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def prepare_env ( app , env , docname ) : if not hasattr ( env , 'needs_all_needs' ) : env . needs_all_needs = { } if not hasattr ( env , 'needs_functions' ) : env . needs_functions = { } needs_functions = app . needs_functions if needs_functions is None : needs_functions = [ ] if not isinstance ( needs_functions , lis...
Prepares the sphinx environment to store sphinx - needs internal data .
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def make_entity_name ( name ) : invalid_chars = "-=!#$%^&*[](){}/~'`<>:;" for char in invalid_chars : name = name . replace ( char , "_" ) return name
Creates a valid PlantUML entity name from the given value .
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def copy ( app , need , needs , option , need_id = None ) : if need_id is not None : need = needs [ need_id ] return need [ option ]
Copies the value of one need option to another
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def check_linked_values ( app , need , needs , result , search_option , search_value , filter_string = None , one_hit = False ) : links = need [ "links" ] if not isinstance ( search_value , list ) : search_value = [ search_value ] for link in links : if filter_string is not None : try : if not filter_single_need ( need...
Returns a specific value if for all linked needs a given option has a given value .
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def calc_sum ( app , need , needs , option , filter = None , links_only = False ) : if not links_only : check_needs = needs . values ( ) else : check_needs = [ ] for link in need [ "links" ] : check_needs . append ( needs [ link ] ) calculated_sum = 0 for check_need in check_needs : if filter is not None : try : if not...
Sums the values of a given option in filtered needs up to single number .
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def noaa_prompt_1 ( ) : print ( "Enter the project information below. We'll use this to create the WDS URL" ) print ( "What is the project name?" ) _project = input ( ">" ) print ( "What is the project version?" ) _version = input ( ">" ) return _project , _version
For converting LiPD files to NOAA we need a couple more pieces of information to create the WDS links
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def lpd_to_noaa ( D , wds_url , lpd_url , version , path = "" ) : logger_noaa . info ( "enter process_lpd" ) d = D try : dsn = get_dsn ( D ) dsn = re . sub ( r'[^A-Za-z-.0-9]' , '' , dsn ) version = re . sub ( r'[^A-Za-z-.0-9]' , '' , version ) _convert_obj = LPD_NOAA ( D , dsn , wds_url , lpd_url , version , path ) _c...
Convert a LiPD format to NOAA format
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def __write_noaas ( dat , path ) : for filename , text in dat . items ( ) : try : with open ( os . path . join ( path , filename ) , "w+" ) as f : f . write ( text ) except Exception as e : print ( "write_noaas: There was a problem writing the NOAA text file: {}: {}" . format ( filename , e ) ) return
Use the filename - text data pairs to write the data as NOAA text files
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def _parse_java_version ( line : str ) -> tuple : m = VERSION_RE . search ( line ) version_str = m and m . group ( 0 ) . replace ( '"' , '' ) or '0.0.0' if '_' in version_str : fst , snd = version_str . split ( '_' , maxsplit = 2 ) version = parse_version ( fst ) return ( version [ 1 ] , version [ 2 ] , int ( snd ) ) e...
Return the version number found in the first line of java - version
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def find_java_home ( cratedb_version : tuple ) -> str : if MIN_VERSION_FOR_JVM11 <= cratedb_version < ( 4 , 0 ) : return os . environ . get ( 'JAVA_HOME' , '' ) if cratedb_version < MIN_VERSION_FOR_JVM11 : return _find_matching_java_home ( lambda ver : ver [ 0 ] == 8 ) else : return _find_matching_java_home ( lambda ve...
Return a path to a JAVA_HOME suites for the given CrateDB version
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def percentile ( sorted_values , p ) : size = len ( sorted_values ) idx = ( p / 100.0 ) * size - 0.5 if idx < 0 or idx > size : raise ValueError ( 'Too few data points ({}) for {}th percentile' . format ( size , p ) ) return sorted_values [ int ( idx ) ]
Calculate the percentile using the nearest rank method .
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def get_sampler ( sample_mode : str ) : if sample_mode == 'all' : return All mode = sample_mode . split ( ':' ) if mode [ 0 ] == 'reservoir' : if len ( mode ) == 2 : return partial ( UniformReservoir , size = int ( mode [ 1 ] ) ) else : return UniformReservoir raise TypeError ( f'Invalid sample_mode: {sample_mode}' )
Return a sampler constructor
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def _get_sheet_metadata ( workbook , name ) : ct_paleo = 1 ct_chron = 1 metadata_str = "" sheets = [ ] skip_sheets = [ "example" , "sample" , "lists" , "guidelines" ] for sheet in workbook . sheet_names ( ) : old = "" . join ( sheet . lower ( ) . strip ( ) . split ( ) ) if not any ( word in sheet . lower ( ) for word i...
Get worksheet metadata . The sheet names tell us what type of table it is and where in the LiPD structure the data should be placed .
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def idx_num_to_name ( L ) : logger_jsons . info ( "enter idx_num_to_name" ) try : if "paleoData" in L : L [ "paleoData" ] = _import_data ( L [ "paleoData" ] , "paleo" ) if "chronData" in L : L [ "chronData" ] = _import_data ( L [ "chronData" ] , "chron" ) except Exception as e : logger_jsons . error ( "idx_num_to_name:...
Switch from index - by - number to index - by - name .
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def _import_data ( sections , crumbs ) : logger_jsons . info ( "enter import_data: {}" . format ( crumbs ) ) _sections = OrderedDict ( ) try : for _idx , section in enumerate ( sections ) : _tmp = OrderedDict ( ) if "measurementTable" in section : _tmp [ "measurementTable" ] = _idx_table_by_name ( section [ "measuremen...
Import the section metadata and change it to index - by - name .
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def _import_model ( models , crumbs ) : logger_jsons . info ( "enter import_model" . format ( crumbs ) ) _models = OrderedDict ( ) try : for _idx , model in enumerate ( models ) : if "summaryTable" in model : model [ "summaryTable" ] = _idx_table_by_name ( model [ "summaryTable" ] , "{}{}{}" . format ( crumbs , _idx , ...
Change the nested items of the paleoModel data . Overwrite the data in - place .
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def _idx_table_by_name ( tables , crumbs ) : _tables = OrderedDict ( ) try : for _idx , _table in enumerate ( tables ) : _name = "{}{}" . format ( crumbs , _idx ) _tmp = _idx_col_by_name ( _table ) if _name in _tables : _name = "{}_{}" . format ( _name , _idx ) _tmp [ "tableName" ] = _name _tables [ _name ] = _tmp exce...
Import summary ensemble or distribution data .
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def _idx_col_by_name ( table ) : _columns = OrderedDict ( ) try : for _column in table [ "columns" ] : try : _name = _column [ "variableName" ] if _name in _columns : _name = get_appended_name ( _name , _columns ) _columns [ _name ] = _column except Exception as e : print ( "Error: idx_col_by_name: inner: {}" . format ...
Iter over columns list . Turn indexed - by - num list into an indexed - by - name dict . Keys are the variable names .
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def _export_model ( models ) : logger_jsons . info ( "enter export_model" ) _models = [ ] try : for name , model in models . items ( ) : if "summaryTable" in model : model [ "summaryTable" ] = _idx_table_by_num ( model [ "summaryTable" ] ) if "ensembleTable" in model : model [ "ensembleTable" ] = _idx_table_by_num ( mo...
Switch model tables to index - by - number
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def _idx_table_by_num ( tables ) : logger_jsons . info ( "enter idx_table_by_num" ) _tables = [ ] for name , table in tables . items ( ) : try : tmp = _idx_col_by_num ( table ) _tables . append ( tmp ) except Exception as e : logger_jsons . error ( "idx_table_by_num: {}" . format ( e ) ) logger_jsons . info ( "exit idx...
Switch tables to index - by - number
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def _idx_col_by_num ( table ) : _columns = [ ] try : _columns = [ None for i in range ( 0 , len ( table [ "columns" ] ) ) ] for _name , _dat in table [ "columns" ] . items ( ) : try : if isinstance ( _dat [ "number" ] , list ) : _columns . append ( _dat ) else : n = int ( _dat [ "number" ] ) _columns [ n - 1 ] = _dat e...
Index columns by number instead of by name . Use number key in column to maintain order
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def _parse_tags ( tag_file ) : tag_name = None tag_value = None for num , line in enumerate ( tag_file ) : if num == 0 : if line . startswith ( BOM ) : line = line . lstrip ( BOM ) if len ( line ) == 0 or line . isspace ( ) : continue elif line [ 0 ] . isspace ( ) and tag_value is not None : tag_value += line else : if...
Parses a tag file according to RFC 2822 . This includes line folding permitting extra - long field values .
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def compare_fetch_with_fs ( self ) : files_on_fs = set ( self . payload_files ( ) ) files_in_fetch = set ( self . files_to_be_fetched ( ) ) return list ( files_in_fetch - files_on_fs )
Compares the fetch entries with the files actually in the payload and returns a list of all the files that still need to be fetched .
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def _validate_bagittxt ( self ) : bagit_file_path = os . path . join ( self . path , "bagit.txt" ) with open ( bagit_file_path , 'r' ) as bagit_file : first_line = bagit_file . readline ( ) if first_line . startswith ( BOM ) : raise BagValidationError ( "bagit.txt must not contain a byte-order mark" )
Verify that bagit . txt conforms to specification
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def resolve_dynamic_values ( env ) : if env . needs_workflow [ 'dynamic_values_resolved' ] : return needs = env . needs_all_needs for key , need in needs . items ( ) : for need_option in need : if need_option in [ 'docname' , 'lineno' , 'target_node' , 'content' ] : continue if not isinstance ( need [ need_option ] , (...
Resolve dynamic values inside need data .
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def run ( ) : global cwd , files , logger_start , logger_benchmark , settings , _timeseries_data _timeseries_data = { } settings = { "note_update" : True , "note_validate" : True , "verbose" : True } cwd = os . getcwd ( ) logger_start = create_logger ( "start" ) logger_benchmark = create_benchmark ( "benchmarks" , "ben...
Initialize and start objects . This is called automatically when importing the package .
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def excel ( ) : global files , cwd , settings _d = { } settings [ "verbose" ] = False print ( "Found " + str ( len ( files [ ".xls" ] ) ) + " Excel files" ) logger_start . info ( "found excel files: {}" . format ( len ( files [ ".xls" ] ) ) ) start = clock ( ) for file in files [ ".xls" ] : dsn = excel_main ( file ) tr...
Convert Excel files to LiPD files . LiPD data is returned directly from this function .
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def noaa ( D = "" , path = "" , wds_url = "" , lpd_url = "" , version = "" ) : global files , cwd _mode = noaa_prompt ( ) start = clock ( ) if _mode == "1" : if not version or not lpd_url : print ( "Missing parameters: Please try again and provide all parameters." ) return if not D : print ( "Error: LiPD data must be p...
Convert between NOAA and LiPD files
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def collapseTs ( ts = None ) : global _timeseries_data _d = { } if not ts : print ( "Error: Time series data not provided. Pass time series into the function." ) else : try : _raw = _timeseries_data [ ts [ 0 ] [ "time_id" ] ] print ( mode_ts ( "collapse" , mode = "" , ts = ts ) ) _d = collapse ( ts , _raw ) _d = rm_emp...
Collapse a time series back into LiPD record form .
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def filterTs ( ts , expressions ) : new_ts = ts [ : ] if isinstance ( expressions , str ) : expr_lst = translate_expression ( expressions ) if expr_lst : new_ts , _idx = get_matches ( expr_lst , new_ts ) elif isinstance ( expressions , list ) : for expr in expressions : expr_lst = translate_expression ( expr ) if expr_...
Create a new time series that only contains entries that match the given expression .
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def queryTs ( ts , expression ) : _idx = [ ] if isinstance ( expressions , str ) : expr_lst = translate_expression ( expressions ) if expr_lst : new_ts , _idx = get_matches ( expr_lst , new_ts ) elif isinstance ( expressions , list ) : for expr in expressions : expr_lst = translate_expression ( expr ) if expr_lst : new...
Find the indices of the time series entries that match the given expression .
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def viewTs ( ts ) : _ts = ts if isinstance ( ts , list ) : _ts = ts [ 0 ] print ( "It looks like you input a full time series. It's best to view one entry at a time.\n" "I'll show you the first entry..." ) _tmp_sort = OrderedDict ( ) _tmp_sort [ "ROOT" ] = { } _tmp_sort [ "PUBLICATION" ] = { } _tmp_sort [ "GEO" ] = { }...
View the contents of one time series entry in a nicely formatted way
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def showLipds ( D = None ) : if not D : print ( "Error: LiPD data not provided. Pass LiPD data into the function." ) else : print ( json . dumps ( D . keys ( ) , indent = 2 ) ) return
Display the dataset names of a given LiPD data
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def showMetadata ( dat ) : _tmp = rm_values_fields ( copy . deepcopy ( dat ) ) print ( json . dumps ( _tmp , indent = 2 ) ) return
Display the metadata specified LiPD in pretty print
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def showDfs ( d ) : if "metadata" in d : print ( "metadata" ) if "paleoData" in d : try : for k , v in d [ "paleoData" ] . items ( ) : print ( k ) except KeyError : pass except AttributeError : pass if "chronData" in d : try : for k , v in d [ "chronData" ] . items ( ) : print ( k ) except KeyError : pass except Attrib...
Display the available data frame names in a given data frame collection
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def getLipdNames ( D = None ) : _names = [ ] try : if not D : print ( "Error: LiPD data not provided. Pass LiPD data into the function." ) else : _names = D . keys ( ) except Exception : pass return _names
Get a list of all LiPD names in the library
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def getMetadata ( L ) : _l = { } try : _l = copy . deepcopy ( L ) _l = rm_values_fields ( _l ) except Exception as e : print ( "Error: Unable to get data. Please check that input is LiPD data: {}" . format ( e ) ) return _l
Get metadata from a LiPD data in memory
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def getCsv ( L = None ) : _c = { } try : if not L : print ( "Error: LiPD data not provided. Pass LiPD data into the function." ) else : _j , _c = get_csv_from_metadata ( L [ "dataSetName" ] , L ) except KeyError as ke : print ( "Error: Unable to get data. Please check that input is one LiPD dataset: {}" . format ( ke )...
Get CSV from LiPD metadata
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def __universal_read ( file_path , file_type ) : global files , cwd , settings correct_ext = load_fn_matches_ext ( file_path , file_type ) valid_path = path_type ( file_path , "file" ) if valid_path and correct_ext : file_meta = collect_metadata_file ( file_path ) if file_type == ".lpd" : files [ ".lpd" ] . append ( fi...
Use a file path to create file metadata and load a file in the appropriate way according to the provided file type .
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def __read_lipd_contents ( ) : global files , settings _d = { } try : if len ( files [ ".lpd" ] ) == 1 : _d = lipd_read ( files [ ".lpd" ] [ 0 ] [ "full_path" ] ) if settings [ "verbose" ] : print ( "Finished read: 1 record" ) else : for file in files [ ".lpd" ] : _d [ file [ "filename_no_ext" ] ] = lipd_read ( file [ ...
Use the file metadata to read in the LiPD file contents as a dataset library
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def __read_file ( usr_path , file_type ) : global files if not usr_path : src_dir , src_files = get_src_or_dst ( "read" , "file" ) if src_files : for file_path in src_files : __universal_read ( file_path , file_type ) else : print ( "No file(s) chosen" ) else : __universal_read ( usr_path , file_type ) return
Universal read file . Given a path and a type it will do the appropriate read actions
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def __read_directory ( usr_path , file_type ) : if not usr_path : usr_path , src_files = get_src_or_dst ( "read" , "directory" ) valid_path = path_type ( usr_path , "directory" ) if valid_path : files_found = [ ] if file_type == ".xls" : files_found += list_files ( ".xlsx" , usr_path ) files_found += list_files ( file_...
Universal read directory . Given a path and a type it will do the appropriate read actions
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def __write_lipd ( dat , usr_path ) : global settings if not usr_path : usr_path , _ignore = get_src_or_dst ( "write" , "directory" ) valid_path = path_type ( usr_path , "directory" ) if valid_path : if "paleoData" in dat : try : if settings [ "verbose" ] : print ( "writing: {}" . format ( dat [ "dataSetName" ] ) ) lip...
Write LiPD data to file provided an output directory and dataset name .
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def __disclaimer ( opt = "" ) : global settings if opt is "update" : print ( "Disclaimer: LiPD files may be updated and modified to adhere to standards\n" ) settings [ "note_update" ] = False if opt is "validate" : print ( "Note: Use lipd.validate() or www.LiPD.net/create " "to ensure that your new LiPD file(s) are val...
Print the disclaimers once . If they ve already been shown skip over .
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def get_shreds ( self , feature_extractors , sheet_name ) : if self . _shreds is None : shreds = [ ] _ , contours , _ = cv2 . findContours ( self . _foreground_mask , cv2 . RETR_EXTERNAL , cv2 . CHAIN_APPROX_SIMPLE ) for i , contour in enumerate ( contours ) : shred = self . _make_shred ( contour , i , feature_extracto...
Detects shreds in the current sheet and constructs Shred instances .
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def run_track ( track , result_hosts = None , crate_root = None , output_fmt = None , logfile_info = None , logfile_result = None , failfast = False , sample_mode = 'reservoir' ) : with Logger ( output_fmt = output_fmt , logfile_info = logfile_info , logfile_result = logfile_result ) as log : executor = Executor ( trac...
Execute a track file
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def update_lipd_version ( L ) : L , version = get_lipd_version ( L ) if version in [ 1.0 , "1.0" ] : L = update_lipd_v1_1 ( L ) version = 1.1 if version in [ 1.1 , "1.1" ] : L = update_lipd_v1_2 ( L ) version = 1.2 if version in [ 1.2 , "1.2" ] : L = update_lipd_v1_3 ( L ) version = 1.3 L = fix_doi ( L ) L [ "lipdVersi...
Metadata is indexed by number at this step .
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def update_lipd_v1_1 ( d ) : logger_versions . info ( "enter update_lipd_v1_1" ) tmp_all = [ ] try : if "chronData" in d : for table in d [ "chronData" ] : if "chronMeasurementTable" not in table : tmp_all . append ( { "chronMeasurementTable" : [ table ] } ) elif "chronMeasurementTable" in table : if isinstance ( table...
Update LiPD v1 . 0 to v1 . 1 - chronData entry is a list that allows multiple tables - paleoData entry is a list that allows multiple tables - chronData now allows measurement model summary modelTable ensemble calibratedAges tables - Added lipdVersion key
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def merge_csv_metadata ( d , csvs ) : logger_csvs . info ( "enter merge_csv_metadata" ) if "paleoData" in d : d [ "paleoData" ] = _merge_csv_section ( d [ "paleoData" ] , "paleo" , csvs ) if "chronData" in d : d [ "chronData" ] = _merge_csv_section ( d [ "chronData" ] , "chron" , csvs ) logger_csvs . info ( "exit merge...
Using the given metadata dictionary retrieve CSV data from CSV files and insert the CSV values into their respective metadata columns . Checks for both paleoData and chronData tables .
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def _merge_csv_section ( sections , pc , csvs ) : logger_csvs . info ( "enter merge_csv_section" ) try : for _name , _section in sections . items ( ) : if "measurementTable" in _section : sections [ _name ] [ "measurementTable" ] = _merge_csv_table ( _section [ "measurementTable" ] , pc , csvs ) if "model" in _section ...
Add csv data to all paleo data tables
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def _merge_csv_model ( models , pc , csvs ) : logger_csvs . info ( "enter merge_csv_model" ) try : for _name , _model in models . items ( ) : if "summaryTable" in _model : models [ _name ] [ "summaryTable" ] = _merge_csv_table ( _model [ "summaryTable" ] , pc , csvs ) if "ensembleTable" in _model : models [ _name ] [ "...
Add csv data to each column in chron model
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def _merge_csv_column ( table , csvs ) : try : ensemble = is_ensemble ( table [ "columns" ] ) if ensemble : if len ( table [ "columns" ] ) == 1 : for _name , _column in table [ "columns" ] . items ( ) : _column [ "values" ] = csvs elif len ( table [ "columns" ] ) == 2 : _multi_column = False for _name , _column in tabl...
Add csv data to each column in a list of columns
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def read_csv_from_file ( filename ) : logger_csvs . info ( "enter read_csv_from_file" ) d = { } l = [ ] try : logger_csvs . info ( "open file: {}" . format ( filename ) ) with open ( filename , 'r' ) as f : r = csv . reader ( f , delimiter = ',' ) for idx , col in enumerate ( next ( r ) ) : d [ idx ] = [ ] d = cast_val...
Opens the target CSV file and creates a dictionary with one list for each CSV column .
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def write_csv_to_file ( d ) : logger_csvs . info ( "enter write_csv_to_file" ) try : for filename , data in d . items ( ) : try : l_columns = _reorder_csv ( data , filename ) rows = zip ( * l_columns ) with open ( filename , 'w+' ) as f : w = csv . writer ( f ) for row in rows : row2 = decimal_precision ( row ) w . wri...
Writes columns of data to a target CSV file .
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def get_csv_from_metadata ( dsn , d ) : logger_csvs . info ( "enter get_csv_from_metadata" ) _csvs = OrderedDict ( ) _d = copy . deepcopy ( d ) try : if "paleoData" in _d : _d [ "paleoData" ] , _csvs = _get_csv_from_section ( _d [ "paleoData" ] , "{}.paleo" . format ( dsn ) , _csvs ) if "chronData" in _d : _d [ "chronD...
Two goals . Get all csv from metadata and return new metadata with generated filenames to match files .
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def _get_csv_from_section ( sections , crumbs , csvs ) : logger_csvs . info ( "enter get_csv_from_section: {}" . format ( crumbs ) ) _idx = 0 try : for _name , _section in sections . items ( ) : if "measurementTable" in _section : sections [ _name ] [ "measurementTable" ] , csvs = _get_csv_from_table ( _section [ "meas...
Get table name variable name and column values from paleo metadata
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def _get_csv_from_model ( models , crumbs , csvs ) : logger_csvs . info ( "enter get_csv_from_model: {}" . format ( crumbs ) ) _idx = 0 try : for _name , _model in models . items ( ) : if "distributionTable" in _model : models [ _name ] [ "distributionTable" ] , csvs = _get_csv_from_table ( _model [ "distributionTable"...
Get csv from model data
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def get_validator_format ( L ) : _api_data = [ ] _j , _csvs = get_csv_from_metadata ( L [ "dataSetName" ] , L ) _j = rm_values_fields ( copy . deepcopy ( L ) ) _j = idx_name_to_num ( _j ) _filenames = [ "metadata.jsonld" , "bagit.txt" , "bag-info.txt" , "manifest-md5.txt" , "tagmanifest-md5.txt" ] + [ k for k , v in _c...
Format the LIPD data in the layout that the Lipd . net validator accepts .
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def create_detailed_results ( result ) : string = "" string += "STATUS: {}\n" . format ( result [ "status" ] ) if result [ "feedback" ] : string += "WARNINGS: {}\n" . format ( len ( result [ "feedback" ] [ "wrnMsgs" ] ) ) for msg in result [ "feedback" ] [ "wrnMsgs" ] : string += "- {}\n" . format ( msg ) string += "ER...
Use the result from the API call to create an organized single string output for printing to the console .
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def display_results ( results , detailed = False ) : if not detailed : print ( 'FILENAME......................................... STATUS..........' ) for entry in results : try : if detailed : print ( "\n{}" . format ( entry [ "filename" ] ) ) print ( create_detailed_results ( entry ) ) else : print ( "{:<50}{}" . form...
Display the results from the validator in a brief or detailed output
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def call_validator_api ( dsn , api_data ) : _filename = dsn + ".lpd" try : api_data = json . dumps ( api_data ) payload = { 'json_payload' : api_data , 'apikey' : 'lipd_linked' } response = requests . post ( 'http://www.lipd.net/api/validator' , data = payload ) if response . status_code == 413 : result = { "dat" : { }...
Single call to the lipd . net validator API
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def procces_filters ( all_needs , current_needlist ) : if current_needlist [ "sort_by" ] is not None : if current_needlist [ "sort_by" ] == "id" : all_needs = sorted ( all_needs , key = lambda node : node [ "id" ] ) elif current_needlist [ "sort_by" ] == "status" : all_needs = sorted ( all_needs , key = status_sorter )...
Filters all needs with given configuration
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def filter_needs ( needs , filter_string = "" , filter_parts = True , merge_part_with_parent = True ) : if filter_string is None or filter_string == "" : return needs found_needs = [ ] for filter_need in needs : try : if filter_single_need ( filter_need , filter_string ) : found_needs . append ( filter_need ) except Ex...
Filters given needs based on a given filter string . Returns all needs which pass the given filter .
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def get_logging_level ( debug ) : level = logging . INFO if debug : level = logging . DEBUG return level
Returns logging level based on boolean
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def run_spec ( spec , benchmark_hosts , result_hosts = None , output_fmt = None , logfile_info = None , logfile_result = None , action = None , fail_if = None , sample_mode = 'reservoir' ) : with Logger ( output_fmt = output_fmt , logfile_info = logfile_info , logfile_result = logfile_result ) as log : do_run_spec ( sp...
Run a spec file executing the statements on the benchmark_hosts .
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def get_sections ( need_info ) : sections = [ ] current_node = need_info [ 'target_node' ] while current_node : if isinstance ( current_node , nodes . section ) : title = current_node . children [ 0 ] . astext ( ) title = NON_BREAKING_SPACE . sub ( ' ' , title ) sections . append ( title ) current_node = getattr ( curr...
Gets the hierarchy of the section nodes as a list starting at the section of the current need and then its parent sections
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def add_sections ( app , doctree , fromdocname ) : needs = getattr ( app . builder . env , 'needs_all_needs' , { } ) for key , need_info in needs . items ( ) : sections = get_sections ( need_info ) need_info [ 'sections' ] = sections need_info [ 'section_name' ] = sections [ 0 ] if sections else ""
Add section titles to the needs as additional attributes that can be used in tables and filters
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def create_back_links ( env ) : if env . needs_workflow [ 'backlink_creation' ] : return needs = env . needs_all_needs for key , need in needs . items ( ) : for link in need [ "links" ] : link_main = link . split ( '.' ) [ 0 ] try : link_part = link . split ( '.' ) [ 1 ] except IndexError : link_part = None if link_mai...
Create back - links in all found needs . But do this only once as all needs are already collected and this sorting is for all needs and not only for the ones of the current document .
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def _fix_list_dyn_func ( list ) : open_func_string = False new_list = [ ] for element in list : if '[[' in element : open_func_string = True new_link = [ element ] elif ']]' in element : new_link . append ( element ) open_func_string = False element = "," . join ( new_link ) new_list . append ( element ) elif open_func...
This searches a list for dynamic function fragments which may have been cut by generic searches for | ; .
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def merge_extra_options ( self , needs_info ) : extra_keys = set ( self . options . keys ( ) ) . difference ( set ( needs_info . keys ( ) ) ) for key in extra_keys : needs_info [ key ] = self . options [ key ] for key in self . option_spec : if key not in needs_info . keys ( ) : needs_info [ key ] = "" return extra_key...
Add any extra options introduced via options_ext to needs_info
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def merge_global_options ( self , needs_info ) : global_options = getattr ( self . env . app . config , 'needs_global_options' , None ) if global_options is None : return for key , value in global_options . items ( ) : if key in needs_info . keys ( ) : continue needs_info [ key ] = value
Add all global defined options to needs_info
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def process_needlist ( app , doctree , fromdocname ) : env = app . builder . env for node in doctree . traverse ( Needlist ) : if not app . config . needs_include_needs : for att in ( 'ids' , 'names' , 'classes' , 'dupnames' ) : node [ att ] = [ ] node . replace_self ( [ ] ) continue id = node . attributes [ "ids" ] [ ...
Replace all needlist nodes with a list of the collected needs . Augment each need with a backlink to the original location .
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def get_lines ( filename : str ) -> Iterator [ str ] : if filename . endswith ( '.gz' ) : with gzip . open ( filename , 'r' ) as f : for line in f : yield line . decode ( 'utf-8' ) else : with open ( filename , 'r' , encoding = 'utf-8' ) as f : for line in f : yield line
Create an iterator that returns the lines of a utf - 8 encoded file .
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def as_statements ( lines : Iterator [ str ] ) -> Iterator [ str ] : lines = ( l . strip ( ) for l in lines if l ) lines = ( l for l in lines if l and not l . startswith ( '--' ) ) parts = [ ] for line in lines : parts . append ( line . rstrip ( ';' ) ) if line . endswith ( ';' ) : yield ' ' . join ( parts ) parts . cl...
Create an iterator that transforms lines into sql statements .
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def break_iterable ( iterable , pred ) : sublist = [ ] for i in iterable : if pred ( i ) : yield sublist sublist = [ ] else : sublist . append ( i ) yield sublist
Break a iterable on the item that matches the predicate into lists .
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def regenerate ( location = 'http://www.iana.org/assignments/language-subtag-registry' , filename = None , default_encoding = 'utf-8' ) : paren = re . compile ( '\([^)]*\)' ) data = urllib2 . urlopen ( location ) if ( 'content-type' in data . headers and 'charset=' in data . headers [ 'content-type' ] ) : encoding = da...
Generate the languages Python module .
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def newton ( power_sum , elementary_symmetric_polynomial , order ) : r if len ( power_sum ) > len ( elementary_symmetric_polynomial ) : _update_elementary_symmetric_polynomial ( power_sum , elementary_symmetric_polynomial , order ) elif len ( power_sum ) < len ( elementary_symmetric_polynomial ) : _update_power_sum ( p...
r Given two lists of values the first list being the power sum s of a polynomial and the second being expressions of the roots of the polynomial as found by Viete s Formula use information from the longer list to fill out the shorter list using Newton s Identities .
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def max_variants ( composition ) : max_n_variants = 0 for element , count in composition . items ( ) : if element == "H+" : continue try : max_n_variants += count * periodic_table [ element ] . max_neutron_shift ( ) except KeyError : pass return max_n_variants
Calculates the maximum number of isotopic variants that could be produced by a composition .
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def isotopic_variants ( composition , npeaks = None , charge = 0 , charge_carrier = PROTON ) : if npeaks is None : max_n_variants = max_variants ( composition ) npeaks = int ( sqrt ( max_n_variants ) - 2 ) npeaks = max ( npeaks , 3 ) else : npeaks -= 1 return IsotopicDistribution ( composition , npeaks ) . aggregated_i...
Compute a peak list representing the theoretical isotopic cluster for composition .
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def getnii_descr ( fim ) : nim = nib . load ( fim ) hdr = nim . header rcnlst = hdr [ 'descrip' ] . item ( ) . split ( ';' ) rcndic = { } if rcnlst [ 0 ] == '' : return rcndic for ci in range ( len ( rcnlst ) ) : tmp = rcnlst [ ci ] . split ( '=' ) rcndic [ tmp [ 0 ] ] = tmp [ 1 ] return rcndic
Extracts the custom description header field to dictionary
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def orientnii ( imfile ) : strorient = [ 'L-R' , 'S-I' , 'A-P' ] niiorient = [ ] niixyz = np . zeros ( 3 , dtype = np . int8 ) if os . path . isfile ( imfile ) : nim = nib . load ( imfile ) pct = nim . get_data ( ) A = nim . get_sform ( ) for i in range ( 3 ) : niixyz [ i ] = np . argmax ( abs ( A [ i , : - 1 ] ) ) nii...
Get the orientation from NIfTI sform . Not fully functional yet .
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def pick_t1w ( mri ) : if isinstance ( mri , dict ) : if 'T1N4' in mri and os . path . isfile ( mri [ 'T1N4' ] ) : ft1w = mri [ 'T1N4' ] elif 'T1bc' in mri and os . path . isfile ( mri [ 'T1bc' ] ) : ft1w = mri [ 'T1bc' ] elif 'T1nii' in mri and os . path . isfile ( mri [ 'T1nii' ] ) : ft1w = mri [ 'T1nii' ] elif 'T1DC...
Pick the MR T1w from the dictionary for MR - > PET registration .
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def list_dcm_datain ( datain ) : if not isinstance ( datain , dict ) : raise ValueError ( 'The input is not a dictionary!' ) dcmlst = [ ] if 'mumapDCM' in datain : dcmump = os . listdir ( datain [ 'mumapDCM' ] ) dcmump = [ os . path . join ( datain [ 'mumapDCM' ] , d ) for d in dcmump if d . endswith ( dcmext ) ] dcmls...
List all DICOM file paths in the datain dictionary of input data .
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def find_cuda ( ) : for fldr in os . environ [ 'PATH' ] . split ( os . pathsep ) : cuda_path = join ( fldr , 'nvcc' ) if os . path . exists ( cuda_path ) : cuda_path = os . path . dirname ( os . path . dirname ( cuda_path ) ) break cuda_path = None if cuda_path is None : print 'w> nvcc compiler could not be found from ...
Locate the CUDA environment on the system .
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def resources_setup ( ) : print 'i> installing file <resources.py> into home directory if it does not exist.' path_current = os . path . dirname ( os . path . realpath ( __file__ ) ) path_install = os . path . join ( path_current , 'resources' ) path_resources = path_niftypet_local ( ) print path_current flg_resources ...
This function checks CUDA devices selects some and installs resources . py
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def coroutine ( f ) : @ functools . wraps ( f ) def _coroutine ( * args , ** kwargs ) : def _resolver ( resolve , reject ) : try : generator = f ( * args , ** kwargs ) except BaseException as e : reject ( e ) else : if not isinstance ( generator , types . GeneratorType ) : resolve ( generator ) else : def _step ( previ...
Implementation of a coroutine .
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def no_coroutine ( f ) : @ functools . wraps ( f ) def _no_coroutine ( * args , ** kwargs ) : generator = f ( * args , ** kwargs ) if not isinstance ( generator , types . GeneratorType ) : return generator previous = None first = True while True : element = None try : if first : element = next ( generator ) else : elem...
This is not a coroutine ; )
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def maybe_coroutine ( decide ) : def _maybe_coroutine ( f ) : @ functools . wraps ( f ) def __maybe_coroutine ( * args , ** kwargs ) : if decide ( * args , ** kwargs ) : return coroutine ( f ) ( * args , ** kwargs ) else : return no_coroutine ( f ) ( * args , ** kwargs ) return __maybe_coroutine return _maybe_coroutine
Either be a coroutine or not .
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def makeCallbackPromise ( function , * args , ** kwargs ) : def _resolver ( resolve , reject ) : function ( lambda success , result : resolve ( result ) if success else reject ( result ) , * args , ** kwargs ) return Promise ( _resolver )
Take a function that reports its result using a callback and return a Promise that listenes for this callback .
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def calculate_mass ( composition , mass_data = None ) : mass = 0.0 if mass_data is None : mass_data = nist_mass for element in composition : try : mass += ( composition [ element ] * mass_data [ element ] [ 0 ] [ 0 ] ) except KeyError : match = re . search ( r"(\S+)\[(\d+)\]" , element ) if match : element_ = match . g...
Calculates the monoisotopic mass of a composition
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def login ( self , username = None , password = None ) : if username is not None : self . _username = username if password is not None : self . _password = password if self . _username is None or not isinstance ( self . _username , str ) : raise SkybellAuthenticationException ( ERROR . USERNAME ) if self . _password is...
Execute Skybell login .
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def logout ( self ) : if self . cache ( CONST . ACCESS_TOKEN ) : self . _session = requests . session ( ) self . _devices = None self . update_cache ( { CONST . ACCESS_TOKEN : None } ) return True
Explicit Skybell logout .
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def send_request ( self , method , url , headers = None , json_data = None , retry = True ) : if not self . cache ( CONST . ACCESS_TOKEN ) and url != CONST . LOGIN_URL : self . login ( ) if not headers : headers = { } if self . cache ( CONST . ACCESS_TOKEN ) : headers [ 'Authorization' ] = 'Bearer ' + self . cache ( CO...
Send requests to Skybell .
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def update_cache ( self , data ) : UTILS . update ( self . _cache , data ) self . _save_cache ( )
Update a cached value .
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def dev_cache ( self , device , key = None ) : device_cache = self . _cache . get ( CONST . DEVICES , { } ) . get ( device . device_id ) if device_cache and key : return device_cache . get ( key ) return device_cache
Get a cached value for a device .
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def update_dev_cache ( self , device , data ) : self . update_cache ( { CONST . DEVICES : { device . device_id : data } } )
Update cached values for a device .
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def deleteInactiveDevicesByQuota ( self , per_jid_max = 15 , global_max = 0 ) : if per_jid_max < 1 and global_max < 1 : return if per_jid_max < 1 : per_jid_max = None if global_max < 1 : global_max = None bare_jids = yield self . _storage . listJIDs ( ) if not per_jid_max == None : for bare_jid in bare_jids : devices =...
Delete inactive devices by setting a quota . With per_jid_max you can define the amount of inactive devices that are kept for each jid with global_max you can define a global maximum for inactive devices . If any of the quotas is reached inactive devices are deleted on an LRU basis . This also deletes the corresponding...
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def deleteInactiveDevicesByAge ( self , age_days ) : if age_days < 1 : return now = time . time ( ) bare_jids = yield self . _storage . listJIDs ( ) for bare_jid in bare_jids : devices = yield self . __loadInactiveDevices ( bare_jid ) delete_devices = [ ] for device , timestamp in list ( devices . items ( ) ) : elapsed...
Delete all inactive devices from the device list storage and cache that are older then a given number of days . This also deletes the corresponding sessions so if a device comes active again and tries to send you an encrypted message you will not be able to decrypt it . You are not allowed to delete inactive devices th...
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def runInactiveDeviceCleanup ( self ) : yield self . deleteInactiveDevicesByQuota ( self . __inactive_per_jid_max , self . __inactive_global_max ) yield self . deleteInactiveDevicesByAge ( self . __inactive_max_age )
Runs both the deleteInactiveDevicesByAge and the deleteInactiveDevicesByQuota methods with the configuration that was set when calling create .
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def get_setup ( Cnt = { } ) : Cnt [ 'DIRTOOLS' ] = DIRTOOLS Cnt [ 'CMAKE_TLS_PAR' ] = CMAKE_TLS_PAR Cnt [ 'HMULIST' ] = hrdwr_mu Cnt [ 'MSVC_VRSN' ] = MSVC_VRSN Cnt = get_gpu_constants ( Cnt ) if 'PATHTOOLS' in globals ( ) and PATHTOOLS != '' : Cnt [ 'PATHTOOLS' ] = PATHTOOLS if 'RESPATH' in globals ( ) and RESPATH != ...
Return a dictionary of GPU mu - map hardware and third party set - up .