idx int64 0 251k | question stringlengths 53 3.53k | target stringlengths 5 1.23k | len_question int64 20 893 | len_target int64 3 238 |
|---|---|---|---|---|
18,700 | def calculate_tetra ( infiles ) : logger . info ( "Running TETRA." ) # First, find Z-scores logger . info ( "Calculating TETRA Z-scores for each sequence." ) tetra_zscores = { } for filename in infiles : logger . info ( "Calculating TETRA Z-scores for %s" , filename ) org = os . path . splitext ( os . path . split ( filename ) [ - 1 ] ) [ 0 ] tetra_zscores [ org ] = tetra . calculate_tetra_zscore ( filename ) # Then calculate Pearson correlation between Z-scores for each sequence logger . info ( "Calculating TETRA correlation scores." ) tetra_correlations = tetra . calculate_correlations ( tetra_zscores ) return tetra_correlations | Calculate TETRA for files in input directory . | 192 | 12 |
18,701 | def unified_anib ( infiles , org_lengths ) : logger . info ( "Running %s" , args . method ) blastdir = os . path . join ( args . outdirname , ALIGNDIR [ args . method ] ) logger . info ( "Writing BLAST output to %s" , blastdir ) # Build BLAST databases and run pairwise BLASTN if not args . skip_blastn : # Make sequence fragments logger . info ( "Fragmenting input files, and writing to %s" , args . outdirname ) # Fraglengths does not get reused with BLASTN fragfiles , fraglengths = anib . fragment_fasta_files ( infiles , blastdir , args . fragsize ) # Export fragment lengths as JSON, in case we re-run with --skip_blastn with open ( os . path . join ( blastdir , "fraglengths.json" ) , "w" ) as outfile : json . dump ( fraglengths , outfile ) # Which executables are we using? # if args.method == "ANIblastall": # format_exe = args.formatdb_exe # blast_exe = args.blastall_exe # else: # format_exe = args.makeblastdb_exe # blast_exe = args.blastn_exe # Run BLAST database-building and executables from a jobgraph logger . info ( "Creating job dependency graph" ) jobgraph = anib . make_job_graph ( infiles , fragfiles , anib . make_blastcmd_builder ( args . method , blastdir ) ) # jobgraph = anib.make_job_graph(infiles, fragfiles, blastdir, # format_exe, blast_exe, args.method, # jobprefix=args.jobprefix) if args . scheduler == "multiprocessing" : logger . info ( "Running jobs with multiprocessing" ) logger . info ( "Running job dependency graph" ) if args . workers is None : logger . info ( "(using maximum number of available " + "worker threads)" ) else : logger . info ( "(using %d worker threads, if available)" , args . workers ) cumval = run_mp . run_dependency_graph ( jobgraph , workers = args . workers , logger = logger ) if 0 < cumval : logger . warning ( "At least one BLAST run failed. " + "%s may fail." , args . method ) else : logger . info ( "All multiprocessing jobs complete." ) else : run_sge . run_dependency_graph ( jobgraph , logger = logger ) logger . info ( "Running jobs with SGE" ) else : # Import fragment lengths from JSON if args . method == "ANIblastall" : with open ( os . path . join ( blastdir , "fraglengths.json" ) , "rU" ) as infile : fraglengths = json . load ( infile ) else : fraglengths = None logger . warning ( "Skipping BLASTN runs (as instructed)!" ) # Process pairwise BLASTN output logger . info ( "Processing pairwise %s BLAST output." , args . method ) try : data = anib . process_blast ( blastdir , org_lengths , fraglengths = fraglengths , mode = args . method ) except ZeroDivisionError : logger . error ( "One or more BLAST output files has a problem." ) if not args . skip_blastn : if 0 < cumval : logger . error ( "This is possibly due to BLASTN run failure, " + "please investigate" ) else : logger . error ( "This is possibly due to a BLASTN comparison " + "being too distant for use." ) logger . error ( last_exception ( ) ) if not args . nocompress : logger . info ( "Compressing/deleting %s" , blastdir ) compress_delete_outdir ( blastdir ) # Return processed BLAST data return data | Calculate ANIb for files in input directory . | 875 | 12 |
18,702 | def subsample_input ( infiles ) : logger . info ( "--subsample: %s" , args . subsample ) try : samplesize = float ( args . subsample ) except TypeError : # Not a number logger . error ( "--subsample must be int or float, got %s (exiting)" , type ( args . subsample ) ) sys . exit ( 1 ) if samplesize <= 0 : # Not a positive value logger . error ( "--subsample must be positive value, got %s" , str ( args . subsample ) ) sys . exit ( 1 ) if int ( samplesize ) > 1 : logger . info ( "Sample size integer > 1: %d" , samplesize ) k = min ( int ( samplesize ) , len ( infiles ) ) else : logger . info ( "Sample size proportion in (0, 1]: %.3f" , samplesize ) k = int ( min ( samplesize , 1.0 ) * len ( infiles ) ) logger . info ( "Randomly subsampling %d sequences for analysis" , k ) if args . seed : logger . info ( "Setting random seed with: %s" , args . seed ) random . seed ( args . seed ) else : logger . warning ( "Subsampling without specified random seed!" ) logger . warning ( "Subsampling may NOT be easily reproducible!" ) return random . sample ( infiles , k ) | Returns a random subsample of the input files . | 307 | 10 |
18,703 | def wait ( self , interval = SGE_WAIT ) : finished = False while not finished : time . sleep ( interval ) interval = min ( 2 * interval , 60 ) finished = os . system ( "qstat -j %s > /dev/null" % ( self . name ) ) | Wait until the job finishes and poll SGE on its status . | 63 | 13 |
18,704 | def generate_nucmer_jobs ( filenames , outdir = "." , nucmer_exe = pyani_config . NUCMER_DEFAULT , filter_exe = pyani_config . FILTER_DEFAULT , maxmatch = False , jobprefix = "ANINUCmer" , ) : ncmds , fcmds = generate_nucmer_commands ( filenames , outdir , nucmer_exe , filter_exe , maxmatch ) joblist = [ ] for idx , ncmd in enumerate ( ncmds ) : njob = pyani_jobs . Job ( "%s_%06d-n" % ( jobprefix , idx ) , ncmd ) fjob = pyani_jobs . Job ( "%s_%06d-f" % ( jobprefix , idx ) , fcmds [ idx ] ) fjob . add_dependency ( njob ) # joblist.append(njob) # not required: dependency in fjob joblist . append ( fjob ) return joblist | Return a list of Jobs describing NUCmer command - lines for ANIm | 232 | 15 |
18,705 | def generate_nucmer_commands ( filenames , outdir = "." , nucmer_exe = pyani_config . NUCMER_DEFAULT , filter_exe = pyani_config . FILTER_DEFAULT , maxmatch = False , ) : nucmer_cmdlines , delta_filter_cmdlines = [ ] , [ ] for idx , fname1 in enumerate ( filenames [ : - 1 ] ) : for fname2 in filenames [ idx + 1 : ] : ncmd , dcmd = construct_nucmer_cmdline ( fname1 , fname2 , outdir , nucmer_exe , filter_exe , maxmatch ) nucmer_cmdlines . append ( ncmd ) delta_filter_cmdlines . append ( dcmd ) return ( nucmer_cmdlines , delta_filter_cmdlines ) | Return a tuple of lists of NUCmer command - lines for ANIm | 195 | 15 |
18,706 | def construct_nucmer_cmdline ( fname1 , fname2 , outdir = "." , nucmer_exe = pyani_config . NUCMER_DEFAULT , filter_exe = pyani_config . FILTER_DEFAULT , maxmatch = False , ) : outsubdir = os . path . join ( outdir , pyani_config . ALIGNDIR [ "ANIm" ] ) outprefix = os . path . join ( outsubdir , "%s_vs_%s" % ( os . path . splitext ( os . path . split ( fname1 ) [ - 1 ] ) [ 0 ] , os . path . splitext ( os . path . split ( fname2 ) [ - 1 ] ) [ 0 ] , ) , ) if maxmatch : mode = "--maxmatch" else : mode = "--mum" nucmercmd = "{0} {1} -p {2} {3} {4}" . format ( nucmer_exe , mode , outprefix , fname1 , fname2 ) filtercmd = "delta_filter_wrapper.py " + "{0} -1 {1} {2}" . format ( filter_exe , outprefix + ".delta" , outprefix + ".filter" ) return ( nucmercmd , filtercmd ) | Returns a tuple of NUCmer and delta - filter commands | 294 | 12 |
18,707 | def process_deltadir ( delta_dir , org_lengths , logger = None ) : # Process directory to identify input files - as of v0.2.4 we use the # .filter files that result from delta-filter (1:1 alignments) deltafiles = pyani_files . get_input_files ( delta_dir , ".filter" ) # Hold data in ANIResults object results = ANIResults ( list ( org_lengths . keys ( ) ) , "ANIm" ) # Fill diagonal NA values for alignment_length with org_lengths for org , length in list ( org_lengths . items ( ) ) : results . alignment_lengths [ org ] [ org ] = length # Process .delta files assuming that the filename format holds: # org1_vs_org2.delta for deltafile in deltafiles : qname , sname = os . path . splitext ( os . path . split ( deltafile ) [ - 1 ] ) [ 0 ] . split ( "_vs_" ) # We may have .delta files from other analyses in the same directory # If this occurs, we raise a warning, and skip the .delta file if qname not in list ( org_lengths . keys ( ) ) : if logger : logger . warning ( "Query name %s not in input " % qname + "sequence list, skipping %s" % deltafile ) continue if sname not in list ( org_lengths . keys ( ) ) : if logger : logger . warning ( "Subject name %s not in input " % sname + "sequence list, skipping %s" % deltafile ) continue tot_length , tot_sim_error = parse_delta ( deltafile ) if tot_length == 0 and logger is not None : if logger : logger . warning ( "Total alignment length reported in " + "%s is zero!" % deltafile ) query_cover = float ( tot_length ) / org_lengths [ qname ] sbjct_cover = float ( tot_length ) / org_lengths [ sname ] # Calculate percentage ID of aligned length. This may fail if # total length is zero. # The ZeroDivisionError that would arise should be handled # Common causes are that a NUCmer run failed, or that a very # distant sequence was included in the analysis. try : perc_id = 1 - float ( tot_sim_error ) / tot_length except ZeroDivisionError : perc_id = 0 # set arbitrary value of zero identity results . zero_error = True # Populate dataframes: when assigning data from symmetrical MUMmer # output, both upper and lower triangles will be populated results . add_tot_length ( qname , sname , tot_length ) results . add_sim_errors ( qname , sname , tot_sim_error ) results . add_pid ( qname , sname , perc_id ) results . add_coverage ( qname , sname , query_cover , sbjct_cover ) return results | Returns a tuple of ANIm results for . deltas in passed directory . | 680 | 16 |
18,708 | def set_ncbi_email ( ) : Entrez . email = args . email logger . info ( "Set NCBI contact email to %s" , args . email ) Entrez . tool = "genbank_get_genomes_by_taxon.py" | Set contact email for NCBI . | 58 | 7 |
18,709 | def entrez_retry ( func , * fnargs , * * fnkwargs ) : tries , success = 0 , False while not success and tries < args . retries : try : output = func ( * fnargs , * * fnkwargs ) success = True except ( HTTPError , URLError ) : tries += 1 logger . warning ( "Entrez query %s(%s, %s) failed (%d/%d)" , func , fnargs , fnkwargs , tries + 1 , args . retries ) logger . warning ( last_exception ( ) ) if not success : logger . error ( "Too many Entrez failures (exiting)" ) sys . exit ( 1 ) return output | Retries the passed function up to the number of times specified by args . retries | 152 | 17 |
18,710 | def entrez_batch_webhistory ( record , expected , batchsize , * fnargs , * * fnkwargs ) : results = [ ] for start in range ( 0 , expected , batchsize ) : batch_handle = entrez_retry ( Entrez . efetch , retstart = start , retmax = batchsize , webenv = record [ "WebEnv" ] , query_key = record [ "QueryKey" ] , * fnargs , * * fnkwargs ) batch_record = Entrez . read ( batch_handle , validate = False ) results . extend ( batch_record ) return results | Recovers the Entrez data from a prior NCBI webhistory search in batches of defined size using Efetch . Returns all results as a list . | 133 | 31 |
18,711 | def get_asm_uids ( taxon_uid ) : query = "txid%s[Organism:exp]" % taxon_uid logger . info ( "Entrez ESearch with query: %s" , query ) # Perform initial search for assembly UIDs with taxon ID as query. # Use NCBI history for the search. handle = entrez_retry ( Entrez . esearch , db = "assembly" , term = query , format = "xml" , usehistory = "y" ) record = Entrez . read ( handle , validate = False ) result_count = int ( record [ 'Count' ] ) logger . info ( "Entrez ESearch returns %d assembly IDs" , result_count ) # Recover assembly UIDs from the web history asm_ids = entrez_batch_webhistory ( record , result_count , 250 , db = "assembly" , retmode = "xml" ) logger . info ( "Identified %d unique assemblies" , len ( asm_ids ) ) return asm_ids | Returns a set of NCBI UIDs associated with the passed taxon . | 226 | 15 |
18,712 | def extract_filestem ( data ) : escapes = re . compile ( r"[\s/,#\(\)]" ) escname = re . sub ( escapes , '_' , data [ 'AssemblyName' ] ) return '_' . join ( [ data [ 'AssemblyAccession' ] , escname ] ) | Extract filestem from Entrez eSummary data . | 69 | 12 |
18,713 | def write_contigs ( asm_uid , contig_uids , batchsize = 10000 ) : # Has duplicate code with get_class_label_info() - needs refactoring logger . info ( "Collecting contig data for %s" , asm_uid ) # Assembly record - get binomial and strain names asm_record = Entrez . read ( entrez_retry ( Entrez . esummary , db = 'assembly' , id = asm_uid , rettype = 'text' ) , validate = False ) asm_organism = asm_record [ 'DocumentSummarySet' ] [ 'DocumentSummary' ] [ 0 ] [ 'SpeciesName' ] try : asm_strain = asm_record [ 'DocumentSummarySet' ] [ 'DocumentSummary' ] [ 0 ] [ 'Biosource' ] [ 'InfraspeciesList' ] [ 0 ] [ 'Sub_value' ] except KeyError : asm_strain = "" # Assembly UID (long form) for the output filename outfilename = "%s.fasta" % os . path . join ( args . outdirname , asm_record [ 'DocumentSummarySet' ] [ 'DocumentSummary' ] [ 0 ] [ 'AssemblyAccession' ] ) # Create label and class strings genus , species = asm_organism . split ( ' ' , 1 ) # Get FASTA records for contigs logger . info ( "Downloading FASTA records for assembly %s (%s)" , asm_uid , ' ' . join ( [ genus [ 0 ] + '.' , species , asm_strain ] ) ) # We're doing an explicit outer retry loop here because we want to confirm # we have the correct data, as well as test for Entrez connection errors, # which is all the entrez_retry function does. tries , success = 0 , False while not success and tries < args . retries : records = [ ] # Holds all return records # We may need to batch contigs query_uids = ',' . join ( contig_uids ) try : for start in range ( 0 , len ( contig_uids ) , batchsize ) : logger . info ( "Batch: %d-%d" , start , start + batchsize ) records . extend ( list ( SeqIO . parse ( entrez_retry ( Entrez . efetch , db = 'nucleotide' , id = query_uids , rettype = 'fasta' , retmode = 'text' , retstart = start , retmax = batchsize ) , 'fasta' ) ) ) tries += 1 # Check only that correct number of records returned. if len ( records ) == len ( contig_uids ) : success = True else : logger . warning ( "%d contigs expected, %d contigs returned" , len ( contig_uids ) , len ( records ) ) logger . warning ( "FASTA download for assembly %s failed" , asm_uid ) logger . warning ( "try %d/20" , tries ) # Could also check expected assembly sequence length? logger . info ( "Downloaded genome size: %d" , sum ( [ len ( r ) for r in records ] ) ) except : logger . warning ( "FASTA download for assembly %s failed" , asm_uid ) logger . warning ( last_exception ( ) ) logger . warning ( "try %d/20" , tries ) if not success : # Could place option on command-line to stop or continue here. logger . error ( "Failed to download records for %s (continuing)" , asm_uid ) # Write contigs to file retval = SeqIO . write ( records , outfilename , 'fasta' ) logger . info ( "Wrote %d contigs to %s" , retval , outfilename ) | Writes assembly contigs out to a single FASTA file in the script s designated output directory . | 847 | 21 |
18,714 | def logreport_downloaded ( accession , skippedlist , accessiondict , uidaccdict ) : for vid in accessiondict [ accession . split ( '.' ) [ 0 ] ] : if vid in skippedlist : status = "NOT DOWNLOADED" else : status = "DOWNLOADED" logger . warning ( "\t\t%s: %s - %s" , vid , uidaccdict [ vid ] , status ) | Reports to logger whether alternative assemblies for an accession that was missing have been downloaded | 100 | 16 |
18,715 | def calculate_tetra_zscores ( infilenames ) : org_tetraz = { } for filename in infilenames : org = os . path . splitext ( os . path . split ( filename ) [ - 1 ] ) [ 0 ] org_tetraz [ org ] = calculate_tetra_zscore ( filename ) return org_tetraz | Returns dictionary of TETRA Z - scores for each input file . | 85 | 14 |
18,716 | def calculate_tetra_zscore ( filename ) : # For the Teeling et al. method, the Z-scores require us to count # mono, di, tri and tetranucleotide sequences - these are stored # (in order) in the counts tuple counts = ( collections . defaultdict ( int ) , collections . defaultdict ( int ) , collections . defaultdict ( int ) , collections . defaultdict ( int ) ) for rec in SeqIO . parse ( filename , 'fasta' ) : for seq in [ str ( rec . seq ) . upper ( ) , str ( rec . seq . reverse_complement ( ) ) . upper ( ) ] : # The Teeling et al. algorithm requires us to consider # both strand orientations, so monocounts are easy for base in ( 'G' , 'C' , 'T' , 'A' ) : counts [ 0 ] [ base ] += seq . count ( base ) # For di, tri and tetranucleotide counts, loop over the # sequence and its reverse complement, until near the end: for i in range ( len ( seq [ : - 4 ] ) ) : din , tri , tetra = seq [ i : i + 2 ] , seq [ i : i + 3 ] , seq [ i : i + 4 ] counts [ 1 ] [ str ( din ) ] += 1 counts [ 2 ] [ str ( tri ) ] += 1 counts [ 3 ] [ str ( tetra ) ] += 1 # Then clean up the straggling bit at the end: counts [ 2 ] [ str ( seq [ - 4 : - 1 ] ) ] += 1 counts [ 2 ] [ str ( seq [ - 3 : ] ) ] += 1 counts [ 1 ] [ str ( seq [ - 4 : - 2 ] ) ] += 1 counts [ 1 ] [ str ( seq [ - 3 : - 1 ] ) ] += 1 counts [ 1 ] [ str ( seq [ - 2 : ] ) ] += 1 # Following Teeling (2004), calculate expected frequencies for each # tetranucleotide; we ignore ambiguity symbols tetra_exp = { } for tet in [ tetn for tetn in counts [ 3 ] if tetra_clean ( tetn ) ] : tetra_exp [ tet ] = 1. * counts [ 2 ] [ tet [ : 3 ] ] * counts [ 2 ] [ tet [ 1 : ] ] / counts [ 1 ] [ tet [ 1 : 3 ] ] # Following Teeling (2004) we approximate the std dev and Z-score for each # tetranucleotide tetra_sd = { } tetra_z = { } for tet , exp in list ( tetra_exp . items ( ) ) : den = counts [ 1 ] [ tet [ 1 : 3 ] ] tetra_sd [ tet ] = math . sqrt ( exp * ( den - counts [ 2 ] [ tet [ : 3 ] ] ) * ( den - counts [ 2 ] [ tet [ 1 : ] ] ) / ( den * den ) ) try : tetra_z [ tet ] = ( counts [ 3 ] [ tet ] - exp ) / tetra_sd [ tet ] except ZeroDivisionError : # To record if we hit a zero in the estimation of variance # zeroes = [k for k, v in list(tetra_sd.items()) if v == 0] tetra_z [ tet ] = 1 / ( counts [ 1 ] [ tet [ 1 : 3 ] ] * counts [ 1 ] [ tet [ 1 : 3 ] ] ) return tetra_z | Returns TETRA Z - score for the sequence in the passed file . | 759 | 15 |
18,717 | def calculate_correlations ( tetra_z ) : orgs = sorted ( tetra_z . keys ( ) ) correlations = pd . DataFrame ( index = orgs , columns = orgs , dtype = float ) . fillna ( 1.0 ) for idx , org1 in enumerate ( orgs [ : - 1 ] ) : for org2 in orgs [ idx + 1 : ] : assert sorted ( tetra_z [ org1 ] . keys ( ) ) == sorted ( tetra_z [ org2 ] . keys ( ) ) tets = sorted ( tetra_z [ org1 ] . keys ( ) ) zscores = [ [ tetra_z [ org1 ] [ t ] for t in tets ] , [ tetra_z [ org2 ] [ t ] for t in tets ] ] zmeans = [ sum ( zscore ) / len ( zscore ) for zscore in zscores ] zdiffs = [ [ z - zmeans [ 0 ] for z in zscores [ 0 ] ] , [ z - zmeans [ 1 ] for z in zscores [ 1 ] ] ] diffprods = sum ( [ zdiffs [ 0 ] [ i ] * zdiffs [ 1 ] [ i ] for i in range ( len ( zdiffs [ 0 ] ) ) ] ) zdiffs2 = [ sum ( [ z * z for z in zdiffs [ 0 ] ] ) , sum ( [ z * z for z in zdiffs [ 1 ] ] ) ] correlations [ org1 ] [ org2 ] = diffprods / math . sqrt ( zdiffs2 [ 0 ] * zdiffs2 [ 1 ] ) correlations [ org2 ] [ org1 ] = correlations [ org1 ] [ org2 ] return correlations | Returns dataframe of Pearson correlation coefficients . | 393 | 8 |
18,718 | def get_labels ( filename , logger = None ) : labeldict = { } if filename is not None : if logger : logger . info ( "Reading labels from %s" , filename ) with open ( filename , "r" ) as ifh : count = 0 for line in ifh . readlines ( ) : count += 1 try : key , label = line . strip ( ) . split ( "\t" ) except ValueError : if logger : logger . warning ( "Problem with class file: %s" , filename ) logger . warning ( "%d: %s" , ( count , line . strip ( ) ) ) logger . warning ( "(skipping line)" ) continue else : labeldict [ key ] = label return labeldict | Returns a dictionary of alternative sequence labels or None | 162 | 9 |
18,719 | def add_tot_length ( self , qname , sname , value , sym = True ) : self . alignment_lengths . loc [ qname , sname ] = value if sym : self . alignment_lengths . loc [ sname , qname ] = value | Add a total length value to self . alignment_lengths . | 60 | 13 |
18,720 | def add_sim_errors ( self , qname , sname , value , sym = True ) : self . similarity_errors . loc [ qname , sname ] = value if sym : self . similarity_errors . loc [ sname , qname ] = value | Add a similarity error value to self . similarity_errors . | 57 | 12 |
18,721 | def add_pid ( self , qname , sname , value , sym = True ) : self . percentage_identity . loc [ qname , sname ] = value if sym : self . percentage_identity . loc [ sname , qname ] = value | Add a percentage identity value to self . percentage_identity . | 57 | 13 |
18,722 | def add_coverage ( self , qname , sname , qcover , scover = None ) : self . alignment_coverage . loc [ qname , sname ] = qcover if scover : self . alignment_coverage . loc [ sname , qname ] = scover | Add percentage coverage values to self . alignment_coverage . | 63 | 12 |
18,723 | def get_db_name ( self , fname ) : return self . funcs . db_func ( fname , self . outdir , self . exes . format_exe ) [ 1 ] | Return database filename | 43 | 3 |
18,724 | def build_blast_cmd ( self , fname , dbname ) : return self . funcs . blastn_func ( fname , dbname , self . outdir , self . exes . blast_exe ) | Return BLASTN command | 47 | 5 |
18,725 | def fragment_fasta_files ( infiles , outdirname , fragsize ) : outfnames = [ ] for fname in infiles : outstem , outext = os . path . splitext ( os . path . split ( fname ) [ - 1 ] ) outfname = os . path . join ( outdirname , outstem ) + "-fragments" + outext outseqs = [ ] count = 0 for seq in SeqIO . parse ( fname , "fasta" ) : idx = 0 while idx < len ( seq ) : count += 1 newseq = seq [ idx : idx + fragsize ] newseq . id = "frag%05d" % count outseqs . append ( newseq ) idx += fragsize outfnames . append ( outfname ) SeqIO . write ( outseqs , outfname , "fasta" ) return outfnames , get_fraglength_dict ( outfnames ) | Chops sequences of the passed files into fragments returns filenames . | 220 | 14 |
18,726 | def get_fraglength_dict ( fastafiles ) : fraglength_dict = { } for filename in fastafiles : qname = os . path . split ( filename ) [ - 1 ] . split ( "-fragments" ) [ 0 ] fraglength_dict [ qname ] = get_fragment_lengths ( filename ) return fraglength_dict | Returns dictionary of sequence fragment lengths keyed by query name . | 80 | 12 |
18,727 | def get_fragment_lengths ( fastafile ) : fraglengths = { } for seq in SeqIO . parse ( fastafile , "fasta" ) : fraglengths [ seq . id ] = len ( seq ) return fraglengths | Returns dictionary of sequence fragment lengths keyed by fragment ID . | 57 | 12 |
18,728 | def build_db_jobs ( infiles , blastcmds ) : dbjobdict = { } # Dict of database construction jobs, keyed by filename # Create dictionary of database building jobs, keyed by db name # defining jobnum for later use as last job index used for idx , fname in enumerate ( infiles ) : dbjobdict [ blastcmds . get_db_name ( fname ) ] = pyani_jobs . Job ( "%s_db_%06d" % ( blastcmds . prefix , idx ) , blastcmds . build_db_cmd ( fname ) ) return dbjobdict | Returns dictionary of db - building commands keyed by dbname . | 137 | 13 |
18,729 | def make_blastcmd_builder ( mode , outdir , format_exe = None , blast_exe = None , prefix = "ANIBLAST" ) : if mode == "ANIb" : # BLAST/formatting executable depends on mode blastcmds = BLASTcmds ( BLASTfunctions ( construct_makeblastdb_cmd , construct_blastn_cmdline ) , BLASTexes ( format_exe or pyani_config . MAKEBLASTDB_DEFAULT , blast_exe or pyani_config . BLASTN_DEFAULT , ) , prefix , outdir , ) else : blastcmds = BLASTcmds ( BLASTfunctions ( construct_formatdb_cmd , construct_blastall_cmdline ) , BLASTexes ( format_exe or pyani_config . FORMATDB_DEFAULT , blast_exe or pyani_config . BLASTALL_DEFAULT , ) , prefix , outdir , ) return blastcmds | Returns BLASTcmds object for construction of BLAST commands . | 210 | 13 |
18,730 | def make_job_graph ( infiles , fragfiles , blastcmds ) : joblist = [ ] # Holds list of job dependency graphs # Get dictionary of database-building jobs dbjobdict = build_db_jobs ( infiles , blastcmds ) # Create list of BLAST executable jobs, with dependencies jobnum = len ( dbjobdict ) for idx , fname1 in enumerate ( fragfiles [ : - 1 ] ) : for fname2 in fragfiles [ idx + 1 : ] : jobnum += 1 jobs = [ pyani_jobs . Job ( "%s_exe_%06d_a" % ( blastcmds . prefix , jobnum ) , blastcmds . build_blast_cmd ( fname1 , fname2 . replace ( "-fragments" , "" ) ) , ) , pyani_jobs . Job ( "%s_exe_%06d_b" % ( blastcmds . prefix , jobnum ) , blastcmds . build_blast_cmd ( fname2 , fname1 . replace ( "-fragments" , "" ) ) , ) , ] jobs [ 0 ] . add_dependency ( dbjobdict [ fname1 . replace ( "-fragments" , "" ) ] ) jobs [ 1 ] . add_dependency ( dbjobdict [ fname2 . replace ( "-fragments" , "" ) ] ) joblist . extend ( jobs ) # Return the dependency graph return joblist | Return a job dependency graph based on the passed input sequence files . | 318 | 13 |
18,731 | def construct_makeblastdb_cmd ( filename , outdir , blastdb_exe = pyani_config . MAKEBLASTDB_DEFAULT ) : title = os . path . splitext ( os . path . split ( filename ) [ - 1 ] ) [ 0 ] outfilename = os . path . join ( outdir , os . path . split ( filename ) [ - 1 ] ) return ( "{0} -dbtype nucl -in {1} -title {2} -out {3}" . format ( blastdb_exe , filename , title , outfilename ) , outfilename , ) | Returns a single makeblastdb command . | 129 | 8 |
18,732 | def construct_formatdb_cmd ( filename , outdir , blastdb_exe = pyani_config . FORMATDB_DEFAULT ) : title = os . path . splitext ( os . path . split ( filename ) [ - 1 ] ) [ 0 ] newfilename = os . path . join ( outdir , os . path . split ( filename ) [ - 1 ] ) shutil . copy ( filename , newfilename ) return ( "{0} -p F -i {1} -t {2}" . format ( blastdb_exe , newfilename , title ) , newfilename , ) | Returns a single formatdb command . | 128 | 7 |
18,733 | def generate_blastn_commands ( filenames , outdir , blast_exe = None , mode = "ANIb" ) : if mode == "ANIb" : construct_blast_cmdline = construct_blastn_cmdline else : construct_blast_cmdline = construct_blastall_cmdline cmdlines = [ ] for idx , fname1 in enumerate ( filenames [ : - 1 ] ) : dbname1 = fname1 . replace ( "-fragments" , "" ) for fname2 in filenames [ idx + 1 : ] : dbname2 = fname2 . replace ( "-fragments" , "" ) if blast_exe is None : cmdlines . append ( construct_blast_cmdline ( fname1 , dbname2 , outdir ) ) cmdlines . append ( construct_blast_cmdline ( fname2 , dbname1 , outdir ) ) else : cmdlines . append ( construct_blast_cmdline ( fname1 , dbname2 , outdir , blast_exe ) ) cmdlines . append ( construct_blast_cmdline ( fname2 , dbname1 , outdir , blast_exe ) ) return cmdlines | Return a list of blastn command - lines for ANIm | 262 | 12 |
18,734 | def construct_blastn_cmdline ( fname1 , fname2 , outdir , blastn_exe = pyani_config . BLASTN_DEFAULT ) : fstem1 = os . path . splitext ( os . path . split ( fname1 ) [ - 1 ] ) [ 0 ] fstem2 = os . path . splitext ( os . path . split ( fname2 ) [ - 1 ] ) [ 0 ] fstem1 = fstem1 . replace ( "-fragments" , "" ) prefix = os . path . join ( outdir , "%s_vs_%s" % ( fstem1 , fstem2 ) ) cmd = ( "{0} -out {1}.blast_tab -query {2} -db {3} " + "-xdrop_gap_final 150 -dust no -evalue 1e-15 " + "-max_target_seqs 1 -outfmt '6 qseqid sseqid length mismatch " + "pident nident qlen slen qstart qend sstart send positive " + "ppos gaps' -task blastn" ) return cmd . format ( blastn_exe , prefix , fname1 , fname2 ) | Returns a single blastn command . | 266 | 7 |
18,735 | def construct_blastall_cmdline ( fname1 , fname2 , outdir , blastall_exe = pyani_config . BLASTALL_DEFAULT ) : fstem1 = os . path . splitext ( os . path . split ( fname1 ) [ - 1 ] ) [ 0 ] fstem2 = os . path . splitext ( os . path . split ( fname2 ) [ - 1 ] ) [ 0 ] fstem1 = fstem1 . replace ( "-fragments" , "" ) prefix = os . path . join ( outdir , "%s_vs_%s" % ( fstem1 , fstem2 ) ) cmd = ( "{0} -p blastn -o {1}.blast_tab -i {2} -d {3} " + "-X 150 -q -1 -F F -e 1e-15 " + "-b 1 -v 1 -m 8" ) return cmd . format ( blastall_exe , prefix , fname1 , fname2 ) | Returns a single blastall command . | 225 | 7 |
18,736 | def process_blast ( blast_dir , org_lengths , fraglengths = None , mode = "ANIb" , identity = 0.3 , coverage = 0.7 , logger = None , ) : # Process directory to identify input files blastfiles = pyani_files . get_input_files ( blast_dir , ".blast_tab" ) # Hold data in ANIResults object results = ANIResults ( list ( org_lengths . keys ( ) ) , mode ) # Fill diagonal NA values for alignment_length with org_lengths for org , length in list ( org_lengths . items ( ) ) : results . alignment_lengths [ org ] [ org ] = length # Process .blast_tab files assuming that the filename format holds: # org1_vs_org2.blast_tab: for blastfile in blastfiles : qname , sname = os . path . splitext ( os . path . split ( blastfile ) [ - 1 ] ) [ 0 ] . split ( "_vs_" ) # We may have BLAST files from other analyses in the same directory # If this occurs, we raise a warning, and skip the file if qname not in list ( org_lengths . keys ( ) ) : if logger : logger . warning ( "Query name %s not in input " % qname + "sequence list, skipping %s" % blastfile ) continue if sname not in list ( org_lengths . keys ( ) ) : if logger : logger . warning ( "Subject name %s not in input " % sname + "sequence list, skipping %s" % blastfile ) continue resultvals = parse_blast_tab ( blastfile , fraglengths , identity , coverage , mode ) query_cover = float ( resultvals [ 0 ] ) / org_lengths [ qname ] # Populate dataframes: when assigning data, we need to note that # we have asymmetrical data from BLAST output, so only the # upper triangle is populated results . add_tot_length ( qname , sname , resultvals [ 0 ] , sym = False ) results . add_sim_errors ( qname , sname , resultvals [ 1 ] , sym = False ) results . add_pid ( qname , sname , 0.01 * resultvals [ 2 ] , sym = False ) results . add_coverage ( qname , sname , query_cover ) return results | Returns a tuple of ANIb results for . blast_tab files in the output dir . | 523 | 19 |
18,737 | def split_seq ( iterable , size ) : elm = iter ( iterable ) item = list ( itertools . islice ( elm , size ) ) while item : yield item item = list ( itertools . islice ( elm , size ) ) | Splits a passed iterable into chunks of a given size . | 60 | 13 |
18,738 | def build_joblist ( jobgraph ) : jobset = set ( ) for job in jobgraph : jobset = populate_jobset ( job , jobset , depth = 1 ) return list ( jobset ) | Returns a list of jobs from a passed jobgraph . | 45 | 11 |
18,739 | def compile_jobgroups_from_joblist ( joblist , jgprefix , sgegroupsize ) : jobcmds = defaultdict ( list ) for job in joblist : jobcmds [ job . command . split ( ' ' , 1 ) [ 0 ] ] . append ( job . command ) jobgroups = [ ] for cmds in list ( jobcmds . items ( ) ) : # Break arglist up into batches of sgegroupsize (default: 10,000) sublists = split_seq ( cmds [ 1 ] , sgegroupsize ) count = 0 for sublist in sublists : count += 1 sge_jobcmdlist = [ '\"%s\"' % jc for jc in sublist ] jobgroups . append ( JobGroup ( "%s_%d" % ( jgprefix , count ) , "$cmds" , arguments = { 'cmds' : sge_jobcmdlist } ) ) return jobgroups | Return list of jobgroups rather than list of jobs . | 207 | 11 |
18,740 | def run_dependency_graph ( jobgraph , logger = None , jgprefix = "ANIm_SGE_JG" , sgegroupsize = 10000 , sgeargs = None ) : joblist = build_joblist ( jobgraph ) # Try to be informative by telling the user what jobs will run dep_count = 0 # how many dependencies are there if logger : logger . info ( "Jobs to run with scheduler" ) for job in joblist : logger . info ( "{0}: {1}" . format ( job . name , job . command ) ) if len ( job . dependencies ) : dep_count += len ( job . dependencies ) for dep in job . dependencies : logger . info ( "\t[^ depends on: %s]" % dep . name ) logger . info ( "There are %d job dependencies" % dep_count ) # If there are no job dependencies, we can use an array (or series of # arrays) to schedule our jobs. This cuts down on problems with long # job lists choking up the queue. if dep_count == 0 : logger . info ( "Compiling jobs into JobGroups" ) joblist = compile_jobgroups_from_joblist ( joblist , jgprefix , sgegroupsize ) # Send jobs to scheduler logger . info ( "Running jobs with scheduler..." ) logger . info ( "Jobs passed to scheduler in order:" ) for job in joblist : logger . info ( "\t%s" % job . name ) build_and_submit_jobs ( os . curdir , joblist , sgeargs ) logger . info ( "Waiting for SGE-submitted jobs to finish (polling)" ) for job in joblist : job . wait ( ) | Creates and runs GridEngine scripts for jobs based on the passed jobgraph . | 376 | 16 |
18,741 | def populate_jobset ( job , jobset , depth ) : jobset . add ( job ) if len ( job . dependencies ) == 0 : return jobset for j in job . dependencies : jobset = populate_jobset ( j , jobset , depth + 1 ) return jobset | Creates a set of jobs containing jobs at difference depths of the dependency tree retaining dependencies as strings not Jobs . | 61 | 22 |
18,742 | def build_job_scripts ( root_dir , jobs ) : # Loop over the job list, creating each job script in turn, and then adding # scriptPath to the Job object for job in jobs : scriptpath = os . path . join ( root_dir , "jobs" , job . name ) with open ( scriptpath , "w" ) as scriptfile : scriptfile . write ( "#!/bin/sh\n#$ -S /bin/bash\n%s\n" % job . script ) job . scriptpath = scriptpath | Constructs the script for each passed Job in the jobs iterable | 116 | 13 |
18,743 | def extract_submittable_jobs ( waiting ) : submittable = set ( ) # Holds jobs that are able to be submitted # Loop over each job, and check all the subjobs in that job's dependency # list. If there are any, and all of these have been submitted, then # append the job to the list of submittable jobs. for job in waiting : unsatisfied = sum ( [ ( subjob . submitted is False ) for subjob in job . dependencies ] ) if unsatisfied == 0 : submittable . add ( job ) return list ( submittable ) | Obtain a list of jobs that are able to be submitted from the passed list of pending jobs | 125 | 19 |
18,744 | def submit_safe_jobs ( root_dir , jobs , sgeargs = None ) : # Loop over each job, constructing SGE command-line based on job settings for job in jobs : job . out = os . path . join ( root_dir , "stdout" ) job . err = os . path . join ( root_dir , "stderr" ) # Add the job name, current working directory, and SGE stdout/stderr # directories to the SGE command line args = " -N %s " % ( job . name ) args += " -cwd " args += " -o %s -e %s " % ( job . out , job . err ) # If a queue is specified, add this to the SGE command line # LP: This has an undeclared variable, not sure why - delete? #if job.queue is not None and job.queue in local_queues: # args += local_queues[job.queue] # If the job is actually a JobGroup, add the task numbering argument if isinstance ( job , JobGroup ) : args += "-t 1:%d " % ( job . tasks ) # If there are dependencies for this job, hold the job until they are # complete if len ( job . dependencies ) > 0 : args += "-hold_jid " for dep in job . dependencies : args += dep . name + "," args = args [ : - 1 ] # Build the qsub SGE commandline (passing local environment) qsubcmd = ( "%s -V %s %s" % ( pyani_config . QSUB_DEFAULT , args , job . scriptpath ) ) if sgeargs is not None : qsubcmd = "%s %s" % ( qsubcmd , sgeargs ) os . system ( qsubcmd ) # Run the command job . submitted = True | Submit the passed list of jobs to the Grid Engine server using the passed directory as the root for scheduler output . | 405 | 23 |
18,745 | def submit_jobs ( root_dir , jobs , sgeargs = None ) : waiting = list ( jobs ) # List of jobs still to be done # Loop over the list of pending jobs, while there still are any while len ( waiting ) > 0 : # extract submittable jobs submittable = extract_submittable_jobs ( waiting ) # run those jobs submit_safe_jobs ( root_dir , submittable , sgeargs ) # remove those from the waiting list for job in submittable : waiting . remove ( job ) | Submit each of the passed jobs to the SGE server using the passed directory as root for SGE output . | 116 | 22 |
18,746 | def build_and_submit_jobs ( root_dir , jobs , sgeargs = None ) : # If the passed set of jobs is not a list, turn it into one. This makes the # use of a single JobGroup a little more intutitive if not isinstance ( jobs , list ) : jobs = [ jobs ] # Build and submit the passed jobs build_directories ( root_dir ) # build all necessary directories build_job_scripts ( root_dir , jobs ) # build job scripts submit_jobs ( root_dir , jobs , sgeargs ) | Submits the passed iterable of Job objects to SGE placing SGE s output in the passed root directory | 121 | 22 |
18,747 | def params_mpl ( df ) : return { 'ANIb_alignment_lengths' : ( 'afmhot' , df . values . min ( ) , df . values . max ( ) ) , 'ANIb_percentage_identity' : ( 'spbnd_BuRd' , 0 , 1 ) , 'ANIb_alignment_coverage' : ( 'BuRd' , 0 , 1 ) , 'ANIb_hadamard' : ( 'hadamard_BuRd' , 0 , 1 ) , 'ANIb_similarity_errors' : ( 'afmhot' , df . values . min ( ) , df . values . max ( ) ) , 'ANIm_alignment_lengths' : ( 'afmhot' , df . values . min ( ) , df . values . max ( ) ) , 'ANIm_percentage_identity' : ( 'spbnd_BuRd' , 0 , 1 ) , 'ANIm_alignment_coverage' : ( 'BuRd' , 0 , 1 ) , 'ANIm_hadamard' : ( 'hadamard_BuRd' , 0 , 1 ) , 'ANIm_similarity_errors' : ( 'afmhot' , df . values . min ( ) , df . values . max ( ) ) , 'TETRA_correlations' : ( 'spbnd_BuRd' , 0 , 1 ) , 'ANIblastall_alignment_lengths' : ( 'afmhot' , df . values . min ( ) , df . values . max ( ) ) , 'ANIblastall_percentage_identity' : ( 'spbnd_BuRd' , 0 , 1 ) , 'ANIblastall_alignment_coverage' : ( 'BuRd' , 0 , 1 ) , 'ANIblastall_hadamard' : ( 'hadamard_BuRd' , 0 , 1 ) , 'ANIblastall_similarity_errors' : ( 'afmhot' , df . values . min ( ) , df . values . max ( ) ) } | Returns dict of matplotlib parameters dependent on dataframe . | 473 | 12 |
18,748 | def download_file ( fname , target_dir = None , force = False ) : target_dir = target_dir or temporary_dir ( ) target_fname = os . path . join ( target_dir , fname ) if force or not os . path . isfile ( target_fname ) : url = urljoin ( datasets_url , fname ) urlretrieve ( url , target_fname ) return target_fname | Download fname from the datasets_url and save it to target_dir unless the file already exists and force is False . | 95 | 25 |
18,749 | def parse_idx ( fd ) : DATA_TYPES = { 0x08 : 'B' , # unsigned byte 0x09 : 'b' , # signed byte 0x0b : 'h' , # short (2 bytes) 0x0c : 'i' , # int (4 bytes) 0x0d : 'f' , # float (4 bytes) 0x0e : 'd' } # double (8 bytes) header = fd . read ( 4 ) if len ( header ) != 4 : raise IdxDecodeError ( 'Invalid IDX file, ' 'file empty or does not contain a full header.' ) zeros , data_type , num_dimensions = struct . unpack ( '>HBB' , header ) if zeros != 0 : raise IdxDecodeError ( 'Invalid IDX file, ' 'file must start with two zero bytes. ' 'Found 0x%02x' % zeros ) try : data_type = DATA_TYPES [ data_type ] except KeyError : raise IdxDecodeError ( 'Unknown data type ' '0x%02x in IDX file' % data_type ) dimension_sizes = struct . unpack ( '>' + 'I' * num_dimensions , fd . read ( 4 * num_dimensions ) ) data = array . array ( data_type , fd . read ( ) ) data . byteswap ( ) # looks like array.array reads data as little endian expected_items = functools . reduce ( operator . mul , dimension_sizes ) if len ( data ) != expected_items : raise IdxDecodeError ( 'IDX file has wrong number of items. ' 'Expected: %d. Found: %d' % ( expected_items , len ( data ) ) ) return numpy . array ( data ) . reshape ( dimension_sizes ) | Parse an IDX file and return it as a numpy array . | 417 | 15 |
18,750 | def download_and_parse_mnist_file ( fname , target_dir = None , force = False ) : fname = download_file ( fname , target_dir = target_dir , force = force ) fopen = gzip . open if os . path . splitext ( fname ) [ 1 ] == '.gz' else open with fopen ( fname , 'rb' ) as fd : return parse_idx ( fd ) | Download the IDX file named fname from the URL specified in dataset_url and return it as a numpy array . | 100 | 25 |
18,751 | def fetch_next_page ( self ) : for page in self : return page else : return Page ( self . _resultset . cursor , iter ( ( ) ) ) | Fetch the next Page of results . | 36 | 8 |
18,752 | def count ( self , * , page_size = DEFAULT_BATCH_SIZE , * * options ) : entities = 0 options = QueryOptions ( self ) . replace ( keys_only = True ) for page in self . paginate ( page_size = page_size , * * options ) : entities += len ( list ( page ) ) return entities | Counts the number of entities that match this query . | 75 | 11 |
18,753 | def delete ( self , * , page_size = DEFAULT_BATCH_SIZE , * * options ) : from . model import delete_multi deleted = 0 options = QueryOptions ( self ) . replace ( keys_only = True ) for page in self . paginate ( page_size = page_size , * * options ) : keys = list ( page ) deleted += len ( keys ) delete_multi ( keys ) return deleted | Deletes all the entities that match this query . | 91 | 10 |
18,754 | def get ( self , * * options ) : sub_query = self . with_limit ( 1 ) options = QueryOptions ( sub_query ) . replace ( batch_size = 1 ) for result in sub_query . run ( * * options ) : return result return None | Run this query and get the first result . | 58 | 9 |
18,755 | def paginate ( self , * , page_size , * * options ) : return Pages ( self . _prepare ( ) , page_size , QueryOptions ( self , * * options ) ) | Run this query and return a page iterator . | 42 | 9 |
18,756 | def namespace ( namespace ) : try : current_namespace = _namespace . current except AttributeError : current_namespace = None set_namespace ( namespace ) try : yield finally : set_namespace ( current_namespace ) | Context manager for stacking the current thread - local default namespace . Exiting the context sets the thread - local default namespace back to the previously - set namespace . If there is no previous namespace then the thread - local namespace is cleared . | 51 | 46 |
18,757 | def lookup_model_by_kind ( kind ) : model = _known_models . get ( kind ) if model is None : raise RuntimeError ( f"Model for kind {kind!r} not found." ) return model | Look up the model instance for a given Datastore kind . | 48 | 13 |
18,758 | def delete_multi ( keys ) : if not keys : return adapter = None for key in keys : if key . is_partial : raise RuntimeError ( f"Key {key!r} is partial." ) model = lookup_model_by_kind ( key . kind ) if adapter is None : adapter = model . _adapter model . pre_delete_hook ( key ) adapter . delete_multi ( keys ) for key in keys : # Micro-optimization to avoid calling get_model. This is OK # to do here because we've already proved that a model for # that kind exists in the previous block. model = _known_models [ key . kind ] model . post_delete_hook ( key ) | Delete a set of entitites from Datastore by their respective keys . | 151 | 15 |
18,759 | def get_multi ( keys ) : if not keys : return [ ] adapter = None for key in keys : if key . is_partial : raise RuntimeError ( f"Key {key!r} is partial." ) model = lookup_model_by_kind ( key . kind ) if adapter is None : adapter = model . _adapter model . pre_get_hook ( key ) entities_data , entities = adapter . get_multi ( keys ) , [ ] for key , entity_data in zip ( keys , entities_data ) : if entity_data is None : entities . append ( None ) continue # Micro-optimization to avoid calling get_model. This is OK # to do here because we've already proved that a model for # that kind exists in the previous block. model = _known_models [ key . kind ] entity = model . _load ( key , entity_data ) entities . append ( entity ) entity . post_get_hook ( ) return entities | Get a set of entities from Datastore by their respective keys . | 207 | 14 |
18,760 | def put_multi ( entities ) : if not entities : return [ ] adapter , requests = None , [ ] for entity in entities : if adapter is None : adapter = entity . _adapter entity . pre_put_hook ( ) requests . append ( PutRequest ( entity . key , entity . unindexed_properties , entity ) ) keys = adapter . put_multi ( requests ) for key , entity in zip ( keys , entities ) : entity . key = key entity . post_put_hook ( ) return entities | Persist a set of entities to Datastore . | 109 | 11 |
18,761 | def from_path ( cls , * path , namespace = None ) : parent = None for i in range ( 0 , len ( path ) , 2 ) : parent = cls ( * path [ i : i + 2 ] , parent = parent , namespace = namespace ) return parent | Build up a Datastore key from a path . | 59 | 11 |
18,762 | def validate ( self , value ) : if isinstance ( value , self . _types ) : return value elif self . optional and value is None : return [ ] if self . repeated else None elif self . repeated and isinstance ( value , ( tuple , list ) ) and all ( isinstance ( x , self . _types ) for x in value ) : return value else : raise TypeError ( f"Value of type {classname(value)} assigned to {classname(self)} property." ) | Validates that value can be assigned to this Property . | 107 | 11 |
18,763 | def prepare_to_store ( self , entity , value ) : if value is None and not self . optional : raise RuntimeError ( f"Property {self.name_on_model} requires a value." ) return value | Prepare value for storage . Called by the Model for each Property value pair it contains before handing the data off to an adapter . | 47 | 26 |
18,764 | def get ( cls , id_or_name , * , parent = None , namespace = None ) : return Key ( cls , id_or_name , parent = parent , namespace = namespace ) . get ( ) | Get an entity by id . | 47 | 6 |
18,765 | def init_app ( self , app , env_file = None , verbose_mode = False ) : if self . app is None : self . app = app self . verbose_mode = verbose_mode if env_file is None : env_file = os . path . join ( os . getcwd ( ) , ".env" ) if not os . path . exists ( env_file ) : warnings . warn ( "can't read {0} - it doesn't exist" . format ( env_file ) ) else : self . __import_vars ( env_file ) | Imports . env file . | 127 | 6 |
18,766 | def __import_vars ( self , env_file ) : with open ( env_file , "r" ) as f : # pylint: disable=invalid-name for line in f : try : line = line . lstrip ( ) if line . startswith ( 'export' ) : line = line . replace ( 'export' , '' , 1 ) key , val = line . strip ( ) . split ( '=' , 1 ) except ValueError : # Take care of blank or comment lines pass else : if not callable ( val ) : if self . verbose_mode : if key in self . app . config : print ( " * Overwriting an existing config var:" " {0}" . format ( key ) ) else : print ( " * Setting an entirely new config var:" " {0}" . format ( key ) ) self . app . config [ key ] = re . sub ( r"\A[\"']|[\"']\Z" , "" , val ) | Actual importing function . | 213 | 5 |
18,767 | def process_response ( self , request , response ) : if hasattr ( request , 'COUNTRY_CODE' ) : response . set_cookie ( key = constants . COUNTRY_COOKIE_NAME , value = request . COUNTRY_CODE , max_age = settings . LANGUAGE_COOKIE_AGE , path = settings . LANGUAGE_COOKIE_PATH , domain = settings . LANGUAGE_COOKIE_DOMAIN ) return response | Shares config with the language cookie as they serve a similar purpose | 107 | 12 |
18,768 | def create_option ( self , name , value , label , selected , index , subindex = None , attrs = None ) : index = str ( index ) if subindex is None else "%s%s%s" % ( index , self . id_separator , subindex ) if attrs is None : attrs = { } option_attrs = self . build_attrs ( self . attrs , attrs ) if self . option_inherits_attrs else { } if selected : option_attrs . update ( self . checked_attribute ) if 'id' in option_attrs : if self . use_nice_ids : option_attrs [ 'id' ] = "%s%s%s" % ( option_attrs [ 'id' ] , self . id_separator , slugify ( label . lower ( ) ) ) else : option_attrs [ 'id' ] = self . id_for_label ( option_attrs [ 'id' ] , index ) return { 'name' : name , 'value' : value , 'label' : label , 'selected' : selected , 'index' : index , 'attrs' : option_attrs , 'type' : self . input_type , 'template_name' : self . option_template_name , 'wrap_label' : True , } | Patch to use nicer ids . | 294 | 7 |
18,769 | def current_version ( ) : filepath = os . path . abspath ( project_root / "directory_components" / "version.py" ) version_py = get_file_string ( filepath ) regex = re . compile ( Utils . get_version ) if regex . search ( version_py ) is not None : current_version = regex . search ( version_py ) . group ( 0 ) print ( color ( "Current directory-components version: {}" . format ( current_version ) , fg = 'blue' , style = 'bold' ) ) get_update_info ( ) else : print ( color ( 'Error finding directory-components version.' , fg = 'red' , style = 'bold' ) ) | Get current version of directory - components . | 163 | 8 |
18,770 | def get_file_string ( filepath ) : with open ( os . path . abspath ( filepath ) ) as f : return f . read ( ) | Get string from file . | 34 | 5 |
18,771 | def replace_in_dirs ( version ) : print ( color ( "Upgrading directory-components dependency in all repos..." , fg = 'blue' , style = 'bold' ) ) for dirname in Utils . dirs : replace = "directory-components=={}" . format ( version ) replace_in_files ( dirname , replace ) done ( version ) | Look through dirs and run replace_in_files in each . | 83 | 14 |
18,772 | def replace_in_files ( dirname , replace ) : filepath = os . path . abspath ( dirname / "requirements.in" ) if os . path . isfile ( filepath ) and header_footer_exists ( filepath ) : replaced = re . sub ( Utils . exp , replace , get_file_string ( filepath ) ) with open ( filepath , "w" ) as f : f . write ( replaced ) print ( color ( "Written to file: {}" . format ( filepath ) , fg = 'magenta' , style = 'bold' ) ) | Replace current version with new version in requirements files . | 132 | 11 |
18,773 | def header_footer_exists ( filepath ) : with open ( filepath ) as f : return re . search ( Utils . exp , f . read ( ) ) | Check if directory - components is listed in requirements files . | 38 | 11 |
18,774 | def linedelimited ( inlist , delimiter ) : outstr = '' for item in inlist : if type ( item ) != StringType : item = str ( item ) outstr = outstr + item + delimiter outstr = outstr [ 0 : - 1 ] return outstr | Returns a string composed of elements in inlist with each element separated by delimiter . Used by function writedelimited . Use \ t for tab - delimiting . | 62 | 35 |
18,775 | def lineincustcols ( inlist , colsizes ) : outstr = '' for i in range ( len ( inlist ) ) : if type ( inlist [ i ] ) != StringType : item = str ( inlist [ i ] ) else : item = inlist [ i ] size = len ( item ) if size <= colsizes [ i ] : for j in range ( colsizes [ i ] - size ) : outstr = outstr + ' ' outstr = outstr + item else : outstr = outstr + item [ 0 : colsizes [ i ] + 1 ] return outstr | Returns a string composed of elements in inlist with each element right - aligned in a column of width specified by a sequence colsizes . The length of colsizes must be greater than or equal to the number of columns in inlist . | 133 | 49 |
18,776 | def list2string ( inlist , delimit = ' ' ) : stringlist = [ makestr ( _ ) for _ in inlist ] return string . join ( stringlist , delimit ) | Converts a 1D list to a single long string for file output using the string . join function . | 43 | 21 |
18,777 | def replace ( inlst , oldval , newval ) : lst = inlst * 1 for i in range ( len ( lst ) ) : if type ( lst [ i ] ) not in [ ListType , TupleType ] : if lst [ i ] == oldval : lst [ i ] = newval else : lst [ i ] = replace ( lst [ i ] , oldval , newval ) return lst | Replaces all occurrences of oldval with newval recursively . | 97 | 14 |
18,778 | def duplicates ( inlist ) : dups = [ ] for i in range ( len ( inlist ) ) : if inlist [ i ] in inlist [ i + 1 : ] : dups . append ( inlist [ i ] ) return dups | Returns duplicate items in the FIRST dimension of the passed list . | 55 | 12 |
18,779 | def nonrepeats ( inlist ) : nonrepeats = [ ] for i in range ( len ( inlist ) ) : if inlist . count ( inlist [ i ] ) == 1 : nonrepeats . append ( inlist [ i ] ) return nonrepeats | Returns items that are NOT duplicated in the first dim of the passed list . | 58 | 16 |
18,780 | def lz ( inlist , score ) : z = ( score - mean ( inlist ) ) / samplestdev ( inlist ) return z | Returns the z - score for a given input score given that score and the list from which that score came . Not appropriate for population calculations . | 32 | 28 |
18,781 | def llinregress ( x , y ) : TINY = 1.0e-20 if len ( x ) != len ( y ) : raise ValueError ( 'Input values not paired in linregress. Aborting.' ) n = len ( x ) x = [ float ( _ ) for _ in x ] y = [ float ( _ ) for _ in y ] xmean = mean ( x ) ymean = mean ( y ) r_num = float ( n * ( summult ( x , y ) ) - sum ( x ) * sum ( y ) ) r_den = math . sqrt ( ( n * ss ( x ) - square_of_sums ( x ) ) * ( n * ss ( y ) - square_of_sums ( y ) ) ) r = r_num / r_den z = 0.5 * math . log ( ( 1.0 + r + TINY ) / ( 1.0 - r + TINY ) ) df = n - 2 t = r * math . sqrt ( df / ( ( 1.0 - r + TINY ) * ( 1.0 + r + TINY ) ) ) prob = betai ( 0.5 * df , 0.5 , df / ( df + t * t ) ) slope = r_num / float ( n * ss ( x ) - square_of_sums ( x ) ) intercept = ymean - slope * xmean sterrest = math . sqrt ( 1 - r * r ) * samplestdev ( y ) return slope , intercept , r , prob , sterrest | Calculates a regression line on x y pairs . | 346 | 11 |
18,782 | def lks_2samp ( data1 , data2 ) : j1 = 0 j2 = 0 fn1 = 0.0 fn2 = 0.0 n1 = len ( data1 ) n2 = len ( data2 ) en1 = n1 en2 = n2 d = 0.0 data1 . sort ( ) data2 . sort ( ) while j1 < n1 and j2 < n2 : d1 = data1 [ j1 ] d2 = data2 [ j2 ] if d1 <= d2 : fn1 = ( j1 ) / float ( en1 ) j1 = j1 + 1 if d2 <= d1 : fn2 = ( j2 ) / float ( en2 ) j2 = j2 + 1 dt = ( fn2 - fn1 ) if math . fabs ( dt ) > math . fabs ( d ) : d = dt try : en = math . sqrt ( en1 * en2 / float ( en1 + en2 ) ) prob = ksprob ( ( en + 0.12 + 0.11 / en ) * abs ( d ) ) except : prob = 1.0 return d , prob | Computes the Kolmogorov - Smirnof statistic on 2 samples . From Numerical Recipies in C page 493 . | 256 | 31 |
18,783 | def lranksums ( x , y ) : n1 = len ( x ) n2 = len ( y ) alldata = x + y ranked = rankdata ( alldata ) x = ranked [ : n1 ] y = ranked [ n1 : ] s = sum ( x ) expected = n1 * ( n1 + n2 + 1 ) / 2.0 z = ( s - expected ) / math . sqrt ( n1 * n2 * ( n1 + n2 + 1 ) / 12.0 ) prob = 2 * ( 1.0 - zprob ( abs ( z ) ) ) return z , prob | Calculates the rank sums statistic on the provided scores and returns the result . Use only when the n in each condition is > 20 and you have 2 independent samples of ranks . | 135 | 36 |
18,784 | def lkruskalwallish ( * args ) : args = list ( args ) n = [ 0 ] * len ( args ) all = [ ] n = [ len ( _ ) for _ in args ] for i in range ( len ( args ) ) : all = all + args [ i ] ranked = rankdata ( all ) T = tiecorrect ( ranked ) for i in range ( len ( args ) ) : args [ i ] = ranked [ 0 : n [ i ] ] del ranked [ 0 : n [ i ] ] rsums = [ ] for i in range ( len ( args ) ) : rsums . append ( sum ( args [ i ] ) ** 2 ) rsums [ i ] = rsums [ i ] / float ( n [ i ] ) ssbn = sum ( rsums ) totaln = sum ( n ) h = 12.0 / ( totaln * ( totaln + 1 ) ) * ssbn - 3 * ( totaln + 1 ) df = len ( args ) - 1 if T == 0 : raise ValueError ( 'All numbers are identical in lkruskalwallish' ) h = h / float ( T ) return h , chisqprob ( h , df ) | The Kruskal - Wallis H - test is a non - parametric ANOVA for 3 or more groups requiring at least 5 subjects in each group . This function calculates the Kruskal - Wallis H - test for 3 or more independent samples and returns the result . | 260 | 56 |
18,785 | def lksprob ( alam ) : fac = 2.0 sum = 0.0 termbf = 0.0 a2 = - 2.0 * alam * alam for j in range ( 1 , 201 ) : term = fac * math . exp ( a2 * j * j ) sum = sum + term if math . fabs ( term ) <= ( 0.001 * termbf ) or math . fabs ( term ) < ( 1.0e-8 * sum ) : return sum fac = - fac termbf = math . fabs ( term ) return 1.0 | Computes a Kolmolgorov - Smirnov t - test significance level . Adapted from Numerical Recipies . | 129 | 27 |
18,786 | def outputpairedstats ( fname , writemode , name1 , n1 , m1 , se1 , min1 , max1 , name2 , n2 , m2 , se2 , min2 , max2 , statname , stat , prob ) : suffix = '' # for *s after the p-value try : x = prob . shape prob = prob [ 0 ] except : pass if prob < 0.001 : suffix = ' ***' elif prob < 0.01 : suffix = ' **' elif prob < 0.05 : suffix = ' *' title = [ [ 'Name' , 'N' , 'Mean' , 'SD' , 'Min' , 'Max' ] ] lofl = title + [ [ name1 , n1 , round ( m1 , 3 ) , round ( math . sqrt ( se1 ) , 3 ) , min1 , max1 ] , [ name2 , n2 , round ( m2 , 3 ) , round ( math . sqrt ( se2 ) , 3 ) , min2 , max2 ] ] if type ( fname ) != StringType or len ( fname ) == 0 : print ( ) print ( statname ) print ( ) pstat . printcc ( lofl ) print ( ) try : if stat . shape == ( ) : stat = stat [ 0 ] if prob . shape == ( ) : prob = prob [ 0 ] except : pass print ( 'Test statistic = ' , round ( stat , 3 ) , ' p = ' , round ( prob , 3 ) , suffix ) print ( ) else : file = open ( fname , writemode ) file . write ( '\n' + statname + '\n\n' ) file . close ( ) writecc ( lofl , fname , 'a' ) file = open ( fname , 'a' ) try : if stat . shape == ( ) : stat = stat [ 0 ] if prob . shape == ( ) : prob = prob [ 0 ] except : pass file . write ( pstat . list2string ( [ '\nTest statistic = ' , round ( stat , 4 ) , ' p = ' , round ( prob , 4 ) , suffix , '\n\n' ] ) ) file . close ( ) return None | Prints or write to a file stats for two groups using the name n mean sterr min and max for each group as well as the statistic name its value and the associated p - value . | 491 | 39 |
18,787 | def GeneReader ( fh , format = 'gff' ) : known_formats = ( 'gff' , 'gtf' , 'bed' ) if format not in known_formats : print ( '%s format not in %s' % ( format , "," . join ( known_formats ) ) , file = sys . stderr ) raise Exception ( '?' ) if format == 'bed' : for line in fh : f = line . strip ( ) . split ( ) chrom = f [ 0 ] chrom_start = int ( f [ 1 ] ) name = f [ 4 ] strand = f [ 5 ] cdsStart = int ( f [ 6 ] ) cdsEnd = int ( f [ 7 ] ) blockCount = int ( f [ 9 ] ) blockSizes = [ int ( i ) for i in f [ 10 ] . strip ( ',' ) . split ( ',' ) ] blockStarts = [ chrom_start + int ( i ) for i in f [ 11 ] . strip ( ',' ) . split ( ',' ) ] # grab cdsStart - cdsEnd gene_exons = [ ] for base , offset in zip ( blockStarts , blockSizes ) : exon_start = base exon_end = base + offset gene_exons . append ( ( exon_start , exon_end ) ) yield chrom , strand , gene_exons , name genelist = { } grouplist = [ ] if format == 'gff' or format == 'gtf' : for line in fh : if line . startswith ( '#' ) : continue fields = line . strip ( ) . split ( '\t' ) if len ( fields ) < 9 : continue # fields chrom = fields [ 0 ] ex_st = int ( fields [ 3 ] ) - 1 # make zero-centered ex_end = int ( fields [ 4 ] ) #+ 1 # make exclusive strand = fields [ 6 ] if format == 'gtf' : group = fields [ 8 ] . split ( ';' ) [ 0 ] else : group = fields [ 8 ] if group not in grouplist : grouplist . append ( group ) if group not in genelist : genelist [ group ] = ( chrom , strand , [ ] ) exons_i = 2 genelist [ group ] [ exons_i ] . append ( ( ex_st , ex_end ) ) sp = lambda a , b : cmp ( a [ 0 ] , b [ 0 ] ) #for gene in genelist.values(): for gene in grouplist : chrom , strand , gene_exons = genelist [ gene ] gene_exons = bitset_union ( gene_exons ) yield chrom , strand , gene_exons , gene | yield chrom strand gene_exons name | 601 | 9 |
18,788 | def get ( self , start , length ) : # Check parameters assert length >= 0 , "Length must be non-negative (got %d)" % length assert start >= 0 , "Start must be greater than 0 (got %d)" % start assert start + length <= self . length , "Interval beyond end of sequence (%s..%s > %s)" % ( start , start + length , self . length ) # Fetch sequence and reverse complement if necesary if not self . revcomp : return self . raw_fetch ( start , length ) if self . revcomp == "-3'" : return self . reverse_complement ( self . raw_fetch ( start , length ) ) assert self . revcomp == "-5'" , "unrecognized reverse complement scheme" start = self . length - ( start + length ) return self . reverse_complement ( self . raw_fetch ( start , length ) ) | Fetch subsequence starting at position start with length length . This method is picky about parameters the requested interval must have non - negative length and fit entirely inside the NIB sequence the returned string will contain exactly length characters or an AssertionError will be generated . | 197 | 54 |
18,789 | def read_scoring_scheme ( f , gap_open , gap_extend , gap1 = "-" , gap2 = None , * * kwargs ) : close_it = False if ( type ( f ) == str ) : f = file ( f , "rt" ) close_it = True ss = build_scoring_scheme ( "" . join ( [ line for line in f ] ) , gap_open , gap_extend , gap1 = gap1 , gap2 = gap2 , * * kwargs ) if ( close_it ) : f . close ( ) return ss | Initialize scoring scheme from a file containint a blastz style text blob . f can be either a file or the name of a file . | 130 | 29 |
18,790 | def shuffle_columns ( a ) : mask = range ( a . text_size ) random . shuffle ( mask ) for c in a . components : c . text = '' . join ( [ c . text [ i ] for i in mask ] ) | Randomize the columns of an alignment | 53 | 7 |
18,791 | def slice_by_component ( self , component_index , start , end ) : if type ( component_index ) == type ( 0 ) : ref = self . components [ component_index ] elif type ( component_index ) == type ( "" ) : ref = self . get_component_by_src ( component_index ) elif type ( component_index ) == Component : ref = component_index else : raise ValueError ( "can't figure out what to do" ) start_col = ref . coord_to_col ( start ) end_col = ref . coord_to_col ( end ) if ( ref . strand == '-' ) : ( start_col , end_col ) = ( end_col , start_col ) return self . slice ( start_col , end_col ) | Return a slice of the alignment corresponding to an coordinate interval in a specific component . | 173 | 16 |
18,792 | def remove_all_gap_columns ( self ) : seqs = [ ] for c in self . components : try : seqs . append ( list ( c . text ) ) except TypeError : seqs . append ( None ) i = 0 text_size = self . text_size while i < text_size : all_gap = True for seq in seqs : if seq is None : continue if seq [ i ] != '-' : all_gap = False if all_gap : for seq in seqs : if seq is None : continue del seq [ i ] text_size -= 1 else : i += 1 for i in range ( len ( self . components ) ) : if seqs [ i ] is None : continue self . components [ i ] . text = '' . join ( seqs [ i ] ) self . text_size = text_size | Remove any columns containing only gaps from alignment components text of components is modified IN PLACE . | 183 | 18 |
18,793 | def slice_by_coord ( self , start , end ) : start_col = self . coord_to_col ( start ) end_col = self . coord_to_col ( end ) if ( self . strand == '-' ) : ( start_col , end_col ) = ( end_col , start_col ) return self . slice ( start_col , end_col ) | Return the slice of the component corresponding to a coordinate interval . | 84 | 12 |
18,794 | def coord_to_col ( self , pos ) : start , end = self . get_forward_strand_start ( ) , self . get_forward_strand_end ( ) if pos < start or pos > end : raise ValueError ( "Range error: %d not in %d-%d" % ( pos , start , end ) ) if not self . index : self . index = list ( ) if ( self . strand == '-' ) : # nota bene: for - strand self.index[x] maps to one column # higher than is actually associated with the position; thus # when slice_by_component() and slice_by_coord() flip the ends, # the resulting slice is correct for x in range ( len ( self . text ) - 1 , - 1 , - 1 ) : if not self . text [ x ] == '-' : self . index . append ( x + 1 ) self . index . append ( 0 ) else : for x in range ( len ( self . text ) ) : if not self . text [ x ] == '-' : self . index . append ( x ) self . index . append ( len ( self . text ) ) x = None try : x = self . index [ pos - start ] except : raise Exception ( "Error in index." ) return x | Return the alignment column index corresponding to coordinate pos . | 281 | 10 |
18,795 | def get_components_for_species ( alignment , species ) : # If the number of components in the alignment is less that the requested number # of species we can immediately fail if len ( alignment . components ) < len ( species ) : return None # Otherwise, build an index of components by species, then lookup index = dict ( [ ( c . src . split ( '.' ) [ 0 ] , c ) for c in alignment . components ] ) try : return [ index [ s ] for s in species ] except : return None | Return the component for each species in the list species or None | 111 | 12 |
18,796 | def read_next_maf ( file , species_to_lengths = None , parse_e_rows = False ) : alignment = Alignment ( species_to_lengths = species_to_lengths ) # Attributes line line = readline ( file , skip_blank = True ) if not line : return None fields = line . split ( ) if fields [ 0 ] != 'a' : raise Exception ( "Expected 'a ...' line" ) alignment . attributes = parse_attributes ( fields [ 1 : ] ) if 'score' in alignment . attributes : alignment . score = alignment . attributes [ 'score' ] del alignment . attributes [ 'score' ] else : alignment . score = 0 # Sequence lines last_component = None while 1 : line = readline ( file ) # EOF or Blank line terminates alignment components if not line or line . isspace ( ) : break if line . isspace ( ) : break # Parse row fields = line . split ( ) if fields [ 0 ] == 's' : # An 's' row contains sequence for a component component = Component ( ) component . src = fields [ 1 ] component . start = int ( fields [ 2 ] ) component . size = int ( fields [ 3 ] ) component . strand = fields [ 4 ] component . src_size = int ( fields [ 5 ] ) if len ( fields ) > 6 : component . text = fields [ 6 ] . strip ( ) # Add to set alignment . add_component ( component ) last_component = component elif fields [ 0 ] == 'e' : # An 'e' row, when no bases align for a given species this tells # us something about the synteny if parse_e_rows : component = Component ( ) component . empty = True component . src = fields [ 1 ] component . start = int ( fields [ 2 ] ) component . size = int ( fields [ 3 ] ) component . strand = fields [ 4 ] component . src_size = int ( fields [ 5 ] ) component . text = None synteny = fields [ 6 ] . strip ( ) assert len ( synteny ) == 1 , "Synteny status in 'e' rows should be denoted with a single character code" component . synteny_empty = synteny alignment . add_component ( component ) last_component = component elif fields [ 0 ] == 'i' : # An 'i' row, indicates left and right synteny status for the # previous component, we hope ;) assert fields [ 1 ] == last_component . src , "'i' row does not follow matching 's' row" last_component . synteny_left = ( fields [ 2 ] , int ( fields [ 3 ] ) ) last_component . synteny_right = ( fields [ 4 ] , int ( fields [ 5 ] ) ) elif fields [ 0 ] == 'q' : assert fields [ 1 ] == last_component . src , "'q' row does not follow matching 's' row" # TODO: Should convert this to an integer array? last_component . quality = fields [ 2 ] return alignment | Read the next MAF block from file and return as an Alignment instance . If parse_i_rows is true empty components will be created when e rows are encountered . | 660 | 35 |
18,797 | def readline ( file , skip_blank = False ) : while 1 : line = file . readline ( ) #print "every line: %r" % line if not line : return None if line [ 0 ] != '#' and not ( skip_blank and line . isspace ( ) ) : return line | Read a line from provided file skipping any blank or comment lines | 67 | 12 |
18,798 | def parse_attributes ( fields ) : attributes = { } for field in fields : pair = field . split ( '=' ) attributes [ pair [ 0 ] ] = pair [ 1 ] return attributes | Parse list of key = value strings into a dict | 41 | 11 |
18,799 | def as_dict ( self , key = "id" ) : rval = { } for motif in self : rval [ getattr ( motif , key ) ] = motif return rval | Return a dictionary containing all remaining motifs using key as the dictionary key . | 40 | 15 |
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