diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/tests/test_getlimits.py | 2 | ||||
| -rw-r--r-- | numpy/core/tests/test_regression.py | 263 | ||||
| -rw-r--r-- | numpy/core/tests/test_scalarmath.py | 6 | ||||
| -rw-r--r-- | numpy/lib/tests/test_regression.py | 34 | ||||
| -rw-r--r-- | numpy/lib/tests/test_shape_base.py | 2 | ||||
| -rw-r--r-- | numpy/linalg/tests/test_regression.py | 9 | ||||
| -rw-r--r-- | numpy/ma/tests/test_regression.py | 12 | ||||
| -rw-r--r-- | numpy/matrixlib/tests/test_regression.py | 9 |
8 files changed, 164 insertions, 173 deletions
diff --git a/numpy/core/tests/test_getlimits.py b/numpy/core/tests/test_getlimits.py index 64900b2ad..455f5257c 100644 --- a/numpy/core/tests/test_getlimits.py +++ b/numpy/core/tests/test_getlimits.py @@ -39,7 +39,7 @@ class TestDouble(object): assert_equal(id(ftype), id(ftype2)) class TestLongdouble(object): - def test_singleton(self,level=2): + def test_singleton(self): ftype = finfo(longdouble) ftype2 = finfo(longdouble) assert_equal(id(ftype), id(ftype2)) diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index c3ff6fa97..664a0c383 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -20,19 +20,18 @@ from numpy.testing import ( ) from numpy.compat import asbytes, asunicode, long -rlevel = 1 class TestRegression(object): - def test_invalid_round(self, level=rlevel): + def test_invalid_round(self): # Ticket #3 v = 4.7599999999999998 assert_array_equal(np.array([v]), np.array(v)) - def test_mem_empty(self, level=rlevel): + def test_mem_empty(self): # Ticket #7 np.empty((1,), dtype=[('x', np.int64)]) - def test_pickle_transposed(self, level=rlevel): + def test_pickle_transposed(self): # Ticket #16 a = np.transpose(np.array([[2, 9], [7, 0], [3, 8]])) f = BytesIO() @@ -42,44 +41,44 @@ class TestRegression(object): f.close() assert_array_equal(a, b) - def test_typeNA(self, level=rlevel): + 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, level=rlevel): + def test_dtype_names(self): # Ticket #35 # Should succeed np.dtype([(('name', 'label'), np.int32, 3)]) - def test_reduce(self, level=rlevel): + def test_reduce(self): # Ticket #40 assert_almost_equal(np.add.reduce([1., .5], dtype=None), 1.5) - def test_zeros_order(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_negative_nd_indexing(self): # Ticket #49 c = np.arange(125).reshape((5, 5, 5)) origidx = np.array([-1, 0, 1]) @@ -87,7 +86,7 @@ class TestRegression(object): c[idx] assert_array_equal(idx, origidx) - def test_char_dump(self, level=rlevel): + def test_char_dump(self): # Ticket #50 f = BytesIO() ca = np.char.array(np.arange(1000, 1010), itemsize=4) @@ -96,7 +95,7 @@ class TestRegression(object): ca = np.load(f) f.close() - def test_noncontiguous_fill(self, level=rlevel): + def test_noncontiguous_fill(self): # Ticket #58. a = np.zeros((5, 3)) b = a[:, :2,] @@ -106,30 +105,30 @@ class TestRegression(object): assert_raises(AttributeError, rs) - def test_bool(self, level=rlevel): + def test_bool(self): # Ticket #60 np.bool_(1) # Should succeed - def test_indexing1(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_round(self): # Ticket #67 x = np.array([1+2j]) assert_almost_equal(x**(-1), [1/(1+2j)]) - def test_scalar_compare(self, level=rlevel): + def test_scalar_compare(self): # Trac Ticket #72 # https://github.com/numpy/numpy/issues/565 a = np.array(['test', 'auto']) @@ -143,19 +142,19 @@ class TestRegression(object): assert_(b != 'auto') assert_(b[0] != 'auto') - def test_unicode_swapping(self, level=rlevel): + 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, level=rlevel): + def test_object_array_fill(self): # Ticket #86 x = np.zeros(1, 'O') x.fill([]) - def test_mem_dtype_align(self, level=rlevel): + def test_mem_dtype_align(self): # Ticket #93 assert_raises(TypeError, np.dtype, {'names':['a'], 'formats':['foo']}, align=1) @@ -165,7 +164,7 @@ class TestRegression(object): platform.architecture()[0] == "64bit"), "numpy.intp('0xff', 16) not supported on Py3, " "as it does not inherit from Python int") - def test_intp(self, level=rlevel): + def test_intp(self): # Ticket #99 i_width = np.int_(0).nbytes*2 - 1 np.intp('0x' + 'f'*i_width, 16) @@ -174,7 +173,7 @@ class TestRegression(object): assert_equal(255, np.intp('0xFF', 16)) assert_equal(1024, np.intp(1024)) - def test_endian_bool_indexing(self, level=rlevel): + def test_endian_bool_indexing(self): # Ticket #105 a = np.arange(10., dtype='>f8') b = np.arange(10., dtype='<f8') @@ -187,7 +186,7 @@ class TestRegression(object): assert_(np.all(a[ya] > 0.5)) assert_(np.all(b[yb] > 0.5)) - def test_endian_where(self, level=rlevel): + def test_endian_where(self): # GitHub issue #369 net = np.zeros(3, dtype='>f4') net[1] = 0.00458849 @@ -197,7 +196,7 @@ class TestRegression(object): correct = np.array([ 0.60520202, 0.00458849, 0.60520202]) assert_array_almost_equal(test, correct) - def test_endian_recarray(self, level=rlevel): + def test_endian_recarray(self): # Ticket #2185 dt = np.dtype([ ('head', '>u4'), @@ -213,7 +212,7 @@ class TestRegression(object): buf[0]['data'][0] = d assert_(buf[0]['head'] == 1) - def test_mem_dot(self, level=rlevel): + def test_mem_dot(self): # Ticket #106 x = np.random.randn(0, 1) y = np.random.randn(10, 1) @@ -227,7 +226,7 @@ class TestRegression(object): np.core.multiarray.dot(x, np.transpose(y), out=z) assert_equal(_z, np.ones(10)) - def test_arange_endian(self, level=rlevel): + def test_arange_endian(self): # Ticket #111 ref = np.arange(10) x = np.arange(10, dtype='<f8') @@ -235,31 +234,31 @@ class TestRegression(object): x = np.arange(10, dtype='>f8') assert_array_equal(ref, x) - def test_argmax(self, level=rlevel): + 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, level=rlevel): + def test_mem_divmod(self): # Ticket #126 for i in range(10): divmod(np.array([i])[0], 10) - def test_hstack_invalid_dims(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_add_identity(self): # Ticket #143 assert_equal(0, np.add.identity) @@ -268,11 +267,11 @@ class TestRegression(object): a = np.float_(23.) + 2**135 assert_equal(a, 23. + 2**135) - def test_binary_repr_0(self, level=rlevel): + def test_binary_repr_0(self): # Ticket #151 assert_equal('0', np.binary_repr(0)) - def test_rec_iterate(self, level=rlevel): + 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'), @@ -280,19 +279,19 @@ class TestRegression(object): x[0].tolist() [i for i in x[0]] - def test_unicode_string_comparison(self, level=rlevel): + 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, level=rlevel): + 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.fromstring(x.tobytes())) - def test_flat_assignment(self, level=rlevel): + def test_flat_assignment(self): # Correct behaviour of ticket #194 x = np.empty((3, 1)) x.flat = np.arange(3) @@ -300,7 +299,7 @@ class TestRegression(object): x.flat = np.arange(3, dtype=float) assert_array_almost_equal(x, [[0], [1], [2]]) - def test_broadcast_flat_assignment(self, level=rlevel): + def test_broadcast_flat_assignment(self): # Ticket #194 x = np.empty((3, 1)) @@ -328,7 +327,7 @@ class TestRegression(object): assert_raises(ValueError, assign, a, r, np.nan) a[r] = np.array(np.nan) - def test_unpickle_dtype_with_object(self, level=rlevel): + def test_unpickle_dtype_with_object(self): # Implemented in r2840 dt = np.dtype([('x', int), ('y', np.object_), ('z', 'O')]) f = BytesIO() @@ -338,7 +337,7 @@ class TestRegression(object): f.close() assert_equal(dt, dt_) - def test_mem_array_creation_invalid_specification(self, level=rlevel): + def test_mem_array_creation_invalid_specification(self): # Ticket #196 dt = np.dtype([('x', int), ('y', np.object_)]) # Wrong way @@ -346,7 +345,7 @@ class TestRegression(object): # Correct way np.array([(1, 'object')], dt) - def test_recarray_single_element(self, level=rlevel): + def test_recarray_single_element(self): # Ticket #202 a = np.array([1, 2, 3], dtype=np.int32) b = a.copy() @@ -354,7 +353,7 @@ class TestRegression(object): assert_array_equal(a, b) assert_equal(a, r[0][0]) - def test_zero_sized_array_indexing(self, level=rlevel): + def test_zero_sized_array_indexing(self): # Ticket #205 tmp = np.array([]) @@ -363,14 +362,14 @@ class TestRegression(object): assert_raises(IndexError, index_tmp) - def test_chararray_rstrip(self, level=rlevel): + 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, level=rlevel): + 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)) @@ -379,20 +378,20 @@ class TestRegression(object): 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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) @@ -444,36 +443,36 @@ class TestRegression(object): for name in result.dtype.names: assert_(isinstance(name, str)) - def test_pickle_dtype(self, level=rlevel): + def test_pickle_dtype(self): # Ticket #251 pickle.dumps(float) - def test_swap_real(self, level=rlevel): + 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, level=rlevel): + def test_object_array_from_list(self): # Ticket #270 assert_(np.array([1, 'A', None]).shape == (3,)) - def test_multiple_assign(self, level=rlevel): + def test_multiple_assign(self): # Ticket #273 a = np.zeros((3, 1), int) a[[1, 2]] = 1 - def test_empty_array_type(self, level=rlevel): + def test_empty_array_type(self): assert_equal(np.array([]).dtype, np.zeros(0).dtype) - def test_void_copyswap(self, level=rlevel): + 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, level=rlevel): + def test_method_args(self): # Make sure methods and functions have same default axis # keyword and arguments funcs1 = ['argmax', 'argmin', 'sum', ('product', 'prod'), @@ -515,17 +514,17 @@ class TestRegression(object): res2 = getattr(np, func)(arr1, arr2) assert_(abs(res1-res2).max() < 1e-8, func) - def test_mem_lexsort_strings(self, level=rlevel): + def test_mem_lexsort_strings(self): # Ticket #298 lst = ['abc', 'cde', 'fgh'] np.lexsort((lst,)) - def test_fancy_index(self, level=rlevel): + 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, level=rlevel): + def test_recarray_copy(self): # Ticket #312 dt = [('x', np.int16), ('y', np.float64)] ra = np.array([(1, 2.3)], dtype=dt) @@ -533,64 +532,64 @@ class TestRegression(object): rb['x'] = 2. assert_(ra['x'] != rb['x']) - def test_rec_fromarray(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_mem_axis_minimization(self): # Ticket #327 data = np.arange(5) data = np.add.outer(data, data) - def test_mem_float_imag(self, level=rlevel): + def test_mem_float_imag(self): # Ticket #330 np.float64(1.0).imag - def test_dtype_tuple(self, level=rlevel): + def test_dtype_tuple(self): # Ticket #334 assert_(np.dtype('i4') == np.dtype(('i4', ()))) - def test_dtype_posttuple(self, level=rlevel): + def test_dtype_posttuple(self): # Ticket #335 np.dtype([('col1', '()i4')]) - def test_numeric_carray_compare(self, level=rlevel): + def test_numeric_carray_compare(self): # Ticket #341 assert_equal(np.array(['X'], 'c'), b'X') - def test_string_array_size(self, level=rlevel): + def test_string_array_size(self): # Ticket #342 assert_raises(ValueError, np.array, [['X'], ['X', 'X', 'X']], '|S1') - def test_dtype_repr(self, level=rlevel): + 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, level=rlevel): + 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]]) @@ -598,13 +597,13 @@ class TestRegression(object): b = a[:, 1] assert_equal(b.reshape(2, 2, order='F'), [[2, 6], [4, 8]]) - def test_reshape_zero_strides(self, level=rlevel): + 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, level=rlevel): + 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) @@ -621,22 +620,22 @@ class TestRegression(object): 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_object_argmax(self): a = np.array([1, 2, 3], dtype=object) assert_(a.argmax() == 2) - def test_recarray_fields(self, level=rlevel): + def test_recarray_fields(self): # Ticket #372 dt0 = np.dtype([('f0', 'i4'), ('f1', 'i4')]) dt1 = np.dtype([('f0', 'i8'), ('f1', 'i8')]) @@ -647,22 +646,22 @@ class TestRegression(object): np.rec.fromarrays([(1, 2), (3, 4)])]: assert_(a.dtype in [dt0, dt1]) - def test_random_shuffle(self, level=rlevel): + 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, level=rlevel): + def test_refcount_vdot(self): # Changeset #3443 _assert_valid_refcount(np.vdot) - def test_startswith(self, level=rlevel): + def test_startswith(self): ca = np.char.array(['Hi', 'There']) assert_equal(ca.startswith('H'), [True, False]) - def test_noncommutative_reduce_accumulate(self, level=rlevel): + def test_noncommutative_reduce_accumulate(self): # Ticket #413 tosubtract = np.arange(5) todivide = np.array([2.0, 0.5, 0.25]) @@ -673,28 +672,28 @@ class TestRegression(object): assert_array_equal(np.divide.accumulate(todivide), np.array([2., 4., 16.])) - def test_convolve_empty(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + 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) @@ -715,13 +714,13 @@ class TestRegression(object): if HAS_REFCOUNT: assert_(ref_d == sys.getrefcount(d)) - def test_array_str_64bit(self, level=rlevel): + 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, level=rlevel): + def test_frompyfunc_endian(self): # Ticket #503 from math import radians uradians = np.frompyfunc(radians, 1, 1) @@ -730,33 +729,33 @@ class TestRegression(object): assert_almost_equal(uradians(big_endian).astype(float), uradians(little_endian).astype(float)) - def test_mem_string_arr(self, level=rlevel): + def test_mem_string_arr(self): # Ticket #514 s = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" t = [] np.hstack((t, s)) - def test_arr_transpose(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_argmax_byteorder(self): # Ticket #546 a = np.arange(3, dtype='>f') assert_(a[a.argmax()] == a.max()) - def test_rand_seed(self, level=rlevel): + def test_rand_seed(self): # Ticket #555 for l in np.arange(4): np.random.seed(l) - def test_mem_deallocation_leak(self, level=rlevel): + def test_mem_deallocation_leak(self): # Ticket #562 a = np.zeros(5, dtype=float) b = np.array(a, dtype=float) @@ -766,7 +765,7 @@ class TestRegression(object): "Ticket #583" assert_raises(ValueError, np.fromiter, [['12', ''], ['13', '']], str) - def test_dot_negative_stride(self, level=rlevel): + def test_dot_negative_stride(self): # Ticket #588 x = np.array([[1, 5, 25, 125., 625]]) y = np.array([[20.], [160.], [640.], [1280.], [1024.]]) @@ -774,7 +773,7 @@ class TestRegression(object): y2 = y[::-1] assert_equal(np.dot(x, z), np.dot(x, y2)) - def test_object_casting(self, level=rlevel): + def test_object_casting(self): # This used to trigger the object-type version of # the bitwise_or operation, because float64 -> object # casting succeeds @@ -785,14 +784,14 @@ class TestRegression(object): assert_raises(TypeError, rs) - def test_unicode_scalar(self, level=rlevel): + 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, level=rlevel): + def test_arange_non_native_dtype(self): # Ticket #616 for T in ('>f4', '<f4'): dt = np.dtype(T) @@ -800,7 +799,7 @@ class TestRegression(object): 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, level=rlevel): + def test_bool_flat_indexing_invalid_nr_elements(self): s = np.ones(10, dtype=float) x = np.array((15,), dtype=float) @@ -814,59 +813,59 @@ class TestRegression(object): 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, level=rlevel): + 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, level=rlevel): + def test_binary_repr_0_width(self): assert_equal(np.binary_repr(0, width=3), '000') - def test_fromstring(self, level=rlevel): + def test_fromstring(self): assert_equal(np.fromstring("12:09:09", dtype=int, sep=":"), [12, 9, 9]) - def test_searchsorted_variable_length(self, level=rlevel): + 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, level=rlevel): + def test_string_argsort_with_zeros(self): # Check argsort for strings containing zeros. x = np.fromstring("\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, level=rlevel): + def test_string_sort_with_zeros(self): # Check sort for strings containing zeros. x = np.fromstring("\x00\x02\x00\x01", dtype="|S2") y = np.fromstring("\x00\x01\x00\x02", dtype="|S2") assert_array_equal(np.sort(x, kind="q"), y) - def test_copy_detection_zero_dim(self, level=rlevel): + def test_copy_detection_zero_dim(self): # Ticket #658 np.indices((0, 3, 4)).T.reshape(-1, 3) - def test_flat_byteorder(self, level=rlevel): + 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_uint64_from_negative(self, level=rlevel): + def test_uint64_from_negative(self): assert_equal(np.uint64(-2), np.uint64(18446744073709551614)) - def test_sign_bit(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_copy_detection_corner_case(self): # Ticket #658 np.indices((0, 3, 4)).T.reshape(-1, 3) @@ -874,13 +873,13 @@ class TestRegression(object): # 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, level=rlevel): + 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, level=rlevel): + def test_object_array_refcounting(self): # Ticket #633 if not hasattr(sys, 'getrefcount'): return @@ -983,7 +982,7 @@ class TestRegression(object): del tmp # Avoid pyflakes unused variable warning - def test_mem_custom_float_to_array(self, level=rlevel): + def test_mem_custom_float_to_array(self): # Ticket 702 class MyFloat(object): def __float__(self): @@ -992,7 +991,7 @@ class TestRegression(object): tmp = np.atleast_1d([MyFloat()]) tmp.astype(float) # Should succeed - def test_object_array_refcount_self_assign(self, level=rlevel): + def test_object_array_refcount_self_assign(self): # Ticket #711 class VictimObject(object): deleted = False @@ -1009,23 +1008,23 @@ class TestRegression(object): arr[:] = arr # trying to induce a segfault by doing it again... assert_(not arr[0].deleted) - def test_mem_fromiter_invalid_dtype_string(self, level=rlevel): + 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, level=rlevel): + 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, level=rlevel): + def test_mem_0d_array_index(self): # Ticket #714 np.zeros(10)[np.array(0)] - def test_floats_from_string(self, level=rlevel): + def test_floats_from_string(self): # Ticket #640, floats from string fsingle = np.single('1.234') fdouble = np.double('1.234') @@ -1034,7 +1033,7 @@ class TestRegression(object): assert_almost_equal(fdouble, 1.234) assert_almost_equal(flongdouble, 1.234) - def test_nonnative_endian_fill(self, level=rlevel): + def test_nonnative_endian_fill(self): # Non-native endian arrays were incorrectly filled with scalars # before r5034. if sys.byteorder == 'little': @@ -1045,7 +1044,7 @@ class TestRegression(object): x.fill(1) assert_equal(x, np.array([1], dtype=dtype)) - def test_dot_alignment_sse2(self, level=rlevel): + def test_dot_alignment_sse2(self): # Test for ticket #551, changeset r5140 x = np.zeros((30, 40)) y = pickle.loads(pickle.dumps(x)) @@ -1054,7 +1053,7 @@ class TestRegression(object): # This shouldn't cause a segmentation fault: np.dot(z, y) - def test_astype_copy(self, level=rlevel): + 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. @@ -1072,7 +1071,7 @@ class TestRegression(object): assert_((xp.__array_interface__['data'][0] != xpd.__array_interface__['data'][0])) - def test_compress_small_type(self, level=rlevel): + def test_compress_small_type(self): # Ticket #789, changeset 5217. # compress with out argument segfaulted if cannot cast safely import numpy as np @@ -1086,7 +1085,7 @@ class TestRegression(object): except TypeError: pass - def test_attributes(self, level=rlevel): + def test_attributes(self): # Ticket #791 class TestArray(np.ndarray): def __new__(cls, data, info): @@ -1158,7 +1157,7 @@ class TestRegression(object): assert_(type(dat.nonzero()[0]) is np.ndarray) assert_(type(dat.nonzero()[1]) is np.ndarray) - def test_recarray_tolist(self, level=rlevel): + def test_recarray_tolist(self): # Ticket #793, changeset r5215 # Comparisons fail for NaN, so we can't use random memory # for the test. @@ -1173,12 +1172,12 @@ class TestRegression(object): a = np.arange(5) assert_raises(ValueError, a.item) - def test_char_array_creation(self, level=rlevel): + 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, level=rlevel): + def test_unaligned_unicode_access(self): # Ticket #825 for i in range(1, 9): msg = 'unicode offset: %d chars' % i @@ -1189,7 +1188,7 @@ class TestRegression(object): else: assert_equal(str(x), "[('a', u'b')]", err_msg=msg) - def test_sign_for_complex_nan(self, level=rlevel): + 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]) @@ -1197,7 +1196,7 @@ class TestRegression(object): 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, level=rlevel): + def test_for_equal_names(self): # Ticket #674 dt = np.dtype([('foo', float), ('bar', float)]) a = np.zeros(10, dt) @@ -1207,7 +1206,7 @@ class TestRegression(object): assert_(a.dtype.names[0] == "notfoo") assert_(a.dtype.names[1] == "bar") - def test_for_object_scalar_creation(self, level=rlevel): + def test_for_object_scalar_creation(self): # Ticket #816 a = np.object_() b = np.object_(3) @@ -1226,7 +1225,7 @@ class TestRegression(object): x = np.array([[0, 1], [2, 3]]) assert_raises(TypeError, x.resize, (2, 2), order='C') - def test_for_zero_length_in_choose(self, level=rlevel): + def test_for_zero_length_in_choose(self): "Ticket #882" a = np.array(1) assert_raises(ValueError, lambda x: x.choose([]), a) @@ -1235,7 +1234,7 @@ class TestRegression(object): "Ticket #947." assert_raises(ValueError, lambda: np.array([1], ndmin=33)) - def test_void_scalar_with_titles(self, level=rlevel): + def test_void_scalar_with_titles(self): # No ticket data = [('john', 4), ('mary', 5)] dtype1 = [(('source:yy', 'name'), 'O'), (('source:xx', 'id'), int)] @@ -1491,7 +1490,7 @@ class TestRegression(object): # Check if log1p is behaving on 32 bit intel systems. assert_(np.isfinite(np.log1p(np.exp2(-53)))) - def test_fromiter_comparison(self, level=rlevel): + 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]))) diff --git a/numpy/core/tests/test_scalarmath.py b/numpy/core/tests/test_scalarmath.py index d2e326d24..cff9f7985 100644 --- a/numpy/core/tests/test_scalarmath.py +++ b/numpy/core/tests/test_scalarmath.py @@ -23,12 +23,12 @@ floating_types = np.floating.__subclasses__() # This compares scalarmath against ufuncs. class TestTypes(object): - def test_types(self, level=1): + def test_types(self): for atype in types: a = atype(1) assert_(a == 1, "error with %r: got %r" % (atype, a)) - def test_type_add(self, level=1): + def test_type_add(self): # list of types for k, atype in enumerate(types): a_scalar = atype(3) @@ -48,7 +48,7 @@ class TestTypes(object): "error with types (%d/'%c' + %d/'%c')" % (k, np.dtype(atype).char, l, np.dtype(btype).char)) - def test_type_create(self, level=1): + def test_type_create(self): for k, atype in enumerate(types): a = np.array([1, 2, 3], atype) b = atype([1, 2, 3]) diff --git a/numpy/lib/tests/test_regression.py b/numpy/lib/tests/test_regression.py index 74c47df7c..d96d3422d 100644 --- a/numpy/lib/tests/test_regression.py +++ b/numpy/lib/tests/test_regression.py @@ -10,16 +10,14 @@ from numpy.testing import ( ) from numpy.compat import unicode -rlevel = 1 - class TestRegression(object): - def test_poly1d(self, level=rlevel): + def test_poly1d(self): # Ticket #28 assert_equal(np.poly1d([1]) - np.poly1d([1, 0]), np.poly1d([-1, 1])) - def test_cov_parameters(self, level=rlevel): + def test_cov_parameters(self): # Ticket #91 x = np.random.random((3, 3)) y = x.copy() @@ -27,57 +25,57 @@ class TestRegression(object): np.cov(y, rowvar=0) assert_array_equal(x, y) - def test_mem_digitize(self, level=rlevel): + def test_mem_digitize(self): # Ticket #95 for i in range(100): np.digitize([1, 2, 3, 4], [1, 3]) np.digitize([0, 1, 2, 3, 4], [1, 3]) - def test_unique_zero_sized(self, level=rlevel): + def test_unique_zero_sized(self): # Ticket #205 assert_array_equal([], np.unique(np.array([]))) - def test_mem_vectorise(self, level=rlevel): + def test_mem_vectorise(self): # Ticket #325 vt = np.vectorize(lambda *args: args) vt(np.zeros((1, 2, 1)), np.zeros((2, 1, 1)), np.zeros((1, 1, 2))) vt(np.zeros((1, 2, 1)), np.zeros((2, 1, 1)), np.zeros((1, 1, 2)), np.zeros((2, 2))) - def test_mgrid_single_element(self, level=rlevel): + def test_mgrid_single_element(self): # Ticket #339 assert_array_equal(np.mgrid[0:0:1j], [0]) assert_array_equal(np.mgrid[0:0], []) - def test_refcount_vectorize(self, level=rlevel): + def test_refcount_vectorize(self): # Ticket #378 def p(x, y): return 123 v = np.vectorize(p) _assert_valid_refcount(v) - def test_poly1d_nan_roots(self, level=rlevel): + def test_poly1d_nan_roots(self): # Ticket #396 p = np.poly1d([np.nan, np.nan, 1], r=0) assert_raises(np.linalg.LinAlgError, getattr, p, "r") - def test_mem_polymul(self, level=rlevel): + def test_mem_polymul(self): # Ticket #448 np.polymul([], [1.]) - def test_mem_string_concat(self, level=rlevel): + def test_mem_string_concat(self): # Ticket #469 x = np.array([]) np.append(x, 'asdasd\tasdasd') - def test_poly_div(self, level=rlevel): + def test_poly_div(self): # Ticket #553 u = np.poly1d([1, 2, 3]) v = np.poly1d([1, 2, 3, 4, 5]) q, r = np.polydiv(u, v) assert_equal(q*v + r, u) - def test_poly_eq(self, level=rlevel): + def test_poly_eq(self): # Ticket #554 x = np.poly1d([1, 2, 3]) y = np.poly1d([3, 4]) @@ -134,11 +132,11 @@ class TestRegression(object): # Shouldn't crash: list(np.ndenumerate(np.array([[]]))) - def test_asfarray_none(self, level=rlevel): + def test_asfarray_none(self): # Test for changeset r5065 assert_array_equal(np.array([np.nan]), np.asfarray([None])) - def test_large_fancy_indexing(self, level=rlevel): + def test_large_fancy_indexing(self): # Large enough to fail on 64-bit. nbits = np.dtype(np.intp).itemsize * 8 thesize = int((2**nbits)**(1.0/5.0)+1) @@ -158,12 +156,12 @@ class TestRegression(object): assert_raises(ValueError, dp) assert_raises(ValueError, dp2) - def test_void_coercion(self, level=rlevel): + def test_void_coercion(self): dt = np.dtype([('a', 'f4'), ('b', 'i4')]) x = np.zeros((1,), dt) assert_(np.r_[x, x].dtype == dt) - def test_who_with_0dim_array(self, level=rlevel): + def test_who_with_0dim_array(self): # ticket #1243 import os import sys diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py index 9e739ea63..d0afeefd9 100644 --- a/numpy/lib/tests/test_shape_base.py +++ b/numpy/lib/tests/test_shape_base.py @@ -19,7 +19,7 @@ class TestApplyAlongAxis(object): assert_array_equal( apply_along_axis(len, 0, a), len(a)*np.ones(a.shape[1])) - def test_simple101(self, level=11): + def test_simple101(self): a = np.ones((10, 101), 'd') assert_array_equal( apply_along_axis(len, 0, a), len(a)*np.ones(a.shape[1])) diff --git a/numpy/linalg/tests/test_regression.py b/numpy/linalg/tests/test_regression.py index 558abca09..07d72620b 100644 --- a/numpy/linalg/tests/test_regression.py +++ b/numpy/linalg/tests/test_regression.py @@ -12,12 +12,9 @@ from numpy.testing import ( ) -rlevel = 1 - - class TestRegression(object): - def test_eig_build(self, level=rlevel): + def test_eig_build(self): # Ticket #652 rva = array([1.03221168e+02 + 0.j, -1.91843603e+01 + 0.j, @@ -40,7 +37,7 @@ class TestRegression(object): rva.sort() assert_array_almost_equal(va, rva) - def test_eigh_build(self, level=rlevel): + def test_eigh_build(self): # Ticket 662. rvals = [68.60568999, 89.57756725, 106.67185574] @@ -51,7 +48,7 @@ class TestRegression(object): vals, vecs = linalg.eigh(cov) assert_array_almost_equal(vals, rvals) - def test_svd_build(self, level=rlevel): + def test_svd_build(self): # Ticket 627. a = array([[0., 1.], [1., 1.], [2., 1.], [3., 1.]]) m, n = a.shape diff --git a/numpy/ma/tests/test_regression.py b/numpy/ma/tests/test_regression.py index 34dd29d92..925b21a14 100644 --- a/numpy/ma/tests/test_regression.py +++ b/numpy/ma/tests/test_regression.py @@ -8,21 +8,19 @@ from numpy.testing import ( suppress_warnings ) -rlevel = 1 - class TestRegression(object): - def test_masked_array_create(self,level=rlevel): + def test_masked_array_create(self): # Ticket #17 x = np.ma.masked_array([0, 1, 2, 3, 0, 4, 5, 6], mask=[0, 0, 0, 1, 1, 1, 0, 0]) assert_array_equal(np.ma.nonzero(x), [[1, 2, 6, 7]]) - def test_masked_array(self,level=rlevel): + def test_masked_array(self): # Ticket #61 np.ma.array(1, mask=[1]) - def test_mem_masked_where(self,level=rlevel): + def test_mem_masked_where(self): # Ticket #62 from numpy.ma import masked_where, MaskType a = np.zeros((1, 1)) @@ -30,7 +28,7 @@ class TestRegression(object): c = masked_where(b, a) a-c - def test_masked_array_multiply(self,level=rlevel): + def test_masked_array_multiply(self): # Ticket #254 a = np.ma.zeros((4, 1)) a[2, 0] = np.ma.masked @@ -38,7 +36,7 @@ class TestRegression(object): a*b b*a - def test_masked_array_repeat(self, level=rlevel): + def test_masked_array_repeat(self): # Ticket #271 np.ma.array([1], mask=False).repeat(10) diff --git a/numpy/matrixlib/tests/test_regression.py b/numpy/matrixlib/tests/test_regression.py index b681374f2..32cb38ac7 100644 --- a/numpy/matrixlib/tests/test_regression.py +++ b/numpy/matrixlib/tests/test_regression.py @@ -5,15 +5,14 @@ from numpy.testing import ( run_module_suite, assert_, assert_equal, assert_raises ) -rlevel = 1 class TestRegression(object): - def test_kron_matrix(self, level=rlevel): + def test_kron_matrix(self): # Ticket #71 x = np.matrix('[1 0; 1 0]') assert_equal(type(np.kron(x, x)), type(x)) - def test_matrix_properties(self,level=rlevel): + def test_matrix_properties(self): # Ticket #125 a = np.matrix([1.0], dtype=float) assert_(type(a.real) is np.matrix) @@ -22,14 +21,14 @@ class TestRegression(object): assert_(type(c) is np.ndarray) assert_(type(d) is np.ndarray) - def test_matrix_multiply_by_1d_vector(self, level=rlevel): + def test_matrix_multiply_by_1d_vector(self): # Ticket #473 def mul(): np.mat(np.eye(2))*np.ones(2) assert_raises(ValueError, mul) - def test_matrix_std_argmax(self,level=rlevel): + def test_matrix_std_argmax(self): # Ticket #83 x = np.asmatrix(np.random.uniform(0, 1, (3, 3))) assert_equal(x.std().shape, ()) |