Finder_charts is a Python module to create multi-bands finder charts from image data of following sky surveys:
- DSS (DSS1 B, DSS1 R, DSS2 B, DSS2 R, DSS2 IR),
- 2MASS (J, H, K),
- Spitzer (IRAC1, IRAC2, IRAC3, IRAC4, MIPS24),
- WISE (W1, W2, W3, W4),
- UKIDSS (Y, J, H, K),
- UHS (J, K),
- VHS (Y, J, H, K),
- VVV (Z, Y, J, H, K),
- VIKING (Z, Y, J, H, K),
- Pan-STARRS (g, r, i, z, y),
- DECam (g, r, i, z, Y).
It also creates a WISE time series of epochs 2010, (2013), and 2014-2021.
All images are reprojected so that north is up and east is to the left (except for some surveys at high declination).
The create_finder_charts function only takes two mandatory arguments, RA and Dec in decimal degrees, which can be specified either as a scalar, Python sequence (list, tuple, ...), or Numpy array.
This is a minimal usage example:
from Finder_charts import create_finder_charts
create_finder_charts(16.9701886, 0.6992208)The resulting finder charts are saved to the directory given by parameter directory and automatically opened if open_file is set to True.
Catalog search results can be saved to the same directory by setting save_result_tables to True.
This creates one file per catalog search results, e.g. Finder_charts_2MASS_results_16.970189+0.699221.dat :
| _r| RAJ2000| DEJ2000|errMaj|errMin|errPA| _2MASS| Jmag|Jcmsig|e_Jmag| Jsnr| Hmag|Hcmsig|e_Hmag| Hsnr| Kmag|Kcmsig|e_Kmag| Ksnr|Qflg|Rflg|Bflg|Cflg| Ndet| prox|pxPA| pxCntr|Xflg|Aflg| Cntr|Hemis| Date|Scan| GLON| GLAT| Xscan| _tab1_36|Jpsfchi|Hpsfchi|Kpsfchi|Jstdap|e_Jstdap|Hstdap|e_Hstdap|Kstdap|e_Kstdap|edgeNS|edgeEW|edge| dup| use| opt| Dopt|PAopt| Bmag| Rmag|Nopt|extKey|scanKey|coaddKey|coadd| Opt|
|double| double| double| float| float| int| char| float| float| float| double| float| float| float| double| float| float| float| double|char|char|char|char| char| float| int| long| int| int| long| char| char| int| double| double| float| double| float| float| float| float| float| float| float| float| float| long| int|char| int| int|char| float| int|float|float| int| long| long| long| int|char|
| | deg| deg|arcsec|arcsec| deg| | mag| mag| mag| | mag| mag| mag| | mag| mag| mag| | | | | | |arcsec| deg| | | | | | | | deg| deg|arcsec| d| | | | mag| mag| mag| mag| mag| mag|arcsec|arcsec| | | | |arcsec| deg| mag| mag| | | | | | |
| null| null| null| null| null| null| null| null| null| null| null| null| null| null| null| null| null| null| null|null|null|null|null| null| null|null| null|null|null| null| null| null|null| null| null| null| null| null| null| null| null| null| null| null| null| null| null| null|null|null|null|null| null| null| null| null|null| null| null| null| null|null|
6.422 16.968425 0.698999 0.12 0.06 0 01075242+0041563 15.824 0.057 0.058 20.8 14.512 0.038 0.039 30.8 13.709 0.043 0.044 33.0 AAA 222 111 000 365555 44.1 44 1229286793 0 0 1229286809 s 2000-09-02 86 131.679 -61.893 -161.7 2451789.7336 1.13 1.19 0.70 15.898 0.099 14.673 0.086 13.682 0.023 2536 90 se 0 1 0 null null null null 0 null 66111 1520551 245 Opt
39.277 16.976971 0.707773 0.15 0.11 1 01075447+0042279 16.235 0.094 0.095 14.2 15.516 0.082 0.082 12.2 15.443 0.156 0.156 6.7 AAC 222 111 000 160606 44.1 224 1229286809 0 0 1229286793 s 2000-09-02 86 131.695 -61.883 -192.5 2451789.7336 1.23 0.88 1.66 16.086 0.167 15.509 0.210 15.105 0.216 2568 59 se 1 1 0 null null null null 0 null 66111 1520551 245 Opt
44.163 16.981315 0.694039 0.30 0.25 5 01075551+0041385 16.450 0.093 0.094 11.7 15.878 0.142 0.142 8.8 15.739 0.223 0.223 5.1 ABD 222 111 000 060605 49.7 291 1229286809 0 0 1229286817 s 2000-09-02 86 131.708 -61.896 -208.1 2451789.7336 0.93 0.75 0.91 16.591 0.263 15.879 0.285 15.761 0.258 2518 44 se 1 1 U 0.4 266 18.10 17.40 1 null 66111 1520551 245 Opt
The Python Standard Library, numpy, matplotlib, pillow (PIL fork), requests, astropy, astroquery, reproject and tqdm.
Finder_charts has been tested with following dependency versions:
numpy==1.26.4
matplotlib==3.9.2
pillow==10.4.0
requests==2.32.3
astropy==6.1.3
astroquery==0.4.10
reproject==0.14.0
tqdm==4.66.5
The code can be installed as follows:
git clone https://github.com/fkiwy/Finder_charts.git
cd Finder_charts
python setup.py install
ra: right ascension in decimal degrees (type: float)dec: declination in decimal degrees (type: float)img_size: image size in arcseconds (type: int, default: 100)overlays: whether to plot catalog overlays (type: bool, default: False)overlay_color: catalog overlay color (type: str, default: 'red')dss: whether to create DSS image series (type: bool, default: True)twomass: whether to create 2MASS image series (type: bool, default: True)spitzer: whether to create Spitzer image series (type: bool, default: True)wise: whether to create WISE image series (type: bool, default: True)ukidss: whether to create UKIDSS image series (type: bool, default: True)uhs: whether to create UHS image series (type: bool, default: True)vhs: whether to create VHS image series (type: bool, default: True)vvv: whether to create VVV image series (type: bool, default: True)viking: whether to create VIKING image series (type: bool, default: True)ps1: whether to create Pan-STARRS image series (type: bool, default: True)decam: whether to create DECam image series (type: bool, default: True)neowise: whether to create WISE time series (type: bool, default: True)neowise_contrast: WISE time series contrast (type: int, default: 3)gaia_images: whether to create simulated Gaia image series (type: bool, default: False)gaia_entries: whether to plot Gaia catalog overlays (type: bool, default: False)gaia_pm_vectors: whether to plot Gaia porper motion vectors (type: bool, default: False)gaia_pm_years: the number of years to scale the proper motion vectors (type: int, default: 10)gaia_color: Gaia overlay color (type: str, default: 'green')targets: a list of targets to be plotted on the specified image series/survey (type: list of Finder_charts.Target objects, default: None)
targets = [
Target(catalog='2MASS', epoch=2000.5, ra=0.123, dec=0.123, marker_size=10, marker_color='red', survey=Survey.TWO_MASS),
Target(catalog='AllWISE', epoch=2010.6, ra=1.234, dec=1.234, marker_size=9, marker_color='blue', survey=Survey.ALLWISE),
...
]where catalog is the catalog label and survey is of type Finder_charts.Survey
pmra: proper motion in RA (mas/yr) used to propagate the crosshair position to the appropriate survey epoch (type: float, default: None)pmdec: proper motion in declination (mas/yr) used to propagate the crosshair position to the appropriate survey epoch (type: float, default: None)ref_epoch: epoch ofraanddecused to propagate the crosshair position to the appropriate survey epoch (type: astropy.time.Time, default: None)crosshair_type: the shape of the crosshair (type: Finder_charts.Crosshair, default: Crosshair.CIRCLE_DOT)propagate_gaia_positions: whether to propagate the Gaia catalog positions to the appropriate survey epoch (type: bool, default: False)chrono_order: whether to plot image series in chronological order (type: bool, default: True)object_info: whether to plot object information like coordinates, etc. (type: bool, default: True)directory: directory where the finder charts should be saved (type: str, default: tempfile.gettempdir())cache: whether to cache the downloaded files (type: bool, default: True)show_progress: whether to show the file download progress (type: bool, default: True)timeout: timeout for remote requests in seconds (type: int, default: 300)open_pdf: deprecated, replaced byopen_fileopen_file: whether to open the saved finder charts automatically (type: bool, default: True)file_format: output file format: pdf, png, eps, etc. (type: str, default: 'pdf')save_result_tables: whether to save the catalog search result tables to the specified directory (type: bool, default: False)result_tables_format: catalog search result tables output format (type: str, default: 'ipac')result_tables_extension: catalog search result tables file extension (type: str, default: 'dat')
Here's a more advanced example with propagated crosshairs and Gaia positions plus proper motion vectors:
from Finder_charts import create_finder_charts, Crosshair, Survey, Target
from astropy.time import Time
import tempfile
ra, dec = 152.9226066, 28.7632385
pmra, pmdec = -124.825, -713.244
ref_epoch = Time(2016.0, format='jyear')
create_finder_charts(ra, dec, img_size=100, overlays=True, overlay_color='red', dss=True, twomass=True, spitzer=True, wise=True,
ukidss=True, uhs=True, vhs=True, vvv=True, viking=True, ps1=True, decam=True, neowise=True, neowise_contrast=5,
gaia_images=True, gaia_entries=True, gaia_pm_vectors=True, gaia_pm_years=50, gaia_color='green', targets=None,
pmra=pmra, pmdec=pmdec, ref_epoch=ref_epoch, crosshair_type=Crosshair.CROSS_NO_CENTER, propagate_gaia_positions=True,
chrono_order=True, object_info=True, directory=tempfile.gettempdir(), cache=True, show_progress=True, timeout=300,
open_file=True, file_format='png', save_result_tables=True, result_tables_format='ipac', result_tables_extension='dat')