classic-isotherms


Nameclassic-isotherms JSON
Version 0.0.1 PyPI version JSON
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home_pagehttps://github.com/mv-per/classic-isotherms
SummaryA package to calculate the classic and empirical isotherms
upload_time2023-06-11 20:43:39
maintainer
docs_urlNone
authorMarcus Pereira
requires_python
license
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requirements No requirements were recorded.
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            # ClassicIsotherms

ClassicIsotherms is a Python module that provides implementations of various classic adsorption isotherm equations. It allows you to calculate the loading and deviations for different isotherm models based on pressure, temperature, and parameters.

## Installation

You can install ClassicIsotherms using pip:

```shell
    pip install classic-isotherms
```

## Usage

```python
    import ClassicIsotherms

    # Create an instance of ClassicIsotherm
    isotherm = ClassicIsotherms("freundlich")

    # Calculate loading for a given pressure, temperature, and parameters
    pressure = 1.5
    temperature = 298.15
    parameters = [2.0, 1.5]
    loading = isotherm.get_loading(pressure, temperature, parameters)
    print("Loading:", loading)

    # Calculate loadings for multiple pressures
    pressures = [1.0, 2.0, 3.0]
    loadings = isotherm.get_loadings(pressures, temperature, parameters)
    print("Loadings:", loadings)

    # Calculate deviation using a specific deviation function
    experimental_loadings = [0.5, 1.0, 1.5]
    deviation_equation = "SSE"
    deviation = isotherm.get_deviation(pressures, experimental_loadings, temperature, parameters, deviation_equation)
    print("Deviation:", deviation)
```

# Supported Isotherm Models

The following classic adsorption isotherm models are currently supported:

- Freundlich (`'freundlich'`)
- Langmuir (`'langmuir'`)
- Redlich-Peterson (`'redlich-perterson'`)
- Sips (`'sips'`)
- Toth (`'toth'`)
- Unilan (`'unilan'`)
- Keller-Staudt-Toth (`'keller-staudt-toth'`)

# Supported Deviation Methods

The following deviation methods are currently supported:

- Sum of Squared Errors (`'SSE'`)
- Average Relative Error (`'ARE'`)
- Absolute Error (`'EABS'`)
- Hybrid Deviation (`'HYBRID'`)
- Mean Percentage Standard Deviation (`'MPSD'`)
- Sum of Relative Errors (`'SRE'`)
- Chi-square Deviation ('`CHI_2'`)
- Residual Sum of Squares Deviation (`'R_S'`)

# Contributing

Contributions are welcome! If you have suggestions, bug reports, or feature requests, please open an issue on the [GitHub repository](https://github.com/mv-per/ClassicIsotherms).

# License

ClassicIsotherms is licensed under the MIT License. See the [LICENSE](https://github.com/mv-per/ClassicIsotherms/blob/main/LICENSE) file for more information.

            

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    "description": "# ClassicIsotherms\n\nClassicIsotherms is a Python module that provides implementations of various classic adsorption isotherm equations. It allows you to calculate the loading and deviations for different isotherm models based on pressure, temperature, and parameters.\n\n## Installation\n\nYou can install ClassicIsotherms using pip:\n\n```shell\n    pip install classic-isotherms\n```\n\n## Usage\n\n```python\n    import ClassicIsotherms\n\n    # Create an instance of ClassicIsotherm\n    isotherm = ClassicIsotherms(\"freundlich\")\n\n    # Calculate loading for a given pressure, temperature, and parameters\n    pressure = 1.5\n    temperature = 298.15\n    parameters = [2.0, 1.5]\n    loading = isotherm.get_loading(pressure, temperature, parameters)\n    print(\"Loading:\", loading)\n\n    # Calculate loadings for multiple pressures\n    pressures = [1.0, 2.0, 3.0]\n    loadings = isotherm.get_loadings(pressures, temperature, parameters)\n    print(\"Loadings:\", loadings)\n\n    # Calculate deviation using a specific deviation function\n    experimental_loadings = [0.5, 1.0, 1.5]\n    deviation_equation = \"SSE\"\n    deviation = isotherm.get_deviation(pressures, experimental_loadings, temperature, parameters, deviation_equation)\n    print(\"Deviation:\", deviation)\n```\n\n# Supported Isotherm Models\n\nThe following classic adsorption isotherm models are currently supported:\n\n- Freundlich (`'freundlich'`)\n- Langmuir (`'langmuir'`)\n- Redlich-Peterson (`'redlich-perterson'`)\n- Sips (`'sips'`)\n- Toth (`'toth'`)\n- Unilan (`'unilan'`)\n- Keller-Staudt-Toth (`'keller-staudt-toth'`)\n\n# Supported Deviation Methods\n\nThe following deviation methods are currently supported:\n\n- Sum of Squared Errors (`'SSE'`)\n- Average Relative Error (`'ARE'`)\n- Absolute Error (`'EABS'`)\n- Hybrid Deviation (`'HYBRID'`)\n- Mean Percentage Standard Deviation (`'MPSD'`)\n- Sum of Relative Errors (`'SRE'`)\n- Chi-square Deviation ('`CHI_2'`)\n- Residual Sum of Squares Deviation (`'R_S'`)\n\n# Contributing\n\nContributions are welcome! If you have suggestions, bug reports, or feature requests, please open an issue on the [GitHub repository](https://github.com/mv-per/ClassicIsotherms).\n\n# License\n\nClassicIsotherms is licensed under the MIT License. See the [LICENSE](https://github.com/mv-per/ClassicIsotherms/blob/main/LICENSE) file for more information.\n",
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