Python numpy.intp() Examples
The following are 30
code examples of numpy.intp().
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Example #1
Source File: test_indexing.py From recruit with Apache License 2.0 | 6 votes |
def test_get_indexer_consistency(idx): # See GH 16819 if isinstance(idx, IntervalIndex): pass if idx.is_unique or isinstance(idx, CategoricalIndex): indexer = idx.get_indexer(idx[0:2]) assert isinstance(indexer, np.ndarray) assert indexer.dtype == np.intp else: e = "Reindexing only valid with uniquely valued Index objects" with pytest.raises(InvalidIndexError, match=e): idx.get_indexer(idx[0:2]) indexer, _ = idx.get_indexer_non_unique(idx[0:2]) assert isinstance(indexer, np.ndarray) assert indexer.dtype == np.intp
Example #2
Source File: test_index_tricks.py From recruit with Apache License 2.0 | 6 votes |
def test_big_indices(self): # ravel_multi_index for big indices (issue #7546) if np.intp == np.int64: arr = ([1, 29], [3, 5], [3, 117], [19, 2], [2379, 1284], [2, 2], [0, 1]) assert_equal( np.ravel_multi_index(arr, (41, 7, 120, 36, 2706, 8, 6)), [5627771580, 117259570957]) # test overflow checking for too big array (issue #7546) dummy_arr = ([0],[0]) half_max = np.iinfo(np.intp).max // 2 assert_equal( np.ravel_multi_index(dummy_arr, (half_max, 2)), [0]) assert_raises(ValueError, np.ravel_multi_index, dummy_arr, (half_max+1, 2)) assert_equal( np.ravel_multi_index(dummy_arr, (half_max, 2), order='F'), [0]) assert_raises(ValueError, np.ravel_multi_index, dummy_arr, (half_max+1, 2), order='F')
Example #3
Source File: test_shape_base.py From recruit with Apache License 2.0 | 6 votes |
def test_invalid(self): """ Test it errors when indices has too few dimensions """ a = np.ones((10, 10)) ai = np.ones((10, 2), dtype=np.intp) # sanity check take_along_axis(a, ai, axis=1) # not enough indices assert_raises(ValueError, take_along_axis, a, np.array(1), axis=1) # bool arrays not allowed assert_raises(IndexError, take_along_axis, a, ai.astype(bool), axis=1) # float arrays not allowed assert_raises(IndexError, take_along_axis, a, ai.astype(float), axis=1) # invalid axis assert_raises(np.AxisError, take_along_axis, a, ai, axis=10)
Example #4
Source File: test_core.py From recruit with Apache License 2.0 | 6 votes |
def test_count_func(self): # Tests count assert_equal(1, count(1)) assert_equal(0, array(1, mask=[1])) ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) res = count(ott) assert_(res.dtype.type is np.intp) assert_equal(3, res) ott = ott.reshape((2, 2)) res = count(ott) assert_(res.dtype.type is np.intp) assert_equal(3, res) res = count(ott, 0) assert_(isinstance(res, ndarray)) assert_equal([1, 2], res) assert_(getmask(res) is nomask) ott = array([0., 1., 2., 3.]) res = count(ott, 0) assert_(isinstance(res, ndarray)) assert_(res.dtype.type is np.intp) assert_raises(np.AxisError, ott.count, axis=1)
Example #5
Source File: _internal.py From recruit with Apache License 2.0 | 6 votes |
def _getintp_ctype(): val = _getintp_ctype.cache if val is not None: return val if ctypes is None: import numpy as np val = dummy_ctype(np.intp) else: char = dtype('p').char if (char == 'i'): val = ctypes.c_int elif char == 'l': val = ctypes.c_long elif char == 'q': val = ctypes.c_longlong else: val = ctypes.c_long _getintp_ctype.cache = val return val
Example #6
Source File: test_indexing.py From recruit with Apache License 2.0 | 6 votes |
def test_reverse_strides_and_subspace_bufferinit(self): # This tests that the strides are not reversed for simple and # subspace fancy indexing. a = np.ones(5) b = np.zeros(5, dtype=np.intp)[::-1] c = np.arange(5)[::-1] a[b] = c # If the strides are not reversed, the 0 in the arange comes last. assert_equal(a[0], 0) # This also tests that the subspace buffer is initialized: a = np.ones((5, 2)) c = np.arange(10).reshape(5, 2)[::-1] a[b, :] = c assert_equal(a[0], [0, 1])
Example #7
Source File: methods.py From recruit with Apache License 2.0 | 6 votes |
def test_searchsorted(self, data_for_sorting, as_series): b, c, a = data_for_sorting arr = type(data_for_sorting)._from_sequence([a, b, c]) if as_series: arr = pd.Series(arr) assert arr.searchsorted(a) == 0 assert arr.searchsorted(a, side="right") == 1 assert arr.searchsorted(b) == 1 assert arr.searchsorted(b, side="right") == 2 assert arr.searchsorted(c) == 2 assert arr.searchsorted(c, side="right") == 3 result = arr.searchsorted(arr.take([0, 2])) expected = np.array([0, 2], dtype=np.intp) tm.assert_numpy_array_equal(result, expected) # sorter sorter = np.array([1, 2, 0]) assert data_for_sorting.searchsorted(a, sorter=sorter) == 0
Example #8
Source File: fermionic_simulation.py From OpenFermion-Cirq with Apache License 2.0 | 6 votes |
def _eigen_components(self): components = [(0, np.diag([1, 1, 1, 0, 1, 0, 0, 1]))] nontrivial_part = np.zeros((3, 3), dtype=np.complex128) for ij, w in zip([(1, 2), (0, 2), (0, 1)], self.weights): nontrivial_part[ij] = w nontrivial_part[ij[::-1]] = w.conjugate() assert np.allclose(nontrivial_part, nontrivial_part.conj().T) eig_vals, eig_vecs = np.linalg.eigh(nontrivial_part) for eig_val, eig_vec in zip(eig_vals, eig_vecs.T): exp_factor = -eig_val / np.pi proj = np.zeros((8, 8), dtype=np.complex128) nontrivial_indices = np.array([3, 5, 6], dtype=np.intp) proj[nontrivial_indices[:, np.newaxis], nontrivial_indices] = ( np.outer(eig_vec.conjugate(), eig_vec)) components.append((exp_factor, proj)) return components
Example #9
Source File: test_ops.py From recruit with Apache License 2.0 | 6 votes |
def test_nat(self): assert pd.TimedeltaIndex._na_value is pd.NaT assert pd.TimedeltaIndex([])._na_value is pd.NaT idx = pd.TimedeltaIndex(['1 days', '2 days']) assert idx._can_hold_na tm.assert_numpy_array_equal(idx._isnan, np.array([False, False])) assert idx.hasnans is False tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.intp)) idx = pd.TimedeltaIndex(['1 days', 'NaT']) assert idx._can_hold_na tm.assert_numpy_array_equal(idx._isnan, np.array([False, True])) assert idx.hasnans is True tm.assert_numpy_array_equal(idx._nan_idxs, np.array([1], dtype=np.intp))
Example #10
Source File: common.py From recruit with Apache License 2.0 | 6 votes |
def test_get_indexer_consistency(self): # See GH 16819 for name, index in self.indices.items(): if isinstance(index, IntervalIndex): continue if index.is_unique or isinstance(index, CategoricalIndex): indexer = index.get_indexer(index[0:2]) assert isinstance(indexer, np.ndarray) assert indexer.dtype == np.intp else: e = "Reindexing only valid with uniquely valued Index objects" with pytest.raises(InvalidIndexError, match=e): index.get_indexer(index[0:2]) indexer, _ = index.get_indexer_non_unique(index[0:2]) assert isinstance(indexer, np.ndarray) assert indexer.dtype == np.intp
Example #11
Source File: test_numeric.py From recruit with Apache License 2.0 | 6 votes |
def test_get_indexer(self): target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63) indexer = self.index.get_indexer(target) expected = np.array([0, -1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp) tm.assert_numpy_array_equal(indexer, expected) target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63) indexer = self.index.get_indexer(target, method='pad') expected = np.array([0, 0, 1, 2, 3, 4, 4, 4, 4, 4], dtype=np.intp) tm.assert_numpy_array_equal(indexer, expected) target = UInt64Index(np.arange(10).astype('uint64') * 5 + 2**63) indexer = self.index.get_indexer(target, method='backfill') expected = np.array([0, 1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp) tm.assert_numpy_array_equal(indexer, expected)
Example #12
Source File: test_datetime.py From recruit with Apache License 2.0 | 6 votes |
def test_sort_values(self): idx = DatetimeIndex(['2000-01-04', '2000-01-01', '2000-01-02']) ordered = idx.sort_values() assert ordered.is_monotonic ordered = idx.sort_values(ascending=False) assert ordered[::-1].is_monotonic ordered, dexer = idx.sort_values(return_indexer=True) assert ordered.is_monotonic tm.assert_numpy_array_equal(dexer, np.array([1, 2, 0], dtype=np.intp)) ordered, dexer = idx.sort_values(return_indexer=True, ascending=False) assert ordered[::-1].is_monotonic tm.assert_numpy_array_equal(dexer, np.array([0, 2, 1], dtype=np.intp))
Example #13
Source File: test_datetime.py From recruit with Apache License 2.0 | 6 votes |
def test_factorize_dst(self): # GH 13750 idx = pd.date_range('2016-11-06', freq='H', periods=12, tz='US/Eastern') for obj in [idx, pd.Series(idx)]: arr, res = obj.factorize() tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp)) tm.assert_index_equal(res, idx) idx = pd.date_range('2016-06-13', freq='H', periods=12, tz='US/Eastern') for obj in [idx, pd.Series(idx)]: arr, res = obj.factorize() tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp)) tm.assert_index_equal(res, idx)
Example #14
Source File: test_ops.py From recruit with Apache License 2.0 | 6 votes |
def test_nat(self, tz_naive_fixture): tz = tz_naive_fixture assert pd.DatetimeIndex._na_value is pd.NaT assert pd.DatetimeIndex([])._na_value is pd.NaT idx = pd.DatetimeIndex(['2011-01-01', '2011-01-02'], tz=tz) assert idx._can_hold_na tm.assert_numpy_array_equal(idx._isnan, np.array([False, False])) assert idx.hasnans is False tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.intp)) idx = pd.DatetimeIndex(['2011-01-01', 'NaT'], tz=tz) assert idx._can_hold_na tm.assert_numpy_array_equal(idx._isnan, np.array([False, True])) assert idx.hasnans is True tm.assert_numpy_array_equal(idx._nan_idxs, np.array([1], dtype=np.intp))
Example #15
Source File: test_indexing.py From recruit with Apache License 2.0 | 6 votes |
def test_get_indexer_non_unique(self): # GH 17717 p1 = pd.Period('2017-09-02') p2 = pd.Period('2017-09-03') p3 = pd.Period('2017-09-04') p4 = pd.Period('2017-09-05') idx1 = pd.PeriodIndex([p1, p2, p1]) idx2 = pd.PeriodIndex([p2, p1, p3, p4]) result = idx1.get_indexer_non_unique(idx2) expected_indexer = np.array([1, 0, 2, -1, -1], dtype=np.intp) expected_missing = np.array([2, 3], dtype=np.int64) tm.assert_numpy_array_equal(result[0], expected_indexer) tm.assert_numpy_array_equal(result[1], expected_missing) # TODO: This method came from test_period; de-dup with version above
Example #16
Source File: test_range.py From recruit with Apache License 2.0 | 6 votes |
def test_join_left(self): # Join with Int64Index other = Int64Index(np.arange(25, 14, -1)) res, lidx, ridx = self.index.join(other, how='left', return_indexers=True) eres = self.index eridx = np.array([-1, -1, -1, -1, -1, -1, -1, -1, 9, 7], dtype=np.intp) assert isinstance(res, RangeIndex) tm.assert_index_equal(res, eres) assert lidx is None tm.assert_numpy_array_equal(ridx, eridx) # Join withRangeIndex other = Int64Index(np.arange(25, 14, -1)) res, lidx, ridx = self.index.join(other, how='left', return_indexers=True) assert isinstance(res, RangeIndex) tm.assert_index_equal(res, eres) assert lidx is None tm.assert_numpy_array_equal(ridx, eridx)
Example #17
Source File: test_ops.py From recruit with Apache License 2.0 | 6 votes |
def test_nat(self): assert pd.PeriodIndex._na_value is NaT assert pd.PeriodIndex([], freq='M')._na_value is NaT idx = pd.PeriodIndex(['2011-01-01', '2011-01-02'], freq='D') assert idx._can_hold_na tm.assert_numpy_array_equal(idx._isnan, np.array([False, False])) assert idx.hasnans is False tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.intp)) idx = pd.PeriodIndex(['2011-01-01', 'NaT'], freq='D') assert idx._can_hold_na tm.assert_numpy_array_equal(idx._isnan, np.array([False, True])) assert idx.hasnans is True tm.assert_numpy_array_equal(idx._nan_idxs, np.array([1], dtype=np.intp))
Example #18
Source File: test_timedelta.py From recruit with Apache License 2.0 | 6 votes |
def test_factorize(self): idx1 = TimedeltaIndex(['1 day', '1 day', '2 day', '2 day', '3 day', '3 day']) exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp) exp_idx = TimedeltaIndex(['1 day', '2 day', '3 day']) arr, idx = idx1.factorize() tm.assert_numpy_array_equal(arr, exp_arr) tm.assert_index_equal(idx, exp_idx) arr, idx = idx1.factorize(sort=True) tm.assert_numpy_array_equal(arr, exp_arr) tm.assert_index_equal(idx, exp_idx) # freq must be preserved idx3 = timedelta_range('1 day', periods=4, freq='s') exp_arr = np.array([0, 1, 2, 3], dtype=np.intp) arr, idx = idx3.factorize() tm.assert_numpy_array_equal(arr, exp_arr) tm.assert_index_equal(idx, idx3)
Example #19
Source File: common.py From recruit with Apache License 2.0 | 5 votes |
def test_reindex_base(self): idx = self.create_index() expected = np.arange(idx.size, dtype=np.intp) actual = idx.get_indexer(idx) tm.assert_numpy_array_equal(expected, actual) with pytest.raises(ValueError, match='Invalid fill method'): idx.get_indexer(idx, method='invalid')
Example #20
Source File: test_base.py From recruit with Apache License 2.0 | 5 votes |
def test_get_indexer_nearest(self, method, tolerance, indexer, expected): index = Index(np.arange(10)) actual = index.get_indexer(indexer, method=method, tolerance=tolerance) tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
Example #21
Source File: test_base.py From recruit with Apache License 2.0 | 5 votes |
def test_get_indexer(self): index1 = Index([1, 2, 3, 4, 5]) index2 = Index([2, 4, 6]) r1 = index1.get_indexer(index2) e1 = np.array([1, 3, -1], dtype=np.intp) assert_almost_equal(r1, e1)
Example #22
Source File: test_range.py From recruit with Apache License 2.0 | 5 votes |
def test_join_non_unique(self): other = Index([4, 4, 3, 3]) res, lidx, ridx = self.index.join(other, return_indexers=True) eres = Int64Index([0, 2, 4, 4, 6, 8, 10, 12, 14, 16, 18]) elidx = np.array([0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9], dtype=np.intp) eridx = np.array([-1, -1, 0, 1, -1, -1, -1, -1, -1, -1, -1], dtype=np.intp) tm.assert_index_equal(res, eres) tm.assert_numpy_array_equal(lidx, elidx) tm.assert_numpy_array_equal(ridx, eridx)
Example #23
Source File: test_base.py From recruit with Apache License 2.0 | 5 votes |
def test_get_indexer_nearest_decreasing(self, method, expected): index = Index(np.arange(10))[::-1] actual = index.get_indexer([0, 5, 9], method=method) tm.assert_numpy_array_equal(actual, np.array([9, 4, 0], dtype=np.intp)) actual = index.get_indexer([0.2, 1.8, 8.5], method=method) tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
Example #24
Source File: test_function_base.py From recruit with Apache License 2.0 | 5 votes |
def test_dtype_reference_leaks(self): # gh-6805 intp_refcount = sys.getrefcount(np.dtype(np.intp)) double_refcount = sys.getrefcount(np.dtype(np.double)) for j in range(10): np.bincount([1, 2, 3]) assert_equal(sys.getrefcount(np.dtype(np.intp)), intp_refcount) assert_equal(sys.getrefcount(np.dtype(np.double)), double_refcount) for j in range(10): np.bincount([1, 2, 3], [4, 5, 6]) assert_equal(sys.getrefcount(np.dtype(np.intp)), intp_refcount) assert_equal(sys.getrefcount(np.dtype(np.double)), double_refcount)
Example #25
Source File: test_category.py From recruit with Apache License 2.0 | 5 votes |
def test_reindex_dtype(self): c = CategoricalIndex(['a', 'b', 'c', 'a']) res, indexer = c.reindex(['a', 'c']) tm.assert_index_equal(res, Index(['a', 'a', 'c']), exact=True) tm.assert_numpy_array_equal(indexer, np.array([0, 3, 2], dtype=np.intp)) c = CategoricalIndex(['a', 'b', 'c', 'a']) res, indexer = c.reindex(Categorical(['a', 'c'])) exp = CategoricalIndex(['a', 'a', 'c'], categories=['a', 'c']) tm.assert_index_equal(res, exp, exact=True) tm.assert_numpy_array_equal(indexer, np.array([0, 3, 2], dtype=np.intp)) c = CategoricalIndex(['a', 'b', 'c', 'a'], categories=['a', 'b', 'c', 'd']) res, indexer = c.reindex(['a', 'c']) exp = Index(['a', 'a', 'c'], dtype='object') tm.assert_index_equal(res, exp, exact=True) tm.assert_numpy_array_equal(indexer, np.array([0, 3, 2], dtype=np.intp)) c = CategoricalIndex(['a', 'b', 'c', 'a'], categories=['a', 'b', 'c', 'd']) res, indexer = c.reindex(Categorical(['a', 'c'])) exp = CategoricalIndex(['a', 'a', 'c'], categories=['a', 'c']) tm.assert_index_equal(res, exp, exact=True) tm.assert_numpy_array_equal(indexer, np.array([0, 3, 2], dtype=np.intp))
Example #26
Source File: test_category.py From recruit with Apache License 2.0 | 5 votes |
def test_reindex_empty_index(self): # See GH16770 c = CategoricalIndex([]) res, indexer = c.reindex(['a', 'b']) tm.assert_index_equal(res, Index(['a', 'b']), exact=True) tm.assert_numpy_array_equal(indexer, np.array([-1, -1], dtype=np.intp))
Example #27
Source File: test_category.py From recruit with Apache License 2.0 | 5 votes |
def test_get_indexer(self): idx1 = CategoricalIndex(list('aabcde'), categories=list('edabc')) idx2 = CategoricalIndex(list('abf')) for indexer in [idx2, list('abf'), Index(list('abf'))]: r1 = idx1.get_indexer(idx2) assert_almost_equal(r1, np.array([0, 1, 2, -1], dtype=np.intp)) pytest.raises(NotImplementedError, lambda: idx2.get_indexer(idx1, method='pad')) pytest.raises(NotImplementedError, lambda: idx2.get_indexer(idx1, method='backfill')) pytest.raises(NotImplementedError, lambda: idx2.get_indexer(idx1, method='nearest'))
Example #28
Source File: test_numeric.py From recruit with Apache License 2.0 | 5 votes |
def test_get_indexer(self): idx = Float64Index([0.0, 1.0, 2.0]) tm.assert_numpy_array_equal(idx.get_indexer(idx), np.array([0, 1, 2], dtype=np.intp)) target = [-0.1, 0.5, 1.1] tm.assert_numpy_array_equal(idx.get_indexer(target, 'pad'), np.array([-1, 0, 1], dtype=np.intp)) tm.assert_numpy_array_equal(idx.get_indexer(target, 'backfill'), np.array([0, 1, 2], dtype=np.intp)) tm.assert_numpy_array_equal(idx.get_indexer(target, 'nearest'), np.array([0, 1, 1], dtype=np.intp))
Example #29
Source File: test_numeric.py From recruit with Apache License 2.0 | 5 votes |
def test_join_left(self): other = Int64Index([7, 12, 25, 1, 2, 5]) other_mono = Int64Index([1, 2, 5, 7, 12, 25]) # not monotonic res, lidx, ridx = self.index.join(other, how='left', return_indexers=True) eres = self.index eridx = np.array([-1, 4, -1, -1, -1, -1, 1, -1, -1, -1], dtype=np.intp) assert isinstance(res, Int64Index) tm.assert_index_equal(res, eres) assert lidx is None tm.assert_numpy_array_equal(ridx, eridx) # monotonic res, lidx, ridx = self.index.join(other_mono, how='left', return_indexers=True) eridx = np.array([-1, 1, -1, -1, -1, -1, 4, -1, -1, -1], dtype=np.intp) assert isinstance(res, Int64Index) tm.assert_index_equal(res, eres) assert lidx is None tm.assert_numpy_array_equal(ridx, eridx) # non-unique idx = Index([1, 1, 2, 5]) idx2 = Index([1, 2, 5, 7, 9]) res, lidx, ridx = idx2.join(idx, how='left', return_indexers=True) eres = Index([1, 1, 2, 5, 7, 9]) # 1 is in idx2, so it should be x2 eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp) elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp) tm.assert_index_equal(res, eres) tm.assert_numpy_array_equal(lidx, elidx) tm.assert_numpy_array_equal(ridx, eridx)
Example #30
Source File: test_numeric.py From recruit with Apache License 2.0 | 5 votes |
def test_join_non_unique(self): left = Index([4, 4, 3, 3]) joined, lidx, ridx = left.join(left, return_indexers=True) exp_joined = Index([3, 3, 3, 3, 4, 4, 4, 4]) tm.assert_index_equal(joined, exp_joined) exp_lidx = np.array([2, 2, 3, 3, 0, 0, 1, 1], dtype=np.intp) tm.assert_numpy_array_equal(lidx, exp_lidx) exp_ridx = np.array([2, 3, 2, 3, 0, 1, 0, 1], dtype=np.intp) tm.assert_numpy_array_equal(ridx, exp_ridx)