Python Equivalents for IDL commands
This page lists Pythonic versions of some of the more common commands from the Goddard IDL astronomy library, plus some useful more general translations for e.g. plotting and IO commands. For a more generic, non-astro specific guide see NumPy for IDL Users or Mapping IDL to Python.
There are often multiple Python equivalents to a given IDL routine, in which case there are multiple entries listed in the Python column below.
Astronomical Calculations:
Coordinates, Dates, and Magnitudes
|
IDL
|
Python
|
function
|
| AIRTOVAC |
pyastrolib.airtovac(wave) astropysics.spec.air_to_vacuum(wave) |
Convert air wavelengths to vacuum wavelengths |
| VACTOAIR |
pyastrolib.vactoair(wave) astropysics.spec.vacuum_to_air(wave) |
Converts vacuum wavelengths to air wavelengths |
| ALTAZ2HADEC | pyastrolib.altaz2hadec(alt,az,lat) | Convert Horizon (Alt-Az) coordinates to Hour Angle and Declination |
| BPRECESS |
coords.position("12:34:45 -23:42:32").b1950() astropysics.coords.FK5Coordinates("12:34:45 -23:42:32").convert(FK4Coordinates) |
Convert coordinates from J2000 to B1950 |
| JPRECESS |
coords.position("12:34:45 -23:42:32").j2000() astropysics.coords.FK4Coordinates("12:34:45 -23:42:32").convert(FK5Coordinates) |
Convert coordinates from B1950 to J2000 |
| CCM_UNRED |
pyastrolib.ccm_unred(wave,flux,ebv) astropysics.obstools.CardelliExtinction(ebv).correctFlux(flux,wave) |
Deredden a flux vector using the CCM 1989 parameterization |
| DATE_CONV |
SLA_CALDJ? dayconv.py astropysics.obstools.calendar_to_jd(date)+additional astropysics.obstools.jd_to_? funcs |
Convert date to various formats, including Julian Date |
| DAYCONV |
dayconv.py astropysics.obstools.jd_to_calendar(jd) |
Converts Julian dates to Gregorian calendar dates |
| FLUX2MAG |
pyastrolib.flux2mag(flux) astropysics.phot.lum_to_mag(flux,0,1,fluxerr) |
Convert from flux (ergs/s/cm^2/A) to magnitudes |
| MAG2FLUX | astropysics.phot.mag_to_lum(mag,0,1,magerr) | Convert from magnitudes to flux |
| GLACTC |
coords.position("12:34:45 -23:42:32").galactic() astropysics.coords.ICRSCoordinates("12:34:45 -23:42:32").convert(GalacticCoordinates) |
Convert between celestial and Galactic coordinates. |
| HELIO_RV | Return the heliocentric radial velocity of a spectroscopic binary | |
| PLANCK |
pyastrolib.plank(wave,temp) astropysics.models.BlackbodyModel(T=temp)(wave) |
calculate the Planck function in units of ergs/cm2/s/A |
| SIXTY, RADEC |
coords.position((188.681,-22.326)).hmsdms() pyastrolib.sixty(dd) pyastrolib.radec(ra,dec,hours="") astropysics.coords.AngularCoordinate(188.681).hms or .dms |
Convert decimal number to sexigesimal |
| TEN |
coords.position("12:34:45 -23:42:32").dd() pyastrolib.ten(dd,mm="",ss="") astropysics.coords.AngularCoordinate("12:34:45").d |
Convert sexigesimal number to decimal |
Photometry
|
IDL/IRAF
|
Python
|
function
|
| astropysics.phot | ||
| find | pyastrolib.find | Find point sources within an image |
| synphot | pysynphot |
synthetic photometry software package suitable for either library or interactive use. Intended as a modern-language successor to the IRAF/STSDAS synphot package. create a throughput file (wavelength and throughput in dimensionless units between 0 and 1) for each band in your instrument, and a spectrum file or array (wavelength and flux) or black body as a function of temperature. Once you have those, you can simulate an observation and predict the magnitude, something like this:
import pysynphot as psyn |
FITS I/O
|
IDL
IRAF |
Python
|
function
|
| data=READFITS('file',header) | data=pyfits.open('file') | open fits file |
| CHECKFITS | data[0].verify() | verify file is FITS compliant |
| WRITEFITS(data,'newfile') | data.writeto('newfile') | write fits file to disk |
|
SXPAR() imheader |
data[0].header['KEY'] | Obtain value of header keyword |
|
SXADDPAR() hedit |
data[0].header['KEY']='value' OR data[0].header.update('KEY','value', 'comment') | Add or modify header keyword |
|
SXDELPAR hedit |
del data[0].header['KEY'] | Delete header keyword |
| SXADDHIST | data[0].header.add_history('history') | Add history keyword |
| SXADDHIST,/Comment | data[0].header.add_comment('comment') | Add comment keyword |
Image Manipulation
|
IDL
|
Python
|
function
|
| filter_image | scipy.ndimage.filters.gaussian_filter | Gaussian filter with options for handling the edges. |
Math and Statistics
|
IDL
|
Python
|
function
|
| smoothed=smooth(data,3,/edge_truncate) | smoothed=scipy.ndimage.filters.uniform_filter(data,size=3) | Smooth a multi-dimensional array. |
PLOTTING
also see NumPy for IDL users
|
IDL
|
Python
|
function
|
| most IDL plotting commands | matplotlib.pyplot.similarname | matplotlib has equivalent functions for all standard IDL plots |
| Veusz | Interactive GUI plotting package | |
| PLOTTERR | errorbar (matplotlib) | Plot Y vs. X with optional X and Y error bars |
| plot,x,y,psym=10 | pyplot.plot(x,y,drawstyle='steps-mid') | Plot a histogram-style stepped bar chart. |
ASCII I/O
|
IDL
|
Python
|
function
|
| FORPRINT | numpy.savetxt(filename,vec) | Print a set of vectors to Terminal or file. Inverse of READCOL. |
| READCOL |
numpy.loadtxt(filename) |
Read ascii tables
ATPy is the most flexible (reads non-ASCII data formats too), asciitable is the most configurable for custom ASCII table formats.
SExtractor format only? not modular, but intuitive. |
Array Manipulation
Numpy array manipulation rountines.
|
IDL
|
Python
|
function
|
| REFORM(array,d1,d2) | numpy.reshape(array,(d1,d2)) | Changes the dimensions of an array without changing the total number of elements. |
Miscellaneous (Non-Astronomy) Procedures
|
IDL
|
Python
|
function
|
| STRN(string) | str(string) | Converts anything to a string for printing. |