An Interactive Online Curve Fitting Tool
Improve Your Data Processing Workflow

with our free curve fitting software:

  • build regression models interactively,
  • reuse them in code,
  • share models with your team.
Curve Fitting Tool Fine-tunning Spline

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Efficient and Accurate Curve Fitting Online

Take your curve fitting to a new level of simplicity with an interactive interface and advanced auto-fitting methods using SplineCloud's online tool

Use our advanced fine-tuning mode to manually adjust curve shapes and achieve the best fit for datasets of arbitrary complexity

Reuse online curve fit models in external applications using our RESTful API and client libraries

Share your datasets and regression models constructed using curve fitter online with your community

Few steps to use the curve fitting tool

1. Create Repository

2. Upload Your Data

3. Apply Curve Fitting

4. Reuse Curves in Code

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Advanced Online Curve Fitting With Powerfull Features

versatile online curve fitting tool that helps you in smoothing noisy data and building complex regression models

Curve Fit Online Integrations

access datasets and models created with the curve fit online tool in your code

Python Integration Icon

Client library for Python

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Client library for MATLAB

Use our API directly

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Explore Use Cases
For Our Curve Fitting Software Online

Watch the video explaining SplineCloud's approach to online fitting and learn about:

  • The traditional way to perform curve fitting;
  • The downsides of ‘hard-coded’ fitting methods;
  • How to leverage SplineCloud's rich capabilities, including advanced fine-tuning feature;
  • How SplineCloud's online tool simplifies the workflow and enhances model sharing.
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Curve Fitting Made Easy with SplineCloud

Typical Use Cases for the Online Curve Fitting Tool

Interpolate missing datapoints with our online tool to maintain continuity in relations represented by data.

Leverage regression models constructed with an online curve fitter in optimization algorithms to find the best combination of system parameters.

Smooth out noisy experimental or field data to obtain clean models that represent relations between variables.

Perfect for students and educators to explore curve fitting online, learn about interpolation, and smoothing techniques in real time.

Fit nonlinear or multivariable relations to approximate the behavior of physical or simulation-based systems.

Fit material properties parameters to build collections of ready-to-use models to support your calculations.

Adjust curve parameters to minimize root-mean-square error and find fit with arbitrary accuracy.

Convert component performance datasheets into reusable models that can be used in calculations and optimization processes.

Manually adjust curve shape to address complex data behavior, when automatic fitting algorithms are not sufficient.

Study statistical trends and discover laws in samples to predict nonlinear behavior in systems.

Extract mathematical relations from graphs or images for converting legacy or partially available data into reusable insights.

Find fit to results of parametric studies, replacing time-consuming simulation-based optimization processes with a lightweight meta-model-based alternative.

Transform Your Data Processing and Modeling Workflows

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Frequently Asked Questions

The SplineCloud online curve fitting tool is a web-based application integrated into a SplineCloud platform. It aims to simplify the workflow of data preparation for consecutive reuse in the code. Unlike other curve fitting software online, that provides a set of predefined fitting models, our free online tool helps users interpolate, approximate, and smoothen noisy data using advanced spline techniques. It is particularly useful for engineers, scientists, and analysts working with complex nonlinear relations.

The tool works with datasets derived from original datafiles. SplineCloud allows uploading text files (CSV, TXT, DAT or other types), spreadsheets, and images containing graphs. Such files may (but not necessarily) represent time series data, experimental measurements, material properties, simulation results, and other types of datasets. Clean subsets should be defined prior to using the curve fitting tool.

Yes, the online curve fitting tool is designed with the idea of allowing the reuse of curves in computer code. SplineCloud provides client libraries for Python and MATLAB, enabling seamless integration into your workflows. You can also use our API to build your custom integrations. With our approach you can fit curve online and refer to it in your code locally.

It depends on how large your datasets are. SplineCloud's online fitting tool works efficiently with datasets of up to several hundred datapoints. For significantly larger datasets, alternative approaches may be more suitable. When dealing with thousands of datapoints or more, you can programmatically apply linear fitting, which is often sufficient since nonlinear effects become negligible. In other cases, different curve fitting tools or machine learning techniques designed for regression on large datasets may be the better choice. However, if your data comes from simulations or experiments, it’s unlikely you’ll encounter size limitations with SplineCloud. Our tool will help you achieve accurate fits with the desired level of smoothness and continuity.

The curve fit online tool uses advanced spline fitting algorithms, ensuring highly accurate fits. You can customize fitting parameters to achieve optimal results for their specific datasets. More of that, SplineCloud allows you to fine-tune curves manually, by dragging, adding and removing control points, interactively adjusting a number of nodes, their position and continuity. You can refer to the RMSE hint on the 'Curves' toolbar to track how root-mean-squared error changes while you are adjusting curve parameters.

Yes, SplineCloud allows you to view and copy spline curve parameters to restore models in third-party software or computer code that supports B-Splines or NURBS. However, it is more convenient to pull the curves using our API or client libraries. Unlike any other curve fitting program that simply provides curve equations or graphical fits, SplineCloud is designed to enable the creation of reusable regression models. These models can be seamlessly integrated into your code, eliminating the need to refit curves on each execution or hard-code formulas for functional relations. With SplineCloud, refining your models becomes a streamlined process that is done separately from code by fitting curves online.

Yes, our online curve fitting tool is free to use with open data. To use our curve fitting online free tool, simply create a public repository and upload the data you wish to share with our community. If you prefer to keep your data private, you can still access our curve fit tool by subscribing to one of our plans, which includes options for restricted access.