Update uncertainty example

WaterFutures · May 31, 2024 · 25434ba · 25434ba
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diff --git a/docs/examples/uncertainties.ipynb b/docs/examples/uncertainties.ipynb
@@ -39,6 +39,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import numpy as np\n",
     "from epyt_flow.data.networks import load_ltown\n",
     "from epyt_flow.simulation import ScenarioSimulator, ModelUncertainty, \\\n",
     "    RelativeUniformUncertainty\n",
@@ -98,7 +99,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Add uncertainty (i.e. randomness) with respect to the demand pattern -- i.e. demand pattern values can deviate up to 25% from their original value."
+    "Add uncertainty (i.e. randomness) with respect to the demand pattern -- i.e. demand pattern values can deviate up to 25% from their original value.\n",
+    "Consequently, the simulation is no longer deterministic and the results vary from run to run."
    ]
   },
   {
@@ -116,7 +118,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Run simulation and retrieve sensor readings at node \"n105\""
+    "Run simulation three times and retrieve sensor readings at node \"n105\""
    ]
   },
   {
@@ -125,9 +127,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "scada_data = sim.run_simulation()\n",
+    "measurements = []\n",
+    "for _ in range(3):\n",
+    "    scada_data = sim.run_simulation()\n",
+    "    measurements.append(scada_data.get_data_pressures(sensor_locations=[\"n105\"]).\n",
+    "                        flatten().tolist())\n",
     "\n",
-    "plot_timeseries_data(scada_data.get_data_pressures(sensor_locations=[\"n105\"]).T,\n",
+    "plot_timeseries_data(np.array(measurements),\n",
     "                     x_axis_label=\"Time (5min steps)\", y_axis_label=\"Pressure in $m$\")"
    ]
   },

diff --git a/examples/uncertainties.py b/examples/uncertainties.py
@@ -1,6 +1,7 @@
 """
 Example of adding uncertainty with respect to WDN parameters (e.g. demand pattern).
 """
+import numpy as np
 from epyt_flow.data.networks import load_ltown
 from epyt_flow.simulation import ScenarioSimulator, ModelUncertainty, RelativeUniformUncertainty
 from epyt_flow.utils import to_seconds
@@ -12,14 +13,20 @@
 
     # Create scenario
     with ScenarioSimulator(scenario_config=network_config) as sim:
-        # Set simulation duration to five hours
-        sim.set_general_parameters(simulation_duration=to_seconds(hours=5))
+        # Set simulation duration to three hours
+        sim.set_general_parameters(simulation_duration=to_seconds(hours=3))
 
         # Add uncertainty (i.e. randomness) with respect to the demand pattern --
         # i.e. demand pattern values can deviate up to 25% from their original value.
+        # Consequently, the simulation is no longer deterministic and the results vary
+        # from run to run.
         uc = RelativeUniformUncertainty(low=0.75, high=1.25)
         sim.set_model_uncertainty(ModelUncertainty(demand_pattern_uncertainty=uc))
 
-        # Run simulation and retrieve sensor readings at node "n105"
-        scada_data = sim.run_simulation()
-        print(scada_data.get_data_pressures(sensor_locations=["n105"]))
+        # Run simulation three times and retrieve sensor readings at node "n105"
+        measurements = []
+        for _ in range(3):
+            scada_data = sim.run_simulation()
+            measurements.append(scada_data.get_data_pressures(sensor_locations=["n105"]).
+                                flatten().tolist())
+        print(np.mean(measurements, axis=0), np.var(measurements, axis=0))