Astropy is a package that can be downloaded directly fron Anaconda. It is hosted at astropy.org
http://docs.astropy.org/en/stable/getting_started.html
Is a goot place to get started, but we'll try our hand at dealing with some data.
In [1]:
#Preamble. These are some standard things I like to include in IPython Notebooks.
import astropy
from astropy.table import Table, Column, MaskedColumn
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
from astropy import units as u
from astropy.coordinates import SkyCoord, Angle
import astropy.cosmology as cos
# special IPython command to prepare the notebook for matplotlib
%matplotlib inline
First we'll download a fits file from SDSS. This is a fits table rather than a fits image, but the general principle for opening any of these is the same. Astropy's I/O is so advanced that it basically will do exactly what you want unless you are opening a mosaic or a multispec file, and then it is generally the case that you can find affiliated packages which can handle the proper data opening.
In [2]:
cat_file='data/DR9Q.fits'
hdu = fits.open(cat_file)
hdu.info()
Filename: data/DR9Q.fits
No. Name Type Cards Dimensions Format
0 PRIMARY PrimaryHDU 16 (15819,) uint8
1 DR9Q BinTableHDU 536 87822R x 131C [18A, D, D, J, J, J, J, D, D, D, J, D, D, D, D, D, D, I, K, K, K, J, J, J, J, J, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, J, D, D, D, D, D, D, D, J, D, D, J, D, D, D, D, D, I, J, 3A, I, I, 19A, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, J, D, D, D, J, D, D, D, J, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D, D]
Typically, you'll want to discover the metadata by reading in the header. For our FITS table, the header isn't as illuminating as it will be for an image file, for example.
In [3]:
cat_header=hdu[0].header
cat_header
Out[3]:
SIMPLE = T / Standard FITS format
BITPIX = 8 / Character data
NAXIS = 1 / Text string
NAXIS1 = 15819 / Number of characters
VOTMETA = T / Table metadata in VOTable format
EXTEND = T / There are standard extensions
COMMENT
COMMENT The data in this primary HDU consists of bytes which
COMMENT comprise a VOTABLE document.
COMMENT The VOTable describes the metadata of the table contained
COMMENT in the following BINTABLE extension.
COMMENT Such a BINTABLE extension can be used on its own as a perfectly
COMMENT good table, but the information from this HDU may provide some
COMMENT useful additional metadata.
COMMENT There is one following BINTABLE.
NTABLE = 1 / Number of following BINTABLE HDUs
This metadata often contains information you will want to use or manipulate later. In that case, it's pretty straightforward to call it.
In [4]:
print cat_header['NAXIS1']
15819
However, what you really want to see is the data, right? From this point on, we'll be referring explicitly to a fits datatable instead of image. One thing to keep in mind is that the data will be read into a numpy array with a zero-based index in the [y, x] order as was discussed in a previous Python club meeting.
In [5]:
cat_data=hdu[1].data
cat_data.columns
Out[5]:
ColDefs(
name = 'SDSS_NAME'; format = '18A'; unit = '-'
name = 'RA'; format = 'D'; unit = 'DEGREE'
name = 'DEC'; format = 'D'; unit = 'DEGREE'
name = 'THING_ID'; format = 'J'; unit = '-'
name = 'PLATE'; format = 'J'; unit = '-'
name = 'MJD'; format = 'J'; unit = '-'
name = 'FIBERID'; format = 'J'; unit = '-'
name = 'Z_VI'; format = 'D'; unit = '-'
name = 'Z_PIPE'; format = 'D'; unit = '-'
name = 'ERR_ZPIPE'; format = 'D'; unit = '-'
name = 'ZWARNING'; format = 'J'; unit = '-'
name = 'Z_PCA'; format = 'D'; unit = '-'
name = 'ERR_ZPCA'; format = 'D'; unit = '-'
name = 'PCA_QUAL'; format = 'D'; unit = '-'
name = 'Z_CIV'; format = 'D'; unit = '-'
name = 'Z_CIII'; format = 'D'; unit = '-'
name = 'Z_MGII'; format = 'D'; unit = '-'
name = 'SDSS_MORPHO'; format = 'I'; unit = '-'
name = 'BOSS_TARGET1'; format = 'K'; unit = '-'
name = 'ANCILLARY_TARGET1'; format = 'K'; unit = '-'
name = 'ANCILLARY_TARGET2'; format = 'K'; unit = '-'
name = 'SDSS_DR7'; format = 'J'; unit = '-'
name = 'PLATE_DR7'; format = 'J'; unit = '-'
name = 'MJD_DR7'; format = 'J'; unit = '-'
name = 'FIBERID_DR7'; format = 'J'; unit = '-'
name = 'UNIFORM'; format = 'J'; unit = '-'
name = 'MI'; format = 'D'; unit = '-'
name = 'DGMI'; format = 'D'; unit = '-'
name = 'ALPHA_NU'; format = 'D'; unit = '-'
name = 'SNR_SPEC'; format = 'D'; unit = '-'
name = 'SNR_1700'; format = 'D'; unit = '-'
name = 'SNR_3000'; format = 'D'; unit = '-'
name = 'SNR_5150'; format = 'D'; unit = '-'
name = 'FWHM_CIV'; format = 'D'; unit = 'km/s'
name = 'BHWHM_CIV'; format = 'D'; unit = 'km/s'
name = 'RHWHM_CIV'; format = 'D'; unit = 'km/s'
name = 'AMP_CIV'; format = 'D'; unit = '-'
name = 'REWE_CIV'; format = 'D'; unit = 'Angstrom'
name = 'ERR_REWE_CIV'; format = 'D'; unit = 'Angstrom'
name = 'FWHM_CIII'; format = 'D'; unit = 'km/s'
name = 'BHWHM_CIII'; format = 'D'; unit = 'km/s'
name = 'RHWHM_CIII'; format = 'D'; unit = 'km/s'
name = 'AMP_CIII'; format = 'D'; unit = '-'
name = 'REWE_CIII'; format = 'D'; unit = 'Angstrom'
name = 'ERR_REWE_CIII'; format = 'D'; unit = 'Angstrom'
name = 'FWHM_MGII'; format = 'D'; unit = 'km/s'
name = 'BHWHM_MGII'; format = 'D'; unit = 'km/s'
name = 'RHWHM_MGII'; format = 'D'; unit = 'km/s'
name = 'AMP_MGII'; format = 'D'; unit = '-'
name = 'REWE_MGII'; format = 'D'; unit = 'Angstrom'
name = 'ERR_REWE_MGII'; format = 'D'; unit = 'Angstrom'
name = 'BAL_FLAG_VI'; format = 'J'; unit = '-'
name = 'BI_CIV'; format = 'D'; unit = 'km/s'
name = 'ERR_BI_CIV'; format = 'D'; unit = 'km/s'
name = 'AI_CIV'; format = 'D'; unit = 'km/s'
name = 'ERR_AI_CIV'; format = 'D'; unit = 'km/s'
name = 'DI_CIV'; format = 'D'; unit = 'km/s'
name = 'ERR_DI_CIV'; format = 'D'; unit = 'km/s'
name = 'CHI2TROUGH'; format = 'D'; unit = '-'
name = 'NCIV_2000'; format = 'J'; unit = '-'
name = 'VMIN_CIV_2000'; format = 'D'; unit = 'km/s'
name = 'VMAX_CIV_2000'; format = 'D'; unit = 'km/s'
name = 'NCIV_450'; format = 'J'; unit = '-'
name = 'VMIN_CIV_450'; format = 'D'; unit = 'km/s'
name = 'VMAX_CIV_450'; format = 'D'; unit = 'km/s'
name = 'REW_SIIV'; format = 'D'; unit = 'Angstrom'
name = 'REW_CIV'; format = 'D'; unit = 'Angstrom'
name = 'REW_ALIII'; format = 'D'; unit = 'Angstrom'
name = 'RUN_NUMBER'; format = 'I'; unit = '-'
name = 'PHOTO_MJD'; format = 'J'; unit = '-'
name = 'RERUN_NUMBER'; format = '3A'; unit = '-'
name = 'COL_NUMBER'; format = 'I'; unit = '-'
name = 'FIELD_NUMBER'; format = 'I'; unit = '-'
name = 'OBJ_ID'; format = '19A'; unit = '-'
name = 'UFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'ERR_UFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'GFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'ERR_GFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'RFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'ERR_RFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'IFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'ERR_IFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'ZFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'ERR_ZFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'TARGET_UFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'TARGET_GFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'TARGET_RFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'TARGET_IFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'TARGET_ZFLUX'; format = 'D'; unit = 'nanomaggies'
name = 'U_EXT'; format = 'D'; unit = 'mag'
name = 'HI_GAL'; format = 'D'; unit = 'cm^-2'
name = 'RASS_COUNT'; format = 'D'; unit = 'COUNT/S'
name = 'RASS_COUNTS_SNR'; format = 'D'; unit = '-'
name = 'SDSS2ROSAT_SEP'; format = 'D'; unit = 'arcsec'
name = 'NUVFLUX'; format = 'D'; unit = 'AB_nanomaggies'
name = 'ERR_NUVFLUX'; format = 'D'; unit = 'AB_nanomaggies'
name = 'FUVFLUX'; format = 'D'; unit = 'AB_nanomaggies'
name = 'ERR_FUVFLUX'; format = 'D'; unit = 'AB_nanomaggies'
name = 'JMAG'; format = 'D'; unit = '-'
name = 'ERR_JMAG'; format = 'D'; unit = '-'
name = 'JSNR'; format = 'D'; unit = '-'
name = 'JRDFLAG'; format = 'J'; unit = '-'
name = 'HMAG'; format = 'D'; unit = '-'
name = 'ERR_HMAG'; format = 'D'; unit = '-'
name = 'HSNR'; format = 'D'; unit = '-'
name = 'HRDFLAG'; format = 'J'; unit = '-'
name = 'KMAG'; format = 'D'; unit = '-'
name = 'ERR_KMAG'; format = 'D'; unit = '-'
name = 'KSNR'; format = 'D'; unit = '-'
name = 'KRDFLAG'; format = 'J'; unit = '-'
name = 'SDSS2MASS_SEP'; format = 'D'; unit = 'arcsec'
name = 'W1MAG'; format = 'D'; unit = '-'
name = 'ERR_W1MAG'; format = 'D'; unit = '-'
name = 'W1SNR'; format = 'D'; unit = '-'
name = 'W1CHI2'; format = 'D'; unit = '-'
name = 'W2MAG'; format = 'D'; unit = '-'
name = 'ERR_W2MAG'; format = 'D'; unit = '-'
name = 'W2SNR'; format = 'D'; unit = '-'
name = 'W2CHI2'; format = 'D'; unit = '-'
name = 'W3MAG'; format = 'D'; unit = '-'
name = 'ERR_W3MAG'; format = 'D'; unit = '-'
name = 'W3SNR'; format = 'D'; unit = '-'
name = 'W3CHI2'; format = 'D'; unit = '-'
name = 'W4MAG'; format = 'D'; unit = '-'
name = 'ERR_W4MAG'; format = 'D'; unit = '-'
name = 'W4SNR'; format = 'D'; unit = '-'
name = 'W4CHI2'; format = 'D'; unit = '-'
name = 'SDSS2WISE_SEP'; format = 'D'; unit = 'arcsec'
name = 'FIRST_FLUX'; format = 'D'; unit = 'mJy'
name = 'FIRST_SNR'; format = 'D'; unit = '-'
name = 'SDSS2FIRST_SEP'; format = 'D'; unit = 'arcsec'
)
This is a particular kind of "FITS record" rather than a data table. You might want to convert this into an astropy data table to see its functionality. Another option would be to convert this into a pandas dataframe, but we'll let Roberto handle that idea at a later time.
In [6]:
data = Table(cat_data)
Let's see how this differs from the other object above. You can get a sense just be doing the self call.
In [7]:
data
Out[7]:
<Table length=87822>
SDSS_NAME RA DEC THING_ID PLATE MJD FIBERID Z_VI Z_PIPE ERR_ZPIPE ZWARNING Z_PCA ERR_ZPCA PCA_QUAL Z_CIV Z_CIII Z_MGII SDSS_MORPHO BOSS_TARGET1 ANCILLARY_TARGET1 ANCILLARY_TARGET2 SDSS_DR7 PLATE_DR7 MJD_DR7 FIBERID_DR7 UNIFORM MI DGMI ALPHA_NU SNR_SPEC SNR_1700 SNR_3000 SNR_5150 FWHM_CIV BHWHM_CIV RHWHM_CIV AMP_CIV REWE_CIV ERR_REWE_CIV FWHM_CIII BHWHM_CIII RHWHM_CIII AMP_CIII REWE_CIII ERR_REWE_CIII FWHM_MGII BHWHM_MGII RHWHM_MGII AMP_MGII REWE_MGII ERR_REWE_MGII BAL_FLAG_VI BI_CIV ERR_BI_CIV AI_CIV ERR_AI_CIV DI_CIV ERR_DI_CIV CHI2TROUGH NCIV_2000 VMIN_CIV_2000 VMAX_CIV_2000 NCIV_450 VMIN_CIV_450 VMAX_CIV_450 REW_SIIV REW_CIV REW_ALIII RUN_NUMBER PHOTO_MJD RERUN_NUMBER COL_NUMBER FIELD_NUMBER OBJ_ID UFLUX ERR_UFLUX GFLUX ERR_GFLUX RFLUX ERR_RFLUX IFLUX ERR_IFLUX ZFLUX ERR_ZFLUX TARGET_UFLUX TARGET_GFLUX TARGET_RFLUX TARGET_IFLUX TARGET_ZFLUX U_EXT HI_GAL RASS_COUNT RASS_COUNTS_SNR SDSS2ROSAT_SEP NUVFLUX ERR_NUVFLUX FUVFLUX ERR_FUVFLUX JMAG ERR_JMAG JSNR JRDFLAG HMAG ERR_HMAG HSNR HRDFLAG KMAG ERR_KMAG KSNR KRDFLAG SDSS2MASS_SEP W1MAG ERR_W1MAG W1SNR W1CHI2 W2MAG ERR_W2MAG W2SNR W2CHI2 W3MAG ERR_W3MAG W3SNR W3CHI2 W4MAG ERR_W4MAG W4SNR W4CHI2 SDSS2WISE_SEP FIRST_FLUX FIRST_SNR SDSS2FIRST_SEP str18 float64 float64 int32 int32 int32 int32 float64 float64 float64 int32 float64 float64 float64 float64 float64 float64 int16 int64 int64 int64 int32 int32 int32 int32 int32 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 int32 float64 float64 float64 float64 float64 float64 float64 int32 float64 float64 int32 float64 float64 float64 float64 float64 int16 int32 str3 int16 int16 str19 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 int32 float64 float64 float64 int32 float64 float64 float64 int32 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 float64 000000.47-002703.9 0.00197831659392 -0.451088294717 85874308 4216 55477 310 0.25 0.249952957034 4.44032411906e-05 0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 1 0 68719476736 0 0 685 52203 178 0 -20.7881925442 0.658929385201 500.0 6.49142721487 -1.0 1.77142105606 7.84186338653 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 2728 52231 301 2 413 1237657190368346361 2.10464334488 0.251895345458 3.34651851654 0.128381692532 6.30769968033 0.175069102903 8.80151939392 0.235546353246 11.4227657318 0.812136318171 -9999.0 -9999.0 -9999.0 -9999.0 -9999.0 0.212342917919 20.5343434568 -9.0 -9.0 0.0 2.4585442543 78.2909271 2.5156826973 61.5269682 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 16.012 0.077 14.0 0.8629 15.497 0.166 6.6 0.9684 12.163 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.205726377502 0.0 0.0 0.0 000001.93-001427.4 0.00806669135031 -0.24097078526 87837348 4216 55477 312 2.163 2.16453075409 0.000302524451399 0 2.16007701253 -1.0 0.0541167216808 2.15088819426 2.15465589026 2.16833757817 0 2199023255552 0 8 1 -1 -1 -1 0 -26.1409116142 0.0810805915605 -0.0911119177982 7.06683969348 9.50213116971 2.07160085751 -1.0 6538.1626008 3118.87706723 3419.28553357 7.57619096816 29.0224373899 0.872970491405 7925.87818757 3763.58657783 4162.29160973 2.98835074972 28.1557852541 1.34855053201 5143.80974938 2371.29470013 2772.51504924 2.80710051702 37.5869327781 1.4014457384 0 14.5377544497 1.69026289853 606.441066226 37.2281206519 358.166755507 20.7121455508 21.48386854 0 -13187.6563803 -11035.8632193 4 -13963.3027523 -1552.96080067 0.0 0.0 0.0 4263 52963 301 3 116 1237663783660552482 6.77103662491 0.285805492849 9.08086204529 0.202807899475 10.690320015 0.19394244101 11.2202253342 0.373180271121 13.3799591064 0.758386800562 5.66870832443 7.71396303177 7.71396303177 7.71396303177 7.71396303177 0.175267785788 20.5431364148 -9.0 -9.0 0.0 0.8409730792 218.7284794 -0.031143887 774.7557397 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 16.683 0.133 8.2 0.8558 15.694 0.181 6.0 0.9398 11.979 0.303 3.6 0.9257 9.012 0.0 0.0 0.0 0.791973981391 0.0 0.0 0.0 000003.17+011510.6 0.0132289989878 1.25296711228 124419674 4296 55499 364 2.354 2.35428118706 0.000525987532455 0 2.35223260658 -1.0 0.111959523853 2.35299894126 2.3485447737 2.36535366127 0 16492675088384 0 16 1 -1 -1 -1 1 -25.414104132 0.0455786015779 0.244583287896 2.8580424133 3.43100347149 0.853030222339 -1.0 6492.38435707 3145.28223579 3347.10212128 4.56907780819 32.8177703777 0.872815690514 8362.41213954 4014.3548025 4348.05733704 1.6298103419 34.5995031123 3.66949158374 6756.70114729 1823.17242653 4933.52872076 1.36277876512 52.0748750007 3.94385402445 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 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3.70247721672 0.000589627597947 0 3.68855526824 0.00168885885093 0.140127268146 3.68953115859 3.69303714895 -1.0 0 0 536870912 16 1 -1 -1 -1 0 -26.7513314507 0.0873100507852 -0.684959042729 1.67146305184 1.39920910193 -1.0 -1.0 3345.58826731 1603.56684638 1742.02142093 7.7995979658 66.9181779919 2.56292612976 4742.54818051 1606.58530078 3135.96287973 1.85654666598 30.6921026198 43.741615638 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 4263 52963 301 3 115 1237663783660487206 -0.147562518716 45.1603240967 1.94447016716 0.0904789188669 6.0746846199 0.163761329612 6.35642147064 0.217852597504 5.26231336594 0.70857107319 -9999.0 -9999.0 -9999.0 -9999.0 -9999.0 0.192241415381 20.5343434568 -9.0 -9.0 0.0 0.0075732977 81.874338 -0.0093469508 693.8696266 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 235958.62+002551.4 359.994273164 0.430947746568 107732352 4216 55477 734 3.066 3.0647892952 0.000213231673115 0 3.0625652413 0.00198782981476 0.209739013623 3.06472197074 3.06305828594 -1.0 0 2199023259648 0 0 1 -1 -1 -1 0 -25.7842200731 -0.271400581063 -1.30854690733 1.18050516374 1.26621508026 -1.0 -1.0 2689.37138615 1160.50600132 1528.86538483 5.9589893211 52.7436161339 4.02669453957 3203.36590919 2077.76804968 1125.59785951 1.68263999519 23.7988428848 17.8520897268 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 -1.0 -1.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 4145 52910 301 5 110 1237663277927760502 0.893194019794 0.194211482283 3.7390203476 0.125147117711 4.14037752151 0.149076790653 3.83683252335 0.216841966924 2.84015607834 0.760335115219 0.839014530182 3.82685041428 3.82685041428 3.82685041428 3.82685041428 0.139909893274 20.5142155963 -9.0 -9.0 0.0 -0.0806212574 969.1113533 -0.0125431838 1066.8030039 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 235959.10+024906.7 359.996269773 2.81855191344 136595331 4277 55506 138 2.398 2.39827179909 0.000217534339754 0 2.37460517335 -1.0 0.198519790411 2.38481286193 -1.0 -1.0 0 16492675088384 0 0 1 -1 -1 -1 1 -25.4286238112 -0.0251857293429 0.561044246857 1.37650927225 1.14700043834 0.999642175981 -1.0 5329.6152227 2290.73920165 3038.87602104 2.86559673977 34.0841442048 0.841921813667 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 -1.0 -1.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 7712 54741 301 4 329 1237678597553586438 2.69098162651 0.328360585102 4.4373960495 0.136570747918 5.17349052429 0.175643865494 4.55736637115 0.230397366429 5.80289983749 1.03780101942 2.69098162651 4.4373960495 4.4373960495 4.4373960495 4.4373960495 0.109388269484 20.5175257836 -9.0 -9.0 0.0 -0.2523953319 2.8225939 -0.2246919125 7.7458577 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 17.319 0.197 5.5 0.7723 16.822 0.466 2.3 0.9052 12.044 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.88391054433 0.0 0.0 0.0
I note that this table is fairly large, so let's pare it down a bit.
In [8]:
len(data)
Out[8]:
87822
In [9]:
truncated_data = data[0:49]
print(truncated_data)
SDSS_NAME RA ... FIRST_SNR SDSS2FIRST_SEP
------------------ ---------------- ... ------------- ---------------
000000.47-002703.9 0.00197831659392 ... 0.0 0.0
000001.93-001427.4 0.00806669135031 ... 0.0 0.0
000003.17+011510.6 0.0132289989878 ... 0.0 0.0
000004.61+035122.4 0.019223183834 ... 0.0 0.0
00004.967-001642.0 0.020695853072 ... 0.0 0.0
000005.02-003829.0 0.0209285614674 ... 0.0 0.0
000007.58+002943.2 0.0316175511158 ... 0.0 0.0
000009.27+020622.0 0.0386573639274 ... 0.0 0.0
000013.03+044403.5 0.0543102195074 ... 0.0 0.0
000014.07+012951.5 0.0586536988573 ... 0.0 0.0
... ... ... ... ...
000048.17+013313.6 0.200734237359 ... 0.0 0.0
000050.59+010959.1 0.210809644556 ... 0.0 0.0
000051.26-001411.0 0.213592530117 ... 0.0 0.0
000051.56+001202.5 0.21485717292 ... 24.0677788089 0.0438004385461
000051.80+042717.7 0.215862585165 ... 0.0 0.0
000052.27+001552.1 0.217830790085 ... 0.0 0.0
000053.17-001732.9 0.221547284805 ... 0.0 0.0
000054.95+010143.4 0.228998875313 ... 22.4960275175 0.521496121263
000057.58+010658.6 0.239926274963 ... 0.0 0.0
000058.12+034301.4 0.242172037082 ... 0.0 0.0
000059.24-003934.7 0.246836598348 ... 0.0 0.0
Length = 49 rows
There are other ways you may want to view your table. For example, the "show in notebook" functionality.
In [10]:
truncated_data.show_in_notebook()
Out[10]:
<Table length=49>
idx SDSS_NAME RA DEC THING_ID PLATE MJD FIBERID Z_VI Z_PIPE ERR_ZPIPE ZWARNING Z_PCA ERR_ZPCA PCA_QUAL Z_CIV Z_CIII Z_MGII SDSS_MORPHO BOSS_TARGET1 ANCILLARY_TARGET1 ANCILLARY_TARGET2 SDSS_DR7 PLATE_DR7 MJD_DR7 FIBERID_DR7 UNIFORM MI DGMI ALPHA_NU SNR_SPEC SNR_1700 SNR_3000 SNR_5150 FWHM_CIV BHWHM_CIV RHWHM_CIV AMP_CIV REWE_CIV ERR_REWE_CIV FWHM_CIII BHWHM_CIII RHWHM_CIII AMP_CIII REWE_CIII ERR_REWE_CIII FWHM_MGII BHWHM_MGII RHWHM_MGII AMP_MGII REWE_MGII ERR_REWE_MGII BAL_FLAG_VI BI_CIV ERR_BI_CIV AI_CIV ERR_AI_CIV DI_CIV ERR_DI_CIV CHI2TROUGH NCIV_2000 VMIN_CIV_2000 VMAX_CIV_2000 NCIV_450 VMIN_CIV_450 VMAX_CIV_450 REW_SIIV REW_CIV REW_ALIII RUN_NUMBER PHOTO_MJD RERUN_NUMBER COL_NUMBER FIELD_NUMBER OBJ_ID UFLUX ERR_UFLUX GFLUX ERR_GFLUX RFLUX ERR_RFLUX IFLUX ERR_IFLUX ZFLUX ERR_ZFLUX TARGET_UFLUX TARGET_GFLUX TARGET_RFLUX TARGET_IFLUX TARGET_ZFLUX U_EXT HI_GAL RASS_COUNT RASS_COUNTS_SNR SDSS2ROSAT_SEP NUVFLUX ERR_NUVFLUX FUVFLUX ERR_FUVFLUX JMAG ERR_JMAG JSNR JRDFLAG HMAG ERR_HMAG HSNR HRDFLAG KMAG ERR_KMAG KSNR KRDFLAG SDSS2MASS_SEP W1MAG ERR_W1MAG W1SNR W1CHI2 W2MAG ERR_W2MAG W2SNR W2CHI2 W3MAG ERR_W3MAG W3SNR W3CHI2 W4MAG ERR_W4MAG W4SNR W4CHI2 SDSS2WISE_SEP FIRST_FLUX FIRST_SNR SDSS2FIRST_SEP 0 000000.47-002703.9 0.00197831659392 -0.451088294717 85874308 4216 55477 310 0.25 0.249952957034 4.44032411906e-05 0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 1 0 68719476736 0 0 685 52203 178 0 -20.7881925442 0.658929385201 500.0 6.49142721487 -1.0 1.77142105606 7.84186338653 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 2728 52231 301 2 413 1237657190368346361 2.10464334488 0.251895345458 3.34651851654 0.128381692532 6.30769968033 0.175069102903 8.80151939392 0.235546353246 11.4227657318 0.812136318171 -9999.0 -9999.0 -9999.0 -9999.0 -9999.0 0.212342917919 20.5343434568 -9.0 -9.0 0.0 2.4585442543 78.2909271 2.5156826973 61.5269682 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 16.012 0.077 14.0 0.8629 15.497 0.166 6.6 0.9684 12.163 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.205726377502 0.0 0.0 0.0 1 000001.93-001427.4 0.00806669135031 -0.24097078526 87837348 4216 55477 312 2.163 2.16453075409 0.000302524451399 0 2.16007701253 -1.0 0.0541167216808 2.15088819426 2.15465589026 2.16833757817 0 2199023255552 0 8 1 -1 -1 -1 0 -26.1409116142 0.0810805915605 -0.0911119177982 7.06683969348 9.50213116971 2.07160085751 -1.0 6538.1626008 3118.87706723 3419.28553357 7.57619096816 29.0224373899 0.872970491405 7925.87818757 3763.58657783 4162.29160973 2.98835074972 28.1557852541 1.34855053201 5143.80974938 2371.29470013 2772.51504924 2.80710051702 37.5869327781 1.4014457384 0 14.5377544497 1.69026289853 606.441066226 37.2281206519 358.166755507 20.7121455508 21.48386854 0 -13187.6563803 -11035.8632193 4 -13963.3027523 -1552.96080067 0.0 0.0 0.0 4263 52963 301 3 116 1237663783660552482 6.77103662491 0.285805492849 9.08086204529 0.202807899475 10.690320015 0.19394244101 11.2202253342 0.373180271121 13.3799591064 0.758386800562 5.66870832443 7.71396303177 7.71396303177 7.71396303177 7.71396303177 0.175267785788 20.5431364148 -9.0 -9.0 0.0 0.8409730792 218.7284794 -0.031143887 774.7557397 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 16.683 0.133 8.2 0.8558 15.694 0.181 6.0 0.9398 11.979 0.303 3.6 0.9257 9.012 0.0 0.0 0.0 0.791973981391 0.0 0.0 0.0 2 000003.17+011510.6 0.0132289989878 1.25296711228 124419674 4296 55499 364 2.354 2.35428118706 0.000525987532455 0 2.35223260658 -1.0 0.111959523853 2.35299894126 2.3485447737 2.36535366127 0 16492675088384 0 16 1 -1 -1 -1 1 -25.414104132 0.0455786015779 0.244583287896 2.8580424133 3.43100347149 0.853030222339 -1.0 6492.38435707 3145.28223579 3347.10212128 4.56907780819 32.8177703777 0.872815690514 8362.41213954 4014.3548025 4348.05733704 1.6298103419 34.5995031123 3.66949158374 6756.70114729 1823.17242653 4933.52872076 1.36277876512 52.0748750007 3.94385402445 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 7717 54742 301 1 329 1237678617417810395 2.2573530674 0.244377446951 4.22009086609 0.131031835024 5.04395532608 0.157655068663 4.65703296661 0.209228583451 6.46461963654 0.726653514604 2.19698762894 3.92831420898 3.92831420898 3.92831420898 3.92831420898 0.14041569829 20.5415792439 -9.0 -9.0 0.0 0.8614116311 2.4325518 0.1407600939 671.7233136 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 17.062 0.177 6.1 1.146 15.843 0.2 5.4 0.8893 11.851 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.14590465572 0.0 0.0 0.0 3 000004.61+035122.4 0.019223183834 3.85623149692 145054116 4277 55506 896 2.795 2.79500842094 0.000524882751051 0 2.78601880364 -1.0 0.280761158497 2.79080751436 2.78577374894 -1.0 0 16492675088384 0 0 1 -1 -1 -1 0 -25.4076076481 -0.0157979580093 -0.818548843652 0.877779845676 0.605089811941 -1.0 -1.0 5457.80434235 2846.08294653 2611.72139582 3.9879907672 124.072556439 4.98545256276 5859.64342472 2519.50449945 3340.13892527 1.46247414862 51.668516727 13.536489525 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 -1.0 -1.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 7727 54747 301 1 66 1237678660350247162 2.03563928604 0.321354473274 2.9753818512 0.13823047819 3.33211016655 0.177822295737 3.3447933197 0.253811148181 4.21481657028 1.10238927364 2.03563928604 2.9753818512 2.9753818512 2.9753818512 2.9753818512 0.147570297122 20.5918989867 -9.0 -9.0 0.0 -0.2550503612 100.3506035 -0.2487099171 214.2405504 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4 00004.967-001642.0 0.020695853072 -0.278343319322 87837710 4216 55477 302 2.879 2.87940812111 0.000977562507614 0 2.89171080211 0.00133798968813 0.248356712632 2.86927683498 2.89364072733 -1.0 0 2199023255552 0 0 1 -1 -1 -1 0 -24.3723417775 -0.131186142485 -1.22596482906 0.872117840075 0.8244578685 -1.0 -1.0 4193.88185157 2633.0489332 1560.83291837 2.27126718474 47.5488452538 2.45512926598 7431.56427656 2992.46720782 4439.09706874 1.11057855022 47.3460586906 15.0793877541 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 -1.0 -1.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 4263 52963 301 3 116 1237663783660552224 0.501980006695 0.502082063676 1.14019930363 0.0980536438678 1.74799466133 0.117933631008 1.17390108109 0.191756930614 0.793585836887 0.827670182119 -9999.0 -9999.0 -9999.0 -9999.0 -9999.0 0.173455864191 20.5431364148 -9.0 -9.0 0.0 0.1538473666 335.4860817 -0.0448066629 592.0778003 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5 000005.02-003829.0 0.0209285614674 -0.641393022532 77764016 4216 55477 292 2.662 2.66177582741 0.000591442279983 0 2.65788625491 -1.0 0.17807593886 2.65960026255 2.64631071761 -1.0 0 2199023255552 0 0 1 -1 -1 -1 0 -25.4679923806 0.0646339717636 -0.651012581516 1.53530404618 1.45996977599 -1.0 -1.0 4955.76716655 1791.3254242 3164.44174236 1.97867320241 23.5379655303 0.827919890347 8066.48262233 3579.06040036 4487.42222197 1.51368354951 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2.75884583466 -1.0 0 2199023259648 0 0 0 685 52203 154 2 -26.8702921947 -0.139561782599 0.419824195897 3.43404789152 3.10687937989 -1.0 -1.0 3496.38148416 1506.71917751 1989.66230664 16.486640348 101.768563334 4.76999366456 3331.32547833 1379.6160122 1951.70946613 5.34760731513 40.7527304 5.77534438758 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 4263 52963 301 3 117 1237663783660617828 5.15334415436 0.271298564827 13.1029634476 0.212954695622 13.9866256714 0.250224362982 13.1183443069 0.350080253062 15.4770183563 0.718938649367 5.04591417313 13.2563972473 13.2563972473 13.2563972473 13.2563972473 0.173833504319 20.5343434568 -9.0 -9.0 0.0 0.0464979634 92.0440128 0.0639714301 555.5430615 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 16.922 0.172 6.3 0.902 16.081 0.277 3.9 0.8993 12.335 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.37967560048 0.0 0.0 0.0 45 000054.95+010143.4 0.228998875313 1.02872693041 116879225 4296 55499 322 1.459 1.46171188354 0.000228773511481 0 1.46024476143 0.000283663593042 0.0316989815458 1.46108514878 1.45841183326 1.45940426023 0 0 2251799813685248 0 0 685 52203 502 0 -25.6995312972 0.300060005994 500.0 12.4221562955 10.022453708 14.1769437404 -1.0 3320.56274363 1470.30043401 1850.26230962 9.84509901088 30.1278993177 2.76028225847 5138.40711076 2083.20630521 3055.20080555 8.72403290676 22.0543078782 0.413942463346 3605.91404641 1826.94192558 1778.97212083 10.6588497685 43.338199452 0.45380156746 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 4145 52910 301 6 112 1237663278464761946 8.80787086487 0.322365887902 11.7573204041 0.204482439976 15.6449918747 0.291122981719 19.829618454 0.495053323807 23.2103099823 1.14647842592 -9999.0 -9999.0 -9999.0 -9999.0 -9999.0 0.139875084162 20.5415792439 -9.0 -9.0 0.0 3.4080715179 124.1093905 1.0793243647 164.4830767 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 15.802 0.067 16.2 0.8796 14.64 0.084 13.0 0.8349 11.727 0.257 4.2 0.9033 8.671 0.0 0.0 0.0 0.289345506963 3.3599998951 22.4960275175 0.521496121263 46 000057.58+010658.6 0.239926274963 1.1162778972 122289693 4216 55477 750 2.549 2.54931044579 0.000615280296188 0 2.54828549312 0.000851523208732 0.0637189035131 2.54836852789 2.55021625383 -1.0 0 2199023259648 0 0 0 1091 52902 546 2 -26.5167666849 0.166921139262 -0.759339584665 6.91282209785 6.88538027658 -1.0 -1.0 3665.05471937 1614.32232024 2050.73239913 10.3320337048 32.6687637497 0.890713584706 5401.74913804 2199.86458969 3201.88454835 4.47733129828 21.6208469893 1.74586207073 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 524.227096773 16.3653070366 0.0 0.0 25.7015935013 0 0.0 0.0 2 -15239.3661384 -10235.1959967 0.0 0.0 0.0 2728 52231 301 6 414 1237657192515895495 4.61055040359 0.350303730039 8.35048389435 0.201765796403 10.1150083542 0.203596619311 10.6622285843 0.284249824068 12.0825004578 0.908596503693 4.7655005455 8.98957824707 8.98957824707 8.98957824707 8.98957824707 0.140373274684 20.5415792439 -9.0 -9.0 0.0 0.0109611079 74.0423109 0.0259450451 871.0204221 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 17.108 0.186 5.8 1.744 15.58 0.165 6.6 0.8491 12.037 0.344 3.2 1.043 8.931 0.488 2.2 1.062 1.18582546439 0.0 0.0 0.0 47 000058.12+034301.4 0.242172037082 3.71707533708 143580514 4277 55506 112 0.905 0.90504270792 0.00013061898062 0 0.906780810395 -1.0 0.0562971378244 -1.0 -1.0 -1.0 0 16492675072000 0 0 1 -1 -1 -1 1 -23.3792292008 0.210952203863 500.0 3.5570237573 -1.0 3.83476495629 1.00272384246 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 7712 54741 301 6 331 1237678598627459271 1.94448959827 0.350400334482 4.06837654114 0.145840556121 4.23524141312 0.180167468685 5.48773765564 0.262695491803 6.58621692657 1.05085074772 1.94448959827 4.06837654114 4.06837654114 4.06837654114 4.06837654114 0.116992987692 20.6190933306 -9.0 -9.0 0.0 3.5990846157 8.5587501 1.118928194 11.4429756 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 16.416 0.103 10.5 0.8647 15.543 0.17 6.4 0.9523 12.012 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.174763593463 0.0 0.0 0.0 48 000059.24-003934.7 0.246836598348 -0.659666627587 77765425 4216 55477 211 2.142 2.15174865723 0.000302145956084 0 2.14937860763 0.00130128891918 0.148088817699 2.1465137342 2.14959219277 2.14870861268 0 2199023255552 0 0 1 -1 -1 -1 0 -24.7273910522 0.210600510973 -0.794389535287 1.64027993693 2.50954105565 0.928840951921 -1.0 4361.67555565 1905.00973214 2456.66582351 5.44333550205 45.5435511519 2.04047195477 5118.84306914 1528.91225296 3589.93081618 2.0818539536 43.726938282 4.61911218328 3184.27730608 1579.59767177 1604.67963431 2.21788424275 70.2628991505 5.12297607232 0 0.0 0.0 -1.0 -1.0 0.0 0.0 0.0 0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 4263 52963 301 2 117 1237663783123747072 1.49918937683 0.211143813933 2.17320132256 0.0981310622797 2.50684118271 0.138470306042 3.08259773254 0.175610419225 3.93939161301 0.605900215117 1.18515777588 2.10536122322 2.10536122322 2.10536122322 2.10536122322 0.211970463395 20.5343434568 -9.0 -9.0 0.0 -0.0234345403 410.8931715 0.0359612852 133.0988244 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 0.0 0.0 0 0.0 17.215 0.202 5.4 0.86 15.716 0.169 6.4 1.025 12.645 0.523 2.1 0.9572 8.748 0.0 0.0 0.0 0.373597620977 0.0 0.0 0.0
There is also an option to show it in browser either as a static HTML or sortable javascript table.
In [11]:
truncated_data.show_in_browser()
truncated_data.show_in_browser(jsviewer=True)
Astropy also contains a number of "units" objects which can be very useful. We have to add these by hand at this point (I think, but correct me if you know of a trick for SDSS fits tables... it seems like there should be one.) So we'll create a new column that is a "coordinate" object.
In [12]:
data['coordinate'] = SkyCoord(ra=data['RA']*u.degree, dec=cat_data['DEC']*u.degree)
In [13]:
some_coordinate = data['coordinate'][data['SDSS_NAME'] == '000048.17+013313.6']
In [14]:
print(some_coordinate.galactic)
<SkyCoord (Galactic): (l, b) in deg
(97.88919198, -58.83396132)>
In [15]:
print(some_coordinate.ra.hms.h[0], some_coordinate.ra.hms.m[0], some_coordinate.ra.hms.s[0])
(0.0, 0.0, 48.176216966139698)
In [16]:
#Here's a way to plot the Mollweide projection of our data in degrees.
def plot_mwd(ra,dec,org=0,title='Mollweide projection', projection='mollweide', coordinate='equatorial'):
x = np.remainder(ra+360-org,360) # shift RA values
ind = x>180
x[ind] -=360 # scale conversion to [-180, 180]
x=-x # reverse the scale: East to the left
tick_labels = np.array([150, 120, 90, 60, 30, 0, 330, 300, 270, 240, 210])
tick_labels = np.remainder(tick_labels+360+org,360)
fig = plt.figure(figsize=(10, 5))
ax = fig.add_subplot(111, projection=projection, axisbg ='LightCyan')
ax.scatter(np.radians(x),np.radians(dec), marker='o', s=5, facecolor='green', edgecolor='', alpha=0.5) # convert degrees to radians
ax.set_xticklabels(tick_labels) # we add the scale on the x axis
ax.set_title(title)
ax.title.set_fontsize(15)
if coordinate == 'equatorial':
ax.set_xlabel("RA")
ax.set_ylabel("Dec")
elif coordinate == 'galactic':
ax.set_xlabel("Gal longitude")
ax.set_ylabel("Gal latitude")
else:
ax.set_xlabel("NA")
ax.set_ylabel("NA")
ax.xaxis.label.set_fontsize(12)
ax.yaxis.label.set_fontsize(12)
ax.grid(True)
In [17]:
plot_mwd(data['coordinate'].ra.degree,data['coordinate'].dec.degree, org=180.)
In [18]:
plot_mwd(data['coordinate'].galactic.l.degree,data['coordinate'].galactic.b.degree, org=0., coordinate='galactic')
In [19]:
plt.hist(data['Z_VI'])
Out[19]:
(array([ 2.53200000e+03, 1.30560000e+04, 5.14700000e+03,
2.56730000e+04, 2.86790000e+04, 9.59600000e+03,
2.60000000e+03, 4.35000000e+02, 9.90000000e+01,
5.00000000e+00]),
array([ 0.058 , 0.6377, 1.2174, 1.7971, 2.3768, 2.9565, 3.5362,
4.1159, 4.6956, 5.2753, 5.855 ]),
<a list of 10 Patch objects>)
In [20]:
# load a standard cosmology
cosmo = cos.WMAP9
plt.hist(cosmo.age(truncated_data['Z_VI']))
plt.xlabel('Gyrs')
Out[20]:
<matplotlib.text.Text at 0x113398e10>
In [21]:
# arcsec/kpc
plt.hist(cosmo.arcsec_per_kpc_proper(truncated_data['Z_VI']))
Out[21]:
(array([ 41., 6., 1., 0., 0., 0., 0., 0., 0., 1.]),
array([ 0.11598282, 0.12964881, 0.1433148 , 0.15698079, 0.17064677,
0.18431276, 0.19797875, 0.21164473, 0.22531072, 0.23897671,
0.25264269]),
<a list of 10 Patch objects>)
In [22]:
# luminosity distance
plt.hist(cosmo.luminosity_distance(truncated_data['Z_VI'])/1000)
plt.xlabel('Gpc')
Out[22]:
<matplotlib.text.Text at 0x11324e390>
In [23]:
plt.plot(np.sort(truncated_data['Z_VI']), np.sort(cosmo.H(truncated_data['Z_VI'])), '-')
plt.xlabel('z')
plt.ylabel(r'H in km sec$^{-1}$ Mpc$^{-1}$')
Out[23]:
<matplotlib.text.Text at 0x1144a0850>
In [24]:
# Temp of CMB as a function of redshift
plt.plot(np.sort(truncated_data['Z_VI']), np.sort(cosmo.Tcmb(truncated_data['Z_VI'])), '-')
plt.xlabel('z')
plt.ylabel(r'$T_{CMB}$ in K')
Out[24]:
<matplotlib.text.Text at 0x115052150>
In [25]:
# H_0
cosmo.H0
Out[25]:
$69.32 \; \mathrm{\frac{km}{Mpc\,s}}$
In [26]:
# What redshift is it when the Universe is 500 Myr old?
import astropy.units as u
cos.z_at_value(cosmo.age, 500 * u.Myr)
Out[26]:
9.6930902880244503
In [27]:
# Now, define our own cosmology, old-school H0 value, but keep the Universe
# flat
mycos = cos.FlatLambdaCDM(H0=100, Om0=0.3)
plt.hist(mycos.luminosity_distance(truncated_data['Z_VI'])/1000)
plt.xlabel('Gpc')
Out[27]:
<matplotlib.text.Text at 0x115052a10>
In [ ]:
Content source: privong/pythonclub
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