https://github.com/scivision/signal_subspace
vector and ensemble signal analysis w/ subspace methods such as Esprit and RootMusic
https://github.com/scivision/signal_subspace
esprit f2py frequency-estimation modern-fortran music root-music
Last synced: 9 months ago
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vector and ensemble signal analysis w/ subspace methods such as Esprit and RootMusic
- Host: GitHub
- URL: https://github.com/scivision/signal_subspace
- Owner: scivision
- License: mit
- Created: 2016-03-13T08:30:35.000Z (about 10 years ago)
- Default Branch: main
- Last Pushed: 2024-05-10T03:20:00.000Z (about 2 years ago)
- Last Synced: 2025-04-12T08:12:53.297Z (about 1 year ago)
- Topics: esprit, f2py, frequency-estimation, modern-fortran, music, root-music
- Language: Python
- Homepage:
- Size: 360 KB
- Stars: 26
- Watchers: 7
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Signal Subspace
[](http://pepy.tech/project/signal_subspace)
1-D and ensemble signal subspace analysis with methods such as Esprit
and RootMusic in Fortran, C, and Python
based in part upon the
[Spectral Analysis Lib public domain code](https://github.com/vincentchoqueuse/spectral_analysis_project)
The core subspace code is written in Fortran 2008 and is called from other languages (Python, C).
Since the programs are Fortran / Python based, they should compile and run in virtually any platform from embedded to supercomputer.
```sh
cmake -B build
cmake --build build
```
If Lapack is not available, it is built automatically.
In 2023-2024, F2PY and Numpy are going through a transition of build systems.
[CMake script build the f2py bindings](https://numpy.org/doc/stable/f2py/buildtools/cmake.html)
are used to build the f2py targets that allow Python use of this library.
```sh
cmake -B build -Dpython=yes
cmake --build build
```
In the examples below, observe the frequency estimates printed along with their corresponding eigenvalues.
A larger eigenvalue is increased confidence in that particular frequency estimate.
## ESPRIT examples
All example use a noisy sinusoid.
Some are "complex" using complex numbers, while others use real numbers.
There are two versions of the complex program, one a full accuracy using `double complex` numbers, and the other using `single real` numbers as input.
The single real (4 bytes/number) runs about 4 times faster than the double complex (16 bytes/number) program.
```sh
build/f_esprit_cmpl
build/f_esprit_real
```
Call Fortran Esprit from C using real single precision float:
```sh
build/c_esprit
```
Call Fortran Esprit from C++ using real single precision float:
```sh
build/cpp_esprit
```
---
Plots comparing real vs. complex ESPRIT:
```sh
python BasicEspritExample.py
```