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p-snft merged 2 commits into from
Jun 18, 2025
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Revision/osmnx 2 #152

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8d69d8b
Switch to osmnx >= 2.0.0
p-snft Jun 18, 2025
13f8439
Adhere to Black
p-snft Jun 18, 2025
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2 changes: 1 addition & 1 deletion dhnx/input_output.py
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Original file line number Diff line number Diff line change
Expand Up @@ -205,7 +205,7 @@ def download_footprints(self):

print('Downloading footprints...')

footprints = ox.geometries_from_point(
footprints = ox.features_from_point(
center_point=self.place,
dist=self.distance,
tags={'building': True},
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94 changes: 69 additions & 25 deletions examples/optimisation/discrete_DN_numbers/discrete_DN_numbers.py
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Expand Up @@ -8,59 +8,103 @@

For each of the DN numbers a separate row is given in the table.
"""

import os

import matplotlib.pyplot as plt
import dhnx


os.chdir(os.path.dirname(__file__))

# Initialize thermal network
network = dhnx.network.ThermalNetwork()
network = network.from_csv_folder('twn_data')
network = network.from_csv_folder("twn_data")

# Load investment parameter
invest_opt = dhnx.input_output.load_invest_options('invest_data')
invest_opt = dhnx.input_output.load_invest_options("invest_data")

# plot network
static_map = dhnx.plotting.StaticMap(network)
static_map.draw(background_map=False)
plt.title('Given network')
plt.scatter(network.components.consumers['lon'], network.components.consumers['lat'],
color='tab:green', label='consumers', zorder=2.5, s=50)
plt.scatter(network.components.producers['lon'], network.components.producers['lat'],
color='tab:red', label='producers', zorder=2.5, s=50)
plt.scatter(network.components.forks['lon'], network.components.forks['lat'],
color='tab:grey', label='forks', zorder=2.5, s=50)
plt.text(-2, 32, 'P0', fontsize=14)
plt.title("Given network")
plt.scatter(
network.components.consumers["lon"],
network.components.consumers["lat"],
color="tab:green",
label="consumers",
zorder=2.5,
s=50,
)
plt.scatter(
network.components.producers["lon"],
network.components.producers["lat"],
color="tab:red",
label="producers",
zorder=2.5,
s=50,
)
plt.scatter(
network.components.forks["lon"],
network.components.forks["lat"],
color="tab:grey",
label="forks",
zorder=2.5,
s=50,
)
plt.text(-2, 32, "P0", fontsize=14)
plt.legend()
plt.show()

# Execute investment optimization
network.optimize_investment(invest_options=invest_opt)

# ####### Postprocessing and Plotting ###########

# get results
results_edges = network.results.optimization['components']['pipes']
print(results_edges[['from_node', 'to_node', 'hp_type', 'capacity',
'direction', 'costs', 'losses']])
results_edges = network.results.optimization["components"]["pipes"]
print(
results_edges[
["from_node", "to_node", "hp_type", "capacity", "direction", "costs", "losses"]
]
)

# print(results_edges[['invest_costs[€]']].sum())
print('Objective value: ', network.results.optimization['oemof_meta']['objective'])
print("Objective value: ", network.results.optimization["oemof_meta"]["objective"])

# assign new ThermalNetwork with invested pipes
twn_results = network
twn_results.components['pipes'] = results_edges[results_edges['capacity'] > 0.001]
twn_results.components["pipes"] = results_edges[results_edges["capacity"] > 0.001]

# plot invested edges
static_map_2 = dhnx.plotting.StaticMap(twn_results)
static_map_2.draw(background_map=False)
plt.title('Result network')
plt.scatter(network.components.consumers['lon'], network.components.consumers['lat'],
color='tab:green', label='consumers', zorder=2.5, s=50)
plt.scatter(network.components.producers['lon'], network.components.producers['lat'],
color='tab:red', label='producers', zorder=2.5, s=50)
plt.scatter(network.components.forks['lon'], network.components.forks['lat'],
color='tab:grey', label='forks', zorder=2.5, s=50)
plt.text(-2, 32, 'P0', fontsize=14)
for r, c in twn_results.components['pipes'].iterrows():
plt.title("Result network")
plt.scatter(
network.components.consumers["lon"],
network.components.consumers["lat"],
color="tab:green",
label="consumers",
zorder=2.5,
s=50,
)
plt.scatter(
network.components.producers["lon"],
network.components.producers["lat"],
color="tab:red",
label="producers",
zorder=2.5,
s=50,
)
plt.scatter(
network.components.forks["lon"],
network.components.forks["lat"],
color="tab:grey",
label="forks",
zorder=2.5,
s=50,
)
plt.text(-2, 32, "P0", fontsize=14)
for r, c in twn_results.components["pipes"].iterrows():
size = c["hp_type"]
type = c["from_node"].split("-")[0]
id = c["from_node"].split("-")[1]
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51 changes: 27 additions & 24 deletions examples/optimisation/invest_with_existing/invest_with_existing.py
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Original file line number Diff line number Diff line change
@@ -1,60 +1,63 @@
import matplotlib.pyplot as plt
import dhnx
import os

os.chdir(os.path.dirname(__file__))
# Initialize thermal network
network = dhnx.network.ThermalNetwork()
network = network.from_csv_folder('twn_data')
network = network.from_csv_folder("twn_data")

# general optimisation settings
set = {'num_ts': 3,
'time_res': 1,
'start_date': '1/1/2018',
'frequence': 'H',
'solver': 'cbc',
'solve_kw': {'tee': True},
'simultaneity': 0.8,
'bidirectional_pipes': True,
'print_logging_info': True,
'heat_demand': 'series',
}

invest_opt = dhnx.input_output.load_invest_options('invest_data')
set = {
"num_ts": 3,
"time_res": 1,
"start_date": "1/1/2018",
"frequence": "H",
"solver": "cbc",
"solve_kw": {"tee": True},
"simultaneity": 0.8,
"bidirectional_pipes": True,
"print_logging_info": True,
"heat_demand": "series",
}

invest_opt = dhnx.input_output.load_invest_options("invest_data")

network.optimize_investment(**set, invest_options=invest_opt)

# Draw network
static_map = dhnx.plotting.StaticMap(network)
static_map.draw(background_map=False)
plt.title('Given network')
plt.title("Given network")
plt.show()

# get results
results_edges = network.results.optimization['components']['pipes']
print('*Results*')
results_edges = network.results.optimization["components"]["pipes"]
print("*Results*")
print(results_edges)

# get indices which are existing or invested
ind = results_edges[results_edges['capacity'] > 0].index
ind = results_edges[results_edges["capacity"] > 0].index

edges = network.components['pipes']
ind_exist = list(edges[edges['existing'] == 1].index)
edges = network.components["pipes"]
ind_exist = list(edges[edges["existing"] == 1].index)

# plot existing network
network_exist = network
network_exist.components['pipes'] = edges.loc[ind_exist]
network_exist.components["pipes"] = edges.loc[ind_exist]

# plot existing network
static_map = dhnx.plotting.StaticMap(network_exist)
static_map.draw(background_map=False)
plt.title('Existing pipes')
plt.title("Existing pipes")
plt.show()

# select xisting or invested edges
network_result = network
network_result.components['pipes'] = results_edges.loc[ind]
network_result.components["pipes"] = results_edges.loc[ind]

# plot results network
static_map = dhnx.plotting.StaticMap(network_result)
static_map.draw(background_map=False)
plt.title('Investment result')
plt.title("Investment result")
plt.show()
31 changes: 17 additions & 14 deletions examples/optimisation/minimal_network/minimal_network.py
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Original file line number Diff line number Diff line change
@@ -1,46 +1,49 @@
import os

import matplotlib.pyplot as plt
import dhnx


os.chdir(os.path.dirname(__file__))


# Initialize thermal network
network = dhnx.network.ThermalNetwork()
network = network.from_csv_folder('twn_data')
network = network.from_csv_folder("twn_data")

# Load investment parameter
invest_opt = dhnx.input_output.load_invest_options('invest_data')
invest_opt = dhnx.input_output.load_invest_options("invest_data")

# Execute investment optimization
network.optimize_investment(invest_options=invest_opt,
write_lp_file=True)
network.optimize_investment(invest_options=invest_opt, write_lp_file=True)

# ####### Postprocessing and Plotting ###########
# Draw network
static_map = dhnx.plotting.StaticMap(network)
static_map.draw(background_map=False)
plt.title('Given network')
plt.title("Given network")
plt.show()

# get results
results_edges = network.results.optimization['components']['pipes']
print('*Results*')
results_edges = network.results.optimization["components"]["pipes"]
print("*Results*")
print(results_edges)
print('')
print('Objective Value: ',
network.results.optimization['oemof_meta']['objective'])
print("")
print("Objective Value: ", network.results.optimization["oemof_meta"]["objective"])

# manually recalculate total costs
total_costs = (33 * 3.162 + 15 * 1 + 18 * 1 + 18 * 0.5) * 0.5
print('Costs re-calculation: ', total_costs)
print("Costs re-calculation: ", total_costs)

# get indices which are existing or invested
ind = results_edges[results_edges['capacity'] > 0].index
ind = results_edges[results_edges["capacity"] > 0].index

# select invested edges
network_result = network
network_result.components['pipes'] = results_edges.loc[ind]
network_result.components["pipes"] = results_edges.loc[ind]

# plot results network
static_map = dhnx.plotting.StaticMap(network_result)
static_map.draw(background_map=False)
plt.title('Optimization result')
plt.title("Optimization result")
plt.show()
2 changes: 1 addition & 1 deletion setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ def read(fname):
extras_require={
'cartopy': ['cartopy'],
'geopandas': ['geopandas'],
'osmnx': ['osmnx >= 0.16.1'],
'osmnx': ['osmnx >= 2.0.0'],
"tests": [
"geopandas", "osmnx",
"CoolProp",
Expand Down