Enable Mac ARM support

.github/workflows/conda_lock.yml

@@ -0,0 +1,24 @@
+name: conda-lock
+
+on:
+  pull_request:
+    types: [opened, synchronize]
+    branches: [master]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - name: Install conda-lock with Micromamba
+        uses: mamba-org/setup-micromamba@v1
+        with:
+          environment-name: ci
+          create-args: conda-lock
+          init-shell: bash
+
+      - name: Run conda-lock
+        run: conda-lock --mamba -f environment.yml -p osx-64 -p linux-64 -p win-64 --lockfile ${{ runner.temp }}/conda-lock.yml
+        shell: bash -el {0}

MANIFEST.in

@@ -21,3 +21,5 @@ include cea/workflows/*.yml
 include cea/dev/conda.bat
 
 graft cea/resources/radiation/bin
+
+graft cea/lib

bin/test_substation_calc_hex_cooling.py

@@ -64,7 +64,7 @@ def calc_HEX_cooling_orig(Q, UA, thi, tho, tci, ch):
     else:
         tco = 0
         cc = 0
-    return np.float(tco), np.float(cc)
+    return float(tco), float(cc)
 
 
 if __name__ == '__main__':

bin/test_substation_calc_hex_heating.py

@@ -58,7 +58,7 @@ def calc_HEX_heating_orig(Q, UA, thi, tco, tci, cc):
     else:
         tho = 0
         ch = 0
-    return np.float(tho), np.float(ch)
+    return float(tho), float(ch)
 
 
 if __name__ == '__main__':

cea/datamanagement/streets_helper.py

@@ -6,6 +6,7 @@
 
 import osmnx
 import osmnx.utils_graph
+import pandas as pd
 from geopandas import GeoDataFrame as Gdf
 
 import cea.config
@@ -27,8 +28,10 @@ def calc_bounding_box(locator):
     # connect both files and avoid repetition
     data_zone, data_dis = get_zone_and_surr_in_projected_crs(locator)
     data_dis = data_dis.loc[~data_dis["Name"].isin(data_zone["Name"])]
-    data = data_zone.append(data_dis, ignore_index=True, sort=True)
-    data = data.to_crs(get_geographic_coordinate_system())
+    data = pd.concat([
+        data_zone.to_crs(get_geographic_coordinate_system()),
+        data_dis.to_crs(get_geographic_coordinate_system())
+    ], ignore_index=True, sort=True)
     result = data.total_bounds  # in float
     return result
 

cea/datamanagement/terrain_helper.py

@@ -41,12 +41,13 @@ def request_elevation(lon, lat):
 
 
 def calc_bounding_box_projected_coordinates(locator):
-
     # connect both files and avoid repetition
     data_zone, data_dis = get_zone_and_surr_in_projected_crs(locator)
     data_dis = data_dis.loc[~data_dis["Name"].isin(data_zone["Name"])]
-    data = data_zone.append(data_dis, ignore_index = True, sort=True)
-    data = data.to_crs(get_geographic_coordinate_system())
+    data = pd.concat([
+        data_zone.to_crs(get_geographic_coordinate_system()),
+        data_dis.to_crs(get_geographic_coordinate_system())
+    ], ignore_index=True, sort=True)
     lon = data.geometry[0].centroid.coords.xy[0][0]
     lat = data.geometry[0].centroid.coords.xy[1][0]
     crs = get_projected_coordinate_system(float(lat), float(lon))

cea/datamanagement/zone_helper.py

@@ -500,16 +500,19 @@ def polygon_to_zone(buildings_floors, buildings_floors_below_ground, buildings_h
     lon = poly.geometry[0].centroid.coords.xy[0][0]
     lat = poly.geometry[0].centroid.coords.xy[1][0]
     # get all footprints in the district tagged as 'building' or 'building:part' in OSM
-    shapefile = osmnx.geometries.geometries_from_polygon(polygon=poly['geometry'].values[0], tags={"building": True})
+    shapefile = osmnx.features.features_from_polygon(polygon=poly['geometry'].values[0], tags={"building": True})
     if include_building_parts:
-        # get all footprints in the district tagged as 'building' or 'building:part' in OSM
-        building_parts = osmnx.geometries.geometries_from_polygon(polygon=poly['geometry'].values[0],
+        try:
+            # get all footprints in the district tagged as 'building' or 'building:part' in OSM
+            building_parts = osmnx.features.features_from_polygon(polygon=poly['geometry'].values[0],
                                                                   tags={"building": ["part"]})
-        shapefile = pd.concat([shapefile, building_parts], ignore_index=True)
-        # using building:part tags requires fixing overlapping polygons
-        if not fix_overlapping:
-            print('Building parts included, fixing overlapping geometries activated.')
-            fix_overlapping = True
+            shapefile = pd.concat([shapefile, building_parts], ignore_index=True)
+            # using building:part tags requires fixing overlapping polygons
+            if not fix_overlapping:
+                print('Building parts included, fixing overlapping geometries activated.')
+                fix_overlapping = True
+        except osmnx._errors.InsufficientResponseError:
+            pass
 
     # clean geometries
     shapefile = clean_geometries(shapefile)

cea/glossary.py

@@ -44,7 +44,7 @@ def read_glossary_df(plugins):
                     cd = schemas[lm]["schema"]["columns"][col]  # cd: column definition
                     rows.append(glossary_row(script, file_path, col, lm, cd, worksheet=""))
 
-        glossary_df = glossary_df.append(rows, ignore_index=True)
+        glossary_df = pd.concat([glossary_df, pd.DataFrame(rows)], ignore_index=True)
         glossary_df['key'] = glossary_df['FILE_NAME'] + '!!!' + glossary_df['VARIABLE']
         glossary_df = glossary_df.set_index(['key'])
         glossary_df = glossary_df.sort_values(by=['LOCATOR_METHOD', 'FILE_NAME', 'VARIABLE'])

cea/interfaces/dashboard/dashboard.py

@@ -9,24 +9,15 @@
 import cea.plots
 import cea.plots.cache
 
-socketio = None
-
 
 def main(config):
     config.restricted_to = None  # allow access to the whole config file
     plot_cache = cea.plots.cache.MemoryPlotCache(config.project)
     app = Flask(__name__, static_folder='base/static', )
     CORS(app)
     app.config.from_mapping({'SECRET_KEY': 'secret'})
-
-    global socketio
     socketio = SocketIO(app, cors_allowed_origins="*")
 
-    def shutdown(signum, frame):
-        print("Shutting Down...")
-        socketio.stop()
-    signal.signal(signal.SIGINT, shutdown)
-
     if config.server.browser:
         from cea.interfaces.dashboard.frontend import blueprint as frontend
         app.register_blueprint(frontend)
@@ -44,16 +35,17 @@ def shutdown(signum, frame):
     app.plot_cache = plot_cache
     app.socketio = socketio
 
-    print("start socketio.run")
-
+    print("start CEA dashboard server")
+    
     if config.server.browser:
         url = f"http://{config.server.host}:{config.server.port}"
         print(f"Open {url} in your browser to access the GUI")
         webbrowser.open(url)
 
     print("Press Ctrl+C to stop server")
-    socketio.run(app, host=config.server.host, port=config.server.port)
-    print("done socketio.run")
+    socketio.run(app, host=config.server.host, port=config.server.port, allow_unsafe_werkzeug=True)
+
+    print("\nserver exited")
 
 
 if __name__ == '__main__':

cea/interfaces/dashboard/server/streams.py

@@ -5,7 +5,7 @@
 """
 
 from flask import request, current_app
-from flask_restx import Namespace, Resource, fields
+from flask_restx import Namespace, Resource
 
 __author__ = "Daren Thomas"
 __copyright__ = "Copyright 2019, Architecture and Building Systems - ETH Zurich"

cea/lib/__init__.py

@@ -0,0 +1,33 @@
+"""
+This only works for wntr v0.2.3
+
+Apple Silicon lib builds from:
+WNTR (https://github.com/USEPA/WNTR/tree/0.2.3)
+set `use_swig` and `build` to True in setup.py
+make sure swig is installed
+python setup.py build_ext --inplace
+copy _evaluator and _network from build
+
+EPANET (https://github.com/OpenWaterAnalytics/EPANET/tree/v2.0.12)
+replace all `malloc.h` with `stdlib.h`
+gcc -dynamiclib *.c -o libepanet.dylib
+copy libepanet.dylib to Darwin folder
+"""
+
+import platform
+import sys
+import os
+
+if sys.platform == "darwin" and platform.processor() == "arm":
+    # Add required shared objects to path before importing wntr
+    sys.path.append(os.path.dirname(__file__))
+
+    # Make sure correct version of wntr is installed
+    import wntr
+    if wntr.__version__ != '0.2.3':
+        raise ImportError(f"Require wntr version 0.2.3, found {wntr.__version__}")
+
+    print("Applying fix for Apple Silicon")
+    # Change where wntr looks for libepanet
+    import wntr.epanet.toolkit
+    wntr.epanet.toolkit.epanet_toolkit = "cea.lib"

cea/optimization/preprocessing/decentralized_buildings_cooling.py

@@ -233,12 +233,14 @@ def disconnected_cooling_for_building(building_name, supply_systems, lca, locato
     # capacity of cooling technologies
     operation_results[2][0] = Qc_nom_AHU_ARU_SCU_W
     operation_results[2][4] = Qc_nom_AHU_ARU_SCU_W  # 4: ACH_SC_FP
-    q_total_load = q_chw_single_ACH_Wh[None, :] + q_sc_gen_FP_Wh[None,
-                                                  :] + q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh[None, :]
-    system_COP_list = np.divide(q_total_load, (
-            el_total_Wh[None, :] + q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh[None, :])).flatten()
-    system_COP = np.nansum(q_total_load * system_COP_list) / np.nansum(
-        q_total_load)  # weighted average of the system efficiency
+    q_total_load = (q_chw_single_ACH_Wh[None, :] +
+                    q_sc_gen_FP_Wh[None, :] +
+                    q_load_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh[None, :])
+    system_COP_list = np.divide(q_total_load,
+                                (el_total_Wh[None, :] + q_gas_Boiler_FP_to_single_ACH_to_AHU_ARU_SCU_Wh[None, :])
+                                ).flatten()
+    system_COP = (np.nansum(q_total_load * system_COP_list) /
+                  np.nansum(q_total_load))  # weighted average of the system efficiency
     operation_results[2][9] += system_COP
 
     # 3: SC_ET + single-effect ACH (AHU + ARU + SCU) + CT + Boiler + SC_ET
@@ -286,8 +288,8 @@ def disconnected_cooling_for_building(building_name, supply_systems, lca, locato
     operation_results[3][5] = Qc_nom_AHU_ARU_SCU_W
     q_total_load = (q_burner_load_Wh[None, :] + q_chw_single_ACH_Wh[None, :] + q_sc_gen_ET_Wh[None, :])
     system_COP_list = np.divide(q_total_load, (el_total_Wh[None, :] + q_gas_for_burner_Wh[None, :])).flatten()
-    system_COP = np.nansum(q_total_load * system_COP_list) / np.nansum(
-        q_total_load)  # weighted average of the system efficiency
+    system_COP = (np.nansum(q_total_load * system_COP_list) /
+                  np.nansum(q_total_load))  # weighted average of the system efficiency
     operation_results[3][9] += system_COP
 
     # these two configurations are only activated when SCU is in use
@@ -673,9 +675,9 @@ def get_SC_data(building_name, locator, panel_type):
     SC_data = pd.read_csv(locator.SC_results(building_name, panel_type),
                           usecols=["T_SC_sup_C", "T_SC_re_C", "mcp_SC_kWperC", "Q_SC_gen_kWh", "Area_SC_m2",
                                    "Eaux_SC_kWh"])
-    q_sc_gen_Wh = SC_data['Q_SC_gen_kWh'] * 1000
+    q_sc_gen_Wh = (SC_data['Q_SC_gen_kWh'] * 1000).values
     q_sc_gen_Wh = np.where(q_sc_gen_Wh < 0.0, 0.0, q_sc_gen_Wh)
-    el_aux_SC_Wh = SC_data['Eaux_SC_kWh'] * 1000
+    el_aux_SC_Wh = (SC_data['Eaux_SC_kWh'] * 1000).values
     if panel_type == "FP":
         T_hw_in_C = [x if x > T_GENERATOR_FROM_FP_C else T_GENERATOR_FROM_FP_C for x in SC_data['T_SC_re_C']]
     elif panel_type == "ET":

cea/optimization/slave/cooling_resource_activation.py

@@ -334,15 +334,15 @@ def activate_CCandACH_trigen(Q_cooling_unmet_W,
             if Qh_CCGT_req_W <= Q_output_CC_max_W:  # Normal operation possible within part load regime
                 Q_CHP_gen_W = float(Qh_CCGT_req_W)
                 NG_Trigen_req_W = Q_used_prim_CC_fn_W(Q_CHP_gen_W)
-                E_Trigen_NG_gen_W = np.float(eta_elec_interpol(NG_Trigen_req_W)) * NG_Trigen_req_W
+                E_Trigen_NG_gen_W = float(eta_elec_interpol(NG_Trigen_req_W)) * NG_Trigen_req_W
 
             else:  # Only part of the demand can be delivered as 100% load achieved
                 # This case should never occur, since it means that another heat source would be required to run
                 # the absorption chiller at the required capacity.
                 print("WARNING: Gas turbine can not output enough heat to power the absorption chiller!")
                 Q_CHP_gen_W = Q_output_CC_max_W
                 NG_Trigen_req_W = Q_used_prim_CC_fn_W(Q_CHP_gen_W)
-                E_Trigen_NG_gen_W = np.float(eta_elec_interpol(NG_Trigen_req_W)) * NG_Trigen_req_W
+                E_Trigen_NG_gen_W = float(eta_elec_interpol(NG_Trigen_req_W)) * NG_Trigen_req_W
 
         # if the operation of the combined cycle is not possible due to its limited capacity, the absorption chiller
         # (i.e. the cooling technology of the tri-generation plant) can not be powered either

cea/optimization/slave/heating_resource_activation.py

@@ -62,11 +62,11 @@ def heating_source_activator(Q_therm_req_W,
             if Q_heat_unmet_W <= Q_output_CC_max_W:  # Normal operation Possible within partload regime
                 Q_CHP_gen_W = Q_heat_unmet_W
                 NG_CHP_req_W = Q_used_prim_CC_fn_W(Q_CHP_gen_W)
-                E_CHP_gen_W = np.float(eta_elec_interpol(NG_CHP_req_W)) * NG_CHP_req_W
+                E_CHP_gen_W = float(eta_elec_interpol(NG_CHP_req_W)) * NG_CHP_req_W
             else:  # Only part of the demand can be delivered as 100% load achieved
                 Q_CHP_gen_W = Q_output_CC_max_W
                 NG_CHP_req_W = Q_used_prim_CC_fn_W(Q_CHP_gen_W)
-                E_CHP_gen_W = np.float(eta_elec_interpol(NG_CHP_req_W)) * NG_CHP_req_W
+                E_CHP_gen_W = float(eta_elec_interpol(NG_CHP_req_W)) * NG_CHP_req_W
         else:
             NG_CHP_req_W = 0.0
             E_CHP_gen_W = 0.0

cea/optimization_new/building.py

@@ -31,6 +31,7 @@ def __init__(self, identifier, demands_file_path):
         self.identifier = identifier
         self.demands_file_path = demands_file_path
         self.stand_alone_supply_system = SupplySystem()
+        self.crs = None
         self._demand_flow = EnergyFlow()
         self._footprint = None
         self._location = None
@@ -98,6 +99,7 @@ def load_building_location(self, domain_shp_file):
         reference system).
         """
         if self.location is None:
+            self.crs = domain_shp_file.crs
             self.footprint = domain_shp_file[domain_shp_file.Name == self.identifier].geometry.iloc[0]
             self.location = self.footprint.representative_point()
         else:
@@ -190,7 +192,7 @@ def distribute_building_potentials(domain_energy_potentials, domain_buildings):
 
         # group the potentials by energy carriers and sum them up if necessary
         for potential in building_scale_energy_potentials:
-            for building, profile in potential.main_building_profiles.iteritems():
+            for building, profile in potential.main_building_profiles.items():
                 if potential.main_potential.energy_carrier.code in building_energy_potentials[building].keys():
                     building_energy_potentials[building][potential.main_potential.energy_carrier.code] += \
                         EnergyFlow('source', 'secondary',
@@ -199,7 +201,7 @@ def distribute_building_potentials(domain_energy_potentials, domain_buildings):
                     building_energy_potentials[building][potential.main_potential.energy_carrier.code] = \
                         EnergyFlow('source', 'secondary',
                                     potential.main_potential.energy_carrier.code, profile)
-            for building, profile in potential.auxiliary_building_profiles.iteritems():
+            for building, profile in potential.auxiliary_building_profiles.items():
                 if potential.auxiliary_potential.energy_carrier.code in building_energy_potentials[building].keys():
                     building_energy_potentials[building][potential.auxiliary_potential.energy_carrier.code] += \
                         EnergyFlow('source', 'secondary',

cea/optimization_new/network.py

@@ -17,6 +17,8 @@
 __email__ = "mathias.niffeler@sec.ethz.ch"
 __status__ = "Production"
 
+import cea.lib
+
 import os.path
 import tempfile
 
@@ -245,7 +247,8 @@ def _load_pot_network(domain):
         # join building locations (shapely.POINTS) and the corresponding identifiers in a DataFrame
         building_identifiers = [building.identifier for building in domain.buildings]
         building_locations = [building.location for building in domain.buildings]
-        buildings_df = pd.DataFrame(list(zip(building_locations, building_identifiers)), columns=['geometry', 'Name'])
+        buildings_df = Gdf(list(zip(building_locations, building_identifiers)), columns=['geometry', 'Name'],
+                           crs=domain.buildings[0].crs, geometry="geometry")
 
         # create a potential network grid with orthogonal connections between buildings and their closest street
         network_grid_shp = calc_connectivity_network(domain.locator.get_street_network(),
@@ -450,7 +453,7 @@ def _set_plant_next_to_building(self, anchor_building):
         plant_terminal = plant_terminal.rename({plant_terminal.index[0]: plant_terminal_node})
         plant_terminal['Type'][0] = "PLANT"
 
-        self.network_nodes = self.network_nodes.append(plant_terminal)
+        self.network_nodes = pd.concat([self.network_nodes, plant_terminal])
 
         # create new edge
         point1 = (plant_terminal.geometry[0].x, plant_terminal.geometry[0].y)
@@ -461,7 +464,7 @@ def _set_plant_next_to_building(self, anchor_building):
                                 'end node': plant_terminal_node},
                                index=['PIPE' + str(len(self.network_edges.index))],
                                crs=Network._coordinate_reference_system)
-        self.network_edges = self.network_edges.append(plant_to_network)
+        self.network_edges = pd.concat([self.network_edges, plant_to_network])
 
     def _run_water_network_model(self):
         """

cea/technologies/boiler.py

@@ -162,7 +162,7 @@ def calc_Cop_boiler(q_load_Wh, Q_nom_W, T_return_to_boiler_K):
         phi = float(q_load_Wh) / float(Q_nom_W)
         if phi >=1.0: # avoid rounding error
             phi = 0.98
-        T_return_C = np.float(T_return_to_boiler_K - 273.15)
+        T_return_C = float(T_return_to_boiler_K - 273.15)
         eff_score = eff_of_phi(phi) / eff_of_phi(1)
         boiler_eff = (eff_score * eff_of_T_return([T_return_C]))[0] / 100.0
     else:

cea/technologies/chiller_absorption.py

@@ -6,9 +6,9 @@
 import pandas as pd
 import numpy as np
 from math import log, ceil
-import sympy
+# import sympy
 from cea.constants import HEAT_CAPACITY_OF_WATER_JPERKGK
-from cea.analysis.costs.equations import calc_capex_annualized, calc_opex_annualized
+from cea.analysis.costs.equations import calc_capex_annualized
 
 __author__ = "Shanshan Hsieh"
 __copyright__ = "Copyright 2015, Architecture and Building Systems - ETH Zurich"