I am running Chama on two signals files. Both files were created programmatically with Python code to generate a signal file as a CSV. The signal file is the only input that is different between the two files. One file runs while the other file is giving me an error.

The signal files appear to be correct. Both are in the same format.
Node, Time, Data
The sensor locations are the same as is the time the same. Both are different lengths but the longer file is one that is working. The major diffrence is the values in the
I have attached part of the csv's zipped here as the files are too large even zipped to put in full. I am looking into our process of generating these files in order to fix this issue.
not working signals.zip
working signals.zip

Running the code below with values of granularity to be 40 and 100 gives different concentration values in chama.simulation.GaussianPlume model. granularity below is a variable that tells how much finely we want to divide the volume.

Expected Output:
Similar concentration values, irrespective of the value of granularity.

Current Output:
Radically different values by just changing the granularity. I was able to get the max concentration values to be equal to S = 389.843737 for the case when granularity = 100
And S = 48.59 when granularity = 40.

# %% Imports
import numpy as np
import pandas as pd
import chama
import matplotlib.pyplot as plt
#%matplotlib inline

# %% Making a 3D grid
x_vals = (0, 40)
y_vals = x_vals
z_vals = (0, 10)
x_start = 10
y_start = x_start
z_start = 5
granularity = 40  ######### ←← Just changing this makes the concentration values fluctuate
x_grid = np.linspace(*x_vals, granularity) # this is in mts
y_grid = np.linspace(*y_vals, granularity)
z_grid = np.linspace(*z_vals, granularity)
grid = chama.simulation.Grid(x_grid, y_grid, z_grid)

# %% Defining a pollutant source with rate
source = chama.simulation.Source(x_start, y_start, z_start, rate = 3)

# %% Defining the Atmospheric Conditions (We only support x-y plane air movement)
atm = pd.DataFrame(
        {
           'Wind Direction': [45],
           'Wind Speed': [2],
           'Stability Class': ['A'],
        },
        index=[0]
      )

# %% Gives the concentrations during steady state
gauss_plume = chama.simulation.GaussianPlume(grid, source, atm)
gauss_plume.run()
signal = gauss_plume.conc
print(signal.head(5))
print(signal.tail(5))

# %%
chama.graphics.signal_convexhull(
        signal, 
        scenarios=['S'], 
        threshold=1e-5,
        x_range = x_vals, 
        y_range = y_vals, 
        z_range = z_vals
    )
print (signal.max())
plt.show()

I was hoping the value of the concentrations should not fluctuate. Is there something that I am missing here?

Thanks a lot for the help.

I had selected the source location as y = 20 and x = 20. I expected the Concentration values to be maximum near the source, but according to the cross-section of the concentration values, that is not being followed.

If this something that is expected, kindly accept my apologies. It would be fantastic if you could direct me to some source to study Gaussian Plumes.

Thanks a lot for your help.

Hello.
I am trying to run of the code samples provided in WNTR projects repository. https://github.com/USEPA/WNTR/blob/main/examples/sensor_placement.py

At a certain moment I get the following error.

Traceback (most recent call last):
  File "../main.py", line 68, in <module>
    results[n] = impactform.solve(min_det_time, sensor_characteristics,
  File "..\optimize.py", line 107, in solve
    self.create_pyomo_model(impact=impact, sensor=sensor, scenario=scenario,
  File "..\optimize.py", line 140, in create_pyomo_model
    cu._df_columns_required('impact', impact,
  File "..\chama\utils.py", line 23, in _df_columns_required
    raise TypeError('Expected column "{0}" of type {1} in DataFrame '
TypeError: Expected column "Impact" of type [<class 'numpy.float64'>, <class 'numpy.int64'>] in DataFrame "impact".

I looked at your examples (e.g. https://chama.readthedocs.io/en/stable/optimization.html) and source code. In the examples it is shown that Impact column is of (most likely) float64 type. However, in the source code it is written the following:

cu._df_columns_required('impact', impact,
                                {'Scenario': np.object,
                                 'Sensor': np.object,
                                 impact_col_name: [np.float64, np.int64]})

So the example from tutorial and a source code don't match.
What is the best way to fix it? Should I simply change to e.g. impact_col_name: np.float64? Or is there another workaround?
Thank you.

Hi,

Is there an example somewhere about importing an INP file (defining a water network) to be used by Chama?

The closest I could find is test_examples.py that reads from a csv file. I would like to do the same, but from an INP file like

Please note that this issue is not just about file formats, but also about the data within the INP that might be different from the CSV data given in the example above. For an example, check out the benchmark Hanoi network INP description here.

Thank you,
Paul Irofti

I was playing around with the library by changing the values of parameters and I noticed that making the wind_speed close to 0 in the chama.simulation.GaussianPlume model, the concentration of the pollutants becomes zero everywhere.

For the case of wind_speed = 10.

For the case of wind_speed = 0.1.

Expected Output:
Non-zero concentration values, irrespective of the value of wind_speed. At max, the Gaussian plume would be facing upwards.

Current Output:
zero valued Concentration Values for the case when wind_speed = 0.1, but Non-zero values when wind_speed = 10.

To Reproduce:

# %% Imports
import numpy as np
import pandas as pd
import chama
import matplotlib.pyplot as plt
#%matplotlib inline

# %% Making a 3D grid
x_vals = (0, 100)
y_vals = x_vals
z_vals = (0, 100)
x_start = 50
y_start = x_start
z_start = 20
granularity = 40
x_grid = np.linspace(*x_vals, granularity) # this is in mts
y_grid = np.linspace(*y_vals, granularity)
z_grid = np.linspace(*z_vals, granularity)
grid = chama.simulation.Grid(x_grid, y_grid, z_grid)

# %% Defining a pollutant source with rate
source = chama.simulation.Source(x_start, y_start, z_start, rate = 300)

# %% Defining the Atmospheric Conditions
atm = pd.DataFrame(
        {
           'Wind Direction': [0],
           'Wind Speed': [0.1], ## ←← Changing this to 0.1 makes concenration values die.
           'Stability Class': ['C'],
        },
        index=[0]
      )

# %% Gives the concentrations during steady state
gauss_plume = chama.simulation.GaussianPlume(grid, source, atm)
gauss_plume.run()
signal = gauss_plume.conc
print(signal.head(5))
print(signal.tail(5))

# %%
chama.graphics.signal_convexhull(
        signal, 
        scenarios=['S'], 
        threshold=1e-5,
        x_range = x_vals, 
        y_range = y_vals, 
        z_range = z_vals
    )

plt.show()
print (signal.max())
chama.graphics.signal_xsection(signal, 'S')
plt.show()

I was assuming the value of the concentrations should not die when wind_speed nears zero. Is there something that I am missing here?

Thanks a lot for the help.