Removed area_types

openquake/risklib/asset.py

@@ -103,16 +103,10 @@ class CostCalculator(object):
 
     The same "formula" applies to retrofitting cost.
     """
-    def __init__(self, cost_types, area_types, units, tagi={'taxonomy': 0}):
-        if set(cost_types) != set(area_types):
-            raise ValueError('cost_types has keys %s, area_types has keys %s'
-                             % (sorted(cost_types), sorted(area_types)))
+    def __init__(self, cost_types, units, tagi={'taxonomy': 0}):
         for ct in cost_types.values():
             assert ct in ('aggregated', 'per_asset', 'per_area'), ct
-        for at in area_types.values():
-            assert at in ('aggregated', 'per_asset'), at
         self.cost_types = cost_types
-        self.area_types = area_types
         self.units = units
         self.tagi = tagi
 
@@ -142,7 +136,7 @@ def __call__(self, loss_type, assetcol):
         if cost_type == "per_asset":
             return cost * number
         if cost_type == "per_area":
-            area_type = self.area_types[loss_type]
+            area_type = self.cost_types['area']
             if area_type == "aggregated":
                 return cost * area
             elif area_type == "per_asset":
@@ -657,11 +651,10 @@ def _get_exposure(fname, stop=None):
     cost_types.sort(key=operator.itemgetter(0))
     cost_types = numpy.array(cost_types, cost_type_dt)
     cc = CostCalculator(
-        {}, {}, {}, {name: i for i, name in enumerate(tagnames)})
+        {}, {}, {name: i for i, name in enumerate(tagnames)})
     for ct in cost_types:
         name = ct['name']  # structural, nonstructural, ...
         cc.cost_types[name] = ct['type']  # aggregated, per_asset, per_area
-        cc.area_types[name] = get_area_type(cost_types)
         cc.units[name] = ct['unit']
     exp = Exposure(occupancy_periods, [], cc, TagCollection(tagnames), pairs)
     assets_text = xml.assets.text.strip()
@@ -883,12 +876,9 @@ class Exposure(object):
     def __toh5__(self):
         cc = self.cost_calculator
         loss_types = sorted(cc.cost_types)
-        dt = numpy.dtype([('cost_type', hdf5.vstr),
-                          ('area_type', hdf5.vstr),
-                          ('unit', hdf5.vstr)])
+        dt = numpy.dtype([('cost_type', hdf5.vstr), ('unit', hdf5.vstr)])
         array = numpy.zeros(len(loss_types), dt)
         array['cost_type'] = [cc.cost_types[lt] for lt in loss_types]
-        array['area_type'] = [cc.area_types[lt] for lt in loss_types]
         array['unit'] = [cc.units[lt] for lt in loss_types]
         attrs = dict(
             loss_types=hdf5.array_of_vstr(loss_types),
@@ -900,7 +890,6 @@ def __fromh5__(self, array, attrs):
         vars(self).update(attrs)
         cc = self.cost_calculator = object.__new__(CostCalculator)
         cc.cost_types = dict(zip(self.loss_types, decode(array['cost_type'])))
-        cc.area_types = dict(zip(self.loss_types, decode(array['area_type'])))
         cc.units = dict(zip(self.loss_types, decode(array['unit'])))
 
     @staticmethod