Absolute bounds

docs/software.rst

@@ -238,4 +238,4 @@ Release Notes
   * v0.4.1 - package updates
   * v0.4.2 - validation script in Python
   * v0.4.3 - allow non-binary incidence 
-  * v0.5 - support for multiprocessing
+  * v0.5 - support for multiprocessing

example_survey_weighting/configs/settings.yaml

@@ -18,7 +18,8 @@ USE_SIMUL_INTEGERIZER: True
 USE_CVXPY: False
 max_expansion_factor: 4 # Default is 30
 min_expansion_factor: 0.5
-
+absolute_upper_bounds: 20000 
+absolute_lower_bounds: 1
 
 # Geographic Settings
 # ------------------------------------------------------------------

populationsim/balancer.py

@@ -242,6 +242,7 @@ def np_balancer(
 def do_balancing(control_spec,
                  total_hh_control_col,
                  max_expansion_factor, min_expansion_factor,
+                 absolute_upper_bound, absolute_lower_bound,
                  incidence_df, control_totals, initial_weights):
 
     # incidence table should only have control columns
@@ -262,14 +263,21 @@ def do_balancing(control_spec,
 
     if min_expansion_factor:
 
-        # number_of_households in this seed geograpy as specified in seed_controlss
+        # number_of_households in this seed geograpy as specified in seed_controls
         number_of_households = control_totals[total_hh_control_index]
 
         total_weights = initial_weights.sum()
         lb_ratio = min_expansion_factor * float(number_of_households) / float(total_weights)
 
         lb_weights = initial_weights * lb_ratio
-        lb_weights = lb_weights.clip(lower=0)
+
+        if absolute_lower_bound:
+            lb_weights = lb_weights.clip(lower=absolute_lower_bound)
+        else:
+            lb_weights = lb_weights.clip(lower=0)
+
+    elif absolute_lower_bound:
+        lb_weights = initial_weights.clip(lower=absolute_lower_bound)
 
     else:
         lb_weights = None
@@ -283,7 +291,14 @@ def do_balancing(control_spec,
         ub_ratio = max_expansion_factor * float(number_of_households) / float(total_weights)
 
         ub_weights = initial_weights * ub_ratio
-        ub_weights = ub_weights.round().clip(lower=1).astype(int)
+
+        if absolute_upper_bound:
+            ub_weights = ub_weights.round().clip(upper=absolute_upper_bound, lower=1).astype(int)
+        else:
+            ub_weights = ub_weights.round().clip(lower=1).astype(int)
+
+    elif absolute_upper_bound:
+        ub_weights = ub_weights.round().clip(upper=absolute_upper_bound, lower=1).astype(int)
 
     else:
         ub_weights = None

populationsim/steps/final_seed_balancing.py

@@ -68,6 +68,8 @@ def final_seed_balancing(settings, crosswalk, control_spec, incidence_table):
 
     max_expansion_factor = settings.get('max_expansion_factor', None)
     min_expansion_factor = settings.get('min_expansion_factor', None)
+    absolute_upper_bound = settings.get('absolute_upper_bound', None)
+    absolute_lower_bound = settings.get('absolute_lower_bound', None)
 
     relaxation_factors = pd.DataFrame(index=seed_controls_df.columns.tolist())
 
@@ -86,6 +88,8 @@ def final_seed_balancing(settings, crosswalk, control_spec, incidence_table):
             total_hh_control_col=total_hh_control_col,
             max_expansion_factor=max_expansion_factor,
             min_expansion_factor=min_expansion_factor,
+            absolute_lower_bound=absolute_lower_bound,
+            absolute_upper_bound=absolute_upper_bound,
             incidence_df=seed_incidence_df,
             control_totals=seed_controls_df.loc[seed_id],
             initial_weights=seed_incidence_df['sample_weight'])

populationsim/steps/initial_seed_balancing.py

@@ -65,6 +65,8 @@ def initial_seed_balancing(settings, crosswalk, control_spec, incidence_table):
 
     max_expansion_factor = settings.get('max_expansion_factor', None)
     min_expansion_factor = settings.get('min_expansion_factor', None)
+    absolute_upper_bound = settings.get('absolute_upper_bound', None)
+    absolute_lower_bound = settings.get('absolute_lower_bound', None)
 
     # run balancer for each seed geography
     weight_list = []
@@ -82,6 +84,8 @@ def initial_seed_balancing(settings, crosswalk, control_spec, incidence_table):
             total_hh_control_col=total_hh_control_col,
             max_expansion_factor=max_expansion_factor,
             min_expansion_factor=min_expansion_factor,
+            absolute_upper_bound=absolute_upper_bound,
+            absolute_lower_bound=absolute_lower_bound,
             incidence_df=seed_incidence_df,
             control_totals=seed_controls_df.loc[seed_id],
             initial_weights=seed_incidence_df['sample_weight'])

populationsim/steps/repop_balancing.py

@@ -60,6 +60,8 @@ def repop_balancing(settings, crosswalk, control_spec, incidence_table):
 
     max_expansion_factor = settings.get('max_expansion_factor', None)
     min_expansion_factor = settings.get('min_expansion_factor', None)
+    absolute_upper_bound = settings.get('absolute_upper_bound', None)
+    absolute_lower_bound = settings.get('absolute_lower_bound', None)
 
     # run balancer for each low geography
     low_weight_list = []
@@ -101,6 +103,8 @@ def repop_balancing(settings, crosswalk, control_spec, incidence_table):
                 total_hh_control_col=total_hh_control_col,
                 max_expansion_factor=max_expansion_factor,
                 min_expansion_factor=min_expansion_factor,
+                absolute_upper_bound=absolute_upper_bound,
+                absolute_lower_bound=absolute_lower_bound,
                 incidence_df=seed_incidence_df,
                 control_totals=low_controls_df.loc[low_id],
                 initial_weights=initial_weights)