Advanced Quality Analysis Example

[1]:

from IPython.display import display, HTML
display(HTML('<a target="_blank" href="https://colab.research.google.com/github/WaterFutures/EPyT-Flow/blob/main/docs/examples/net2-cl2_example.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>'))
Open In Colab

Example of running an advanced quality analysis of Cl2 in Net2 using EPANET-MSX – more information on how to run advanced quality analysis using EPANET-MSX can be found in the documentation.

[2]:

%pip install epyt-flow --quiet

Note: you may need to restart the kernel to use updated packages.

[3]:

from epyt_flow.simulation import ScenarioSimulator
from epyt_flow.visualization import ScenarioVisualizer, black_colors
from epyt_flow.utils import to_seconds

Create a new scenario for chlorine analysis in the Net2 network:

[4]:

scenario = ScenarioSimulator(f_inp_in="net2-cl2.inp", f_msx_in="net2-cl2.msx")

Set simulation duration to five days:

[5]:

scenario.set_general_parameters(simulation_duration=to_seconds(days=5))

Monitor the “CL2” bulk species at every node by calling set_bulk_species_node_sensors():

[6]:

scenario.set_bulk_species_node_sensors(sensor_info={"CL2": scenario.sensor_config.nodes})

Run the entire simulation:

[7]:

scada_data = scenario.run_simulation()

Show “CL2” concentration at the 11th node over the entire simulation:

[8]:

scada_data.plot_bulk_species_node_concentration({"CL2": [scenario.sensor_config.nodes[10]]})
../_images/examples_net2-cl2_example_14_0.png 
[8]:

<Axes: xlabel='Time (60min steps)', ylabel='Concentration in $MG/L$'>

[9]:

from IPython.display import HTML

scenario.place_bulk_species_node_sensors_everywhere(['CL2'])
vis = ScenarioVisualizer(scenario, color_scheme=black_colors)
vis.color_nodes(data=scada_data, parameter='bulk_species_concentration',
                species='CL2', use_sensor_data=True, statistic='time_step',
                pit=(0, 60))
anim = vis.show_animation(return_animation=True, duration=10)
HTML(anim.to_jshtml(fps=15))

[9]:

<Figure size 640x480 with 0 Axes>

Do not forget to close the simulation!

[10]:

scenario.close()