS'<'\np18\nNNNI-1\n"
               b"I-1\nI0\ntp19\nbI0\ntp20\nsI8\nI1\nI0\ntp21\n"
               b"bI00\nS'O\\x81\\xb7Z\\xaa:\\xabY'\np22\ntp23\nb."),
          ]
  
          for original, data in test_data:
              result = pickle.loads(data, encoding='bytes')
              assert_equal(result, original)
  
              if isinstance(result, np.ndarray) and result.dtype.names is not None:
                  for name in result.dtype.names:
                      assert_(isinstance(name, str))
  
      def test_pickle_dtype(self):
          # Ticket #251
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              pickle.dumps(float, protocol=proto)
  
      def test_swap_real(self):
          # Ticket #265
          assert_equal(np.arange(4, dtype='>c8').imag.max(), 0.0)
          assert_equal(np.arange(4, dtype='<c8').imag.max(), 0.0)
          assert_equal(np.arange(4, dtype='>c8').real.max(), 3.0)
          assert_equal(np.arange(4, dtype='<c8').real.max(), 3.0)
  
      def test_object_array_from_list(self):
          # Ticket #270
          assert_(np.array([1, 'A', None]).shape == (3,))
  
      def test_multiple_assign(self):
          # Ticket #273
          a = np.zeros((3, 1), int)
          a[[1, 2]] = 1
  
      def test_empty_array_type(self):
          assert_equal(np.array([]).dtype, np.zeros(0).dtype)
  
      def test_void_copyswap(self):
          dt = np.dtype([('one', '<i4'), ('two', '<i4')])
          x = np.array((1, 2), dtype=dt)
          x = x.byteswap()
          assert_(x['one'] > 1 and x['two'] > 2)
  
      def test_method_args(self):
          # Make sure methods and functions have same default axis
          # keyword and arguments
          funcs1 = ['argmax', 'argmin', 'sum', ('product', 'prod'),
                   ('sometrue', 'any'),
                   ('alltrue', 'all'), 'cumsum', ('cumproduct', 'cumprod'),
                   'ptp', 'cumprod', 'prod', 'std', 'var', 'mean',
                   'round', 'min', 'max', 'argsort', 'sort']
          funcs2 = ['compress', 'take', 'repeat']
  
          for func in funcs1:
              arr = np.random.rand(8, 7)
              arr2 = arr.copy()
              if isinstance(func, tuple):
                  func_meth = func[1]
                  func = func[0]
              else:
                  func_meth = func
              res1 = getattr(arr, func_meth)()
              res2 = getattr(np, func)(arr2)
              if res1 is None:
                  res1 = arr
  
              if res1.dtype.kind in 'uib':
                  assert_((res1 == res2).all(), func)
              else:
                  assert_(abs(res1-res2).max() < 1e-8, func)
  
          for func in funcs2:
              arr1 = np.random.rand(8, 7)
              arr2 = np.random.rand(8, 7)
              res1 = None
              if func == 'compress':
                  arr1 = arr1.ravel()
                  res1 = getattr(arr2, func)(arr1)
              else:
                  arr2 = (15*arr2).astype(int).ravel()
              if res1 is None:
                  res1 = getattr(arr1, func)(arr2)
              res2 = getattr(np, func)(arr1, arr2)
              assert_(abs(res1-res2).max() < 1e-8, func)
  
      def test_mem_lexsort_strings(self):
          # Ticket #298
          lst = ['abc', 'cde', 'fgh']
          np.lexsort((lst,))
  
      def test_fancy_index(self):
          # Ticket #302
          x = np.array([1, 2])[np.array([0])]
          assert_equal(x.shape, (1,))
  
      def test_recarray_copy(self):
          # Ticket #312
          dt = [('x', np.int16), ('y', np.float64)]
          ra = np.array([(1, 2.3)], dtype=dt)
          rb = np.rec.array(ra, dtype=dt)
          rb['x'] = 2.
          assert_(ra['x'] != rb['x'])
  
      def test_rec_fromarray(self):
          # Ticket #322
          x1 = np.array([[1, 2], [3, 4], [5, 6]])
          x2 = np.array(['a', 'dd', 'xyz'])
          x3 = np.array([1.1, 2, 3])
          np.rec.fromarrays([x1, x2, x3], formats="(2,)i4,a3,f8")
  
      def test_object_array_assign(self):
          x = np.empty((2, 2), object)
          x.flat[2] = (1, 2, 3)
          assert_equal(x.flat[2], (1, 2, 3))
  
      def test_ndmin_float64(self):
          # Ticket #324
          x = np.array([1, 2, 3], dtype=np.float64)
          assert_equal(np.array(x, dtype=np.float32, ndmin=2).ndim, 2)
          assert_equal(np.array(x, dtype=np.float64, ndmin=2).ndim, 2)
  
      def test_ndmin_order(self):
          # Issue #465 and related checks
          assert_(np.array([1, 2], order='C', ndmin=3).flags.c_contiguous)
          assert_(np.array([1, 2], order='F', ndmin=3).flags.f_contiguous)
          assert_(np.array(np.ones((2, 2), order='F'), ndmin=3).flags.f_contiguous)
          assert_(np.array(np.ones((2, 2), order='C'), ndmin=3).flags.c_contiguous)
  
      def test_mem_axis_minimization(self):
          # Ticket #327
          data = np.arange(5)
          data = np.add.outer(data, data)
  
      def test_mem_float_imag(self):
          # Ticket #330
          np.float64(1.0).imag
  
      def test_dtype_tuple(self):
          # Ticket #334
          assert_(np.dtype('i4') == np.dtype(('i4', ())))
  
      def test_dtype_posttuple(self):
          # Ticket #335
          np.dtype([('col1', '()i4')])
  
      def test_numeric_carray_compare(self):
          # Ticket #341
          assert_equal(np.array(['X'], 'c'), b'X')
  
      def test_string_array_size(self):
          # Ticket #342
          assert_raises(ValueError,
                                np.array, [['X'], ['X', 'X', 'X']], '|S1')
  
      def test_dtype_repr(self):
          # Ticket #344
          dt1 = np.dtype(('uint32', 2))
          dt2 = np.dtype(('uint32', (2,)))
          assert_equal(dt1.__repr__(), dt2.__repr__())
  
      def test_reshape_order(self):
          # Make sure reshape order works.
          a = np.arange(6).reshape(2, 3, order='F')
          assert_equal(a, [[0, 2, 4], [1, 3, 5]])
          a = np.array([[1, 2], [3, 4], [5, 6], [7, 8]])
          b = a[:, 1]
          assert_equal(b.reshape(2, 2, order='F'), [[2, 6], [4, 8]])
  
      def test_reshape_zero_strides(self):
          # Issue #380, test reshaping of zero strided arrays
          a = np.ones(1)
          a = np.lib.stride_tricks.as_strided(a, shape=(5,), strides=(0,))
          assert_(a.reshape(5, 1).strides[0] == 0)
  
      def test_reshape_zero_size(self):
          # GitHub Issue #2700, setting shape failed for 0-sized arrays
          a = np.ones((0, 2))
          a.shape = (-1, 2)
  
      # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides.
      # With NPY_RELAXED_STRIDES_CHECKING the test becomes superfluous.
      @pytest.mark.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max,
                          reason="Using relaxed stride checking")
      def test_reshape_trailing_ones_strides(self):
          # GitHub issue gh-2949, bad strides for trailing ones of new shape
          a = np.zeros(12, dtype=np.int32)[::2]  # not contiguous
          strides_c = (16, 8, 8, 8)
          strides_f = (8, 24, 48, 48)
          assert_equal(a.reshape(3, 2, 1, 1).strides, strides_c)
          assert_equal(a.reshape(3, 2, 1, 1, order='F').strides, strides_f)
          assert_equal(np.array(0, dtype=np.int32).reshape(1, 1).strides, (4, 4))
  
      def test_repeat_discont(self):
          # Ticket #352
          a = np.arange(12).reshape(4, 3)[:, 2]
          assert_equal(a.repeat(3), [2, 2, 2, 5, 5, 5, 8, 8, 8, 11, 11, 11])
  
      def test_array_index(self):
          # Make sure optimization is not called in this case.
          a = np.array([1, 2, 3])
          a2 = np.array([[1, 2, 3]])
          assert_equal(a[np.where(a == 3)], a2[np.where(a2 == 3)])
  
      def test_object_argmax(self):
          a = np.array([1, 2, 3], dtype=object)
          assert_(a.argmax() == 2)
  
      def test_recarray_fields(self):
          # Ticket #372
          dt0 = np.dtype([('f0', 'i4'), ('f1', 'i4')])
          dt1 = np.dtype([('f0', 'i8'), ('f1', 'i8')])
          for a in [np.array([(1, 2), (3, 4)], "i4,i4"),
                    np.rec.array([(1, 2), (3, 4)], "i4,i4"),
                    np.rec.array([(1, 2), (3, 4)]),
                    np.rec.fromarrays([(1, 2), (3, 4)], "i4,i4"),
                    np.rec.fromarrays([(1, 2), (3, 4)])]:
              assert_(a.dtype in [dt0, dt1])
  
      def test_random_shuffle(self):
          # Ticket #374
          a = np.arange(5).reshape((5, 1))
          b = a.copy()
          np.random.shuffle(b)
          assert_equal(np.sort(b, axis=0), a)
  
      def test_refcount_vdot(self):
          # Changeset #3443
          _assert_valid_refcount(np.vdot)
  
      def test_startswith(self):
          ca = np.char.array(['Hi', 'There'])
          assert_equal(ca.startswith('H'), [True, False])
  
      def test_noncommutative_reduce_accumulate(self):
          # Ticket #413
          tosubtract = np.arange(5)
          todivide = np.array([2.0, 0.5, 0.25])
          assert_equal(np.subtract.reduce(tosubtract), -10)
          assert_equal(np.divide.reduce(todivide), 16.0)
          assert_array_equal(np.subtract.accumulate(tosubtract),
              np.array([0, -1, -3, -6, -10]))
          assert_array_equal(np.divide.accumulate(todivide),
              np.array([2., 4., 16.]))
  
      def test_convolve_empty(self):
          # Convolve should raise an error for empty input array.
          assert_raises(ValueError, np.convolve, [], [1])
          assert_raises(ValueError, np.convolve, [1], [])
  
      def test_multidim_byteswap(self):
          # Ticket #449
          r = np.array([(1, (0, 1, 2))], dtype="i2,3i2")
          assert_array_equal(r.byteswap(),
                             np.array([(256, (0, 256, 512))], r.dtype))
  
      def test_string_NULL(self):
          # Changeset 3557
          assert_equal(np.array("a\x00\x0b\x0c\x00").item(),
                       'a\x00\x0b\x0c')
  
      def test_junk_in_string_fields_of_recarray(self):
          # Ticket #483
          r = np.array([[b'abc']], dtype=[('var1', '|S20')])
          assert_(asbytes(r['var1'][0][0]) == b'abc')
  
      def test_take_output(self):
          # Ensure that 'take' honours output parameter.
          x = np.arange(12).reshape((3, 4))
          a = np.take(x, [0, 2], axis=1)
          b = np.zeros_like(a)
          np.take(x, [0, 2], axis=1, out=b)
          assert_array_equal(a, b)
  
      def test_take_object_fail(self):
          # Issue gh-3001
          d = 123.
          a = np.array([d, 1], dtype=object)
          if HAS_REFCOUNT:
              ref_d = sys.getrefcount(d)
          try:
              a.take([0, 100])
          except IndexError:
              pass
          if HAS_REFCOUNT:
              assert_(ref_d == sys.getrefcount(d))
  
      def test_array_str_64bit(self):
          # Ticket #501
          s = np.array([1, np.nan], dtype=np.float64)
          with np.errstate(all='raise'):
              np.array_str(s)  # Should succeed
  
      def test_frompyfunc_endian(self):
          # Ticket #503
          from math import radians
          uradians = np.frompyfunc(radians, 1, 1)
          big_endian = np.array([83.4, 83.5], dtype='>f8')
          little_endian = np.array([83.4, 83.5], dtype='<f8')
          assert_almost_equal(uradians(big_endian).astype(float),
                              uradians(little_endian).astype(float))
  
      def test_mem_string_arr(self):
          # Ticket #514
          s = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
          t = []
          np.hstack((t, s))
  
      def test_arr_transpose(self):
          # Ticket #516
          x = np.random.rand(*(2,)*16)
          x.transpose(list(range(16)))  # Should succeed
  
      def test_string_mergesort(self):
          # Ticket #540
          x = np.array(['a']*32)
          assert_array_equal(x.argsort(kind='m'), np.arange(32))
  
      def test_argmax_byteorder(self):
          # Ticket #546
          a = np.arange(3, dtype='>f')
          assert_(a[a.argmax()] == a.max())
  
      def test_rand_seed(self):
          # Ticket #555
          for l in np.arange(4):
              np.random.seed(l)
  
      def test_mem_deallocation_leak(self):
          # Ticket #562
          a = np.zeros(5, dtype=float)
          b = np.array(a, dtype=float)
          del a, b
  
      def test_mem_on_invalid_dtype(self):
          "Ticket #583"
          assert_raises(ValueError, np.fromiter, [['12', ''], ['13', '']], str)
  
      def test_dot_negative_stride(self):
          # Ticket #588
          x = np.array([[1, 5, 25, 125., 625]])
          y = np.array([[20.], [160.], [640.], [1280.], [1024.]])
          z = y[::-1].copy()
          y2 = y[::-1]
          assert_equal(np.dot(x, z), np.dot(x, y2))
  
      def test_object_casting(self):
          # This used to trigger the object-type version of
          # the bitwise_or operation, because float64 -> object
          # casting succeeds
          def rs():
              x = np.ones([484, 286])
              y = np.zeros([484, 286])
              x |= y
  
          assert_raises(TypeError, rs)
  
      def test_unicode_scalar(self):
          # Ticket #600
          x = np.array(["DROND", "DROND1"], dtype="U6")
          el = x[1]
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              new = pickle.loads(pickle.dumps(el, protocol=proto))
              assert_equal(new, el)
  
      def test_arange_non_native_dtype(self):
          # Ticket #616
          for T in ('>f4', '<f4'):
              dt = np.dtype(T)
              assert_equal(np.arange(0, dtype=dt).dtype, dt)
              assert_equal(np.arange(0.5, dtype=dt).dtype, dt)
              assert_equal(np.arange(5, dtype=dt).dtype, dt)
  
      def test_bool_flat_indexing_invalid_nr_elements(self):
          s = np.ones(10, dtype=float)
          x = np.array((15,), dtype=float)
  
          def ia(x, s, v):
              x[(s > 0)] = v
  
          assert_raises(IndexError, ia, x, s, np.zeros(9, dtype=float))
          assert_raises(IndexError, ia, x, s, np.zeros(11, dtype=float))
  
          # Old special case (different code path):
          assert_raises(ValueError, ia, x.flat, s, np.zeros(9, dtype=float))
          assert_raises(ValueError, ia, x.flat, s, np.zeros(11, dtype=float))
  
      def test_mem_scalar_indexing(self):
          # Ticket #603
          x = np.array([0], dtype=float)
          index = np.array(0, dtype=np.int32)
          x[index]
  
      def test_binary_repr_0_width(self):
          assert_equal(np.binary_repr(0, width=3), '000')
  
      def test_fromstring(self):
          assert_equal(np.fromstring("12:09:09", dtype=int, sep=":"),
                       [12, 9, 9])
  
      def test_searchsorted_variable_length(self):
          x = np.array(['a', 'aa', 'b'])
          y = np.array(['d', 'e'])
          assert_equal(x.searchsorted(y), [3, 3])
  
      def test_string_argsort_with_zeros(self):
          # Check argsort for strings containing zeros.
          x = np.frombuffer(b"\x00\x02\x00\x01", dtype="|S2")
          assert_array_equal(x.argsort(kind='m'), np.array([1, 0]))
          assert_array_equal(x.argsort(kind='q'), np.array([1, 0]))
  
      def test_string_sort_with_zeros(self):
          # Check sort for strings containing zeros.
          x = np.frombuffer(b"\x00\x02\x00\x01", dtype="|S2")
          y = np.frombuffer(b"\x00\x01\x00\x02", dtype="|S2")
          assert_array_equal(np.sort(x, kind="q"), y)
  
      def test_copy_detection_zero_dim(self):
          # Ticket #658
          np.indices((0, 3, 4)).T.reshape(-1, 3)
  
      def test_flat_byteorder(self):
          # Ticket #657
          x = np.arange(10)
          assert_array_equal(x.astype('>i4'), x.astype('<i4').flat[:])
          assert_array_equal(x.astype('>i4').flat[:], x.astype('<i4'))
  
      def test_sign_bit(self):
          x = np.array([0, -0.0, 0])
          assert_equal(str(np.abs(x)), '[0. 0. 0.]')
  
      def test_flat_index_byteswap(self):
          for dt in (np.dtype('<i4'), np.dtype('>i4')):
              x = np.array([-1, 0, 1], dtype=dt)
              assert_equal(x.flat[0].dtype, x[0].dtype)
  
      def test_copy_detection_corner_case(self):
          # Ticket #658
          np.indices((0, 3, 4)).T.reshape(-1, 3)
  
      # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides.
      # With NPY_RELAXED_STRIDES_CHECKING the test becomes superfluous,
      # 0-sized reshape itself is tested elsewhere.
      @pytest.mark.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max,
                          reason="Using relaxed stride checking")
      def test_copy_detection_corner_case2(self):
          # Ticket #771: strides are not set correctly when reshaping 0-sized
          # arrays
          b = np.indices((0, 3, 4)).T.reshape(-1, 3)
          assert_equal(b.strides, (3 * b.itemsize, b.itemsize))
  
      def test_object_array_refcounting(self):
          # Ticket #633
          if not hasattr(sys, 'getrefcount'):
              return
  
          # NB. this is probably CPython-specific
  
          cnt = sys.getrefcount
  
          a = object()
          b = object()
          c = object()
  
          cnt0_a = cnt(a)
          cnt0_b = cnt(b)
          cnt0_c = cnt(c)
  
          # -- 0d -> 1-d broadcast slice assignment
  
          arr = np.zeros(5, dtype=np.object_)
  
          arr[:] = a
          assert_equal(cnt(a), cnt0_a + 5)
  
          arr[:] = b
          assert_equal(cnt(a), cnt0_a)
          assert_equal(cnt(b), cnt0_b + 5)
  
          arr[:2] = c
          assert_equal(cnt(b), cnt0_b + 3)
          assert_equal(cnt(c), cnt0_c + 2)
  
          del arr
  
          # -- 1-d -> 2-d broadcast slice assignment
  
          arr = np.zeros((5, 2), dtype=np.object_)
          arr0 = np.zeros(2, dtype=np.object_)
  
          arr0[0] = a
          assert_(cnt(a) == cnt0_a + 1)
          arr0[1] = b
          assert_(cnt(b) == cnt0_b + 1)
  
          arr[:, :] = arr0
          assert_(cnt(a) == cnt0_a + 6)
          assert_(cnt(b) == cnt0_b + 6)
  
          arr[:, 0] = None
          assert_(cnt(a) == cnt0_a + 1)
  
          del arr, arr0
  
          # -- 2-d copying + flattening
  
          arr = np.zeros((5, 2), dtype=np.object_)
  
          arr[:, 0] = a
          arr[:, 1] = b
          assert_(cnt(a) == cnt0_a + 5)
          assert_(cnt(b) == cnt0_b + 5)
  
          arr2 = arr.copy()
          assert_(cnt(a) == cnt0_a + 10)
          assert_(cnt(b) == cnt0_b + 10)
  
          arr2 = arr[:, 0].copy()
          assert_(cnt(a) == cnt0_a + 10)
          assert_(cnt(b) == cnt0_b + 5)
  
          arr2 = arr.flatten()
          assert_(cnt(a) == cnt0_a + 10)
          assert_(cnt(b) == cnt0_b + 10)
  
          del arr, arr2
  
          # -- concatenate, repeat, take, choose
  
          arr1 = np.zeros((5, 1), dtype=np.object_)
          arr2 = np.zeros((5, 1), dtype=np.object_)
  
          arr1[...] = a
          arr2[...] = b
          assert_(cnt(a) == cnt0_a + 5)
          assert_(cnt(b) == cnt0_b + 5)
  
          tmp = np.concatenate((arr1, arr2))
          assert_(cnt(a) == cnt0_a + 5 + 5)
          assert_(cnt(b) == cnt0_b + 5 + 5)
  
          tmp = arr1.repeat(3, axis=0)
          assert_(cnt(a) == cnt0_a + 5 + 3*5)
  
          tmp = arr1.take([1, 2, 3], axis=0)
          assert_(cnt(a) == cnt0_a + 5 + 3)
  
          x = np.array([[0], [1], [0], [1], [1]], int)
          tmp = x.choose(arr1, arr2)
          assert_(cnt(a) == cnt0_a + 5 + 2)
          assert_(cnt(b) == cnt0_b + 5 + 3)
  
          del tmp  # Avoid pyflakes unused variable warning
  
      def test_mem_custom_float_to_array(self):
          # Ticket 702
          class MyFloat:
              def __float__(self):
                  return 1.0
  
          tmp = np.atleast_1d([MyFloat()])
          tmp.astype(float)  # Should succeed
  
      def test_object_array_refcount_self_assign(self):
          # Ticket #711
          class VictimObject:
              deleted = False
  
              def __del__(self):
                  self.deleted = True
  
          d = VictimObject()
          arr = np.zeros(5, dtype=np.object_)
          arr[:] = d
          del d
          arr[:] = arr  # refcount of 'd' might hit zero here
          assert_(not arr[0].deleted)
          arr[:] = arr  # trying to induce a segfault by doing it again...
          assert_(not arr[0].deleted)
  
      def test_mem_fromiter_invalid_dtype_string(self):
          x = [1, 2, 3]
          assert_raises(ValueError,
                                np.fromiter, [xi for xi in x], dtype='S')
  
      def test_reduce_big_object_array(self):
          # Ticket #713
          oldsize = np.setbufsize(10*16)
          a = np.array([None]*161, object)
          assert_(not np.any(a))
          np.setbufsize(oldsize)
  
      def test_mem_0d_array_index(self):
          # Ticket #714
          np.zeros(10)[np.array(0)]
  
      def test_nonnative_endian_fill(self):
          # Non-native endian arrays were incorrectly filled with scalars
          # before r5034.
          if sys.byteorder == 'little':
              dtype = np.dtype('>i4')
          else:
              dtype = np.dtype('<i4')
          x = np.empty([1], dtype=dtype)
          x.fill(1)
          assert_equal(x, np.array([1], dtype=dtype))
  
      def test_dot_alignment_sse2(self):
          # Test for ticket #551, changeset r5140
          x = np.zeros((30, 40))
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              y = pickle.loads(pickle.dumps(x, protocol=proto))
              # y is now typically not aligned on a 8-byte boundary
              z = np.ones((1, y.shape[0]))
              # This shouldn't cause a segmentation fault:
              np.dot(z, y)
  
      def test_astype_copy(self):
          # Ticket #788, changeset r5155
          # The test data file was generated by scipy.io.savemat.
          # The dtype is float64, but the isbuiltin attribute is 0.
          data_dir = path.join(path.dirname(__file__), 'data')
          filename = path.join(data_dir, "astype_copy.pkl")
          with open(filename, 'rb') as f:
              xp = pickle.load(f, encoding='latin1')
          xpd = xp.astype(np.float64)
          assert_((xp.__array_interface__['data'][0] !=
                  xpd.__array_interface__['data'][0]))
  
      def test_compress_small_type(self):
          # Ticket #789, changeset 5217.
          # compress with out argument segfaulted if cannot cast safely
          import numpy as np
          a = np.array([[1, 2], [3, 4]])
          b = np.zeros((2, 1), dtype=np.single)
          try:
              a.compress([True, False], axis=1, out=b)
              raise AssertionError("compress with an out which cannot be "
                                   "safely casted should not return "
                                   "successfully")
          except TypeError:
              pass
  
      def test_attributes(self):
          # Ticket #791
          class TestArray(np.ndarray):
              def __new__(cls, data, info):
                  result = np.array(data)
                  result = result.view(cls)
                  result.info = info
                  return result
  
              def __array_finalize__(self, obj):
                  self.info = getattr(obj, 'info', '')
  
          dat = TestArray([[1, 2, 3, 4], [5, 6, 7, 8]], 'jubba')
          assert_(dat.info == 'jubba')
          dat.resize((4, 2))
          assert_(dat.info == 'jubba')
          dat.sort()
          assert_(dat.info == 'jubba')
          dat.fill(2)
          assert_(dat.info == 'jubba')
          dat.put([2, 3, 4], [6, 3, 4])
          assert_(dat.info == 'jubba')
          dat.setfield(4, np.int32, 0)
          assert_(dat.info == 'jubba')
          dat.setflags()
          assert_(dat.info == 'jubba')
          assert_(dat.all(1).info == 'jubba')
          assert_(dat.any(1).info == 'jubba')
          assert_(dat.argmax(1).info == 'jubba')
          assert_(dat.argmin(1).info == 'jubba')
          assert_(dat.argsort(1).info == 'jubba')
          assert_(dat.astype(TestArray).info == 'jubba')
          assert_(dat.byteswap().info == 'jubba')
          assert_(dat.clip(2, 7).info == 'jubba')
          assert_(dat.compress([0, 1, 1]).info == 'jubba')
          assert_(dat.conj().info == 'jubba')
          assert_(dat.conjugate().info == 'jubba')
          assert_(dat.copy().info == 'jubba')
          dat2 = TestArray([2, 3, 1, 0], 'jubba')
          choices = [[0, 1, 2, 3], [10, 11, 12, 13],
                     [20, 21, 22, 23], [30, 31, 32, 33]]
          assert_(dat2.choose(choices).info == 'jubba')
          assert_(dat.cumprod(1).info == 'jubba')
          assert_(dat.cumsum(1).info == 'jubba')
          assert_(dat.diagonal().info == 'jubba')
          assert_(dat.flatten().info == 'jubba')
          assert_(dat.getfield(np.int32, 0).info == 'jubba')
          assert_(dat.imag.info == 'jubba')
          assert_(dat.max(1).info == 'jubba')
          assert_(dat.mean(1).info == 'jubba')
          assert_(dat.min(1).info == 'jubba')
          assert_(dat.newbyteorder().info == 'jubba')
          assert_(dat.prod(1).info == 'jubba')
          assert_(dat.ptp(1).info == 'jubba')
          assert_(dat.ravel().info == 'jubba')
          assert_(dat.real.info == 'jubba')
          assert_(dat.repeat(2).info == 'jubba')
          assert_(dat.reshape((2, 4)).info == 'jubba')
          assert_(dat.round().info == 'jubba')
          assert_(dat.squeeze().info == 'jubba')
          assert_(dat.std(1).info == 'jubba')
          assert_(dat.sum(1).info == 'jubba')
          assert_(dat.swapaxes(0, 1).info == 'jubba')
          assert_(dat.take([2, 3, 5]).info == 'jubba')
          assert_(dat.transpose().info == 'jubba')
          assert_(dat.T.info == 'jubba')
          assert_(dat.var(1).info == 'jubba')
          assert_(dat.view(TestArray).info == 'jubba')
          # These methods do not preserve subclasses
          assert_(type(dat.nonzero()[0]) is np.ndarray)
          assert_(type(dat.nonzero()[1]) is np.ndarray)
  
      def test_recarray_tolist(self):
          # Ticket #793, changeset r5215
          # Comparisons fail for NaN, so we can't use random memory
          # for the test.
          buf = np.zeros(40, dtype=np.int8)
          a = np.recarray(2, formats="i4,f8,f8", names="id,x,y", buf=buf)
          b = a.tolist()
          assert_( a[0].tolist() == b[0])
          assert_( a[1].tolist() == b[1])
  
      def test_nonscalar_item_method(self):
          # Make sure that .item() fails graciously when it should
          a = np.arange(5)
          assert_raises(ValueError, a.item)
  
      def test_char_array_creation(self):
          a = np.array('123', dtype='c')
          b = np.array([b'1', b'2', b'3'])
          assert_equal(a, b)
  
      def test_unaligned_unicode_access(self):
          # Ticket #825
          for i in range(1, 9):
              msg = 'unicode offset: %d chars' % i
              t = np.dtype([('a', 'S%d' % i), ('b', 'U2')])
              x = np.array([(b'a', u'b')], dtype=t)
              assert_equal(str(x), "[(b'a', 'b')]", err_msg=msg)
  
      def test_sign_for_complex_nan(self):
          # Ticket 794.
          with np.errstate(invalid='ignore'):
              C = np.array([-np.inf, -2+1j, 0, 2-1j, np.inf, np.nan])
              have = np.sign(C)
              want = np.array([-1+0j, -1+0j, 0+0j, 1+0j, 1+0j, np.nan])
              assert_equal(have, want)
  
      def test_for_equal_names(self):
          # Ticket #674
          dt = np.dtype([('foo', float), ('bar', float)])
          a = np.zeros(10, dt)
          b = list(a.dtype.names)
          b[0] = "notfoo"
          a.dtype.names = b
          assert_(a.dtype.names[0] == "notfoo")
          assert_(a.dtype.names[1] == "bar")
  
      def test_for_object_scalar_creation(self):
          # Ticket #816
          a = np.object_()
          b = np.object_(3)
          b2 = np.object_(3.0)
          c = np.object_([4, 5])
          d = np.object_([None, {}, []])
          assert_(a is None)
          assert_(type(b) is int)
          assert_(type(b2) is float)
          assert_(type(c) is np.ndarray)
          assert_(c.dtype == object)
          assert_(d.dtype == object)
  
      def test_array_resize_method_system_error(self):
          # Ticket #840 - order should be an invalid keyword.
          x = np.array([[0, 1], [2, 3]])
          assert_raises(TypeError, x.resize, (2, 2), order='C')
  
      def test_for_zero_length_in_choose(self):
          "Ticket #882"
          a = np.array(1)
          assert_raises(ValueError, lambda x: x.choose([]), a)
  
      def test_array_ndmin_overflow(self):
          "Ticket #947."
          assert_raises(ValueError, lambda: np.array([1], ndmin=33))
  
      def test_void_scalar_with_titles(self):
          # No ticket
          data = [('john', 4), ('mary', 5)]
          dtype1 = [(('source:yy', 'name'), 'O'), (('source:xx', 'id'), int)]
          arr = np.array(data, dtype=dtype1)
          assert_(arr[0][0] == 'john')
          assert_(arr[0][1] == 4)
  
      def test_void_scalar_constructor(self):
          #Issue #1550
  
          #Create test string data, construct void scalar from data and assert
          #that void scalar contains original data.
          test_string = np.array("test")
          test_string_void_scalar = np.core.multiarray.scalar(
              np.dtype(("V", test_string.dtype.itemsize)), test_string.tobytes())
  
          assert_(test_string_void_scalar.view(test_string.dtype) == test_string)
  
          #Create record scalar, construct from data and assert that
          #reconstructed scalar is correct.
          test_record = np.ones((), "i,i")
          test_record_void_scalar = np.core.multiarray.scalar(
              test_record.dtype, test_record.tobytes())
  
          assert_(test_record_void_scalar == test_record)
  
          # Test pickle and unpickle of void and record scalars
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              assert_(pickle.loads(
                  pickle.dumps(test_string, protocol=proto)) == test_string)
              assert_(pickle.loads(
                  pickle.dumps(test_record, protocol=proto)) == test_record)
  
      @_no_tracing
      def test_blasdot_uninitialized_memory(self):
          # Ticket #950
          for m in [0, 1, 2]:
              for n in [0, 1, 2]:
                  for k in range(3):
                      # Try to ensure that x->data contains non-zero floats
                      x = np.array([123456789e199], dtype=np.float64)
                      if IS_PYPY:
                          x.resize((m, 0), refcheck=False)
                      else:
                          x.resize((m, 0))
                      y = np.array([123456789e199], dtype=np.float64)
                      if IS_PYPY:
                          y.resize((0, n), refcheck=False)
                      else:
                          y.resize((0, n))
  
                      # `dot` should just return zero (m, n) matrix
                      z = np.dot(x, y)
                      assert_(np.all(z == 0))
                      assert_(z.shape == (m, n))
  
      def test_zeros(self):
          # Regression test for #1061.
          # Set a size which cannot fit into a 64 bits signed integer
          sz = 2 ** 64
          with assert_raises_regex(ValueError,
                                   'Maximum allowed dimension exceeded'):
              np.empty(sz)
  
      def test_huge_arange(self):
          # Regression test for #1062.
          # Set a size which cannot fit into a 64 bits signed integer
          sz = 2 ** 64
          with assert_raises_regex(ValueError,
                                   'Maximum allowed size exceeded'):
              np.arange(sz)
              assert_(np.size == sz)
  
      def test_fromiter_bytes(self):
          # Ticket #1058
          a = np.fromiter(list(range(10)), dtype='b')
          b = np.fromiter(list(range(10)), dtype='B')
          assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
          assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
  
      def test_array_from_sequence_scalar_array(self):
          # Ticket #1078: segfaults when creating an array with a sequence of
          # 0d arrays.
          a = np.array((np.ones(2), np.array(2)), dtype=object)
          assert_equal(a.shape, (2,))
          assert_equal(a.dtype, np.dtype(object))
          assert_equal(a[0], np.ones(2))
          assert_equal(a[1], np.array(2))
  
          a = np.array(((1,), np.array(1)), dtype=object)
          assert_equal(a.shape, (2,))
          assert_equal(a.dtype, np.dtype(object))
          assert_equal(a[0], (1,))
          assert_equal(a[1], np.array(1))
  
      def test_array_from_sequence_scalar_array2(self):
          # Ticket #1081: weird array with strange input...
          t = np.array([np.array([]), np.array(0, object)], dtype=object)
          assert_equal(t.shape, (2,))
          assert_equal(t.dtype, np.dtype(object))
  
      def test_array_too_big(self):
          # Ticket #1080.
          assert_raises(ValueError, np.zeros, [975]*7, np.int8)
          assert_raises(ValueError, np.zeros, [26244]*5, np.int8)
  
      def test_dtype_keyerrors_(self):
          # Ticket #1106.
          dt = np.dtype([('f1', np.uint)])
          assert_raises(KeyError, dt.__getitem__, "f2")
          assert_raises(IndexError, dt.__getitem__, 1)
          assert_raises(TypeError, dt.__getitem__, 0.0)
  
      def test_lexsort_buffer_length(self):
          # Ticket #1217, don't segfault.
          a = np.ones(100, dtype=np.int8)
          b = np.ones(100, dtype=np.int32)
          i = np.lexsort((a[::-1], b))
          assert_equal(i, np.arange(100, dtype=int))
  
      def test_object_array_to_fixed_string(self):
          # Ticket #1235.
          a = np.array(['abcdefgh', 'ijklmnop'], dtype=np.object_)
          b = np.array(a, dtype=(np.str_, 8))
          assert_equal(a, b)
          c = np.array(a, dtype=(np.str_, 5))
          assert_equal(c, np.array(['abcde', 'ijklm']))
          d = np.array(a, dtype=(np.str_, 12))
          assert_equal(a, d)
          e = np.empty((2, ), dtype=(np.str_, 8))
          e[:] = a[:]
          assert_equal(a, e)
  
      def test_unicode_to_string_cast(self):
          # Ticket #1240.
          a = np.array([[u'abc', u'\u03a3'],
                        [u'asdf', u'erw']],
                       dtype='U')
          assert_raises(UnicodeEncodeError, np.array, a, 'S4')
  
      def test_unicode_to_string_cast_error(self):
          # gh-15790
          a = np.array([u'\x80'] * 129, dtype='U3')
          assert_raises(UnicodeEncodeError, np.array, a, 'S')
          b = a.reshape(3, 43)[:-1, :-1]
          assert_raises(UnicodeEncodeError, np.array, b, 'S')
  
      def test_mixed_string_unicode_array_creation(self):
          a = np.array(['1234', u'123'])
          assert_(a.itemsize == 16)
          a = np.array([u'123', '1234'])
          assert_(a.itemsize == 16)
          a = np.array(['1234', u'123', '12345'])
          assert_(a.itemsize == 20)
          a = np.array([u'123', '1234', u'12345'])
          assert_(a.itemsize == 20)
          a = np.array([u'123', '1234', u'1234'])
          assert_(a.itemsize == 16)
  
      def test_misaligned_objects_segfault(self):
          # Ticket #1198 and #1267
          a1 = np.zeros((10,), dtype='O,c')
          a2 = np.array(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], 'S10')
          a1['f0'] = a2
          repr(a1)
          np.argmax(a1['f0'])
          a1['f0'][1] = "FOO"
          a1['f0'] = "FOO"
          np.array(a1['f0'], dtype='S')
          np.nonzero(a1['f0'])
          a1.sort()
          copy.deepcopy(a1)
  
      def test_misaligned_scalars_segfault(self):
          # Ticket #1267
          s1 = np.array(('a', 'Foo'), dtype='c,O')
          s2 = np.array(('b', 'Bar'), dtype='c,O')
          s1['f1'] = s2['f1']
          s1['f1'] = 'Baz'
  
      def test_misaligned_dot_product_objects(self):
          # Ticket #1267
          # This didn't require a fix, but it's worth testing anyway, because
          # it may fail if .dot stops enforcing the arrays to be BEHAVED
          a = np.array([[(1, 'a'), (0, 'a')], [(0, 'a'), (1, 'a')]], dtype='O,c')
          b = np.array([[(4, 'a'), (1, 'a')], [(2, 'a'), (2, 'a')]], dtype='O,c')
          np.dot(a['f0'], b['f0'])
  
      def test_byteswap_complex_scalar(self):
          # Ticket #1259 and gh-441
          for dtype in [np.dtype('<'+t) for t in np.typecodes['Complex']]:
              z = np.array([2.2-1.1j], dtype)
              x = z[0]  # always native-endian
              y = x.byteswap()
              if x.dtype.byteorder == z.dtype.byteorder:
                  # little-endian machine
                  assert_equal(x, np.frombuffer(y.tobytes(), dtype=dtype.newbyteorder()))
              else:
                  # big-endian machine
                  assert_equal(x, np.frombuffer(y.tobytes(), dtype=dtype))
              # double check real and imaginary parts:
              assert_equal(x.real, y.real.byteswap())
              assert_equal(x.imag, y.imag.byteswap())
  
      def test_structured_arrays_with_objects1(self):
          # Ticket #1299
          stra = 'aaaa'
          strb = 'bbbb'
          x = np.array([[(0, stra), (1, strb)]], 'i8,O')
          x[x.nonzero()] = x.ravel()[:1]
          assert_(x[0, 1] == x[0, 0])
  
      @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
      def test_structured_arrays_with_objects2(self):
          # Ticket #1299 second test
          stra = 'aaaa'
          strb = 'bbbb'
          numb = sys.getrefcount(strb)
          numa = sys.getrefcount(stra)
          x = np.array([[(0, stra), (1, strb)]], 'i8,O')
          x[x.nonzero()] = x.ravel()[:1]
          assert_(sys.getrefcount(strb) == numb)
          assert_(sys.getrefcount(stra) == numa + 2)
  
      def test_duplicate_title_and_name(self):
          # Ticket #1254
          dtspec = [(('a', 'a'), 'i'), ('b', 'i')]
          assert_raises(ValueError, np.dtype, dtspec)
  
      def test_signed_integer_division_overflow(self):
          # Ticket #1317.
          def test_type(t):
              min = np.array([np.iinfo(t).min])
              min //= -1
  
          with np.errstate(divide="ignore"):
              for t in (np.int8, np.int16, np.int32, np.int64, int):
                  test_type(t)
  
      def test_buffer_hashlib(self):
          from hashlib import md5
  
          x = np.array([1, 2, 3], dtype=np.dtype('<i4'))
          assert_equal(md5(x).hexdigest(), '2a1dd1e1e59d0a384c26951e316cd7e6')
  
      def test_0d_string_scalar(self):
          # Bug #1436; the following should succeed
          np.asarray('x', '>c')
  
      def test_log1p_compiler_shenanigans(self):
          # Check if log1p is behaving on 32 bit intel systems.
          assert_(np.isfinite(np.log1p(np.exp2(-53))))
  
      def test_fromiter_comparison(self):
          a = np.fromiter(list(range(10)), dtype='b')
          b = np.fromiter(list(range(10)), dtype='B')
          assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
          assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
  
      def test_fromstring_crash(self):
          # Ticket #1345: the following should not cause a crash
          with assert_warns(DeprecationWarning):
              np.fromstring(b'aa, aa, 1.0', sep=',')
  
      def test_ticket_1539(self):
          dtypes = [x for x in np.typeDict.values()
                    if (issubclass(x, np.number)
                        and not issubclass(x, np.timedelta64))]
          a = np.array([], np.bool_)  # not x[0] because it is unordered
          failures = []
  
          for x in dtypes:
              b = a.astype(x)
              for y in dtypes:
                  c = a.astype(y)
                  try:
                      np.dot(b, c)
                  except TypeError:
                      failures.append((x, y))
          if failures:
              raise AssertionError("Failures: %r" % failures)
  
      def test_ticket_1538(self):
          x = np.finfo(np.float32)
          for name in 'eps epsneg max min resolution tiny'.split():
              assert_equal(type(getattr(x, name)), np.float32,
                           err_msg=name)
  
      def test_ticket_1434(self):
          # Check that the out= argument in var and std has an effect
          data = np.array(((1, 2, 3), (4, 5, 6), (7, 8, 9)))
          out = np.zeros((3,))
  
          ret = data.var(axis=1, out=out)
          assert_(ret is out)
          assert_array_equal(ret, data.var(axis=1))
  
          ret = data.std(axis=1, out=out)
          assert_(ret is out)
          assert_array_equal(ret, data.std(axis=1))
  
      def test_complex_nan_maximum(self):
          cnan = complex(0, np.nan)
          assert_equal(np.maximum(1, cnan), cnan)
  
      def test_subclass_int_tuple_assignment(self):
          # ticket #1563
          class Subclass(np.ndarray):
              def __new__(cls, i):
                  return np.ones((i,)).view(cls)
  
          x = Subclass(5)
          x[(0,)] = 2  # shouldn't raise an exception
          assert_equal(x[0], 2)
  
      def test_ufunc_no_unnecessary_views(self):
          # ticket #1548
          class Subclass(np.ndarray):
              pass
          x = np.array([1, 2, 3]).view(Subclass)
          y = np.add(x, x, x)
          assert_equal(id(x), id(y))
  
      @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
      def test_take_refcount(self):
          # ticket #939
          a = np.arange(16, dtype=float)
          a.shape = (4, 4)
          lut = np.ones((5 + 3, 4), float)
          rgba = np.empty(shape=a.shape + (4,), dtype=lut.dtype)
          c1 = sys.getrefcount(rgba)
          try:
              lut.take(a, axis=0, mode='clip', out=rgba)
          except TypeError:
              pass
          c2 = sys.getrefcount(rgba)
          assert_equal(c1, c2)
  
      def test_fromfile_tofile_seeks(self):
          # On Python 3, tofile/fromfile used to get (#1610) the Python
          # file handle out of sync
          f0 = tempfile.NamedTemporaryFile()
          f = f0.file
          f.write(np.arange(255, dtype='u1').tobytes())
  
          f.seek(20)
          ret = np.fromfile(f, count=4, dtype='u1')
          assert_equal(ret, np.array([20, 21, 22, 23], dtype='u1'))
          assert_equal(f.tell(), 24)
  
          f.seek(40)
          np.array([1, 2, 3], dtype='u1').tofile(f)
          assert_equal(f.tell(), 43)
  
          f.seek(40)
          data = f.read(3)
          assert_equal(data, b"\x01\x02\x03")
  
          f.seek(80)
          f.read(4)
          data = np.fromfile(f, dtype='u1', count=4)
          assert_equal(data, np.array([84, 85, 86, 87], dtype='u1'))
  
          f.close()
  
      def test_complex_scalar_warning(self):
          for tp in [np.csingle, np.cdouble, np.clongdouble]:
              x = tp(1+2j)
              assert_warns(np.ComplexWarning, float, x)
              with suppress_warnings() as sup:
                  sup.filter(np.ComplexWarning)
                  assert_equal(float(x), float(x.real))
  
      def test_complex_scalar_complex_cast(self):
          for tp in [np.csingle, np.cdouble, np.clongdouble]:
              x = tp(1+2j)
              assert_equal(complex(x), 1+2j)
  
      def test_complex_boolean_cast(self):
          # Ticket #2218
          for tp in [np.csingle, np.cdouble, np.clongdouble]:
              x = np.array([0, 0+0.5j, 0.5+0j], dtype=tp)
              assert_equal(x.astype(bool), np.array([0, 1, 1], dtype=bool))
              assert_(np.any(x))
              assert_(np.all(x[1:]))
  
      def test_uint_int_conversion(self):
          x = 2**64 - 1
          assert_equal(int(np.uint64(x)), x)
  
      def test_duplicate_field_names_assign(self):
          ra = np.fromiter(((i*3, i*2) for i in range(10)), dtype='i8,f8')
          ra.dtype.names = ('f1', 'f2')
          repr(ra)  # should not cause a segmentation fault
          assert_raises(ValueError, setattr, ra.dtype, 'names', ('f1', 'f1'))
  
      def test_eq_string_and_object_array(self):
          # From e-mail thread "__eq__ with str and object" (Keith Goodman)
          a1 = np.array(['a', 'b'], dtype=object)
          a2 = np.array(['a', 'c'])
          assert_array_equal(a1 == a2, [True, False])
          assert_array_equal(a2 == a1, [True, False])
  
      def test_nonzero_byteswap(self):
          a = np.array([0x80000000, 0x00000080, 0], dtype=np.uint32)
          a.dtype = np.float32
          assert_equal(a.nonzero()[0], [1])
          a = a.byteswap().newbyteorder()
          assert_equal(a.nonzero()[0], [1])  # [0] if nonzero() ignores swap
  
      def test_find_common_type_boolean(self):
          # Ticket #1695
          assert_(np.find_common_type([], ['?', '?']) == '?')
  
      def test_empty_mul(self):
          a = np.array([1.])
          a[1:1] *= 2
          assert_equal(a, [1.])
  
      def test_array_side_effect(self):
          # The second use of itemsize was throwing an exception because in
          # ctors.c, discover_itemsize was calling PyObject_Length without
          # checking the return code.  This failed to get the length of the
          # number 2, and the exception hung around until something checked
          # PyErr_Occurred() and returned an error.
          assert_equal(np.dtype('S10').itemsize, 10)
          np.array([['abc', 2], ['long   ', '0123456789']], dtype=np.string_)
          assert_equal(np.dtype('S10').itemsize, 10)
  
      def test_any_float(self):
          # all and any for floats
          a = np.array([0.1, 0.9])
          assert_(np.any(a))
          assert_(np.all(a))
  
      def test_large_float_sum(self):
          a = np.arange(10000, dtype='f')
          assert_equal(a.sum(dtype='d'), a.astype('d').sum())
  
      def test_ufunc_casting_out(self):
          a = np.array(1.0, dtype=np.float32)
          b = np.array(1.0, dtype=np.float64)
          c = np.array(1.0, dtype=np.float32)
          np.add(a, b, out=c)
          assert_equal(c, 2.0)
  
      def test_array_scalar_contiguous(self):
          # Array scalars are both C and Fortran contiguous
          assert_(np.array(1.0).flags.c_contiguous)
          assert_(np.array(1.0).flags.f_contiguous)
          assert_(np.array(np.float32(1.0)).flags.c_contiguous)
          assert_(np.array(np.float32(1.0)).flags.f_contiguous)
  
      def test_squeeze_contiguous(self):
          # Similar to GitHub issue #387
          a = np.zeros((1, 2)).squeeze()
          b = np.zeros((2, 2, 2), order='F')[:, :, ::2].squeeze()
          assert_(a.flags.c_contiguous)
          assert_(a.flags.f_contiguous)
          assert_(b.flags.f_contiguous)
  
      def test_squeeze_axis_handling(self):
          # Issue #10779
          # Ensure proper handling of objects
          # that don't support axis specification
          # when squeezing
  
          class OldSqueeze(np.ndarray):
  
              def __new__(cls,
                          input_array):
                  obj = np.asarray(input_array).view(cls)
                  return obj
  
              # it is perfectly reasonable that prior
              # to numpy version 1.7.0 a subclass of ndarray
              # might have been created that did not expect
              # squeeze to have an axis argument
              # NOTE: this example is somewhat artificial;
              # it is designed to simulate an old API
              # expectation to guard against regression
              def squeeze(self):
                  return super(OldSqueeze, self).squeeze()
  
          oldsqueeze = OldSqueeze(np.array([[1],[2],[3]]))
  
          # if no axis argument is specified the old API
          # expectation should give the correct result
          assert_equal(np.squeeze(oldsqueeze),
                       np.array([1,2,3]))
  
          # likewise, axis=None should work perfectly well
          # with the old API expectation
          assert_equal(np.squeeze(oldsqueeze, axis=None),
                       np.array([1,2,3]))
  
          # however, specification of any particular axis
          # should raise a TypeError in the context of the
          # old API specification, even when using a valid
          # axis specification like 1 for this array
          with assert_raises(TypeError):
              # this would silently succeed for array
              # subclasses / objects that did not support
              # squeeze axis argument handling before fixing
              # Issue #10779
              np.squeeze(oldsqueeze, axis=1)
  
          # check for the same behavior when using an invalid
          # axis specification -- in this case axis=0 does not
          # have size 1, but the priority should be to raise
          # a TypeError for the axis argument and NOT a
          # ValueError for squeezing a non-empty dimension
          with assert_raises(TypeError):
              np.squeeze(oldsqueeze, axis=0)
  
          # the new API knows how to handle the axis
          # argument and will return a ValueError if
          # attempting to squeeze an axis that is not
          # of length 1
          with assert_raises(ValueError):
              np.squeeze(np.array([[1],[2],[3]]), axis=0)
  
      def test_reduce_contiguous(self):
          # GitHub issue #387
          a = np.add.reduce(np.zeros((2, 1, 2)), (0, 1))
          b = np.add.reduce(np.zeros((2, 1, 2)), 1)
          assert_(a.flags.c_contiguous)
          assert_(a.flags.f_contiguous)
          assert_(b.flags.c_contiguous)
  
      def test_object_array_self_reference(self):
          # Object arrays with references to themselves can cause problems
          a = np.array(0, dtype=object)
          a[()] = a
          assert_raises(RecursionError, int, a)
          assert_raises(RecursionError, float, a)
          a[()] = None
  
      def test_object_array_circular_reference(self):
          # Test the same for a circular reference.
          a = np.array(0, dtype=object)
          b = np.array(0, dtype=object)
          a[()] = b
          b[()] = a
          assert_raises(RecursionError, int, a)
          # NumPy has no tp_traverse currently, so circular references
          # cannot be detected. So resolve it:
          a[()] = None
  
          # This was causing a to become like the above
          a = np.array(0, dtype=object)
          a[...] += 1
          assert_equal(a, 1)
  
      def test_object_array_nested(self):
          # but is fine with a reference to a different array
          a = np.array(0, dtype=object)
          b = np.array(0, dtype=object)
          a[()] = b
          assert_equal(int(a), int(0))
          assert_equal(float(a), float(0))
  
      def test_object_array_self_copy(self):
          # An object array being copied into itself DECREF'ed before INCREF'ing
          # causing segmentation faults (gh-3787)
          a = np.array(object(), dtype=object)
          np.copyto(a, a)
          if HAS_REFCOUNT:
              assert_(sys.getrefcount(a[()]) == 2)
          a[()].__class__  # will segfault if object was deleted
  
      def test_zerosize_accumulate(self):
          "Ticket #1733"
          x = np.array([[42, 0]], dtype=np.uint32)
          assert_equal(np.add.accumulate(x[:-1, 0]), [])
  
      def test_objectarray_setfield(self):
          # Setfield should not overwrite Object fields with non-Object data
          x = np.array([1, 2, 3], dtype=object)
          assert_raises(TypeError, x.setfield, 4, np.int32, 0)
  
      def test_setting_rank0_string(self):
          "Ticket #1736"
          s1 = b"hello1"
          s2 = b"hello2"
          a = np.zeros((), dtype="S10")
          a[()] = s1
          assert_equal(a, np.array(s1))
          a[()] = np.array(s2)
          assert_equal(a, np.array(s2))
  
          a = np.zeros((), dtype='f4')
          a[()] = 3
          assert_equal(a, np.array(3))
          a[()] = np.array(4)
          assert_equal(a, np.array(4))
  
      def test_string_astype(self):
          "Ticket #1748"
          s1 = b'black'
          s2 = b'white'
          s3 = b'other'
          a = np.array([[s1], [s2], [s3]])
          assert_equal(a.dtype, np.dtype('S5'))
          b = a.astype(np.dtype('S0'))
          assert_equal(b.dtype, np.dtype('S5'))
  
      def test_ticket_1756(self):
          # Ticket #1756
          s = b'0123456789abcdef'
          a = np.array([s]*5)
          for i in range(1, 17):
              a1 = np.array(a, "|S%d" % i)
              a2 = np.array([s[:i]]*5)
              assert_equal(a1, a2)
  
      def test_fields_strides(self):
          "gh-2355"
          r = np.frombuffer(b'abcdefghijklmnop'*4*3, dtype='i4,(2,3)u2')
          assert_equal(r[0:3:2]['f1'], r['f1'][0:3:2])
          assert_equal(r[0:3:2]['f1'][0], r[0:3:2][0]['f1'])
          assert_equal(r[0:3:2]['f1'][0][()], r[0:3:2][0]['f1'][()])
          assert_equal(r[0:3:2]['f1'][0].strides, r[0:3:2][0]['f1'].strides)
  
      def test_alignment_update(self):
          # Check that alignment flag is updated on stride setting
          a = np.arange(10)
          assert_(a.flags.aligned)
          a.strides = 3
          assert_(not a.flags.aligned)
  
      def test_ticket_1770(self):
          "Should not segfault on python 3k"
          import numpy as np
          try:
              a = np.zeros((1,), dtype=[('f1', 'f')])
              a['f1'] = 1
              a['f2'] = 1
          except ValueError:
              pass
          except Exception:
              raise AssertionError
  
      def test_ticket_1608(self):
          "x.flat shouldn't modify data"
          x = np.array([[1, 2], [3, 4]]).T
          np.array(x.flat)
          assert_equal(x, [[1, 3], [2, 4]])
  
      def test_pickle_string_overwrite(self):
          import re
  
          data = np.array([1], dtype='b')
          blob = pickle.dumps(data, protocol=1)
          data = pickle.loads(blob)
  
          # Check that loads does not clobber interned strings
          s = re.sub("a(.)", "\x01\\1", "a_")
          assert_equal(s[0], "\x01")
          data[0] = 0xbb
          s = re.sub("a(.)", "\x01\\1", "a_")
          assert_equal(s[0], "\x01")
  
      def test_pickle_bytes_overwrite(self):
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              data = np.array([1], dtype='b')
              data = pickle.loads(pickle.dumps(data, protocol=proto))
              data[0] = 0xdd
              bytestring = "\x01  ".encode('ascii')
              assert_equal(bytestring[0:1], '\x01'.encode('ascii'))
  
      def test_pickle_py2_array_latin1_hack(self):
          # Check that unpickling hacks in Py3 that support
          # encoding='latin1' work correctly.
  
          # Python2 output for pickle.dumps(numpy.array([129], dtype='b'))
          data = (b"cnumpy.core.multiarray\n_reconstruct\np0\n(cnumpy\nndarray\np1\n(I0\n"
                  b"tp2\nS'b'\np3\ntp4\nRp5\n(I1\n(I1\ntp6\ncnumpy\ndtype\np7\n(S'i1'\np8\n"
                  b"I0\nI1\ntp9\nRp10\n(I3\nS'|'\np11\nNNNI-1\nI-1\nI0\ntp12\nbI00\nS'\\x81'\n"
                  b"p13\ntp14\nb.")
          # This should work:
          result = pickle.loads(data, encoding='latin1')
          assert_array_equal(result, np.array([129], dtype='b'))
          # Should not segfault:
          assert_raises(Exception, pickle.loads, data, encoding='koi8-r')
  
      def test_pickle_py2_scalar_latin1_hack(self):
          # Check that scalar unpickling hack in Py3 that supports
          # encoding='latin1' work correctly.
  
          # Python2 output for pickle.dumps(...)
          datas = [
              # (original, python2_pickle, koi8r_validity)
              (np.unicode_('\u6bd2'),
               (b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                b"(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                b"tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
               'invalid'),
  
              (np.float64(9e123),
               (b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                b"p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                b"bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
               'invalid'),
  
              (np.bytes_(b'\x9c'),  # different 8-bit code point in KOI8-R vs latin1
               (b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                b"I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                b"tp8\nRp9\n."),
               'different'),
          ]
          for original, data, koi8r_validity in datas:
              result = pickle.loads(data, encoding='latin1')
              assert_equal(result, original)
  
              # Decoding under non-latin1 encoding (e.g.) KOI8-R can
              # produce bad results, but should not segfault.
              if koi8r_validity == 'different':
                  # Unicode code points happen to lie within latin1,
                  # but are different in koi8-r, resulting to silent
                  # bogus results
                  result = pickle.loads(data, encoding='koi8-r')
                  assert_(result != original)
              elif koi8r_validity == 'invalid':
                  # Unicode code points outside latin1, so results
                  # to an encoding exception
                  assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
              else:
                  raise ValueError(koi8r_validity)
  
      def test_structured_type_to_object(self):
          a_rec = np.array([(0, 1), (3, 2)], dtype='i4,i8')
          a_obj = np.empty((2,), dtype=object)
          a_obj[0] = (0, 1)
          a_obj[1] = (3, 2)
          # astype records -> object
          assert_equal(a_rec.astype(object), a_obj)
          # '=' records -> object
          b = np.empty_like(a_obj)
          b[...] = a_rec
          assert_equal(b, a_obj)
          # '=' object -> records
          b = np.empty_like(a_rec)
          b[...] = a_obj
          assert_equal(b, a_rec)
  
      def test_assign_obj_listoflists(self):
          # Ticket # 1870
          # The inner list should get assigned to the object elements
          a = np.zeros(4, dtype=object)
          b = a.copy()
          a[0] = [1]
          a[1] = [2]
          a[2] = [3]
          a[3] = [4]
          b[...] = [[1], [2], [3], [4]]
          assert_equal(a, b)
          # The first dimension should get broadcast
          a = np.zeros((2, 2), dtype=object)
          a[...] = [[1, 2]]
          assert_equal(a, [[1, 2], [1, 2]])
  
      @pytest.mark.slow_pypy
      def test_memoryleak(self):
          # Ticket #1917 - ensure that array data doesn't leak
          for i in range(1000):
              # 100MB times 1000 would give 100GB of memory usage if it leaks
              a = np.empty((100000000,), dtype='i1')
              del a
  
      @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
      def test_ufunc_reduce_memoryleak(self):
          a = np.arange(6)
          acnt = sys.getrefcount(a)
          np.add.reduce(a)
          assert_equal(sys.getrefcount(a), acnt)
  
      def test_search_sorted_invalid_arguments(self):
          # Ticket #2021, should not segfault.
          x = np.arange(0, 4, dtype='datetime64[D]')
          assert_raises(TypeError, x.searchsorted, 1)
  
      def test_string_truncation(self):
          # Ticket #1990 - Data can be truncated in creation of an array from a
          # mixed sequence of numeric values and strings
          for val in [True, 1234, 123.4, complex(1, 234)]:
              for tostr in [asunicode, asbytes]:
                  b = np.array([val, tostr('xx')])
                  assert_equal(tostr(b[0]), tostr(val))
                  b = np.array([tostr('xx'), val])
                  assert_equal(tostr(b[1]), tostr(val))
  
                  # test also with longer strings
                  b = np.array([val, tostr('xxxxxxxxxx')])
                  assert_equal(tostr(b[0]), tostr(val))
                  b = np.array([tostr('xxxxxxxxxx'), val])
                  assert_equal(tostr(b[1]), tostr(val))
  
      def test_string_truncation_ucs2(self):
          # Ticket #2081. Python compiled with two byte unicode
          # can lead to truncation if itemsize is not properly
          # adjusted for NumPy's four byte unicode.
          a = np.array(['abcd'])
          assert_equal(a.dtype.itemsize, 16)
  
      def test_unique_stable(self):
          # Ticket #2063 must always choose stable sort for argsort to
          # get consistent results
          v = np.array(([0]*5 + [1]*6 + [2]*6)*4)
          res = np.unique(v, return_index=True)
          tgt = (np.array([0, 1, 2]), np.array([ 0,  5, 11]))
          assert_equal(res, tgt)
  
      def test_unicode_alloc_dealloc_match(self):
          # Ticket #1578, the mismatch only showed up when running
          # python-debug for python versions >= 2.7, and then as
          # a core dump and error message.
          a = np.array(['abc'], dtype=np.unicode_)[0]
          del a
  
      def test_refcount_error_in_clip(self):
          # Ticket #1588
          a = np.zeros((2,), dtype='>i2').clip(min=0)
          x = a + a
          # This used to segfault:
          y = str(x)
          # Check the final string:
          assert_(y == "[0 0]")
  
      def test_searchsorted_wrong_dtype(self):
          # Ticket #2189, it used to segfault, so we check that it raises the
          # proper exception.
          a = np.array([('a', 1)], dtype='S1, int')
          assert_raises(TypeError, np.searchsorted, a, 1.2)
          # Ticket #2066, similar problem:
          dtype = np.format_parser(['i4', 'i4'], [], [])
          a = np.recarray((2, ), dtype)
          assert_raises(TypeError, np.searchsorted, a, 1)
  
      def test_complex64_alignment(self):
          # Issue gh-2668 (trac 2076), segfault on sparc due to misalignment
          dtt = np.complex64
          arr = np.arange(10, dtype=dtt)
          # 2D array
          arr2 = np.reshape(arr, (2, 5))
          # Fortran write followed by (C or F) read caused bus error
          data_str = arr2.tobytes('F')
          data_back = np.ndarray(arr2.shape,
                                arr2.dtype,
                                buffer=data_str,
                                order='F')
          assert_array_equal(arr2, data_back)
  
      def test_structured_count_nonzero(self):
          arr = np.array([0, 1]).astype('i4, (2)i4')[:1]
          count = np.count_nonzero(arr)
          assert_equal(count, 0)
  
      def test_copymodule_preserves_f_contiguity(self):
          a = np.empty((2, 2), order='F')
          b = copy.copy(a)
          c = copy.deepcopy(a)
          assert_(b.flags.fortran)
          assert_(b.flags.f_contiguous)
          assert_(c.flags.fortran)
          assert_(c.flags.f_contiguous)
  
      def test_fortran_order_buffer(self):
          import numpy as np
          a = np.array([['Hello', 'Foob']], dtype='U5', order='F')
          arr = np.ndarray(shape=[1, 2, 5], dtype='U1', buffer=a)
          arr2 = np.array([[[u'H', u'e', u'l', u'l', u'o'],
                            [u'F', u'o', u'o', u'b', u'']]])
          assert_array_equal(arr, arr2)
  
      def test_assign_from_sequence_error(self):
          # Ticket #4024.
          arr = np.array([1, 2, 3])
          assert_raises(ValueError, arr.__setitem__, slice(None), [9, 9])
          arr.__setitem__(slice(None), [9])
          assert_equal(arr, [9, 9, 9])
  
      def test_format_on_flex_array_element(self):
          # Ticket #4369.
          dt = np.dtype([('date', '<M8[D]'), ('val', '<f8')])
          arr = np.array([('2000-01-01', 1)], dt)
          formatted = '{0}'.format(arr[0])
          assert_equal(formatted, str(arr[0]))
  
      def test_deepcopy_on_0d_array(self):
          # Ticket #3311.
          arr = np.array(3)
          arr_cp = copy.deepcopy(arr)
  
          assert_equal(arr, arr_cp)
          assert_equal(arr.shape, arr_cp.shape)
          assert_equal(int(arr), int(arr_cp))
          assert_(arr is not arr_cp)
          assert_(isinstance(arr_cp, type(arr)))
  
      def test_deepcopy_F_order_object_array(self):
          # Ticket #6456.
          a = {'a': 1}
          b = {'b': 2}
          arr = np.array([[a, b], [a, b]], order='F')
          arr_cp = copy.deepcopy(arr)
  
          assert_equal(arr, arr_cp)
          assert_(arr is not arr_cp)
          # Ensure that we have actually copied the item.
          assert_(arr[0, 1] is not arr_cp[1, 1])
          # Ensure we are allowed to have references to the same object.
          assert_(arr[0, 1] is arr[1, 1])
          # Check the references hold for the copied objects.
          assert_(arr_cp[0, 1] is arr_cp[1, 1])
  
      def test_deepcopy_empty_object_array(self):
          # Ticket #8536.
          # Deepcopy should succeed
          a = np.array([], dtype=object)
          b = copy.deepcopy(a)
          assert_(a.shape == b.shape)
  
      def test_bool_subscript_crash(self):
          # gh-4494
          c = np.rec.array([(1, 2, 3), (4, 5, 6)])
          masked = c[np.array([True, False])]
          base = masked.base
          del masked, c
          base.dtype
  
      def test_richcompare_crash(self):
          # gh-4613
          import operator as op
  
          # dummy class where __array__ throws exception
          class Foo:
              __array_priority__ = 1002
  
              def __array__(self, *args, **kwargs):
                  raise Exception()
  
          rhs = Foo()
          lhs = np.array(1)
          for f in [op.lt, op.le, op.gt, op.ge]:
              assert_raises(TypeError, f, lhs, rhs)
          assert_(not op.eq(lhs, rhs))
          assert_(op.ne(lhs, rhs))
  
      def test_richcompare_scalar_and_subclass(self):
          # gh-4709
          class Foo(np.ndarray):
              def __eq__(self, other):
                  return "OK"
  
          x = np.array([1, 2, 3]).view(Foo)
          assert_equal(10 == x, "OK")
          assert_equal(np.int32(10) == x, "OK")
          assert_equal(np.array([10]) == x, "OK")
  
      def test_pickle_empty_string(self):
          # gh-3926
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              test_string = np.string_('')
              assert_equal(pickle.loads(
                  pickle.dumps(test_string, protocol=proto)), test_string)
  
      def test_frompyfunc_many_args(self):
          # gh-5672
  
          def passer(*args):
              pass
  
          assert_raises(ValueError, np.frompyfunc, passer, 32, 1)
  
      def test_repeat_broadcasting(self):
          # gh-5743
          a = np.arange(60).reshape(3, 4, 5)
          for axis in chain(range(-a.ndim, a.ndim), [None]):
              assert_equal(a.repeat(2, axis=axis), a.repeat([2], axis=axis))
  
      def test_frompyfunc_nout_0(self):
          # gh-2014
  
          def f(x):
              x[0], x[-1] = x[-1], x[0]
  
          uf = np.frompyfunc(f, 1, 0)
          a = np.array([[1, 2, 3], [4, 5], [6, 7, 8, 9]], dtype=object)
          assert_equal(uf(a), ())
          expected = np.array([[3, 2, 1], [5, 4], [9, 7, 8, 6]], dtype=object)
          assert_array_equal(a, expected)
  
      @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
      def test_leak_in_structured_dtype_comparison(self):
          # gh-6250
          recordtype = np.dtype([('a', np.float64),
                                 ('b', np.int32),
                                 ('d', (str, 5))])
  
          # Simple case
          a = np.zeros(2, dtype=recordtype)
          for i in range(100):
              a == a
          assert_(sys.getrefcount(a) < 10)
  
          # The case in the bug report.
          before = sys.getrefcount(a)
          u, v = a[0], a[1]
          u == v
          del u, v
          gc.collect()
          after = sys.getrefcount(a)
          assert_equal(before, after)
  
      def test_empty_percentile(self):
          # gh-6530 / gh-6553
          assert_array_equal(np.percentile(np.arange(10), []), np.array([]))
  
      def test_void_compare_segfault(self):
          # gh-6922. The following should not segfault
          a = np.ones(3, dtype=[('object', 'O'), ('int', '<i2')])
          a.sort()
  
      def test_reshape_size_overflow(self):
          # gh-7455
          a = np.ones(20)[::2]
          if np.dtype(np.intp).itemsize == 8:
              # 64 bit. The following are the prime factors of 2**63 + 5,
              # plus a leading 2, so when multiplied together as int64,
              # the result overflows to a total size of 10.
              new_shape = (2, 13, 419, 691, 823, 2977518503)
          else:
              # 32 bit. The following are the prime factors of 2**31 + 5,
              # plus a leading 2, so when multiplied together as int32,
              # the result overflows to a total size of 10.
              new_shape = (2, 7, 7, 43826197)
          assert_raises(ValueError, a.reshape, new_shape)
  
      def test_invalid_structured_dtypes(self):
          # gh-2865
          # mapping python objects to other dtypes
          assert_raises(ValueError, np.dtype, ('O', [('name', 'i8')]))
          assert_raises(ValueError, np.dtype, ('i8', [('name', 'O')]))
          assert_raises(ValueError, np.dtype,
                        ('i8', [('name', [('name', 'O')])]))
          assert_raises(ValueError, np.dtype, ([('a', 'i4'), ('b', 'i4')], 'O'))
          assert_raises(ValueError, np.dtype, ('i8', 'O'))
          # wrong number/type of tuple elements in dict
          assert_raises(ValueError, np.dtype,
                        ('i', {'name': ('i', 0, 'title', 'oops')}))
          assert_raises(ValueError, np.dtype,
                        ('i', {'name': ('i', 'wrongtype', 'title')}))
          # disallowed as of 1.13
          assert_raises(ValueError, np.dtype,
                        ([('a', 'O'), ('b', 'O')], [('c', 'O'), ('d', 'O')]))
          # allowed as a special case due to existing use, see gh-2798
          a = np.ones(1, dtype=('O', [('name', 'O')]))
          assert_equal(a[0], 1)
          # In particular, the above union dtype (and union dtypes in general)
          # should mainly behave like the main (object) dtype:
          assert a[0] is a.item()
          assert type(a[0]) is int
  
      def test_correct_hash_dict(self):
          # gh-8887 - __hash__ would be None despite tp_hash being set
          all_types = set(np.typeDict.values()) - {np.void}
          for t in all_types:
              val = t()
  
              try:
                  hash(val)
              except TypeError as e:
                  assert_equal(t.__hash__, None)
              else:
                  assert_(t.__hash__ != None)
  
      def test_scalar_copy(self):
          scalar_types = set(np.sctypeDict.values())
          values = {
              np.void: b"a",
              np.bytes_: b"a",
              np.unicode_: "a",
              np.datetime64: "2017-08-25",
          }
          for sctype in scalar_types:
              item = sctype(values.get(sctype, 1))
              item2 = copy.copy(item)
              assert_equal(item, item2)
  
      def test_void_item_memview(self):
          va = np.zeros(10, 'V4')
          x = va[:1].item()
          va[0] = b'\xff\xff\xff\xff'
          del va
          assert_equal(x, b'\x00\x00\x00\x00')
  
      def test_void_getitem(self):
          # Test fix for gh-11668.
          assert_(np.array([b'a'], 'V1').astype('O') == b'a')
          assert_(np.array([b'ab'], 'V2').astype('O') == b'ab')
          assert_(np.array([b'abc'], 'V3').astype('O') == b'abc')
          assert_(np.array([b'abcd'], 'V4').astype('O') == b'abcd')
  
      def test_structarray_title(self):
          # The following used to segfault on pypy, due to NPY_TITLE_KEY
          # not working properly and resulting to double-decref of the
          # structured array field items:
          # See: https://bitbucket.org/pypy/pypy/issues/2789
          for j in range(5):
              structure = np.array([1], dtype=[(('x', 'X'), np.object_)])
              structure[0]['x'] = np.array([2])
              gc.collect()
  
      def test_dtype_scalar_squeeze(self):
          # gh-11384
          values = {
              'S': b"a",
              'M': "2018-06-20",
          }
          for ch in np.typecodes['All']:
              if ch in 'O':
                  continue
              sctype = np.dtype(ch).type
              scvalue = sctype(values.get(ch, 3))
              for axis in [None, ()]:
                  squeezed = scvalue.squeeze(axis=axis)
                  assert_equal(squeezed, scvalue)
                  assert_equal(type(squeezed), type(scvalue))
  
      def test_field_access_by_title(self):
          # gh-11507
          s = 'Some long field name'
          if HAS_REFCOUNT:
              base = sys.getrefcount(s)
          t = np.dtype([((s, 'f1'), np.float64)])
          data = np.zeros(10, t)
          for i in range(10):
              str(data[['f1']])
              if HAS_REFCOUNT:
                  assert_(base <= sys.getrefcount(s))
  
      @pytest.mark.parametrize('val', [
          # arrays and scalars
          np.ones((10, 10), dtype='int32'),
          np.uint64(10),
          ])
      @pytest.mark.parametrize('protocol',
          range(2, pickle.HIGHEST_PROTOCOL + 1)
          )
      def test_pickle_module(self, protocol, val):
          # gh-12837
          s = pickle.dumps(val, protocol)
          assert b'_multiarray_umath' not in s
          if protocol == 5 and len(val.shape) > 0:
              # unpickling ndarray goes through _frombuffer for protocol 5
              assert b'numpy.core.numeric' in s
          else:
              assert b'numpy.core.multiarray' in s
  
      def test_object_casting_errors(self):
          # gh-11993 update to ValueError (see gh-16909), since strings can in
          # principle be converted to complex, but this string cannot.
          arr = np.array(['AAAAA', 18465886.0, 18465886.0], dtype=object)
          assert_raises(ValueError, arr.astype, 'c8')
  
      def test_eff1d_casting(self):
          # gh-12711
          x = np.array([1, 2, 4, 7, 0], dtype=np.int16)
          res = np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99]))
          assert_equal(res, [-99,   1,   2,   3,  -7,  88,  99])
  
          # The use of safe casting means, that 1<<20 is cast unsafely, an
          # error may be better, but currently there is no mechanism for it.
          res = np.ediff1d(x, to_begin=(1<<20), to_end=(1<<20))
          assert_equal(res, [0,   1,   2,   3,  -7,  0])
  
      def test_pickle_datetime64_array(self):
          # gh-12745 (would fail with pickle5 installed)
          d = np.datetime64('2015-07-04 12:59:59.50', 'ns')
          arr = np.array([d])
          for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
              dumped = pickle.dumps(arr, protocol=proto)
              assert_equal(pickle.loads(dumped), arr)
  
      def test_bad_array_interface(self):
          class T:
              __array_interface__ = {}
  
          with assert_raises(ValueError):
              np.array([T()])
  
      def test_2d__array__shape(self):
          class T(object):
              def __array__(self):
                  return np.ndarray(shape=(0,0))
  
              # Make sure __array__ is used instead of Sequence methods.
              def __iter__(self):
                  return iter([])
  
              def __getitem__(self, idx):
                  raise AssertionError("__getitem__ was called")
  
              def __len__(self):
                  return 0
  
  
          t = T()
          # gh-13659, would raise in broadcasting [x=t for x in result]
          arr = np.array([t])
          assert arr.shape == (1, 0, 0)
  
      @pytest.mark.skipif(sys.maxsize < 2 ** 31 + 1, reason='overflows 32-bit python')
      @pytest.mark.skipif(sys.platform == 'win32' and sys.version_info[:2] < (3, 8),
                          reason='overflows on windows, fixed in bpo-16865')
      def test_to_ctypes(self):
          #gh-14214
          arr = np.zeros((2 ** 31 + 1,), 'b')
          assert arr.size * arr.itemsize > 2 ** 31
          c_arr = np.ctypeslib.as_ctypes(arr)
          assert_equal(c_arr._length_, arr.size)
  
      def test_complex_conversion_error(self):
          # gh-17068
          with pytest.raises(TypeError, match=r"Unable to convert dtype.*"):
              complex(np.array("now", np.datetime64))
  
      def test__array_interface__descr(self):
          # gh-17068
          dt = np.dtype(dict(names=['a', 'b'],
                             offsets=[0, 0],
                             formats=[np.int64, np.int64]))
          descr = np.array((1, 1), dtype=dt).__array_interface__['descr']
          assert descr == [('', '|V8')]  # instead of [(b'', '|V8')]
  
apis: numpy.ones numpy.testing.assert_equal numpy.any numpy.asarray numpy.compat.pickle.loads numpy.testing.assert_warns numpy.datetime64 numpy.transpose numpy.abs numpy.bool_ numpy.bytes_ numpy.unique numpy.typeDict.values numpy.string_ numpy.float32 numpy.errstate numpy.rec.fromarrays numpy.unicode_ numpy.array numpy.random.normal numpy.dot numpy.subtract.reduce numpy.find_common_type numpy.testing.assert_raises_regex numpy.compat.pickle.dump numpy.random.seed numpy.add numpy.add.reduce numpy.ediff1d numpy.char.array numpy.reshape numpy.fromstring numpy.binary_repr numpy.load numpy.argmax numpy.copyto numpy.divide.reduce numpy.count_nonzero numpy.hstack numpy.uint64 numpy.int32 numpy.finfo numpy.testing.assert_raises numpy.zeros_like numpy.random.shuffle numpy.format_parser numpy.concatenate numpy.rec.array numpy.array_str numpy.frombuffer numpy.take numpy.add.outer numpy.frompyfunc numpy.float64 numpy.empty_like numpy.sctypeDict.values numpy.random.rand numpy.nonzero numpy.fromfile numpy.float_ numpy.zeros numpy.arange numpy.lexsort numpy.testing.assert_array_almost_equal numpy.recarray numpy.chararray numpy.sort numpy.divide.accumulate numpy.random.randn numpy.compat.asbytes numpy.subtract.accumulate numpy.setbufsize numpy.compat.pickle.load numpy.dtype numpy.testing._assert_valid_refcount numpy.object_ numpy.testing.assert_almost_equal numpy.testing.assert_array_equal numpy.ndarray numpy.where numpy.linspace numpy.compat.pickle.dumps numpy.exp2 numpy.lib.stride_tricks.as_strided numpy.all numpy.indices numpy.maximum numpy.sign numpy.empty numpy.squeeze numpy.ctypeslib.as_ctypes numpy.add.accumulate numpy.iinfo numpy.testing.suppress_warnings numpy.testing.assert_