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aguaclara

Pypi Version Documentation Build Status Code Coverage

aguaclara is a Python package developed by AguaClara Cornell and AguaClara Reach for designing and performing research on AguaClara water treatment plants. The package has several main functionalities:

  • DESIGN of AguaClara water treatment plant components
  • MODELING of physical, chemical, and hydraulic processes in water treatment
  • PLANNING of experimental setup for water treatment research
  • ANALYSIS of data collected by ProCoDA (process control and data acquisition tool)

Installing

The aguaclara package can be installed from Pypi by running the following command in the command line:

pip install aguaclara

To upgrade an existing installation, run

pip install aguaclara --upgrade

Using aguaclara

aguaclara's main functionalities come from several sub-packages.

  1. Core: fundamental physical, chemical, and hydraulic functions and values
  2. Design: modules for designing components of an AguaClara water treatment plant
  3. Research: modules for process modeling, experimental design, and data analysis in AguaClara research

To use aguaclara's registry of scientific units (based on the Pint package), use from aguaclara.core.units import u. Any other function or value in a sub-package can be accessed by importing the package itself:

Example Usage: Design

import aguaclara as ac
from aguaclara.core.units import u

# Design a water treatment plant
plant = ac.Plant(
    q = 40 * u.L / u.s,
    cdc = ac.CDC(coag_type = 'pacl'),
    floc = ac.Flocculator(hl = 40 * u.cm),
    sed = ac.Sedimentor(temp = 20 * u.degC),
    filter = ac.Filter(q = 20 * u.L / u.s)
)

Example Usage: Core

# continued from Example Usage: Design

# Model physical, chemical, and hydraulic properties 
cdc = plant.cdc
coag_tube_reynolds_number = ac.re_pipe(
    FlowRate = cdc.coag_q_max,
    Diam = cdc.coag_tube_id,
    Nu = cdc.coag_nu(cdc.coag_stock_conc, cdc.coag_type)
)

Example Usage: Research

import aguaclara as ac
from aguaclara.core.units import u
import matplotlib.pyplot as plt

# Plan a research experiment
reactor = ac.Variable_C_Stock(
    Q_sys = 2 * u.mL / u.s, 
    C_sys = 1.4 * u.mg / u.L, 
    Q_stock = 0.01 * u.mL / u.s
)
C_stock_PACl = reactor.C_stock()

# Visualize and analyze ProCoDA data
ac.iplot_columns(
    path = "https://raw.githubusercontent.com/AguaClara/team_resources/master/Data/datalog%206-14-2018.xls", 
    columns = [3, 4], 
    x_axis = 0
)
plt.ylabel("Turbidity (NTU)")
plt.xlabel("Time (hr)")
plt.legend(("Influent", "Effluent"))

The package is still undergoing rapid development. As it becomes more stable, a user guide will be written with more detailed tutorials. At the moment, you can find some more examples in specific pages of the API reference.

Contributing

Bug reports, features requests, documentation updates, and any other enhancements are welcome! To suggest a change, make an issue in the aguaclara Github repository.

To contribute to the package as a developer, refer to the Developer Guide.