idx int64 0 63k | question stringlengths 53 5.28k | target stringlengths 5 805 |
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35,900 | def make_catalog_comp_dict ( ** kwargs ) : library_yamlfile = kwargs . pop ( 'library' , 'models/library.yaml' ) csm = kwargs . pop ( 'CatalogSourceManager' , CatalogSourceManager ( ** kwargs ) ) if library_yamlfile is None or library_yamlfile == 'None' : yamldict = { } else : yamldict = yaml . safe_load ( open ( libra... | Build and return the information about the catalog components |
35,901 | def read_catalog_info_yaml ( self , splitkey ) : catalog_info_yaml = self . _name_factory . catalog_split_yaml ( sourcekey = splitkey , fullpath = True ) yaml_dict = yaml . safe_load ( open ( catalog_info_yaml ) ) yaml_dict [ 'catalog_file' ] = os . path . expandvars ( yaml_dict [ 'catalog_file' ] ) yaml_dict [ 'catalo... | Read the yaml file for a particular split key |
35,902 | def build_catalog_info ( self , catalog_info ) : cat = SourceFactory . build_catalog ( ** catalog_info ) catalog_info [ 'catalog' ] = cat catalog_info [ 'catalog_table' ] = cat . table catalog_info [ 'roi_model' ] = SourceFactory . make_fermipy_roi_model_from_catalogs ( [ cat ] ) catalog_info [ 'srcmdl_name' ] = self .... | Build a CatalogInfo object |
35,903 | def catalog_components ( self , catalog_name , split_ver ) : return sorted ( self . _split_comp_info_dicts [ "%s_%s" % ( catalog_name , split_ver ) ] . keys ( ) ) | Return the set of merged components for a particular split key |
35,904 | def split_comp_info ( self , catalog_name , split_ver , split_key ) : return self . _split_comp_info_dicts [ "%s_%s" % ( catalog_name , split_ver ) ] [ split_key ] | Return the info for a particular split key |
35,905 | def make_catalog_comp_info_dict ( self , catalog_sources ) : catalog_ret_dict = { } split_ret_dict = { } for key , value in catalog_sources . items ( ) : if value is None : continue if value [ 'model_type' ] != 'catalog' : continue versions = value [ 'versions' ] for version in versions : ver_key = "%s_%s" % ( key , ve... | Make the information about the catalog components |
35,906 | def extract_images_from_tscube ( infile , outfile ) : inhdulist = fits . open ( infile ) wcs = pywcs . WCS ( inhdulist [ 0 ] . header ) map_shape = inhdulist [ 0 ] . data . shape t_eng = Table . read ( infile , "EBOUNDS" ) t_scan = Table . read ( infile , "SCANDATA" ) t_fit = Table . read ( infile , "FITDATA" ) n_ebin ... | Extract data from table HDUs in TSCube file and convert them to FITS images |
35,907 | def truncate_array ( array1 , array2 , position ) : slices = [ ] for i in range ( array1 . ndim ) : xmin = 0 xmax = array1 . shape [ i ] dxlo = array1 . shape [ i ] // 2 dxhi = array1 . shape [ i ] - dxlo if position [ i ] - dxlo < 0 : xmin = max ( dxlo - position [ i ] , 0 ) if position [ i ] + dxhi > array2 . shape [... | Truncate array1 by finding the overlap with array2 when the array1 center is located at the given position in array2 . |
35,908 | def _sum_wrapper ( fn ) : def wrapper ( * args , ** kwargs ) : v = 0 new_args = _cast_args_to_list ( args ) for arg in zip ( * new_args ) : v += fn ( * arg , ** kwargs ) return v return wrapper | Wrapper to perform row - wise aggregation of list arguments and pass them to a function . The return value of the function is summed over the argument groups . Non - list arguments will be automatically cast to a list . |
35,909 | def _amplitude_bounds ( counts , bkg , model ) : if isinstance ( counts , list ) : counts = np . concatenate ( [ t . flat for t in counts ] ) bkg = np . concatenate ( [ t . flat for t in bkg ] ) model = np . concatenate ( [ t . flat for t in model ] ) s_model = np . sum ( model ) s_counts = np . sum ( counts ) sn = bkg... | Compute bounds for the root of _f_cash_root_cython . |
35,910 | def _root_amplitude_brentq ( counts , bkg , model , root_fn = _f_cash_root ) : amplitude_min , amplitude_max = _amplitude_bounds ( counts , bkg , model ) if not np . sum ( counts ) > 0 : return amplitude_min , 0 args = ( counts , bkg , model ) if root_fn ( 0.0 , * args ) < 0 : return 0.0 , 1 with warnings . catch_warni... | Fit amplitude by finding roots using Brent algorithm . |
35,911 | def poisson_log_like ( counts , model ) : loglike = np . array ( model ) m = counts > 0 loglike [ m ] -= counts [ m ] * np . log ( model [ m ] ) return loglike | Compute the Poisson log - likelihood function for the given counts and model arrays . |
35,912 | def f_cash ( x , counts , bkg , model ) : return 2.0 * poisson_log_like ( counts , bkg + x * model ) | Wrapper for cash statistics that defines the model function . |
35,913 | def _ts_value_newton ( position , counts , bkg , model , C_0_map ) : extract_fn = _collect_wrapper ( extract_large_array ) truncate_fn = _collect_wrapper ( extract_small_array ) counts_slice = extract_fn ( counts , model , position ) bkg_slice = extract_fn ( bkg , model , position ) C_0_map_slice = extract_fn ( C_0_map... | Compute TS value at a given pixel position using the newton method . |
35,914 | def tsmap ( self , prefix = '' , ** kwargs ) : timer = Timer . create ( start = True ) schema = ConfigSchema ( self . defaults [ 'tsmap' ] ) schema . add_option ( 'loglevel' , logging . INFO ) schema . add_option ( 'map_skydir' , None , '' , astropy . coordinates . SkyCoord ) schema . add_option ( 'map_size' , 1.0 ) sc... | Generate a spatial TS map for a source component with properties defined by the model argument . The TS map will have the same geometry as the ROI . The output of this method is a dictionary containing ~fermipy . skymap . Map objects with the TS and amplitude of the best - fit test source . By default this method will ... |
35,915 | def tscube ( self , prefix = '' , ** kwargs ) : self . logger . info ( 'Generating TS cube' ) schema = ConfigSchema ( self . defaults [ 'tscube' ] ) schema . add_option ( 'make_plots' , True ) schema . add_option ( 'write_fits' , True ) schema . add_option ( 'write_npy' , True ) config = schema . create_config ( self .... | Generate a spatial TS map for a source component with properties defined by the model argument . This method uses the gttscube ST application for source fitting and will simultaneously fit the test source normalization as well as the normalizations of any background components that are currently free . The output of th... |
35,916 | def compute_ps_counts ( ebins , exp , psf , bkg , fn , egy_dim = 0 , spatial_model = 'PointSource' , spatial_size = 1E-3 ) : ewidth = utils . edge_to_width ( ebins ) ectr = np . exp ( utils . edge_to_center ( np . log ( ebins ) ) ) r68 = psf . containment_angle ( ectr , fraction = 0.68 ) if spatial_model != 'PointSourc... | Calculate the observed signal and background counts given models for the exposure background intensity PSF and source flux . |
35,917 | def create_psf ( event_class , event_type , dtheta , egy , cth ) : irf = create_irf ( event_class , event_type ) theta = np . degrees ( np . arccos ( cth ) ) m = np . zeros ( ( len ( dtheta ) , len ( egy ) , len ( cth ) ) ) for i , x in enumerate ( egy ) : for j , y in enumerate ( theta ) : m [ : , i , j ] = irf . psf ... | Create an array of PSF response values versus energy and inclination angle . |
35,918 | def create_edisp ( event_class , event_type , erec , egy , cth ) : irf = create_irf ( event_class , event_type ) theta = np . degrees ( np . arccos ( cth ) ) v = np . zeros ( ( len ( erec ) , len ( egy ) , len ( cth ) ) ) m = ( erec [ : , None ] / egy [ None , : ] < 3.0 ) & ( erec [ : , None ] / egy [ None , : ] > 0.33... | Create an array of energy response values versus energy and inclination angle . |
35,919 | def create_aeff ( event_class , event_type , egy , cth ) : irf = create_irf ( event_class , event_type ) irf . aeff ( ) . setPhiDependence ( False ) theta = np . degrees ( np . arccos ( cth ) ) m = np . zeros ( ( len ( egy ) , len ( cth ) ) ) for i , x in enumerate ( egy ) : for j , y in enumerate ( theta ) : m [ i , j... | Create an array of effective areas versus energy and incidence angle . Binning in energy and incidence angle is controlled with the egy and cth input parameters . |
35,920 | def calc_exp ( skydir , ltc , event_class , event_types , egy , cth_bins , npts = None ) : if npts is None : npts = int ( np . ceil ( np . max ( cth_bins [ 1 : ] - cth_bins [ : - 1 ] ) / 0.025 ) ) exp = np . zeros ( ( len ( egy ) , len ( cth_bins ) - 1 ) ) cth_bins = utils . split_bin_edges ( cth_bins , npts ) cth = ed... | Calculate the exposure on a 2D grid of energy and incidence angle . |
35,921 | def create_avg_rsp ( rsp_fn , skydir , ltc , event_class , event_types , x , egy , cth_bins , npts = None ) : if npts is None : npts = int ( np . ceil ( np . max ( cth_bins [ 1 : ] - cth_bins [ : - 1 ] ) / 0.05 ) ) wrsp = np . zeros ( ( len ( x ) , len ( egy ) , len ( cth_bins ) - 1 ) ) exps = np . zeros ( ( len ( egy ... | Calculate the weighted response function . |
35,922 | def create_avg_psf ( skydir , ltc , event_class , event_types , dtheta , egy , cth_bins , npts = None ) : return create_avg_rsp ( create_psf , skydir , ltc , event_class , event_types , dtheta , egy , cth_bins , npts ) | Generate model for exposure - weighted PSF averaged over incidence angle . |
35,923 | def create_avg_edisp ( skydir , ltc , event_class , event_types , erec , egy , cth_bins , npts = None ) : return create_avg_rsp ( create_edisp , skydir , ltc , event_class , event_types , erec , egy , cth_bins , npts ) | Generate model for exposure - weighted DRM averaged over incidence angle . |
35,924 | def create_wtd_psf ( skydir , ltc , event_class , event_types , dtheta , egy_bins , cth_bins , fn , nbin = 64 , npts = 1 ) : egy_bins = np . exp ( utils . split_bin_edges ( np . log ( egy_bins ) , npts ) ) etrue_bins = 10 ** np . linspace ( 1.0 , 6.5 , nbin * 5.5 + 1 ) etrue = 10 ** utils . edge_to_center ( np . log10 ... | Create an exposure - and dispersion - weighted PSF model for a source with spectral parameterization fn . The calculation performed by this method accounts for the influence of energy dispersion on the PSF . |
35,925 | def calc_drm ( skydir , ltc , event_class , event_types , egy_bins , cth_bins , nbin = 64 ) : npts = int ( np . ceil ( 128. / bins_per_dec ( egy_bins ) ) ) egy_bins = np . exp ( utils . split_bin_edges ( np . log ( egy_bins ) , npts ) ) etrue_bins = 10 ** np . linspace ( 1.0 , 6.5 , nbin * 5.5 + 1 ) egy = 10 ** utils .... | Calculate the detector response matrix . |
35,926 | def calc_counts ( skydir , ltc , event_class , event_types , egy_bins , cth_bins , fn , npts = 1 ) : egy_bins = np . exp ( utils . split_bin_edges ( np . log ( egy_bins ) , npts ) ) exp = calc_exp ( skydir , ltc , event_class , event_types , egy_bins , cth_bins ) dnde = fn . dnde ( egy_bins ) cnts = loglog_quad ( egy_b... | Calculate the expected counts vs . true energy and incidence angle for a source with spectral parameterization fn . |
35,927 | def calc_counts_edisp ( skydir , ltc , event_class , event_types , egy_bins , cth_bins , fn , nbin = 16 , npts = 1 ) : egy_bins = np . exp ( utils . split_bin_edges ( np . log ( egy_bins ) , npts ) ) etrue_bins = 10 ** np . linspace ( 1.0 , 6.5 , nbin * 5.5 + 1 ) drm = calc_drm ( skydir , ltc , event_class , event_type... | Calculate the expected counts vs . observed energy and true incidence angle for a source with spectral parameterization fn . |
35,928 | def calc_wtd_exp ( skydir , ltc , event_class , event_types , egy_bins , cth_bins , fn , nbin = 16 ) : cnts = calc_counts_edisp ( skydir , ltc , event_class , event_types , egy_bins , cth_bins , fn , nbin = nbin ) flux = fn . flux ( egy_bins [ : - 1 ] , egy_bins [ 1 : ] ) return cnts / flux [ : , None ] | Calculate the effective exposure . |
35,929 | def eval ( self , ebin , dtheta , scale_fn = None ) : if scale_fn is None and self . scale_fn is not None : scale_fn = self . scale_fn if scale_fn is None : scale_factor = 1.0 else : dtheta = dtheta / scale_fn ( self . energies [ ebin ] ) scale_factor = 1. / scale_fn ( self . energies [ ebin ] ) ** 2 vals = 10 ** np . ... | Evaluate the PSF at the given energy bin index . |
35,930 | def interp ( self , energies , dtheta , scale_fn = None ) : if scale_fn is None and self . scale_fn : scale_fn = self . scale_fn log_energies = np . log10 ( energies ) shape = ( energies * dtheta ) . shape scale_factor = np . ones ( shape ) if scale_fn is not None : dtheta = dtheta / scale_fn ( energies ) scale_factor ... | Evaluate the PSF model at an array of energies and angular separations . |
35,931 | def interp_bin ( self , egy_bins , dtheta , scale_fn = None ) : npts = 4 egy_bins = np . exp ( utils . split_bin_edges ( np . log ( egy_bins ) , npts ) ) egy = np . exp ( utils . edge_to_center ( np . log ( egy_bins ) ) ) log_energies = np . log10 ( egy ) vals = self . interp ( egy [ None , : ] , dtheta [ : , None ] , ... | Evaluate the bin - averaged PSF model over the energy bins egy_bins . |
35,932 | def containment_angle ( self , energies = None , fraction = 0.68 , scale_fn = None ) : if energies is None : energies = self . energies vals = self . interp ( energies [ np . newaxis , : ] , self . dtheta [ : , np . newaxis ] , scale_fn = scale_fn ) dtheta = np . radians ( self . dtheta [ : , np . newaxis ] * np . ones... | Evaluate the PSF containment angle at a sequence of energies . |
35,933 | def containment_angle_bin ( self , egy_bins , fraction = 0.68 , scale_fn = None ) : vals = self . interp_bin ( egy_bins , self . dtheta , scale_fn = scale_fn ) dtheta = np . radians ( self . dtheta [ : , np . newaxis ] * np . ones ( vals . shape ) ) return self . _calc_containment ( dtheta , vals , fraction ) | Evaluate the PSF containment angle averaged over energy bins . |
35,934 | def create ( cls , skydir , ltc , event_class , event_types , energies , cth_bins = None , ndtheta = 500 , use_edisp = False , fn = None , nbin = 64 ) : if isinstance ( event_types , int ) : event_types = bitmask_to_bits ( event_types ) if fn is None : fn = spectrum . PowerLaw ( [ 1E-13 , - 2.0 ] ) dtheta = np . logspa... | Create a PSFModel object . This class can be used to evaluate the exposure - weighted PSF for a source with a given observing profile and energy distribution . |
35,935 | def remove_file ( filepath , dry_run = False ) : if dry_run : sys . stdout . write ( "rm %s\n" % filepath ) else : try : os . remove ( filepath ) except OSError : pass | Remove the file at filepath |
35,936 | def clean_job ( logfile , outfiles , dry_run = False ) : remove_file ( logfile , dry_run ) for outfile in outfiles . values ( ) : remove_file ( outfile , dry_run ) | Removes log file and files created by failed jobs . |
35,937 | def check_log ( logfile , exited = 'Exited with exit code' , successful = 'Successfully completed' ) : if not os . path . exists ( logfile ) : return JobStatus . ready if exited in open ( logfile ) . read ( ) : return JobStatus . failed elif successful in open ( logfile ) . read ( ) : return JobStatus . done return Job... | Check a log file to determine status of LSF job |
35,938 | def check_job ( cls , job_details ) : return check_log ( job_details . logfile , cls . string_exited , cls . string_successful ) | Check the status of a specfic job |
35,939 | def dispatch_job_hook ( self , link , key , job_config , logfile , stream = sys . stdout ) : raise NotImplementedError ( "SysInterface.dispatch_job_hook" ) | Hook to dispatch a single job |
35,940 | def dispatch_job ( self , link , key , job_archive , stream = sys . stdout ) : try : job_details = link . jobs [ key ] except KeyError : print ( key , link . jobs ) job_config = job_details . job_config link . update_args ( job_config ) logfile = job_config [ 'logfile' ] try : self . dispatch_job_hook ( link , key , jo... | Function to dispatch a single job |
35,941 | def submit_jobs ( self , link , job_dict = None , job_archive = None , stream = sys . stdout ) : failed = False if job_dict is None : job_dict = link . jobs for job_key , job_details in sorted ( job_dict . items ( ) ) : job_config = job_details . job_config if job_details . status == JobStatus . failed : clean_job ( jo... | Run the Link with all of the items job_dict as input . |
35,942 | def clean_jobs ( self , link , job_dict = None , clean_all = False ) : failed = False if job_dict is None : job_dict = link . jobs for job_details in job_dict . values ( ) : if job_details . status == JobStatus . failed or clean_all : clean_job ( job_details . logfile , { } , self . _dry_run ) job_details . status = Jo... | Clean up all the jobs associated with this link . |
35,943 | def get_spatial_type ( spatial_model ) : if spatial_model in [ 'SkyDirFunction' , 'PointSource' , 'Gaussian' ] : return 'SkyDirFunction' elif spatial_model in [ 'SpatialMap' ] : return 'SpatialMap' elif spatial_model in [ 'RadialGaussian' , 'RadialDisk' ] : try : import pyLikelihood if hasattr ( pyLikelihood , 'RadialG... | Translate a spatial model string to a spatial type . |
35,944 | def create_pars_from_dict ( name , pars_dict , rescale = True , update_bounds = False ) : o = get_function_defaults ( name ) pars_dict = pars_dict . copy ( ) for k in o . keys ( ) : if not k in pars_dict : continue v = pars_dict [ k ] if not isinstance ( v , dict ) : v = { 'name' : k , 'value' : v } o [ k ] . update ( ... | Create a dictionary for the parameters of a function . |
35,945 | def make_parameter_dict ( pdict , fixed_par = False , rescale = True , update_bounds = False ) : o = copy . deepcopy ( pdict ) o . setdefault ( 'scale' , 1.0 ) if rescale : value , scale = utils . scale_parameter ( o [ 'value' ] * o [ 'scale' ] ) o [ 'value' ] = np . abs ( value ) * np . sign ( o [ 'value' ] ) o [ 'sca... | Update a parameter dictionary . This function will automatically set the parameter scale and bounds if they are not defined . Bounds are also adjusted to ensure that they encompass the parameter value . |
35,946 | def cast_pars_dict ( pars_dict ) : o = { } for pname , pdict in pars_dict . items ( ) : o [ pname ] = { } for k , v in pdict . items ( ) : if k == 'free' : o [ pname ] [ k ] = bool ( int ( v ) ) elif k == 'name' : o [ pname ] [ k ] = v else : o [ pname ] [ k ] = float ( v ) return o | Cast the bool and float elements of a parameters dict to the appropriate python types . |
35,947 | def do_gather ( flist ) : hlist = [ ] nskip = 3 for fname in flist : fin = fits . open ( fname ) if len ( hlist ) == 0 : if fin [ 1 ] . name == 'SKYMAP' : nskip = 4 start = 0 else : start = nskip for h in fin [ start : ] : hlist . append ( h ) hdulistout = fits . HDUList ( hlist ) return hdulistout | Gather all the HDUs from a list of files |
35,948 | def main_browse ( ) : parser = argparse . ArgumentParser ( usage = "job_archive.py [options]" , description = "Browse a job archive" ) parser . add_argument ( '--jobs' , action = 'store' , dest = 'job_archive_table' , type = str , default = 'job_archive_temp2.fits' , help = "Job archive file" ) parser . add_argument ( ... | Entry point for command line use for browsing a JobArchive |
35,949 | def n_waiting ( self ) : return self . _counters [ JobStatus . no_job ] + self . _counters [ JobStatus . unknown ] + self . _counters [ JobStatus . not_ready ] + self . _counters [ JobStatus . ready ] | Return the number of jobs in various waiting states |
35,950 | def n_failed ( self ) : return self . _counters [ JobStatus . failed ] + self . _counters [ JobStatus . partial_failed ] | Return the number of failed jobs |
35,951 | def get_status ( self ) : if self . n_total == 0 : return JobStatus . no_job elif self . n_done == self . n_total : return JobStatus . done elif self . n_failed > 0 : if self . n_failed > self . n_total / 4. : return JobStatus . failed return JobStatus . partial_failed elif self . n_running > 0 : return JobStatus . run... | Return an overall status based on the number of jobs in various states . |
35,952 | def make_tables ( job_dict ) : col_dbkey = Column ( name = 'dbkey' , dtype = int ) col_jobname = Column ( name = 'jobname' , dtype = 'S64' ) col_jobkey = Column ( name = 'jobkey' , dtype = 'S64' ) col_appname = Column ( name = 'appname' , dtype = 'S64' ) col_logfile = Column ( name = 'logfile' , dtype = 'S256' ) col_jo... | Build and return an astropy . table . Table to store JobDetails |
35,953 | def get_file_ids ( self , file_archive , creator = None , status = FileStatus . no_file ) : file_dict = copy . deepcopy ( self . file_dict ) if self . sub_file_dict is not None : file_dict . update ( self . sub_file_dict . file_dict ) infiles = file_dict . input_files outfiles = file_dict . output_files rmfiles = file_... | Fill the file id arrays from the file lists |
35,954 | def get_file_paths ( self , file_archive , file_id_array ) : full_list = [ ] status_dict = { } full_list += file_archive . get_file_paths ( file_id_array [ self . infile_ids ] ) full_list += file_archive . get_file_paths ( file_id_array [ self . outfile_ids ] ) full_list += file_archive . get_file_paths ( file_id_array... | Get the full paths of the files used by this object from the the id arrays |
35,955 | def _fill_array_from_list ( the_list , the_array ) : for i , val in enumerate ( the_list ) : the_array [ i ] = val return the_array | Fill an array from a list |
35,956 | def make_dict ( cls , table ) : ret_dict = { } for row in table : job_details = cls . create_from_row ( row ) ret_dict [ job_details . dbkey ] = job_details return ret_dict | Build a dictionary map int to JobDetails from an astropy . table . Table |
35,957 | def check_status_logfile ( self , checker_func ) : self . status = checker_func ( self . logfile ) return self . status | Check on the status of this particular job using the logfile |
35,958 | def _read_table_file ( self , table_file ) : self . _table_file = table_file if os . path . exists ( self . _table_file ) : self . _table = Table . read ( self . _table_file , hdu = 'JOB_ARCHIVE' ) self . _table_ids = Table . read ( self . _table_file , hdu = 'FILE_IDS' ) else : self . _table , self . _table_ids = JobD... | Read an astropy . table . Table from table_file to set up the JobArchive |
35,959 | def get_details ( self , jobname , jobkey ) : fullkey = JobDetails . make_fullkey ( jobname , jobkey ) return self . _cache [ fullkey ] | Get the JobDetails associated to a particular job instance |
35,960 | def register_job ( self , job_details ) : try : job_details_old = self . get_details ( job_details . jobname , job_details . jobkey ) if job_details_old . status <= JobStatus . running : job_details_old . status = job_details . status job_details_old . update_table_row ( self . _table , job_details_old . dbkey - 1 ) jo... | Register a job in this JobArchive |
35,961 | def register_jobs ( self , job_dict ) : njobs = len ( job_dict ) sys . stdout . write ( "Registering %i total jobs: " % njobs ) for i , job_details in enumerate ( job_dict . values ( ) ) : if i % 10 == 0 : sys . stdout . write ( '.' ) sys . stdout . flush ( ) self . register_job ( job_details ) sys . stdout . write ( '... | Register a bunch of jobs in this archive |
35,962 | def register_job_from_link ( self , link , key , ** kwargs ) : job_config = kwargs . get ( 'job_config' , None ) if job_config is None : job_config = link . args status = kwargs . get ( 'status' , JobStatus . unknown ) job_details = JobDetails ( jobname = link . linkname , jobkey = key , appname = link . appname , logf... | Register a job in the JobArchive from a Link object |
35,963 | def update_job ( self , job_details ) : other = self . get_details ( job_details . jobname , job_details . jobkey ) other . timestamp = job_details . timestamp other . status = job_details . status other . update_table_row ( self . _table , other . dbkey - 1 ) return other | Update a job in the JobArchive |
35,964 | def remove_jobs ( self , mask ) : jobnames = self . table [ mask ] [ 'jobname' ] jobkey = self . table [ mask ] [ 'jobkey' ] self . table [ mask ] [ 'status' ] = JobStatus . removed for jobname , jobkey in zip ( jobnames , jobkey ) : fullkey = JobDetails . make_fullkey ( jobname , jobkey ) self . _cache . pop ( fullkey... | Mark all jobs that match a mask as removed |
35,965 | def build_temp_job_archive ( cls ) : try : os . unlink ( 'job_archive_temp.fits' ) os . unlink ( 'file_archive_temp.fits' ) except OSError : pass cls . _archive = cls ( job_archive_table = 'job_archive_temp.fits' , file_archive_table = 'file_archive_temp.fits' , base_path = os . path . abspath ( '.' ) + '/' ) return cl... | Build and return a JobArchive using defualt locations of persistent files . |
35,966 | def update_job_status ( self , checker_func ) : njobs = len ( self . cache . keys ( ) ) status_vect = np . zeros ( ( 8 ) , int ) sys . stdout . write ( "Updating status of %i jobs: " % njobs ) sys . stdout . flush ( ) for i , key in enumerate ( self . cache . keys ( ) ) : if i % 200 == 0 : sys . stdout . write ( '.' ) ... | Update the status of all the jobs in the archive |
35,967 | def build_archive ( cls , ** kwargs ) : if cls . _archive is None : cls . _archive = cls ( ** kwargs ) return cls . _archive | Return the singleton JobArchive instance building it if needed |
35,968 | def elapsed_time ( self ) : if self . _t0 is not None : return self . _time + self . _get_time ( ) else : return self . _time | Get the elapsed time . |
35,969 | def make_spatialmap_source ( name , Spatial_Filename , spectrum ) : data = dict ( Spatial_Filename = Spatial_Filename , ra = 0.0 , dec = 0.0 , SpatialType = 'SpatialMap' , Source_Name = name ) if spectrum is not None : data . update ( spectrum ) return roi_model . Source ( name , data ) | Construct and return a fermipy . roi_model . Source object |
35,970 | def make_mapcube_source ( name , Spatial_Filename , spectrum ) : data = dict ( Spatial_Filename = Spatial_Filename ) if spectrum is not None : data . update ( spectrum ) return roi_model . MapCubeSource ( name , data ) | Construct and return a fermipy . roi_model . MapCubeSource object |
35,971 | def make_isotropic_source ( name , Spectrum_Filename , spectrum ) : data = dict ( Spectrum_Filename = Spectrum_Filename ) if spectrum is not None : data . update ( spectrum ) return roi_model . IsoSource ( name , data ) | Construct and return a fermipy . roi_model . IsoSource object |
35,972 | def make_composite_source ( name , spectrum ) : data = dict ( SpatialType = 'CompositeSource' , SpatialModel = 'CompositeSource' , SourceType = 'CompositeSource' ) if spectrum is not None : data . update ( spectrum ) return roi_model . CompositeSource ( name , data ) | Construct and return a fermipy . roi_model . CompositeSource object |
35,973 | def make_catalog_sources ( catalog_roi_model , source_names ) : sources = { } for source_name in source_names : sources [ source_name ] = catalog_roi_model [ source_name ] return sources | Construct and return dictionary of sources that are a subset of sources in catalog_roi_model . |
35,974 | def make_sources ( comp_key , comp_dict ) : srcdict = OrderedDict ( ) try : comp_info = comp_dict . info except AttributeError : comp_info = comp_dict try : spectrum = comp_dict . spectrum except AttributeError : spectrum = None model_type = comp_info . model_type if model_type == 'PointSource' : srcdict [ comp_key ] =... | Make dictionary mapping component keys to a source or set of sources |
35,975 | def add_sources ( self , source_info_dict ) : self . _source_info_dict . update ( source_info_dict ) for key , value in source_info_dict . items ( ) : self . _sources . update ( make_sources ( key , value ) ) | Add all of the sources in source_info_dict to this factory |
35,976 | def build_catalog ( ** kwargs ) : catalog_type = kwargs . get ( 'catalog_type' ) catalog_file = kwargs . get ( 'catalog_file' ) catalog_extdir = kwargs . get ( 'catalog_extdir' ) if catalog_type == '2FHL' : return catalog . Catalog2FHL ( fitsfile = catalog_file , extdir = catalog_extdir ) elif catalog_type == '3FGL' : ... | Build a fermipy . catalog . Catalog object |
35,977 | def make_fermipy_roi_model_from_catalogs ( cataloglist ) : data = dict ( catalogs = cataloglist , src_roiwidth = 360. ) return roi_model . ROIModel ( data , skydir = SkyCoord ( 0.0 , 0.0 , unit = 'deg' ) ) | Build and return a fermipy . roi_model . ROIModel object from a list of fermipy . catalog . Catalog objects |
35,978 | def make_roi ( cls , sources = None ) : if sources is None : sources = { } src_fact = cls ( ) src_fact . add_sources ( sources ) ret_model = roi_model . ROIModel ( { } , skydir = SkyCoord ( 0.0 , 0.0 , unit = 'deg' ) ) for source in src_fact . sources . values ( ) : ret_model . load_source ( source , build_index = Fals... | Build and return a fermipy . roi_model . ROIModel object from a dict with information about the sources |
35,979 | def copy_selected_sources ( cls , roi , source_names ) : roi_new = cls . make_roi ( ) for source_name in source_names : try : src_cp = roi . copy_source ( source_name ) except Exception : continue roi_new . load_source ( src_cp , build_index = False ) return roi_new | Build and return a fermipy . roi_model . ROIModel object by copying selected sources from another such object |
35,980 | def build_from_yamlfile ( yamlfile ) : d = yaml . load ( open ( yamlfile ) ) return MktimeFilterDict ( d [ 'aliases' ] , d [ 'selections' ] ) | Build a list of components from a yaml file |
35,981 | def collect_jobs ( dirs , runscript , overwrite = False , max_job_age = 90 ) : jobs = [ ] for dirname in sorted ( dirs ) : o = dict ( cfgfile = os . path . join ( dirname , 'config.yaml' ) , logfile = os . path . join ( dirname , os . path . splitext ( runscript ) [ 0 ] + '.log' ) , runscript = os . path . join ( dirna... | Construct a list of job dictionaries . |
35,982 | def delete_source_map ( srcmap_file , names , logger = None ) : with fits . open ( srcmap_file ) as hdulist : hdunames = [ hdu . name . upper ( ) for hdu in hdulist ] if not isinstance ( names , list ) : names = [ names ] for name in names : if not name . upper ( ) in hdunames : continue del hdulist [ name . upper ( ) ... | Delete a map from a binned analysis source map file if it exists . |
35,983 | def get_offsets ( self , pix ) : idx = [ ] for i in range ( self . ndim ) : if i == 0 : idx += [ 0 ] else : npix1 = int ( self . shape [ i ] ) pix0 = int ( pix [ i - 1 ] ) - npix1 // 2 idx += [ pix0 ] return idx | Get offset of the first pixel in each dimension in the global coordinate system . |
35,984 | def shift_to_coords ( self , pix , fill_value = np . nan ) : pix_offset = self . get_offsets ( pix ) dpix = np . zeros ( len ( self . shape ) - 1 ) for i in range ( len ( self . shape ) - 1 ) : x = self . rebin * ( pix [ i ] - pix_offset [ i + 1 ] ) + ( self . rebin - 1.0 ) / 2. dpix [ i ] = x - self . _pix_ref [ i ] p... | Create a new map that is shifted to the pixel coordinates pix . |
35,985 | def create_map ( self , pix ) : k0 = self . _m0 . shift_to_coords ( pix ) k1 = self . _m1 . shift_to_coords ( pix ) k0 [ np . isfinite ( k1 ) ] = k1 [ np . isfinite ( k1 ) ] k0 [ ~ np . isfinite ( k0 ) ] = 0 return k0 | Create a new map with reference pixel coordinates shifted to the pixel coordinates pix . |
35,986 | def render_pep440 ( vcs ) : if vcs is None : return None tags = vcs . split ( '-' ) if len ( tags ) == 1 : return tags [ 0 ] else : return tags [ 0 ] + '+' + '.' . join ( tags [ 1 : ] ) | Convert git release tag into a form that is PEP440 compliant . |
35,987 | def read_release_version ( ) : import re dirname = os . path . abspath ( os . path . dirname ( __file__ ) ) try : f = open ( os . path . join ( dirname , "_version.py" ) , "rt" ) for line in f . readlines ( ) : m = re . match ( "__version__ = '([^']+)'" , line ) if m : ver = m . group ( 1 ) return ver except : return N... | Read the release version from _version . py . |
35,988 | def write_release_version ( version ) : dirname = os . path . abspath ( os . path . dirname ( __file__ ) ) f = open ( os . path . join ( dirname , "_version.py" ) , "wt" ) f . write ( "__version__ = '%s'\n" % version ) f . close ( ) | Write the release version to _version . py . |
35,989 | def make_full_path ( basedir , outkey , origname ) : return os . path . join ( basedir , outkey , os . path . basename ( origname ) . replace ( '.fits' , '_%s.fits' % outkey ) ) | Make a full file path by combining tokens |
35,990 | def init_matplotlib_backend ( backend = None ) : import matplotlib try : os . environ [ 'DISPLAY' ] except KeyError : matplotlib . use ( 'Agg' ) else : if backend is not None : matplotlib . use ( backend ) | This function initializes the matplotlib backend . When no DISPLAY is available the backend is automatically set to Agg . |
35,991 | def load_data ( infile , workdir = None ) : infile = resolve_path ( infile , workdir = workdir ) infile , ext = os . path . splitext ( infile ) if os . path . isfile ( infile + '.npy' ) : infile += '.npy' elif os . path . isfile ( infile + '.yaml' ) : infile += '.yaml' else : raise Exception ( 'Input file does not exis... | Load python data structure from either a YAML or numpy file . |
35,992 | def resolve_file_path_list ( pathlist , workdir , prefix = '' , randomize = False ) : files = [ ] with open ( pathlist , 'r' ) as f : files = [ line . strip ( ) for line in f ] newfiles = [ ] for f in files : f = os . path . expandvars ( f ) if os . path . isfile ( f ) : newfiles += [ f ] else : newfiles += [ os . path... | Resolve the path of each file name in the file pathlist and write the updated paths to a new file . |
35,993 | def collect_dirs ( path , max_depth = 1 , followlinks = True ) : if not os . path . isdir ( path ) : return [ ] o = [ path ] if max_depth == 0 : return o for subdir in os . listdir ( path ) : subdir = os . path . join ( path , subdir ) if not os . path . isdir ( subdir ) : continue o += [ subdir ] if os . path . islink... | Recursively find directories under the given path . |
35,994 | def match_regex_list ( patterns , string ) : for p in patterns : if re . findall ( p , string ) : return True return False | Perform a regex match of a string against a list of patterns . Returns true if the string matches at least one pattern in the list . |
35,995 | def find_rows_by_string ( tab , names , colnames = [ 'assoc' ] ) : mask = np . empty ( len ( tab ) , dtype = bool ) mask . fill ( False ) names = [ name . lower ( ) . replace ( ' ' , '' ) for name in names ] for colname in colnames : if colname not in tab . columns : continue col = tab [ [ colname ] ] . copy ( ) col [ ... | Find the rows in a table tab that match at least one of the strings in names . This method ignores whitespace and case when matching strings . |
35,996 | def separation_cos_angle ( lon0 , lat0 , lon1 , lat1 ) : return ( np . sin ( lat1 ) * np . sin ( lat0 ) + np . cos ( lat1 ) * np . cos ( lat0 ) * np . cos ( lon1 - lon0 ) ) | Evaluate the cosine of the angular separation between two direction vectors . |
35,997 | def angle_to_cartesian ( lon , lat ) : theta = np . array ( np . pi / 2. - lat ) return np . vstack ( ( np . sin ( theta ) * np . cos ( lon ) , np . sin ( theta ) * np . sin ( lon ) , np . cos ( theta ) ) ) . T | Convert spherical coordinates to cartesian unit vectors . |
35,998 | def cov_to_correlation ( cov ) : err = np . sqrt ( np . diag ( cov ) ) errinv = np . ones_like ( err ) * np . nan m = np . isfinite ( err ) & ( err != 0 ) errinv [ m ] = 1. / err [ m ] corr = np . array ( cov ) return corr * np . outer ( errinv , errinv ) | Compute the correlation matrix given the covariance matrix . |
35,999 | def ellipse_to_cov ( sigma_maj , sigma_min , theta ) : cth = np . cos ( theta ) sth = np . sin ( theta ) covxx = cth ** 2 * sigma_maj ** 2 + sth ** 2 * sigma_min ** 2 covyy = sth ** 2 * sigma_maj ** 2 + cth ** 2 * sigma_min ** 2 covxy = cth * sth * sigma_maj ** 2 - cth * sth * sigma_min ** 2 return np . array ( [ [ cov... | Compute the covariance matrix in two variables x and y given the std . deviation along the semi - major and semi - minor axes and the rotation angle of the error ellipse . |
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