Metadata-Version: 2.4
Name: tess-asteroids
Version: 1.4.1
Summary: Create TPFs and LCs for solar system asteroids observed by NASA's TESS mission.
License: MIT
License-File: LICENSE
Author: Amy Tuson
Author-email: amy.l.tuson@nasa.gov
Requires-Python: >=3.9,<3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: astropy (>=5.3.4,<6.0.0)
Requires-Dist: fbpca (>=1.0,<2.0)
Requires-Dist: lkprf (>=1.1.1,<2.0.0)
Requires-Dist: lkspacecraft (>=1.0.5,<2.0.0)
Requires-Dist: matplotlib (>=3.9,<4.0)
Requires-Dist: numpy (>=1.26.4,<2.0.0)
Requires-Dist: pandas (>=2.0,<3.0)
Requires-Dist: patsy (>=0.5.6,<0.6.0)
Requires-Dist: tess-ephem (>=0.6.3,<0.7.0)
Requires-Dist: tesscube (>=1.2,<2.0)
Requires-Dist: tesswcs (>=1.7.0,<2.0.0)
Requires-Dist: tqdm (>=4.67.1,<5.0.0)
Description-Content-Type: text/markdown

[![pytest](https://github.com/altuson/tess-asteroids/actions/workflows/test.yml/badge.svg)](https://github.com/altuson/tess-asteroids/actions/workflows/test.yml)
[![mypy](https://github.com/altuson/tess-asteroids/actions/workflows/mypy.yml/badge.svg)](https://github.com/altuson/tess-asteroids/actions/workflows/mypy.yml/)
[![ruff](https://github.com/altuson/tess-asteroids/actions/workflows/ruff.yml/badge.svg)](https://github.com/altuson/tess-asteroids/actions/workflows/ruff.yml)
[![PyPI](https://img.shields.io/pypi/v/tess-asteroids.svg)](https://pypi.python.org/pypi/tess-asteroids)
[![Generic badge](https://img.shields.io/badge/documentation-live-blue.svg)](https://altuson.github.io/tess-asteroids/)
[![DOI](https://zenodo.org/badge/848357424.svg)](https://doi.org/10.5281/zenodo.15882329)

# tess-asteroids

`tess-asteroids` allows you to make Target Pixel Files (TPFs) and Light Curve Files (LCFs) for any object that moves through the TESS field of view, for example solar system asteroids, comets or minor planets.

See the full documentation, including tutorials, [here](https://altuson.github.io/tess-asteroids/). 

## Installation

The easiest way to install `tess-asteroids` and all of its dependencies is to run the following command in a terminal window:

```bash
pip install tess-asteroids
```

### `lkspacecraft` dependency

`tess-asteroids` uses `lkspacecraft` to derive barycentric time corrections (see [below](https://github.com/altuson/tess-asteroids?tab=readme-ov-file#barycentric-time-correction)). **The first time you run `lkspacecraft` it will download a set of files (the SPICE kernels for TESS). This will take approximately 5 minutes, depending on your internet connection, and the total file volume will be about 1GB.** The files will be cached once they are downloaded and if a new version of any file becomes available they will be automatically retrieved.

## Quickstart

You can easily make and save a TPF and LCF for any object in the JPL Small-Body Database that has been observed by TESS. For example,

```python
from tess_asteroids import MovingTPF

# Initialise MovingTPF for asteroid 1980 VR1 in TESS sector 1
target = MovingTPF.from_name("1980 VR1", sector=1, camera=1, ccd=1)

# Make TPF and save to file (tess-1980VR1-s0001-1-1-shape11x11-moving_tp.fits)
target.make_tpf(save=True)

# Make LC and save to file (tess-1980VR1-s0001-1-1-shape11x11_lc.fits)
target.make_lc(save=True)
```

<p align="center">
  <img alt="Example TPF" src="https://github.com/altuson/tess-asteroids/blob/main/docs/tess-1980VR1-s0001-1-1-shape11x11-moving_tp.gif?raw=true" width="43%">
&nbsp; &nbsp; &nbsp; &nbsp;
  <img alt="Example LC" src="https://github.com/altuson/tess-asteroids/blob/main/docs/tess-1980VR1-s0001-1-1-shape11x11_lc.png?raw=true" width="52%">
</p>

## Tutorial

### Making a TPF

You can create a TPF that tracks a moving object from the JPL Small-Body Database by providing the object's name and TESS sector:

```python
from tess_asteroids import MovingTPF

# Initialise MovingTPF for asteroid 1998 YT6 in TESS sector 6
target = MovingTPF.from_name("1998 YT6", sector=6)

# Make TPF and save to file (tess-1998YT6-s0006-1-1-shape11x11-moving_tp.fits)
target.make_tpf(save=True)
```

The `make_tpf()` function is retrieving and reshaping the FFI data, performing a background correction, computing an aperture and saving a SPOC-like TPF. There are a few optional parameters in the `make_tpf()` function. This includes:

- `shape` controls the shape (nrows,ncols) of the TPF. Default : (11,11).
- `bg_method` defines the method used to correct the background flux. Default: `linear_model`.
- `ap_method` defines the method used to create the aperture. Default: `prf`.
- `save` determines whether or not the TPF will be saved as a FITS file. Default: `False`.
- `outdir` is the directory where the TPF will be saved. Note, the directory is not automatically created.
- `file_name` is the name the TPF will be saved with. If one is not given, a default name will be generated.

These settings can be changed as follows:

```python
# Make TPF and save to file - change default settings
target.make_tpf(shape=(20,10), bg_method="rolling", ap_method="threshold", save=True, file_name="test.fits", outdir="movingTPF")
```

A TPF can only be created for a single combination of sector/camera/CCD at a time. If the object crosses multiple cameras or CCDs during a sector, then the camera/CCD must also be specified when initialising `MovingTPF()`:

```python
# Initialise MovingTPF for asteroid 2013 OS3 in TESS sector 20
target = MovingTPF.from_name("2013 OS3", sector=20, camera=2, ccd=3)
```

You can also initialise `MovingTPF()` with your own ephemeris:

```python
from tess_asteroids import MovingTPF
import numpy as np
import pandas as pd

# Create an artificial ephemeris
time = np.linspace(1790.5, 1795.5, 100)
ephem = pd.DataFrame({
            "time": time,
            "sector": np.full(len(time), 18),
            "camera": np.full(len(time), 3),
            "ccd": np.full(len(time), 2),
            "column": np.linspace(500, 600, len(time)),
            "row": np.linspace(1000, 900, len(time)),
        })

# Initialise MovingTPF
target = MovingTPF("example", ephem, barycentric=False)

# Make TPF, but do not save to file
target.make_tpf()
```

A few things to note about the format of the ephemeris:

- `time` must have format (JD - 2457000) in the TDB scale. See explanation of the `barycentric` parameter [below](https://github.com/altuson/tess-asteroids?tab=readme-ov-file#time).
- `sector`, `camera`, `ccd` must each have one unique value.
- `column`, `row` must be one-indexed, where the lower left pixel of the FFI has value (1,1).

### Animating the TPF

`animate_tpf()` is a built-in helper function to plot the TPF and aperture over time:

```python
from tess_asteroids import MovingTPF

# Initialise MovingTPF for asteroid 1998 YT6 in TESS sector 6
target = MovingTPF.from_name("1998 YT6", sector=6)

# Make TPF, but do not save to file
target.make_tpf()

# Animate TPF and save to file (tess-1998YT6-s0006-1-1-shape11x11-moving_tp.gif)
target.animate_tpf(save=True)
```

### Making a LC

You can extract a LC from the TPF using aperture photometry and/or PSF photometry. For example:

```python
from tess_asteroids import MovingTPF

# Initialise MovingTPF for asteroid 1998 YT6 in TESS sector 6
target = MovingTPF.from_name("1998 YT6", sector=6)

# Make TPF and save to file (tess-1998YT6-s0006-1-1-shape11x11-moving_tp.fits)
target.make_tpf(save=True)

# Make LC and save to file (tess-1998YT6-s0006-1-1-shape11x11_lc.fits)
target.make_lc(save=True)
```

The `make_lc()` function extracts the lightcurve, creates a quality mask and optionally saves the LCF. There are a few optional parameters in the `make_lc()` function. This includes:

- `method` defines the method used to perform photometry. Default: `aperture`.
- `save` determines whether or not the LCF will be saved as a FITS file. Default: `False`.
- `outdir` is the directory where the LCF will be saved. Note, the directory is not automatically created.
- `file_name` is the name the LCF will be saved with. If one is not given, a default name will be generated.

### Compatibility with `lightkurve`

The TPFs and LCFs that get created by `tess-asteroids` can be opened with `lightkurve`, as follows:

```python
import lightkurve as lk

# Read in TPF and LCF, without removing bad cadences
tpf = lk.TessTargetPixelFile("tess-1998YT6-s0006-1-1-shape11x11-moving_tp.fits", quality_bitmask="none")
lc = lk.io.tess.read_tess_lightcurve("tess-1998YT6-s0006-1-1-shape11x11_lc.fits", quality_bitmask="none")

# Plot TPF and aperture for a single frame
tpf.plot(aperture_mask=tpf.hdu[3].data["APERTURE"][200], frame=200)

# Plot LC
lc.plot()
```

## Time

When you initialise `MovingTPF()`, the parameter `barycentric` is defined as follows:

- `True` (default): this means the input `time` must be in TDB measured **at the solar system barycenter**. This is the case for the TSTART/TSTOP keywords in SPOC FFI headers and the TIME column in SPOC TPFs and LCFs.
- `False`: this means the input `time` must be in TDB measured **at the spacecraft**. This can be recovered from the SPOC data products: for FFIs subtract the header keyword BARYCORR from TSTART/TSTOP and for TPFs/LCFs subtract the TIMECORR column from the TIME column.

When `MovingTPF()` is initialised `from_name()`, the `barycentric` parameter is handled internally. As a user, you will only need to consider the `barycentric` parameter if you are inputting a custom ephemeris. 

For more information about time scales, see the `astropy` [documentation](https://docs.astropy.org/en/stable/time/index.html#time-scale).

### Barycentric time correction

The barycentric time correction derived by SPOC (BARYCORR) is used to transform the time at the spacecraft into the time at the solar system barycenter. This correction is calculated at the center of each FFI (i.e. one correction for each CCD) but, in reality, the correction depends upon RA and Dec. Therefore, within `tess-asteroids` we use `lkspacecraft` to re-derive the barycentric time correction based upon the position of the moving target. In the output TPFs and LCFs, you will see columns called ORIGINAL_TIME (FFI timestamp in TDB at barycenter, as derived by SPOC), ORIGINAL_TIMECORR (correction to transform time at spacecraft into time at barycenter, as derived by SPOC), TIME (re-derived time in TDB at barycenter) and TIMECORR (re-derived time correction).

## Understanding the TPF and LCF

The TPF has four HDUs: 

- "PRIMARY" - a primary HDU containing only a header.
- "PIXELS" - a table with the same columns as a SPOC TPF. Note that "POS_CORR1" and "POS_CORR2" are defined as the offset between the center of the TPF and the expected position of the moving object given the input ephemeris. 
- "APERTURE" - an image HDU containing the average aperture across all times.
- "EXTRAS" - a table HDU containing columns not found in a SPOC TPF. This includes "RA_PRED"/"DEC_PRED" (expected position of target in world coordinates), "CORNER1"/"CORNER2" (original FFI column/row of the lower-left pixel in the TPF), "PIXEL_QUALITY" (3D pixel quality mask identifying e.g. strap columns, non-science pixels and saturation), "APERTURE" (aperture as a function of time) and "ORIGINAL_TIME"/"ORIGINAL_TIMECORR" (time and barycentric correction derived by SPOC).

The LCF has two or three HDUs (depending upon which lightcurves you created): 

- "PRIMARY" - a primary HDU containing only a header.
- "LIGHTCURVE_AP" - a table HDU containing the aperture photomety light curve, with columns including "TIME" (timestamps in BTJD), "FLUX"/"FLUX_ERR" (flux and error from aperture photometry) and "TESSMAG"/"TESSMAG_ERR" (measured TESS magnitude and error).
- "LIGHTCURVE_PSF" - a table HDU containing the PSF photomety light curve, with columns including "TIME" (timestamps in BTJD), "FLUX"/"FLUX_ERR" (flux and error from PSF photometry) and "TESSMAG"/"TESSMAG_ERR" (measured TESS magnitude and error).

## Citation

If you make use of `tess-asteroids` in your work, please cite our software using the version-specific DOI from [Zenodo](https://zenodo.org/records/15882329). You can generate a BibTex citation using Zenodo.
