from __future__ import division, absolute_import, print_function import copy import pickle import sys import platform import gc import warnings import tempfile from os import path from io import BytesIO from itertools import chain import numpy as np from numpy.testing import ( run_module_suite, assert_, assert_equal, IS_PYPY, assert_almost_equal, assert_array_equal, assert_array_almost_equal, assert_raises, assert_warns, dec, suppress_warnings, _assert_valid_refcount, HAS_REFCOUNT, ) from numpy.compat import asbytes, asunicode, long try: RecursionError except NameError: RecursionError = RuntimeError # python < 3.5 class TestRegression(object): 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]])) f = BytesIO() pickle.dump(a, f) f.seek(0) b = pickle.load(f) f.close() assert_array_equal(a, b) def test_typeNA(self): # Ticket #31 assert_equal(np.typeNA[np.int64], 'Int64') assert_equal(np.typeNA[np.uint64], 'UInt64') 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(' 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='= (3, 4): # encoding='bytes' was added in Py3.4 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: for name in result.dtype.names: assert_(isinstance(name, str)) def test_pickle_dtype(self): # Ticket #251 pickle.dumps(float) def test_swap_real(self): # Ticket #265 assert_equal(np.arange(4, dtype='>c8').imag.max(), 0.0) assert_equal(np.arange(4, dtype=' 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. @dec.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max) 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=' 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] new = pickle.loads(pickle.dumps(el)) assert_equal(new, el) def test_arange_non_native_dtype(self): # Ticket #616 for T in ('>f4', ' 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[:], x.astype('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. @dec.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max) 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(object): 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(object): 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('= 3: f = open(filename, 'rb') xp = pickle.load(f, encoding='latin1') f.close() else: f = open(filename) xp = pickle.load(f) f.close() 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) if sys.version_info[0] >= 3: assert_equal(str(x), "[(b'a', 'b')]", err_msg=msg) else: assert_equal(str(x), "[('a', u'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 assert_(pickle.loads(pickle.dumps(test_string)) == test_string) assert_(pickle.loads(pickle.dumps(test_record)) == test_record) 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 good = 'Maximum allowed dimension exceeded' try: np.empty(sz) except ValueError as e: if not str(e) == good: self.fail("Got msg '%s', expected '%s'" % (e, good)) except Exception as e: self.fail("Got exception of type %s instead of ValueError" % type(e)) def test_huge_arange(self): # Regression test for #1062. # Set a size which cannot fit into a 64 bits signed integer sz = 2 ** 64 good = 'Maximum allowed size exceeded' try: np.arange(sz) assert_(np.size == sz) except ValueError as e: if not str(e) == good: self.fail("Got msg '%s', expected '%s'" % (e, good)) except Exception as e: self.fail("Got exception of type %s instead of ValueError" % type(e)) 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))) 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))) 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)]) 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_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]) @dec._needs_refcount 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, np.long): test_type(t) def test_buffer_hashlib(self): try: from hashlib import md5 except ImportError: from md5 import new as md5 x = np.array([1, 2, 3], dtype=np.dtype('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 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)) @dec._needs_refcount 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_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, long, a) assert_raises(RecursionError, float, a) if sys.version_info.major == 2: # in python 3, this falls back on operator.index, which fails on # on dtype=object assert_raises(RecursionError, oct, a) assert_raises(RecursionError, hex, 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(long(a), long(0)) assert_equal(float(a), float(0)) if sys.version_info.major == 2: # in python 3, this falls back on operator.index, which fails on # on dtype=object assert_equal(oct(a), oct(0)) assert_equal(hex(a), hex(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): if sys.version_info[0] >= 3: data = np.array([1], dtype='b') data = pickle.loads(pickle.dumps(data)) 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.") if sys.version_info[0] >= 3: # 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'), ] if sys.version_info[0] >= 3: 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]]) 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 @dec._needs_refcount 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. if sys.version_info[0] >= 3: a = np.array(['abcd']) else: a = np.array([u'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', '= 3: assert_raises(TypeError, f, lhs, rhs) elif not sys.py3kwarning: # With -3 switch in python 2, DeprecationWarning is raised # which we are not interested in 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 import pickle test_string = np.string_('') assert_equal(pickle.loads(pickle.dumps(test_string)), 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]]) assert_equal(uf(a), ()) assert_array_equal(a, [[3, 2, 1], [5, 4], [9, 7, 8, 6]]) @dec._needs_refcount 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', '