add building_sqft_per_job to developer

so res units and non-res units can be computed no matter which is being developerd (e.g. to account for mixed use buildings properly

urbansim/developer/developer.py

@@ -94,7 +94,7 @@ def compute_units_to_build(num_agents, num_units, target_vacancy):
 
     def pick(self, form, target_units, parcel_size, ave_unit_size,
              current_units, max_parcel_size=200000, min_unit_size=400,
-             drop_after_build=True, residential=True):
+             drop_after_build=True, residential=True, bldg_sqft_per_job=400.0):
         """
         Choose the buildings from the list that are feasible to build in
         order to match the specified demand.
@@ -114,9 +114,11 @@ def pick(self, form, target_units, parcel_size, ave_unit_size,
             The size of the parcels.  This was passed to feasibility as well,
             but should be passed here as well.  Index should be parcel_ids.
         ave_unit_size : series
-            The average unit size around each parcel - this is indexed
-            by parcel, but is usually a disaggregated version of a zonal or
-            accessibility aggregation.
+            The average residential unit size around each parcel - this is
+            indexed by parcel, but is usually a disaggregated version of a
+            zonal or accessibility aggregation.
+        bldg_sqft_per_job : float (default 400.0)
+            The average square feet per job for this building form.
         min_unit_size : float
             Values less than this number in ave_unit_size will be set to this
             number.  Deals with cases where units are currently not built.
@@ -152,11 +154,12 @@ def pick(self, form, target_units, parcel_size, ave_unit_size,
         df['current_units'] = current_units
         df = df[df.parcel_size < max_parcel_size]
 
+        df['residential_units'] = np.round(df.residential_sqft / df.ave_unit_size)
+        df['job_spaces'] = np.round(df.non_residential_sqft / bldg_sqft_per_job)
+
         if residential:
-            df['residential_units'] = np.round(df.residential_sqft / df.ave_unit_size)
             df['net_units'] = df.residential_units - df.current_units
         else:
-            df['job_spaces'] = np.round(df.non_residential_sqft / df.ave_unit_size)
             df['net_units'] = df.job_spaces - df.current_units
         df = df[df.net_units > 0]