Curve fitting is an essential tool in chemical engineering, enabling professionals and researchers to model complex processes and phenomena through mathematical equations. This app was developed to simplify the application of different curve fitting models, such as Linear, Exponential, First Order Model, Generalized Logistic Function, Granulometric Distribution, and Nagata Equation, facilitating precise and optimized analyses in various chemical engineering contexts.
Curve fitting is crucial in chemical engineering for process modeling, reaction optimization, quality control, and the development of new materials and products. The ability to predict behaviors and deeply understand the relationships between variables allows for innovations and operational efficiencies, highlighting the importance of tools like this app for professionals in the field.
Ideal for direct relationships between variables, offering a simple solution for initial trend analyses.
Applicable in growth or decay processes that follow a constant rate proportional to the current size of the system.
Often used in system dynamics where the rate of change is proportional to the current state.
Used to model population growth, saturation processes, and other phenomena that approach a maximum limit.
Essential for characterizing the size distribution of particles in mixtures, commonly used in soil, sediment, and powdered materials analyses.
Applies to fluid dynamics and the study of flows, especially useful in chemical engineering for modeling behaviors of mixtures and reactions.
The unique feature of this app is the ability to create and adjust your own custom models. You are not limited to predefined models; our intuitive interface allows you to define any type of equation to fit your specific data, offering unprecedented flexibility in your analyses.
The Ramer-Douglas-Peucker algorithm is a method used in computer graphics and GIS to simplify curves or polylines by reducing points. It was independently developed by Urs Ramer in 1972 and by David Douglas and Thomas Peucker in 1973. The algorithm works by approximating a curve with fewer points, maintaining the shape's essential features within a specified tolerance.
The process starts by connecting the first and last points of the curve with a line, identifying the farthest point from this line, and keeping it if its distance exceeds the tolerance. This point divides the curve into two segments, and the algorithm recursively simplifies each segment. This iterative approach significantly reduces data complexity in GIS applications, enhancing storage, processing, and display efficiencies without compromising the geographical features' visual integrity.
The Ramer-Douglas-Peucker algorithm exemplifies how data reduction can be achieved without losing significant geometric detail, making it invaluable in digital mapping and various applications requiring efficient rendering of complex shapes.
To install the necessary dependencies, you need to have Python installed on your system. If you don't have Python, you can download it here. After installing Python, follow the steps below:
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Clone the Repository
First, clone the Easy Curve Fit repository to your local machine.
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Install Dependencies
Inside the project directory, there is a file called
requirements.txtthat contains all the necessary libraries. To install them, execute the following command: pip install -r requirements.txtThis will install all the necessary dependencies to run Easy Curve Fit.
To run the application, follow these steps:
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Navigate to the project directory where
main.pyis located. -
Execute the
main.pyfile using Python: python main.py -
After running the command, Dash will start the local server and you can access the application through your browser. Normally, the URL will be something like
http://127.0.0.1:8050/.
- In the Datasets directory, you will find example datasets that can assist you.
If you encounter any problems or have any questions, do not hesitate to open an issue in the GitHub repository or contact us directly.
Contact: https://linktr.ee/CascaGrossaSuprema
We hope you enjoy using Easy Curve Fit!