A package for the gathering and plotting of astronomical data.
Project description
Toolkit
Collection of tools for data fetching, plotting and analysis
Installation
- With pip, the package can be installed using:
pip install AstroToolkit
- Once this has finished, you should navigate to the package location. This should be in a '.../Lib/site-packages/AstroToolkit' folder where ... is your python install location. If you wish to find this, you can can run the following commands:
python
from AstroToolkit.Tools import getztfanalysis
getztfanalysis(source=6050296829033196032)
As long as there are no issues with ZTF, this should return an error which will include the file path.
-
Navigate to this file in any terminal that can access your python environment, and run either buildwin.bat (windows) or build.sh (linux).
-
Re-run the above python commands and the error should no longer appear. The package is now fully installed.
NOTE: See README.txt (Linux) or README - Windows.txt (Windows) in the above directory for any additional dependencies.
Usage
1. Bokeh
The central module within which all functions are found is toolkit.py.
NOTE: In this version, Toolkit has been rewritten to use Bokeh as its plotting library. The official documentation can be found at https://bokeh.org/. All plots will be saved as a static .html file, which can be opened in the browser (or from a python script using:
show(plot)
where 'plot' is the name of the parameter that the plot is assigned to.
2. Importing Tools
All Tools in the package are located in AstroTools.Tools
3. Input
All Toolkit functions require atleast one input from:
- source = ...
where source is a Gaia source_id (string)
- pos = ...
where pos is a 1D list with two elements: [ra,dec] in units of degrees
For example:
when trying to obtain a panstarrs image, there are therefore two options:
getpanstarrsimage(source=...)
and
getpanstarrsimage(pos=...)
The key difference between these input formats is the way that proper motion is handled. Given coordinates (pos), the results retrieved by any Toolkit function are simply the raw data obtained from that location in Gaia's epoch of Jan 2016, with no proper motion correction. The one exception for this is detection overlays in imaging functions, as these are still possible without an initial reference proper motion (i.e. a specific object in Gaia).
In contrast to this, any Toolkit functions called using a Gaia source_id as input will correct for any proper motion of that object between the time at which the data was taken and Gaia's epoch of Jan 2016, pre-execution. An example of this difference is seen in imaging functions for objects with a large proper motion. Here, using a source as input will result in an image that is centred on the object, regardless of the magnitude of its proper motion.
Using a position as input may still produce an image which contains the object, but it is unlikely to be centred as the focus of the image has not accounted for the proper motion of the object.
Note: As the functions need to sort between the different input formats, explicit declaration is required, i.e.:
getpanstarrsimage(6050296829033196032)
will fail.
Instead, use:
getpanstarrsimage(source=6050296829033196032)
Toolkit Functions
Imaging functions
These functions produce images of objects from supported surveys.
Note: When not using source mode, some detections can be missing for high proper motion objects. When using a source_id as input, this is no longer an issue as 'adaptive' proper motion correction is used. Here, the search radius for detections is increased to include the maximum distance that the object could have travelled in the gap between the epoch of the image and the epoch of the detection coordinates so that it is still picked up.
1. getpanstarrsimage
Retrieves Pan-STARRS image
getpanstarrsimage(source=None,pos=None,image_size=60,band='g',overlay=['gaia'])
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
image_size = integer
= size of image in arcseconds (maximum = 1500).
band = string
= list of all filters to include (e.g. for all filters, use band='grizy').
overlay = 1D tuple of strings
= for example, for Gaia and ZTF overlays, use overlay=['gaia','ztf']. Note, only supported for fits output_format.
returns: Bokeh figure or None (if no data retrieved).
2. getskymapperimage
getskymapperimage(source=None,pos=None,image_size=60,band='g',output_format='fits',contrast=50,overlay=['gaia'],ax=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
image_size = integer
= size of image in arcseconds (maximum = 600).
band = string
= string of filter to use (supported filters are: 'g','r','i','z','u','v'
overlay = 1D tuple of strings
= for example, for Gaia and ZTF overlays, use overlay=['gaia','ztf']. Note, only supported for fits output_format.
returns: Bokeh figure or None (if no data retrieved).
3. getdssimage
getdssimage(source=None,pos=None,image_size=60,contrast=50,overlay=['gaia'],ax=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
image_size = integer
= size of image in arcseconds (maximum = 600).
overlay = 1D tuple of strings
= for example, for Gaia and ZTF overlays, use overlay=['gaia','ztf']. Note, only supported for fits output_format.
returns: Bokeh figure or None (if no data retrieved).
Data queries
These functions return all raw data retrieved from various surveys.
1. panstarrsquery
panstarrsquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
2. skymapperquery
skymapperquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
3. gaiaquery
gaiaquery(source=None,pos=None,radius=3,catalogue='dr3')
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
catalogue = string
= 'dr2' or 'dr3'. Determines the data release from which the data is retrieved.
returns: pandas dataframe or None (if no data retrieved).
4. galexquery
galexquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
5. rosatquery
rosatquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
6. ztfquery
ztfquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
7. sdssquery
sdssquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
8. wisequery
wisequery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
9. twomassquery
twomassquery(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
Photometry queries
These functions return only the photometry retrieved from various surveys.
1. getpanstarrsphot
getpanstarrsphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
2. getskymapperphot
getskymapperphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
3. getgaiaphot
getgaiaphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
4. getgalexphot
getgalexphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
5. getsdssphot
getsdssphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
6. getwisephot
getwisephot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
4. gettwomassphot
gettwomassphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: pandas dataframe or None (if no data retrieved).
Photometry bulk search
This function returns all retrieved photometry for all supported surveys for a given object.
1. getbulkphot
getbulkphot(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: dictionary in format: 'survey':pandas dataframe or None (if no data retrieved).
Timeseries queries
These functions create light curves from supported surveys.
1. getztflc
getztflc(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: Bokeh figure or None (if no data retrieved).
SED queries
This function creates a spectral energy distribution from all supported surveys.
1. getsed
getsed(source=None,pos=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
returns: matplotlib axis or None (if no data retrieved).
Spectra queries
These functions retrieve spectra from supported surveys.
1. getsdssspectrum
getsdssspectrum(source=None,pos=None,radius=3)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
returns: Bokeh figure or None (if no data retrieved).
HR diagram function
1. gethrd
gethrd(source=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
returns: Bokeh figure or None (if no data retrieved).
Timeseries analysis tools
1. getztfanalysis
Allows for timeseries analysis of ZTF data for a given object.
getztfanalysis(source=None,pos=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
2. getps
Produces a power spectrum using ZTF data for a given object.
getps(source=None,pos=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
returns: Bokeh figure or None (if no data retrieved).
Miscellaneous tools
1. correctPM
correctPM(input,target,ra,dec,pmra,pmdec)
where:
input = 1D tuple of integers in form [year, month]
= current epoch of coordinates
output = 1D tuple of integers in form [year, month]
= target epoch of coordinates
ra = float
= right ascension of object in degrees
dec = float
= declination of object in degrees
pmra = float
= right ascension component of proper motion in milli-arcseconds/year
pmdec = float
= declination component of proper motion in milli-arcseconds/year
returns: ra (float), dec (float).
2. getgaiacoords
getgaiacoords(source,catalogue='dr3')
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
catalogue = string
= 'dr2' or 'dr3'. Determines the data release from which the data is retrieved.
returns: 1D tuple of floats in format [ra,dec] or None (if no data retrieved).
3. getgaiasource
getgaiasource(pos,radius=3,catalogue='dr3')
where:
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
radius = integer
= search radius of query in arcseconds.
catalogue = string
= 'dr2' or 'dr3'. Determines the data release from which the data is retrieved.
returns: string or None (if no data retrieved)
4. getsources
getsources(file_name)
where:
file_name = string
= .fits file containing a column 'source_id' of Gaia source IDs
returns: list of source_id's.
5. getpositions
getpositions(file_name)
where:
file_name = string
= .fits file containing two columns 'ra' and 'dec'
returns: list of 'pos' objects, i.e. a list of lists with each 'pos' = [ra,dec].
Datapage functions
This function produces a datapage using all available data for an object, given its position or Gaia source_id.
1. getdatapage
getdatapage(source=None,pos=None,prefs=None)
where:
source = integer/string
= Gaia source_id (e.g. 6050296829033196032).
pos = 1D tuple of two integers
= [ra,dec], object coordinates in degrees.
prefs = dictionary
= preferences for datapage functionality (see below)
Datapage elements
1 - 1 | 2 - 2 | 3 - 3
1 - 1 | 2 - 2 | 4 - 4
5 | 6 - 6 - 6 | 7 - 7
where:
1: Image with survey preference according to: PanSTARRS > SkyMapper > DSS
2: HR Diagram
3: SED plot with any photometry obtained from all supported surveys
4: Spectrum
5: SIMBAD/Vizier Buttons
6: ZTF Lightcurves
7: Power Spectrum
Datapage preferences
The argument 'prefs' in the above allows for the user to modify various aspects of datapages. It takes the form of a dictionary, i.e.:
prefs={}
with the below accepted parameters:
band : string
= string containing bands to use for image datapage element (see format and accepted filters in imaging functions above). Default = 'g'.
overlay : list
= list of overlays to use in image datapage element (see below for suppported overlays). Default = ['gaia'].
image_size : integer
= size of image datapage element in arcseconds. Default = 20".
lc_radius : integer
= radius in arcseconds to use when looking for avaialble lightcurve data. Default = 3".
sed_radius : integer
= radius in arcseconds to use when looking for available photometry for use in SED datapage element. Default = 3".
spec_radius : integer
= radius in arcseconds to use when looking for available specta. Default = 3".
simbad_radius : integer
= radius to use in a SIMBAD query when 'SIMBAD' button is clicked. Default = 3".
vizier_radius : integer
= provides an override to the radius used in a Vizier query when the 'Vizier' button is clicked. Default = See below.
NOTE: by default, the Vizier radius scales with proper motion (i.e. adpative pm correction, see above) to include all images in the image datapage element. I.e. if the image_size is set to 30, then the Vizier radius will likely be approximately 30", but will be scaled to include possible proper motion of the object.
grid_size : integer
= size of overall datapage (i.e. every datapage element scales with this parameter). Default = 300.
Currently supported overlays
- gaia (default)
- galex_nuv
- galex_fuv
- ztf
- rosat
Note: all overlays are proper motion corrected except rosat in all imaging functions. ZTF detections are particularly expensive, but can be useful in 'tracking' high proper motion objects through time.
TestFile
To run a file that tests all functions, use:
from AstroToolkit.Miscellaneous import TestFile
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 AstroToolkit-1.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b518a21f45afac6e6e780a1a43216ae99ac0af89370a825545f93bd950a8b497 |
|
MD5 | 1d17cbc6becd57d044b93be6133dc35a |
|
BLAKE2b-256 | ea9c0003cd9cc766a1979a1c2d4cc57d9a6569df5e5b9961e30e2989b3d63cc9 |