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def add_segment ( self , name , model_expression = None , ytransform = 'default' ) : if not model_expression : if self . default_model_expr is None : raise ValueError ( 'No default model available, ' 'you must supply a model experssion.' ) model_expression = self . default_model_expr if ytransform == 'default' : ytrans...
Add a new segment with its own model expression and ytransform .
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def fit ( self , data , debug = False ) : data = util . apply_filter_query ( data , self . fit_filters ) unique = data [ self . segmentation_col ] . unique ( ) value_counts = data [ self . segmentation_col ] . value_counts ( ) gone = set ( self . _group . models ) - set ( unique ) for g in gone : del self . _group . mo...
Fit each segment . Segments that have not already been explicitly added will be automatically added with default model and ytransform .
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def columns_used ( self ) : return list ( tz . unique ( tz . concatv ( util . columns_in_filters ( self . fit_filters ) , util . columns_in_filters ( self . predict_filters ) , util . columns_in_formula ( self . default_model_expr ) , self . _group . columns_used ( ) , [ self . segmentation_col ] ) ) )
Returns all the columns used across all models in the group for filtering and in the model expression .
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def find_movers ( choosers , rates , rate_column ) : logger . debug ( 'start: find movers for relocation' ) relocation_rates = pd . Series ( np . zeros ( len ( choosers ) ) , index = choosers . index ) for _ , row in rates . iterrows ( ) : indexes = util . filter_table ( choosers , row , ignore = { rate_column } ) . in...
Returns an array of the indexes of the choosers that are slated to move .
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def _calculate_adjustment ( lcm , choosers , alternatives , alt_segmenter , clip_change_low , clip_change_high , multiplier_func = None ) : logger . debug ( 'start: calculate supply and demand price adjustment ratio' ) demand = lcm . summed_probabilities ( choosers , alternatives ) demand = demand . groupby ( alt_segme...
Calculate adjustments to prices to compensate for supply and demand effects .
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def supply_and_demand ( lcm , choosers , alternatives , alt_segmenter , price_col , base_multiplier = None , clip_change_low = 0.75 , clip_change_high = 1.25 , iterations = 5 , multiplier_func = None ) : logger . debug ( 'start: calculating supply and demand price adjustment' ) alternatives = alternatives . copy ( ) if...
Adjust real estate prices to compensate for supply and demand effects .
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def _max_form ( f , colname ) : df = f . stack ( level = 0 ) [ [ colname ] ] . stack ( ) . unstack ( level = 1 ) . reset_index ( level = 1 , drop = True ) return df . idxmax ( axis = 1 )
Assumes dataframe with hierarchical columns with first index equal to the use and second index equal to the attribute .
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def keep_form_with_max_profit ( self , forms = None ) : f = self . feasibility if forms is not None : f = f [ forms ] if len ( f ) > 0 : mu = self . _max_form ( f , "max_profit" ) indexes = [ tuple ( x ) for x in mu . reset_index ( ) . values ] else : indexes = [ ] df = f . stack ( level = 0 ) . loc [ indexes ] df . in...
This converts the dataframe which shows all profitable forms to the form with the greatest profit so that more profitable forms outcompete less profitable forms .
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def compute_units_to_build ( num_agents , num_units , target_vacancy ) : print ( "Number of agents: {:,}" . format ( num_agents ) ) print ( "Number of agent spaces: {:,}" . format ( int ( num_units ) ) ) assert target_vacancy < 1.0 target_units = int ( max ( num_agents / ( 1 - target_vacancy ) - num_units , 0 ) ) print...
Compute number of units to build to match target vacancy .
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def pick ( self , form , target_units , parcel_size , ave_unit_size , current_units , max_parcel_size = 200000 , min_unit_size = 400 , drop_after_build = True , residential = True , bldg_sqft_per_job = 400.0 , profit_to_prob_func = None ) : if len ( self . feasibility ) == 0 : return if form is None : df = self . feasi...
Choose the buildings from the list that are feasible to build in order to match the specified demand .
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def _analyze_root_causes ( self ) : causes = { } for a in self . anomalies : try : causes [ a ] = self . correlations [ a ] [ 0 ] except IndexError : raise exceptions . InvalidDataFormat ( 'luminol.luminol: dict correlations contains empty list.' ) self . causes = causes
Conduct root cause analysis . The first metric of the list is taken as the root cause right now .
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def _sanity_check ( self ) : if len ( self . time_series_a ) < 2 or len ( self . time_series_b ) < 2 : raise exceptions . NotEnoughDataPoints ( 'luminol.Correlator: Too few data points!' )
Check if the time series have more than two data points .
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def _correlate ( self ) : a = self . algorithm ( ** self . algorithm_params ) self . correlation_result = a . run ( )
Run correlation algorithm .
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def _analyze ( self ) : output = defaultdict ( list ) output_by_name = defaultdict ( list ) scores = self . anomaly_detector . get_all_scores ( ) if self . anomalies : for anomaly in self . anomalies : metrix_scores = scores start_t , end_t = anomaly . get_time_window ( ) t = anomaly . exact_timestamp room = ( end_t - ...
Analyzes if a matrix has anomalies . If any anomaly is found determine if the matrix correlates with any other matrixes . To be implemented .
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def _set_scores ( self ) : anom_scores_ema = self . exp_avg_detector . run ( ) anom_scores_deri = self . derivative_detector . run ( ) anom_scores = { } for timestamp in anom_scores_ema . timestamps : anom_scores [ timestamp ] = max ( anom_scores_ema [ timestamp ] , anom_scores_ema [ timestamp ] * DEFAULT_DETECTOR_EMA_...
Set anomaly scores using a weighted sum .
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def _compute_derivatives ( self ) : derivatives = [ ] for i , ( timestamp , value ) in enumerate ( self . time_series_items ) : if i > 0 : pre_item = self . time_series_items [ i - 1 ] pre_timestamp = pre_item [ 0 ] pre_value = pre_item [ 1 ] td = timestamp - pre_timestamp derivative = ( value - pre_value ) / td if td ...
Compute derivatives of the time series .
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def _sanity_check ( self ) : windows = self . lag_window_size + self . future_window_size if ( not self . lag_window_size or not self . future_window_size or self . time_series_length < windows or windows < DEFAULT_BITMAP_MINIMAL_POINTS_IN_WINDOWS ) : raise exceptions . NotEnoughDataPoints if self . lag_window_size > D...
Check if there are enough data points .
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def _generate_SAX ( self ) : sections = { } self . value_min = self . time_series . min ( ) self . value_max = self . time_series . max ( ) section_height = ( self . value_max - self . value_min ) / self . precision for section_number in range ( self . precision ) : sections [ section_number ] = self . value_min + sect...
Generate SAX representation for all values of the time series .
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def _set_scores ( self ) : anom_scores = { } self . _generate_SAX ( ) self . _construct_all_SAX_chunk_dict ( ) length = self . time_series_length lws = self . lag_window_size fws = self . future_window_size for i , timestamp in enumerate ( self . time_series . timestamps ) : if i < lws or i > length - fws : anom_scores...
Compute anomaly scores for the time series by sliding both lagging window and future window .
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def _detect_correlation ( self ) : correlations = [ ] shifted_correlations = [ ] self . time_series_a . normalize ( ) self . time_series_b . normalize ( ) a , b = self . time_series_a . align ( self . time_series_b ) a_values , b_values = a . values , b . values a_avg , b_avg = a . average ( ) , b . average ( ) a_stdev...
Detect correlation by computing correlation coefficients for all allowed shift steps then take the maximum .
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def _compute_anom_data_using_window ( self ) : anom_scores = { } values = self . time_series . values stdev = numpy . std ( values ) for i , ( timestamp , value ) in enumerate ( self . time_series_items ) : if i < self . lag_window_size : anom_score = self . _compute_anom_score ( values [ : i + 1 ] , value ) else : ano...
Compute anomaly scores using a lagging window .
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def _compute_anom_data_decay_all ( self ) : anom_scores = { } values = self . time_series . values ema = utils . compute_ema ( self . smoothing_factor , values ) stdev = numpy . std ( values ) for i , ( timestamp , value ) in enumerate ( self . time_series_items ) : anom_score = abs ( ( value - ema [ i ] ) / stdev ) if...
Compute anomaly scores using a lagging window covering all the data points before .
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def _generic_binary_op ( self , other , op ) : output = { } if isinstance ( other , TimeSeries ) : for key , value in self . items ( ) : if key in other : try : result = op ( value , other [ key ] ) if result is NotImplemented : other_type = type ( other [ key ] ) other_op = vars ( other_type ) . get ( op . __name__ ) ...
Perform the method operation specified in the op parameter on the values within the instance s time series values and either another time series or a constant number value .
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def _get_value_type ( self , other ) : if self . values : return type ( self . values [ 0 ] ) elif isinstance ( other , TimeSeries ) and other . values : return type ( other . values [ 0 ] ) else : raise ValueError ( 'Cannot perform arithmetic on empty time series.' )
Get the object type of the value within the values portion of the time series .
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def smooth ( self , smoothing_factor ) : forward_smooth = { } backward_smooth = { } output = { } if self : pre = self . values [ 0 ] next = self . values [ - 1 ] for key , value in self . items ( ) : forward_smooth [ key ] = smoothing_factor * pre + ( 1 - smoothing_factor ) * value pre = forward_smooth [ key ] for key ...
return a new time series which is a exponential smoothed version of the original data series . soomth forward once backward once and then take the average .
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def add_offset ( self , offset ) : self . timestamps = [ ts + offset for ts in self . timestamps ]
Return a new time series with all timestamps incremented by some offset .
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def normalize ( self ) : maximum = self . max ( ) if maximum : self . values = [ value / maximum for value in self . values ]
Return a new time series with all values normalized to 0 to 1 .
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def crop ( self , start_timestamp , end_timestamp ) : output = { } for key , value in self . items ( ) : if key >= start_timestamp and key <= end_timestamp : output [ key ] = value if output : return TimeSeries ( output ) else : raise ValueError ( 'TimeSeries data was empty or invalid.' )
Return a new TimeSeries object contains all the timstamps and values within the specified range .
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def average ( self , default = None ) : return numpy . asscalar ( numpy . average ( self . values ) ) if self . values else default
Calculate the average value over the time series .
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def median ( self , default = None ) : return numpy . asscalar ( numpy . median ( self . values ) ) if self . values else default
Calculate the median value over the time series .
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def max ( self , default = None ) : return numpy . asscalar ( numpy . max ( self . values ) ) if self . values else default
Calculate the maximum value over the time series .
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def min ( self , default = None ) : return numpy . asscalar ( numpy . min ( self . values ) ) if self . values else default
Calculate the minimum value over the time series .
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def percentile ( self , n , default = None ) : return numpy . asscalar ( numpy . percentile ( self . values , n ) ) if self . values else default
Calculate the Nth Percentile value over the time series .
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def stdev ( self , default = None ) : return numpy . asscalar ( numpy . std ( self . values ) ) if self . values else default
Calculate the standard deviation of the time series .
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def sum ( self , default = None ) : return numpy . asscalar ( numpy . sum ( self . values ) ) if self . values else default
Calculate the sum of all the values in the times series .
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def _detect_anomalies ( self ) : anom_scores = self . anom_scores max_anom_score = anom_scores . max ( ) anomalies = [ ] if max_anom_score : threshold = self . threshold or max_anom_score * self . score_percent_threshold intervals = [ ] start , end = None , None for timestamp , value in anom_scores . iteritems ( ) : if...
Detect anomalies using a threshold on anomaly scores .
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def handle_response ( response ) : if response . status_code < 400 : return cls = _status_to_exception_type . get ( response . status_code , HttpError ) kwargs = { 'code' : response . status_code , 'method' : response . request . method , 'url' : response . request . url , 'details' : response . text , } if response . ...
Given a requests . Response object throw the appropriate exception if applicable .
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def create ( self , data , ** kwargs ) : self . client . post ( self . url , data = data )
Create classifitions for specific entity
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def create ( self , ** kwargs ) : raise exceptions . MethodNotImplemented ( method = self . create , url = self . url , details = 'GUID cannot be duplicated, to create a new GUID use the relationship resource' )
Raise error since guid cannot be duplicated
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def normalize_underscore_case ( name ) : normalized = name . lower ( ) normalized = re . sub ( r'_(\w)' , lambda match : ' ' + match . group ( 1 ) . upper ( ) , normalized ) return normalized [ 0 ] . upper ( ) + normalized [ 1 : ]
Normalize an underscore - separated descriptor to something more readable .
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def normalize_camel_case ( name ) : normalized = re . sub ( '([a-z])([A-Z])' , lambda match : ' ' . join ( [ match . group ( 1 ) , match . group ( 2 ) ] ) , name ) return normalized [ 0 ] . upper ( ) + normalized [ 1 : ]
Normalize a camelCase descriptor to something more readable .
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def version_tuple ( version ) : if isinstance ( version , str ) : return tuple ( int ( x ) for x in version . split ( '.' ) ) elif isinstance ( version , tuple ) : return version else : raise ValueError ( "Invalid version: %s" % version )
Convert a version string or tuple to a tuple .
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def version_str ( version ) : if isinstance ( version , str ) : return version elif isinstance ( version , tuple ) : return '.' . join ( [ str ( int ( x ) ) for x in version ] ) else : raise ValueError ( "Invalid version: %s" % version )
Convert a version tuple or string to a string .
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def generate_http_basic_token ( username , password ) : token = base64 . b64encode ( '{}:{}' . format ( username , password ) . encode ( 'utf-8' ) ) . decode ( 'utf-8' ) return token
Generates a HTTP basic token from username and password
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def identifier ( self ) : if self . primary_key not in self . _data : return 'Unknown' return str ( self . _data [ self . primary_key ] )
These models have server - generated identifiers .
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def url ( self ) : if self . parent is None : pieces = [ self . client . base_url , 'api' , 'atlas' , 'v2' ] else : pieces = [ self . parent . url ] pieces . append ( self . model_class . path ) return '/' . join ( pieces )
The url for this collection .
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def inflate ( self ) : if not self . _is_inflated : self . check_version ( ) for k , v in self . _filter . items ( ) : if '[' in v : self . _filter [ k ] = ast . literal_eval ( v ) self . load ( self . client . get ( self . url , params = self . _filter ) ) self . _is_inflated = True return self
Load the collection from the server if necessary .
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def load ( self , response ) : self . _models = [ ] if isinstance ( response , dict ) : for key in response . keys ( ) : model = self . model_class ( self , href = '' ) model . load ( response [ key ] ) self . _models . append ( model ) else : for item in response : model = self . model_class ( self , href = item . get...
Parse the GET response for the collection .
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def create ( self , * args , ** kwargs ) : href = self . url if len ( args ) == 1 : kwargs [ self . model_class . primary_key ] = args [ 0 ] href = '/' . join ( [ href , args [ 0 ] ] ) model = self . model_class ( self , href = href . replace ( 'classifications/' , 'classification/' ) , data = kwargs ) model . create (...
Add a resource to this collection .
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def update ( self , ** kwargs ) : self . inflate ( ) for model in self . _models : model . update ( ** kwargs ) return self
Update all resources in this collection .
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def delete ( self , ** kwargs ) : self . inflate ( ) for model in self . _models : model . delete ( ** kwargs ) return
Delete all resources in this collection .
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def wait ( self , ** kwargs ) : if self . request : self . request . wait ( ** kwargs ) self . request = None return self . inflate ( )
Wait until any pending asynchronous requests are finished for this collection .
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def url ( self ) : if self . _href is not None : return self . _href if self . identifier : path = '/' . join ( [ self . parent . url . replace ( 'classifications/' , 'classficiation/' ) , self . identifier ] ) return path raise exceptions . ClientError ( "Not able to determine object URL" )
Gets the url for the resource this model represents .
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def inflate ( self ) : if not self . _is_inflated : if self . _is_inflating : msg = ( "There is not enough data to inflate this object. " "Need either an href: {} or a {}: {}" ) msg = msg . format ( self . _href , self . primary_key , self . _data . get ( self . primary_key ) ) raise exceptions . ClientError ( msg ) s...
Load the resource from the server if not already loaded .
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def load ( self , response ) : if 'href' in response : self . _href = response . pop ( 'href' ) if self . data_key and self . data_key in response : self . _data . update ( response . pop ( self . data_key ) ) for rel in [ x for x in self . relationships if x in response and response [ x ] ] : rel_class = self . relati...
The load method parses the raw JSON response from the server .
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def delete ( self , ** kwargs ) : self . method = 'delete' if len ( kwargs ) > 0 : self . load ( self . client . delete ( self . url , params = kwargs ) ) else : self . load ( self . client . delete ( self . url ) ) self . parent . remove ( self ) return
Delete a resource by issuing a DELETE http request against it .
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def publish ( obj , event , event_state , ** kwargs ) : if len ( EVENT_HANDLERS ) == 0 : return if inspect . isclass ( obj ) : pub_cls = obj else : pub_cls = obj . __class__ potential = [ x . __name__ for x in inspect . getmro ( pub_cls ) ] fallbacks = None callbacks = [ ] for cls in potential : event_key = '.' . join ...
Publish an event from an object .
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def subscribe ( obj , event , callback , event_state = None ) : if inspect . isclass ( obj ) : cls = obj . __name__ else : cls = obj . __class__ . __name__ if event_state is None : event_state = states . ANY event_key = '.' . join ( [ cls , event , event_state ] ) if event_key not in EVENT_HANDLERS : EVENT_HANDLERS [ e...
Subscribe an event from an class .
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def clean_name ( self , suffix = True , prefix = False , middle = False , multi = False ) : "return cleared version of the business name" name = self . business_name name = self . string_stripper ( name ) loname = name . lower ( ) for item in suffix_sort : if suffix : if loname . endswith ( " " + item ) : start = lonam...
return cleared version of the business name
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def _add_nodes ( self ) : for n , atom in enumerate ( self . ast . select ( 'atom' ) ) : self . add_node ( n , atom = atom ) self . _atom_indices [ id ( atom ) ] = n
Add all atoms in the SMARTS string as nodes in the graph .
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def _add_edges ( self , ast_node , trunk = None ) : atom_indices = self . _atom_indices for atom in ast_node . tail : if atom . head == 'atom' : atom_idx = atom_indices [ id ( atom ) ] if atom . is_first_kid and atom . parent ( ) . head == 'branch' : trunk_idx = atom_indices [ id ( trunk ) ] self . add_edge ( atom_idx ...
Add all bonds in the SMARTS string as edges in the graph .
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def _add_label_edges ( self ) : labels = self . ast . select ( 'atom_label' ) if not labels : return label_digits = defaultdict ( list ) for label in labels : digits = list ( label . tail [ 0 ] ) for digit in digits : label_digits [ digit ] . append ( label . parent ( ) ) for label , ( atom1 , atom2 ) in label_digits ....
Add edges between all atoms with the same atom_label in rings .
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def find_matches ( self , topology ) : ring_tokens = [ 'ring_size' , 'ring_count' ] has_ring_rules = any ( self . ast . select ( token ) for token in ring_tokens ) _prepare_atoms ( topology , compute_cycles = has_ring_rules ) top_graph = nx . Graph ( ) top_graph . add_nodes_from ( ( ( a . index , { 'atom' : a } ) for a...
Return sets of atoms that match this SMARTS pattern in a topology .
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def candidate_pairs_iter ( self ) : G2_nodes = self . G2_nodes T1_inout = set ( self . inout_1 . keys ( ) ) - set ( self . core_1 . keys ( ) ) T2_inout = set ( self . inout_2 . keys ( ) ) - set ( self . core_2 . keys ( ) ) if T1_inout and T2_inout : for node in T1_inout : yield node , min ( T2_inout ) else : other_node...
Iterator over candidate pairs of nodes in G1 and G2 .
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def find_atomtypes ( topology , forcefield , max_iter = 10 ) : rules = _load_rules ( forcefield ) subrules = dict ( ) system_elements = { a . element . symbol for a in topology . atoms ( ) } for key , val in rules . items ( ) : atom = val . node [ 0 ] [ 'atom' ] if len ( atom . select ( 'atom_symbol' ) ) == 1 and not a...
Determine atomtypes for all atoms .
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def _load_rules ( forcefield ) : rules = dict ( ) for rule_name , smarts in forcefield . atomTypeDefinitions . items ( ) : overrides = forcefield . atomTypeOverrides . get ( rule_name ) if overrides is not None : overrides = set ( overrides ) else : overrides = set ( ) rules [ rule_name ] = SMARTSGraph ( smarts_string ...
Load atomtyping rules from a forcefield into SMARTSGraphs .
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def _iterate_rules ( rules , topology , max_iter ) : atoms = list ( topology . atoms ( ) ) for _ in range ( max_iter ) : max_iter -= 1 found_something = False for rule in rules . values ( ) : for match_index in rule . find_matches ( topology ) : atom = atoms [ match_index ] if rule . name not in atom . whitelist : atom...
Iteratively run all the rules until the white - and backlists converge .
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def _resolve_atomtypes ( topology ) : for atom in topology . atoms ( ) : atomtype = [ rule_name for rule_name in atom . whitelist - atom . blacklist ] if len ( atomtype ) == 1 : atom . id = atomtype [ 0 ] elif len ( atomtype ) > 1 : raise FoyerError ( "Found multiple types for atom {} ({}): {}." . format ( atom . index...
Determine the final atomtypes from the white - and blacklists .
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def generate_topology ( non_omm_topology , non_element_types = None , residues = None ) : if non_element_types is None : non_element_types = set ( ) if isinstance ( non_omm_topology , pmd . Structure ) : return _topology_from_parmed ( non_omm_topology , non_element_types ) elif has_mbuild : mb = import_ ( 'mbuild' ) if...
Create an OpenMM Topology from another supported topology structure .
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def _topology_from_parmed ( structure , non_element_types ) : topology = app . Topology ( ) residues = dict ( ) for pmd_residue in structure . residues : chain = topology . addChain ( ) omm_residue = topology . addResidue ( pmd_residue . name , chain ) residues [ pmd_residue ] = omm_residue atoms = dict ( ) for pmd_ato...
Convert a ParmEd Structure to an OpenMM Topology .
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def _topology_from_residue ( res ) : topology = app . Topology ( ) chain = topology . addChain ( ) new_res = topology . addResidue ( res . name , chain ) atoms = dict ( ) for res_atom in res . atoms ( ) : topology_atom = topology . addAtom ( name = res_atom . name , element = res_atom . element , residue = new_res ) at...
Converts a openmm . app . Topology . Residue to openmm . app . Topology .
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def _check_independent_residues ( topology ) : for res in topology . residues ( ) : atoms_in_residue = set ( [ atom for atom in res . atoms ( ) ] ) bond_partners_in_residue = [ item for sublist in [ atom . bond_partners for atom in res . atoms ( ) ] for item in sublist ] if not bond_partners_in_residue : continue if se...
Check to see if residues will constitute independent graphs .
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def _update_atomtypes ( unatomtyped_topology , res_name , prototype ) : for res in unatomtyped_topology . residues ( ) : if res . name == res_name : for old_atom , new_atom_id in zip ( [ atom for atom in res . atoms ( ) ] , [ atom . id for atom in prototype . atoms ( ) ] ) : old_atom . id = new_atom_id
Update atomtypes in residues in a topology using a prototype topology .
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def registerAtomType ( self , parameters ) : name = parameters [ 'name' ] if name in self . _atomTypes : raise ValueError ( 'Found multiple definitions for atom type: ' + name ) atom_class = parameters [ 'class' ] mass = _convertParameterToNumber ( parameters [ 'mass' ] ) element = None if 'element' in parameters : ele...
Register a new atom type .
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def run_atomtyping ( self , topology , use_residue_map = True ) : if use_residue_map : independent_residues = _check_independent_residues ( topology ) if independent_residues : residue_map = dict ( ) for res in topology . residues ( ) : if res . name not in residue_map . keys ( ) : residue = _topology_from_residue ( re...
Atomtype the topology
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def cd ( directory ) : old_dir = os . getcwd ( ) try : os . chdir ( directory ) yield finally : os . chdir ( old_dir )
Change the current working directory temporarily .
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def mkdtemp ( hint = '' ) : dirname = tempfile . mkdtemp ( prefix = 'check-manifest-' , suffix = hint ) try : yield dirname finally : rmtree ( dirname )
Create a temporary directory then clean it up .
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def chmod_plus ( path , add_bits = stat . S_IWUSR ) : try : os . chmod ( path , stat . S_IMODE ( os . stat ( path ) . st_mode ) | add_bits ) except OSError : pass
Change a file s mode by adding a few bits .
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def rmtree ( path ) : def onerror ( func , path , exc_info ) : if func is os . remove or func is os . unlink or func is os . rmdir : if sys . platform != 'win32' : chmod_plus ( os . path . dirname ( path ) , stat . S_IWUSR | stat . S_IXUSR ) chmod_plus ( path ) func ( path ) else : raise shutil . rmtree ( path , onerro...
A version of rmtree that can deal with read - only files and directories .
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def copy_files ( filelist , destdir ) : for filename in filelist : destfile = os . path . join ( destdir , filename ) assert destfile . startswith ( destdir + os . path . sep ) destfiledir = os . path . dirname ( destfile ) if not os . path . isdir ( destfiledir ) : os . makedirs ( destfiledir ) if os . path . isdir ( ...
Copy a list of files to destdir preserving directory structure .
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def get_one_file_in ( dirname ) : files = os . listdir ( dirname ) if len ( files ) > 1 : raise Failure ( 'More than one file exists in %s:\n%s' % ( dirname , '\n' . join ( sorted ( files ) ) ) ) elif not files : raise Failure ( 'No files found in %s' % dirname ) return os . path . join ( dirname , files [ 0 ] )
Return the pathname of the one file in a directory .
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def unicodify ( filename ) : if isinstance ( filename , bytes ) : return filename . decode ( locale . getpreferredencoding ( ) ) else : return filename
Make sure filename is Unicode .
47,082
def get_archive_file_list ( archive_filename ) : if archive_filename . endswith ( '.zip' ) : with closing ( zipfile . ZipFile ( archive_filename ) ) as zf : return add_directories ( zf . namelist ( ) ) elif archive_filename . endswith ( ( '.tar.gz' , '.tar.bz2' , '.tar' ) ) : with closing ( tarfile . open ( archive_fil...
Return the list of files in an archive .
47,083
def strip_toplevel_name ( filelist ) : if not filelist : return filelist prefix = filelist [ 0 ] if '/' in prefix : prefix = prefix . partition ( '/' ) [ 0 ] + '/' names = filelist else : prefix = prefix + '/' names = filelist [ 1 : ] for name in names : if not name . startswith ( prefix ) : raise Failure ( "File doesn...
Strip toplevel name from a file list .
47,084
def detect_vcs ( ) : location = os . path . abspath ( '.' ) while True : for vcs in Git , Mercurial , Bazaar , Subversion : if vcs . detect ( location ) : return vcs parent = os . path . dirname ( location ) if parent == location : raise Failure ( "Couldn't find version control data" " (git/hg/bzr/svn supported)" ) loc...
Detect the version control system used for the current directory .
47,085
def normalize_name ( name ) : name = os . path . normpath ( name ) name = unicodify ( name ) if sys . platform == 'darwin' : name = unicodedata . normalize ( 'NFC' , name ) return name
Some VCS print directory names with trailing slashes . Strip them .
47,086
def read_config ( ) : config = _load_config ( ) if config . get ( CFG_IGNORE_DEFAULT_RULES [ 1 ] , False ) : del IGNORE [ : ] if CFG_IGNORE [ 1 ] in config : IGNORE . extend ( p for p in config [ CFG_IGNORE [ 1 ] ] if p ) if CFG_IGNORE_BAD_IDEAS [ 1 ] in config : IGNORE_BAD_IDEAS . extend ( p for p in config [ CFG_IGNO...
Read configuration from file if possible .
47,087
def _load_config ( ) : if os . path . exists ( "pyproject.toml" ) : config = toml . load ( "pyproject.toml" ) if CFG_SECTION_CHECK_MANIFEST in config . get ( "tool" , { } ) : return config [ "tool" ] [ CFG_SECTION_CHECK_MANIFEST ] search_files = [ 'setup.cfg' , 'tox.ini' ] config_parser = ConfigParser . ConfigParser ( ...
Searches for config files reads them and returns a dictionary
47,088
def read_manifest ( ) : if not os . path . isfile ( 'MANIFEST.in' ) : return ignore , ignore_regexps = _get_ignore_from_manifest ( 'MANIFEST.in' ) IGNORE . extend ( ignore ) IGNORE_REGEXPS . extend ( ignore_regexps )
Read existing configuration from MANIFEST . in .
47,089
def file_matches ( filename , patterns ) : return any ( fnmatch . fnmatch ( filename , pat ) or fnmatch . fnmatch ( os . path . basename ( filename ) , pat ) for pat in patterns )
Does this filename match any of the patterns?
47,090
def file_matches_regexps ( filename , patterns ) : return any ( re . match ( pat , filename ) for pat in patterns )
Does this filename match any of the regular expressions?
47,091
def strip_sdist_extras ( filelist ) : return [ name for name in filelist if not file_matches ( name , IGNORE ) and not file_matches_regexps ( name , IGNORE_REGEXPS ) ]
Strip generated files that are only present in source distributions .
47,092
def find_suggestions ( filelist ) : suggestions = set ( ) unknowns = [ ] for filename in filelist : if os . path . isdir ( filename ) : continue for pattern , suggestion in SUGGESTIONS : m = pattern . match ( filename ) if m is not None : suggestions . add ( pattern . sub ( suggestion , filename ) ) break else : unknow...
Suggest MANIFEST . in patterns for missing files .
47,093
def extract_version_from_filename ( filename ) : filename = os . path . splitext ( os . path . basename ( filename ) ) [ 0 ] if filename . endswith ( '.tar' ) : filename = os . path . splitext ( filename ) [ 0 ] return filename . partition ( '-' ) [ 2 ]
Extract version number from sdist filename .
47,094
def zest_releaser_check ( data ) : from zest . releaser . utils import ask source_tree = data [ 'workingdir' ] if not is_package ( source_tree ) : return if not ask ( "Do you want to run check-manifest?" ) : return try : if not check_manifest ( source_tree ) : if not ask ( "MANIFEST.in has problems. " " Do you want to ...
Check the completeness of MANIFEST . in before the release .
47,095
def get_versioned_files ( cls ) : files = cls . _git_ls_files ( ) submodules = cls . _list_submodules ( ) for subdir in submodules : subdir = os . path . relpath ( subdir ) . replace ( os . path . sep , '/' ) files += add_prefix_to_each ( subdir , cls . _git_ls_files ( subdir ) ) return add_directories ( files )
List all files versioned by git in the current directory .
47,096
def get_versioned_files ( cls ) : encoding = cls . _get_terminal_encoding ( ) output = run ( [ 'bzr' , 'ls' , '-VR' ] , encoding = encoding ) return output . splitlines ( )
List all files versioned in Bazaar in the current directory .
47,097
def get_versioned_files ( cls ) : output = run ( [ 'svn' , 'st' , '-vq' , '--xml' ] , decode = False ) tree = ET . XML ( output ) return sorted ( entry . get ( 'path' ) for entry in tree . findall ( './/entry' ) if cls . is_interesting ( entry ) )
List all files under SVN control in the current directory .
47,098
def is_interesting ( entry ) : if entry . get ( 'path' ) == '.' : return False status = entry . find ( 'wc-status' ) if status is None : warning ( 'svn status --xml parse error: <entry path="%s"> without' ' <wc-status>' % entry . get ( 'path' ) ) return False if status . get ( 'item' ) in ( 'unversioned' , 'external' )...
Is this entry interesting?
47,099
def validate ( self ) : if not self . principals : raise InvalidApplicationPolicyError ( error_message = 'principals not provided' ) if not self . actions : raise InvalidApplicationPolicyError ( error_message = 'actions not provided' ) if any ( not self . _PRINCIPAL_PATTERN . match ( p ) for p in self . principals ) : ...
Check if the formats of principals and actions are valid .