Loader for SDSS Imaging sample data
- data_homeoptional, default=None
Specify another download and cache folder for the datasets. By default all astroML data is stored in ‘~/astroML_data’.
- download_if_missingoptional, default=True
If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site.
- datarecarray, shape = (330753,)
record array containing imaging data
This data was selected from the SDSS database using the following SQL query:
SELECT round(p.ra,6) as ra, round(p.dec,6) as dec, p.run, --- comments are preceded by --- round(p.extinction_r,3) as rExtSFD, --- r band extinction from SFD round(p.modelMag_u,3) as uRaw, --- ISM-uncorrected model mags round(p.modelMag_g,3) as gRaw, --- rounding up model magnitudes round(p.modelMag_r,3) as rRaw, round(p.modelMag_i,3) as iRaw, round(p.modelMag_z,3) as zRaw, round(p.modelMagErr_u,3) as uErr, --- errors are important! round(p.modelMagErr_g,3) as gErr, round(p.modelMagErr_r,3) as rErr, round(p.modelMagErr_i,3) as iErr, round(p.modelMagErr_z,3) as zErr, round(p.psfMag_u,3) as psfRaw, --- psf magnitudes round(p.psfMag_g,3) as psfRaw, round(p.psfMag_r,3) as psfRaw, round(p.psfMag_i,3) as psfRaw, round(p.psfMag_z,3) as psfRaw, round(p.psfMagErr_u,3) as psfuErr, round(p.psfMagErr_g,3) as psfgErr, round(p.psfMagErr_r,3) as psfrErr, round(p.psfMagErr_i,3) as psfiErr, round(p.psfMagErr_z,3) as psfzErr, p.type, --- tells if a source is resolved or not (case when (p.flags & '16') = 0 then 1 else 0 end) as ISOLATED INTO mydb.SDSSimagingSample FROM PhotoTag p WHERE --- 10x2 sq.deg. p.ra > 0.0 and p.ra < 10.0 and p.dec > -1 and p.dec < 1 --- resolved and unresolved sources and (p.type = 3 OR p.type = 6) and --- '4295229440' is magic code for no --- DEBLENDED_AS_MOVING or SATURATED objects (p.flags & '4295229440') = 0 and --- PRIMARY objects only, which implies --- !BRIGHT && (!BLENDED || NODEBLEND || nchild == 0)] p.mode = 1 and --- adopted faint limit (same as about SDSS limit) p.modelMag_r < 22.5 --- the end of query
>>> from astroML.datasets import fetch_imaging_sample >>> data = fetch_imaging_sample() >>> # number of objects in dataset >>> data.shape (330753,) >>> # names of the first five columns >>> print(data.dtype.names[:5]) ('ra', 'dec', 'run', 'rExtSFD', 'uRaw') >>> print(data['ra'][:2]) [0.358174 0.358382] >>> print(data['dec'][:2]) [-0.508718 -0.551157]