Update syntehtic network with flh matrices, fixed networkx export fun…

…ction
jylambert · Dec 2, 2024 · 269402b · 269402b
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commit 269402b
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Showing 13 changed files with 8 additions and 37 deletions.
diff --git a/examples/one-producer/run_sts.py b/examples/one-producer/run_sts.py
@@ -67,7 +67,6 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='economic'):
 
     # modify either in code or in the config file
     settings.economics.source_c_inv = [0.]  # no investment costs for sources
-    settings.temperatures.supply = 90
 
     model_sets = tt.sets.create(mat)
     model = tt.single_timestep.model(
@@ -110,7 +109,6 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='economic'):
         f.savefig(os.path.join(outputpath, 'district_optimal.svg'),
                     bbox_inches='tight')
 
-
 if __name__ == '__main__':
     main(filepath=os.path.join(DATAPATH), outputpath=os.path.join(OUTPUTPATH),
          plots=PLOTS, solver=SOLVER, mode='economic')

diff --git a/examples/synthetic-network/convert_npy_to_parquet.py b/examples/synthetic-network/convert_npy_to_parquet.py
diff --git a/examples/synthetic-network/data/A_c.npy b/examples/synthetic-network/data/A_c.npy
diff --git a/examples/synthetic-network/data/A_i.npy b/examples/synthetic-network/data/A_i.npy
diff --git a/examples/synthetic-network/data/A_p.npy b/examples/synthetic-network/data/A_p.npy
diff --git a/examples/synthetic-network/data/Q_c.npy b/examples/synthetic-network/data/Q_c.npy
diff --git a/examples/synthetic-network/data/config.yaml b/examples/synthetic-network/data/config.yaml
@@ -25,12 +25,10 @@ solver:
   time_limit: 10000
 
 economics:
-  source_flh: [2500]  # h/y
   source_c_inv: [0]  # Investment costs for each source
   source_c_irr: [0.08]  # Interest rate for each source
   source_lifetime: [40.]  # years for source investments
   source_price: [80e-3]  # Price for heat production at supply in €/kW
-  consumer_flh: 2500  # h/y
   heat_price: 120e-3  # Selling Price for heat in €/kW
   pipes_c_irr: 0.08  # Interest rate
   pipes_lifetime: 40.  # years for piping investments
diff --git a/examples/synthetic-network/data/flh_consumer.parquet b/examples/synthetic-network/data/flh_consumer.parquet
diff --git a/examples/synthetic-network/data/flh_source.parquet b/examples/synthetic-network/data/flh_source.parquet
diff --git a/examples/synthetic-network/data/l_i.npy b/examples/synthetic-network/data/l_i.npy
diff --git a/examples/synthetic-network/data/rel_positions.npy b/examples/synthetic-network/data/rel_positions.npy
diff --git a/examples/synthetic-network/run_sts.py b/examples/synthetic-network/run_sts.py
@@ -67,8 +67,6 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='forced'):
     settings = tt.settings.load(os.path.join(filepath, 'config.yaml'))
     print(settings)
     settings.economics.source_c_inv = [0.]  # no investment costs for sources
-    settings.economics.source_flh = [2500.]  # full load hours
-    settings.economics.consumers_flh = [2500.]  # full load hours
 
     model_sets = tt.sets.create(mat)
     model = tt.single_timestep.model(
@@ -118,11 +116,6 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='forced'):
 
     network = tt.postprocessing.to_networkx_graph(opt_mats)
 
-    print(len(network.edges))
-    print(mat['a_i'].shape[1])
-    print(len(network.nodes))
-    print(mat['a_i'].shape[0])
-
     fig, ax = plt.subplots(figsize=(20, 20), layout='constrained')
     node_colors = []
     node_label = []
@@ -133,7 +126,7 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='forced'):
 
     for node in network.nodes(data=True):
         node_colors.append(node[1]['color'])
-        node_label.append(node[1]['type'])
+        node_label.append(node[1]['type_'])
         node_id[node[0]] = str(node[0])
         node_pos.append([node[1]['x'], node[1]['y']])
 
@@ -145,13 +138,14 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='forced'):
                             edgelist=network.edges, width=edges_p, ax=ax,
                             label=edges_label, alpha=0.3, edge_color='grey')
     nx.draw_networkx_nodes(network, pos=node_pos, node_color=node_colors,
-                            ax=ax, label=node)
+                            ax=ax, label=node_label)
 
     nx.draw_networkx_labels(network, pos=node_pos, labels=node_id, ax=ax)#
     nx.draw_networkx_edge_labels(network, pos=node_pos, edge_labels=edges_label, ax=ax)
+    adjancency = nx.to_numpy_array(network, weight=None)
+    print(adjancency)
 
     fig.show()
-    plt.pause(120)
     fig.savefig(os.path.join(outputpath, 'networkx.svg'), bbox_inches='tight')
     # close all figures
     plt.close('all')

diff --git a/topotherm/postprocessing.py b/topotherm/postprocessing.py
@@ -358,19 +358,19 @@ def to_networkx_graph(matrices):
     for q in range(matrices['a_c'].shape[0]):
         x, y = matrices['position'][q, 0], matrices['position'][q, 1]
         if ges[q] == 1:
-            G.add_node(q, color='Red', type='consumer', x=x, y=y)
+            G.add_node(q, color='Red', type_='consumer', x=x, y=y)
         elif ges[q] == 0:
-            G.add_node(q, color='Green', type='internal', x=x, y=y)
+            G.add_node(q, color='Green', type_='internal', x=x, y=y)
         if ges[q] <= -1:
-            G.add_node(q, color='Orange', type='source', x=x, y=y)
+            G.add_node(q, color='Orange', type_='source', x=x, y=y)
 
     # edge_labels = dict()
     # Add the edges to the graph
     for k in range(matrices['a_i'].shape[1]):
         s = (np.where(matrices['a_i'][:, k] == 1)[0][0],
              np.where(matrices['a_i'][:, k] == -1)[0][0])   
         G.add_edge(s[0], s[1],
-                   weight=matrices['l_i'][k],
+                   weight=matrices['l_i'][k].item(),
                    d=matrices['d_i_0'][k],
                    p=matrices['p'][k])