update printing and aggregation

nismod · Mar 5, 2019 · 273204f · 273204f
1 parent 8ef1c97
commit 273204f
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Showing 11 changed files with 53 additions and 108 deletions.
diff --git a/energy_demand/basic/demand_supply_interaction.py b/energy_demand/basic/demand_supply_interaction.py
@@ -5,7 +5,7 @@
 import numpy as np
 import pandas as pd
 
-from energy_demand.basic import date_prop, testing_functions, lookup_tables, basic_functions 
+from energy_demand.basic import date_prop, testing_functions, lookup_tables
 
 def constrained_results(
         results_constrained,
@@ -85,7 +85,7 @@ def constrained_results(
     # Substract constrained fuel from nonconstrained (total) fuel
     non_heating_ed = results_unconstrained - sum(results_constrained.values())
 
-    #assert not testing_functions.test_if_minus_value_in_array(results_unconstrained)
+    assert not testing_functions.test_if_minus_value_in_array(non_heating_ed)
 
     # ---------------------------------
     # Add non_heating for all fueltypes

diff --git a/energy_demand/basic/testing_functions.py b/energy_demand/basic/testing_functions.py
@@ -5,7 +5,7 @@
 from energy_demand.basic import basic_functions
 from energy_demand.basic import lookup_tables
 
-def test_if_minus_value_in_array(arraytotest, tolerance_min_max=0.00000000001):
+def test_if_minus_value_in_array(arraytotest):#, tolerance_min_max=0.00000000001):
     """Test if array has negative value according to a tolerance
     criteria
 
@@ -25,7 +25,9 @@ def test_if_minus_value_in_array(arraytotest, tolerance_min_max=0.00000000001):
 
     if len(only_neg_elements) > 0:
         for element in only_neg_elements:
-            if (element > tolerance_min_max) or (element < tolerance_min_max):
+            #if (element > tolerance_min_max) or (element < tolerance_min_max):
+            if element < 0:
+                print("---")
                 print("Sum of all negative:     " + str(np.sum(only_neg_elements)))
                 print("Average negative value:  " + str(np.sum(only_neg_elements) / len(only_neg_elements)))
                 print("Smalles value:           " + str(np.min(only_neg_elements)))

diff --git a/energy_demand/enduse_func.py b/energy_demand/enduse_func.py
@@ -123,8 +123,7 @@ def __init__(
             self.fuel_yh = 0
             self.enduse_techs = []
         else:
-            #print("------INFO  {} {} {}  {}".format(self.enduse, sector, region, curr_yr))
-            #print("strarr")
+            #logging.debug("------INFO  {} {} {}  {}".format(self.enduse, sector, region, curr_yr))
             # Get technologies of enduse
             self.enduse_techs = get_enduse_techs(fuel_tech_p_by)
 
@@ -198,7 +197,7 @@ def __init__(
                 strategy_vars['generic_fuel_switch'],
                 self.fuel_y)
             self.fuel_y = _fuel_new_y
-            #print("eeeemd")
+
             # ----------------------------------
             # Hourly Disaggregation
             # ----------------------------------
@@ -225,8 +224,6 @@ def __init__(
                         make_all_flat=make_all_flat)
             else:
                 #If technologies are defined for an enduse
-                #print("A")
-                # Get enduse specific configurations
                 mode_constrained = get_enduse_configuration(
                     criterias['mode_constrained'],
                     enduse,
@@ -235,7 +232,6 @@ def __init__(
                 # ------------------------------------
                 # Calculate regional energy service
                 # ------------------------------------
-                #print("A " + str(np.sum(self.fuel_y)))
                 s_tot_y_cy, s_tech_y_by = fuel_to_service(
                     enduse,
                     sector,
@@ -302,7 +298,6 @@ def __init__(
                 if self.flat_profile_crit:
                     pass
                 else:
-                    #print("B")
                     fuel_yh = calc_fuel_tech_yh(
                         enduse,
                         sector,
@@ -312,7 +307,7 @@ def __init__(
                         fueltypes_nr,
                         fueltypes,
                         mode_constrained)
-                    #print("C")
+
                     # --------------------------------------
                     # Peak shifting
                     # --------------------------------------
@@ -322,7 +317,6 @@ def __init__(
                         # If no demand management improvenent, no peak shifting
                         if strategy_vars['dm_improvement'][enduse][curr_yr] == 0:
                             self.techs_fuel_yh = fuel_yh
-                            #print("D1")
                         else:
                             self.techs_fuel_yh = load_shifting_multiple_tech(
                                 enduse,
@@ -331,15 +325,14 @@ def __init__(
                                 assumptions.technologies,
                                 fuel_yh,
                                 param_lf_improved_cy=strategy_vars['dm_improvement'][enduse][curr_yr])
-                            #print("D2")
                     else:
                         self.fuel_yh = load_shifting(
                             enduse,
                             fuel_yh,
                             mode_constrained=False,
                             param_lf_improved_cy=strategy_vars['dm_improvement'][enduse][curr_yr],
                             make_all_flat=make_all_flat)
-                        #print("D3")
+
                         if testing_functions.test_if_minus_value_in_array(self.fuel_yh):
                             raise Exception("Minus fuel value detected: {}  {} {}".format(enduse, sector, np.sum(self.fuel_yh)))
 

diff --git a/energy_demand/main.py b/energy_demand/main.py
@@ -23,7 +23,6 @@
 from energy_demand.validation import lad_validation
 from energy_demand.scripts import s_scenario_param, init_scripts, s_disaggregation
 from energy_demand.plotting import fig_enduse_yh
-from energy_demand.basic import lookup_tables, date_prop, basic_functions, conversions
 from energy_demand import enduse_func
 from energy_demand.technologies import tech_related
 

diff --git a/energy_demand/model.py b/energy_demand/model.py
@@ -23,7 +23,7 @@
   testable and refactored going forward, so some profiling would help direct
   attention to where further work is most appropriate
 """
-import copy
+import logging
 from collections import defaultdict
 import numpy as np
 
@@ -43,7 +43,6 @@ def tqdm(iterator, *_, **__):
 from energy_demand.profiles import load_factors
 from energy_demand.profiles import generic_shapes
 from energy_demand.basic import demand_supply_interaction
-from energy_demand.basic import testing_functions
 from energy_demand.geography import weather_station_location
 
 class EnergyDemandModel(object):
@@ -78,7 +77,7 @@ def __init__(
         # ------------------------
         # Create Dwelling Stock
         # ------------------------
-        logging.debug("... generating cy dwelling stocks", flush=True)
+        logging.debug("... generating dwelling stocks", flush=True)
         lookups = lookup_tables.basic_lookups()
 
         if criterias['virtual_building_stock_criteria']:
@@ -103,15 +102,13 @@ def __init__(
         # -------------------------------------------
         # Simulate regions
         # -------------------------------------------
-        logging.debug("... generating by dwelling stocks", flush=True)
         #_all_closest_weather_stations = []
         for reg_array_nr, region in enumerate(tqdm(regions)):
 
+            print("... Simulate: region %s, simulation year: %s, percent: (%s)",
+                region, assumptions.curr_yr, round((100/assumptions.reg_nrs)*reg_array_nr, 2), flush=True)
             #logging.info("... Simulate: region %s, simulation year: %s, percent: (%s)",
             #    region, assumptions.curr_yr, round((100/assumptions.reg_nrs)*reg_array_nr, 2))
-            logging.debug("... Simulate: region %s, simulation year: %s, percent: (%s)",
-                region, assumptions.curr_yr, round((100/assumptions.reg_nrs)*reg_array_nr, 2), flush=True)
-
             all_submodels = simulate_region(
                 region,
                 data,
@@ -126,7 +123,6 @@ def __init__(
             # Aggregate results specifically over regions
             # ---------------------------------------------
             aggr_results = aggregate_single_region(
-                assumptions,
                 assumptions.reg_nrs,
                 assumptions.lookup_enduses,
                 aggr_results,
@@ -183,20 +179,6 @@ def aggregate_across_all_regs(
         Technologies per enduse
     """
     fueltypes = lookup_tables.basic_lookups()['fueltypes']
-    '''# -----------------------------
-    # Aggregate residential demand [fueltype, region]
-    # -----------------------------
-    
-    submodel_nr = 0
-    array_init = np.zeros((fueltypes_nr, reg_nrs))
-
-    for enduse_array_nr in assumptions.lookup_sector_enduses[submodel_nr]:
-        for enduse in aggr_results['ed_enduse_fueltype_regs_yh'][enduse_array_nr]:
-
-            # Sum across all hours in a year
-            array_init += np.sum(aggr_results['ed_enduse_fueltype_regs_yh'][enduse_array_nr], axis=2)
-
-    aggr_results['ed_residential_tot_reg_y'] = array_init'''
 
     # ----------------------------------------------------
     # Aggregate: [fueltype, region, fuel_yh_8760]
@@ -396,7 +378,7 @@ def simulate_region(
     for submodel_name in submodel_names:
         for sector in data['sectors'][submodel_name]:
             for enduse in data['enduses'][submodel_name]:
-                #print("A - 0")
+
                 # ------------------------------------------------------
                 # Configure and select correct Enduse specific inputs
                 # ------------------------------------------------------
@@ -724,7 +706,6 @@ def aggregate_result_unconstrained(
     return constrained_array
 
 def aggregate_single_region(
-        assumptions,
         reg_nrs,
         lookup_enduses,
         aggr_results,
@@ -782,17 +763,23 @@ def aggregate_single_region(
         techs_fueltypes_yh = get_fuels_yh(enduse_object, 'techs_fuel_yh')
 
         if isinstance(techs_fueltypes_yh, dict):
-
             enduse_array_nr = lookup_enduses[enduse_object.enduse]
             submodel_nr = submodel_to_idx[enduse_object.submodel_name]
 
             for tech, fuel_tech in techs_fueltypes_yh.items():
                 tech_fueltype = technologies[tech].fueltype_int
+
+                # -------------------------------------------            
+                # Add all technologies to main aggreator (heating & non heating)
+                # -------------------------------------------
+                aggr_results['ed_enduse_fueltype_regs_yh'][enduse_array_nr][tech_fueltype][reg_array_nr] += fuel_tech.reshape(8760)
 
                 # -----------------------------------------------------------------
                 # Aggregate fuel of constrained technologies for heating
                 # -----------------------------------------------------------------
                 if mode_constrained:
+
+                    # Only add heating technologies to constrained results
                     if enduse_object.enduse in enduse_space_heating:
 
                         # Aggregate Submodel (sector) specific enduse for fueltype
@@ -803,8 +790,14 @@ def aggregate_single_region(
                                 aggr_results['results_constrained'][tech] = np.zeros((len(submodel_to_idx), reg_nrs, fueltypes_nr, 8760), dtype="float")
                             aggr_results['results_constrained'][tech][submodel_nr][reg_array_nr][tech_fueltype] += fuel_tech.reshape(8760)
 
-                # Sum non heating techs
-                aggr_results['ed_enduse_fueltype_regs_yh'][enduse_array_nr][tech_fueltype][reg_array_nr] += fuel_tech.reshape(8760)
+                    #else: # Add all other non-heating technologies to main aggreator
+                    #    aggr_results['ed_enduse_fueltype_regs_yh'][enduse_array_nr][tech_fueltype][reg_array_nr] += fuel_tech.reshape(8760)
+
+                #non_heating_ed = results_unconstrained - sum(results_constrained.values())
+                #assert not testing_functions.test_if_minus_value_in_array(non_heating_ed)
+                #print("AAA {} {}".format(
+                #    np.sum(aggr_results['ed_enduse_fueltype_regs_yh']),
+                #    np.sum(aggr_results['results_constrained'])))
         else:
             fueltype_yh_365_24 = get_fuels_yh(enduse_object, 'fuel_yh')
             fueltype_yh_8760 = fueltype_yh_365_24.reshape(fueltypes_nr, 8760)
@@ -875,14 +868,16 @@ def aggregate_from_full_results(
         time_resolution,
         per_region,
         per_sector,
-        per_enduse,
-        reg_array_nr=False
+        per_enduse
     ):
-    """Function to read from full simulation data
-    specific demands
+    """Function to read from full simulation data specific demands
 
     Argument
     --------
+    lookup_enduse : dict
+        Enduse lookup
+    aggregated_container : dict
+        Container to aggregate
     full_sim_data : dict
          Modelling results per submodel, enduse, region, fueltype, 8760h
     time_resolution : str

diff --git a/energy_demand/plotting/_scrap.py b/energy_demand/plotting/_scrap.py
diff --git a/energy_demand/read_write/load_parameter_values.py b/energy_demand/read_write/load_parameter_values.py
diff --git a/energy_demand/read_write/narrative_related.py b/energy_demand/read_write/narrative_related.py
@@ -1,5 +1,6 @@
 """Functions handling the narratives
 """
+import logging
 from collections import defaultdict
 
 from energy_demand.basic import lookup_tables
@@ -195,8 +196,8 @@ def default_narrative(
         'sig_midpoint': sig_midpoint,
         'sig_steepness': sig_steepness,
         'regional_specific': regional_specific,
-        'fueltype_replace': 0,
-        'fueltype_new': 0
+        'fueltype_replace': fueltype_replace,
+        'fueltype_new': fueltype_new
         }]
 
 def autocomplete(parameter_narratives, simulation_base_yr, sub_param_crit):
@@ -205,7 +206,7 @@ def autocomplete(parameter_narratives, simulation_base_yr, sub_param_crit):
     autocomplet_param_narr = defaultdict(dict)
 
     for sub_param_name, narratives_sector in parameter_narratives.items():
-        print("   ... " + str(sub_param_name))
+        logging.debug("   ... " + str(sub_param_name))
         for sector, narratives in narratives_sector.items():
             autocomplet_param_narr[sub_param_name][sector] = []
 
@@ -339,7 +340,6 @@ def read_user_defined_param(
                             _ = default_streategy_var[enduse]
                             defined_in_model = True
                         except KeyError:
-                            #print("... not defined in model")
                             defined_in_model = False
 
                         # All entries of this year df_enduse and this fueltype
@@ -451,7 +451,7 @@ def read_user_defined_param(
         # ------------
         # Autocomplete
         # ------------
-        print("... autocomplete")
+        logging.debug("... autocomplete")
         parameter_narratives = autocomplete(
             parameter_narratives,
             simulation_base_yr,