For clening ATLAS light curves
Project description
ATLAS Object
Package for "cleaning" ATLAS light curves by doing variance-weighted rolling mean or sigma clipping.
Conda environment
It is recommended to create an environment before installing ATLAS Object:
conda create -n atlas pip
conda activate atlas
pip install atlas_object
Usage example
First, make sure that your data has the same output format as given by the ATLAS API. One can easily plot the light curves:
import numpy as np
import matplotlib.pyplot as plt
import atlas_object as ao
# let's download a test file
ao.utils.download_test_data()
lc_file = 'test_lc.csv' # downloaded ATLAS forced photometry file
obj = ao.atlas_object(lc_file)
obj.plot_lcs(58600, 58800) # the user can choose the x-axis range
The user can choose to do a sigma clipping within the rolling mean:
sigclip_kwargs = {'n_sigma':3}
obj.rolling(3, center=False, sigma_clip=True, **sigclip_kwargs)
obj.plot_lcs(58600, 58800)
sigclip_kwargs
needs to have the same input parameters as obj.sigma_clip()
. All the changes occur on obj.lcs
, while obj.init_lcs
contains the initial light curves.
The user also has access to the indices of the data removed by the sigma clipping, for each band (e.g. obj.lcs.o.indices
):
mags = np.empty(0)
fig, ax = plt.subplots(figsize=(8, 6))
for filt in 'co':
lc = obj.init_lcs[filt]
time = lc.time
mag = lc.mag
mag_err = lc.mag_err
mask = ~obj.lcs[filt].indices
ax.errorbar(time, mag, mag_err,
fmt='o', c=lc.color, mec='k',
alpha=0.2)
ax.errorbar(time[mask], mag[mask], mag_err[mask],
fmt='o', label=filt, c=lc.color, mec='k'
)
mags = np.r_[mags, mag]
ax.set_ylabel('Appartent Magnitude', fontsize=18)
ax.set_xlabel('MJD', fontsize=18)
ax.tick_params(labelsize=18)
ax.set_ylim(mags.min()-0.5, mags.max()+0.5)
ax.set_xlim(58600, 58800)
ax.invert_yaxis()
ax.legend(fontsize=18)
plt.show()
ATLAS forced photometry
For information about public ATLAS forced photometry, check: https://fallingstar-data.com/forcedphot/. For specific information about the data, check: https://fallingstar-data.com/forcedphot/resultdesc/.
Contributing
To contribute, either open an issue or send a pull request (prefered option). You can also contact me directly.
Citing ATLAS Object
If you make use of ATLAS Object, please cite:
coming soon...
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for ATLAS_Object-0.1.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7473781ace454f4acf3ed74a99bcb65d86b5f21d795d14b39304936976863354 |
|
MD5 | a6f9bd51454bbc6a5fac71f9946bb7ab |
|
BLAKE2b-256 | 7a80c26680848a123fec50a5b9cbc71a8150e164ebccd8f37e59428817b63f72 |