"""Test functions for 1D array set operations. """ from __future__ import division, absolute_import, print_function from numpy.testing import * import numpy as np from numpy.lib.arraysetops import * import warnings class TestSetOps(TestCase): def test_unique( self ): def check_all(a, b, i1, i2, dt): msg = "check values failed for type '%s'" % dt v = unique(a) assert_array_equal(v, b, msg) msg = "check indexes failed for type '%s'" % dt v, j = unique(a, 1, 0) assert_array_equal(v, b, msg) assert_array_equal(j, i1, msg) msg = "check reverse indexes failed for type '%s'" % dt v, j = unique(a, 0, 1) assert_array_equal(v, b, msg) assert_array_equal(j, i2, msg) msg = "check with all indexes failed for type '%s'" % dt v, j1, j2 = unique(a, 1, 1) assert_array_equal(v, b, msg) assert_array_equal(j1, i1, msg) assert_array_equal(j2, i2, 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 # 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, 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, 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, dt) 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)) 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([],[])) 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 ) if __name__ == "__main__": run_module_suite()