idx int64 0 63k | question stringlengths 61 4.03k | target stringlengths 6 1.23k |
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43,100 | def reanimate ( self , _time = None ) : n_reanimated = 0 now = _time or time . time ( ) for proxy in list ( self . dead ) : state = self . proxies [ proxy ] assert state . next_check is not None if state . next_check <= now : self . dead . remove ( proxy ) self . unchecked . add ( proxy ) n_reanimated += 1 return n_rea... | Move dead proxies to unchecked if a backoff timeout passes |
43,101 | def reset ( self ) : for proxy in list ( self . dead ) : self . dead . remove ( proxy ) self . unchecked . add ( proxy ) | Mark all dead proxies as unchecked |
43,102 | def on_change ( self , path , event_type ) : sql = cursor = self . _execute ( sql , ( path , ) ) results = cursor . fetchall ( ) for result in results : collection_id = result [ 0 ] sql = cursor = self . _execute ( sql , ( collection_id , ) ) self . _load_keywords ( collection_id , path = path ) | Respond to changes in the file system |
43,103 | def _load_keywords ( self , collection_id , path = None , libdoc = None ) : if libdoc is None and path is None : raise ( Exception ( "You must provide either a path or libdoc argument" ) ) if libdoc is None : libdoc = LibraryDocumentation ( path ) if len ( libdoc . keywords ) > 0 : for keyword in libdoc . keywords : se... | Load a collection of keywords |
43,104 | def add_file ( self , path ) : libdoc = LibraryDocumentation ( path ) if len ( libdoc . keywords ) > 0 : if libdoc . doc . startswith ( "Documentation for resource file" ) : libdoc . doc = "" collection_id = self . add_collection ( path , libdoc . name , libdoc . type , libdoc . doc , libdoc . version , libdoc . scope ... | Add a resource file or library file to the database |
43,105 | def add_library ( self , name ) : libdoc = LibraryDocumentation ( name ) if len ( libdoc . keywords ) > 0 : collection_id = self . add_collection ( None , libdoc . name , libdoc . type , libdoc . doc , libdoc . version , libdoc . scope , libdoc . named_args , libdoc . doc_format ) self . _load_keywords ( collection_id ... | Add a library to the database |
43,106 | def add_folder ( self , dirname , watch = True ) : ignore_file = os . path . join ( dirname , ".rfhubignore" ) exclude_patterns = [ ] try : with open ( ignore_file , "r" ) as f : exclude_patterns = [ ] for line in f . readlines ( ) : line = line . strip ( ) if ( re . match ( r'^\s*#' , line ) ) : continue if len ( line... | Recursively add all files in a folder to the database |
43,107 | def add_installed_libraries ( self , extra_libs = [ "Selenium2Library" , "SudsLibrary" , "RequestsLibrary" ] ) : libdir = os . path . dirname ( robot . libraries . __file__ ) loaded = [ ] for filename in os . listdir ( libdir ) : if filename . endswith ( ".py" ) or filename . endswith ( ".pyc" ) : libname , ext = os . ... | Add any installed libraries that we can find |
43,108 | def get_collection ( self , collection_id ) : sql = cursor = self . _execute ( sql , ( collection_id , collection_id ) ) sql_result = cursor . fetchone ( ) return { "collection_id" : sql_result [ 0 ] , "type" : sql_result [ 1 ] , "name" : sql_result [ 2 ] , "path" : sql_result [ 3 ] , "doc" : sql_result [ 4 ] , "versio... | Get a specific collection |
43,109 | def get_keyword ( self , collection_id , name ) : sql = cursor = self . _execute ( sql , ( collection_id , name ) ) row = cursor . fetchone ( ) if row is not None : return { "name" : row [ 0 ] , "args" : json . loads ( row [ 1 ] ) , "doc" : row [ 2 ] , "collection_id" : collection_id } return { } | Get a specific keyword from a library |
43,110 | def _looks_like_libdoc_file ( self , name ) : if name . lower ( ) . endswith ( ".xml" ) : with open ( name , "r" ) as f : data = f . read ( 200 ) index = data . lower ( ) . find ( "<keywordspec " ) if index > 0 : return True return False | Return true if an xml file looks like a libdoc file |
43,111 | def _looks_like_resource_file ( self , name ) : if ( re . search ( r'__init__.(txt|robot|html|tsv)$' , name ) ) : return False found_keyword_table = False if ( name . lower ( ) . endswith ( ".robot" ) or name . lower ( ) . endswith ( ".txt" ) or name . lower ( ) . endswith ( ".tsv" ) ) : with open ( name , "r" ) as f :... | Return true if the file has a keyword table but not a testcase table |
43,112 | def _should_ignore ( self , name ) : _name = name . lower ( ) return ( _name . startswith ( "deprecated" ) or _name . startswith ( "_" ) or _name in ( "remote" , "reserved" , "dialogs_py" , "dialogs_ipy" , "dialogs_jy" ) ) | Return True if a given library name should be ignored |
43,113 | def _execute ( self , * args ) : cursor = self . db . cursor ( ) cursor . execute ( * args ) return cursor | Execute an SQL query |
43,114 | def _glob_to_sql ( self , string ) : table = ( ( r'\\' , chr ( 1 ) ) , ( r'\*' , chr ( 2 ) ) , ( r'\?' , chr ( 3 ) ) , ( r'%' , r'\%' ) , ( r'?' , '_' ) , ( r'*' , '%' ) , ( chr ( 1 ) , r'\\' ) , ( chr ( 2 ) , r'\*' ) , ( chr ( 3 ) , r'\?' ) ) for ( a , b ) in table : string = string . replace ( a , b ) string = string... | Convert glob - like wildcards to SQL wildcards |
43,115 | def doc ( ) : kwdb = current_app . kwdb libraries = get_collections ( kwdb , libtype = "library" ) resource_files = get_collections ( kwdb , libtype = "resource" ) hierarchy = get_navpanel_data ( kwdb ) return flask . render_template ( "home.html" , data = { "libraries" : libraries , "version" : __version__ , "libdoc" ... | Show a list of libraries along with the nav panel on the left |
43,116 | def index ( ) : kwdb = current_app . kwdb libraries = get_collections ( kwdb , libtype = "library" ) resource_files = get_collections ( kwdb , libtype = "resource" ) return flask . render_template ( "libraryNames.html" , data = { "libraries" : libraries , "version" : __version__ , "resource_files" : resource_files } ) | Show a list of available libraries and resource files |
43,117 | def search ( ) : pattern = flask . request . args . get ( 'pattern' , "*" ) . strip ( ) . lower ( ) collections = [ c [ "name" ] . lower ( ) for c in current_app . kwdb . get_collections ( ) ] words = [ ] filters = [ ] if pattern . startswith ( "name:" ) : pattern = pattern [ 5 : ] . strip ( ) mode = "name" else : mode... | Show all keywords that match a pattern |
43,118 | def get_collections ( kwdb , libtype = "*" ) : collections = kwdb . get_collections ( libtype = libtype ) for result in collections : url = flask . url_for ( ".doc_for_library" , collection_id = result [ "collection_id" ] ) result [ "url" ] = url return collections | Get list of collections from kwdb then add urls necessary for hyperlinks |
43,119 | def get_navpanel_data ( kwdb ) : data = kwdb . get_keyword_hierarchy ( ) for library in data : library [ "url" ] = flask . url_for ( ".doc_for_library" , collection_id = library [ "collection_id" ] ) for keyword in library [ "keywords" ] : url = flask . url_for ( ".doc_for_library" , collection_id = library [ "collecti... | Get navpanel data from kwdb and add urls necessary for hyperlinks |
43,120 | def doc_to_html ( doc , doc_format = "ROBOT" ) : from robot . libdocpkg . htmlwriter import DocToHtml return DocToHtml ( doc_format ) ( doc ) | Convert documentation to HTML |
43,121 | def start ( self ) : if self . args . debug : self . app . run ( port = self . args . port , debug = self . args . debug , host = self . args . interface ) else : root = "http://%s:%s" % ( self . args . interface , self . args . port ) print ( "tornado web server running on " + root ) self . shutdown_requested = False ... | Start the app |
43,122 | def check_shutdown_flag ( self ) : if self . shutdown_requested : tornado . ioloop . IOLoop . instance ( ) . stop ( ) print ( "web server stopped." ) | Shutdown the server if the flag has been set |
43,123 | def coords ( obj ) : if 'features' in obj : for f in obj [ 'features' ] : for c in coords ( f ) : yield c else : if isinstance ( obj , ( tuple , list ) ) : coordinates = obj elif 'geometry' in obj : coordinates = obj [ 'geometry' ] [ 'coordinates' ] else : coordinates = obj . get ( 'coordinates' , obj ) for e in coordi... | Yields the coordinates from a Feature or Geometry . |
43,124 | def map_tuples ( func , obj ) : if obj [ 'type' ] == 'Point' : coordinates = tuple ( func ( obj [ 'coordinates' ] ) ) elif obj [ 'type' ] in [ 'LineString' , 'MultiPoint' ] : coordinates = [ tuple ( func ( c ) ) for c in obj [ 'coordinates' ] ] elif obj [ 'type' ] in [ 'MultiLineString' , 'Polygon' ] : coordinates = [ ... | Returns the mapped coordinates from a Geometry after applying the provided function to each coordinate . |
43,125 | def map_geometries ( func , obj ) : simple_types = [ 'Point' , 'LineString' , 'MultiPoint' , 'MultiLineString' , 'Polygon' , 'MultiPolygon' , ] if obj [ 'type' ] in simple_types : return func ( obj ) elif obj [ 'type' ] == 'GeometryCollection' : geoms = [ func ( geom ) if geom else None for geom in obj [ 'geometries' ]... | Returns the result of passing every geometry in the given geojson object through func . |
43,126 | def to_instance ( cls , ob , default = None , strict = False ) : if ob is None and default is not None : instance = default ( ) elif isinstance ( ob , GeoJSON ) : instance = ob else : mapping = to_mapping ( ob ) d = { } for k in mapping : d [ k ] = mapping [ k ] try : type_ = d . pop ( "type" ) try : type_ = str ( type... | Encode a GeoJSON dict into an GeoJSON object . Assumes the caller knows that the dict should satisfy a GeoJSON type . |
43,127 | def check_list_errors ( self , checkFunc , lst ) : results = ( checkFunc ( i ) for i in lst ) return [ err for err in results if err ] | Validation helper function . |
43,128 | def run_only_once ( self , keyword ) : lock_name = 'pabot_run_only_once_%s' % keyword try : self . acquire_lock ( lock_name ) passed = self . get_parallel_value_for_key ( lock_name ) if passed != '' : if passed == 'FAILED' : raise AssertionError ( 'Keyword failed in other process' ) return BuiltIn ( ) . run_keyword ( k... | Runs a keyword only once in one of the parallel processes . As the keyword will be called only in one process and the return value could basically be anything . The Run Only Once can t return the actual return value . If the keyword fails Run Only Once fails . Others executing Run Only Once wait before going through th... |
43,129 | def set_parallel_value_for_key ( self , key , value ) : if self . _remotelib : self . _remotelib . run_keyword ( 'set_parallel_value_for_key' , [ key , value ] , { } ) else : _PabotLib . set_parallel_value_for_key ( self , key , value ) | Set a globally available key and value that can be accessed from all the pabot processes . |
43,130 | def get_parallel_value_for_key ( self , key ) : if self . _remotelib : return self . _remotelib . run_keyword ( 'get_parallel_value_for_key' , [ key ] , { } ) return _PabotLib . get_parallel_value_for_key ( self , key ) | Get the value for a key . If there is no value for the key then empty string is returned . |
43,131 | def acquire_lock ( self , name ) : if self . _remotelib : try : while not self . _remotelib . run_keyword ( 'acquire_lock' , [ name , self . _my_id ] , { } ) : time . sleep ( 0.1 ) logger . debug ( 'waiting for lock to release' ) return True except RuntimeError : logger . warn ( 'no connection' ) self . __remotelib = N... | Wait for a lock with name . This will prevent other processes from acquiring the lock with the name while it is held . Thus they will wait in the position where they are acquiring the lock until the process that has it releases it . |
43,132 | def release_lock ( self , name ) : if self . _remotelib : self . _remotelib . run_keyword ( 'release_lock' , [ name , self . _my_id ] , { } ) else : _PabotLib . release_lock ( self , name , self . _my_id ) | Release a lock with name . This will enable others to acquire the lock . |
43,133 | def release_locks ( self ) : if self . _remotelib : self . _remotelib . run_keyword ( 'release_locks' , [ self . _my_id ] , { } ) else : _PabotLib . release_locks ( self , self . _my_id ) | Release all locks called by instance . |
43,134 | def acquire_value_set ( self , * tags ) : setname = self . _acquire_value_set ( * tags ) if setname is None : raise ValueError ( "Could not aquire a value set" ) return setname | Reserve a set of values for this execution . No other process can reserve the same set of values while the set is reserved . Acquired value set needs to be released after use to allow other processes to access it . Add tags to limit the possible value sets that this returns . |
43,135 | def get_value_from_set ( self , key ) : key = key . lower ( ) if self . _remotelib : while True : value = self . _remotelib . run_keyword ( 'get_value_from_set' , [ key , self . _my_id ] , { } ) if value : return value time . sleep ( 0.1 ) logger . debug ( 'waiting for a value' ) else : return _PabotLib . get_value_fro... | Get a value from previously reserved value set . |
43,136 | def release_value_set ( self ) : if self . _remotelib : self . _remotelib . run_keyword ( 'release_value_set' , [ self . _my_id ] , { } ) else : _PabotLib . release_value_set ( self , self . _my_id ) | Release a reserved value set so that other executions can use it also . |
43,137 | def install_all_patches ( ) : from . import mysqldb from . import psycopg2 from . import strict_redis from . import sqlalchemy from . import tornado_http from . import urllib from . import urllib2 from . import requests mysqldb . install_patches ( ) psycopg2 . install_patches ( ) strict_redis . install_patches ( ) sqla... | A convenience method that installs all available hooks . |
43,138 | def install_patches ( patchers = 'all' ) : if patchers is None or patchers == 'all' : install_all_patches ( ) return if not _valid_args ( patchers ) : raise ValueError ( 'patchers argument must be None, "all", or a list' ) for patch_func_name in patchers : logging . info ( 'Loading client hook %s' , patch_func_name ) p... | Usually called from middleware to install client hooks specified in the client_hooks section of the configuration . |
43,139 | def install_client_interceptors ( client_interceptors = ( ) ) : if not _valid_args ( client_interceptors ) : raise ValueError ( 'client_interceptors argument must be a list' ) from . . http_client import ClientInterceptors for client_interceptor in client_interceptors : logging . info ( 'Loading client interceptor %s' ... | Install client interceptors for the patchers . |
43,140 | def _load_symbol ( name ) : module_name , key = name . rsplit ( '.' , 1 ) try : module = importlib . import_module ( module_name ) except ImportError as err : module_name , class_name = module_name . rsplit ( '.' , 1 ) module = importlib . import_module ( module_name ) cls = getattr ( module , class_name , None ) if cl... | Load a symbol by name . |
43,141 | def span_in_stack_context ( span ) : if not isinstance ( opentracing . tracer . scope_manager , TornadoScopeManager ) : raise RuntimeError ( 'scope_manager is not TornadoScopeManager' ) context = tracer_stack_context ( ) entered_context = _TracerEnteredStackContext ( context ) if span is None : return entered_context o... | Create Tornado s StackContext that stores the given span in the thread - local request context . This function is intended for use in Tornado applications based on IOLoop although will work fine in single - threaded apps like Flask albeit with more overhead . |
43,142 | def traced_function ( func = None , name = None , on_start = None , require_active_trace = False ) : if func is None : return functools . partial ( traced_function , name = name , on_start = on_start , require_active_trace = require_active_trace ) if name : operation_name = name else : operation_name = func . __name__ ... | A decorator that enables tracing of the wrapped function or Tornado co - routine provided there is a parent span already established . |
43,143 | def start_child_span ( operation_name , tracer = None , parent = None , tags = None ) : tracer = tracer or opentracing . tracer return tracer . start_span ( operation_name = operation_name , child_of = parent . context if parent else None , tags = tags ) | Start a new span as a child of parent_span . If parent_span is None start a new root span . |
43,144 | def before_request ( request , tracer = None ) : if tracer is None : tracer = opentracing . tracer tags_dict = { tags . SPAN_KIND : tags . SPAN_KIND_RPC_SERVER , tags . HTTP_URL : request . full_url , } remote_ip = request . remote_ip if remote_ip : tags_dict [ tags . PEER_HOST_IPV4 ] = remote_ip caller_name = request ... | Attempts to extract a tracing span from incoming request . If no tracing context is passed in the headers or the data cannot be parsed a new root span is started . |
43,145 | def _parse_wsgi_headers ( wsgi_environ ) : prefix = 'HTTP_' p_len = len ( prefix ) headers = { key [ p_len : ] . replace ( '_' , '-' ) . lower ( ) : val for ( key , val ) in wsgi_environ . items ( ) if key . startswith ( prefix ) } return headers | HTTP headers are presented in WSGI environment with HTTP_ prefix . This method finds those headers removes the prefix converts underscores to dashes and converts to lower case . |
43,146 | def append ( cls , interceptor ) : cls . _check ( interceptor ) cls . _interceptors . append ( interceptor ) | Add interceptor to the end of the internal list . |
43,147 | def insert ( cls , index , interceptor ) : cls . _check ( interceptor ) cls . _interceptors . insert ( index , interceptor ) | Add interceptor to the given index in the internal list . |
43,148 | def singleton ( func ) : @ functools . wraps ( func ) def wrapper ( * args , ** kwargs ) : if wrapper . __call_state__ == CALLED : return ret = func ( * args , ** kwargs ) wrapper . __call_state__ = CALLED return ret def reset ( ) : wrapper . __call_state__ = NOT_CALLED wrapper . reset = reset reset ( ) wrapper . __ori... | This decorator allows you to make sure that a function is called once and only once . Note that recursive functions will still work . |
43,149 | def smooth_image ( image , sigma , sigma_in_physical_coordinates = True , FWHM = False , max_kernel_width = 32 ) : if image . components == 1 : return _smooth_image_helper ( image , sigma , sigma_in_physical_coordinates , FWHM , max_kernel_width ) else : imagelist = utils . split_channels ( image ) newimages = [ ] for ... | Smooth an image |
43,150 | def build_template ( initial_template = None , image_list = None , iterations = 3 , gradient_step = 0.2 , ** kwargs ) : wt = 1.0 / len ( image_list ) if initial_template is None : initial_template = image_list [ 0 ] * 0 for i in range ( len ( image_list ) ) : initial_template = initial_template + image_list [ i ] * wt ... | Estimate an optimal template from an input image_list |
43,151 | def resample_image ( image , resample_params , use_voxels = False , interp_type = 1 ) : if image . components == 1 : inimage = image . clone ( 'float' ) outimage = image . clone ( 'float' ) rsampar = 'x' . join ( [ str ( rp ) for rp in resample_params ] ) args = [ image . dimension , inimage , outimage , rsampar , int ... | Resample image by spacing or number of voxels with various interpolators . Works with multi - channel images . |
43,152 | def apply_ants_transform ( transform , data , data_type = "point" , reference = None , ** kwargs ) : return transform . apply ( data , data_type , reference , ** kwargs ) | Apply ANTsTransform to data |
43,153 | def compose_ants_transforms ( transform_list ) : precision = transform_list [ 0 ] . precision dimension = transform_list [ 0 ] . dimension for tx in transform_list : if precision != tx . precision : raise ValueError ( 'All transforms must have the same precision' ) if dimension != tx . dimension : raise ValueError ( 'A... | Compose multiple ANTsTransform s together |
43,154 | def transform_index_to_physical_point ( image , index ) : if not isinstance ( image , iio . ANTsImage ) : raise ValueError ( 'image must be ANTsImage type' ) if isinstance ( index , np . ndarray ) : index = index . tolist ( ) if not isinstance ( index , ( tuple , list ) ) : raise ValueError ( 'index must be tuple or li... | Get spatial point from index of an image . |
43,155 | def invert ( self ) : libfn = utils . get_lib_fn ( 'inverseTransform%s' % ( self . _libsuffix ) ) inv_tx_ptr = libfn ( self . pointer ) new_tx = ANTsTransform ( precision = self . precision , dimension = self . dimension , transform_type = self . transform_type , pointer = inv_tx_ptr ) return new_tx | Invert the transform |
43,156 | def apply ( self , data , data_type = 'point' , reference = None , ** kwargs ) : if data_type == 'point' : return self . apply_to_point ( data ) elif data_type == 'vector' : return self . apply_to_vector ( data ) elif data_type == 'image' : return self . apply_to_image ( data , reference , ** kwargs ) | Apply transform to data |
43,157 | def apply_to_point ( self , point ) : libfn = utils . get_lib_fn ( 'transformPoint%s' % ( self . _libsuffix ) ) return tuple ( libfn ( self . pointer , point ) ) | Apply transform to a point |
43,158 | def apply_to_vector ( self , vector ) : if isinstance ( vector , np . ndarray ) : vector = vector . tolist ( ) libfn = utils . get_lib_fn ( 'transformVector%s' % ( self . _libsuffix ) ) return np . asarray ( libfn ( self . pointer , vector ) ) | Apply transform to a vector |
43,159 | def plot_hist ( image , threshold = 0. , fit_line = False , normfreq = True , title = None , grid = True , xlabel = None , ylabel = None , facecolor = 'green' , alpha = 0.75 ) : img_arr = image . numpy ( ) . flatten ( ) img_arr = img_arr [ np . abs ( img_arr ) > threshold ] if normfreq != False : normfreq = 1. if normf... | Plot a histogram from an ANTsImage |
43,160 | def morphology ( image , operation , radius , mtype = 'binary' , value = 1 , shape = 'ball' , radius_is_parametric = False , thickness = 1 , lines = 3 , include_center = False ) : if image . components > 1 : raise ValueError ( 'multichannel images not yet supported' ) _sflag_dict = { 'ball' : 1 , 'box' : 2 , 'cross' : ... | Apply morphological operations to an image |
43,161 | def rgb_to_vector ( image ) : if image . pixeltype != 'unsigned char' : image = image . clone ( 'unsigned char' ) idim = image . dimension libfn = utils . get_lib_fn ( 'RgbToVector%i' % idim ) new_ptr = libfn ( image . pointer ) new_img = iio . ANTsImage ( pixeltype = image . pixeltype , dimension = image . dimension ,... | Convert an RGB ANTsImage to a Vector ANTsImage |
43,162 | def vector_to_rgb ( image ) : if image . pixeltype != 'unsigned char' : image = image . clone ( 'unsigned char' ) idim = image . dimension libfn = utils . get_lib_fn ( 'VectorToRgb%i' % idim ) new_ptr = libfn ( image . pointer ) new_img = iio . ANTsImage ( pixeltype = image . pixeltype , dimension = image . dimension ,... | Convert an Vector ANTsImage to a RGB ANTsImage |
43,163 | def quantile ( image , q , nonzero = True ) : img_arr = image . numpy ( ) if isinstance ( q , ( list , tuple ) ) : q = [ qq * 100. if qq <= 1. else qq for qq in q ] if nonzero : img_arr = img_arr [ img_arr > 0 ] vals = [ np . percentile ( img_arr , qq ) for qq in q ] return tuple ( vals ) elif isinstance ( q , ( float ... | Get the quantile values from an ANTsImage |
43,164 | def bandpass_filter_matrix ( matrix , tr = 1 , lowf = 0.01 , highf = 0.1 , order = 3 ) : from scipy . signal import butter , filtfilt def butter_bandpass ( lowcut , highcut , fs , order ) : nyq = 0.5 * fs low = lowcut / nyq high = highcut / nyq b , a = butter ( order , [ low , high ] , btype = 'band' ) return b , a def... | Bandpass filter the input time series image |
43,165 | def compcor ( boldImage , ncompcor = 4 , quantile = 0.975 , mask = None , filter_type = False , degree = 2 ) : def compute_tSTD ( M , quantile , x = 0 , axis = 0 ) : stdM = np . std ( M , axis = axis ) stdM [ stdM == 0 ] = x stdM [ np . isnan ( stdM ) ] = x tt = round ( quantile * 100 ) threshold_std = np . percentile ... | Compute noise components from the input image |
43,166 | def n3_bias_field_correction ( image , downsample_factor = 3 ) : outimage = image . clone ( ) args = [ image . dimension , image , outimage , downsample_factor ] processed_args = pargs . _int_antsProcessArguments ( args ) libfn = utils . get_lib_fn ( 'N3BiasFieldCorrection' ) libfn ( processed_args ) return outimage | N3 Bias Field Correction |
43,167 | def n4_bias_field_correction ( image , mask = None , shrink_factor = 4 , convergence = { 'iters' : [ 50 , 50 , 50 , 50 ] , 'tol' : 1e-07 } , spline_param = 200 , verbose = False , weight_mask = None ) : if image . pixeltype != 'float' : image = image . clone ( 'float' ) iters = convergence [ 'iters' ] tol = convergence... | N4 Bias Field Correction |
43,168 | def abp_n4 ( image , intensity_truncation = ( 0.025 , 0.975 , 256 ) , mask = None , usen3 = False ) : if ( not isinstance ( intensity_truncation , ( list , tuple ) ) ) or ( len ( intensity_truncation ) != 3 ) : raise ValueError ( 'intensity_truncation must be list/tuple with 3 values' ) outimage = iMath ( image , 'Trun... | Truncate outlier intensities and bias correct with the N4 algorithm . |
43,169 | def image_mutual_information ( image1 , image2 ) : if ( image1 . pixeltype != 'float' ) or ( image2 . pixeltype != 'float' ) : raise ValueError ( 'Both images must have float pixeltype' ) if image1 . dimension != image2 . dimension : raise ValueError ( 'Both images must have same dimension' ) libfn = utils . get_lib_fn... | Compute mutual information between two ANTsImage types |
43,170 | def get_mask ( image , low_thresh = None , high_thresh = None , cleanup = 2 ) : cleanup = int ( cleanup ) if isinstance ( image , iio . ANTsImage ) : if image . pixeltype != 'float' : image = image . clone ( 'float' ) if low_thresh is None : low_thresh = image . mean ( ) if high_thresh is None : high_thresh = image . m... | Get a binary mask image from the given image after thresholding |
43,171 | def label_image_centroids ( image , physical = False , convex = True , verbose = False ) : d = image . shape if len ( d ) != 3 : raise ValueError ( 'image must be 3 dimensions' ) xcoords = np . asarray ( np . arange ( d [ 0 ] ) . tolist ( ) * ( d [ 1 ] * d [ 2 ] ) ) ycoords = np . asarray ( np . repeat ( np . arange ( ... | Converts a label image to coordinates summarizing their positions |
43,172 | def transform ( self , X , y = None ) : insuffix = X . _libsuffix multires_fn = utils . get_lib_fn ( 'multiResolutionAntsImage%s' % ( insuffix ) ) casted_ptrs = multires_fn ( X . pointer , self . levels ) imgs = [ ] for casted_ptr in casted_ptrs : img = iio . ANTsImage ( pixeltype = X . pixeltype , dimension = X . dime... | Generate a set of multi - resolution ANTsImage types |
43,173 | def transform ( self , X , y = None ) : insuffix = X . _libsuffix cast_fn = utils . get_lib_fn ( 'locallyBlurAntsImage%s' % ( insuffix ) ) casted_ptr = cast_fn ( X . pointer , self . iters , self . conductance ) return iio . ANTsImage ( pixeltype = X . pixeltype , dimension = X . dimension , components = X . components... | Locally blur an image by applying a gradient anisotropic diffusion filter . |
43,174 | def get_data ( name = None ) : if name is None : files = [ ] for fname in os . listdir ( data_path ) : if ( fname . endswith ( '.nii.gz' ) ) or ( fname . endswith ( '.jpg' ) or ( fname . endswith ( '.csv' ) ) ) : fname = os . path . join ( data_path , fname ) files . append ( fname ) return files else : datapath = None... | Get ANTsPy test data filename |
43,175 | def convolve_image ( image , kernel_image , crop = True ) : if not isinstance ( image , iio . ANTsImage ) : raise ValueError ( 'image must be ANTsImage type' ) if not isinstance ( kernel_image , iio . ANTsImage ) : raise ValueError ( 'kernel must be ANTsImage type' ) orig_ptype = image . pixeltype if image . pixeltype ... | Convolve one image with another |
43,176 | def ndimage_to_list ( image ) : inpixeltype = image . pixeltype dimension = image . dimension components = 1 imageShape = image . shape nSections = imageShape [ dimension - 1 ] subdimension = dimension - 1 suborigin = iio . get_origin ( image ) [ 0 : subdimension ] subspacing = iio . get_spacing ( image ) [ 0 : subdime... | Split a n dimensional ANTsImage into a list of n - 1 dimensional ANTsImages |
43,177 | def _int_antsProcessArguments ( args ) : p_args = [ ] if isinstance ( args , dict ) : for argname , argval in args . items ( ) : if '-MULTINAME-' in argname : argname = argname [ : argname . find ( '-MULTINAME-' ) ] if argval is not None : if len ( argname ) > 1 : p_args . append ( '--%s' % argname ) else : p_args . ap... | Needs to be better validated . |
43,178 | def initialize_eigenanatomy ( initmat , mask = None , initlabels = None , nreps = 1 , smoothing = 0 ) : if isinstance ( initmat , iio . ANTsImage ) : if mask is not None : selectvec = mask > 0 else : selectvec = initmat > 0 initmatvec = initmat [ selectvec ] if initlabels is None : ulabs = np . sort ( np . unique ( ini... | InitializeEigenanatomy is a helper function to initialize sparseDecom and sparseDecom2 . Can be used to estimate sparseness parameters per eigenvector . The user then only chooses nvecs and optional regularization parameters . |
43,179 | def eig_seg ( mask , img_list , apply_segmentation_to_images = False , cthresh = 0 , smooth = 1 ) : maskvox = mask > 0 maskseg = mask . clone ( ) maskseg [ maskvox ] = 0 if isinstance ( img_list , np . ndarray ) : mydata = img_list elif isinstance ( img_list , ( tuple , list ) ) : mydata = core . image_list_to_matrix (... | Segment a mask into regions based on the max value in an image list . At a given voxel the segmentation label will contain the index to the image that has the largest value . If the 3rd image has the greatest value the segmentation label will be 3 at that voxel . |
43,180 | def label_stats ( image , label_image ) : image_float = image . clone ( 'float' ) label_image_int = label_image . clone ( 'unsigned int' ) libfn = utils . get_lib_fn ( 'labelStats%iD' % image . dimension ) df = libfn ( image_float . pointer , label_image_int . pointer ) return pd . DataFrame ( df ) | Get label statistics from image |
43,181 | def spacing ( self ) : libfn = utils . get_lib_fn ( 'getSpacing%s' % self . _libsuffix ) return libfn ( self . pointer ) | Get image spacing |
43,182 | def set_spacing ( self , new_spacing ) : if not isinstance ( new_spacing , ( tuple , list ) ) : raise ValueError ( 'arg must be tuple or list' ) if len ( new_spacing ) != self . dimension : raise ValueError ( 'must give a spacing value for each dimension (%i)' % self . dimension ) libfn = utils . get_lib_fn ( 'setSpaci... | Set image spacing |
43,183 | def origin ( self ) : libfn = utils . get_lib_fn ( 'getOrigin%s' % self . _libsuffix ) return libfn ( self . pointer ) | Get image origin |
43,184 | def set_origin ( self , new_origin ) : if not isinstance ( new_origin , ( tuple , list ) ) : raise ValueError ( 'arg must be tuple or list' ) if len ( new_origin ) != self . dimension : raise ValueError ( 'must give a origin value for each dimension (%i)' % self . dimension ) libfn = utils . get_lib_fn ( 'setOrigin%s' ... | Set image origin |
43,185 | def direction ( self ) : libfn = utils . get_lib_fn ( 'getDirection%s' % self . _libsuffix ) return libfn ( self . pointer ) | Get image direction |
43,186 | def set_direction ( self , new_direction ) : if isinstance ( new_direction , ( tuple , list ) ) : new_direction = np . asarray ( new_direction ) if not isinstance ( new_direction , np . ndarray ) : raise ValueError ( 'arg must be np.ndarray or tuple or list' ) if len ( new_direction ) != self . dimension : raise ValueE... | Set image direction |
43,187 | def astype ( self , dtype ) : if dtype not in _supported_dtypes : raise ValueError ( 'Datatype %s not supported. Supported types are %s' % ( dtype , _supported_dtypes ) ) pixeltype = _npy_to_itk_map [ dtype ] return self . clone ( pixeltype ) | Cast & clone an ANTsImage to a given numpy datatype . |
43,188 | def new_image_like ( self , data ) : if not isinstance ( data , np . ndarray ) : raise ValueError ( 'data must be a numpy array' ) if not self . has_components : if data . shape != self . shape : raise ValueError ( 'given array shape (%s) and image array shape (%s) do not match' % ( data . shape , self . shape ) ) else... | Create a new ANTsImage with the same header information but with a new image array . |
43,189 | def to_file ( self , filename ) : filename = os . path . expanduser ( filename ) libfn = utils . get_lib_fn ( 'toFile%s' % self . _libsuffix ) libfn ( self . pointer , filename ) | Write the ANTsImage to file |
43,190 | def apply ( self , fn ) : this_array = self . numpy ( ) new_array = fn ( this_array ) return self . new_image_like ( new_array ) | Apply an arbitrary function to ANTsImage . |
43,191 | def sum ( self , axis = None , keepdims = False ) : return self . numpy ( ) . sum ( axis = axis , keepdims = keepdims ) | Return sum along specified axis |
43,192 | def range ( self , axis = None ) : return ( self . min ( axis = axis ) , self . max ( axis = axis ) ) | Return range tuple along specified axis |
43,193 | def argrange ( self , axis = None ) : amin = self . argmin ( axis = axis ) amax = self . argmax ( axis = axis ) if axis is None : return ( amin , amax ) else : return np . stack ( [ amin , amax ] ) . T | Return argrange along specified axis |
43,194 | def unique ( self , sort = False ) : unique_vals = np . unique ( self . numpy ( ) ) if sort : unique_vals = np . sort ( unique_vals ) return unique_vals | Return unique set of values in image |
43,195 | def uniquekeys ( self , metakey = None ) : if metakey is None : return self . _uniquekeys else : if metakey not in self . metakeys ( ) : raise ValueError ( 'metakey %s does not exist' % metakey ) return self . _uniquekeys [ metakey ] | Get keys for a given metakey |
43,196 | def label_clusters ( image , min_cluster_size = 50 , min_thresh = 1e-6 , max_thresh = 1 , fully_connected = False ) : dim = image . dimension clust = threshold_image ( image , min_thresh , max_thresh ) temp = int ( fully_connected ) args = [ dim , clust , clust , min_cluster_size , temp ] processed_args = _int_antsProc... | This will give a unique ID to each connected component 1 through N of size > min_cluster_size |
43,197 | def make_points_image ( pts , mask , radius = 5 ) : powers_lblimg = mask * 0 npts = len ( pts ) dim = mask . dimension if pts . shape [ 1 ] != dim : raise ValueError ( 'points dimensionality should match that of images' ) for r in range ( npts ) : pt = pts [ r , : ] idx = tio . transform_physical_point_to_index ( mask ... | Create label image from physical space points |
43,198 | def weingarten_image_curvature ( image , sigma = 1.0 , opt = 'mean' ) : if image . dimension not in { 2 , 3 } : raise ValueError ( 'image must be 2D or 3D' ) if image . dimension == 2 : d = image . shape temp = np . zeros ( list ( d ) + [ 10 ] ) for k in range ( 1 , 7 ) : voxvals = image [ : d [ 0 ] , : d [ 1 ] ] temp ... | Uses the weingarten map to estimate image mean or gaussian curvature |
43,199 | def from_numpy ( data , origin = None , spacing = None , direction = None , has_components = False , is_rgb = False ) : data = data . astype ( 'float32' ) if data . dtype . name == 'float64' else data img = _from_numpy ( data . T . copy ( ) , origin , spacing , direction , has_components , is_rgb ) return img | Create an ANTsImage object from a numpy array |
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