SignalSharp 0.1.5
There is a newer version of this package available.
See the version list below for details.
See the version list below for details.
dotnet add package SignalSharp --version 0.1.5
NuGet\Install-Package SignalSharp -Version 0.1.5
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="SignalSharp" Version="0.1.5" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="SignalSharp" Version="0.1.5" />
<PackageReference Include="SignalSharp" />
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add SignalSharp --version 0.1.5
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: SignalSharp, 0.1.5"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
#addin nuget:?package=SignalSharp&version=0.1.5
#tool nuget:?package=SignalSharp&version=0.1.5
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
SignalSharp
C# library designed for efficient signal processing and time series analysis.
Features
Change Point Detection
- PELT (Pruned Exact Linear Time): Efficiently detects multiple change points in a signal using a pruning technique for improved speed without sacrificing accuracy.
- CUSUM (Cumulative Sum): Detects shifts in the mean value of a signal by accumulating deviations from a target value over time.
Signal Analysis
- Cost Functions:
- L1: Robust against outliers and non-Gaussian noise.
- L2: Ideal for normally distributed data.
- RBF (Radial Basis Function): Handles non-linear relationships between data points.
Signal Processing
Smoothing and Filtering:
- Savitzky-Golay Filter: Smooths data while preserving signal shape.
- Moving Average: Simple smoothing using a moving window.
- Kalman Filter: Estimates the state of a linear dynamic system from noisy measurements.
Resampling:
- Downsampling: Reduces the number of samples in a signal.
- Segment Statistics: Computes statistics (mean, median, max, min) for signal segments.
Installation
To install SignalSharp, you can use NuGet Package Manager:
dotnet add package SignalSharp
Usage
For detailed examples and API documentation, please refer to the official documentation.
Here's a quick example of how to use the PELT algorithm for change point detection:
using SignalSharp;
// Create a sample signal
double[] signal = [1, 1, 1, 5, 5, 5, 1, 1, 1];
// Initialize PELT algorithm
var options = new PELTOptions { CostFunction = new L2CostFunction(), MinSize = 1, Jump = 1 };
var algo = new PELTAlgorithm(options);
// Detect change points
var breakpoints = algo.FitAndDetect(signal, 2); // breakpoints = [3, 6]
Contributing
Contributions are welcome! If you have ideas, suggestions, or bug reports, feel free to open an issue or submit a pull request.
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net8.0 is compatible. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
net8.0
- MathNet.Numerics (>= 5.0.0)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.
Version | Downloads | Last updated |
---|---|---|
0.1.8 | 0 | 4/29/2025 |
0.1.7 | 0 | 4/29/2025 |
0.1.6 | 160 | 4/22/2025 |
0.1.5 | 165 | 4/20/2025 |
0.1.3 | 187 | 6/3/2024 |
0.1.2 | 108 | 6/3/2024 |
0.1.1 | 117 | 6/1/2024 |
0.1.0 | 118 | 5/30/2024 |
0.0.12 | 118 | 5/30/2024 |
0.0.11 | 116 | 5/30/2024 |
0.0.10 | 127 | 5/30/2024 |
0.0.7 | 137 | 5/30/2024 |
0.0.6 | 127 | 5/29/2024 |
0.0.5-ci14 | 101 | 5/29/2024 |
0.0.1 | 130 | 5/29/2024 |