Flux-conserving legacy routines in Fortran and Python
Project description
FluxConserving
A Fortran legacy package to easily compute the flux-density conservation
Obs.: A Fortran legacy Interpolation routines also furnished
email: antineutrinomuon@gmail.com, jean@astro.up.pt
© Copyright ®
J.G. - Jean Gomes
RESUME
Original Fortran 2003+ routines date back to 2003-2004. Read the LICENSE.txt file. When analyzing astronomical spectra, astronomers often bin the data to increase the signal-to-noise ratio and reduce the effects of noise in the data. Binning refers to the process of averaging the intensity of adjacent spectral channels, or pixels, to produce a new, coarser set of data.
In the process of binning, it is important to ensure that the principle of flux density conservation is maintained. This means that the total energy emitted by the object, and hence its flux density, must remain constant after binning.
To conserve flux density, the intensity of each binned pixel should be scaled by the number of pixels it represents. For example, if two adjacent pixels are binned together, the intensity of the resulting bin should be the sum of the intensities of the two original pixels, divided by two. This ensures that the total energy in the bin is conserved, and that the flux density of the object remains the same.
It's worth noting that binning can introduce errors in the spectral data, especially if the signal-to-noise ratio is low or if the binning is too coarse. In general, astronomers choose a binning size that balances the need for a high signal-to-noise ratio with the desire to maintain the spectral resolution and avoid introducing significant errors in the data.
In summary, the principle of flux density conservation is important to consider when binning astronomical spectra, and astronomers need to scale the intensity of each binned pixel to ensure that the total energy emitted by the object is conserved. SpectRes from A. Carnall is NOT part of the distribution, but used as a comparison: https://github.com/ACCarnall/SpectRes.
Accompanying there are several routines for interpolations.
INSTALLATION
You can easily install pyfluxconserving by using pip - PyPI - The Python Package Index:
pip install pyfluxconserving
or by using a generated conda repository https://anaconda.org/neutrinomuon/pyfluxconserving:
conda install -c neutrinomuon pyfluxconserving
OBS.: Linux, OS-X and Windows pre-compilations available in conda.
You can also clone the repository and install by yourself in your machine:
git clone https://github.com/neutrinomuon/FluxConserving python setup.py install
METHOD & REFERENCES
Here, the method used is with the Cumulative function to produce a new flux-conserved, some options can be chosen for the interpolation:
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1) | Interpolado | Based on a linear interpolation within
a table of pair values.
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STRUCTURE
The main structure of the directories and files are:
FluxConserving ├── dist │ └── pyfluxconserving-0.0.1.tar.gz ├── README.md ├── LICENSE.txt ├── setup.py ├── tutorials │ ├── fluxconserving.png │ └── Flux-Conserving Example.ipynb ├── pyfluxconserving.egg-info │ ├── PKG-INFO │ ├── dependency_links.txt │ ├── SOURCES.txt │ ├── top_level.txt │ └── requires.txt ├── src │ ├── python │ │ ├── PyFluxConSpec.py │ │ ├── califa_cmap_alternative.py │ │ ├── PyLinear__int.py │ │ ├── PyLINinterpol.py │ │ ├── PySPLINECubic.py │ │ ├── fluxconserve.py │ │ ├── __init__.py │ │ ├── PySPLINE1DArr.py │ │ ├── PySPLINE3DFor.py │ │ ├── fluxconserving.png │ │ ├── PyAkimaSpline.py │ │ ├── PySPLINE3DAlt.py │ │ ├── PyInterpolado.py │ │ └── PyLINdexerpol.py │ └── fortran │ ├── LINdexerpol.f90 │ ├── SPLINE3DFor.cpython-39-x86_64-linux-gnu.so │ ├── SPLINE1DFlt.cpython-39-x86_64-linux-gnu.so │ ├── SPLINE3DFor.compile │ ├── FluxConSpec.compile │ ├── SPLINE1DArr.compile │ ├── Interpolado.cpython-39-x86_64-linux-gnu.so │ ├── Interpolado.cpython-38-x86_64-linux-gnu.so │ ├── SPLINE1DFlt.f90 │ ├── AkimaSpline.f90 │ ├── SPLINE1DArr.f90 │ ├── SPLINE1DFlt.cpython-38-x86_64-linux-gnu.so │ ├── SPLINE3DFor.cpython-38-x86_64-linux-gnu.so │ ├── AkimaSpline.compile │ ├── DataTypes.f90 │ ├── LINdexerpol.compile │ ├── SPLINE3DFor.f90 │ ├── SPLINE1DFlt.compile │ ├── Interpolado.f90 │ ├── SPLINE1DFlt.cpython-310-x86_64-linux-gnu.so │ ├── FluxConSpec.f90 │ ├── Interpolado.cpython-310-x86_64-linux-gnu.so │ ├── LINdexerpol.cpython-310-x86_64-linux-gnu.so │ ├── README.txt │ ├── Interpolado.compile │ ├── SPLINE3DFor.cpython-310-x86_64-linux-gnu.so │ ├── LINinterpol.f90 │ ├── LINdexerpol.cpython-39-x86_64-linux-gnu.so │ └── LINdexerpol.cpython-38-x86_64-linux-gnu.so ├── version.txt └── build ├── lib.linux-x86_64-3.9 │ └── pyfluxconserving ├── src.linux-x86_64-3.9 │ ├── pyfluxconserving │ ├── build │ └── numpy └── temp.linux-x86_64-3.9 ├── pyfluxconserving ├── ccompiler_opt_cache_ext.py ├── src ├── .libs └── build 18 directories, 56 files
PyFluxConSPec.py is a python wrapper to the library in fortran called
pyfluxconserving.flib. The fortran directory can be compiled separately for
each individual subroutine.
LICENSE
This software is provided "AS IS" (see DISCLAIMER below). Permission to use, for non-commercial purposes is granted. Permission to modify for personal or internal use is granted, provided this copyright and disclaimer are included in ALL copies of the software. All other rights are reserved. In particular, redistribution of the code is not allowed without explicit permission by the author.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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