bossdata¶

bossdata.path module¶

Generate paths to BOSS data files.

The path module provides convenience methods for building the paths of frequently used data files. Most scripts will create a single Finder object using the default constructor for this purpose:

import bossdata.path
finder = bossdata.path.Finder()

This finder object is normally configured by the $BOSS_SAS_PATH and $BOSS_REDUX_VERSION environment variables and no other modules uses these variables, except through a a Finder object. These parameters can also be set by Finder constructor arguments. When neither the environment variables nor the constructor arguments are set, defaults appropriate for the most recent public data release (DR12) are used.

Finder objects never interact with any local or remote filesystems: use the bossdata.remote module to download data files and access them locally. See API Usage for recommendations on using the bossdata.path and bossdata.remote modules together.

class bossdata.path.Finder(sas_path=None, redux_version=None, verbose=True)[source]¶

Bases: object

Initialize a path finder object.

When the constructor is called with no arguments, it will raise a ValueError if either BOSS_SAS_PATH or BOSS_REDUX_VERSION is not set.

Parameters:	sas_path (str) – Location of the SAS root path to use, e.g., /sas/dr12. Will use the value of the BOSS_SAS_PATH environment variable if this is not set. redux_version (str) – String tag specifying the BOSS spectro reduction version to use, e.g., v5_7_0. Will use the value of the BOSS_REDUX_VERSION environment variable if this is not set.
Raises:	ValueError – No SAS root or redux version specified on the command line or via environment variables.

default_quasar_catalog_name = 'DR12Q'¶

Default quasar catalog name.

For more info about the BOSS quasar catalog, see http://www.sdss.org/dr12/algorithms/boss-dr12-quasar-catalog/

default_redux_version = 'v5_7_0'¶

Default to use when $BOSS_REDUX_VERSION is not set.

See Executable scripts and API Usage for details.

default_sas_path = '/sas/dr12/boss'¶

Default to use when $BOSS_SAS_PATH is not set.

See Executable scripts and API Usage for details.

get_plate_path(plate, filename=None)[source]¶

Get the path to the specified plate directory or file.

The returned path contains files that include all targets on the plate. Use the get_spec_path() method for the path of a single spectrum file.

This method only performs minimal checks that the requested plate number is valid.

Parameters:	plate (int) – Plate number, which must be positive. filename (str) – Name of a file within the plate directory to append to the returned path.
Returns:	Full path to the specified plate directory or file within this directory.
Return type:	str
Raises:	ValueError – Invalid plate number must be > 0.

get_plate_plan_path(plate, mjd, combined=True)[source]¶

Get the path to the specified plate plan file.

A combined plan may span several nearby MJDs, in which case the last MJD is the one used to identify the plan.

Parameters:	plate (int) – Plate number, which must be positive. mjd (int) – Modified Julian date of the observation, which must be > 45000. combined (bool) – Specifies the combined plan, which spans all MJDs associated with a coadd, but does not include calibration frames (arcs,flats) for a specific MJD.
Returns:	Full path to the requested plan file.
Return type:	str
Raises:	ValueError – Invalid plate or mjd inputs.

get_plate_spec_path(plate, mjd)[source]¶

Get the path to the file containing combined spectra for a whole plate.

Combined spectra for all exposures of a plate are packaged in spPlate files. As of DR12, these files are about 110Mb for 1000 spectra.

Parameters:	plate (int) – Plate number, which must be positive. mjd (int) – Modified Julian date of the observation, which must be > 45000.
Returns:	Full path to the requested plan file.
Return type:	str
Raises:	ValueError – Invalid plate or mjd inputs.

get_platelist_path()[source]¶

Get the location of the platelist summary file.

The platelist contains one row per observation (PLATE-MJD), unlike most other sources of metadata which contain one row per target (PLATE-MJD-FIBER).

get_quasar_catalog_path(catalog_name=None)[source]¶

Get the location of the quasar catalog file.

The quasar catalog is documented at http://www.sdss.org/dr12/algorithms/boss-dr12-quasar-catalog/. As of DR12, the file size is about 513Mb.

Parameters:	catalog_name (str) – BOSS quasar catalog name. Will use the get_default_quasar_catalog_name() method if this is not set.

get_sp_all_path(lite=True)[source]¶

Get the location of the metadata summary file.

The spAll file provides extensive metadata for all survey targets as a FITS file. There is also a smaller “lite” version containing a subset of this metadata in compressed text format. As of DR12, the full file size is about 10Gb and the lite file is about 115Mb.

Parameters:	lite (bool) – Specifies the “lite” version which contains all rows but only the most commonly used subset of columns. The lite version is a compressed (.gz) text data file, while the full version is a FITS file.

get_spec_path(plate, mjd, fiber, lite=True)[source]¶

Get the location of the spectrum file for the specified observation.

The DR12 data model for the returned files is at http://dr12.sdss3.org/datamodel/files/BOSS_SPECTRO_REDUX/RUN2D/spectra/PLATE4/spec.html but only HDUs 0-3 are included in the (default) lite format. Each lite (full) file is approximately 0.2Mb (1.7Mb) in size.

Use the get_plate_path() method for the path to files that include all targets on a plate.

This method only performs minimal checks that the requested plate-mjd-fiber are valid.

Parameters:	plate (int) – Plate number, which must be positive. mjd (int) – Modified Julian date of the observation, which must be > 45000. fiber (int) – Fiber number of the target on this plate, which must be in the range 1-1000 (or 1-640 for plate < 3510). lite (bool) – Specifies the “lite” version which contains only HDUs 0-3, so no per-exposure data is included.
Returns:	Full path to the spectrum file for the specified observation.
Return type:	str
Raises:	ValueError – Invalid plate, mjd or fiber inputs.

bossdata.remote module¶

Download BOSS data files from a remote server.

The remote module is responsible for downloading data files into a local filesystem using a directory layout that mirrors the remote data source. Most scripts will create a single Manager object using the default constructor for this purpose:

import bossdata.remote
mirror = bossdata.remote.Manager()

This mirror object is normally configured by the $BOSS_DATA_URL and $BOSS_LOCAL_ROOT environment variables and no other modules uses these variables, except through a a Manager object. These parameters can also be set by Manager constructor arguments. When neither the environment variables nor the constructor arguments are set, a default data URL appropriate for the most recent public data release (DR12) is used, and a temporary directory is created and used for the local root.

Manager objects have no knowledge of how data files are organized or named: use the bossdata.path module to build the paths of frequently used data files. See API Usage for recommendations on using the bossdata.path and bossdata.remote modules together.

class bossdata.remote.Manager(data_url=None, local_root=None, verbose=True)[source]¶

Bases: object

Manage downloads of BOSS data via HTTP.

The default mapping from remote to local filenames is to mirror the remote file hierarchy on the local disk. The normal mode of operation is to establish the local root for the mirror using the BOSS_LOCAL_ROOT environment variable. When the constructor is called with no arguments, it will raise a ValueError if either BOSS_DATA_URL or BOSS_LOCAL_ROOT is not set.

Parameters:

data_url (str) – Base URL of all BOSS data files. A trailing / on the URL is optional. If this arg is None, then the value of the BOSS_DATA_URL environment variable we be used instead. local_root (str) – Local path to use as the root of the locally mirrored file hierarchy. If this arg is None, then the value of the BOSS_LOCAL_ROOT environment variable, if any, will be used instead. If a value is provided, it should identify an existing writeable directory.

Raises:

ValueError – No such directory local_root or missing data_url.

default_data_url = 'http://dr12.sdss3.org'¶

Default to use when $BOSS_DATA_URL is not set.

See Executable scripts and API Usage for details.

download(remote_path, local_path, chunk_size=4096, progress_min_size=10)[source]¶

Download a single BOSS data file.

Downloads are streamed so that the memory requirements are independent of the file size. During the download, the file is written to its final location but with ‘.downloading’ appended to the file name. This means than any download that is interrupted or fails will normally not lead to an incomplete file being returned by a subsequent call to get(). Instead, the file will be re-downloaded. Tere is no facility for resuming a previous partial download. After a successful download, the file is renamed to its final location and has its permission bits set to read only (to prevent accidental modifications of files that are supposed to exactly mirror the remote file system).

Parameters:	remote_path (str) – The full path to the remote file relative to the remote server root, which should normally be obtained using bossdata.path methods. local_path (str) – The (absolute or relative) path of the local file to write. chunk_size (int) – Size of data chunks to use for the streaming download. Larger sizes will potentially download faster but also require more memory. progress_min_size (int) – Display a text progress bar for any downloads whose size in Mb exceeds this value. No progress bar will ever be shown if this value is None.
Returns:	Absolute local path of the downloaded file.
Return type:	str
Raises:	ValueError – local_path directory does not exist. RuntimeError – HTTP request returned an error status.

get(remote_path, progress_min_size=10, auto_download=True, local_paths=None)[source]¶

Get a local file that mirrors a remote file, downloading the file if necessary.

Parameters:	remote_path (str,iterable) – This arg will normally be a single string but can optionally be an iterable over strings for some advanced functionality. Strings give the full path to a remote file and should normally be obtained using bossdata.path methods. When passing an iterable, the first item specifies the desired file and subsequent items specify acceptable substitutes. If the desired file is not already available locally but at least one substitute file is locally available, this method immediately returns the first substitute without downloading the desired file. If no substitute is available, the desired file is downloaded and returned. progress_min_size (int) – Display a text progress bar for any downloads whose size in Mb exceeds this value. No progress bar will ever be shown if this value is None. auto_download (bool) – Automatically download the file to the local mirror if necessary. If this is not set and the file is not already mirrored, then a RuntimeError occurs. local_paths (list) – When this arg is not None, the local paths corresponding to each input remote path are stored to this arg, resulting in a list of the same size as the input remote_path (or length 1 if remote_path is a single string). This enables the following pattern for detecting when a substitution has ocurred: mirror = bossdata.remote.Manager() remote_paths = [the_preferred_path, a_backup_path] local_paths = [] local_path = mirror.get(remote_paths, local_paths=local_paths) if local_path != local_paths[0]: print('substituted {} for {}.'.format(local_path, local_paths[0]))
Returns:	Absolute local path of the local file that mirrors the remote file.
Return type:	str
Raises:	RuntimeError – File is not already mirrored and auto_download is False.

local_path(remote_path)[source]¶

Get the local path corresponding to a remote path.

Does not check that the file or its parent directory exists. Use get() to ensure that the file exists, downloading it if necessary.

Parameters:	remote_path (str) – The full path to the remote file relative to the remote server root, which should normally be obtained using bossdata.path methods.
Returns:	Absolute local path of the local file that mirrors the remote file.
Return type:	str
Raises:	RuntimeError – No local_root specified when this manager was created.

bossdata.meta module¶

Support for querying the metadata associated with BOSS observations.

class bossdata.meta.Database(finder=None, mirror=None, lite=True, quasar_catalog=False, quasar_catalog_name=None, platelist=False, verbose=False)[source]¶

Bases: object

Initialize a searchable database of BOSS observation metadata.

Parameters:

finder (bossdata.path.Finder) – Object used to find the names of BOSS data files. If not specified, the default Finder constructor is used. mirror (bossdata.remote.Manager) – Object used to interact with the local mirror of BOSS data. If not specified, the default Manager constructor is used. lite (bool) – Use the “lite” metadata format, which is considerably faster but only provides a subset of the most commonly accessed fields. Ignored if either quasar_catalog or platelist is True. quasar_catalog (bool) – Initialize database using the BOSS quasar catalog instead of spAll. quasar_catalog_name (str) – The name of the BOSS quasar catalog to use, or use the default if this is None. platelist (bool) – Initialize the database use the platelist catalog instead of spAll.

prepare_columns(column_names)[source]¶

Validate column names and lookup their types.

Parameters:	column_names (str) – Comma-separated list of column names or the special value ‘*’ to indicate all available columns.
Returns:	Tuple (names,dtypes) of lists of column names and corresponding numpy data types. Use zip() to convert the return value into a recarray dtype.
Return type:	tuple
Raises:	ValueError – Invalid column name.

select_all(what='*', where=None, sort=None, max_rows=100000)[source]¶

Fetch all results of an SQL select query.

Since this method loads all the results into memory, it is not suitable for queries that are expected to return a large number of rows. Instead, use select_each() for large queries.

Parameters:	what (str) – Comma separated list of column names to return or ‘*’ to return all columns. where (str) – SQL selection clause or None for no filtering. Reserved column names such as PRIMARY must be escaped with backticks in this clause. max_rows (int) – Maximum number of rows that will be returned.
Returns:	astropy.table.Table: Table of results with column names matching those in the database, and column types inferred automatically. Returns None if no rows are selected.
Return type:	:class
Raises:	RuntimeError – failed to execute query.

select_each(what='*', where=None)[source]¶

Iterate over the results of an SQL select query.

This method is normally used as an iterator, e.g.

for row in select(...):

# each row is a tuple of values ...

Since this method does not load all the results of a large query into memory, it is suitable for queries that are expected to return a large number of rows. For smaller queries, the select_all() method might be more convenient.

Parameters:	what (str) – Comma separated list of column names to return or ‘*’ to return all columns. where (str) – SQL selection clause or None for no filtering. Reserved column names such as PRIMARY must be escaped with backticks in this clause.
Raises:	sqlite3.OperationalError – failed to execute query.

bossdata.meta.create_meta_full(catalog_path, db_path, verbose=True, primary_key='(PLATE, MJD, FIBER)')[source]¶

Create the “full” meta database from a locally mirrored catalog file.

The created database renames FIBERID to FIBER and has a composite primary index on the (PLATE,MJD,FIBER) columns. Sub-array columns are also unrolled: see sql_create_table() for details. The conversion takes about 24 minutes on a laptop with sufficient memory (~4 Gb). During the conversion, the file being written has the extension .building appended, then this extension is removed (and the file is made read only) once the conversion successfully completes. This means that if the conversion is interrupted for any reason, it will be restarted the next time this function is called and you are unlikely to end up with an invalid database file.

Parameters:	catalog_path (str) – Absolute local path of the “full” catalog file, which is expected to be a FITS file. db_path (str) – Local path where the corresponding sqlite3 database will be written.

bossdata.meta.create_meta_lite(sp_all_path, db_path, verbose=True)[source]¶

Create the “lite” meta database from a locally mirrored spAll file.

The created database has a composite primary index on the (PLATE,MJD,FIBER) columns and the input columns MODELFLUX0..4 are renamed MODELFLUX_0..4 to be consistent with their names in the full database after sub-array un-rolling.

The DR12 spAll lite file is ~115Mb and converts to a ~470Mb SQL database file. The conversion takes about 3 minutes on a laptop with sufficient memory (~4 Gb). During the conversion, the file being written has the extension .building appended, then this extension is removed (and the file is made read only) once the conversion successfully completes. This means that if the conversion is interrupted for any reason, it will be restarted the next time this function is called and you are unlikely to end up with an invalid database file.

Parameters:	sp_all_path (str) – Absolute local path of the “lite” spAll file, which is expected to be a gzipped ASCII data file. db_path (str) – Local path where the corresponding sqlite3 database will be written.

bossdata.meta.get_plate_mjd_list(plate, finder=None, mirror=None)[source]¶

Return the list of MJD values when a plate was observed.

Uses a query of the platelist, so this file will be automatically downloaded if necessary. Only MJD values for which the observation data quality is marked “good” will be returned.

Parameters:	plate (int) – Plate number. finder (bossdata.path.Finder) – Object used to find the names of BOSS data files. If not specified, the default Finder constructor is used. mirror (bossdata.remote.Manager) – Object used to interact with the local mirror of BOSS data. If not specified, the default Manager constructor is used.
Returns:	A list of MJD values when this plate was observed. The list will be empty if this plate has never been observed.
Return type:	list

bossdata.meta.sql_create_table(table_name, recarray_dtype, renaming_rules={}, primary_key=None)[source]¶

Prepare an SQL statement to create a database for a numpy structured array.

Any columns in the structured array data type that are themselves arrays will be unrolled to a list of scalar columns with names COLNAME_I for element [i] of a 1D array and COLNAME_I_J for element [i,j] of a 2D array, etc, with indices I,J,... starting from zero.

Parameters:	table_name (str) – Name to give the new table. recarray_dtype – Numpy structured array data type that defines the columns to create. renaming_rules (dict) – Dictionary of rules for renaming columns. There are no explicit checks that these rules do not create duplicate column names or that all rules are applied. primary_key (str) – Column name(s) to use as the primary key, after apply renaming rules. No index is created if this argument is None.
Returns:	Tuple (sql,num_cols) where sql is an executable SQL statement to create the database and num_cols is the number of columns created.
Return type:	tuple
Raises:	ValueError – Cannot map data type to SQL.

bossdata.spec module¶

Access spectroscopic data for a single BOSS target.

class bossdata.spec.Exposures(header)[source]¶

Bases: object

Table of exposure info extracted from FITS header keywords.

Parse the NEXP and EXPIDnn keywords that are present in the header of HDU0 in spPlate and spec FITS files.

The constructor initializes the table attribute with column names offset, camera, science, flat and arc, and creates one row for each keyword EXPIDnn, where offset equals the keyword sequence number nn, camera is one of b1, b2, r1, r2, and the remaining columns record the science and calibration exposure numbers.

Use get_info() to retrieve the n-th exposure for a particular camera (b1, b2, r1, r2). Note that when this class is initialized from a spec file header, it will only describe the two cameras of a single spectrograph (b1+r1 or b2+r2). The num_by_camera attribute is a dictionary of ints indexed by camera that records the number of science exposures available for that camera.

Parameters:	header (dict) – dictionary of FITS header keyword, value pairs.

Returns:

get_info(exposure_index, camera)[source]¶

Get information about a single camera exposure.

Parameters:	exposure_index (int) – The sequence number for the requested camera exposure, in the range 0 - (num_exposures[camera]-1). camera (str) – One of b1,b2,r1,r2.
Returns:	A structured array with information about the requested exposure, corresponding to one row of our table attribute.
Raises:	ValueError – Invalid exposure_index or camera. RuntimeError – Exposure not present.

class bossdata.spec.SpecFile(path)[source]¶

Bases: object

A BOSS spec file containing summary data for a single target.

A spec file contains co-added spectra for a single target of an observation. This class supports the full version described in the data model as well as a lite version that does not contain the per-exposure HDUs with indices >= 4. Use the lite attribute to detect which version an object represents.

To read all co-added spectra of an observation use bossdata.plate.PlateFile. Individual exposures of a half-plate can be read using bossdata.plate.FrameFile.

The plate, mjd and fiber attributes specify the target observation. The info attribute contains this target’s row from spAll as a structured numpy array, so its metadata can be accessed as info['OBJTYPE'], etc.

Use get_valid_data() to access this target’s spectra, or the exposures attribute for a list of exposures used in the coadd (see bossdata.plate.Plan for alternative information about the exposures used in a coadd.) The num_exposures attribute gives the number of science exposures used for this target’s co-added spectrum (counting a blue+red pair as one exposure). Use get_exposure_name() to locate files associated the individual exposures used for this co-added spectrum.

This class is only intended for reading the BOSS spec file format, so generic operations on spectroscopic data (redshifting, resampling, etc) are intentionally not included here, but are instead provided in the speclite package.

Parameters:	path (str) – Local path of the spec FITS file to use. This should normally be obtained via bossdata.path.Finder.get_spec_path() and can be automatically mirrored via bossdata.remote.Manager.get() or using the bossfetch script. The file is opened in read-only mode so you do not need write privileges.

get_exposure_hdu(exposure_index, camera)[source]¶

Lookup the HDU for one exposure.

This method will not work on “lite” files, which do not include individual exposures.

Parameters:	exposure_index (int) – Individual exposure to use, specified as a sequence number starting from zero, for the first exposure, and increasing up to self.num_exposures-1. camera (str) – Which camera to use. Must be one of b1,b2,r1,r2.
Returns:	The HDU containing data for the requested exposure.
Return type:	hdu
Raises:	RuntimeError – individual exposures not available in lite file.

get_exposure_name(sequence_number, band, ftype='spCFrame')[source]¶

Get the file name of a single science exposure data product.

Use the exposure name to locate FITS data files associated with individual exposures. The supported file types are: spCFrame, spFrame, spFluxcalib and spFluxcorr. This method is analogous to bossdata.plate.Plan.get_exposure_name(), but operates for a single target and only knows about exposures actually used in the final co-add.

Parameters:	sequence_number (int) – Science exposure sequence number, counting from zero. Must be less than our num_exposures attribute. band (str) – Must be ‘blue’ or ‘red’. ftype (str) – Type of exposure file whose name to return. Must be one of spCFrame, spFrame, spFluxcalib, spFluxcorr. An spCFrame is assumed to be uncompressed, and all other files are assumed to be compressed.
Returns:	Exposure name of the form [ftype]-[cc]-[eeeeeeee].[ext] where [cc] identifies the spectrograph (one of b1,r1,b2,r2) and [eeeeeeee] is the zero-padded exposure number. The extension [ext] is “fits” for spCFrame files and “fits.gz” for all other file types.
Return type:	str
Raises:	ValueError – one of the inputs is invalid.

get_pixel_mask(exposure_index=None, camera=None)[source]¶

Get the pixel mask for a specified exposure or the combined coadd.

Returns the and_mask for coadded spectra. The entire mask is returned, including any pixels with zero inverse variance.

Parameters:	exposure_index (int) – Individual exposure to use, specified as a sequence number starting from zero, for the first exposure, and increasing up to self.num_exposures-1. Uses the co-added spectrum when the value is None. camera (str) – Which camera to use. Must be either ‘b1’, ‘b2’ (blue) or ‘r1’, ‘r2’ (red) unless exposure_index is None, in which case this argument is ignored.
Returns:	Array of integers, one per pixel, encoding the mask bits defined in bossdata.bits.SPPIXMASK (see also http://www.sdss3.org/dr10/algorithms/bitmask_sppixmask.php).
Return type:	numpy.ndarray

get_valid_data(exposure_index=None, camera=None, pixel_quality_mask=None, include_wdisp=False, include_sky=False, use_ivar=False, use_loglam=False, fiducial_grid=False)[source]¶

Get the valid data for a specified exposure or the combined coadd.

You will probably find yourself using this idiom often:

data = spec.get_valid_data(...)
wlen,flux,dflux = data['wavelength'][:],data['flux'][:],data['dflux'][:]

Parameters:	exposure_index (int) – Individual exposure to use, specified as a sequence number starting from zero, for the first exposure, and increasing up to self.num_exposures-1. Uses the co-added spectrum when the value is None. camera (str) – Which camera to use. Must be either ‘b1’, ‘b2’ (blue) or ‘r1’, ‘r2’ (red) unless exposure_index is None, in which case this argument is ignored. pixel_quality_mask (int) – An integer value interpreted as a bit pattern using the bits defined in bossdata.bits.SPPIXMASK (see also http://www.sdss3.org/dr10/algorithms/bitmask_sppixmask.php). Any bits set in this mask are considered harmless and the corresponding spectrum pixels are assumed to contain valid data. When accessing the coadded spectrum, this mask is applied to the AND of the masks for each individual exposure. No mask is applied if this value is None. include_wdisp – Include a wavelength dispersion column in the returned data. include_sky – Include a sky flux column in the returned data. use_ivar – Replace dflux with ivar (inverse variance) in the returned data. use_loglam – Replace wavelength with loglam (log10(wavelength)) in the returned data. fiducial_grid – Return co-added data using the fiducial wavelength grid. If False, the returned array uses the native grid of the SpecFile, which generally trims pixels on both ends that have zero inverse variance. Set this value True to ensure that all co-added spectra use aligned wavelength grids when this matters.
Returns:	Masked array of per-pixel records. Pixels with no valid data are included but masked. The record for each pixel has at least the following named fields: wavelength in Angstroms (or loglam), flux and dflux in 1e-17 ergs/s/cm2/Angstrom (or flux and ivar). Wavelength values are strictly increasing and dflux is calculated as ivar**-0.5 for pixels with valid data. Optional fields are wdisp in constant-log10-lambda pixels and sky in 1e-17 ergs/s/cm2/Angstrom. The wavelength (or loglam) field is never masked and all other fields are masked when ivar is zero or a pipeline flag is set (and not allowed by pixel_quality_mask).
Return type:	numpy.ma.MaskedArray
Raises:	ValueError – fiducial grid is not supported for individual exposures. RuntimeError – co-added wavelength grid is not aligned with the fiducial grid.

bossdata.spec.fiducial_loglam[source]¶

Array of fiducial log10(wavelength in Angstroms) covering all spectra.

Lookup the log10(wavelength) or wavelength corresponding to a particular integral pixel index using:

>>> fiducial_loglam[100]
3.554100305027835
>>> 10**fiducial_loglam[100]
3581.7915291606305

The bounding wavelengths of this range are:

>>> 10**fiducial_loglam[[0,-1]]
array([  3500.26      ,  10568.18251472])

The SpecFile.get_valid_data() and PlateFile.get_valid_data() methods provide a fiducial_grid option that returns data using this grid.

bossdata.spec.fiducial_pixel_index_range = (0, 4800)¶

Range of fiducial pixel indices that covers all spectra.

Use get_fiducial_pixel_index() to calculate fiducial pixel indices.

bossdata.spec.get_fiducial_pixel_index(wavelength)[source]¶

Convert a wavelength to a fiducial pixel index.

The fiducial wavelength grid used by all SDSS co-added spectra is logarithmically spaced:

wavelength = wavelength0 * 10**(coef * index)

The value coef = 1e-4 is encoded in the FITS HDU headers of SDSS coadded data files with the keyword CD1_1 (and sometimes also COEFF1). The value of wavelength0 defines index = 0 and is similarly encoded as CRVAL1 (and sometimes also COEFF0). However, its value is not constant between different SDSS co-added spectra because varying amounts of invalid data are trimmed. This function adopts the constant value 3500.26 Angstrom corresponding to index = 0:

>>> get_fiducial_pixel_index(3500.26)
0.0

Note that the return value is a float so that wavelengths not on the fiducial grid can be converted and detected:

>>> get_fiducial_pixel_index(3500.5)
0.29776960129179741

The calculation is automatically broadcast over an input wavelength array:

>>> wlen = np.arange(4000,4400,100)
>>> get_fiducial_pixel_index(wlen)
array([ 579.596863  ,  686.83551692,  791.4898537 ,  893.68150552])

Use fiducial_pixel_index_range for an index range that covers all SDSS spectra and fiducial_loglam to covert integer indices to wavelengths.

Parameters:	wavelength (float) – Input wavelength in Angstroms.
Returns:	Array of floating-point indices relative to the fiducial wavelength grid.
Return type:	numpy.ndarray

bossdata.bits module¶

Define bit masks used in BOSS data and support symbolic operations on masks.

The SDSS bitmasks are documented at http://www.sdss3.org/dr10/algorithms/bitmasks.php. The authoritative definition of the bit masks is the file http://www.sdss3.org/svn/repo/idlutils/trunk/data/sdss/sdssMaskbits.par. A copy of this file is included in this package’s top-level directory and was used to automatically generate the bitmask definitions in this file with the extract_sdss_bitmasks() function.

class bossdata.bits.ANCILLARY_TARGET1[source]¶

Bases: object

BOSS survey target flags for ancillary programs

RQSS_STMC¶

int

(1<<35) defined in rqss090630.descr

BLAZGXQSO¶

int

(1<<53) defined in anderson-blazar.par

BLAZR¶

int

(1<<7) defined in brandtxmm-andersonblazar-merged.descr

SPOKE¶

int

(1<<41) defined in BOSS_slowpokes_v2.descr

VARS¶

int

(1<<5) defined in blake_boss_v2.descr

QSO_RADIO_AAL¶

int

(1<<26) defined in qsoals_v2.descr

FAINTERM¶

int

(1<<47) defined in sd3targets_final.descr

RQSS_SFC¶

int

(1<<33) defined in rqss090630.descr

CHANDRAV1¶

int

(1<<57) defined in haggard-sf-accrete.fits

BRIGHTGAL¶

int

(1<<21) defined in bright_gal_v3.descr

CXOBRIGHT¶

int

(1<<58) defined in brandt-xray.par

QSO_HIZ¶

int

(1<<30) defined in sdss3_fan.descr

RVTEST¶

int

(1<<49) defined in redkg.descr

GAL_NEAR_QSO¶

int

(1<<62) defined in weiner-qso-sightline.fits

MTEMP¶

int

(1<<63) defined in blake-transient-v3.fits

BLAZGXR¶

int

(1<<54) defined in anderson-blazar.par

SPEC_SN¶

int

(1<<40) defined in ancillary_supernova_hosts_v5.descr

CXOGRIZ¶

int

(1<<59) defined in brandt-xray.par

QSO_AAL¶

int

(1<<22) defined in qsoals_v2.descr

AMC¶

int

(1<<0) defined in blake_boss_v2.descr

BLAZXRSAM¶

int

(1<<9) defined in brandtxmm-andersonblazar-merged.descr

QSO_RIZ¶

int

(1<<31) defined in sdss3_fan.descr

FBQSBAL¶

int

(1<<15) defined in master-BAL-targets.descr

BLAZXR¶

int

(1<<8) defined in brandtxmm-andersonblazar-merged.descr

RQSS_SF¶

int

(1<<32) defined in rqss090630.descr

BLUE_RADIO¶

int

(1<<56) defined in tremonti-blue-radio.fits.gz

RED_KG¶

int

(1<<48) defined in redkg.descr

BLAZGVAR¶

int

(1<<6) defined in brandtxmm-andersonblazar-merged.descr

QSO_AALS¶

int

(1<<23) defined in qsoals_v2.descr

PREVBAL¶

int

(1<<19) defined in master-BAL-targets.descr

LBQSBAL¶

int

(1<<16) defined in master-BAL-targets.descr

QSO_RADIO¶

int

(1<<25) defined in qsoals_v2.descr

QSO_NOAALS¶

int

(1<<28) defined in qsoals_v2.descr

XMMBRIGHT¶

int

(1<<11) defined in brandtxmm-andersonblazar-merged.descr

ELG¶

int

(1<<61) defined in kneib-cfht-elg.fits

QSO_GRI¶

int

(1<<29) defined in sdss3_fan.descr

FLARE2¶

int

(1<<2) defined in blake_boss_v2.descr

SN_GAL3¶

int

(1<<38) defined in ancillary_supernova_hosts_v5.descr

FLARE1¶

int

(1<<1) defined in blake_boss_v2.descr

QSO_RADIO_IAL¶

int

(1<<27) defined in qsoals_v2.descr

HPM¶

int

(1<<3) defined in blake_boss_v2.descr

SN_GAL2¶

int

(1<<37) defined in ancillary_supernova_hosts_v5.descr

FAINTERL¶

int

(1<<46) defined in sd3targets_final.descr

BLAZGRFLAT¶

int

(1<<50) defined in anderson-blazar.par

SN_GAL1¶

int

(1<<36) defined in ancillary_supernova_hosts_v5.descr

VARBAL¶

int

(1<<20) defined in master-BAL-targets.descr

RQSS_STM¶

int

(1<<34) defined in rqss090630.descr

OTBAL¶

int

(1<<18) defined in master-BAL-targets.descr

BLAZGX¶

int

(1<<52) defined in anderson-blazar.par

XMMRED¶

int

(1<<14) defined in brandtxmm-andersonblazar-merged.descr

BLAZGRQSO¶

int

(1<<51) defined in anderson-blazar.par

CXORED¶

int

(1<<60) defined in brandt-xray.par

BRIGHTERL¶

int

(1<<44) defined in sd3targets_final.descr

BRIGHTERM¶

int

(1<<45) defined in sd3targets_final.descr

LOW_MET¶

int

(1<<4) defined in blake_boss_v2.descr

XMMGRIZ¶

int

(1<<12) defined in brandtxmm-andersonblazar-merged.descr

SN_LOC¶

int

(1<<39) defined in ancillary_supernova_hosts_v5.descr

WHITEDWARF_NEW¶

int

(1<<42) defined in WDv5_eisenste_fixed.descr

QSO_IAL¶

int

(1<<24) defined in qsoals_v2.descr

WHITEDWARF_SDSS¶

int

(1<<43) defined in WDv5_eisenste_fixed.descr

XMMHR¶

int

(1<<13) defined in brandtxmm-andersonblazar-merged.descr

ODDBAL¶

int

(1<<17) defined in master-BAL-targets.descr

BLAZXRVAR¶

int

(1<<10) defined in brandtxmm-andersonblazar-merged.descr

AMC = 1

BLAZGRFLAT = 1125899906842624

BLAZGRQSO = 2251799813685248

BLAZGVAR = 64

BLAZGX = 4503599627370496

BLAZGXQSO = 9007199254740992

BLAZGXR = 18014398509481984

BLAZR = 128

BLAZXR = 256

BLAZXRSAM = 512

BLAZXRVAR = 1024

BLUE_RADIO = 72057594037927936

BRIGHTERL = 17592186044416

BRIGHTERM = 35184372088832

BRIGHTGAL = 2097152

CHANDRAV1 = 144115188075855872

CXOBRIGHT = 288230376151711744

CXOGRIZ = 576460752303423488

CXORED = 1152921504606846976

ELG = 2305843009213693952

FAINTERL = 70368744177664

FAINTERM = 140737488355328

FBQSBAL = 32768

FLARE1 = 2

FLARE2 = 4

GAL_NEAR_QSO = 4611686018427387904

HPM = 8

LBQSBAL = 65536

LOW_MET = 16

MTEMP = 9223372036854775808L

ODDBAL = 131072

OTBAL = 262144

PREVBAL = 524288

QSO_AAL = 4194304

QSO_AALS = 8388608

QSO_GRI = 536870912

QSO_HIZ = 1073741824

QSO_IAL = 16777216

QSO_NOAALS = 268435456

QSO_RADIO = 33554432

QSO_RADIO_AAL = 67108864

QSO_RADIO_IAL = 134217728

QSO_RIZ = 2147483648

RED_KG = 281474976710656

RQSS_SF = 4294967296

RQSS_SFC = 8589934592

RQSS_STM = 17179869184

RQSS_STMC = 34359738368

RVTEST = 562949953421312

SN_GAL1 = 68719476736

SN_GAL2 = 137438953472

SN_GAL3 = 274877906944

SN_LOC = 549755813888

SPEC_SN = 1099511627776

SPOKE = 2199023255552

VARBAL = 1048576

VARS = 32

WHITEDWARF_NEW = 4398046511104

WHITEDWARF_SDSS = 8796093022208

XMMBRIGHT = 2048

XMMGRIZ = 4096

XMMHR = 8192

XMMRED = 16384

class bossdata.bits.ANCILLARY_TARGET2[source]¶

Bases: object

additional BOSS survey target flags for ancillary programs

QSO_WISE_FULL_SKY¶

int

(1<<10) defined in none

KQSO_BOSS¶

int

(1<<2) defined in mcmahon-ukidss.fits

TAU_STAR¶

int

(1<<52) defined in knapp_taurus.descr

_2MASSFILL¶

int

(1<<51) defined in rocksi_ges_segue.descr

LRG_ROUND3¶

int

(1<<22) defined in newman.descr

QSO_WISE_SUPP¶

int

(1<<9) defined in BOSS_QSO_targets_July_WISE.descr

DISKEMITTER_REPEAT¶

int

(1<<13) defined in shen.descr

SEQUELS_ELG¶

int

(1<<34) defined in sequels_elg.descr

ELAIS_N1_GMRT_GARN¶

int

(1<<60) LOFAR-selected target

QSO_VAR_SDSS¶

int

(1<<8) defined in VARQSO.descr

SDSSFILLER¶

int

(1<<38) defined in rockosi_ges_segue.descr

QSO_EBOSS_W3_ADM¶

int

(1<<31) defined in myers_eboss_qso_w3.descr

HIZ_LRG¶

int

(1<<21) defined in newman.descr

RADIO_2LOBE_QSO¶

int

(1<<5) defined in kimball-radio-2lobe-qso.fits.gz

COROTGES¶

int

(1<<49) defined in rocksi_ges_segue.descr

COROTGESAPOG¶

int

(1<<48) defined in rocksi_ges_segue.descr

HIZQSO82¶

int

(1<<0) defined in mcgreer-hizqso.fits

STRIPE82BCG¶

int

(1<<6) defined in alexie-bcgs.fits

KOE2068_STAR¶

int

(1<<44) defined in knapp_ngc2068.descr

QSO_VAR_LF¶

int

(1<<27) defined in palanque_str82.descr

SPIDERS_PILOT¶

int

(1<<25) defined in GreenMerloni_MD01.descr

ELAIS_N1_LOFAR¶

int

(1<<58) LOFAR-selected target

HIZQSOIR¶

int

(1<<1) defined in mcgreer-hizqso.fits

ELAIS_N1_JVLA¶

int

(1<<62) LOFAR-selected target

QSO_DEEP¶

int

(1<<56) DEEP QSO described in QSO_DEEP_LBG.descr

XMM_PRIME¶

int

(1<<32) defined in georgekaksi_xmmxll.descr

TDSS_SPIDERS_PILOT¶

int

(1<<26) defined in GreenMerloni_MD01.descr

XMMSDSS¶

int

(1<<11) defined in georgakakis.descr

KOE2068BSTAR¶

int

(1<<46) defined in knapp_ngc2068.descr

SPOKE2¶

int

(1<<17) defined in dhital.descr

LBG¶

int

(1<<57) LBG described in QSO_DEEP_LBG.descr

RM_TILE1¶

int

(1<<54) reverberation mapping, high priority

CLUSTER_MEMBER¶

int

(1<<16) defined in finoguenov_auxBOSS.descr

GES¶

int

(1<<35) defined in rockosi_ges_segue.descr

ELAIS_N1_FIRST¶

int

(1<<59) LOFAR-selected target

FAINT_ELG¶

int

(1<<18) defined in comparat.descr

SEQUELS_ELG_LOWP¶

int

(1<<39) defined in sequels_elg.descr

WISE_BOSS_QSO¶

int

(1<<14) defined in ross_wisebossqso.descr

PTF_GAL¶

int

(1<<19) defined in kasliwal.descr

_25ORI_WISE_W3¶

int

(1<<41) defined in knapp_25ori.descr

SEGUE1¶

int

(1<<36) defined in rockosi_ges_segue.descr

SEGUE2¶

int

(1<<37) defined in rockosi_ges_segue.descr

_25ORI_WISE¶

int

(1<<40) defined in knapp_25ori.descr

KOE2023_STAR¶

int

(1<<43) defined in knapp_ngc2023.descr

KOEKAP_STAR¶

int

(1<<42) defined in knapp_kappaori.descr

TDSS_PILOT_SNHOST¶

int

(1<<29) defined in TDSS_SPIDERS_MD03.descr

IAMASERS¶

int

(1<<12) defined in zaw.descr

XMM_SECOND¶

int

(1<<33) defined in georgekaksi_xmmxll.descr

KOEKAPBSTAR¶

int

(1<<47) defined in knapp_kappaori.descr

KOE2023BSTAR¶

int

(1<<45) defined in knapp_ngc2023.descr

ELAIS_N1_GMRT_TAYLOR¶

int

(1<<61) LOFAR-selected target

QSO_XD_KDE_PAIR¶

int

(1<<15) defined in myers.descr

QSO_SUPPZ¶

int

(1<<7) defined in qso_suppz.descr

QSO_VAR_FPG¶

int

(1<<4) defined in nathalie-ancillary3.par

RM_TILE2¶

int

(1<<55) reverberation mapping, low priority

QSO_STD¶

int

(1<<20) defined in margala.descr

WISE_COMPLETE¶

int

(1<<23) defined in weiner_wise.descr

QSO_VAR¶

int

(1<<3) defined in butler-variable.fits.gz

TDSS_PILOT¶

int

(1<<24) defined in GreenMerloni_MD01.descr

TDSS_PILOT_PM¶

int

(1<<28) defined in TDSS_SPIDERS_MD03.descr

SEQUELS_TARGET¶

int

(1<<53) any target in SEQUELS darktime program

FAINT_HIZ_LRG¶

int

(1<<30) defined in newman_lrg_w3.descr

APOGEE¶

int

(1<<50) defined in rocksi_ges_segue.descr

APOGEE = 1125899906842624

CLUSTER_MEMBER = 65536

COROTGES = 562949953421312

COROTGESAPOG = 281474976710656

DISKEMITTER_REPEAT = 8192

ELAIS_N1_FIRST = 576460752303423488

ELAIS_N1_GMRT_GARN = 1152921504606846976

ELAIS_N1_GMRT_TAYLOR = 2305843009213693952

ELAIS_N1_JVLA = 4611686018427387904

ELAIS_N1_LOFAR = 288230376151711744

FAINT_ELG = 262144

FAINT_HIZ_LRG = 1073741824

GES = 34359738368

HIZQSO82 = 1

HIZQSOIR = 2

HIZ_LRG = 2097152

IAMASERS = 4096

KOE2023BSTAR = 35184372088832

KOE2023_STAR = 8796093022208

KOE2068BSTAR = 70368744177664

KOE2068_STAR = 17592186044416

KOEKAPBSTAR = 140737488355328

KOEKAP_STAR = 4398046511104

KQSO_BOSS = 4

LBG = 144115188075855872

LRG_ROUND3 = 4194304

PTF_GAL = 524288

QSO_DEEP = 72057594037927936

QSO_EBOSS_W3_ADM = 2147483648

QSO_STD = 1048576

QSO_SUPPZ = 128

QSO_VAR = 8

QSO_VAR_FPG = 16

QSO_VAR_LF = 134217728

QSO_VAR_SDSS = 256

QSO_WISE_FULL_SKY = 1024

QSO_WISE_SUPP = 512

QSO_XD_KDE_PAIR = 32768

RADIO_2LOBE_QSO = 32

RM_TILE1 = 18014398509481984

RM_TILE2 = 36028797018963968

SDSSFILLER = 274877906944

SEGUE1 = 68719476736

SEGUE2 = 137438953472

SEQUELS_ELG = 17179869184

SEQUELS_ELG_LOWP = 549755813888

SEQUELS_TARGET = 9007199254740992

SPIDERS_PILOT = 33554432

SPOKE2 = 131072

STRIPE82BCG = 64

TAU_STAR = 4503599627370496

TDSS_PILOT = 16777216

TDSS_PILOT_PM = 268435456

TDSS_PILOT_SNHOST = 536870912

TDSS_SPIDERS_PILOT = 67108864

WISE_BOSS_QSO = 16384

WISE_COMPLETE = 8388608

XMMSDSS = 2048

XMM_PRIME = 4294967296

XMM_SECOND = 8589934592

class bossdata.bits.APOGEE2_TARGET1[source]¶

Bases: object

APOGEE2 primary target bits

APOGEE2_FAINT_EXTRA¶

int

(1<<29) Faint star (fainter than cohort limit; not required to reach survey S/N requirement)

APOGEE2_SCI_CLUSTER¶

int

(1<<9) Science cluster candidate member

APOGEE2_TWOBIN_0_5_TO_0_8¶

int

(1<<1) Selected in blue 0.5 < (J-Ks)o < 0.8 color bin

APOGEE2_NO_DERED¶

int

(1<<6) Selected with no dereddening

APOGEE2_MAGCLOUD_CANDIDATE¶

int

(1<<23) Selected as potential Mag Cloud member (based on photometry)

APOGEE2_DSPH_CANDIDATE¶

int

(1<<21) Selected as potential dSph member (non Sgr) (based on photometry)

APOGEE2_TWOBIN_GT_0_8¶

int

(1<<2) Selected in red (J-Ks)o > 0.8 color bin

APOGEE2_DSPH_MEMBER¶

int

(1<<20) Selected as confirmed dSph member (non Sgr)

APOGEE2_APOKASC_DWARF¶

int

(1<<28) Selected as part of APOKASC dwarf sample

APOGEE2_NORMAL_SAMPLE¶

int

(1<<14) Selected as part of the random sample

APOGEE2_APOKASC_GIANT¶

int

(1<<27) Selected as part of APOKASC giant sample

APOGEE2_SGR_DSPH¶

int

(1<<26) Selected as confirmed Sgr core/stream member

APOGEE2_WASH_NOCLASS¶

int

(1<<17) Selected because it has no W+D classification

APOGEE2_MAGCLOUD_MEMBER¶

int

(1<<22) Selected as confirmed Mag Cloud member

APOGEE2_RRLYR¶

int

(1<<24) Selected as a bulge RR Lyrae star

APOGEE2_WASH_DWARF¶

int

(1<<8) Selected as Wash+DDO51 photometric dwarf

APOGEE2_MANGA_LED¶

int

(1<<15) Star on a shared MaNGA-led design

APOGEE2_WASH_GIANT¶

int

(1<<7) Selected as Wash+DDO51 photometric giant

APOGEE2_SFD_DERED¶

int

(1<<5) Selected with SFD_EBV dereddening

APOGEE2_APOKASC¶

int

(1<<30) Selected as part of the APOKASC program (incl. seismic/gyro targets and others)

APOGEE2_STREAM_CANDIDATE¶

int

(1<<19) Selected as potential halo tidal stream member (based on photometry)

APOGEE2_IRAC_DERED¶

int

(1<<3) Selected with RJCE-IRAC dereddening

APOGEE2_SHORT¶

int

(1<<11) Selected as part of a short cohort

APOGEE2_MEDIUM¶

int

(1<<12) Selected as part of a medium cohort

APOGEE2_LONG¶

int

(1<<13) Selected as part of a long cohort

APOGEE2_STREAM_MEMBER¶

int

(1<<18) Selected as confirmed halo tidal stream member

APOGEE2_ONEBIN_GT_0_5¶

int

(1<<0) Selected in single (J-Ks)o > 0.5 color bin

APOGEE2_WISE_DERED¶

int

(1<<4) Selected with RJCE-WISE dereddening

APOGEE2_ONEBIN_GT_0_3¶

int

(1<<16) Selected in single (J-Ks)o > 0.3 color bin

APOGEE2_APOKASC = 1073741824

APOGEE2_APOKASC_DWARF = 268435456

APOGEE2_APOKASC_GIANT = 134217728

APOGEE2_DSPH_CANDIDATE = 2097152

APOGEE2_DSPH_MEMBER = 1048576

APOGEE2_FAINT_EXTRA = 536870912

APOGEE2_IRAC_DERED = 8

APOGEE2_LONG = 8192

APOGEE2_MAGCLOUD_CANDIDATE = 8388608

APOGEE2_MAGCLOUD_MEMBER = 4194304

APOGEE2_MANGA_LED = 32768

APOGEE2_MEDIUM = 4096

APOGEE2_NORMAL_SAMPLE = 16384

APOGEE2_NO_DERED = 64

APOGEE2_ONEBIN_GT_0_3 = 65536

APOGEE2_ONEBIN_GT_0_5 = 1

APOGEE2_RRLYR = 16777216

APOGEE2_SCI_CLUSTER = 512

APOGEE2_SFD_DERED = 32

APOGEE2_SGR_DSPH = 67108864

APOGEE2_SHORT = 2048

APOGEE2_STREAM_CANDIDATE = 524288

APOGEE2_STREAM_MEMBER = 262144

APOGEE2_TWOBIN_0_5_TO_0_8 = 2

APOGEE2_TWOBIN_GT_0_8 = 4

APOGEE2_WASH_DWARF = 256

APOGEE2_WASH_GIANT = 128

APOGEE2_WASH_NOCLASS = 131072

APOGEE2_WISE_DERED = 16

class bossdata.bits.APOGEE2_TARGET2[source]¶

Bases: object

APOGEE2 secondary target bits

APOGEE2_STANDARD_STAR¶

int

(1<<2) Stellar parameters/abundance standard

APOGEE2_GES_OVERLAP¶

int

(1<<14) Overlap with Gaia-ESO

APOGEE2_1M_TARGET¶

int

(1<<22) Selected as a 1-m target

APOGEE2_EXTERNAL_CALIB¶

int

(1<<5) External survey calibration target (generic flag; others below dedicated to specific surveys)

APOGEE2_GALAH_OVERLAP¶

int

(1<<17) Overlap with GALAH

APOGEE2_ARGOS_OVERLAP¶

int

(1<<15) Overlap with ARGOS

APOGEE2_INTERNAL_CALIB¶

int

(1<<6) Internal survey calibration target (observed in at least 2 of: APOGEE-1, -2N, -2S)

APOGEE2_GAIA_OVERLAP¶

int

(1<<16) Overlap with Gaia

APOGEE2_OBJECT¶

int

(1<<30) This object is an APOGEE-2 target

APOGEE2_TELLURIC¶

int

(1<<9) Telluric calibrator target

APOGEE2_LITERATURE_CALIB¶

int

(1<<13) Overlap with high-resolution literature studies

APOGEE2_RAVE_OVERLAP¶

int

(1<<18) Overlap with RAVE

APOGEE2_SKY¶

int

(1<<4) Sky fiber

APOGEE2_CALIB_CLUSTER¶

int

(1<<10) Selected as calibration cluster member

APOGEE2_RV_STANDARD¶

int

(1<<3) Stellar RV standard

APOGEE2_1M_TARGET = 4194304

APOGEE2_ARGOS_OVERLAP = 32768

APOGEE2_CALIB_CLUSTER = 1024

APOGEE2_EXTERNAL_CALIB = 32

APOGEE2_GAIA_OVERLAP = 65536

APOGEE2_GALAH_OVERLAP = 131072

APOGEE2_GES_OVERLAP = 16384

APOGEE2_INTERNAL_CALIB = 64

APOGEE2_LITERATURE_CALIB = 8192

APOGEE2_OBJECT = 1073741824

APOGEE2_RAVE_OVERLAP = 262144

APOGEE2_RV_STANDARD = 8

APOGEE2_SKY = 16

APOGEE2_STANDARD_STAR = 4

APOGEE2_TELLURIC = 512

class bossdata.bits.APOGEE2_TARGET3[source]¶

Bases: object

APOGEE2 trinary target bits

APOGEE2_YOUNG_CLUSTER¶

int

(1<<5) Selected as part of the young cluster study (IN-SYNC)

APOGEE2_SUBSTELLAR_COMPANIONS¶

int

(1<<4) Selected as part of the substellar companion search

APOGEE2_KOI_CONTROL¶

int

(1<<2) Selected as part of the long cadence KOI control sample

APOGEE2_ANCILLARY¶

int

(1<<8) Selected as an ancillary target

APOGEE2_MASSIVE_STAR¶

int

(1<<9) Selected as part of the Massive Star program

APOGEE2_EB¶

int

(1<<1) Selected as part of the EB program

APOGEE2_KOI¶

int

(1<<0) Selected as part of the long cadence KOI study

APOGEE2_MDWARF¶

int

(1<<3) Selected as part of the M dwarf study

APOGEE2_ANCILLARY = 256

APOGEE2_EB = 2

APOGEE2_KOI = 1

APOGEE2_KOI_CONTROL = 4

APOGEE2_MASSIVE_STAR = 512

APOGEE2_MDWARF = 8

APOGEE2_SUBSTELLAR_COMPANIONS = 16

APOGEE2_YOUNG_CLUSTER = 32

class bossdata.bits.APOGEE_ASPCAPFLAG[source]¶

Bases: object

APOGEE ASPCAP mask bits

METALS_BAD¶

int

(1<<19) BAD metals (see PARAMFLAG[3] for details)

TEFF_BAD¶

int

(1<<16) BAD effective temperature (see PARAMFLAG[0] for details)

CHI2_WARN¶

int

(1<<8) high chi^2 (> 2*median at ASPCAP temperature (WARN)

NFE_WARN¶

int

(1<<6) WARNING on [N/Fe] (see PARAMFLAG[6] for details)

VMICRO_WARN¶

int

(1<<2) WARNING on vmicro (see PARAMFLAG[2] for details)

COLORTE_WARN¶

int

(1<<9) effective temperature more than 500K from photometric temperature for dereddened color (WARN)

COLORTE_BAD¶

int

(1<<25) effective temperature more than 1000K from photometric temperature for dereddened color (BAD)

TEFF_WARN¶

int

(1<<0) WARNING on effective temperature (see PARAMFLAG[0] for details)

CHI2_BAD¶

int

(1<<24) high chi^2 (> 5*median at ASPCAP temperature (BAD)

STAR_WARN¶

int

(1<<7) WARNING overall for star: set if any of TEFF, LOGG, CHI2, COLORTE, ROTATION, SN warn are set

CFE_BAD¶

int

(1<<21) BAD [C/Fe] (see PARAMFLAG[5] for details)

VMICRO_BAD¶

int

(1<<18) BAD vmicro (see PARAMFLAG[2] for details)

CFE_WARN¶

int

(1<<5) WARNING on [C/Fe] (see PARAMFLAG[5] for details)

LOGG_BAD¶

int

(1<<17) BAD log g (see PARAMFLAG[1] for details)

ALPHAFE_BAD¶

int

(1<<20) BAD [alpha/Fe] (see PARAMFLAG[4] for details)

NFE_BAD¶

int

(1<<22) BAD [N/Fe] (see PARAMFLAG[6] for details)

ALPHAFE_WARN¶

int

(1<<4) WARNING on [alpha/Fe] (see PARAMFLAG[4] for details)

SN_WARN¶

int

(1<<11) S/N<70 (WARN)

SN_BAD¶

int

(1<<27) S/N<50 (BAD)

METALS_WARN¶

int

(1<<3) WARNING on metals (see PARAMFLAG[3] for details)

ROTATION_WARN¶

int

(1<<10) Spectrum has broad lines, with possible bad effects: FWHM of cross-correlation of spectrum with best RV template relative to auto-correltion of template > 1.5 (WARN)

STAR_BAD¶

int

(1<<23) BAD overall for star: set if any of TEFF, LOGG, CHI2, COLORTE, ROTATION, SN error are set, or any parameter is near grid edge (GRIDEDGE_BAD is set in any PARAMFLAG)

NO_ASPCAP_RESULT¶

int

(1<<31) No result

LOGG_WARN¶

int

(1<<1) WARNING on log g (see PARAMFLAG[1] for details)

ROTATION_BAD¶

int

(1<<26) Spectrum has broad lines, with possible bad effects: FWHM of cross-correlation of spectrum with best RV template relative to auto-correltion of template > 2 (BAD)

ALPHAFE_BAD = 1048576

ALPHAFE_WARN = 16

CFE_BAD = 2097152

CFE_WARN = 32

CHI2_BAD = 16777216

CHI2_WARN = 256

COLORTE_BAD = 33554432

COLORTE_WARN = 512

LOGG_BAD = 131072

LOGG_WARN = 2

METALS_BAD = 524288

METALS_WARN = 8

NFE_BAD = 4194304

NFE_WARN = 64

NO_ASPCAP_RESULT = 2147483648

ROTATION_BAD = 67108864

ROTATION_WARN = 1024

SN_BAD = 134217728

SN_WARN = 2048

STAR_BAD = 8388608

STAR_WARN = 128

TEFF_BAD = 65536

TEFF_WARN = 1

VMICRO_BAD = 262144

VMICRO_WARN = 4

class bossdata.bits.APOGEE_EXTRATARG[source]¶

Bases: object

APOGEE pixel level mask bits

COMMISSIONING¶

int

(1<<1) Commissioning data

NOT_MAIN¶

int

(1<<0) Not main survey target

TELLURIC¶

int

(1<<2) Telluric target

DUPLICATE¶

int

(1<<4) Duplicate observation of star

APO1M¶

int

(1<<3) APO1M + APOGEE observation

APO1M = 8

COMMISSIONING = 2

DUPLICATE = 16

NOT_MAIN = 1

TELLURIC = 4

class bossdata.bits.APOGEE_PARAMFLAG[source]¶

Bases: object

APOGEE parameter mask bits (set for each stellar parameter in ASPCAP fit)

CALRANGE_BAD¶

int

(1<<1) Parameter outside valid range of calibration determination

OTHER_WARN¶

int

(1<<10) Other warning condition

OTHER_BAD¶

int

(1<<2) Other error condition

CALRANGE_WARN¶

int

(1<<9) Parameter in possibly unreliable range of calibration determination

GRIDEDGE_WARN¶

int

(1<<8) Parameter within 1/2 grid spacing of grid edge

PARAM_FIXED¶

int

(1<<16) Parameter set at fixed value, not fit

GRIDEDGE_BAD¶

int

(1<<0) Parameter within 1/8 grid spacing of grid edge

CALRANGE_BAD = 2

CALRANGE_WARN = 512

GRIDEDGE_BAD = 1

GRIDEDGE_WARN = 256

OTHER_BAD = 4

OTHER_WARN = 1024

PARAM_FIXED = 65536

class bossdata.bits.APOGEE_PIXMASK[source]¶

Bases: object

APOGEE extra targeting bits

PERSIST_MED¶

int

(1<<10) Pixel falls in medium persistence region, may be affected

NOSKY¶

int

(1<<7) No sky available for this pixel from sky fibers

CRPIX¶

int

(1<<1) Pixel marked as cosmic ray in ap3d

BADERR¶

int

(1<<6) Pixel set to have very high error (not used)

PERSIST_HIGH¶

int

(1<<9) Pixel falls in high persistence region, may be affected

SIG_TELLURIC¶

int

(1<<13) Pixel falls near telluric line that has significant absorption

SIG_SKYLINE¶

int

(1<<12) Pixel falls near sky line that has significant flux compared with object

UNFIXABLE¶

int

(1<<3) Pixel marked as unfixable in ap3d

SATPIX¶

int

(1<<2) Pixel marked as saturated in ap3d

BADDARK¶

int

(1<<4) Pixel marked as bad as determined from dark frame

PERSIST_LOW¶

int

(1<<11) Pixel falls in low persistence region, may be affected

LITTROW_GHOST¶

int

(1<<8) Pixel falls in Littrow ghost, may be affected

BADFLAT¶

int

(1<<5) Pixel marked as bad as determined from flat frame

BADPIX¶

int

(1<<0) Pixel marked as BAD in bad pixel mask

BADDARK = 16

BADERR = 64

BADFLAT = 32

BADPIX = 1

CRPIX = 2

LITTROW_GHOST = 256

NOSKY = 128

PERSIST_HIGH = 512

PERSIST_LOW = 2048

PERSIST_MED = 1024

SATPIX = 4

SIG_SKYLINE = 4096

SIG_TELLURIC = 8192

UNFIXABLE = 8

class bossdata.bits.APOGEE_STARFLAG[source]¶

Bases: object

APOGEE star-level mask bits

PERSIST_MED¶

int

(1<<10) Spectrum has significant number (>20%) of pixels in medium persistence region: WARN

SUSPECT_RV_COMBINATION¶

int

(1<<16) WARNING: RVs from synthetic template differ significantly from those from combined template

BRIGHT_NEIGHBOR¶

int

(1<<2) Star has neighbor more than 10 times brighter: WARN

PERSIST_JUMP_NEG¶

int

(1<<13) Spectrum show obvious negative jump in blue chip: WARN

BAD_PIXELS¶

int

(1<<0) Spectrum has many bad pixels (>40%): BAD

PERSIST_LOW¶

int

(1<<11) Spectrum has significant number (>20%) of pixels in low persistence region: WARN

LOW_SNR¶

int

(1<<4) Spectrum has low S/N (S/N<5): BAD

VERY_BRIGHT_NEIGHBOR¶

int

(1<<3) Star has neighbor more than 100 times brighter: BAD

SUSPECT_BROAD_LINES¶

int

(1<<17) WARNING: cross-correlation peak with template significantly broader than autocorrelation of template

COMMISSIONING¶

int

(1<<1) Commissioning data (MJD<55761), non-standard configuration, poor LSF: WARN

PERSIST_HIGH¶

int

(1<<9) Spectrum has significant number (>20%) of pixels in high persistence region: WARN

PERSIST_JUMP_POS¶

int

(1<<12) Spectrum show obvious positive jump in blue chip: WARN

BAD_PIXELS = 1

BRIGHT_NEIGHBOR = 4

COMMISSIONING = 2

LOW_SNR = 16

PERSIST_HIGH = 512

PERSIST_JUMP_NEG = 8192

PERSIST_JUMP_POS = 4096

PERSIST_LOW = 2048

PERSIST_MED = 1024

SUSPECT_BROAD_LINES = 131072

SUSPECT_RV_COMBINATION = 65536

VERY_BRIGHT_NEIGHBOR = 8

class bossdata.bits.APOGEE_TARGET1[source]¶

Bases: object

APOGEE primary target bits

APOGEE_INTERMEDIATE¶

int

(1<<12) Intermediate cohort target

APOGEE_KEPLER_EB¶

int

(1<<23) Eclipsing binary from Kepler (ancillary)

APOGEE_FAINT_EXTRA¶

int

(1<<29) Selected as faint target for low target-density field

APOGEE_OLD_STAR¶

int

(1<<21) Selected as old star (ancillary)

APOGEE_IRAC_DERED¶

int

(1<<3) Selected using RJCE-IRAC dereddening

APOGEE_CHECKED¶

int

(1<<31) This target has been checked

APOGEE_WISE_DERED¶

int

(1<<4) Selected using RJCE-WISE dereddening

APOGEE_KEPLER_SEISMO¶

int

(1<<27) Kepler asteroseismology program target

APOGEE_LONG¶

int

(1<<13) Long cohort target

APOGEE_MDWARF¶

int

(1<<19) M dwarfs selected for RV program (ancillary)

APOGEE_ANCILLARY¶

int

(1<<17) An ancillary program

APOGEE_SCI_CLUSTER¶

int

(1<<9) Probable cluster member

APOGEE_GC_PAL1¶

int

(1<<24) Star in globular cluster (ancillary)

APOGEE_M31_CLUSTER¶

int

(1<<18) M31 cluster target (ancillary)

APOGEE_SERENDIPITOUS¶

int

(1<<15) Serendipitously interesting target to reobserve

APOGEE_NO_DERED¶

int

(1<<6) Selected using no dereddening

APOGEE_WASH_DWARF¶

int

(1<<8) Selected as dwarf in Washington photometry

APOGEE_WASH_GIANT¶

int

(1<<7) Selected as giant in Washington photometry

APOGEE_HIRES¶

int

(1<<20) Star with optical hi-res spectra (ancillary)

APOGEE_FIRST_LIGHT¶

int

(1<<16) First list plate target

APOGEE_MASSIVE_STAR¶

int

(1<<25) Selected as massive star (ancillary)

APOGEE_DO_NOT_OBSERVE¶

int

(1<<14) Do not observe (again)

APOGEE_SHORT¶

int

(1<<11) Short cohort target

APOGEE_EXTENDED¶

int

(1<<10) Extended object

APOGEE_KEPLER_HOST¶

int

(1<<28) Kepler planet-host program target

APOGEE_SEGUE_OVERLAP¶

int

(1<<30) Selected because of overlap with SEGUE survey

APOGEE_FAINT¶

int

(1<<0) Selected in faint bin of cohort

APOGEE_SGR_DSPH¶

int

(1<<26) Sagittarius dwarf spheroidal member

APOGEE_BRIGHT¶

int

(1<<2) Selected in bright bin of cohort

APOGEE_SFD_DERED¶

int

(1<<5) Selected using SFD E(B-V) dereddening

APOGEE_MEDIUM¶

int

(1<<1) Selected in medium bin of cohort

APOGEE_DISK_RED_GIANT¶

int

(1<<22) Disk red giant (ancillary)

APOGEE_ANCILLARY = 131072

APOGEE_BRIGHT = 4

APOGEE_CHECKED = 2147483648

APOGEE_DISK_RED_GIANT = 4194304

APOGEE_DO_NOT_OBSERVE = 16384

APOGEE_EXTENDED = 1024

APOGEE_FAINT = 1

APOGEE_FAINT_EXTRA = 536870912

APOGEE_FIRST_LIGHT = 65536

APOGEE_GC_PAL1 = 16777216

APOGEE_HIRES = 1048576

APOGEE_INTERMEDIATE = 4096

APOGEE_IRAC_DERED = 8

APOGEE_KEPLER_EB = 8388608

APOGEE_KEPLER_HOST = 268435456

APOGEE_KEPLER_SEISMO = 134217728

APOGEE_LONG = 8192

APOGEE_M31_CLUSTER = 262144

APOGEE_MASSIVE_STAR = 33554432

APOGEE_MDWARF = 524288

APOGEE_MEDIUM = 2

APOGEE_NO_DERED = 64

APOGEE_OLD_STAR = 2097152

APOGEE_SCI_CLUSTER = 512

APOGEE_SEGUE_OVERLAP = 1073741824

APOGEE_SERENDIPITOUS = 32768

APOGEE_SFD_DERED = 32

APOGEE_SGR_DSPH = 67108864

APOGEE_SHORT = 2048

APOGEE_WASH_DWARF = 256

APOGEE_WASH_GIANT = 128

APOGEE_WISE_DERED = 16

class bossdata.bits.APOGEE_TARGET2[source]¶

Bases: object

APOGEE secondary target bits

BUNDLE_HOLE¶

int

(1<<7) Bundle hole

APOGEE_KEPLER_COOLDWARF¶

int

(1<<16) Kepler cool dwarf/subgiant (ancillary)

APOGEE_CALIB_CLUSTER¶

int

(1<<10) Known calibration cluster member

APOGEE_LONGBAR¶

int

(1<<14) Probable RC star in long bar (ancillary)

GUIDE_STAR¶

int

(1<<6) Guide star

APOGEE_RV_STANDARD¶

int

(1<<3) Radial velocity standard

APOGEE_FLUX_STANDARD¶

int

(1<<1) Flux standard

APOGEE_GC_SUPER_GIANT¶

int

(1<<12) Probable supergiant in Galactic Center

SKY¶

int

(1<<4) Sky

APOGEE_EMISSION_STAR¶

int

(1<<15) Emission-line star (ancillary)

APOGEE_STANDARD_STAR¶

int

(1<<2) Stellar abundance, parameters standard

APOGEE_EMBEDDEDCLUSTER_STAR¶

int

(1<<13) Young embedded clusters (ancillary)

SKY_BAD¶

int

(1<<5) Selected as sky but identified as bad (via visual exam or observation)

APOGEE_TELLURIC¶

int

(1<<9) Hot (telluric) standard

LIGHT_TRAP¶

int

(1<<0) Light trap

APOGEE_MIRCLUSTER_STAR¶

int

(1<<17) Candidate MIR-detected cluster member (ancillary)

APOGEE_CHECKED¶

int

(1<<31) This target has been checked

APOGEE_TELLURIC_BAD¶

int

(1<<8) Selected as telluric standard but identified as bad (via SIMBAD or observation)

APOGEE_GC_GIANT¶

int

(1<<11) Probable giant in Galactic Center

APOGEE_CALIB_CLUSTER = 1024

APOGEE_CHECKED = 2147483648

APOGEE_EMBEDDEDCLUSTER_STAR = 8192

APOGEE_EMISSION_STAR = 32768

APOGEE_FLUX_STANDARD = 2

APOGEE_GC_GIANT = 2048

APOGEE_GC_SUPER_GIANT = 4096

APOGEE_KEPLER_COOLDWARF = 65536

APOGEE_LONGBAR = 16384

APOGEE_MIRCLUSTER_STAR = 131072

APOGEE_RV_STANDARD = 8

APOGEE_STANDARD_STAR = 4

APOGEE_TELLURIC = 512

APOGEE_TELLURIC_BAD = 256

BUNDLE_HOLE = 128

GUIDE_STAR = 64

LIGHT_TRAP = 1

SKY = 16

SKY_BAD = 32

class bossdata.bits.BOSSTILE_STATUS[source]¶

Bases: object

BOSS tiling code status bits

MIDLEVEL_PRIORITY¶

int

(1<<23) targets (from ancillary list) tiled between gals and ancillaries

NAKED¶

int

(1<<1) not in area covered by tiles

DECOLLIDED¶

int

(1<<3) in the decollided set of high priority

DUPLICATE¶

int

(1<<17) trimmed as a duplicate object (only checked if not trimmed for any other reason)

DUPLICATE_PRIMARY¶

int

(1<<18) has associated duplicate object that were trimmed (but this one is kept)

KNOWN_OBJECT¶

int

(1<<16) galaxy has known redshift

DUPLICATE_TILED¶

int

(1<<19) trimmed as a duplicate object, and its primary was tiled

FILLER¶

int

(1<<11) was a filler (not normal repeat)

POSSIBLE_KNOCKOUT¶

int

(1<<5) knocked out of at least one tile by BOSSTARGET

REPEAT¶

int

(1<<10) included on more than one tile

ANCILLARY_ROUND2¶

int

(1<<22) new ancillaries added June 2012 (tiled after old ancillaries)

IGNORE_PRIORITY¶

int

(1<<6) priority exceeds max (ANCILLARY only)

BLUEFIBER¶

int

(1<<8) allocate this object a blue fiber

TOOFAINT¶

int

(1<<20) trimmed because it was fainter than the ifiber2mag limit

OUT_OF_BOUNDS¶

int

(1<<13) outside bounds for this sort of target (for restricted QSO geometry, e.g.)

BAD_CALIB_STATUS¶

int

(1<<14) bad CALIB_STATUS

BOSSTARGET¶

int

(1<<2) in the high priority set of targets

PREVIOUS_CHUNK¶

int

(1<<15) included because not tiled in previous overlapping chunk

ANCILLARY¶

int

(1<<4) in the lower priority, ancillary set

CENTERPOST¶

int

(1<<9) 92 arcsec collision with center post

TOOBRIGHT¶

int

(1<<7) fibermag too bright

SUPPLEMENTARY¶

int

(1<<21) supplementary targets tiles after the ancillaries (subset of ancillaries)

NOT_TILED_TARGET¶

int

(1<<12) though in input file, not a tiled target

TILED¶

int

(1<<0) assigned a fiber

ANCILLARY = 16

ANCILLARY_ROUND2 = 4194304

BAD_CALIB_STATUS = 16384

BLUEFIBER = 256

BOSSTARGET = 4

CENTERPOST = 512

DECOLLIDED = 8

DUPLICATE = 131072

DUPLICATE_PRIMARY = 262144

DUPLICATE_TILED = 524288

FILLER = 2048

IGNORE_PRIORITY = 64

KNOWN_OBJECT = 65536

MIDLEVEL_PRIORITY = 8388608

NAKED = 2

NOT_TILED_TARGET = 4096

OUT_OF_BOUNDS = 8192

POSSIBLE_KNOCKOUT = 32

PREVIOUS_CHUNK = 32768

REPEAT = 1024

SUPPLEMENTARY = 2097152

TILED = 1

TOOBRIGHT = 128

TOOFAINT = 1048576

class bossdata.bits.BOSS_TARGET1[source]¶

Bases: object

BOSS survey primary target selection flags

QSO_UKIDSS¶

int

(1<<15) UKIDSS stars that match sweeps/pass flag cuts

QSO_CORE_MAIN¶

int

(1<<40) Main survey core sample

SDSS_KNOWN¶

int

(1<<6) Matches a known SDSS spectra

QSO_BONUS¶

int

(1<<11) permissive qso selection: commissioning only

QSO_BONUS_MAIN¶

int

(1<<41) Main survey bonus sample

QSO_KDE¶

int

(1<<19) selected by kde+chi2

TEMPLATE_GAL_PHOTO¶

int

(1<<32) galaxy templates

GAL_CMASS_ALL¶

int

(1<<7) GAL_CMASS and the entire sparsely sampled region

QSO_KDE_COADD¶

int

(1<<16) kde targets from the stripe82 coadd

QSO_CORE_ED¶

int

(1<<42) Extreme Deconvolution in Core

TEMPLATE_STAR_PHOTO¶

int

(1<<34) stellar templates

GAL_IFIBER2_FAINT¶

int

(1<<8) ifiber2 > 21.5, extinction corrected. Used after Nov 2010

QSO_KNOWN_MIDZ¶

int

(1<<12) known qso between [2.2,9.99]

GAL_LODPERP_DEPRECATED¶

int

(1<<5) (DEPRECATED) Same as hiz but between dperp00 and dperp0

QSO_CORE_LIKE¶

int

(1<<43) Likelihood that make it into core

STD_FSTAR¶

int

(1<<20) standard f-stars

GAL_CMASS¶

int

(1<<1) dperp > 0.55, color-mag cut

GAL_LOZ¶

int

(1<<0) low-z lrgs

QSO_KNOWN_LOHIZ¶

int

(1<<13) known qso outside of miz range. never target

QSO_NN¶

int

(1<<14) Neural Net that match to sweeps/pass cuts

TEMPLATE_STAR_SPECTRO¶

int

(1<<35) stellar templates (spectroscopically known)

GAL_CMASS_COMM¶

int

(1<<2) dperp > 0.55, commissioning color-mag cut

QSO_CORE¶

int

(1<<10) restrictive qso selection: commissioning only

GAL_CMASS_SPARSE¶

int

(1<<3) GAL_CMASS_COMM & (!GAL_CMASS) & (i < 19.9) sparsely sampled

STD_QSO¶

int

(1<<22) qso

QSO_LIKE¶

int

(1<<17) likelihood method

QSO_KNOWN_SUPPZ¶

int

(1<<44) known qso between [1.8,2.15]

STD_WD¶

int

(1<<21) white dwarfs

QSO_FIRST_BOSS¶

int

(1<<18) FIRST radio match

TEMPLATE_QSO_SDSS1¶

int

(1<<33) QSO templates

GAL_CMASS = 2

GAL_CMASS_ALL = 128

GAL_CMASS_COMM = 4

GAL_CMASS_SPARSE = 8

GAL_IFIBER2_FAINT = 256

GAL_LODPERP_DEPRECATED = 32

GAL_LOZ = 1

QSO_BONUS = 2048

QSO_BONUS_MAIN = 2199023255552

QSO_CORE = 1024

QSO_CORE_ED = 4398046511104

QSO_CORE_LIKE = 8796093022208

QSO_CORE_MAIN = 1099511627776

QSO_FIRST_BOSS = 262144

QSO_KDE = 524288

QSO_KDE_COADD = 65536

QSO_KNOWN_LOHIZ = 8192

QSO_KNOWN_MIDZ = 4096

QSO_KNOWN_SUPPZ = 17592186044416

QSO_LIKE = 131072

QSO_NN = 16384

QSO_UKIDSS = 32768

SDSS_KNOWN = 64

STD_FSTAR = 1048576

STD_QSO = 4194304

STD_WD = 2097152

TEMPLATE_GAL_PHOTO = 4294967296

TEMPLATE_QSO_SDSS1 = 8589934592

TEMPLATE_STAR_PHOTO = 17179869184

TEMPLATE_STAR_SPECTRO = 34359738368

class bossdata.bits.CALIB_STATUS[source]¶

Bases: object

Calibration status for an SDSS image

UNPHOT_EXTRAP_CLEAR¶

int

(1<<2) Extrapolate the solution from the clear part of a night (that was ubercalibrated) to the cloudy part

UNPHOT_EXTRAP_CLOUDY¶

int

(1<<3) The solution here is based on fitting the a-term to cloudy data.

PT_CLEAR¶

int

(1<<8) PT calibration for clear data

UNPHOT_DISJOINT¶

int

(1<<4) Data is disjoint from the rest of the survey (even though conditions may be photometric), the calibration is suspect

PS1_CONTRAIL¶

int

(1<<7) Comparison to PS1 reveals possible contrail

DEFAULT¶

int

(1<<10) a default calibration used

PHOTOMETRIC¶

int

(1<<0) Photometric observations

NO_UBERCAL¶

int

(1<<11) not uber-calibrated

PS1_PCOMP_MODEL¶

int

(1<<13) Enough information for PS1-based principal component flat model

PS1_LOW_RMS¶

int

(1<<14) Low RMS in comparison with PS1

PS1_UNPHOT¶

int

(1<<6) Comparison to PS1 reveals unphotometric conditions

PT_CLOUDY¶

int

(1<<9) PT calibration for cloudy data

INCREMENT_CALIB¶

int

(1<<5) Incrementally calibrated by considering overlaps with ubercalibrated data

ASTROMBAD¶

int

(1<<12) catastrophically bad astrometry

UNPHOT_OVERLAP¶

int

(1<<1) Unphotometric observations, calibrated based on overlaps with clear, ubercalibrated data; this is done on a field-by-field basis

ASTROMBAD = 4096

DEFAULT = 1024

INCREMENT_CALIB = 32

NO_UBERCAL = 2048

PHOTOMETRIC = 1

PS1_CONTRAIL = 128

PS1_LOW_RMS = 16384

PS1_PCOMP_MODEL = 8192

PS1_UNPHOT = 64

PT_CLEAR = 256

PT_CLOUDY = 512

UNPHOT_DISJOINT = 16

UNPHOT_EXTRAP_CLEAR = 4

UNPHOT_EXTRAP_CLOUDY = 8

UNPHOT_OVERLAP = 2

class bossdata.bits.EBOSS_TARGET0[source]¶

Bases: object

targeting bitmask for SEQUELS (eBOSS precursor)

QSO_REOBS¶

int

(1<<12) QSOs from BOSS to be reobserved

SEQUELS_COLLIDED¶

int

(1<<41) Collided galaxies from BOSS

TDSS_FES_VARBAL¶

int

(1<<35) TDSS Few epoch spectroscopy

SPIDERS_ERASS_AGN¶

int

(1<<22) ERASS AGN sources

QSO_EBOSS_KDE¶

int

(1<<13) KDE-selected QSOs (sequels only)

SPIDERS_RASS_AGN¶

int

(1<<20) RASS AGN sources

QSO_EBOSS_CORE¶

int

(1<<10) QSOs in XDQSOz+WISE selection for clustering

SPIDERS_RASS_CLUS¶

int

(1<<21) RASS Cluster sources

TDSS_FES_DE¶

int

(1<<31) TDSS Few epoch spectroscopy

LRG_IZW¶

int

(1<<1) LRG selection in i/z/W plane

QSO_EBOSS_FIRST¶

int

(1<<14) Objects with FIRST radio matches

QSO_PTF¶

int

(1<<11) QSOs with variability in PTF imaging

QSO_KNOWN¶

int

(1<<18) Known QSOs from previous surveys

LRG_RIW¶

int

(1<<2) LRG selection in r/i/W plan with (i-z) cut

TDSS_FES_NQHISN¶

int

(1<<33) TDSS Few epoch spectroscopy

TDSS_FES_DWARFC¶

int

(1<<32) TDSS Few epoch spectroscopy

SPIDERS_ERASS_CLUS¶

int

(1<<23) ERASS Cluster sources

DR9_CALIB_TARGET¶

int

(1<<19) Target found in DR9-calibrated imaging

DO_NOT_OBSERVE¶

int

(1<<0) Don’t put a fiber on this object

TDSS_FES_MGII¶

int

(1<<34) TDSS Few epoch spectroscopy

TDSS_A¶

int

(1<<30) Main PanSTARRS selection for TDSS

QSO_BAD_BOSS¶

int

(1<<15) QSOs from BOSS with bad spectra

QSO_BOSS_TARGET¶

int

(1<<16) Known TARGETS from BOSS with spectra

QSO_SDSS_TARGET¶

int

(1<<17) Known TARGETS from SDSS with spectra

SEQUELS_PTF_VARIABLE¶

int

(1<<40) Variability objects from PTF

DO_NOT_OBSERVE = 1

DR9_CALIB_TARGET = 524288

LRG_IZW = 2

LRG_RIW = 4

QSO_BAD_BOSS = 32768

QSO_BOSS_TARGET = 65536

QSO_EBOSS_CORE = 1024

QSO_EBOSS_FIRST = 16384

QSO_EBOSS_KDE = 8192

QSO_KNOWN = 262144

QSO_PTF = 2048

QSO_REOBS = 4096

QSO_SDSS_TARGET = 131072

SEQUELS_COLLIDED = 2199023255552

SEQUELS_PTF_VARIABLE = 1099511627776

SPIDERS_ERASS_AGN = 4194304

SPIDERS_ERASS_CLUS = 8388608

SPIDERS_RASS_AGN = 1048576

SPIDERS_RASS_CLUS = 2097152

TDSS_A = 1073741824

TDSS_FES_DE = 2147483648

TDSS_FES_DWARFC = 4294967296

TDSS_FES_MGII = 17179869184

TDSS_FES_NQHISN = 8589934592

TDSS_FES_VARBAL = 34359738368

class bossdata.bits.EBOSS_TARGET1[source]¶

Bases: object

targeting bitmask for eBOSS

QSO1_REOBS¶

int

(1<<12) QSOs from BOSS to be reobserved

QSO_SDSS_TARGET¶

int

(1<<17) Known TARGETS from SDSS with spectra

ELG_TEST1¶

int

(1<<40) Test targets for ELG selection

LRG_KNOWN¶

int

(1<<3) LRG selection in r/i/W plan with (i-z) cut

STD_QSO¶

int

(1<<52) qso

LRG1_IDROP¶

int

(1<<2) LRG selection in r/i/W plan with (i-z) cut

QSO1_EBOSS_FIRST¶

int

(1<<14) Ojbects with FIRST radio matches

STD_WD¶

int

(1<<51) white dwarfs

QSO1_BAD_BOSS¶

int

(1<<15) QSOs from BOSS with bad spectra

QSO1_EBOSS_KDE¶

int

(1<<13) KDE-selected QSOs (sequels only)

TDSS_TARGET¶

int

(1<<30) Target for TDSS (subclass found in eboss_target2)

QSO_BOSS_TARGET¶

int

(1<<16) Known TARGETS from BOSS with spectra

STD_FSTAR¶

int

(1<<50) standard f-stars

QSO_KNOWN¶

int

(1<<18) Known QSOs from previous surveys

QSO1_EBOSS_CORE¶

int

(1<<10) QSOs in XDQSOz+WISE selection for clustering

DO_NOT_OBSERVE¶

int

(1<<0) Don’t put a fiber on this object

QSO1_PTF¶

int

(1<<11) QSOs with variability in PTF imaging

LRG1_WISE¶

int

(1<<1) LRG selection in i/z/W plane

QSO1_VAR_S82¶

int

(1<<9) Variability-selected QSOs in the repeated Stripe 82 imaging

SPIDERS_TARGET¶

int

(1<<31) Target for SPIDERS (subclass found in eboss_target2)

DO_NOT_OBSERVE = 1

ELG_TEST1 = 1099511627776

LRG1_IDROP = 4

LRG1_WISE = 2

LRG_KNOWN = 8

QSO1_BAD_BOSS = 32768

QSO1_EBOSS_CORE = 1024

QSO1_EBOSS_FIRST = 16384

QSO1_EBOSS_KDE = 8192

QSO1_PTF = 2048

QSO1_REOBS = 4096

QSO1_VAR_S82 = 512

QSO_BOSS_TARGET = 65536

QSO_KNOWN = 262144

QSO_SDSS_TARGET = 131072

SPIDERS_TARGET = 2147483648

STD_FSTAR = 1125899906842624

STD_QSO = 4503599627370496

STD_WD = 2251799813685248

TDSS_TARGET = 1073741824