golden hour

/opt/alt/python37/lib64/python3.7/site-packages/numpy/lib/tests

File/Folder	Size	Actions
__pycache__	-
data	-
test__datasource.py	10.16 KB
test__iotools.py	13.15 KB
test__version.py	2.08 KB
test_arraypad.py	42.68 KB
test_arraysetops.py	15.49 KB
test_arrayterator.py	1.42 KB
test_financial.py	6.62 KB
test_format.py	33.49 KB
test_function_base.py	126.81 KB
test_index_tricks.py	13.1 KB
test_io.py	75.59 KB
test_mixins.py	6.7 KB
test_nanfunctions.py	34.07 KB
test_packbits.py	12.63 KB
test_polynomial.py	7.03 KB
test_recfunctions.py	30.54 KB
test_regression.py	8.62 KB
test_shape_base.py	19.02 KB
test_stride_tricks.py	14.69 KB
test_twodim_base.py	16.72 KB
test_type_check.py	12.62 KB
test_ufunclike.py	2.96 KB
test_utils.py	1.62 KB

Edit: test_arraysetops.py

"""Test functions for 1D array set operations.

"""
from __future__ import division, absolute_import, print_function

import numpy as np
from numpy.testing import (
    run_module_suite, TestCase, assert_array_equal, assert_equal, assert_raises
    )
from numpy.lib.arraysetops import (
    ediff1d, intersect1d, setxor1d, union1d, setdiff1d, unique, in1d, isin
    )

class TestSetOps(TestCase):

def test_intersect1d(self):
        # unique inputs
        a = np.array([5, 7, 1, 2])
        b = np.array([2, 4, 3, 1, 5])

ec = np.array([1, 2, 5])
        c = intersect1d(a, b, assume_unique=True)
        assert_array_equal(c, ec)

# non-unique inputs
        a = np.array([5, 5, 7, 1, 2])
        b = np.array([2, 1, 4, 3, 3, 1, 5])

ed = np.array([1, 2, 5])
        c = intersect1d(a, b)
        assert_array_equal(c, ed)

assert_array_equal([], intersect1d([], []))

def test_setxor1d(self):
        a = np.array([5, 7, 1, 2])
        b = np.array([2, 4, 3, 1, 5])

ec = np.array([3, 4, 7])
        c = setxor1d(a, b)
        assert_array_equal(c, ec)

a = np.array([1, 2, 3])
        b = np.array([6, 5, 4])

ec = np.array([1, 2, 3, 4, 5, 6])
        c = setxor1d(a, b)
        assert_array_equal(c, ec)

a = np.array([1, 8, 2, 3])
        b = np.array([6, 5, 4, 8])

ec = np.array([1, 2, 3, 4, 5, 6])
        c = setxor1d(a, b)
        assert_array_equal(c, ec)

assert_array_equal([], setxor1d([], []))

def test_ediff1d(self):
        zero_elem = np.array([])
        one_elem = np.array([1])
        two_elem = np.array([1, 2])

assert_array_equal([], ediff1d(zero_elem))
        assert_array_equal([0], ediff1d(zero_elem, to_begin=0))
        assert_array_equal([0], ediff1d(zero_elem, to_end=0))
        assert_array_equal([-1, 0], ediff1d(zero_elem, to_begin=-1, to_end=0))
        assert_array_equal([], ediff1d(one_elem))
        assert_array_equal([1], ediff1d(two_elem))
        assert_array_equal([7,1,9], ediff1d(two_elem, to_begin=7, to_end=9))
        assert_array_equal([5,6,1,7,8], ediff1d(two_elem, to_begin=[5,6], to_end=[7,8]))
        assert_array_equal([1,9], ediff1d(two_elem, to_end=9))
        assert_array_equal([1,7,8], ediff1d(two_elem, to_end=[7,8]))
        assert_array_equal([7,1], ediff1d(two_elem, to_begin=7))
        assert_array_equal([5,6,1], ediff1d(two_elem, to_begin=[5,6]))
        assert(isinstance(ediff1d(np.matrix(1)), np.matrix))
        assert(isinstance(ediff1d(np.matrix(1), to_begin=1), np.matrix))

def test_isin(self):
        # the tests for in1d cover most of isin's behavior
        # if in1d is removed, would need to change those tests to test
        # isin instead.
        def _isin_slow(a, b):
            b = np.asarray(b).flatten().tolist()
            return a in b
        isin_slow = np.vectorize(_isin_slow, otypes=[bool], excluded={1})
        def assert_isin_equal(a, b):
            x = isin(a, b)
            y = isin_slow(a, b)
            assert_array_equal(x, y)
            
        #multidimensional arrays in both arguments
        a = np.arange(24).reshape([2, 3, 4])
        b = np.array([[10, 20, 30], [0, 1, 3], [11, 22, 33]])
        assert_isin_equal(a, b)
        
        #array-likes as both arguments
        c = [(9, 8), (7, 6)]
        d = (9, 7)
        assert_isin_equal(c, d)
        
        #zero-d array:
        f = np.array(3)
        assert_isin_equal(f, b)
        assert_isin_equal(a, f)
        assert_isin_equal(f, f)
        
        #scalar:
        assert_isin_equal(5, b)
        assert_isin_equal(a, 6)
        assert_isin_equal(5, 6)
        
        #empty array-like:
        x = []
        assert_isin_equal(x, b)
        assert_isin_equal(a, x)
        assert_isin_equal(x, x)

def test_in1d(self):
        # we use two different sizes for the b array here to test the
        # two different paths in in1d().
        for mult in (1, 10):
            # One check without np.array to make sure lists are handled correct
            a = [5, 7, 1, 2]
            b = [2, 4, 3, 1, 5] * mult
            ec = np.array([True, False, True, True])
            c = in1d(a, b, assume_unique=True)
            assert_array_equal(c, ec)

a[0] = 8
            ec = np.array([False, False, True, True])
            c = in1d(a, b, assume_unique=True)
            assert_array_equal(c, ec)

a[0], a[3] = 4, 8
            ec = np.array([True, False, True, False])
            c = in1d(a, b, assume_unique=True)
            assert_array_equal(c, ec)

a = np.array([5, 4, 5, 3, 4, 4, 3, 4, 3, 5, 2, 1, 5, 5])
            b = [2, 3, 4] * mult
            ec = [False, True, False, True, True, True, True, True, True,
                  False, True, False, False, False]
            c = in1d(a, b)
            assert_array_equal(c, ec)

b = b + [5, 5, 4] * mult
            ec = [True, True, True, True, True, True, True, True, True, True,
                  True, False, True, True]
            c = in1d(a, b)
            assert_array_equal(c, ec)

a = np.array([5, 7, 1, 2])
            b = np.array([2, 4, 3, 1, 5] * mult)
            ec = np.array([True, False, True, True])
            c = in1d(a, b)
            assert_array_equal(c, ec)

a = np.array([5, 7, 1, 1, 2])
            b = np.array([2, 4, 3, 3, 1, 5] * mult)
            ec = np.array([True, False, True, True, True])
            c = in1d(a, b)
            assert_array_equal(c, ec)

a = np.array([5, 5])
            b = np.array([2, 2] * mult)
            ec = np.array([False, False])
            c = in1d(a, b)
            assert_array_equal(c, ec)

a = np.array([5])
        b = np.array([2])
        ec = np.array([False])
        c = in1d(a, b)
        assert_array_equal(c, ec)

assert_array_equal(in1d([], []), [])

def test_in1d_char_array(self):
        a = np.array(['a', 'b', 'c', 'd', 'e', 'c', 'e', 'b'])
        b = np.array(['a', 'c'])

ec = np.array([True, False, True, False, False, True, False, False])
        c = in1d(a, b)

assert_array_equal(c, ec)

def test_in1d_invert(self):
        "Test in1d's invert parameter"
        # We use two different sizes for the b array here to test the
        # two different paths in in1d().
        for mult in (1, 10):
            a = np.array([5, 4, 5, 3, 4, 4, 3, 4, 3, 5, 2, 1, 5, 5])
            b = [2, 3, 4] * mult
            assert_array_equal(np.invert(in1d(a, b)), in1d(a, b, invert=True))

def test_in1d_ravel(self):
        # Test that in1d ravels its input arrays. This is not documented
        # behavior however. The test is to ensure consistentency.
        a = np.arange(6).reshape(2, 3)
        b = np.arange(3, 9).reshape(3, 2)
        long_b = np.arange(3, 63).reshape(30, 2)
        ec = np.array([False, False, False, True, True, True])

assert_array_equal(in1d(a, b, assume_unique=True), ec)
        assert_array_equal(in1d(a, b, assume_unique=False), ec)
        assert_array_equal(in1d(a, long_b, assume_unique=True), ec)
        assert_array_equal(in1d(a, long_b, assume_unique=False), ec)

def test_union1d(self):
        a = np.array([5, 4, 7, 1, 2])
        b = np.array([2, 4, 3, 3, 2, 1, 5])

ec = np.array([1, 2, 3, 4, 5, 7])
        c = union1d(a, b)
        assert_array_equal(c, ec)

assert_array_equal([], union1d([], []))

def test_setdiff1d(self):
        a = np.array([6, 5, 4, 7, 1, 2, 7, 4])
        b = np.array([2, 4, 3, 3, 2, 1, 5])

ec = np.array([6, 7])
        c = setdiff1d(a, b)
        assert_array_equal(c, ec)

a = np.arange(21)
        b = np.arange(19)
        ec = np.array([19, 20])
        c = setdiff1d(a, b)
        assert_array_equal(c, ec)

assert_array_equal([], setdiff1d([], []))
        a = np.array((), np.uint32)
        assert_equal(setdiff1d(a, []).dtype, np.uint32)

def test_setdiff1d_char_array(self):
        a = np.array(['a', 'b', 'c'])
        b = np.array(['a', 'b', 's'])
        assert_array_equal(setdiff1d(a, b), np.array(['c']))

def test_manyways(self):
        a = np.array([5, 7, 1, 2, 8])
        b = np.array([9, 8, 2, 4, 3, 1, 5])

c1 = setxor1d(a, b)
        aux1 = intersect1d(a, b)
        aux2 = union1d(a, b)
        c2 = setdiff1d(aux2, aux1)
        assert_array_equal(c1, c2)

class TestUnique(TestCase):

def test_unique_1d(self):

def check_all(a, b, i1, i2, c, dt):
            base_msg = 'check {0} failed for type {1}'

msg = base_msg.format('values', dt)
            v = unique(a)
            assert_array_equal(v, b, msg)

msg = base_msg.format('return_index', dt)
            v, j = unique(a, 1, 0, 0)
            assert_array_equal(v, b, msg)
            assert_array_equal(j, i1, msg)

msg = base_msg.format('return_inverse', dt)
            v, j = unique(a, 0, 1, 0)
            assert_array_equal(v, b, msg)
            assert_array_equal(j, i2, msg)

msg = base_msg.format('return_counts', dt)
            v, j = unique(a, 0, 0, 1)
            assert_array_equal(v, b, msg)
            assert_array_equal(j, c, msg)

msg = base_msg.format('return_index and return_inverse', dt)
            v, j1, j2 = unique(a, 1, 1, 0)
            assert_array_equal(v, b, msg)
            assert_array_equal(j1, i1, msg)
            assert_array_equal(j2, i2, msg)

msg = base_msg.format('return_index and return_counts', dt)
            v, j1, j2 = unique(a, 1, 0, 1)
            assert_array_equal(v, b, msg)
            assert_array_equal(j1, i1, msg)
            assert_array_equal(j2, c, msg)

msg = base_msg.format('return_inverse and return_counts', dt)
            v, j1, j2 = unique(a, 0, 1, 1)
            assert_array_equal(v, b, msg)
            assert_array_equal(j1, i2, msg)
            assert_array_equal(j2, c, msg)

msg = base_msg.format(('return_index, return_inverse '
                                   'and return_counts'), dt)
            v, j1, j2, j3 = unique(a, 1, 1, 1)
            assert_array_equal(v, b, msg)
            assert_array_equal(j1, i1, msg)
            assert_array_equal(j2, i2, msg)
            assert_array_equal(j3, c, msg)

a = [5, 7, 1, 2, 1, 5, 7]*10
        b = [1, 2, 5, 7]
        i1 = [2, 3, 0, 1]
        i2 = [2, 3, 0, 1, 0, 2, 3]*10
        c = np.multiply([2, 1, 2, 2], 10)

# test for numeric arrays
        types = []
        types.extend(np.typecodes['AllInteger'])
        types.extend(np.typecodes['AllFloat'])
        types.append('datetime64[D]')
        types.append('timedelta64[D]')
        for dt in types:
            aa = np.array(a, dt)
            bb = np.array(b, dt)
            check_all(aa, bb, i1, i2, c, dt)

# test for object arrays
        dt = 'O'
        aa = np.empty(len(a), dt)
        aa[:] = a
        bb = np.empty(len(b), dt)
        bb[:] = b
        check_all(aa, bb, i1, i2, c, dt)

# test for structured arrays
        dt = [('', 'i'), ('', 'i')]
        aa = np.array(list(zip(a, a)), dt)
        bb = np.array(list(zip(b, b)), dt)
        check_all(aa, bb, i1, i2, c, dt)

# test for ticket #2799
        aa = [1. + 0.j, 1 - 1.j, 1]
        assert_array_equal(np.unique(aa), [1. - 1.j, 1. + 0.j])

# test for ticket #4785
        a = [(1, 2), (1, 2), (2, 3)]
        unq = [1, 2, 3]
        inv = [0, 1, 0, 1, 1, 2]
        a1 = unique(a)
        assert_array_equal(a1, unq)
        a2, a2_inv = unique(a, return_inverse=True)
        assert_array_equal(a2, unq)
        assert_array_equal(a2_inv, inv)

# test for chararrays with return_inverse (gh-5099)
        a = np.chararray(5)
        a[...] = ''
        a2, a2_inv = np.unique(a, return_inverse=True)
        assert_array_equal(a2_inv, np.zeros(5))

def test_unique_axis_errors(self):
        assert_raises(TypeError, self._run_axis_tests, object)
        assert_raises(TypeError, self._run_axis_tests,
                      [('a', int), ('b', object)])

assert_raises(ValueError, unique, np.arange(10), axis=2)
        assert_raises(ValueError, unique, np.arange(10), axis=-2)

def test_unique_axis_list(self):
        msg = "Unique failed on list of lists"
        inp = [[0, 1, 0], [0, 1, 0]]
        inp_arr = np.asarray(inp)
        assert_array_equal(unique(inp, axis=0), unique(inp_arr, axis=0), msg)
        assert_array_equal(unique(inp, axis=1), unique(inp_arr, axis=1), msg)

def test_unique_axis(self):
        types = []
        types.extend(np.typecodes['AllInteger'])
        types.extend(np.typecodes['AllFloat'])
        types.append('datetime64[D]')
        types.append('timedelta64[D]')
        types.append([('a', int), ('b', int)])
        types.append([('a', int), ('b', float)])

for dtype in types:
            self._run_axis_tests(dtype)

msg = 'Non-bitwise-equal booleans test failed'
        data = np.arange(10, dtype=np.uint8).reshape(-1, 2).view(bool)
        result = np.array([[False, True], [True, True]], dtype=bool)
        assert_array_equal(unique(data, axis=0), result, msg)

msg = 'Negative zero equality test failed'
        data = np.array([[-0.0, 0.0], [0.0, -0.0], [-0.0, 0.0], [0.0, -0.0]])
        result = np.array([[-0.0, 0.0]])
        assert_array_equal(unique(data, axis=0), result, msg)

def test_unique_masked(self):
        # issue 8664
        x = np.array([64, 0, 1, 2, 3, 63, 63, 0, 0, 0, 1, 2, 0, 63, 0], dtype='uint8')
        y = np.ma.masked_equal(x, 0)

v = np.unique(y)
        v2, i, c = np.unique(y, return_index=True, return_counts=True)

msg = 'Unique returned different results when asked for index'
        assert_array_equal(v.data, v2.data, msg)
        assert_array_equal(v.mask, v2.mask, msg)

def _run_axis_tests(self, dtype):
        data = np.array([[0, 1, 0, 0],
                         [1, 0, 0, 0],
                         [0, 1, 0, 0],
                         [1, 0, 0, 0]]).astype(dtype)

msg = 'Unique with 1d array and axis=0 failed'
        result = np.array([0, 1])
        assert_array_equal(unique(data), result.astype(dtype), msg)

msg = 'Unique with 2d array and axis=0 failed'
        result = np.array([[0, 1, 0, 0], [1, 0, 0, 0]])
        assert_array_equal(unique(data, axis=0), result.astype(dtype), msg)

msg = 'Unique with 2d array and axis=1 failed'
        result = np.array([[0, 0, 1], [0, 1, 0], [0, 0, 1], [0, 1, 0]])
        assert_array_equal(unique(data, axis=1), result.astype(dtype), msg)

msg = 'Unique with 3d array and axis=2 failed'
        data3d = np.dstack([data] * 3)
        result = data3d[..., :1]
        assert_array_equal(unique(data3d, axis=2), result, msg)

uniq, idx, inv, cnt = unique(data, axis=0, return_index=True,
                                     return_inverse=True, return_counts=True)
        msg = "Unique's return_index=True failed with axis=0"
        assert_array_equal(data[idx], uniq, msg)
        msg = "Unique's return_inverse=True failed with axis=0"
        assert_array_equal(uniq[inv], data)
        msg = "Unique's return_counts=True failed with axis=0"
        assert_array_equal(cnt, np.array([2, 2]), msg)

uniq, idx, inv, cnt = unique(data, axis=1, return_index=True,
                                     return_inverse=True, return_counts=True)
        msg = "Unique's return_index=True failed with axis=1"
        assert_array_equal(data[:, idx], uniq)
        msg = "Unique's return_inverse=True failed with axis=1"
        assert_array_equal(uniq[:, inv], data)
        msg = "Unique's return_counts=True failed with axis=1"
        assert_array_equal(cnt, np.array([2, 1, 1]), msg)

if __name__ == "__main__":
    run_module_suite()