Galaxy Morphology with SDSS and Astrocut

Galaxy Morphology with SDSS and Astrocut#

Learning Goals#

By the end of this tutorial, you will:

Understand how to use astroquery.mast to download the SDSS Legacy Imaging Survey Data from the MAST archive.
Utilize astrocut to create colorized cropped images from 12 different galaxies.
Construct a Hubble Tuning Fork Diagram from the cropped images to learn about galaxy morphology.

Table of Contents#

Introduction
Imports
Accessing SDSS Legacy Imaging Survey Data from MAST
- Querying SDSS Legacy Imaging Survey
- Gathering Galaxies from the SDSS Legacy Imaging Survey
  - Elliptical Galaxies
  - Lenticular Galaxies
  - Spiral Galaxies
  - Barred Spiral Galaxies
  - Irregular Galaxies
- Downloading Data Products
Creating the Cutout Images Using Astrocut
Making the Hubble Tuning Fork Diagram
End of Tutorial
Exercise
Exercise Solution
Additional Resources
Citations
About this Notebook

Introduction#

In the early 1900s, most astronomers believed objects such as the Andromeda galaxy were nebulous clouds within our galaxy. In 1923, Edwin Hubble proved Andromeda was outside the Milky Way using the period-luminosity relationship with Cepheid variables [2]. Once Hubble discovered most “nebulae” visible in the sky were actually galaxies, he created a classification scheme known as the Hubble Tuning Fork, or the Hubble Sequence. Hubble initially separated galaxies into two main groups: elliptical galaxies and spiral galaxies. Elliptical galaxies lack spiral arms, but are ellipses in shape. Hubble classified them by their ellipticity; the more elongated the galaxy, the higher its classification number (i.e. E0 to E7).

Spiral galaxies, which have prominent spiral arms, were further divided into two types based on the presence of a central bar: barred spirals (with a bar) and normal spirals (without). Both types were then categorized as early, intermediate, or late, depending on how tightly wound their arms were. Galaxies that lacked both a central nucleus and spiral structure were classified as “irregular” [3].

Hubble initially proposed that galaxies evolved from left to right on his tuning fork diagram, starting at E0 ellipticals and ending at late-type spiral/barred spiral galaxies. However, we now know this to be incorrect! Despite this, the Hubble Sequence remains a widely used tool for galaxy morphological classification [1].

In this notebook, we’ll construct our own Hubble Tuning Fork Diagram based on this classification scheme using imaging data from the SDSS Legacy Imaging Survey. We can utilize the Astrocut package to crop selected fields and generate color cutouts of various galaxies for our diagram.

Imports#

The main packages and their use-cases in this tutorial are as follows:

numpy to handle array functions
matplotlib.pyplot for plotting data
matplotlib.image to handle .png images
astroquery.mast.Observations to access SDSS data from MAST
astrocut.FITSCutout to mosaic images
astropy for handling FITS files
astropy.table.vstack for combining Astropy tables
warnings to suppress FITS warnings
bz2 to decompress the data files

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from astroquery.mast import Observations
from astrocut import FITSCutout
import astropy
from astropy.table import vstack
import warnings
import bz2

If you’re not sure if you have the required versions of packages installed on your device, you can run the following cell:

with open("requirements.txt") as f:
    print(f"Required packages for this notebook:\n{f.read()}")

Required packages for this notebook:
numpy >= 1.26.4
matplotlib >= 3.9.1
astroquery >= 0.4.9
astropy >= 5.3
astrocut >= 1.0.1

To ensure these requirements are installed, you can run the following command in the terminal:

pip install -r requirements.txt

Accessing SDSS Legacy Imaging Survey Data from MAST#

The Mikulski Archive for Space Telescopes (MAST) hosts a large array of data from several telescope missions. In this tutorial, we will be specifically focusing on data from the Sloan Digital Sky Survey’s (SDSS) Imaging Survey.

The SDSS Legacy Imaging Survey was the first SDSS survey completed! Beginning in 1998, the SDSS Legacy Imaging Survey captured around 35,000 square degrees of images until 2009, which covers about one-third of the whole sky. To do this, the survey took millions of 10 by 13 arcminute pictures (called “fields”). Not only does the SDSS Legacy Imaging Survey data at MAST provide users with preview images in .jpg format, but it also has photometric data in all five broad band SDSS filters (u, g, r, i, and z). For more information about the data and products from the SDSS Legacy Imaging Survey, you can check out the SDSS Imaging Archive Manual.

Querying SDSS Legacy Imaging Survey#

You can query data from MAST using the website portal. You can also query MAST data in Python using the module astroquery.mast!

We can query all of the SDSS Legacy Imaging data using the Observations.query_criteria() function with the parameter provenance_name = "SDSS Legacy Imaging". Since there is a large amount of data in the SDSS Legacy Imaging archive, we can display the first 10 results using the pagesize parameter as well as the page parameter.

# Querying SDSS Legacy Imaging
imaging_data = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging", pagesize=10, page=1
)

# Display first 10 entries
imaging_data

Table masked=True length=10

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str198	str61	str61	str6	bool	float64	str9	str9
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	005973-4-0047	FIELD	sdss_image_005973-4-0047	174.229442517	-3.71090674527	image	SDSS Collaboration	3	53741.47707361111	53741.48101455389	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 174.2883643778937 -3.8370902845458192 174.09108107630817 -3.7279354542798657 174.17063384071784 -3.584772619524905 174.3678949976759 -3.6939097621482793 174.2883643778937 -3.8370902845458192	mast:SDSS/sdss/imaging/5973/4/47/frame-irg-005973-4-0047.jpg	mast:SDSS/sdss/imaging/5973/4/47/photoObj-005973-4-0047.fits	PUBLIC	False	nan	295513881	874391015
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	001462-1-0126	FIELD	sdss_image_001462-1-0126	144.275209514	0.741253271781	image	SDSS Collaboration	3	51669.18672048611	51669.19066177611	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 144.19658829938143 0.6263566454578132 144.19021788017662 0.8513235009682893 144.35383791652822 0.8560386018700294 144.36020003080324 0.6310715111882993 144.19658829938143 0.6263566454578132	mast:SDSS/sdss/imaging/1462/1/126/frame-irg-001462-1-0126.jpg	mast:SDSS/sdss/imaging/1462/1/126/photoObj-001462-1-0126.fits	PUBLIC	False	nan	295513901	874391051
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	002589-1-0103	FIELD	sdss_image_002589-1-0103	30.6386361561	-0.944229797667	image	SDSS Collaboration	3	52173.31714189815	52173.321082609444	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 30.556815019164613 -1.0568566677447302 30.5567540900602 -0.831785879001948 30.720452026468934 -0.8317109537235243 30.7205235541735 -1.0567817393486545 30.556815019164613 -1.0568566677447302	mast:SDSS/sdss/imaging/2589/1/103/frame-irg-002589-1-0103.jpg	mast:SDSS/sdss/imaging/2589/1/103/photoObj-002589-1-0103.fits	PUBLIC	False	nan	295513908	874391076
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	001013-1-0095	FIELD	sdss_image_001013-1-0095	70.7719214022	-1.04767931483	image	SDSS Collaboration	3	51459.480099305554	51459.484040479816	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 70.69004600918034 -1.1602654120268343 70.69010156512687 -0.9351905477520949 70.85379088960994 -0.9352010321171098 70.85374709332649 -1.1602758989866386 70.69004600918034 -1.1602654120268343	mast:SDSS/sdss/imaging/1013/1/95/frame-irg-001013-1-0095.jpg	mast:SDSS/sdss/imaging/1013/1/95/photoObj-001013-1-0095.fits	PUBLIC	False	nan	295513946	874391138
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	005973-5-0037	FIELD	sdss_image_005973-5-0037	173.132629482	-4.816058996	image	SDSS Collaboration	3	53741.472927662035	53741.47686872056	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 173.1914427566512 -4.942374860882622 172.9940314742844 -4.832827572791295 173.07393446271988 -4.689791600591029 173.27131708934695 -4.799315862787537 173.1914427566512 -4.942374860882622	mast:SDSS/sdss/imaging/5973/5/37/frame-irg-005973-5-0037.jpg	mast:SDSS/sdss/imaging/5973/5/37/photoObj-005973-5-0037.fits	PUBLIC	False	nan	295513976	874391191
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	001462-1-0139	FIELD	sdss_image_001462-1-0139	146.220640486	0.795511046803	image	SDSS Collaboration	3	51669.19211134259	51669.19605263259	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 146.1419152529625 0.6807520127105144 146.13577886376785 0.9056991046172137 146.29937309153925 0.9101586882084078 146.3055005693894 0.6852113532500438 146.1419152529625 0.6807520127105144	mast:SDSS/sdss/imaging/1462/1/139/frame-irg-001462-1-0139.jpg	mast:SDSS/sdss/imaging/1462/1/139/photoObj-001462-1-0139.fits	PUBLIC	False	nan	295513995	874391224
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	002589-1-0228	FIELD	sdss_image_002589-1-0228	49.3537096163	-0.944154233102	image	SDSS Collaboration	3	52173.36897152778	52173.372912702034	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 49.27187518653335 -1.0567348956152853 49.271824453431414 -0.8316600492747049 49.43553877625802 -0.8316815982341773 49.43560010836548 -1.0567564419363762 49.27187518653335 -1.0567348956152853	mast:SDSS/sdss/imaging/2589/1/228/frame-irg-002589-1-0228.jpg	mast:SDSS/sdss/imaging/2589/1/228/photoObj-002589-1-0228.fits	PUBLIC	False	nan	295514006	874391254
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	001013-1-0092	FIELD	sdss_image_001013-1-0092	70.3228432592	-1.04763839962	image	SDSS Collaboration	3	51459.47885532407	51459.48279661407	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 70.24097683204889 -1.1601976036920532 70.24102714799464 -0.9351305230571858 70.40470378557966 -0.9351870067813087 70.4046652275189 -1.1602540897366753 70.24097683204889 -1.1601976036920532	mast:SDSS/sdss/imaging/1013/1/92/frame-irg-001013-1-0092.jpg	mast:SDSS/sdss/imaging/1013/1/92/photoObj-001013-1-0092.fits	PUBLIC	False	nan	295514045	874391306
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	005973-5-0131	FIELD	sdss_image_005973-5-0131	179.969352678	7.4943606014	image	SDSS Collaboration	3	53741.51190347222	53741.51584453074	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 180.0283952399242 7.368044789069491 179.8300551327669 7.477623018461708 179.91037279910233 7.620615014737597 180.1087578061914 7.511000816926455 180.0283952399242 7.368044789069491	mast:SDSS/sdss/imaging/5973/5/131/frame-irg-005973-5-0131.jpg	mast:SDSS/sdss/imaging/5973/5/131/photoObj-005973-5-0131.fits	PUBLIC	False	nan	295514071	874391355
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	001462-1-0075	FIELD	sdss_image_001462-1-0075	136.644404654	0.507734474462	image	SDSS Collaboration	3	51669.16557430555	51669.1695157113	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 136.5662754766541 0.39254266058524295 136.55897977522113 0.6174606423234328 136.72254017681908 0.6228154675656018 136.72983019447588 0.3978973013522048 136.5662754766541 0.39254266058524295	mast:SDSS/sdss/imaging/1462/1/75/frame-irg-001462-1-0075.jpg	mast:SDSS/sdss/imaging/1462/1/75/photoObj-001462-1-0075.fits	PUBLIC	False	nan	295514096	874391392

The table above provides some basic information for each object:

instrument_name: SDSS Camera indicates that the imaging data were collected using the SDSS camera.
filters: Indicates the SDSS filters used in the survey (u, g, r, i, and z).
wavelength_region: Indicates the region of the electromagnetic spectrum observed. This should be OPTICAL, since the SDSS Legacy Imaging Survey observed in the optical wavelength range.
target_classification: FIELD indicates the survey captured images of the sky.
obs_id: Observation ID associated with the image.
s_ra and s_dec: Right ascension and declination.
dataproduct_type: This should be image since we’re focusing on an imaging survey.
t_min and t_max: The modified Julian dates indicating the start and end times of the exposures.
em_min and em_max: The minimum and maximum wavelengths observed by the survey. For the SDSS Legacy Imaging survey, this range is approximately 304.8 - 1083.3 nanometers (optical).

Gathering Galaxies from the SDSS Legacy Imaging Survey#

In this tutorial, we’ll be gathering a variety of galaxies to make a Hubble Tuning Fork Diagram. We’ll select the following galaxies:

Elliptical:
- M89 (E0)
- NGC 5982 (E3)
- NGC 4697 (E6)
Lenticular:
- NGC 3384 (S0)
Spiral:
- NGC 488 (Sa)
- M88 (Sb)
- M99 (Sc)
Barred Spiral:
- NGC 109 (SBa)
- M91 (SBb)
- NGC 5068 (SBc)
Irregular:
- IC 3583
- NGC 7292

These galaxies were selected based on their NED classification as well as how they fit in an SDSS field using the MAST Portal Astroview.

We can query MAST using the target name directly! We’ll use M89 as an example:

# Querying MAST for M89 using search radius of 0
m89 = Observations.query_criteria(
    objectname="M89", radius=0, provenance_name="SDSS Legacy Imaging"
)
# Displaying the results
m89

Table masked=True length=3

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID	objID1	distance
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str194	str61	str61	str6	bool	float64	str9	str9	str9	float64
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	003805-4-0012	FIELD	sdss_image_003805-4-0012	188.898701441	12.5764587394	image	SDSS Collaboration	3	52721.22948229167	52721.23342288722	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 188.8132288137322 12.46506119358693 188.81649298124918 12.690134070168584 188.98424657174562 12.687719213107714 188.9808354852855 12.462648412357575 188.8132288137322 12.46506119358693	mast:SDSS/sdss/imaging/3805/4/12/frame-irg-003805-4-0012.jpg	mast:SDSS/sdss/imaging/3805/4/12/photoObj-003805-4-0012.fits	PUBLIC	False	nan	297084970	877110806	877110806	0.0
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	003064-4-0048	FIELD	sdss_image_003064-4-0048	188.888058594	12.5775588961	image	SDSS Collaboration	3	52356.43429236111	52356.43823341963	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 188.80250968110988 12.46618524586542 188.80590815690954 12.69122285024466 188.97368000165366 12.688795440850217 188.97013460213253 12.463759996247843 188.80250968110988 12.46618524586542	mast:SDSS/sdss/imaging/3064/4/48/frame-irg-003064-4-0048.jpg	mast:SDSS/sdss/imaging/3064/4/48/photoObj-003064-4-0048.fits	PUBLIC	False	nan	297485968	878009148	878009148	0.0
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	003804-4-0207	FIELD	sdss_image_003804-4-0207	188.89762961	12.5766093494	image	SDSS Collaboration	3	52721.21609756944	52721.220038743704	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 188.81217294825396 12.46522271055066 188.81545014737785 12.690283256904873 188.98315874867606 12.687858932000672 188.97973467649607 12.46280046903323 188.81217294825396 12.46522271055066	mast:SDSS/sdss/imaging/3804/4/207/frame-irg-003804-4-0207.jpg	mast:SDSS/sdss/imaging/3804/4/207/photoObj-003804-4-0207.fits	PUBLIC	False	nan	297868245	880840069	880840069	0.0

There are three fields available for M89, but we’ll be using the field with target_name=003804-4-0207 since it completely captures the galaxy. For the rest of the tutorial, we’ll be querying by target name (field) as we preselected these from the MAST Portal depending on how the galaxy fit into each field.

Elliptical Galaxies#

Elliptical galaxies have a distinct nucleus, but do not have a disk or spiral arms. Due to the minimal dust and gas present, these galaxies are mostly made up of population II stars. Elliptical galaxies are categorized by number, with E0 being the most round in shape, and E7 being the most elliptical in shape. The elliptical galaxy classification numbers are derived from the equation:

\[ n = 10(\frac{b}{a}) \]

where \(n\) is the classification number, \(b\) is the projected length of the semi-minor axis on the sky, and \(a\) is the projected length of the semi-major axis on the sky [4]. However, this system is sensitive to the angle at which we observe the galaxy. A galaxy that appears highly elliptical when viewed edge-on may be more circular when viewed face-on. Although this classification scheme remains in use, it’s important to remember the limitations imposed by our viewing perspective.

We’ll use the following fields for each galaxy:

M89 field: 003804-4-0207
NGC 5982 field: 004679-1-0034
NGC 4697 field: 006121-1-0124

# Elliptical Galaxies
ellipticals = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging",
    target_name=[
        "003804-4-0207",  # M89
        "004679-1-0034",  # NGC 5982
        "006121-1-0124",  # NGC 4697
    ],
)
ellipticals

Table masked=True length=3

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str196	str61	str61	str6	bool	float64	str9	str9
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	003804-4-0207	FIELD	sdss_image_003804-4-0207	188.89762961	12.5766093494	image	SDSS Collaboration	3	52721.21609756944	52721.220038743704	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 188.81217294825396 12.46522271055066 188.81545014737785 12.690283256904873 188.98315874867606 12.687858932000672 188.97973467649607 12.46280046903323 188.81217294825396 12.46522271055066	mast:SDSS/sdss/imaging/3804/4/207/frame-irg-003804-4-0207.jpg	mast:SDSS/sdss/imaging/3804/4/207/photoObj-003804-4-0207.fits	PUBLIC	False	nan	297868245	880840069
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	004679-1-0034	FIELD	sdss_image_004679-1-0034	234.574548776	59.3448234453	image	SDSS Collaboration	3	53170.30600509259	53170.309946266854	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 234.3046197895768 59.32444261506588 234.62038966365222 59.481940250855786 234.84464256375884 59.36456934478688 234.52892307987 59.20761382067637 234.3046197895768 59.32444261506588	mast:SDSS/sdss/imaging/4679/1/34/frame-irg-004679-1-0034.jpg	mast:SDSS/sdss/imaging/4679/1/34/photoObj-004679-1-0034.fits	PUBLIC	False	nan	298084026	883250573
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	006121-1-0124	FIELD	sdss_image_006121-1-0124	192.206354543	-5.7765959424	image	SDSS Collaboration	3	53856.28209305555	53856.28603411408	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 192.31583595794746 -5.863292886582556 192.08978940731004 -5.853419106917138 192.0970170390151 -5.689882899407467 192.32299845386115 -5.699753837522322 192.31583595794746 -5.863292886582556	mast:SDSS/sdss/imaging/6121/1/124/frame-irg-006121-1-0124.jpg	mast:SDSS/sdss/imaging/6121/1/124/photoObj-006121-1-0124.fits	PUBLIC	False	nan	297963442	881902351

Lenticular Galaxies#

Lenticular galaxies are in-between elliptical and spiral galaxies. They have a central bulge and a disk similar to a spiral galaxy, but lack the spiral arm structure. These galaxies are thought to be former spiral galaxies that lost their interstellar material, likely due to interactions with other galaxies or their environments [5] [6].

We’ll use the field 003631-1-0302 for NGC 3384.

# Lenticular Galaxy
lenticular = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging",
    target_name="003631-1-0302",  # NGC 3384
)
lenticular

Table masked=True length=1

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str194	str61	str61	str6	bool	float64	str9	str9
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	003631-1-0302	FIELD	sdss_image_003631-1-0302	162.00495917	12.6948375209	image	SDSS Collaboration	3	52667.431497453705	52667.43543804926	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 161.9332351533888 12.574530580964552 161.90978380682168 12.798441361659597 162.0767624598467 12.815015802635779 162.10006839174622 12.591090421528067 161.9332351533888 12.574530580964552	mast:SDSS/sdss/imaging/3631/1/302/frame-irg-003631-1-0302.jpg	mast:SDSS/sdss/imaging/3631/1/302/photoObj-003631-1-0302.fits	PUBLIC	False	nan	298398508	885964246

Spiral Galaxies#

Spiral galaxies have distinct spiral arms that protrude from a central bulge of older stars. Within the spiral arms lie stellar “nurseries” of gas and dust that fuel young star formation. Spiral galaxies are classified into Sa, Sb, or Sc groups based on how tightly wound their spirals are, the thickness of the spiral arms, and the size of the central bulge. Sa spirals have large bulges and faint, small spiral arms whereas Sc spirals have smaller bulges, but larger, loose spiral arms [7].

We’ll use the following fields for each galaxy:

NGC 488 field: 007727-5-0202
M88 field: 004381-2-0114
M99 field: 004381-2-0093

# Spiral Galaxies
spirals = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging",
    target_name=[
        "007727-5-0202",  # NGC 488
        "004381-2-0114",  # M88
        "004381-2-0093",  # M99
    ],
)
spirals

Table masked=True length=3

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str195	str61	str61	str6	bool	float64	str9	str9
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	004381-2-0093	FIELD	sdss_image_004381-2-0093	184.719136049	14.4769892626	image	SDSS Collaboration	3	53032.39776828704	53032.401709229816	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 184.63484872415157 14.364236748218197 184.6343524567763 14.58938512819659 184.80350921612668 14.589601743912382 184.80383394846027 14.364453070729992 184.63484872415157 14.364236748218197	mast:SDSS/sdss/imaging/4381/2/93/frame-irg-004381-2-0093.jpg	mast:SDSS/sdss/imaging/4381/2/93/photoObj-004381-2-0093.fits	PUBLIC	False	nan	298352265	885500811
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	004381-2-0114	FIELD	sdss_image_004381-2-0114	187.966141332	14.457917178	image	SDSS Collaboration	3	53032.40647534722	53032.41041640574	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 187.88016114963244 14.346363232959801 187.8830848748545 14.571503687912221 188.05220635612855 14.569329914111023 188.0491114033052 14.344191605583559 187.88016114963244 14.346363232959801	mast:SDSS/sdss/imaging/4381/2/114/frame-irg-004381-2-0114.jpg	mast:SDSS/sdss/imaging/4381/2/114/photoObj-004381-2-0114.fits	PUBLIC	False	nan	298351741	885496458
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	007727-5-0202	FIELD	sdss_image_007727-5-0202	20.406804076	5.3457659483	image	SDSS Collaboration	3	54747.40886678241	54747.41280784093	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 20.321964096341954 5.235060749739203 20.32725877200831 5.460113241855058 20.49167212052815 5.4563495479137645 20.48631705941364 5.231298472919874 20.321964096341954 5.235060749739203	mast:SDSS/sdss/imaging/7727/5/202/frame-irg-007727-5-0202.jpg	mast:SDSS/sdss/imaging/7727/5/202/photoObj-007727-5-0202.fits	PUBLIC	False	nan	298036044	882777689

Barred Spiral Galaxies#

Barred spiral galaxies have a distinct, luminous bar/stripe across their center. This bar is thought to form either from internal dynamical instabilities or from gravitational interactions with neighboring galaxies. Like regular spiral galaxies, they are classified into SBa, SBb, and SBc types: SBa galaxies have tightly wound spiral arms and a larger central bulge, while SBc galaxies have loosely wound arms and a smaller bulge. [8].

We’ll use the following fields for each galaxy:

NGC 109 field: 007932-2-0051
M91 field: 004381-2-0120
NGC 5068 field: 001449-5-0093

# Barred Spirals
barred_spirals = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging",
    target_name=[
        "007932-2-0051",  # NGC 109
        "004381-2-0120",  # M91
        "001449-5-0093",  # NGC 5068
    ],
)
barred_spirals

Table masked=True length=3

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str198	str61	str61	str6	bool	float64	str9	str9
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	001449-5-0093	FIELD	sdss_image_001449-5-0093	199.759449788	-21.0895968268	image	SDSS Collaboration	3	51667.208523726855	51667.21246478537	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 199.68382220371453 -21.209641458700236 199.6605346260022 -20.98555578244084 199.83496672259864 -20.969628194410113 199.8585150712067 -21.19368991756911 199.68382220371453 -21.209641458700236	mast:SDSS/sdss/imaging/1449/5/93/frame-irg-001449-5-0093.jpg	mast:SDSS/sdss/imaging/1449/5/93/photoObj-001449-5-0093.fits	PUBLIC	False	nan	298381053	885786836
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	004381-2-0120	FIELD	sdss_image_004381-2-0120	188.893660009	14.4440133289	image	SDSS Collaboration	3	53032.408963194444	53032.412904368706	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 188.8072050207449 14.332814743629992 188.81110366536907 14.557938939364815 188.98019947543165 14.55507039558893 188.97612983550505 14.329949038635592 188.8072050207449 14.332814743629992	mast:SDSS/sdss/imaging/4381/2/120/frame-irg-004381-2-0120.jpg	mast:SDSS/sdss/imaging/4381/2/120/photoObj-004381-2-0120.fits	PUBLIC	False	nan	298353167	885509568
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	007932-2-0051	FIELD	sdss_image_007932-2-0051	6.52840089436	21.7582967467	image	SDSS Collaboration	3	54857.14674201389	54857.15068307241	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 6.439077306737359 21.646492711571536 6.441505431337264 21.87164565721037 6.617862374334172 21.869942774151156 6.615157893982057 21.644792545902753 6.439077306737359 21.646492711571536	mast:SDSS/sdss/imaging/7932/2/51/frame-irg-007932-2-0051.jpg	mast:SDSS/sdss/imaging/7932/2/51/photoObj-007932-2-0051.fits	PUBLIC	False	nan	298320511	885204258

Irregular Galaxies#

Irregular galaxies are galaxies that do not fit into the elliptical or spiral/barred spiral categories. They typically have chaotic or asymmetric structures, often resulting from violent interactions with other galaxies, collisions, or internal processes. Well-known examples include the Large and Small Magellanic Clouds [9].

We’ll use the following fields for each galaxy:

IC 3583 field: 003836-5-0268
NGC 7292 field: 008115-6-0118

# Irregular galaxies
irregulars = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging",
    target_name=[
        "003836-5-0268",  # IC 3583
        "008115-6-0118",  # NGC 7292
    ],
)
irregulars

Table masked=True length=2

intentType	obs_collection	provenance_name	instrument_name	project	filters	wavelength_region	target_name	target_classification	obs_id	s_ra	s_dec	dataproduct_type	proposal_pi	calib_level	t_min	t_max	t_exptime	em_min	em_max	obs_title	t_obs_release	proposal_id	proposal_type	sequence_number	s_region	jpegURL	dataURL	dataRights	mtFlag	srcDen	obsid	objID
str7	str4	str19	str11	str4	str9	str7	str13	str5	str24	float64	float64	str5	str18	int64	float64	float64	float64	float64	float64	str51	float64	str3	str1	int64	str197	str61	str61	str6	bool	float64	str9	str9
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	003836-5-0268	FIELD	sdss_image_003836-5-0268	189.175059735	13.1998869096	image	SDSS Collaboration	3	52729.241773726855	52729.24571490111	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 189.08925682499807 13.088602004029513 189.09279407361726 13.313649665325844 189.26093904132443 13.311033284196608 189.25724699913016 13.085987980105468 189.08925682499807 13.088602004029513	mast:SDSS/sdss/imaging/3836/5/268/frame-irg-003836-5-0268.jpg	mast:SDSS/sdss/imaging/3836/5/268/photoObj-003836-5-0268.fits	PUBLIC	False	nan	297915282	881405426
science	SDSS	SDSS Legacy Imaging	SDSS Camera	SDSS	u;g;r;i;z	OPTICAL	008115-6-0118	FIELD	sdss_image_008115-6-0118	337.063165401	30.3475793355	image	SDSS Collaboration	3	55122.10941539352	55122.1133563363	53.907456	304.79999999999995	1083.3000000000002	Sloan Digital Sky Survey (SDSS) Legacy Imaging Data	55571.0	N/A	--	--	POLYGON 337.0043270910967 30.21800053821113 336.9384683229479 30.435781036316044 337.12219177360197 30.47702529132038 337.18766967475585 30.259153076577768 337.0043270910967 30.21800053821113	mast:SDSS/sdss/imaging/8115/6/118/frame-irg-008115-6-0118.jpg	mast:SDSS/sdss/imaging/8115/6/118/photoObj-008115-6-0118.fits	PUBLIC	False	nan	297726821	879149237

Downloading SDSS Legacy Imaging Survey Data Products#

For each image, there are 7 available products: The preview .jpg image, the FITS files in each respective SDSS filter (u, g, r, i, and z), and a catalog file containing photometric measurements from all five filters combined. The catalog file is listed as SDSS Imaging Catalogs for the productSubGroupDescription parameter.

For more information about products available at MAST, you can check out the SDSS Legacy Imaging Survey Documentation.

# Combining the Astropy tables for all galaxies
all_galaxies = vstack(
    [ellipticals, lenticular, spirals, barred_spirals, irregulars]
)

# Viewing available products (first 7)
galaxy_products = Observations.get_product_list(all_galaxies)
galaxy_products[:7]

Table masked=True length=7

obsID	obs_collection	dataproduct_type	obs_id	description	type	dataURI	productType	productGroupDescription	productSubGroupDescription	productDocumentationURL	project	prvversion	proposal_id	productFilename	size	parent_obsid	dataRights	calib_level	filters
str9	str4	str12	str28	str246	str1	str64	str7	str28	str21	str48	str19	str3	str3	str30	int64	str9	str6	int64	str9
297726821	SDSS	image	sdss_image_008115-6-0118	Preview-Full	S	mast:SDSS/sdss/imaging/8115/6/118/frame-irg-008115-6-0118.jpg	PREVIEW	--	--	--	SDSS Legacy Imaging	DR8	N/A	frame-irg-008115-6-0118.jpg	1041251	297726821	PUBLIC	3	u;g;r;i;z
297726821	SDSS	image	sdss_image_008115-6-0118	SDSS calibrated, sky-subtracted corrected photometry frame and associated calibration metadata for each run number, camera column, and field name within SDSS.	S	mast:SDSS/sdss/imaging/8115/6/118/frame-g-008115-6-0118.fits.bz2	SCIENCE	Minimum Recommended Products	IMAGE	https://archive.stsci.edu/missions-and-data/sdss	SDSS Legacy Imaging	DR8	N/A	frame-g-008115-6-0118.fits.bz2	3077536	297726821	PUBLIC	2	g
297726821	SDSS	image	sdss_image_008115-6-0118	SDSS calibrated, sky-subtracted corrected photometry frame and associated calibration metadata for each run number, camera column, and field name within SDSS.	S	mast:SDSS/sdss/imaging/8115/6/118/frame-i-008115-6-0118.fits.bz2	SCIENCE	Minimum Recommended Products	IMAGE	https://archive.stsci.edu/missions-and-data/sdss	SDSS Legacy Imaging	DR8	N/A	frame-i-008115-6-0118.fits.bz2	3876498	297726821	PUBLIC	2	i
297726821	SDSS	image	sdss_image_008115-6-0118	SDSS calibrated, sky-subtracted corrected photometry frame and associated calibration metadata for each run number, camera column, and field name within SDSS.	S	mast:SDSS/sdss/imaging/8115/6/118/frame-r-008115-6-0118.fits.bz2	SCIENCE	Minimum Recommended Products	IMAGE	https://archive.stsci.edu/missions-and-data/sdss	SDSS Legacy Imaging	DR8	N/A	frame-r-008115-6-0118.fits.bz2	3661286	297726821	PUBLIC	2	r
297726821	SDSS	image	sdss_image_008115-6-0118	SDSS calibrated, sky-subtracted corrected photometry frame and associated calibration metadata for each run number, camera column, and field name within SDSS.	S	mast:SDSS/sdss/imaging/8115/6/118/frame-u-008115-6-0118.fits.bz2	SCIENCE	Minimum Recommended Products	IMAGE	https://archive.stsci.edu/missions-and-data/sdss	SDSS Legacy Imaging	DR8	N/A	frame-u-008115-6-0118.fits.bz2	3537982	297726821	PUBLIC	2	u
297726821	SDSS	image	sdss_image_008115-6-0118	SDSS calibrated, sky-subtracted corrected photometry frame and associated calibration metadata for each run number, camera column, and field name within SDSS.	S	mast:SDSS/sdss/imaging/8115/6/118/frame-z-008115-6-0118.fits.bz2	SCIENCE	Minimum Recommended Products	IMAGE	https://archive.stsci.edu/missions-and-data/sdss	SDSS Legacy Imaging	DR8	N/A	frame-z-008115-6-0118.fits.bz2	3897222	297726821	PUBLIC	2	z
297726821	SDSS	image	sdss_image_008115-6-0118	SDSS Legacy Imaging photoObj catalog. This contains the full, calibrated outputs of the SDSS Imaging Pipeline including source detection, classification, magnitude measurements, and quality flags for each field and all five filters in that field.	S	mast:SDSS/sdss/imaging/8115/6/118/photoObj-008115-6-0118.fits	SCIENCE	Minimum Recommended Products	SDSS Imaging Catalogs	https://archive.stsci.edu/missions-and-data/sdss	SDSS Legacy Imaging	DR8	N/A	photoObj-008115-6-0118.fits	5705280	297726821	PUBLIC	3	u;g;r;i;z

We’ll now download all FITS files, specifically focusing on the files in specific ugriz filters. For this tutorial, we’ll be using the g, r, and i filters only, so we can filter those out using the filters parameter.

# Downloading products
manifest = Observations.download_products(
    galaxy_products, mrp_only=True, verbose=False, filters=["g", "r", "i"]
)

Each FITS file follows the following naming scheme: frame-{filter}-{RUN}-{CAMCOL}-{FIELD} where RUN is the zero-padded, six-digit identification number for that photometric run, CAMCOL is the camera column identifying the scanline within the run, and FIELD is field number for that observation.

While we won’t be using the photoObj files in this tutorial, these contain the fully calibrated outputs from the SDSS Imaging Pipeline and other respective measurements such as photometry in all five SDSS filters (u, g, r, i, and z), source classification, and quality flags. There is one photoObj file for each run-camcol-field combination.

Creating the Cutout Images Using Astrocut#

Now that we downloaded the FITS files for each galaxy, we can use Astrocut to trim the images and create cutouts!

Astrocut uses FITS files and specified center coordinates to create a trimmed image. We’ll create a dictionary of galaxy names, their target names, and center coordinates. For more information about Astrocut, you can view the documentation.

We’ll use warnings.filterwarnings to suppress FITS warnings due to the change in keyword names since SDSS data was created.

Each Astrocut image cell takes a few seconds to run!

# Suppressing FITS warnings
warnings.filterwarnings("ignore", category=astropy.wcs.FITSFixedWarning)

In order to center the galaxy in our cutout, we need to know the center coordinates! We can use astroquery to resolve the coordinates for each galaxy using Observations.resolve_object. We’ll now make a dictionary to code in the field ID and coordinates per galaxy.

# Making a dictionary for galaxy names with MAST target names and coordinates
galaxies = {
    "m89": {
        "id": "003804-4-0207",
        "coord": Observations.resolve_object("m89"),
    },
    "ngc5982": {
        "id": "004679-1-0034",
        "coord": Observations.resolve_object("ngc5982"),
    },
    "ngc4697": {
        "id": "006121-1-0124",
        "coord": Observations.resolve_object("ngc4697"),
    },
    "ngc3384": {
        "id": "003631-1-0302",
        "coord": Observations.resolve_object("ngc3384"),
    },
    "ngc488": {
        "id": "007727-5-0202",
        "coord": Observations.resolve_object("ngc488"),
    },
    "m88": {
        "id": "004381-2-0114",
        "coord": Observations.resolve_object("m88"),
    },
    "m99": {
        "id": "004381-2-0093",
        "coord": Observations.resolve_object("m99"),
    },
    "ngc109": {
        "id": "007932-2-0051",
        "coord": Observations.resolve_object("ngc109"),
    },
    "m91": {
        "id": "004381-2-0120",
        "coord": Observations.resolve_object("m91"),
    },
    "ngc5068": {
        "id": "001449-5-0093",
        "coord": Observations.resolve_object("ngc5068"),
    },
    "ic3583": {
        "id": "003836-5-0268",
        "coord": Observations.resolve_object("ic3583"),
    },
    "ngc7292": {
        "id": "008115-6-0118",
        "coord": Observations.resolve_object("ngc7292"),
    },
}

# Creating a function to locate files from download, find the r, g, and i files
def get_files_for_galaxy(galaxy_name):
    """
    Finds the files based on galaxy name and returns their r, g, and i FITS files
    """

    # Finding the file by galaxy name
    galaxy_mask = (
        np.char.find(
            manifest["Local Path"].astype(str), galaxies[galaxy_name]["id"]
        )
        >= 0
    )
    files = np.array(manifest["Local Path"][galaxy_mask], dtype=str)

    # Decompressing the files
    fits_files = np.array([], dtype=str)
    for file in files:
        fits_filename = file.replace('.bz2', '')
        fits_files = np.append(fits_files, fits_filename)
        with bz2.open(file, 'rb') as compressed_file:
            with open(fits_filename, 'wb') as decompressed_file:
                decompressed_file.write(compressed_file.read())

    # Finding the r, g, and i files
    rmask = np.char.find(fits_files, "frame-r") >= 0
    gmask = np.char.find(fits_files, "frame-g") >= 0
    imask = np.char.find(fits_files, "frame-i") >= 0

    r_file = fits_files[rmask]
    g_file = fits_files[gmask]
    i_file = fits_files[imask]

    return i_file[0], r_file[0], g_file[0]

# Helper function for creating cutout images
def create_cutouts(galaxy_name, cutout_size):
    """
    This function takes the name of the galaxy and size of the cutout,
    creates cutout using Astrocut, then plots the image using matplotlib
    """

    # Using previous function to get the r, g, and i files
    galaxy_input = get_files_for_galaxy(galaxy_name)

    # Creating the cutouts
    galaxy_colorimage = FITSCutout(
        galaxy_input, galaxies[galaxy_name]["coord"], cutout_size
    ).get_image_cutouts(colorize=True)[0]
    galaxy_colorimage.save(f"{galaxy_name}_cutout.png")

    # Capitalizing the title
    title_name = np.char.upper(galaxy_name)

    # Displaying the cutouts
    plt.figure(figsize=(5, 5))
    plt.imshow(galaxy_colorimage)
    plt.title(f"Cutout of {title_name}")
    plt.show()

# M89
# Creating and displaying the cutout image of M89!
m89_img = create_cutouts("m89", [200, 200])

../../../_images/adfdb33fd5b827ea01b13d9779a789ef66bee9b83aa2a059a5eac96e5d501b69.png

# NGC 5982
# Creating and displaying the cutout image of NGC 5982!
ngc5982_img = create_cutouts("ngc5982", [200, 200])

../../../_images/f26915a4bba2c5e5e0ecfcf87968ce148996bfdb802f783f0c9033e8b2e6b6b2.png

# NGC 4697
# Creating and displaying the cutout image of NGC 4697!
ngc4697_img = create_cutouts("ngc4697", [300, 200])

../../../_images/5e6684438674f7210d9594b8c6cec48e4da1b57c73ea1739d2d847c8affe54de.png

# NGC 3384
# Creating and displaying the cutout image of NGC 3384!
ngc3384_img = create_cutouts("ngc3384", [175, 175])

../../../_images/8c616fedaa690ca903d5f5d5f1fd36480826e2eba851ad1aba91c6ed43610f94.png

# NGC 488
# Creating and displaying the cutout image of NGC 488!
ngc488_img = create_cutouts("ngc488", [440, 500])

../../../_images/049761b31aa22b8c72d01161cb637c2fca9269b104f8945b4d25f63a593ae887.png

# M88
# Creating and displaying the cutout image of M88!
m88_img = create_cutouts("m88", [700, 600])

../../../_images/0c5ef70d311c9e99603509164d5009d68db36c97d0c8a958b9bfa7caf0865a78.png

# M99
# Creating and displaying the cutout image of M99!
m99_img = create_cutouts("m99", [600, 600])

../../../_images/5800b2a327af6d1b19ce608be8aa043fe5c1a0495efa500a9915d6801d4c744d.png

# NGC 109
# Creating and displaying the cutout image of NGC 109!
ngc109_img = create_cutouts("ngc109", [200, 200])

../../../_images/d26a81e375b9176c1e4154498e5a640aea36bb41afe9ebdc32426fe7624fe557.png

# M91
# Creating and displaying the cutout image of M91!
m91_img = create_cutouts("m91", [275, 425])

../../../_images/8ebbbc57adfb9efac4849d37a802b483914baaf3f8881ec3a3a041f8e5ad3380.png

# NGC 5068
# Creating and displaying the cutout image of NGC 5068!
ngc5068_img = create_cutouts("ngc5068", [800, 800])

../../../_images/71a47ddd1e15aed91858c30f19aec67d90471606a7cd9bd2746f2d57638c4e3b.png

# IC 3583
# Creating and displaying the cutout image of IC 3583!
ic3583_img = create_cutouts("ic3583", [300, 150])

../../../_images/17970a72f03b073e3121b8d9c32885f089f0ef87add8a619e40dbd4cadecb4d2.png

# NGC 7292
# Creating and displaying the cutout image of NGC 7292!
ngc7292_img = create_cutouts("ngc7292", [250, 300])

../../../_images/fd30edee48d7c334aee5107df82ee24760e9c17d871b45a3fef432ac2afcfa19.png

Making the Hubble Tuning Fork Diagram#

Now that we have our cutouts saved as .png files, we can create our Hubble Tuning Fork Diagram using matplotlib.image and a series of subplots!

# Creating subplots
fig, ax = plt.subplots(nrows=5, ncols=9, figsize=(15, 10), facecolor="black")
for row in ax:
    for a in row:
        a.axis("off")

# Reading the cutout images
images = {}
for galaxy in galaxies.keys():
    images[galaxy] = mpimg.imread(f"{galaxy}_cutout.png")

# Ading connecting lines
# Straight line
x = np.linspace(0, 10, 11)
y1 = 5 * np.ones(11)


# Plotting the images and lines
# Plotting the elliptical galaxies in the center left
ax[2, 0].imshow(images["m89"])
ax[2, 0].set_title("M89\nE0", y=-0.5, color="white", fontsize=14)
ax[2, 1].imshow(images["ngc5982"])
ax[2, 1].set_title("NGC 5982\nE3", y=-0.5, color="white", fontsize=14)
ax[2, 2].imshow(images["ngc4697"])
ax[2, 2].set_title("NGC 4697\nE6", y=-0.98, color="white", fontsize=14)

# Plotting the connecting straight line
ax[2, 3].plot(x, y1, color="white", lw=4)

# Plotting the lenticular galaxy between the ellipticals and spirals
ax[2, 4].imshow(images["ngc3384"])
ax[2, 4].set_title("NGC 3384\nS0", y=-0.5, color="white", fontsize=14)

# Plotting the connecting v line
ax[2, 5].plot((lambda x: np.abs(x - 5))(x), x, color="white", lw=4)
ax[2, 5].set_xlim(0, 5)

# Plotting the spiral galaxies in the top right
ax[1, 6].imshow(images["ngc488"])
ax[1, 6].set_title("NGC 488\nSa", y=-0.5, color="white", fontsize=14)
ax[1, 7].imshow(images["m88"])
ax[1, 7].set_title("M88\nSb", y=-0.82, color="white", fontsize=14)
ax[1, 8].imshow(images["m99"])
ax[1, 8].set_title("M99\nSc", y=-0.63, color="white", fontsize=14)

# Plotting the barred spirals in the bottom right
ax[3, 6].imshow(images["ngc109"])
ax[3, 6].set_title("NGC 109\nSBa", y=-0.68, color="white", fontsize=14)
ax[3, 7].imshow(images["m91"])
ax[3, 7].set_title("M91\nSBb", y=-0.45, color="white", fontsize=14)
ax[3, 8].imshow(images["ngc5068"])
ax[3, 8].set_title("NGC5068\nSBc", y=-0.68, color="white", fontsize=14)

# Plotting the irregular galaxies in the bottom left
ax[4, 0].imshow(images["ic3583"])
ax[4, 0].set_title("IC 3583", y=-1.43, color="white", fontsize=14)
ax[4, 1].imshow(images["ngc7292"])
ax[4, 1].set_title("NGC 7292", y=-0.3, color="white", fontsize=14)

# Adding labels
fig.text(
    0.3,
    0.815,
    "Hubble Tuning Fork Diagram",
    fontsize=30,
    fontstyle="oblique",
    fontweight="bold",
    color="white",
)
fig.text(
    0.35,
    0.78,
    "Made using SDSS Legacy Imaging Data at MAST",
    fontsize=15,
    fontstyle="oblique",
    # fontweight="bold",
    color="white",
)
fig.text(
    0.22, 0.57, "Elliptical", color="white", fontsize=16, fontweight="bold"
)
fig.text(
    0.475, 0.57, "Lenticular", color="white", fontsize=16, fontweight="bold"
)
fig.text(0.75, 0.74, "Spiral", color="white", fontsize=16, fontweight="bold")
fig.text(
    0.725,
    0.425,
    "Barred Spiral",
    color="white",
    fontsize=16,
    fontweight="bold",
)
fig.text(
    0.172, 0.27, "Irregular", color="white", fontsize=16, fontweight="bold"
)

plt.show()

../../../_images/b0ce6dd2ab17250c5cc91c9dc17129763688b2837672279083cee58594f8fbe5.png

End of Tutorial#

Congratulations, you’ve reached the end of this notebook! You’ve learned how to use astroquery.mast and astrocut to create a Hubble Tuning Fork Diagram!

Exercise#

Can you classify these three galaxies referencing the Hubble Tuning Fork Diagram you constructed above?:

M95
NGC 4125
M74

To choose the right field, you can look at the AstroView on the MAST Portal.

(Hint: You can download just the preview image by using Observations.filter_products and adding the argument productType="PREVIEW")

# Query and download data from MAST

# View preview images

Exercise Solution#

# Query and download data from MAST
# Querying MAST
exercise_galaxies = Observations.query_criteria(
    provenance_name="SDSS Legacy Imaging",
    target_name=["003836-4-0084", "006118-3-0168", "007845-2-0104"],
)
# Get product list for query
exercise_products = Observations.get_product_list(exercise_galaxies)
# Filter products to get preview jpgs only
filtered_products = Observations.filter_products(
    exercise_products,
    # Selecting preview jpgs
    productType="PREVIEW",
)
# Download products
Observations.download_products(filtered_products, flat=True, verbose=False)

Table length=3

Local Path	Status	Message	URL
str29	str8	object	object
./frame-irg-003836-4-0084.jpg	COMPLETE	None	None
./frame-irg-006118-3-0168.jpg	COMPLETE	None	None
./frame-irg-007845-2-0104.jpg	COMPLETE	None	None

# Viewing the previews side-by-side
fig2, ax2 = plt.subplots(nrows=1, ncols=3, figsize=(15, 10), facecolor="black")
for a in ax2:
    a.axis("off")

# Reading images
img1 = mpimg.imread("frame-irg-003836-4-0084.jpg")
img2 = mpimg.imread("frame-irg-006118-3-0168.jpg")
img3 = mpimg.imread("frame-irg-007845-2-0104.jpg")

# Plotting images
ax2[0].imshow(img1)
ax2[0].set_title("M95", color="white", y=-0.2, fontsize=14, fontweight="bold")
ax2[1].imshow(img2)
ax2[1].set_title(
    "NGC 4125", color="white", y=-0.2, fontsize=14, fontweight="bold"
)
ax2[2].imshow(img3)
ax2[2].set_title("M74", color="white", y=-0.2, fontsize=14, fontweight="bold")

plt.show()

../../../_images/3fe6bcb55e7e67b4fed9e354d018f786f08da6aacfb0380a0d847ef0f64cc10f.png

Assumptions:

It appears that M95 is fairly similar to NGC 109 and M91; this must be a barred spiral galaxy! While the spiral arms are somewhat tight, M95 is most likely between an SBa and an SBb.
NGC 4125 does not have spiral arms or dust lanes, so it must be elliptical. Since elliptical galaxies are classified by their ellipticity, NGC 4125 is likely between an E3 and an E6.
M74 has distinct spiral arms, but no visible bar. The spiral arms are fairly loose, but not as loose as M99. M74 is likely between an Sb and an Sc galaxy.

Results from NED:

M95: SBb
NGC 4125: E6
M74: Sc

Additional Resources#

Additional resources are linked below:

Citations#

If you use data from MAST for published research, please see the following links for information on which citations to include in your paper:

About this Notebook#

Author(s): Natalie Haugen (nhaugen@terpmail.umd.edu) and Julie Imig (jimig@stsci.edu)
Keyword(s): Tutorial, SDSS, SDSS Legacy Imaging Survey, galaxies, galaxy morphology
First published: July 2025
Last updated: July 2025

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