switched signature to put more common options in the front
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@@ -14,7 +14,7 @@ import crankshaft.pysal_utils as pu
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# High level interface ---------------------------------------
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def moran(subquery, attr_name,
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permutations, geom_col, id_col, w_type, num_ngbrs):
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w_type, num_ngbrs, permutations, geom_col, id_col):
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"""
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Moran's I (global)
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Implementation building neighbors with a PostGIS database and Moran's I
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@@ -56,7 +56,7 @@ def moran(subquery, attr_name,
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return zip([moran_global.I], [moran_global.EI])
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def moran_local(subquery, attr,
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permutations, geom_col, id_col, w_type, num_ngbrs):
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w_type, num_ngbrs, permutations, geom_col, id_col):
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"""
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Moran's I implementation for PL/Python
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Andy Eschbacher
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@@ -96,7 +96,7 @@ def moran_local(subquery, attr,
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return zip(lisa.Is, quads, lisa.p_sim, weight.id_order, lisa.y)
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def moran_rate(subquery, numerator, denominator,
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permutations, geom_col, id_col, w_type, num_ngbrs):
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w_type, num_ngbrs, permutations, geom_col, id_col):
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"""
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Moran's I Rate (global)
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Andy Eschbacher
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@@ -137,7 +137,7 @@ def moran_rate(subquery, numerator, denominator,
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return zip([lisa_rate.I], [lisa_rate.EI])
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def moran_local_rate(subquery, numerator, denominator,
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permutations, geom_col, id_col, w_type, num_ngbrs):
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w_type, num_ngbrs, permutations, geom_col, id_col):
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"""
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Moran's I Local Rate
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Andy Eschbacher
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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('subquery', 'value', 99, 'the_geom', 'cartodb_id', 'knn', 5)
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result = cc.moran_local('subquery', 'value', 'knn', 5, 99, 'the_geom', 'cartodb_id')
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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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@@ -64,7 +64,7 @@ class MoranTest(unittest.TestCase):
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data = [ { 'id': d['id'], 'attr1': d['value'], 'attr2': 1, '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_rate('subquery', 'numerator', 'denominator', 99, 'the_geom', 'cartodb_id', 'knn', 5)
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result = cc.moran_local_rate('subquery', 'numerator', 'denominator', 'knn', 5, 99, 'the_geom', 'cartodb_id')
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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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expected = self.moran_data
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@@ -76,7 +76,7 @@ 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(1235)
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result = cc.moran('table', 'value', 99, 'the_geom', 'cartodb_id', 'knn', 5)
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result = cc.moran('table', 'value', 'knn', 5, 99, 'the_geom', 'cartodb_id')
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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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