idx int64 0 251k | question stringlengths 53 3.53k | target stringlengths 5 1.23k | len_question int64 20 893 | len_target int64 3 238 |
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231,900 | def interpoled_resampling ( W , x ) : N = W . shape [ 0 ] idx = np . argsort ( x ) xs = x [ idx ] ws = W [ idx ] cs = np . cumsum ( avg_n_nplusone ( ws ) ) u = random . rand ( N ) xrs = np . empty ( N ) where = np . searchsorted ( cs , u ) # costs O(N log(N)) but algorithm has O(N log(N)) complexity anyway for n in range ( N ) : m = where [ n ] if m == 0 : xrs [ n ] = xs [ 0 ] elif m == N : xrs [ n ] = xs [ - 1 ] else : xrs [ n ] = interpol ( cs [ m - 1 ] , cs [ m ] , xs [ m - 1 ] , xs [ m ] , u [ n ] ) return xrs | Resampling based on an interpolated CDF as described in Malik and Pitt . | 209 | 17 |
231,901 | def sort_items ( self , items , args = False ) : if self . settings [ 'sort' ] . lower ( ) == 'src' : return def alpha ( i ) : return i . name def permission ( i ) : if args : if i . intent == 'in' : return 'b' if i . intent == 'inout' : return 'c' if i . intent == 'out' : return 'd' if i . intent == '' : return 'e' perm = getattr ( i , 'permission' , '' ) if perm == 'public' : return 'b' if perm == 'protected' : return 'c' if perm == 'private' : return 'd' return 'a' def permission_alpha ( i ) : return permission ( i ) + '-' + i . name def itype ( i ) : if i . obj == 'variable' : retstr = i . vartype if retstr == 'class' : retstr = 'type' if i . kind : retstr = retstr + '-' + str ( i . kind ) if i . strlen : retstr = retstr + '-' + str ( i . strlen ) if i . proto : retstr = retstr + '-' + i . proto [ 0 ] return retstr elif i . obj == 'proc' : if i . proctype != 'Function' : return i . proctype . lower ( ) else : return i . proctype . lower ( ) + '-' + itype ( i . retvar ) else : return i . obj def itype_alpha ( i ) : return itype ( i ) + '-' + i . name if self . settings [ 'sort' ] . lower ( ) == 'alpha' : items . sort ( key = alpha ) elif self . settings [ 'sort' ] . lower ( ) == 'permission' : items . sort ( key = permission ) elif self . settings [ 'sort' ] . lower ( ) == 'permission-alpha' : items . sort ( key = permission_alpha ) elif self . settings [ 'sort' ] . lower ( ) == 'type' : items . sort ( key = itype ) elif self . settings [ 'sort' ] . lower ( ) == 'type-alpha' : items . sort ( key = itype_alpha ) | Sort the self s contents as contained in the list items as specified in self s meta - data . | 506 | 20 |
231,902 | def contents_size ( self ) : count = 0 if hasattr ( self , 'variables' ) : count += 1 if hasattr ( self , 'types' ) : count += 1 if hasattr ( self , 'modules' ) : count += 1 if hasattr ( self , 'submodules' ) : count += 1 if hasattr ( self , 'subroutines' ) : count += 1 if hasattr ( self , 'modprocedures' ) : count += 1 if hasattr ( self , 'functions' ) : count += 1 if hasattr ( self , 'interfaces' ) : count += 1 if hasattr ( self , 'absinterfaces' ) : count += 1 if hasattr ( self , 'programs' ) : count += 1 if hasattr ( self , 'boundprocs' ) : count += 1 if hasattr ( self , 'finalprocs' ) : count += 1 if hasattr ( self , 'enums' ) : count += 1 if hasattr ( self , 'procedure' ) : count += 1 if hasattr ( self , 'constructor' ) : count += 1 if hasattr ( self , 'modfunctions' ) : count += 1 if hasattr ( self , 'modsubroutines' ) : count += 1 if hasattr ( self , 'modprocs' ) : count += 1 if getattr ( self , 'src' , None ) : count += 1 return count | Returns the number of different categories to be shown in the contents side - bar in the HTML documentation . | 310 | 20 |
231,903 | def sort ( self ) : if hasattr ( self , 'variables' ) : sort_items ( self , self . variables ) if hasattr ( self , 'modules' ) : sort_items ( self , self . modules ) if hasattr ( self , 'submodules' ) : sort_items ( self , self . submodules ) if hasattr ( self , 'common' ) : sort_items ( self , self . common ) if hasattr ( self , 'subroutines' ) : sort_items ( self , self . subroutines ) if hasattr ( self , 'modprocedures' ) : sort_items ( self , self . modprocedures ) if hasattr ( self , 'functions' ) : sort_items ( self , self . functions ) if hasattr ( self , 'interfaces' ) : sort_items ( self , self . interfaces ) if hasattr ( self , 'absinterfaces' ) : sort_items ( self , self . absinterfaces ) if hasattr ( self , 'types' ) : sort_items ( self , self . types ) if hasattr ( self , 'programs' ) : sort_items ( self , self . programs ) if hasattr ( self , 'blockdata' ) : sort_items ( self , self . blockdata ) if hasattr ( self , 'boundprocs' ) : sort_items ( self , self . boundprocs ) if hasattr ( self , 'finalprocs' ) : sort_items ( self , self . finalprocs ) if hasattr ( self , 'args' ) : #sort_items(self.args,args=True) pass | Sorts components of the object . | 357 | 7 |
231,904 | def make_links ( self , project ) : self . doc = ford . utils . sub_links ( self . doc , project ) if 'summary' in self . meta : self . meta [ 'summary' ] = ford . utils . sub_links ( self . meta [ 'summary' ] , project ) # Create links in the project for item in self . iterator ( 'variables' , 'types' , 'enums' , 'modules' , 'submodules' , 'subroutines' , 'functions' , 'interfaces' , 'absinterfaces' , 'programs' , 'boundprocs' , 'args' , 'bindings' ) : if isinstance ( item , FortranBase ) : item . make_links ( project ) if hasattr ( self , 'retvar' ) : if self . retvar : if isinstance ( self . retvar , FortranBase ) : self . retvar . make_links ( project ) if hasattr ( self , 'procedure' ) : if isinstance ( self . procedure , FortranBase ) : self . procedure . make_links ( project ) | Process intra - site links to documentation of other parts of the program . | 247 | 14 |
231,905 | def iterator ( self , * argv ) : for arg in argv : if hasattr ( self , arg ) : for item in getattr ( self , arg ) : yield item | Iterator returning any list of elements via attribute lookup in self | 38 | 11 |
231,906 | def get_used_entities ( self , use_specs ) : if len ( use_specs . strip ( ) ) == 0 : return ( self . pub_procs , self . pub_absints , self . pub_types , self . pub_vars ) only = bool ( self . ONLY_RE . match ( use_specs ) ) use_specs = self . ONLY_RE . sub ( '' , use_specs ) ulist = self . SPLIT_RE . split ( use_specs ) ulist [ - 1 ] = ulist [ - 1 ] . strip ( ) uspecs = { } for item in ulist : match = self . RENAME_RE . search ( item ) if match : uspecs [ match . group ( 1 ) . lower ( ) ] = match . group ( 2 ) else : uspecs [ item . lower ( ) ] = item ret_procs = { } ret_absints = { } ret_types = { } ret_vars = { } for name , obj in self . pub_procs . items ( ) : name = name . lower ( ) if only : if name in uspecs : ret_procs [ name ] = obj else : ret_procs [ name ] = obj for name , obj in self . pub_absints . items ( ) : name = name . lower ( ) if only : if name in uspecs : ret_absints [ name ] = obj else : ret_absints [ name ] = obj for name , obj in self . pub_types . items ( ) : name = name . lower ( ) if only : if name in uspecs : ret_types [ name ] = obj else : ret_types [ name ] = obj for name , obj in self . pub_vars . items ( ) : name = name . lower ( ) if only : if name in uspecs : ret_vars [ name ] = obj else : ret_vars [ name ] = obj return ( ret_procs , ret_absints , ret_types , ret_vars ) | Returns the entities which are imported by a use statement . These are contained in dicts . | 454 | 18 |
231,907 | def get_name ( self , item ) : if not isinstance ( item , ford . sourceform . FortranBase ) : raise Exception ( '{} is not of a type derived from FortranBase' . format ( str ( item ) ) ) if item in self . _items : return self . _items [ item ] else : if item . get_dir ( ) not in self . _counts : self . _counts [ item . get_dir ( ) ] = { } if item . name in self . _counts [ item . get_dir ( ) ] : num = self . _counts [ item . get_dir ( ) ] [ item . name ] + 1 else : num = 1 self . _counts [ item . get_dir ( ) ] [ item . name ] = num name = item . name . lower ( ) . replace ( '<' , 'lt' ) # name is already lower name = name . replace ( '>' , 'gt' ) name = name . replace ( '/' , 'SLASH' ) if name == '' : name = '__unnamed__' if num > 1 : name = name + '~' + str ( num ) self . _items [ item ] = name return name | Return the name for this item registered with this NameSelector . If no name has previously been registered then generate a new one . | 268 | 26 |
231,908 | def main ( proj_data , proj_docs , md ) : if proj_data [ 'relative' ] : proj_data [ 'project_url' ] = '.' # Parse the files in your project project = ford . fortran_project . Project ( proj_data ) if len ( project . files ) < 1 : print ( "Error: No source files with appropriate extension found in specified directory." ) sys . exit ( 1 ) # Convert the documentation from Markdown to HTML. Make sure to properly # handle LateX and metadata. if proj_data [ 'relative' ] : project . markdown ( md , '..' ) else : project . markdown ( md , proj_data [ 'project_url' ] ) project . correlate ( ) if proj_data [ 'relative' ] : project . make_links ( '..' ) else : project . make_links ( proj_data [ 'project_url' ] ) # Convert summaries and descriptions to HTML if proj_data [ 'relative' ] : ford . sourceform . set_base_url ( '.' ) if 'summary' in proj_data : proj_data [ 'summary' ] = md . convert ( proj_data [ 'summary' ] ) proj_data [ 'summary' ] = ford . utils . sub_links ( ford . utils . sub_macros ( ford . utils . sub_notes ( proj_data [ 'summary' ] ) , proj_data [ 'project_url' ] ) , project ) if 'author_description' in proj_data : proj_data [ 'author_description' ] = md . convert ( proj_data [ 'author_description' ] ) proj_data [ 'author_description' ] = ford . utils . sub_links ( ford . utils . sub_macros ( ford . utils . sub_notes ( proj_data [ 'author_description' ] ) , proj_data [ 'project_url' ] ) , project ) proj_docs_ = ford . utils . sub_links ( ford . utils . sub_macros ( ford . utils . sub_notes ( proj_docs ) , proj_data [ 'project_url' ] ) , project ) # Process any pages if 'page_dir' in proj_data : page_tree = ford . pagetree . get_page_tree ( os . path . normpath ( proj_data [ 'page_dir' ] ) , md ) print ( ) else : page_tree = None proj_data [ 'pages' ] = page_tree # Produce the documentation using Jinja2. Output it to the desired location # and copy any files that are needed (CSS, JS, images, fonts, source files, # etc.) docs = ford . output . Documentation ( proj_data , proj_docs_ , project , page_tree ) docs . writeout ( ) print ( '' ) return 0 | Main driver of FORD . | 669 | 6 |
231,909 | def convertToFree ( stream , length_limit = True ) : linestack = [ ] for line in stream : convline = FortranLine ( line , length_limit ) if convline . is_regular : if convline . isContinuation and linestack : linestack [ 0 ] . continueLine ( ) for l in linestack : yield str ( l ) linestack = [ ] linestack . append ( convline ) for l in linestack : yield str ( l ) | Convert stream from fixed source form to free source form . | 108 | 12 |
231,910 | def continueLine ( self ) : if not ( self . isLong and self . is_regular ) : self . line_conv = self . line_conv . rstrip ( ) + " &\n" else : temp = self . line_conv [ : 72 ] . rstrip ( ) + " &" self . line_conv = temp . ljust ( 72 ) + self . excess_line | Insert line continuation symbol at end of line . | 85 | 9 |
231,911 | def id_mods ( obj , modlist , intrinsic_mods = { } , submodlist = [ ] ) : for i in range ( len ( obj . uses ) ) : for candidate in modlist : if obj . uses [ i ] [ 0 ] . lower ( ) == candidate . name . lower ( ) : obj . uses [ i ] = [ candidate , obj . uses [ i ] [ 1 ] ] break else : if obj . uses [ i ] [ 0 ] . lower ( ) in intrinsic_mods : obj . uses [ i ] = [ intrinsic_mods [ obj . uses [ i ] [ 0 ] . lower ( ) ] , obj . uses [ i ] [ 1 ] ] continue if getattr ( obj , 'ancestor' , None ) : for submod in submodlist : if obj . ancestor . lower ( ) == submod . name . lower ( ) : obj . ancestor = submod break if hasattr ( obj , 'ancestor_mod' ) : for mod in modlist : if obj . ancestor_mod . lower ( ) == mod . name . lower ( ) : obj . ancestor_mod = mod break for modproc in getattr ( obj , 'modprocedures' , [ ] ) : id_mods ( modproc , modlist , intrinsic_mods ) for func in getattr ( obj , 'functions' , [ ] ) : id_mods ( func , modlist , intrinsic_mods ) for subroutine in getattr ( obj , 'subroutines' , [ ] ) : id_mods ( subroutine , modlist , intrinsic_mods ) | Match USE statements up with the right modules | 343 | 8 |
231,912 | def allfiles ( self ) : for f in self . files : yield f for f in self . extra_files : yield f | Instead of duplicating files it is much more efficient to create the itterator on the fly | 27 | 19 |
231,913 | def make_links ( self , base_url = '..' ) : ford . sourceform . set_base_url ( base_url ) for src in self . allfiles : src . make_links ( self ) | Substitute intrasite links to documentation for other parts of the program . | 48 | 16 |
231,914 | def sub_notes ( docs ) : def substitute ( match ) : ret = "</p><div class=\"alert alert-{}\" role=\"alert\"><h4>{}</h4>" "<p>{}</p></div>" . format ( NOTE_TYPE [ match . group ( 1 ) . lower ( ) ] , match . group ( 1 ) . capitalize ( ) , match . group ( 2 ) ) if len ( match . groups ( ) ) >= 4 and not match . group ( 4 ) : ret += '\n<p>' return ret for regex in NOTE_RE : docs = regex . sub ( substitute , docs ) return docs | Substitutes the special controls for notes warnings todos and bugs with the corresponding div . | 140 | 18 |
231,915 | def paren_split ( sep , string ) : if len ( sep ) != 1 : raise Exception ( "Separation string must be one character long" ) retlist = [ ] level = 0 blevel = 0 left = 0 for i in range ( len ( string ) ) : if string [ i ] == "(" : level += 1 elif string [ i ] == ")" : level -= 1 elif string [ i ] == "[" : blevel += 1 elif string [ i ] == "]" : blevel -= 1 elif string [ i ] == sep and level == 0 and blevel == 0 : retlist . append ( string [ left : i ] ) left = i + 1 retlist . append ( string [ left : ] ) return retlist | Splits the string into pieces divided by sep when sep is outside of parentheses . | 161 | 16 |
231,916 | def quote_split ( sep , string ) : if len ( sep ) != 1 : raise Exception ( "Separation string must be one character long" ) retlist = [ ] squote = False dquote = False left = 0 i = 0 while i < len ( string ) : if string [ i ] == '"' and not dquote : if not squote : squote = True elif ( i + 1 ) < len ( string ) and string [ i + 1 ] == '"' : i += 1 else : squote = False elif string [ i ] == "'" and not squote : if not dquote : dquote = True elif ( i + 1 ) < len ( string ) and string [ i + 1 ] == "'" : i += 1 else : dquote = False elif string [ i ] == sep and not dquote and not squote : retlist . append ( string [ left : i ] ) left = i + 1 i += 1 retlist . append ( string [ left : ] ) return retlist | Splits the strings into pieces divided by sep when sep in not inside quotes . | 219 | 16 |
231,917 | def split_path ( path ) : def recurse_path ( path , retlist ) : if len ( retlist ) > 100 : fullpath = os . path . join ( * ( [ path , ] + retlist ) ) print ( "Directory '{}' contains too many levels" . format ( fullpath ) ) exit ( 1 ) head , tail = os . path . split ( path ) if len ( tail ) > 0 : retlist . insert ( 0 , tail ) recurse_path ( head , retlist ) elif len ( head ) > 1 : recurse_path ( head , retlist ) else : return retlist = [ ] path = os . path . realpath ( os . path . normpath ( path ) ) drive , path = os . path . splitdrive ( path ) if len ( drive ) > 0 : retlist . append ( drive ) recurse_path ( path , retlist ) return retlist | Splits the argument into its constituent directories and returns them as a list . | 199 | 15 |
231,918 | def sub_macros ( string , base_url ) : macros = { '|url|' : base_url , '|media|' : os . path . join ( base_url , 'media' ) , '|page|' : os . path . join ( base_url , 'page' ) } for key , val in macros . items ( ) : string = string . replace ( key , val ) return string | Replaces macros in documentation with their appropriate values . These macros are used for things like providing URLs . | 91 | 20 |
231,919 | def copytree ( src , dst ) : def touch ( path ) : now = time . time ( ) try : # assume it's there os . utime ( path , ( now , now ) ) except os . error : # if it isn't, try creating the directory, # a file with that name os . makedirs ( os . path . dirname ( path ) ) open ( path , "w" ) . close ( ) os . utime ( path , ( now , now ) ) for root , dirs , files in os . walk ( src ) : relsrcdir = os . path . relpath ( root , src ) dstdir = os . path . join ( dst , relsrcdir ) if not os . path . exists ( dstdir ) : try : os . makedirs ( dstdir ) except OSError as ex : if ex . errno != errno . EEXIST : raise for ff in files : shutil . copy ( os . path . join ( root , ff ) , os . path . join ( dstdir , ff ) ) touch ( os . path . join ( dstdir , ff ) ) | Replaces shutil . copytree to avoid problems on certain file systems . | 242 | 15 |
231,920 | def export_hmaps_csv ( key , dest , sitemesh , array , comment ) : curves = util . compose_arrays ( sitemesh , array ) writers . write_csv ( dest , curves , comment = comment ) return [ dest ] | Export the hazard maps of the given realization into CSV . | 54 | 11 |
231,921 | def export_hcurves_by_imt_csv ( key , kind , rlzs_assoc , fname , sitecol , array , oq , checksum ) : nsites = len ( sitecol ) fnames = [ ] for imt , imls in oq . imtls . items ( ) : slc = oq . imtls ( imt ) dest = add_imt ( fname , imt ) lst = [ ( 'lon' , F32 ) , ( 'lat' , F32 ) , ( 'depth' , F32 ) ] for iml in imls : lst . append ( ( 'poe-%s' % iml , F32 ) ) hcurves = numpy . zeros ( nsites , lst ) for sid , lon , lat , dep in zip ( range ( nsites ) , sitecol . lons , sitecol . lats , sitecol . depths ) : hcurves [ sid ] = ( lon , lat , dep ) + tuple ( array [ sid , slc ] ) fnames . append ( writers . write_csv ( dest , hcurves , comment = _comment ( rlzs_assoc , kind , oq . investigation_time ) + ( ', imt="%s", checksum=%d' % ( imt , checksum ) ) , header = [ name for ( name , dt ) in lst ] ) ) return fnames | Export the curves of the given realization into CSV . | 319 | 10 |
231,922 | def export_hcurves_csv ( ekey , dstore ) : oq = dstore [ 'oqparam' ] info = get_info ( dstore ) rlzs_assoc = dstore [ 'csm_info' ] . get_rlzs_assoc ( ) R = len ( rlzs_assoc . realizations ) sitecol = dstore [ 'sitecol' ] sitemesh = get_mesh ( sitecol ) key , kind , fmt = get_kkf ( ekey ) fnames = [ ] checksum = dstore . get_attr ( '/' , 'checksum32' ) hmap_dt = oq . hmap_dt ( ) for kind in oq . get_kinds ( kind , R ) : fname = hazard_curve_name ( dstore , ( key , fmt ) , kind , rlzs_assoc ) comment = _comment ( rlzs_assoc , kind , oq . investigation_time ) if ( key in ( 'hmaps' , 'uhs' ) and oq . uniform_hazard_spectra or oq . hazard_maps ) : hmap = extract ( dstore , 'hmaps?kind=' + kind ) [ kind ] if key == 'uhs' and oq . poes and oq . uniform_hazard_spectra : uhs_curves = calc . make_uhs ( hmap , info ) writers . write_csv ( fname , util . compose_arrays ( sitemesh , uhs_curves ) , comment = comment + ', checksum=%d' % checksum ) fnames . append ( fname ) elif key == 'hmaps' and oq . poes and oq . hazard_maps : fnames . extend ( export_hmaps_csv ( ekey , fname , sitemesh , hmap . flatten ( ) . view ( hmap_dt ) , comment + ', checksum=%d' % checksum ) ) elif key == 'hcurves' : hcurves = extract ( dstore , 'hcurves?kind=' + kind ) [ kind ] fnames . extend ( export_hcurves_by_imt_csv ( ekey , kind , rlzs_assoc , fname , sitecol , hcurves , oq , checksum ) ) return sorted ( fnames ) | Exports the hazard curves into several . csv files | 529 | 11 |
231,923 | def save_disagg_to_csv ( metadata , matrices ) : skip_keys = ( 'Mag' , 'Dist' , 'Lon' , 'Lat' , 'Eps' , 'TRT' ) base_header = ',' . join ( '%s=%s' % ( key , value ) for key , value in metadata . items ( ) if value is not None and key not in skip_keys ) for disag_tup , ( poe , iml , matrix , fname ) in matrices . items ( ) : header = '%s,poe=%.7f,iml=%.7e\n' % ( base_header , poe , iml ) if disag_tup == ( 'Mag' , 'Lon' , 'Lat' ) : matrix = numpy . swapaxes ( matrix , 0 , 1 ) matrix = numpy . swapaxes ( matrix , 1 , 2 ) disag_tup = ( 'Lon' , 'Lat' , 'Mag' ) axis = [ metadata [ v ] for v in disag_tup ] header += ',' . join ( v for v in disag_tup ) header += ',poe' # compute axis mid points axis = [ ( ax [ : - 1 ] + ax [ 1 : ] ) / 2. if ax . dtype == float else ax for ax in axis ] values = None if len ( axis ) == 1 : values = numpy . array ( [ axis [ 0 ] , matrix . flatten ( ) ] ) . T else : grids = numpy . meshgrid ( * axis , indexing = 'ij' ) values = [ g . flatten ( ) for g in grids ] values . append ( matrix . flatten ( ) ) values = numpy . array ( values ) . T writers . write_csv ( fname , values , comment = header , fmt = '%.5E' ) | Save disaggregation matrices to multiple . csv files . | 412 | 12 |
231,924 | def _interp_function ( self , y_ip1 , y_i , t_ip1 , t_i , imt_per ) : return y_i + ( y_ip1 - y_i ) / ( t_ip1 - t_i ) * ( imt_per - t_i ) | Generic interpolation function used in equation 19 of 2013 report . | 70 | 12 |
231,925 | def _get_SRF_tau ( self , imt_per ) : if imt_per < 1 : srf = 0.87 elif 1 <= imt_per < 5 : srf = self . _interp_function ( 0.58 , 0.87 , 5 , 1 , imt_per ) elif 5 <= imt_per <= 10 : srf = 0.58 else : srf = 1 return srf | Table 6 and equation 19 of 2013 report . | 92 | 9 |
231,926 | def _get_SRF_phi ( self , imt_per ) : if imt_per < 0.6 : srf = 0.8 elif 0.6 <= imt_per < 1 : srf = self . _interp_function ( 0.7 , 0.8 , 1 , 0.6 , imt_per ) elif 1 <= imt_per <= 10 : srf = self . _interp_function ( 0.6 , 0.7 , 10 , 1 , imt_per ) else : srf = 1 return srf | Table 7 and equation 19 of 2013 report . NB change in notation 2013 report calls this term sigma but it is referred to here as phi . | 119 | 30 |
231,927 | def _get_SRF_sigma ( self , imt_per ) : if imt_per < 0.6 : srf = 0.8 elif 0.6 <= imt_per < 1 : srf = self . _interp_function ( 0.7 , 0.8 , 1 , 0.6 , imt_per ) elif 1 <= imt_per <= 10 : srf = self . _interp_function ( 0.6 , 0.7 , 10 , 1 , imt_per ) else : srf = 1 return srf | Table 8 and equation 19 of 2013 report . NB change in notation 2013 report calls this term sigma_t but it is referred to here as sigma . Note that Table 8 is identical to Table 7 in the 2013 report . | 120 | 46 |
231,928 | def _get_dL2L ( self , imt_per ) : if imt_per < 0.18 : dL2L = - 0.06 elif 0.18 <= imt_per < 0.35 : dL2L = self . _interp_function ( 0.12 , - 0.06 , 0.35 , 0.18 , imt_per ) elif 0.35 <= imt_per <= 10 : dL2L = self . _interp_function ( 0.65 , 0.12 , 10 , 0.35 , imt_per ) else : dL2L = 0 return dL2L | Table 3 and equation 19 of 2013 report . | 143 | 9 |
231,929 | def _get_dS2S ( self , imt_per ) : if imt_per == 0 : dS2S = 0.05 elif 0 < imt_per < 0.15 : dS2S = self . _interp_function ( - 0.15 , 0.05 , 0.15 , 0 , imt_per ) elif 0.15 <= imt_per < 0.45 : dS2S = self . _interp_function ( 0.4 , - 0.15 , 0.45 , 0.15 , imt_per ) elif 0.45 <= imt_per < 3.2 : dS2S = 0.4 elif 3.2 <= imt_per < 5 : dS2S = self . _interp_function ( 0.08 , 0.4 , 5 , 3.2 , imt_per ) elif 5 <= imt_per <= 10 : dS2S = 0.08 else : dS2S = 0 return dS2S | Table 4 of 2013 report | 229 | 5 |
231,930 | def context ( src ) : try : yield except Exception : etype , err , tb = sys . exc_info ( ) msg = 'An error occurred with source id=%s. Error: %s' msg %= ( src . source_id , err ) raise_ ( etype , msg , tb ) | Used to add the source_id to the error message . To be used as | 68 | 16 |
231,931 | def get_bounding_box ( self , lon , lat , trt = None , mag = None ) : if trt is None : # take the greatest integration distance maxdist = max ( self ( trt , mag ) for trt in self . dic ) else : # get the integration distance for the given TRT maxdist = self ( trt , mag ) a1 = min ( maxdist * KM_TO_DEGREES , 90 ) a2 = min ( angular_distance ( maxdist , lat ) , 180 ) return lon - a2 , lat - a1 , lon + a2 , lat + a1 | Build a bounding box around the given lon lat by computing the maximum_distance at the given tectonic region type and magnitude . | 138 | 28 |
231,932 | def get_affected_box ( self , src ) : mag = src . get_min_max_mag ( ) [ 1 ] maxdist = self ( src . tectonic_region_type , mag ) bbox = get_bounding_box ( src , maxdist ) return ( fix_lon ( bbox [ 0 ] ) , bbox [ 1 ] , fix_lon ( bbox [ 2 ] ) , bbox [ 3 ] ) | Get the enlarged bounding box of a source . | 96 | 10 |
231,933 | def sitecol ( self ) : if 'sitecol' in vars ( self ) : return self . __dict__ [ 'sitecol' ] if self . filename is None or not os . path . exists ( self . filename ) : # case of nofilter/None sitecol return with hdf5 . File ( self . filename , 'r' ) as h5 : self . __dict__ [ 'sitecol' ] = sc = h5 . get ( 'sitecol' ) return sc | Read the site collection from . filename and cache it | 105 | 10 |
231,934 | def hypocentre_patch_index ( cls , hypocentre , rupture_top_edge , upper_seismogenic_depth , lower_seismogenic_depth , dip ) : totaln_patch = len ( rupture_top_edge ) indexlist = [ ] dist_list = [ ] for i , index in enumerate ( range ( 1 , totaln_patch ) ) : p0 , p1 , p2 , p3 = cls . get_fault_patch_vertices ( rupture_top_edge , upper_seismogenic_depth , lower_seismogenic_depth , dip , index_patch = index ) [ normal , dist_to_plane ] = get_plane_equation ( p0 , p1 , p2 , hypocentre ) indexlist . append ( index ) dist_list . append ( dist_to_plane ) if numpy . allclose ( dist_to_plane , 0. , atol = 25. , rtol = 0. ) : return index break index = indexlist [ numpy . argmin ( dist_list ) ] return index | This methods finds the index of the fault patch including the hypocentre . | 239 | 15 |
231,935 | def get_surface_vertexes ( cls , fault_trace , upper_seismogenic_depth , lower_seismogenic_depth , dip ) : # Similar to :meth:`from_fault_data`, we just don't resample edges dip_tan = math . tan ( math . radians ( dip ) ) hdist_top = upper_seismogenic_depth / dip_tan hdist_bottom = lower_seismogenic_depth / dip_tan strike = fault_trace [ 0 ] . azimuth ( fault_trace [ - 1 ] ) azimuth = ( strike + 90.0 ) % 360 # Collect coordinates of vertices on the top and bottom edge lons = [ ] lats = [ ] for point in fault_trace . points : top_edge_point = point . point_at ( hdist_top , 0 , azimuth ) bottom_edge_point = point . point_at ( hdist_bottom , 0 , azimuth ) lons . append ( top_edge_point . longitude ) lats . append ( top_edge_point . latitude ) lons . append ( bottom_edge_point . longitude ) lats . append ( bottom_edge_point . latitude ) lons = numpy . array ( lons , float ) lats = numpy . array ( lats , float ) return lons , lats | Get surface main vertexes . | 302 | 6 |
231,936 | def surface_projection_from_fault_data ( cls , fault_trace , upper_seismogenic_depth , lower_seismogenic_depth , dip ) : lons , lats = cls . get_surface_vertexes ( fault_trace , upper_seismogenic_depth , lower_seismogenic_depth , dip ) return Mesh ( lons , lats , depths = None ) . get_convex_hull ( ) | Get a surface projection of the simple fault surface . | 102 | 10 |
231,937 | def _compute_distance_term ( self , C , mag , rrup ) : term1 = C [ 'b' ] * rrup term2 = - np . log ( rrup + C [ 'c' ] * np . exp ( C [ 'd' ] * mag ) ) return term1 + term2 | Compute second and third terms in equation 1 p . 901 . | 69 | 14 |
231,938 | def _compute_focal_depth_term ( self , C , hypo_depth ) : # p. 901. "(i.e, depth is capped at 125 km)". focal_depth = hypo_depth if focal_depth > 125.0 : focal_depth = 125.0 # p. 902. "We used the value of 15 km for the # depth coefficient hc ...". hc = 15.0 # p. 901. "When h is larger than hc, the depth terms takes # effect ...". The next sentence specifies h>=hc. return float ( focal_depth >= hc ) * C [ 'e' ] * ( focal_depth - hc ) | Compute fourth term in equation 1 p . 901 . | 153 | 12 |
231,939 | def _compute_site_class_term ( self , C , vs30 ) : # map vs30 value to site class, see table 2, p. 901. site_term = np . zeros ( len ( vs30 ) ) # hard rock site_term [ vs30 > 1100.0 ] = C [ 'CH' ] # rock site_term [ ( vs30 > 600 ) & ( vs30 <= 1100 ) ] = C [ 'C1' ] # hard soil site_term [ ( vs30 > 300 ) & ( vs30 <= 600 ) ] = C [ 'C2' ] # medium soil site_term [ ( vs30 > 200 ) & ( vs30 <= 300 ) ] = C [ 'C3' ] # soft soil site_term [ vs30 <= 200 ] = C [ 'C4' ] return site_term | Compute nine - th term in equation 1 p . 901 . | 183 | 14 |
231,940 | def _compute_magnitude_squared_term ( self , P , M , Q , W , mag ) : return P * ( mag - M ) + Q * ( mag - M ) ** 2 + W | Compute magnitude squared term equation 5 p . 909 . | 47 | 12 |
231,941 | def _compute_slab_correction_term ( self , C , rrup ) : slab_term = C [ 'SSL' ] * np . log ( rrup ) return slab_term | Compute path modification term for slab events that is the 8 - th term in equation 1 p . 901 . | 43 | 23 |
231,942 | def get_mean_and_stddevs ( self , sites , rup , dists , imt , stddev_types ) : dists_mod = copy . deepcopy ( dists ) dists_mod . rrup [ dists . rrup <= 5. ] = 5. return super ( ) . get_mean_and_stddevs ( sites , rup , dists_mod , imt , stddev_types ) | Using a minimum distance of 5km for the calculation . | 100 | 11 |
231,943 | def confirm ( prompt ) : while True : try : answer = input ( prompt ) except KeyboardInterrupt : # the user presses ctrl+c, just say 'no' return False answer = answer . strip ( ) . lower ( ) if answer not in ( 'y' , 'n' ) : print ( 'Please enter y or n' ) continue return answer == 'y' | Ask for confirmation given a prompt and return a boolean value . | 80 | 12 |
231,944 | def _csv_header ( self ) : fields = [ 'id' , 'number' , 'taxonomy' , 'lon' , 'lat' ] for name in self . cost_types [ 'name' ] : fields . append ( name ) if 'per_area' in self . cost_types [ 'type' ] : fields . append ( 'area' ) if self . occupancy_periods : fields . extend ( self . occupancy_periods . split ( ) ) fields . extend ( self . tagcol . tagnames ) return set ( fields ) | Extract the expected CSV header from the exposure metadata | 120 | 10 |
231,945 | def build_vf_node ( vf ) : nodes = [ Node ( 'imls' , { 'imt' : vf . imt } , vf . imls ) , Node ( 'meanLRs' , { } , vf . mean_loss_ratios ) , Node ( 'covLRs' , { } , vf . covs ) ] return Node ( 'vulnerabilityFunction' , { 'id' : vf . id , 'dist' : vf . distribution_name } , nodes = nodes ) | Convert a VulnerabilityFunction object into a Node suitable for XML conversion . | 118 | 15 |
231,946 | def get_riskmodel ( taxonomy , oqparam , * * extra ) : riskmodel_class = registry [ oqparam . calculation_mode ] # arguments needed to instantiate the riskmodel class argnames = inspect . getfullargspec ( riskmodel_class . __init__ ) . args [ 3 : ] # arguments extracted from oqparam known_args = set ( name for name , value in inspect . getmembers ( oqparam . __class__ ) if isinstance ( value , valid . Param ) ) all_args = { } for argname in argnames : if argname in known_args : all_args [ argname ] = getattr ( oqparam , argname ) if 'hazard_imtls' in argnames : # special case all_args [ 'hazard_imtls' ] = oqparam . imtls all_args . update ( extra ) missing = set ( argnames ) - set ( all_args ) if missing : raise TypeError ( 'Missing parameter: %s' % ', ' . join ( missing ) ) return riskmodel_class ( taxonomy , * * all_args ) | Return an instance of the correct riskmodel class depending on the attribute calculation_mode of the object oqparam . | 245 | 23 |
231,947 | def Beachball ( fm , linewidth = 2 , facecolor = 'b' , bgcolor = 'w' , edgecolor = 'k' , alpha = 1.0 , xy = ( 0 , 0 ) , width = 200 , size = 100 , nofill = False , zorder = 100 , outfile = None , format = None , fig = None ) : plot_width = width * 0.95 # plot the figure if not fig : fig = plt . figure ( figsize = ( 3 , 3 ) , dpi = 100 ) fig . subplots_adjust ( left = 0 , bottom = 0 , right = 1 , top = 1 ) fig . set_figheight ( width // 100 ) fig . set_figwidth ( width // 100 ) ax = fig . add_subplot ( 111 , aspect = 'equal' ) # hide axes + ticks ax . axison = False # plot the collection collection = Beach ( fm , linewidth = linewidth , facecolor = facecolor , edgecolor = edgecolor , bgcolor = bgcolor , alpha = alpha , nofill = nofill , xy = xy , width = plot_width , size = size , zorder = zorder ) ax . add_collection ( collection ) ax . autoscale_view ( tight = False , scalex = True , scaley = True ) # export if outfile : if format : fig . savefig ( outfile , dpi = 100 , transparent = True , format = format ) else : fig . savefig ( outfile , dpi = 100 , transparent = True ) elif format and not outfile : imgdata = compatibility . BytesIO ( ) fig . savefig ( imgdata , format = format , dpi = 100 , transparent = True ) imgdata . seek ( 0 ) return imgdata . read ( ) else : plt . show ( ) return fig | Draws a beach ball diagram of an earthquake focal mechanism . | 407 | 12 |
231,948 | def StrikeDip ( n , e , u ) : r2d = 180 / np . pi if u < 0 : n = - n e = - e u = - u strike = np . arctan2 ( e , n ) * r2d strike = strike - 90 while strike >= 360 : strike = strike - 360 while strike < 0 : strike = strike + 360 x = np . sqrt ( np . power ( n , 2 ) + np . power ( e , 2 ) ) dip = np . arctan2 ( x , u ) * r2d return ( strike , dip ) | Finds strike and dip of plane given normal vector having components n e and u . | 128 | 17 |
231,949 | def AuxPlane ( s1 , d1 , r1 ) : r2d = 180 / np . pi z = ( s1 + 90 ) / r2d z2 = d1 / r2d z3 = r1 / r2d # slick vector in plane 1 sl1 = - np . cos ( z3 ) * np . cos ( z ) - np . sin ( z3 ) * np . sin ( z ) * np . cos ( z2 ) sl2 = np . cos ( z3 ) * np . sin ( z ) - np . sin ( z3 ) * np . cos ( z ) * np . cos ( z2 ) sl3 = np . sin ( z3 ) * np . sin ( z2 ) ( strike , dip ) = StrikeDip ( sl2 , sl1 , sl3 ) n1 = np . sin ( z ) * np . sin ( z2 ) # normal vector to plane 1 n2 = np . cos ( z ) * np . sin ( z2 ) h1 = - sl2 # strike vector of plane 2 h2 = sl1 # note h3=0 always so we leave it out # n3 = np.cos(z2) z = h1 * n1 + h2 * n2 z = z / np . sqrt ( h1 * h1 + h2 * h2 ) z = np . arccos ( z ) rake = 0 if sl3 > 0 : rake = z * r2d if sl3 <= 0 : rake = - z * r2d return ( strike , dip , rake ) | Get Strike and dip of second plane . | 340 | 8 |
231,950 | def MT2Plane ( mt ) : ( d , v ) = np . linalg . eig ( mt . mt ) D = np . array ( [ d [ 1 ] , d [ 0 ] , d [ 2 ] ] ) V = np . array ( [ [ v [ 1 , 1 ] , - v [ 1 , 0 ] , - v [ 1 , 2 ] ] , [ v [ 2 , 1 ] , - v [ 2 , 0 ] , - v [ 2 , 2 ] ] , [ - v [ 0 , 1 ] , v [ 0 , 0 ] , v [ 0 , 2 ] ] ] ) IMAX = D . argmax ( ) IMIN = D . argmin ( ) AE = ( V [ : , IMAX ] + V [ : , IMIN ] ) / np . sqrt ( 2.0 ) AN = ( V [ : , IMAX ] - V [ : , IMIN ] ) / np . sqrt ( 2.0 ) AER = np . sqrt ( np . power ( AE [ 0 ] , 2 ) + np . power ( AE [ 1 ] , 2 ) + np . power ( AE [ 2 ] , 2 ) ) ANR = np . sqrt ( np . power ( AN [ 0 ] , 2 ) + np . power ( AN [ 1 ] , 2 ) + np . power ( AN [ 2 ] , 2 ) ) AE = AE / AER if not ANR : AN = np . array ( [ np . nan , np . nan , np . nan ] ) else : AN = AN / ANR if AN [ 2 ] <= 0. : AN1 = AN AE1 = AE else : AN1 = - AN AE1 = - AE ( ft , fd , fl ) = TDL ( AN1 , AE1 ) return NodalPlane ( 360 - ft , fd , 180 - fl ) | Calculates a nodal plane of a given moment tensor . | 401 | 14 |
231,951 | def TDL ( AN , BN ) : XN = AN [ 0 ] YN = AN [ 1 ] ZN = AN [ 2 ] XE = BN [ 0 ] YE = BN [ 1 ] ZE = BN [ 2 ] AAA = 1.0 / ( 1000000 ) CON = 57.2957795 if np . fabs ( ZN ) < AAA : FD = 90. AXN = np . fabs ( XN ) if AXN > 1.0 : AXN = 1.0 FT = np . arcsin ( AXN ) * CON ST = - XN CT = YN if ST >= 0. and CT < 0 : FT = 180. - FT if ST < 0. and CT <= 0 : FT = 180. + FT if ST < 0. and CT > 0 : FT = 360. - FT FL = np . arcsin ( abs ( ZE ) ) * CON SL = - ZE if np . fabs ( XN ) < AAA : CL = XE / YN else : CL = - YE / XN if SL >= 0. and CL < 0 : FL = 180. - FL if SL < 0. and CL <= 0 : FL = FL - 180. if SL < 0. and CL > 0 : FL = - FL else : if - ZN > 1.0 : ZN = - 1.0 FDH = np . arccos ( - ZN ) FD = FDH * CON SD = np . sin ( FDH ) if SD == 0 : return ST = - XN / SD CT = YN / SD SX = np . fabs ( ST ) if SX > 1.0 : SX = 1.0 FT = np . arcsin ( SX ) * CON if ST >= 0. and CT < 0 : FT = 180. - FT if ST < 0. and CT <= 0 : FT = 180. + FT if ST < 0. and CT > 0 : FT = 360. - FT SL = - ZE / SD SX = np . fabs ( SL ) if SX > 1.0 : SX = 1.0 FL = np . arcsin ( SX ) * CON if ST == 0 : CL = XE / CT else : XXX = YN * ZN * ZE / SD / SD + YE CL = - SD * XXX / XN if CT == 0 : CL = YE / ST if SL >= 0. and CL < 0 : FL = 180. - FL if SL < 0. and CL <= 0 : FL = FL - 180. if SL < 0. and CL > 0 : FL = - FL return ( FT , FD , FL ) | Helper function for MT2Plane . | 565 | 8 |
231,952 | def MT2Axes ( mt ) : ( D , V ) = np . linalg . eigh ( mt . mt ) pl = np . arcsin ( - V [ 0 ] ) az = np . arctan2 ( V [ 2 ] , - V [ 1 ] ) for i in range ( 0 , 3 ) : if pl [ i ] <= 0 : pl [ i ] = - pl [ i ] az [ i ] += np . pi if az [ i ] < 0 : az [ i ] += 2 * np . pi if az [ i ] > 2 * np . pi : az [ i ] -= 2 * np . pi pl *= R2D az *= R2D T = PrincipalAxis ( D [ 2 ] , az [ 2 ] , pl [ 2 ] ) N = PrincipalAxis ( D [ 1 ] , az [ 1 ] , pl [ 1 ] ) P = PrincipalAxis ( D [ 0 ] , az [ 0 ] , pl [ 0 ] ) return ( T , N , P ) | Calculates the principal axes of a given moment tensor . | 220 | 13 |
231,953 | def tapered_gutenberg_richter_cdf ( moment , moment_threshold , beta , corner_moment ) : cdf = np . exp ( ( moment_threshold - moment ) / corner_moment ) return ( ( moment / moment_threshold ) ** ( - beta ) ) * cdf | Tapered Gutenberg Richter Cumulative Density Function | 68 | 11 |
231,954 | def tapered_gutenberg_richter_pdf ( moment , moment_threshold , beta , corner_moment ) : return ( ( beta / moment + 1. / corner_moment ) * tapered_gutenberg_richter_cdf ( moment , moment_threshold , beta , corner_moment ) ) | Tapered Gutenberg - Richter Probability Density Function | 70 | 12 |
231,955 | def makedirs ( path ) : if os . path . exists ( path ) : if not os . path . isdir ( path ) : # If it's not a directory, we can't do anything. # This is a problem raise RuntimeError ( '%s already exists and is not a directory.' % path ) else : os . makedirs ( path ) | Make all of the directories in the path using os . makedirs . | 77 | 15 |
231,956 | def _get_observed_mmax ( catalogue , config ) : if config [ 'input_mmax' ] : obsmax = config [ 'input_mmax' ] if config [ 'input_mmax_uncertainty' ] : return config [ 'input_mmax' ] , config [ 'input_mmax_uncertainty' ] else : raise ValueError ( 'Input mmax uncertainty must be specified!' ) max_location = np . argmax ( catalogue [ 'magnitude' ] ) obsmax = catalogue [ 'magnitude' ] [ max_location ] cond = isinstance ( catalogue [ 'sigmaMagnitude' ] , np . ndarray ) and len ( catalogue [ 'sigmaMagnitude' ] ) > 0 and not np . all ( np . isnan ( catalogue [ 'sigmaMagnitude' ] ) ) if cond : if not np . isnan ( catalogue [ 'sigmaMagnitude' ] [ max_location ] ) : return obsmax , catalogue [ 'sigmaMagnitude' ] [ max_location ] else : print ( 'Uncertainty not given on observed Mmax\n' 'Taking largest magnitude uncertainty found in catalogue' ) return obsmax , np . nanmax ( catalogue [ 'sigmaMagnitude' ] ) elif config [ 'input_mmax_uncertainty' ] : return obsmax , config [ 'input_mmax_uncertainty' ] else : raise ValueError ( 'Input mmax uncertainty must be specified!' ) | Check see if observed mmax values are input if not then take from the catalogue | 329 | 16 |
231,957 | def _get_magnitude_vector_properties ( catalogue , config ) : mmin = config . get ( 'input_mmin' , np . min ( catalogue [ 'magnitude' ] ) ) neq = np . float ( np . sum ( catalogue [ 'magnitude' ] >= mmin - 1.E-7 ) ) return neq , mmin | If an input minimum magnitude is given then consider catalogue only above the minimum magnitude - returns corresponding properties | 81 | 19 |
231,958 | def get_dip ( self ) : # uses the same approach as in simple fault surface if self . dip is None : mesh = self . mesh self . dip , self . strike = mesh . get_mean_inclination_and_azimuth ( ) return self . dip | Return the fault dip as the average dip over the mesh . | 60 | 12 |
231,959 | def check_surface_validity ( cls , edges ) : # extract coordinates of surface boundary (as defined from edges) full_boundary = [ ] left_boundary = [ ] right_boundary = [ ] for i in range ( 1 , len ( edges ) - 1 ) : left_boundary . append ( edges [ i ] . points [ 0 ] ) right_boundary . append ( edges [ i ] . points [ - 1 ] ) full_boundary . extend ( edges [ 0 ] . points ) full_boundary . extend ( right_boundary ) full_boundary . extend ( edges [ - 1 ] . points [ : : - 1 ] ) full_boundary . extend ( left_boundary [ : : - 1 ] ) lons = [ p . longitude for p in full_boundary ] lats = [ p . latitude for p in full_boundary ] depths = [ p . depth for p in full_boundary ] # define reference plane. Corner points are separated by an arbitrary # distance of 10 km. The mesh spacing is set to 2 km. Both corner # distance and mesh spacing values do not affect the algorithm results. ul = edges [ 0 ] . points [ 0 ] strike = ul . azimuth ( edges [ 0 ] . points [ - 1 ] ) dist = 10. ur = ul . point_at ( dist , 0 , strike ) bl = Point ( ul . longitude , ul . latitude , ul . depth + dist ) br = bl . point_at ( dist , 0 , strike ) # project surface boundary to reference plane and check for # validity. ref_plane = PlanarSurface . from_corner_points ( ul , ur , br , bl ) _ , xx , yy = ref_plane . _project ( spherical_to_cartesian ( lons , lats , depths ) ) coords = [ ( x , y ) for x , y in zip ( xx , yy ) ] p = shapely . geometry . Polygon ( coords ) if not p . is_valid : raise ValueError ( 'Edges points are not in the right order' ) | Check validity of the surface . | 456 | 6 |
231,960 | def surface_projection_from_fault_data ( cls , edges ) : # collect lons and lats of all the vertices of all the edges lons = [ ] lats = [ ] for edge in edges : for point in edge : lons . append ( point . longitude ) lats . append ( point . latitude ) lons = numpy . array ( lons , dtype = float ) lats = numpy . array ( lats , dtype = float ) return Mesh ( lons , lats , depths = None ) . get_convex_hull ( ) | Get a surface projection of the complex fault surface . | 130 | 10 |
231,961 | def check_time_event ( oqparam , occupancy_periods ) : time_event = oqparam . time_event if time_event and time_event not in occupancy_periods : raise ValueError ( 'time_event is %s in %s, but the exposure contains %s' % ( time_event , oqparam . inputs [ 'job_ini' ] , ', ' . join ( occupancy_periods ) ) ) | Check the time_event parameter in the datastore by comparing with the periods found in the exposure . | 96 | 21 |
231,962 | def get_idxs ( data , eid2idx ) : uniq , inv = numpy . unique ( data [ 'eid' ] , return_inverse = True ) idxs = numpy . array ( [ eid2idx [ eid ] for eid in uniq ] ) [ inv ] return idxs | Convert from event IDs to event indices . | 72 | 9 |
231,963 | def import_gmfs ( dstore , fname , sids ) : array = writers . read_composite_array ( fname ) . array # has header rlzi, sid, eid, gmv_PGA, ... imts = [ name [ 4 : ] for name in array . dtype . names [ 3 : ] ] n_imts = len ( imts ) gmf_data_dt = numpy . dtype ( [ ( 'rlzi' , U16 ) , ( 'sid' , U32 ) , ( 'eid' , U64 ) , ( 'gmv' , ( F32 , ( n_imts , ) ) ) ] ) # store the events eids = numpy . unique ( array [ 'eid' ] ) eids . sort ( ) E = len ( eids ) eid2idx = dict ( zip ( eids , range ( E ) ) ) events = numpy . zeros ( E , rupture . events_dt ) events [ 'eid' ] = eids dstore [ 'events' ] = events # store the GMFs dic = general . group_array ( array . view ( gmf_data_dt ) , 'sid' ) lst = [ ] offset = 0 for sid in sids : n = len ( dic . get ( sid , [ ] ) ) lst . append ( ( offset , offset + n ) ) if n : offset += n gmvs = dic [ sid ] gmvs [ 'eid' ] = get_idxs ( gmvs , eid2idx ) gmvs [ 'rlzi' ] = 0 # effectively there is only 1 realization dstore . extend ( 'gmf_data/data' , gmvs ) dstore [ 'gmf_data/indices' ] = numpy . array ( lst , U32 ) dstore [ 'gmf_data/imts' ] = ' ' . join ( imts ) sig_eps_dt = [ ( 'eid' , U64 ) , ( 'sig' , ( F32 , n_imts ) ) , ( 'eps' , ( F32 , n_imts ) ) ] dstore [ 'gmf_data/sigma_epsilon' ] = numpy . zeros ( 0 , sig_eps_dt ) dstore [ 'weights' ] = numpy . ones ( ( 1 , n_imts ) ) return eids | Import in the datastore a ground motion field CSV file . | 541 | 13 |
231,964 | def save_params ( self , * * kw ) : if ( 'hazard_calculation_id' in kw and kw [ 'hazard_calculation_id' ] is None ) : del kw [ 'hazard_calculation_id' ] vars ( self . oqparam ) . update ( * * kw ) self . datastore [ 'oqparam' ] = self . oqparam # save the updated oqparam attrs = self . datastore [ '/' ] . attrs attrs [ 'engine_version' ] = engine_version attrs [ 'date' ] = datetime . now ( ) . isoformat ( ) [ : 19 ] if 'checksum32' not in attrs : attrs [ 'checksum32' ] = readinput . get_checksum32 ( self . oqparam ) self . datastore . flush ( ) | Update the current calculation parameters and save engine_version | 194 | 10 |
231,965 | def run ( self , pre_execute = True , concurrent_tasks = None , close = True , * * kw ) : with self . _monitor : self . _monitor . username = kw . get ( 'username' , '' ) self . _monitor . hdf5 = self . datastore . hdf5 if concurrent_tasks is None : # use the job.ini parameter ct = self . oqparam . concurrent_tasks else : # used the parameter passed in the command-line ct = concurrent_tasks if ct == 0 : # disable distribution temporarily oq_distribute = os . environ . get ( 'OQ_DISTRIBUTE' ) os . environ [ 'OQ_DISTRIBUTE' ] = 'no' if ct != self . oqparam . concurrent_tasks : # save the used concurrent_tasks self . oqparam . concurrent_tasks = ct self . save_params ( * * kw ) try : if pre_execute : self . pre_execute ( ) self . result = self . execute ( ) if self . result is not None : self . post_execute ( self . result ) self . before_export ( ) self . export ( kw . get ( 'exports' , '' ) ) except Exception : if kw . get ( 'pdb' ) : # post-mortem debug tb = sys . exc_info ( ) [ 2 ] traceback . print_tb ( tb ) pdb . post_mortem ( tb ) else : logging . critical ( '' , exc_info = True ) raise finally : # cleanup globals if ct == 0 : # restore OQ_DISTRIBUTE if oq_distribute is None : # was not set del os . environ [ 'OQ_DISTRIBUTE' ] else : os . environ [ 'OQ_DISTRIBUTE' ] = oq_distribute readinput . pmap = None readinput . exposure = None readinput . gmfs = None readinput . eids = None self . _monitor . flush ( ) if close : # in the engine we close later self . result = None try : self . datastore . close ( ) except ( RuntimeError , ValueError ) : # sometimes produces errors but they are difficult to # reproduce logging . warning ( '' , exc_info = True ) return getattr ( self , 'exported' , { } ) | Run the calculation and return the exported outputs . | 531 | 9 |
231,966 | def export ( self , exports = None ) : self . exported = getattr ( self . precalc , 'exported' , { } ) if isinstance ( exports , tuple ) : fmts = exports elif exports : # is a string fmts = exports . split ( ',' ) elif isinstance ( self . oqparam . exports , tuple ) : fmts = self . oqparam . exports else : # is a string fmts = self . oqparam . exports . split ( ',' ) keys = set ( self . datastore ) has_hcurves = ( 'hcurves-stats' in self . datastore or 'hcurves-rlzs' in self . datastore ) if has_hcurves : keys . add ( 'hcurves' ) for fmt in fmts : if not fmt : continue for key in sorted ( keys ) : # top level keys if 'rlzs' in key and self . R > 1 : continue # skip individual curves self . _export ( ( key , fmt ) ) if has_hcurves and self . oqparam . hazard_maps : self . _export ( ( 'hmaps' , fmt ) ) if has_hcurves and self . oqparam . uniform_hazard_spectra : self . _export ( ( 'uhs' , fmt ) ) | Export all the outputs in the datastore in the given export formats . Individual outputs are not exported if there are multiple realizations . | 298 | 27 |
231,967 | def before_export ( self ) : # sanity check that eff_ruptures have been set, i.e. are not -1 try : csm_info = self . datastore [ 'csm_info' ] except KeyError : csm_info = self . datastore [ 'csm_info' ] = self . csm . info for sm in csm_info . source_models : for sg in sm . src_groups : assert sg . eff_ruptures != - 1 , sg for key in self . datastore : self . datastore . set_nbytes ( key ) self . datastore . flush ( ) | Set the attributes nbytes | 144 | 5 |
231,968 | def read_inputs ( self ) : oq = self . oqparam self . _read_risk_data ( ) self . check_overflow ( ) # check if self.sitecol is too large if ( 'source_model_logic_tree' in oq . inputs and oq . hazard_calculation_id is None ) : self . csm = readinput . get_composite_source_model ( oq , self . monitor ( ) , srcfilter = self . src_filter ) self . init ( ) | Read risk data and sources if any | 117 | 7 |
231,969 | def init ( self ) : oq = self . oqparam if not oq . risk_imtls : if self . datastore . parent : oq . risk_imtls = ( self . datastore . parent [ 'oqparam' ] . risk_imtls ) if 'precalc' in vars ( self ) : self . rlzs_assoc = self . precalc . rlzs_assoc elif 'csm_info' in self . datastore : csm_info = self . datastore [ 'csm_info' ] if oq . hazard_calculation_id and 'gsim_logic_tree' in oq . inputs : # redefine the realizations by reading the weights from the # gsim_logic_tree_file that could be different from the parent csm_info . gsim_lt = logictree . GsimLogicTree ( oq . inputs [ 'gsim_logic_tree' ] , set ( csm_info . trts ) ) self . rlzs_assoc = csm_info . get_rlzs_assoc ( ) elif hasattr ( self , 'csm' ) : self . check_floating_spinning ( ) self . rlzs_assoc = self . csm . info . get_rlzs_assoc ( ) else : # build a fake; used by risk-from-file calculators self . datastore [ 'csm_info' ] = fake = source . CompositionInfo . fake ( ) self . rlzs_assoc = fake . get_rlzs_assoc ( ) | To be overridden to initialize the datasets needed by the calculation | 375 | 12 |
231,970 | def read_exposure ( self , haz_sitecol = None ) : # after load_risk_model with self . monitor ( 'reading exposure' , autoflush = True ) : self . sitecol , self . assetcol , discarded = ( readinput . get_sitecol_assetcol ( self . oqparam , haz_sitecol , self . riskmodel . loss_types ) ) if len ( discarded ) : self . datastore [ 'discarded' ] = discarded if hasattr ( self , 'rup' ) : # this is normal for the case of scenario from rupture logging . info ( '%d assets were discarded because too far ' 'from the rupture; use `oq show discarded` ' 'to show them and `oq plot_assets` to plot ' 'them' % len ( discarded ) ) elif not self . oqparam . discard_assets : # raise an error self . datastore [ 'sitecol' ] = self . sitecol self . datastore [ 'assetcol' ] = self . assetcol raise RuntimeError ( '%d assets were discarded; use `oq show discarded` to' ' show them and `oq plot_assets` to plot them' % len ( discarded ) ) # reduce the riskmodel to the relevant taxonomies taxonomies = set ( taxo for taxo in self . assetcol . tagcol . taxonomy if taxo != '?' ) if len ( self . riskmodel . taxonomies ) > len ( taxonomies ) : logging . info ( 'Reducing risk model from %d to %d taxonomies' , len ( self . riskmodel . taxonomies ) , len ( taxonomies ) ) self . riskmodel = self . riskmodel . reduce ( taxonomies ) return readinput . exposure | Read the exposure the riskmodel and update the attributes . sitecol . assetcol | 390 | 16 |
231,971 | def save_riskmodel ( self ) : self . datastore [ 'risk_model' ] = rm = self . riskmodel self . datastore [ 'taxonomy_mapping' ] = self . riskmodel . tmap attrs = self . datastore . getitem ( 'risk_model' ) . attrs attrs [ 'min_iml' ] = hdf5 . array_of_vstr ( sorted ( rm . min_iml . items ( ) ) ) self . datastore . set_nbytes ( 'risk_model' ) | Save the risk models in the datastore | 124 | 9 |
231,972 | def store_rlz_info ( self , eff_ruptures = None ) : if hasattr ( self , 'csm' ) : # no scenario self . csm . info . update_eff_ruptures ( eff_ruptures ) self . rlzs_assoc = self . csm . info . get_rlzs_assoc ( self . oqparam . sm_lt_path ) if not self . rlzs_assoc : raise RuntimeError ( 'Empty logic tree: too much filtering?' ) self . datastore [ 'csm_info' ] = self . csm . info R = len ( self . rlzs_assoc . realizations ) logging . info ( 'There are %d realization(s)' , R ) if self . oqparam . imtls : self . datastore [ 'weights' ] = arr = build_weights ( self . rlzs_assoc . realizations , self . oqparam . imt_dt ( ) ) self . datastore . set_attrs ( 'weights' , nbytes = arr . nbytes ) if hasattr ( self , 'hdf5cache' ) : # no scenario with hdf5 . File ( self . hdf5cache , 'r+' ) as cache : cache [ 'weights' ] = arr if 'event_based' in self . oqparam . calculation_mode and R >= TWO16 : # rlzi is 16 bit integer in the GMFs, so there is hard limit or R raise ValueError ( 'The logic tree has %d realizations, the maximum ' 'is %d' % ( R , TWO16 ) ) elif R > 10000 : logging . warning ( 'The logic tree has %d realizations(!), please consider ' 'sampling it' , R ) self . datastore . flush ( ) | Save info about the composite source model inside the csm_info dataset | 406 | 14 |
231,973 | def read_shakemap ( self , haz_sitecol , assetcol ) : oq = self . oqparam E = oq . number_of_ground_motion_fields oq . risk_imtls = oq . imtls or self . datastore . parent [ 'oqparam' ] . imtls extra = self . riskmodel . get_extra_imts ( oq . risk_imtls ) if extra : logging . warning ( 'There are risk functions for not available IMTs ' 'which will be ignored: %s' % extra ) logging . info ( 'Getting/reducing shakemap' ) with self . monitor ( 'getting/reducing shakemap' ) : smap = oq . shakemap_id if oq . shakemap_id else numpy . load ( oq . inputs [ 'shakemap' ] ) sitecol , shakemap , discarded = get_sitecol_shakemap ( smap , oq . imtls , haz_sitecol , oq . asset_hazard_distance [ 'default' ] , oq . discard_assets ) if len ( discarded ) : self . datastore [ 'discarded' ] = discarded assetcol = assetcol . reduce_also ( sitecol ) logging . info ( 'Building GMFs' ) with self . monitor ( 'building/saving GMFs' ) : imts , gmfs = to_gmfs ( shakemap , oq . spatial_correlation , oq . cross_correlation , oq . site_effects , oq . truncation_level , E , oq . random_seed , oq . imtls ) save_gmf_data ( self . datastore , sitecol , gmfs , imts ) return sitecol , assetcol | Enabled only if there is a shakemap_id parameter in the job . ini . Download unzip parse USGS shakemap files and build a corresponding set of GMFs which are then filtered with the hazard site collection and stored in the datastore . | 388 | 52 |
231,974 | def bind ( end_point , socket_type ) : sock = context . socket ( socket_type ) try : sock . bind ( end_point ) except zmq . error . ZMQError as exc : sock . close ( ) raise exc . __class__ ( '%s: %s' % ( exc , end_point ) ) return sock | Bind to a zmq URL ; raise a proper error if the URL is invalid ; return a zmq socket . | 75 | 25 |
231,975 | def send ( self , obj ) : self . zsocket . send_pyobj ( obj ) self . num_sent += 1 if self . socket_type == zmq . REQ : return self . zsocket . recv_pyobj ( ) | Send an object to the remote server ; block and return the reply if the socket type is REQ . | 54 | 21 |
231,976 | def angular_distance ( km , lat , lat2 = None ) : if lat2 is not None : # use the largest latitude to compute the angular distance lat = max ( abs ( lat ) , abs ( lat2 ) ) return km * KM_TO_DEGREES / math . cos ( lat * DEGREES_TO_RAD ) | Return the angular distance of two points at the given latitude . | 74 | 12 |
231,977 | def assoc ( objects , sitecol , assoc_dist , mode , asset_refs = ( ) ) : if isinstance ( objects , numpy . ndarray ) or hasattr ( objects , 'lons' ) : # objects is a geo array with lon, lat fields or a mesh-like instance return _GeographicObjects ( objects ) . assoc ( sitecol , assoc_dist , mode ) else : # objects is the list assets_by_site return _GeographicObjects ( sitecol ) . assoc2 ( objects , assoc_dist , mode , asset_refs ) | Associate geographic objects to a site collection . | 132 | 9 |
231,978 | def line_intersects_itself ( lons , lats , closed_shape = False ) : assert len ( lons ) == len ( lats ) if len ( lons ) <= 3 : # line can not intersect itself unless there are # at least four points return False west , east , north , south = get_spherical_bounding_box ( lons , lats ) proj = OrthographicProjection ( west , east , north , south ) xx , yy = proj ( lons , lats ) if not shapely . geometry . LineString ( list ( zip ( xx , yy ) ) ) . is_simple : return True if closed_shape : xx , yy = proj ( numpy . roll ( lons , 1 ) , numpy . roll ( lats , 1 ) ) if not shapely . geometry . LineString ( list ( zip ( xx , yy ) ) ) . is_simple : return True return False | Return True if line of points intersects itself . Line with the last point repeating the first one considered intersecting itself . | 207 | 24 |
231,979 | def get_bounding_box ( obj , maxdist ) : if hasattr ( obj , 'get_bounding_box' ) : return obj . get_bounding_box ( maxdist ) elif hasattr ( obj , 'polygon' ) : bbox = obj . polygon . get_bbox ( ) else : if isinstance ( obj , list ) : # a list of locations lons = numpy . array ( [ loc . longitude for loc in obj ] ) lats = numpy . array ( [ loc . latitude for loc in obj ] ) else : # assume an array with fields lon, lat lons , lats = obj [ 'lon' ] , obj [ 'lat' ] min_lon , max_lon = lons . min ( ) , lons . max ( ) if cross_idl ( min_lon , max_lon ) : lons %= 360 bbox = lons . min ( ) , lats . min ( ) , lons . max ( ) , lats . max ( ) a1 = min ( maxdist * KM_TO_DEGREES , 90 ) a2 = min ( angular_distance ( maxdist , bbox [ 1 ] , bbox [ 3 ] ) , 180 ) return bbox [ 0 ] - a2 , bbox [ 1 ] - a1 , bbox [ 2 ] + a2 , bbox [ 3 ] + a1 | Return the dilated bounding box of a geometric object . | 307 | 12 |
231,980 | def get_spherical_bounding_box ( lons , lats ) : north , south = numpy . max ( lats ) , numpy . min ( lats ) west , east = numpy . min ( lons ) , numpy . max ( lons ) assert ( - 180 <= west <= 180 ) and ( - 180 <= east <= 180 ) , ( west , east ) if get_longitudinal_extent ( west , east ) < 0 : # points are lying on both sides of the international date line # (meridian 180). the actual west longitude is the lowest positive # longitude and east one is the highest negative. if hasattr ( lons , 'flatten' ) : # fixes test_surface_crossing_international_date_line lons = lons . flatten ( ) west = min ( lon for lon in lons if lon > 0 ) east = max ( lon for lon in lons if lon < 0 ) if not all ( ( get_longitudinal_extent ( west , lon ) >= 0 and get_longitudinal_extent ( lon , east ) >= 0 ) for lon in lons ) : raise ValueError ( 'points collection has longitudinal extent ' 'wider than 180 deg' ) return SphericalBB ( west , east , north , south ) | Given a collection of points find and return the bounding box as a pair of longitudes and a pair of latitudes . | 288 | 25 |
231,981 | def get_middle_point ( lon1 , lat1 , lon2 , lat2 ) : if lon1 == lon2 and lat1 == lat2 : return lon1 , lat1 dist = geodetic . geodetic_distance ( lon1 , lat1 , lon2 , lat2 ) azimuth = geodetic . azimuth ( lon1 , lat1 , lon2 , lat2 ) return geodetic . point_at ( lon1 , lat1 , azimuth , dist / 2.0 ) | Given two points return the point exactly in the middle lying on the same great circle arc . | 122 | 18 |
231,982 | def cartesian_to_spherical ( vectors ) : rr = numpy . sqrt ( numpy . sum ( vectors * vectors , axis = - 1 ) ) xx , yy , zz = vectors . T lats = numpy . degrees ( numpy . arcsin ( ( zz / rr ) . clip ( - 1. , 1. ) ) ) lons = numpy . degrees ( numpy . arctan2 ( yy , xx ) ) depths = EARTH_RADIUS - rr return lons . T , lats . T , depths | Return the spherical coordinates for coordinates in Cartesian space . | 126 | 11 |
231,983 | def triangle_area ( e1 , e2 , e3 ) : # calculating edges length e1_length = numpy . sqrt ( numpy . sum ( e1 * e1 , axis = - 1 ) ) e2_length = numpy . sqrt ( numpy . sum ( e2 * e2 , axis = - 1 ) ) e3_length = numpy . sqrt ( numpy . sum ( e3 * e3 , axis = - 1 ) ) # calculating half perimeter s = ( e1_length + e2_length + e3_length ) / 2.0 # applying Heron's formula return numpy . sqrt ( s * ( s - e1_length ) * ( s - e2_length ) * ( s - e3_length ) ) | Get the area of triangle formed by three vectors . | 171 | 10 |
231,984 | def normalized ( vector ) : length = numpy . sum ( vector * vector , axis = - 1 ) length = numpy . sqrt ( length . reshape ( length . shape + ( 1 , ) ) ) return vector / length | Get unit vector for a given one . | 49 | 8 |
231,985 | def point_to_polygon_distance ( polygon , pxx , pyy ) : pxx = numpy . array ( pxx ) pyy = numpy . array ( pyy ) assert pxx . shape == pyy . shape if pxx . ndim == 0 : pxx = pxx . reshape ( ( 1 , ) ) pyy = pyy . reshape ( ( 1 , ) ) result = numpy . array ( [ polygon . distance ( shapely . geometry . Point ( pxx . item ( i ) , pyy . item ( i ) ) ) for i in range ( pxx . size ) ] ) return result . reshape ( pxx . shape ) | Calculate the distance to polygon for each point of the collection on the 2d Cartesian plane . | 149 | 22 |
231,986 | def cross_idl ( lon1 , lon2 , * lons ) : lons = ( lon1 , lon2 ) + lons l1 , l2 = min ( lons ) , max ( lons ) # a line crosses the international date line if the end positions # have different sign and they are more than 180 degrees longitude apart return l1 * l2 < 0 and abs ( l1 - l2 ) > 180 | Return True if two longitude values define line crossing international date line . | 96 | 14 |
231,987 | def normalize_lons ( l1 , l2 ) : if l1 > l2 : # exchange lons l1 , l2 = l2 , l1 delta = l2 - l1 if l1 < 0 and l2 > 0 and delta > 180 : return [ ( - 180 , l1 ) , ( l2 , 180 ) ] elif l1 > 0 and l2 > 180 and delta < 180 : return [ ( l1 , 180 ) , ( - 180 , l2 - 360 ) ] elif l1 < - 180 and l2 < 0 and delta < 180 : return [ ( l1 + 360 , 180 ) , ( l2 , - 180 ) ] return [ ( l1 , l2 ) ] | An international date line safe way of returning a range of longitudes . | 156 | 14 |
231,988 | def get_closest ( self , lon , lat , depth = 0 ) : xyz = spherical_to_cartesian ( lon , lat , depth ) min_dist , idx = self . kdtree . query ( xyz ) return self . objects [ idx ] , min_dist | Get the closest object to the given longitude and latitude and its distance . | 66 | 15 |
231,989 | def assoc2 ( self , assets_by_site , assoc_dist , mode , asset_refs ) : assert mode in 'strict filter' , mode self . objects . filtered # self.objects must be a SiteCollection asset_dt = numpy . dtype ( [ ( 'asset_ref' , vstr ) , ( 'lon' , F32 ) , ( 'lat' , F32 ) ] ) assets_by_sid = collections . defaultdict ( list ) discarded = [ ] for assets in assets_by_site : lon , lat = assets [ 0 ] . location obj , distance = self . get_closest ( lon , lat ) if distance <= assoc_dist : # keep the assets, otherwise discard them assets_by_sid [ obj [ 'sids' ] ] . extend ( assets ) elif mode == 'strict' : raise SiteAssociationError ( 'There is nothing closer than %s km ' 'to site (%s %s)' % ( assoc_dist , lon , lat ) ) else : discarded . extend ( assets ) sids = sorted ( assets_by_sid ) if not sids : raise SiteAssociationError ( 'Could not associate any site to any assets within the ' 'asset_hazard_distance of %s km' % assoc_dist ) assets_by_site = [ sorted ( assets_by_sid [ sid ] , key = operator . attrgetter ( 'ordinal' ) ) for sid in sids ] data = [ ( asset_refs [ asset . ordinal ] , ) + asset . location for asset in discarded ] discarded = numpy . array ( data , asset_dt ) return self . objects . filtered ( sids ) , assets_by_site , discarded | Associated a list of assets by site to the site collection used to instantiate GeographicObjects . | 382 | 19 |
231,990 | def ffconvert ( fname , limit_states , ff , min_iml = 1E-10 ) : with context ( fname , ff ) : ffs = ff [ 1 : ] imls = ff . imls nodamage = imls . attrib . get ( 'noDamageLimit' ) if nodamage == 0 : # use a cutoff to avoid log(0) in GMPE.to_distribution_values logging . warning ( 'Found a noDamageLimit=0 in %s, line %s, ' 'using %g instead' , fname , ff . lineno , min_iml ) nodamage = min_iml with context ( fname , imls ) : attrs = dict ( format = ff [ 'format' ] , imt = imls [ 'imt' ] , id = ff [ 'id' ] , nodamage = nodamage ) LS = len ( limit_states ) if LS != len ( ffs ) : with context ( fname , ff ) : raise InvalidFile ( 'expected %d limit states, found %d' % ( LS , len ( ffs ) ) ) if ff [ 'format' ] == 'continuous' : minIML = float ( imls [ 'minIML' ] ) if minIML == 0 : # use a cutoff to avoid log(0) in GMPE.to_distribution_values logging . warning ( 'Found minIML=0 in %s, line %s, using %g instead' , fname , imls . lineno , min_iml ) minIML = min_iml attrs [ 'minIML' ] = minIML attrs [ 'maxIML' ] = float ( imls [ 'maxIML' ] ) array = numpy . zeros ( LS , [ ( 'mean' , F64 ) , ( 'stddev' , F64 ) ] ) for i , ls , node in zip ( range ( LS ) , limit_states , ff [ 1 : ] ) : if ls != node [ 'ls' ] : with context ( fname , node ) : raise InvalidFile ( 'expected %s, found' % ( ls , node [ 'ls' ] ) ) array [ 'mean' ] [ i ] = node [ 'mean' ] array [ 'stddev' ] [ i ] = node [ 'stddev' ] elif ff [ 'format' ] == 'discrete' : attrs [ 'imls' ] = ~ imls valid . check_levels ( attrs [ 'imls' ] , attrs [ 'imt' ] , min_iml ) num_poes = len ( attrs [ 'imls' ] ) array = numpy . zeros ( ( LS , num_poes ) ) for i , ls , node in zip ( range ( LS ) , limit_states , ff [ 1 : ] ) : with context ( fname , node ) : if ls != node [ 'ls' ] : raise InvalidFile ( 'expected %s, found' % ( ls , node [ 'ls' ] ) ) poes = ( ~ node if isinstance ( ~ node , list ) else valid . probabilities ( ~ node ) ) if len ( poes ) != num_poes : raise InvalidFile ( 'expected %s, found' % ( num_poes , len ( poes ) ) ) array [ i , : ] = poes # NB: the format is constrained in nrml.FragilityNode to be either # discrete or continuous, there is no third option return array , attrs | Convert a fragility function into a numpy array plus a bunch of attributes . | 779 | 17 |
231,991 | def taxonomy ( value ) : try : value . encode ( 'ascii' ) except UnicodeEncodeError : raise ValueError ( 'tag %r is not ASCII' % value ) if re . search ( r'\s' , value ) : raise ValueError ( 'The taxonomy %r contains whitespace chars' % value ) return value | Any ASCII character goes into a taxonomy except spaces . | 74 | 11 |
231,992 | def update_validators ( ) : validators . update ( { 'fragilityFunction.id' : valid . utf8 , # taxonomy 'vulnerabilityFunction.id' : valid . utf8 , # taxonomy 'consequenceFunction.id' : valid . utf8 , # taxonomy 'asset.id' : valid . asset_id , 'costType.name' : valid . cost_type , 'costType.type' : valid . cost_type_type , 'cost.type' : valid . cost_type , 'area.type' : valid . name , 'isAbsolute' : valid . boolean , 'insuranceLimit' : valid . positivefloat , 'deductible' : valid . positivefloat , 'occupants' : valid . positivefloat , 'value' : valid . positivefloat , 'retrofitted' : valid . positivefloat , 'number' : valid . compose ( valid . positivefloat , valid . nonzero ) , 'vulnerabilitySetID' : str , # any ASCII string is fine 'vulnerabilityFunctionID' : str , # any ASCII string is fine 'lossCategory' : valid . utf8 , # a description field 'lr' : valid . probability , 'lossRatio' : valid . positivefloats , 'coefficientsVariation' : valid . positivefloats , 'probabilisticDistribution' : valid . Choice ( 'LN' , 'BT' ) , 'dist' : valid . Choice ( 'LN' , 'BT' , 'PM' ) , 'meanLRs' : valid . positivefloats , 'covLRs' : valid . positivefloats , 'format' : valid . ChoiceCI ( 'discrete' , 'continuous' ) , 'mean' : valid . positivefloat , 'stddev' : valid . positivefloat , 'minIML' : valid . positivefloat , 'maxIML' : valid . positivefloat , 'limitStates' : valid . namelist , 'noDamageLimit' : valid . NoneOr ( valid . positivefloat ) , 'loss_type' : valid_loss_types , 'losses' : valid . positivefloats , 'averageLoss' : valid . positivefloat , 'stdDevLoss' : valid . positivefloat , 'ffs.type' : valid . ChoiceCI ( 'lognormal' ) , 'assetLifeExpectancy' : valid . positivefloat , 'interestRate' : valid . positivefloat , 'lossType' : valid_loss_types , 'aalOrig' : valid . positivefloat , 'aalRetr' : valid . positivefloat , 'ratio' : valid . positivefloat , 'cf' : asset_mean_stddev , 'damage' : damage_triple , 'damageStates' : valid . namelist , 'taxonomy' : taxonomy , 'tagNames' : valid . namelist , } ) | Call this to updade the global nrml . validators | 634 | 13 |
231,993 | def barray ( iterlines ) : lst = [ line . encode ( 'utf-8' ) for line in iterlines ] arr = numpy . array ( lst ) return arr | Array of bytes | 40 | 3 |
231,994 | def losses_by_tag ( dstore , tag ) : dt = [ ( tag , vstr ) ] + dstore [ 'oqparam' ] . loss_dt_list ( ) aids = dstore [ 'assetcol/array' ] [ tag ] dset , stats = _get ( dstore , 'avg_losses' ) arr = dset . value tagvalues = dstore [ 'assetcol/tagcol/' + tag ] [ 1 : ] # except tagvalue="?" for s , stat in enumerate ( stats ) : out = numpy . zeros ( len ( tagvalues ) , dt ) for li , ( lt , lt_dt ) in enumerate ( dt [ 1 : ] ) : for i , tagvalue in enumerate ( tagvalues ) : out [ i ] [ tag ] = tagvalue counts = arr [ aids == i + 1 , s , li ] . sum ( ) if counts : out [ i ] [ lt ] = counts yield stat , out | Statistical average losses by tag . For instance call | 221 | 10 |
231,995 | def dump ( self , fname ) : url = '%s/v1/calc/%d/datastore' % ( self . server , self . calc_id ) resp = self . sess . get ( url , stream = True ) down = 0 with open ( fname , 'wb' ) as f : logging . info ( 'Saving %s' , fname ) for chunk in resp . iter_content ( CHUNKSIZE ) : f . write ( chunk ) down += len ( chunk ) println ( 'Downloaded {:,} bytes' . format ( down ) ) print ( ) | Dump the remote datastore on a local path . | 131 | 12 |
231,996 | def _compute_small_mag_correction_term ( C , mag , rhypo ) : if mag >= 3.00 and mag < 5.5 : min_term = np . minimum ( rhypo , C [ 'Rm' ] ) max_term = np . maximum ( min_term , 10 ) term_ln = np . log ( max_term / 20 ) term_ratio = ( ( 5.50 - mag ) / C [ 'a1' ] ) temp = ( term_ratio ) ** C [ 'a2' ] * ( C [ 'b1' ] + C [ 'b2' ] * term_ln ) return 1 / np . exp ( temp ) else : return 1 | small magnitude correction applied to the median values | 157 | 8 |
231,997 | def _apply_adjustments ( COEFFS , C_ADJ , tau_ss , mean , stddevs , sites , rup , dists , imt , stddev_types , log_phi_ss , NL = None , tau_value = None ) : c1_dists = _compute_C1_term ( C_ADJ , dists ) phi_ss = _compute_phi_ss ( C_ADJ , rup . mag , c1_dists , log_phi_ss , C_ADJ [ 'mean_phi_ss' ] ) mean_corr = np . exp ( mean ) * C_ADJ [ 'k_adj' ] * _compute_small_mag_correction_term ( C_ADJ , rup . mag , dists ) mean_corr = np . log ( mean_corr ) std_corr = _get_corr_stddevs ( COEFFS [ imt ] , tau_ss , stddev_types , len ( sites . vs30 ) , phi_ss , NL , tau_value ) stddevs = np . array ( std_corr ) return mean_corr , stddevs | This method applies adjustments to the mean and standard deviation . The small - magnitude adjustments are applied to mean whereas the embeded single station sigma logic tree is applied to the total standard deviation . | 278 | 38 |
231,998 | def get_info ( self , sm_id ) : sm = self . source_models [ sm_id ] num_samples = sm . samples if self . num_samples else 0 return self . __class__ ( self . gsim_lt , self . seed , num_samples , [ sm ] , self . tot_weight ) | Extract a CompositionInfo instance containing the single model of index sm_id . | 74 | 17 |
231,999 | def get_source_model ( self , src_group_id ) : for smodel in self . source_models : for src_group in smodel . src_groups : if src_group . id == src_group_id : return smodel | Return the source model for the given src_group_id | 57 | 12 |
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