add test for global moran
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@ -52,7 +52,7 @@ class MoranTest(unittest.TestCase):
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data = [ { 'id': d['id'], 'attr1': d['value'], 'neighbors': d['neighbors'] } for d in self.neighbors_data]
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plpy._define_result('select', data)
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random_seeds.set_random_seeds(1234)
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result = cc.moran_local('table', 'value', 99, 'the_geom', 'cartodb_id', 'knn', 5)
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result = cc.moran_local('subquery', 'value', 99, 'the_geom', 'cartodb_id', 'knn', 5)
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result = [(row[0], row[1]) for row in result]
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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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@ -70,3 +70,14 @@ class MoranTest(unittest.TestCase):
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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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def test_moran(self):
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"""Test Moran's I global"""
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data = [{ 'id': d['id'], 'attr1': d['value'], 'neighbors': d['neighbors'] } for d in self.neighbors_data]
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plpy._define_result('select', data)
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random_seeds.set_random_seeds(1235)
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result = cc.moran('table', 'value', 99, 'the_geom', 'cartodb_id', 'knn', 5)
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print 'result == None?', result == None
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result_moran = result[0][0]
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expected_moran = np.array([row[0] for row in self.moran_data]).mean()
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self.assertAlmostEqual(expected_moran, result_moran, delta=10e-2)
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