From e924abbaccb14b10c5b43e910595448b96e210bd Mon Sep 17 00:00:00 2001 From: Andy Eschbacher Date: Wed, 21 Sep 2016 13:09:42 -0400 Subject: [PATCH] formatted for pep8 --- .../crankshaft/crankshaft/clustering/moran.py | 23 +++++---- .../crankshaft/pysal_utils/pysal_utils.py | 37 +++++++++----- .../crankshaft/test/test_clustering_moran.py | 48 +++++++++++++------ 3 files changed, 73 insertions(+), 35 deletions(-) diff --git a/src/py/crankshaft/crankshaft/clustering/moran.py b/src/py/crankshaft/crankshaft/clustering/moran.py index 7a97233..4e7086e 100644 --- a/src/py/crankshaft/crankshaft/clustering/moran.py +++ b/src/py/crankshaft/crankshaft/clustering/moran.py @@ -14,6 +14,7 @@ import crankshaft.pysal_utils as pu # High level interface --------------------------------------- + def moran(subquery, attr_name, w_type, num_ngbrs, permutations, geom_col, id_col): """ @@ -39,18 +40,19 @@ def moran(subquery, attr_name, plpy.error('Analysis failed: %s' % e) return pu.empty_zipped_array(2) - ## collect attributes + # collect attributes attr_vals = pu.get_attributes(result) - ## calculate weights + # calculate weights weight = pu.get_weight(result, w_type, num_ngbrs) - ## calculate moran global + # calculate moran global moran_global = ps.esda.moran.Moran(attr_vals, weight, permutations=permutations) return zip([moran_global.I], [moran_global.EI]) + def moran_local(subquery, attr, w_type, num_ngbrs, permutations, geom_col, id_col): """ @@ -90,6 +92,7 @@ def moran_local(subquery, attr, return zip(lisa.Is, quads, lisa.p_sim, weight.id_order, lisa.y) + def moran_rate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col): """ @@ -114,18 +117,19 @@ def moran_rate(subquery, numerator, denominator, plpy.error('Analysis failed: %s' % e) return pu.empty_zipped_array(2) - ## collect attributes + # collect attributes numer = pu.get_attributes(result, 1) denom = pu.get_attributes(result, 2) weight = pu.get_weight(result, w_type, num_ngbrs) - ## calculate moran global rate + # calculate moran global rate lisa_rate = ps.esda.moran.Moran_Rate(numer, denom, weight, permutations=permutations) return zip([lisa_rate.I], [lisa_rate.EI]) + def moran_local_rate(subquery, numerator, denominator, w_type, num_ngbrs, permutations, geom_col, id_col): """ @@ -153,7 +157,7 @@ def moran_local_rate(subquery, numerator, denominator, plpy.error('Analysis failed: %s' % e) return pu.empty_zipped_array(5) - ## collect attributes + # collect attributes numer = pu.get_attributes(result, 1) denom = pu.get_attributes(result, 2) @@ -168,6 +172,7 @@ def moran_local_rate(subquery, numerator, denominator, return zip(lisa.Is, quads, lisa.p_sim, weight.id_order, lisa.y) + def moran_local_bv(subquery, attr1, attr2, permutations, geom_col, id_col, w_type, num_ngbrs): """ @@ -189,11 +194,11 @@ def moran_local_bv(subquery, attr1, attr2, if len(result) == 0: return pu.empty_zipped_array(4) except plpy.SPIError: - plpy.error("Error: areas of interest query failed, " \ + plpy.error("Error: areas of interest query failed, " "check input parameters") return pu.empty_zipped_array(4) - ## collect attributes + # collect attributes attr1_vals = pu.get_attributes(result, 1) attr2_vals = pu.get_attributes(result, 2) @@ -211,6 +216,7 @@ def moran_local_bv(subquery, attr1, attr2, # Low level functions ---------------------------------------- + def map_quads(coord): """ Map a quadrant number to Moran's I designation @@ -231,6 +237,7 @@ def map_quads(coord): else: return None + def quad_position(quads): """ Produce Moran's I classification based of n diff --git a/src/py/crankshaft/crankshaft/pysal_utils/pysal_utils.py b/src/py/crankshaft/crankshaft/pysal_utils/pysal_utils.py index 4622925..6dbcbd8 100644 --- a/src/py/crankshaft/crankshaft/pysal_utils/pysal_utils.py +++ b/src/py/crankshaft/crankshaft/pysal_utils/pysal_utils.py @@ -6,6 +6,7 @@ import numpy as np import pysal as ps + def construct_neighbor_query(w_type, query_vals): """Return query (a string) used for finding neighbors @param w_type text: type of neighbors to calculate ('knn' or 'queen') @@ -17,7 +18,8 @@ def construct_neighbor_query(w_type, query_vals): else: return queen(query_vals) -## Build weight object + +# Build weight object def get_weight(query_res, w_type='knn', num_ngbrs=5): """ Construct PySAL weight from return value of query @@ -39,6 +41,7 @@ def get_weight(query_res, w_type='knn', num_ngbrs=5): return built_weight + def query_attr_select(params): """ Create portion of SELECT statement for attributes inolved in query. @@ -50,21 +53,24 @@ def query_attr_select(params): template = "i.\"%(col)s\"::numeric As attr%(alias_num)s, " if 'time_cols' in params: - ## if markov analysis + # if markov analysis attrs = params['time_cols'] for idx, val in enumerate(attrs): attr_string += template % {"col": val, "alias_num": idx + 1} else: - ## if moran's analysis + # if moran's analysis attrs = [k for k in params - if k not in ('id_col', 'geom_col', 'subquery', 'num_ngbrs', 'subquery')] + if k not in ('id_col', 'geom_col', 'subquery', + 'num_ngbrs', 'subquery')] for idx, val in enumerate(sorted(attrs)): - attr_string += template % {"col": params[val], "alias_num": idx + 1} + attr_string += template % {"col": params[val], + "alias_num": idx + 1} return attr_string + def query_attr_where(params): """ Construct where conditions when building neighbors query @@ -74,7 +80,8 @@ def query_attr_where(params): 'numerator': 'data1', 'denominator': 'data2', '': ...} - Output: 'idx_replace."data1" IS NOT NULL AND idx_replace."data2" IS NOT NULL' + Output: 'idx_replace."data1" IS NOT NULL AND idx_replace."data2" + IS NOT NULL' Input: {'subquery': ..., 'time_cols': ['time1', 'time2', 'time3'], @@ -86,17 +93,18 @@ def query_attr_where(params): template = "idx_replace.\"%s\" IS NOT NULL" if 'time_cols' in params: - ## markov where clauses + # markov where clauses attrs = params['time_cols'] # add values to template for attr in attrs: attr_string.append(template % attr) else: - ## moran where clauses + # moran where clauses # get keys attrs = sorted([k for k in params - if k not in ('id_col', 'geom_col', 'subquery', 'num_ngbrs', 'subquery')]) + if k not in ('id_col', 'geom_col', 'subquery', + 'num_ngbrs', 'subquery')]) # add values to template for attr in attrs: attr_string.append(template % params[attr]) @@ -108,6 +116,7 @@ def query_attr_where(params): return out + def knn(params): """SQL query for k-nearest neighbors. @param vars: dict of values to fill template @@ -139,7 +148,8 @@ def knn(params): return query.format(**params) -## SQL query for finding queens neighbors (all contiguous polygons) + +# SQL query for finding queens neighbors (all contiguous polygons) def queen(params): """SQL query for queen neighbors. @param params dict: information to fill query @@ -167,14 +177,17 @@ def queen(params): return query.format(**params) -## to add more weight methods open a ticket or pull request +# to add more weight methods open a ticket or pull request + def get_attributes(query_res, attr_num=1): """ @param query_res: query results with attributes and neighbors @param attr_num: attribute number (1, 2, ...) """ - return np.array([x['attr' + str(attr_num)] for x in query_res], dtype=np.float) + return np.array([x['attr' + str(attr_num)] for x in query_res], + dtype=np.float) + def empty_zipped_array(num_nones): """ diff --git a/src/py/crankshaft/test/test_clustering_moran.py b/src/py/crankshaft/test/test_clustering_moran.py index 2b683cf..cb54902 100644 --- a/src/py/crankshaft/test/test_clustering_moran.py +++ b/src/py/crankshaft/test/test_clustering_moran.py @@ -14,6 +14,7 @@ import crankshaft.pysal_utils as pu from crankshaft import random_seeds import json + class MoranTest(unittest.TestCase): """Testing class for Moran's I functions""" @@ -26,12 +27,15 @@ class MoranTest(unittest.TestCase): "geom_col": "the_geom", "num_ngbrs": 321} self.params_markov = {"id_col": "cartodb_id", - "time_cols": ["_2013_dec", "_2014_jan", "_2014_feb"], + "time_cols": ["_2013_dec", "_2014_jan", + "_2014_feb"], "subquery": "SELECT * FROM a_list", "geom_col": "the_geom", "num_ngbrs": 321} - self.neighbors_data = json.loads(open(fixture_file('neighbors.json')).read()) - self.moran_data = json.loads(open(fixture_file('moran.json')).read()) + self.neighbors_data = json.loads( + open(fixture_file('neighbors.json')).read()) + self.moran_data = json.loads( + open(fixture_file('moran.json')).read()) def test_map_quads(self): """Test map_quads""" @@ -54,35 +58,49 @@ class MoranTest(unittest.TestCase): def test_moran_local(self): """Test Moran's I local""" - data = [ { 'id': d['id'], 'attr1': d['value'], 'neighbors': d['neighbors'] } for d in self.neighbors_data] + data = [{'id': d['id'], + 'attr1': d['value'], + 'neighbors': d['neighbors']} for d in self.neighbors_data] + plpy._define_result('select', data) random_seeds.set_random_seeds(1234) - result = cc.moran_local('subquery', 'value', 'knn', 5, 99, 'the_geom', 'cartodb_id') + result = cc.moran_local('subquery', 'value', + 'knn', 5, 99, 'the_geom', 'cartodb_id') result = [(row[0], row[1]) for row in result] - expected = self.moran_data - for ([res_val, res_quad], [exp_val, exp_quad]) in zip(result, expected): + zipped_values = zip(result, self.moran_data) + + for ([res_val, res_quad], [exp_val, exp_quad]) in zipped_values: self.assertAlmostEqual(res_val, exp_val) self.assertEqual(res_quad, exp_quad) def test_moran_local_rate(self): """Test Moran's I rate""" - data = [ { 'id': d['id'], 'attr1': d['value'], 'attr2': 1, 'neighbors': d['neighbors'] } for d in self.neighbors_data] + data = [{'id': d['id'], + 'attr1': d['value'], + 'attr2': 1, + 'neighbors': d['neighbors']} for d in self.neighbors_data] + plpy._define_result('select', data) random_seeds.set_random_seeds(1234) - result = cc.moran_local_rate('subquery', 'numerator', 'denominator', 'knn', 5, 99, 'the_geom', 'cartodb_id') - print 'result == None? ', result == None + result = cc.moran_local_rate('subquery', 'numerator', 'denominator', + 'knn', 5, 99, 'the_geom', 'cartodb_id') result = [(row[0], row[1]) for row in result] - expected = self.moran_data - for ([res_val, res_quad], [exp_val, exp_quad]) in zip(result, expected): + + zipped_values = zip(result, self.moran_data) + + for ([res_val, res_quad], [exp_val, exp_quad]) in zipped_values: self.assertAlmostEqual(res_val, exp_val) def test_moran(self): """Test Moran's I global""" - data = [{ 'id': d['id'], 'attr1': d['value'], 'neighbors': d['neighbors'] } for d in self.neighbors_data] + data = [{'id': d['id'], + 'attr1': d['value'], + 'neighbors': d['neighbors']} for d in self.neighbors_data] plpy._define_result('select', data) random_seeds.set_random_seeds(1235) - result = cc.moran('table', 'value', 'knn', 5, 99, 'the_geom', 'cartodb_id') - print 'result == None?', result == None + result = cc.moran('table', 'value', + 'knn', 5, 99, 'the_geom', 'cartodb_id') + result_moran = result[0][0] expected_moran = np.array([row[0] for row in self.moran_data]).mean() self.assertAlmostEqual(expected_moran, result_moran, delta=10e-2)