%global _empty_manifest_terminate_build 0
Name:		python-vetting
Version:	0.3
Release:	1
Summary:	Simple, stand-alone vetting tools for transiting signals in Keper, K2 and TESS data
License:	MIT
URL:		https://github.com/SSDataLab/vetting
Source0:	https://mirrors.aliyun.com/pypi/web/packages/7f/2e/5a2f44fd291eed095ff4393f9e9effdd588c87495ee05311f095facfbd07/vetting-0.3.tar.gz
BuildArch:	noarch

Requires:	python3-lightkurve
Requires:	python3-corner

%description
# vetting

**`vetting` contains simple, stand-alone Python tools for vetting transiting signals in NASA's Kepler, K2 and TESS data. `vetting` requires an installation of Python 3.8 or higher.**

[![pypi](https://img.shields.io/pypi/v/vetting)](https://pypi.org/project/vetting/)
![pytest](https://github.com/ssdatalab/vetting/workflows/pytest/badge.svg)

## Installation

You can install `vetting` by executing the following in a terminal

```
pip install vetting
```

### Centroid testing

An example of a simple test is shown below.

![Example of simple centroid test](https://github.com/SSDataLab/vetting/raw/main/demo.png)

Here a significant offset is detected in the centroid of false positive KOI-608 during transit. The p-value for the points during transit being drawn from the same distribution as the points out of transit is low, (there is a less than 1% chance these are drawn from the same distribution). To recreate this example you can use the following script:

```python
import lightkurve as lk
from vetting import centroid_test

tpf = lk.search_targetpixelfile('KOI-608', mission='Kepler', quarter=10).download()
period, t0, dur = 25.3368592, 192.91552, 8.85/24
r = centroid_test(tpf, period, t0, dur, aperture_mask='pipeline', plot=False)
```


%package -n python3-vetting
Summary:	Simple, stand-alone vetting tools for transiting signals in Keper, K2 and TESS data
Provides:	python-vetting
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-vetting
# vetting

**`vetting` contains simple, stand-alone Python tools for vetting transiting signals in NASA's Kepler, K2 and TESS data. `vetting` requires an installation of Python 3.8 or higher.**

[![pypi](https://img.shields.io/pypi/v/vetting)](https://pypi.org/project/vetting/)
![pytest](https://github.com/ssdatalab/vetting/workflows/pytest/badge.svg)

## Installation

You can install `vetting` by executing the following in a terminal

```
pip install vetting
```

### Centroid testing

An example of a simple test is shown below.

![Example of simple centroid test](https://github.com/SSDataLab/vetting/raw/main/demo.png)

Here a significant offset is detected in the centroid of false positive KOI-608 during transit. The p-value for the points during transit being drawn from the same distribution as the points out of transit is low, (there is a less than 1% chance these are drawn from the same distribution). To recreate this example you can use the following script:

```python
import lightkurve as lk
from vetting import centroid_test

tpf = lk.search_targetpixelfile('KOI-608', mission='Kepler', quarter=10).download()
period, t0, dur = 25.3368592, 192.91552, 8.85/24
r = centroid_test(tpf, period, t0, dur, aperture_mask='pipeline', plot=False)
```


%package help
Summary:	Development documents and examples for vetting
Provides:	python3-vetting-doc
%description help
# vetting

**`vetting` contains simple, stand-alone Python tools for vetting transiting signals in NASA's Kepler, K2 and TESS data. `vetting` requires an installation of Python 3.8 or higher.**

[![pypi](https://img.shields.io/pypi/v/vetting)](https://pypi.org/project/vetting/)
![pytest](https://github.com/ssdatalab/vetting/workflows/pytest/badge.svg)

## Installation

You can install `vetting` by executing the following in a terminal

```
pip install vetting
```

### Centroid testing

An example of a simple test is shown below.

![Example of simple centroid test](https://github.com/SSDataLab/vetting/raw/main/demo.png)

Here a significant offset is detected in the centroid of false positive KOI-608 during transit. The p-value for the points during transit being drawn from the same distribution as the points out of transit is low, (there is a less than 1% chance these are drawn from the same distribution). To recreate this example you can use the following script:

```python
import lightkurve as lk
from vetting import centroid_test

tpf = lk.search_targetpixelfile('KOI-608', mission='Kepler', quarter=10).download()
period, t0, dur = 25.3368592, 192.91552, 8.85/24
r = centroid_test(tpf, period, t0, dur, aperture_mask='pipeline', plot=False)
```


%prep
%autosetup -n vetting-0.3

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-vetting -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3-1
- Package Spec generated