Merge pull request #81 from GeoDaCenter/update_normalization

added normalize type
GeoDaCenter · Jun 9, 2019 · dee2f0d · dee2f0d
2 parents e72e3b3 + 029b0c0
commit dee2f0d
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Showing 5 changed files with 22 additions and 40 deletions.
diff --git a/spatial_access/Models.py b/spatial_access/Models.py
@@ -542,14 +542,14 @@ def _log_category_weight_dict(self, category_weight_dict):
         self.logger.info("Using weights: {}".format(presented_weight_dict))
 
     def calculate(self, upper_threshold, category_weight_dict=None,
-                  normalize=False, normalize_type='z_score'):
+                  normalize=False, normalize_type='minmax'):
         """
         Args:
             category_weight_dict: category_weight_dict: dictionary of {category : [numeric weights]} or None
             upper_threshold: time in seconds.
             normalize: boolean. If true, results will be normalized
                 from 0 to 100.
-            normalize_type: 'z_score'.
+            normalize_type: 'z_score', 'minmax'
         Returns: DataFrame.
         Raises:
             UnexpectedNormalizeColumnsException
@@ -630,7 +630,7 @@ def _normalize(self, column, normalize_type):
         Normalize results.
         Args:
             column: which column to normalize.
-            normalize_type: 'z-score'
+            normalize_type: 'z-score', 'minmax'
 
         Raises:
             UnexpectedEmptyColumnException
@@ -642,6 +642,12 @@ def _normalize(self, column, normalize_type):
                                               - self.model_results[column].mean()) / self.model_results[column].std()
             except ZeroDivisionError:
                 raise UnexpectedEmptyColumnException(column)
+        elif normalize_type == 'minmax':
+            try:
+                normalize_factor = self.model_results[column].max() - self.model_results[column].min()
+            except ZeroDivisionError:
+                raise RuntimeError("column max == column min ({})".format(self.model_results[column].max()))
+            self.model_results[column] = (self.model_results[column] - self.model_results[column].min()) / normalize_factor
         else:
             raise UnexpectedNormalizeTypeException(normalize_type)
 
diff --git a/spatial_access/__init__.py b/spatial_access/__init__.py
@@ -1,4 +1,4 @@
-__version__ = '0.1.18'
+__version__ = '1.0.0'
 __author__ = 'Logan Noel (lmnoel)'
 __url__ = 'https://github.com/GeoDaCenter/spatial_access'
 __license__ = 'GPL'
diff --git a/spatial_access/src/CMakeLists.txt b/spatial_access/src/CMakeLists.txt
diff --git a/spatial_access/src/Matrix.cpp b/spatial_access/src/Matrix.cpp
diff --git a/tests/test_Models.py b/tests/test_Models.py
@@ -400,7 +400,8 @@ def test_16(self):
                                 'D': [4, 3, 1],
                                 'C': [1]}
         coverage_model.transit_matrix = self.mock_transit_matrix_values(coverage_model.transit_matrix)
-        coverage_model.calculate(category_weight_dict=category_weight_dict, upper_threshold=700, normalize=True)
+        coverage_model.calculate(category_weight_dict=category_weight_dict, upper_threshold=700, normalize=True,
+                                 normalize_type='z_score')
 
         assert almost_equal(coverage_model.model_results['all_categories_score'].max(), 1.336)
         assert almost_equal(coverage_model.model_results['all_categories_score'].min(), -1.336)
@@ -441,11 +442,20 @@ def test_18(self):
         category_weight_dict = {'A': [5, 4, 3, 2, 1],
                                 'D': [4, 3, 1]}
         coverage_model.transit_matrix = self.mock_transit_matrix_values(coverage_model.transit_matrix)
-        coverage_model.calculate(category_weight_dict=category_weight_dict, upper_threshold=200, normalize=['A'])
+        coverage_model.calculate(category_weight_dict=category_weight_dict, upper_threshold=200, normalize=['A'],
+                                 normalize_type='z_score')
 
         assert almost_equal(coverage_model.model_results['A_score'].max(), 2.041)
         assert almost_equal(coverage_model.model_results['A_score'].min(), -0.408)
 
+        coverage_model.calculate(category_weight_dict=category_weight_dict, upper_threshold=200, normalize=True,
+                                 normalize_type='minmax')
+        assert almost_equal(coverage_model.model_results['A_score'].max(), 1.0)
+        assert almost_equal(coverage_model.model_results['A_score'].min(), 0.0)
+        assert almost_equal(coverage_model.model_results['D_score'].max(), 1.0)
+        assert almost_equal(coverage_model.model_results['D_score'].min(), 0.0)
+
+
     def test_19(self):
         """
         Test the DestFloatingCatchmentAreaModel aggregation.