adds test for get_time_data
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@ -26,7 +26,7 @@ class SpaceTimeTests(unittest.TestCase):
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"geom_col": "the_geom",
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"num_ngbrs": 321}
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self.neighbors_data = json.loads(open(fixture_file('neighbors_markov.json')).read())
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# self.moran_data = json.loads(open(fixture_file('markov.json')).read())
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self.markov_data = json.loads(open(fixture_file('markov.json')).read())
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self.time_data = np.array([i * np.ones(10, dtype=float) for i in range(10)]).T
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@ -58,28 +58,211 @@ class SpaceTimeTests(unittest.TestCase):
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[ 0. , 0. , 0. , 0.02352941, 0.97647059]]]
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)
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def test_spatial_markov(self):
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"""Test Spatial Markov."""
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data = [ { 'id': d['id'],
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'attr1': d['y1929'],
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'attr2': d['y1930'],
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'attr3': d['y1931'],
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'neighbors': d['neighbors'] } for d in self.neighbors_data]
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# def test_spatial_markov(self):
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# """Test Spatial Markov."""
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# data = [ { 'id': d['id'],
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# 'attr1': d['y1995'],
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# 'attr2': d['y1996'],
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# 'attr3': d['y1997'],
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# 'attr4': d['y1998'],
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# 'attr5': d['y1999'],
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# 'attr6': d['y2000'],
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# 'attr7': d['y2001'],
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# 'attr8': d['y2002'],
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# 'attr9': d['y2003'],
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# 'attr10': d['y2004'],
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# 'attr11': d['y2005'],
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# 'attr12': d['y2006'],
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# 'attr13': d['y2007'],
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# 'attr14': d['y2008'],
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# 'attr15': d['y2009'],
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# 'neighbors': d['neighbors'] } for d in self.neighbors_data]
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# print(str(data[0]))
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# plpy._define_result('select', data)
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# random_seeds.set_random_seeds(1234)
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#
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# result = std.spatial_markov_trend('subquery', ['y1995', 'y1996', 'y1997', 'y1998', 'y1999', 'y2000', 'y2001', 'y2002', 'y2003', 'y2004', 'y2005', 'y2006', 'y2007', 'y2008', 'y2009'], 7, 'knn', 5, 99, 'the_geom', 'cartodb_id')
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#
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# print 'result == None? ', result == None
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# result = [(row[0], row[1], row[2], row[3], row[4]) for row in result]
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# print result[0]
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# expected = self.markov_data
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# for ([res_trend, res_up, res_down, res_vol, res_id],
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# [exp_trend, exp_up, exp_down, exp_vol, exp_id]
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# ) in zip(result, expected):
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# self.assertAlmostEqual(res_trend, exp_trend)
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plpy._define_result('select', data)
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random_seeds.set_random_seeds(1234)
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def test_get_time_data(self):
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"""Test get_time_data"""
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data = [ { 'attr1': d['y1995'],
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'attr2': d['y1996'],
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'attr3': d['y1997'],
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'attr4': d['y1998'],
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'attr5': d['y1999'],
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'attr6': d['y2000'],
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'attr7': d['y2001'],
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'attr8': d['y2002'],
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'attr9': d['y2003'],
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'attr10': d['y2004'],
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'attr11': d['y2005'],
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'attr12': d['y2006'],
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'attr13': d['y2007'],
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'attr14': d['y2008'],
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'attr15': d['y2009'] } for d in self.neighbors_data]
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result = std.spatial_markov_trend('subquery', ['y1929', 'y1930', 'y1931', 'y1932', 'y1933', 'y1934', 'y1935', 'y1936', 'y1937', 'y1938', 'y1939'], 1, 99, 'the_geom', 'cartodb_id', 'knn', 5)
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result = std.get_time_data(data, ['y1995', 'y1996', 'y1997', 'y1998', 'y1999', 'y2000', 'y2001', 'y2002', 'y2003', 'y2004', 'y2005', 'y2006', 'y2007', 'y2008', 'y2009'])
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print 'result == None? ', result == None
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result = [(row[0], row[1]) for row in result]
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print result[0]
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assertTrue(result[0] == None)
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# expected = self.moran_data
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# for ([res_val, res_quad], [exp_val, exp_quad]) in zip(result, expected):
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# self.assertAlmostEqual(res_val, exp_val)
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## expected was prepared from PySAL example:
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### f = ps.open(ps.examples.get_path("usjoin.csv"))
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### pci = np.array([f.by_col[str(y)] for y in range(1995, 2010)]).transpose()
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### rpci = pci / (pci.mean(axis = 0))
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expected = np.array([[ 0.87654416, 0.863147, 0.85637567, 0.84811668, 0.8446154, 0.83271652
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, 0.83786314, 0.85012593, 0.85509656, 0.86416612, 0.87119375, 0.86302631
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, 0.86148267, 0.86252252, 0.86746356],
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[ 0.9188951, 0.91757931, 0.92333258, 0.92517289, 0.92552388, 0.90746978
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, 0.89830489, 0.89431991, 0.88924794, 0.89815176, 0.91832091, 0.91706054
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, 0.90139505, 0.87897455, 0.86216858],
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[ 0.82591007, 0.82548596, 0.81989793, 0.81503235, 0.81731522, 0.78964559
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, 0.80584442, 0.8084998, 0.82258551, 0.82668196, 0.82373724, 0.81814804
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, 0.83675961, 0.83574199, 0.84647177],
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[ 1.09088176, 1.08537689, 1.08456418, 1.08415404, 1.09898841, 1.14506948
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, 1.12151133, 1.11160697, 1.10888621, 1.11399806, 1.12168029, 1.13164797
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, 1.12958508, 1.11371818, 1.09936775],
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[ 1.10731446, 1.11373944, 1.13283638, 1.14472559, 1.15910025, 1.16898201
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, 1.17212488, 1.14752303, 1.11843284, 1.11024964, 1.11943471, 1.11736468
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, 1.10863242, 1.09642516, 1.07762337],
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[ 1.42269757, 1.42118434, 1.44273502, 1.43577571, 1.44400684, 1.44184737
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, 1.44782832, 1.41978227, 1.39092208, 1.4059372, 1.40788646, 1.44052766
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, 1.45241216, 1.43306098, 1.4174431 ],
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[ 1.13073885, 1.13110513, 1.11074708, 1.13364636, 1.13088149, 1.10888138
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, 1.11856629, 1.13062931, 1.11944984, 1.12446239, 1.11671008, 1.10880034
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, 1.08401709, 1.06959206, 1.07875225],
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[ 1.04706124, 1.04516831, 1.04253372, 1.03239987, 1.02072545, 0.99854316
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, 0.9880258, 0.99669587, 0.99327676, 1.01400905, 1.03176742, 1.040511
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, 1.01749645, 0.9936394, 0.98279746],
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[ 0.98996986, 1.00143564, 0.99491, 1.00188408, 1.00455845, 0.99127006
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, 0.97925917, 0.9683482, 0.95335147, 0.93694787, 0.94308213, 0.92232874
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, 0.91284091, 0.89689833, 0.88928858],
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[ 0.87418391, 0.86416601, 0.84425695, 0.8404494, 0.83903044, 0.8578708
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, 0.86036185, 0.86107306, 0.8500772, 0.86981998, 0.86837929, 0.87204141
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, 0.86633032, 0.84946077, 0.83287146],
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[ 1.14196118, 1.14660262, 1.14892712, 1.14909594, 1.14436624, 1.14450183
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, 1.12349752, 1.12596664, 1.12213996, 1.1119989, 1.10257792, 1.10491258
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, 1.11059842, 1.10509795, 1.10020097],
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[ 0.97282463, 0.96700147, 0.96252588, 0.9653878, 0.96057687, 0.95831051
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, 0.94480909, 0.94804195, 0.95430286, 0.94103989, 0.92122519, 0.91010201
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, 0.89280392, 0.89298243, 0.89165385],
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[ 0.94325468, 0.96436902, 0.96455242, 0.95243009, 0.94117647, 0.9480927
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, 0.93539182, 0.95388718, 0.94597005, 0.96918424, 0.94781281, 0.93466815
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, 0.94281559, 0.96520315, 0.96715441],
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[ 0.97478408, 0.98169225, 0.98712809, 0.98474769, 0.98559897, 0.98687073
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, 0.99237486, 0.98209969, 0.9877653, 0.97399471, 0.96910087, 0.98416665
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, 0.98423613, 0.99823861, 0.99545704],
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[ 0.85570269, 0.85575915, 0.85986132, 0.85693406, 0.8538012, 0.86191535
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, 0.84981451, 0.85472102, 0.84564835, 0.83998883, 0.83478547, 0.82803648
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, 0.8198736, 0.82265395, 0.8399404 ],
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[ 0.87022047, 0.85996258, 0.85961813, 0.85689572, 0.83947136, 0.82785597
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, 0.86008789, 0.86776298, 0.86720209, 0.8676334, 0.89179317, 0.94202108
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, 0.9422231, 0.93902708, 0.94479184],
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[ 0.90134907, 0.90407738, 0.90403991, 0.90201769, 0.90399238, 0.90906632
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, 0.92693339, 0.93695966, 0.94242697, 0.94338265, 0.91981796, 0.91108804
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, 0.90543476, 0.91737138, 0.94793657],
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[ 1.1977611, 1.18222564, 1.18439158, 1.18267865, 1.19286723, 1.20172869
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, 1.21328691, 1.22624778, 1.22397075, 1.23857042, 1.24419893, 1.23929384
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, 1.23418676, 1.23626739, 1.26754398],
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[ 1.24919678, 1.25754773, 1.26991161, 1.28020651, 1.30625667, 1.34790023
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, 1.34399863, 1.32575181, 1.30795492, 1.30544841, 1.30303302, 1.32107766
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, 1.32936244, 1.33001241, 1.33288462],
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[ 1.06768004, 1.03799276, 1.03637303, 1.02768449, 1.03296093, 1.05059016
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, 1.03405057, 1.02747623, 1.03162734, 0.9961416, 0.97356208, 0.94241549
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, 0.92754547, 0.92549227, 0.92138102],
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[ 1.09475614, 1.11526796, 1.11654299, 1.13103948, 1.13143264, 1.13889622
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, 1.12442212, 1.13367018, 1.13982256, 1.14029944, 1.11979401, 1.10905389
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, 1.10577769, 1.11166825, 1.09985155],
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[ 0.76530058, 0.76612841, 0.76542451, 0.76722683, 0.76014284, 0.74480073
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, 0.76098396, 0.76156903, 0.76651952, 0.76533288, 0.78205934, 0.76842416
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, 0.77487118, 0.77768683, 0.78801192],
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[ 0.98391336, 0.98075816, 0.98295341, 0.97386015, 0.96913803, 0.97370819
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, 0.96419154, 0.97209861, 0.97441313, 0.96356162, 0.94745352, 0.93965462
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, 0.93069645, 0.94020973, 0.94358232],
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[ 0.83561828, 0.82298088, 0.81738502, 0.81748588, 0.80904801, 0.80071489
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, 0.83358256, 0.83451613, 0.85175032, 0.85954307, 0.86790024, 0.87170334
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, 0.87863799, 0.87497981, 0.87888675],
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[ 0.98845573, 1.02092428, 0.99665283, 0.99141823, 0.99386619, 0.98733195
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, 0.99644997, 0.99669587, 1.02559097, 1.01116651, 0.99988024, 0.97906749
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, 0.99323123, 1.00204939, 0.99602148],
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[ 1.14930913, 1.15241949, 1.14300962, 1.14265542, 1.13984683, 1.08312397
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, 1.05192626, 1.04230892, 1.05577278, 1.08569751, 1.12443486, 1.08891079
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, 1.08603695, 1.05997314, 1.02160943],
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[ 1.11368269, 1.1057147, 1.11893431, 1.13778669, 1.1432272, 1.18257029
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, 1.16226243, 1.16009196, 1.14467789, 1.14820235, 1.12386598, 1.12680236
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, 1.12357937, 1.1159258, 1.12570828],
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[ 1.30379431, 1.30752186, 1.31206366, 1.31532267, 1.30625667, 1.31210239
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, 1.29989156, 1.29203193, 1.27183516, 1.26830786, 1.2617743, 1.28656675
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, 1.29734097, 1.29390205, 1.29345446],
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[ 0.83953719, 0.82701448, 0.82006005, 0.81188876, 0.80294864, 0.78772975
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, 0.82848011, 0.8259679, 0.82435705, 0.83108634, 0.84373784, 0.83891093
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, 0.84349247, 0.85637272, 0.86539395],
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[ 1.23450087, 1.2426022, 1.23537935, 1.23581293, 1.24522626, 1.2256767
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, 1.21126648, 1.19377804, 1.18355337, 1.19674434, 1.21536573, 1.23653297
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, 1.27962009, 1.27968392, 1.25907738],
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[ 0.9769662, 0.97400719, 0.98035944, 0.97581531, 0.95543282, 0.96480308
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, 0.94686376, 0.93679073, 0.92540049, 0.92988835, 0.93442917, 0.92100464
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, 0.91475304, 0.90249622, 0.9021363 ],
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[ 0.84986886, 0.8986851, 0.84295997, 0.87280534, 0.85659368, 0.88937573
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, 0.894401, 0.90448993, 0.95495898, 0.92698333, 0.94745352, 0.92562488
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, 0.96635366, 1.02520312, 1.0394296 ],
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[ 1.01922808, 1.00258203, 1.00974428, 1.00303417, 0.99765073, 1.00759019
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, 0.99192968, 0.99747298, 0.99550759, 0.97583768, 0.9610168, 0.94779638
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, 0.93759089, 0.93353431, 0.94121705],
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[ 0.86367411, 0.85558932, 0.85544346, 0.85103025, 0.84336613, 0.83434854
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, 0.85813595, 0.84667961, 0.84374558, 0.85951183, 0.87194227, 0.89455097
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, 0.88283929, 0.90349491, 0.90600675],
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[ 1.00947534, 1.00411055, 1.00698819, 0.99513687, 0.99291086, 1.00581626
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, 0.98850522, 0.99291168, 0.98983209, 0.97511924, 0.96134615, 0.96382634
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, 0.95011401, 0.9434686, 0.94637765],
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[ 1.05712571, 1.05459419, 1.05753012, 1.04880786, 1.05103857, 1.04800023
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, 1.03024941, 1.04200483, 1.0402554, 1.03296979, 1.02191682, 1.02476275
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, 1.02347523, 1.02517684, 1.04359571],
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[ 1.07084189, 1.06669497, 1.07937623, 1.07387988, 1.0794043, 1.0531801
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, 1.07452771, 1.09383478, 1.1052447, 1.10322136, 1.09167939, 1.08772756
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, 1.08859544, 1.09177338, 1.1096083 ],
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[ 0.86719222, 0.86628896, 0.86675156, 0.86425632, 0.86511809, 0.86287327
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, 0.85169796, 0.85411285, 0.84886336, 0.84517414, 0.84843858, 0.84488343
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, 0.83374329, 0.82812044, 0.82878599],
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[ 0.88389211, 0.92288667, 0.90282398, 0.91229186, 0.92023286, 0.92652175
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, 0.94278865, 0.93682452, 0.98655146, 0.992237, 0.9798497, 0.93869677
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, 0.96947771, 1.00362626, 0.98102351],
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[ 0.97082064, 0.95320233, 0.94534081, 0.94215593, 0.93967, 0.93092109
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, 0.92662519, 0.93412152, 0.93501274, 0.92879506, 0.92110542, 0.91035556
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, 0.90430364, 0.89994694, 0.90073864],
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[ 0.95861858, 0.95774543, 0.98254811, 0.98919472, 0.98684824, 0.98882205
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, 0.97662234, 0.95601578, 0.94905385, 0.94934888, 0.97152609, 0.97163004
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, 0.9700702, 0.97158948, 0.95884908],
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[ 0.83980439, 0.84726737, 0.85747, 0.85467221, 0.8556751, 0.84818516
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, 0.85265681, 0.84502402, 0.82645665, 0.81743586, 0.83550406, 0.83338919
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, 0.83511679, 0.82136617, 0.80921874],
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[ 0.95118156, 0.9466212, 0.94688098, 0.9508583, 0.9512441, 0.95440787
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, 0.96364363, 0.96804412, 0.97136214, 0.97583768, 0.95571724, 0.96895368
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, 0.97001634, 0.97082733, 0.98782366],
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[ 1.08910044, 1.08248968, 1.08492895, 1.08656923, 1.09454249, 1.10558188
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, 1.1214086, 1.12292577, 1.13021031, 1.13342735, 1.14686068, 1.14502975
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, 1.14474747, 1.14084037, 1.16142926],
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[ 1.06336033, 1.07365823, 1.08691496, 1.09764846, 1.11669863, 1.11856702
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, 1.09764283, 1.08815849, 1.08044313, 1.09278827, 1.07003204, 1.08398066
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, 1.09831768, 1.09298232, 1.09176125],
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[ 0.79772065, 0.78829196, 0.78581151, 0.77615922, 0.77035744, 0.77751194
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, 0.79902974, 0.81437881, 0.80788828, 0.79603865, 0.78966436, 0.79949807
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, 0.80172182, 0.82168155, 0.85587911],
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[ 1.0052447, 1.00007696, 1.00475899, 1.00613942, 1.00639561, 1.00162979
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, 0.99860739, 1.00814981, 1.00574316, 0.99030032, 0.97682565, 0.97292596
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, 0.96519561, 0.96173403, 0.95890284],
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[ 0.95808419, 0.9382568, 0.9654441, 0.95561201, 0.96987289, 0.96608031
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, 0.99727185, 1.00781194, 1.03484236, 1.05333619, 1.0983263, 1.1704974
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, 1.17025154, 1.18730553, 1.14242645]])
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self.assertTrue(np.allclose(result, expected))
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def test_rebin_data(self):
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"""Test rebin_data"""
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||||
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