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def warning ( self , amplexception ) : msg = '\t' + str ( amplexception ) . replace ( '\n' , '\n\t' ) print ( 'Warning:\n{:s}' . format ( msg ) )
Receives notification of a warning .
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def register_magics ( store_name = '_ampl_cells' , ampl_object = None ) : from IPython . core . magic import ( Magics , magics_class , cell_magic , line_magic ) @ magics_class class StoreAMPL ( Magics ) : def __init__ ( self , shell = None , ** kwargs ) : Magics . __init__ ( self , shell = shell , ** kwargs ) self . _s...
Register jupyter notebook magics %%ampl and %%ampl_eval .
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def fix ( self , value = None ) : if value is None : self . _impl . fix ( ) else : self . _impl . fix ( value )
Fix all instances of this variable to a value if provided or to their current value otherwise .
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def toVName ( name , stripNum = 0 , upper = False ) : if upper : name = name . upper ( ) if stripNum != 0 : name = name [ : - stripNum ] return name . replace ( '_' , '-' )
Turn a Python name into an iCalendar style name optionally uppercase and with characters stripped off .
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def readComponents ( streamOrString , validate = False , transform = True , ignoreUnreadable = False , allowQP = False ) : if isinstance ( streamOrString , basestring ) : stream = six . StringIO ( streamOrString ) else : stream = streamOrString try : stack = Stack ( ) versionLine = None n = 0 for line , n in getLogical...
Generate one Component at a time from a stream .
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def readOne ( stream , validate = False , transform = True , ignoreUnreadable = False , allowQP = False ) : return next ( readComponents ( stream , validate , transform , ignoreUnreadable , allowQP ) )
Return the first component from stream .
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def registerBehavior ( behavior , name = None , default = False , id = None ) : if not name : name = behavior . name . upper ( ) if id is None : id = behavior . versionString if name in __behaviorRegistry : if default : __behaviorRegistry [ name ] . insert ( 0 , ( id , behavior ) ) else : __behaviorRegistry [ name ] . ...
Register the given behavior .
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def getBehavior ( name , id = None ) : name = name . upper ( ) if name in __behaviorRegistry : if id : for n , behavior in __behaviorRegistry [ name ] : if n == id : return behavior return __behaviorRegistry [ name ] [ 0 ] [ 1 ] return None
Return a matching behavior if it exists or None .
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def validate ( self , * args , ** kwds ) : if self . behavior : return self . behavior . validate ( self , * args , ** kwds ) return True
Call the behavior s validate method or return True .
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def autoBehavior ( self , cascade = False ) : parentBehavior = self . parentBehavior if parentBehavior is not None : knownChildTup = parentBehavior . knownChildren . get ( self . name , None ) if knownChildTup is not None : behavior = getBehavior ( self . name , knownChildTup [ 2 ] ) if behavior is not None : self . se...
Set behavior if name is in self . parentBehavior . knownChildren .
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def setBehavior ( self , behavior , cascade = True ) : self . behavior = behavior if cascade : for obj in self . getChildren ( ) : obj . parentBehavior = behavior obj . autoBehavior ( True )
Set behavior . If cascade is True autoBehavior all descendants .
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def serialize ( self , buf = None , lineLength = 75 , validate = True , behavior = None ) : if not behavior : behavior = self . behavior if behavior : if DEBUG : logger . debug ( "serializing {0!s} with behavior {1!s}" . format ( self . name , behavior ) ) return behavior . serialize ( self , buf , lineLength , validat...
Serialize to buf if it exists otherwise return a string .
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def valueRepr ( self ) : v = self . value if self . behavior : v = self . behavior . valueRepr ( self ) return v
Transform the representation of the value according to the behavior if any .
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def setProfile ( self , name ) : if self . name or self . useBegin : if self . name == name : return raise VObjectError ( "This component already has a PROFILE or " "uses BEGIN." ) self . name = name . upper ( )
Assign a PROFILE to this unnamed component .
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def add ( self , objOrName , group = None ) : if isinstance ( objOrName , VBase ) : obj = objOrName if self . behavior : obj . parentBehavior = self . behavior obj . autoBehavior ( True ) else : name = objOrName . upper ( ) try : id = self . behavior . knownChildren [ name ] [ 2 ] behavior = getBehavior ( name , id ) i...
Add objOrName to contents set behavior if it can be inferred .
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def remove ( self , obj ) : named = self . contents . get ( obj . name . lower ( ) ) if named : try : named . remove ( obj ) if len ( named ) == 0 : del self . contents [ obj . name . lower ( ) ] except ValueError : pass
Remove obj from contents .
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def setBehaviorFromVersionLine ( self , versionLine ) : v = getBehavior ( self . name , versionLine . value ) if v : self . setBehavior ( v )
Set behavior if one matches name versionLine . value .
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def transformChildrenToNative ( self ) : for childArray in ( self . contents [ k ] for k in self . sortChildKeys ( ) ) : for child in childArray : child = child . transformToNative ( ) child . transformChildrenToNative ( )
Recursively replace children with their native representation .
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def transformChildrenFromNative ( self , clearBehavior = True ) : for childArray in self . contents . values ( ) : for child in childArray : child = child . transformFromNative ( ) child . transformChildrenFromNative ( clearBehavior ) if clearBehavior : child . behavior = None child . parentBehavior = None
Recursively transform native children to vanilla representations .
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def change_tz ( cal , new_timezone , default , utc_only = False , utc_tz = icalendar . utc ) : for vevent in getattr ( cal , 'vevent_list' , [ ] ) : start = getattr ( vevent , 'dtstart' , None ) end = getattr ( vevent , 'dtend' , None ) for node in ( start , end ) : if node : dt = node . value if ( isinstance ( dt , da...
Change the timezone of the specified component .
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def defaultSerialize ( obj , buf , lineLength ) : outbuf = buf or six . StringIO ( ) if isinstance ( obj , Component ) : if obj . group is None : groupString = '' else : groupString = obj . group + '.' if obj . useBegin : foldOneLine ( outbuf , "{0}BEGIN:{1}" . format ( groupString , obj . name ) , lineLength ) for chi...
Encode and fold obj and its children write to buf or return a string .
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def toUnicode ( s ) : if isinstance ( s , six . binary_type ) : s = s . decode ( 'utf-8' ) return s
Take a string or unicode turn it into unicode decoding as utf - 8
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def numToDigits ( num , places ) : s = str ( num ) if len ( s ) < places : return ( "0" * ( places - len ( s ) ) ) + s elif len ( s ) > places : return s [ len ( s ) - places : ] else : return s
Helper for converting numbers to textual digits .
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def timedeltaToString ( delta ) : if delta . days == 0 : sign = 1 else : sign = delta . days / abs ( delta . days ) delta = abs ( delta ) days = delta . days hours = int ( delta . seconds / 3600 ) minutes = int ( ( delta . seconds % 3600 ) / 60 ) seconds = int ( delta . seconds % 60 ) output = '' if sign == - 1 : outpu...
Convert timedelta to an ical DURATION .
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def stringToTextValues ( s , listSeparator = ',' , charList = None , strict = False ) : if charList is None : charList = escapableCharList def escapableChar ( c ) : return c in charList def error ( msg ) : if strict : raise ParseError ( msg ) else : logging . error ( msg ) charIterator = enumerate ( s ) state = "read n...
Returns list of strings .
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def parseDtstart ( contentline , allowSignatureMismatch = False ) : tzinfo = getTzid ( getattr ( contentline , 'tzid_param' , None ) ) valueParam = getattr ( contentline , 'value_param' , 'DATE-TIME' ) . upper ( ) if valueParam == "DATE" : return stringToDate ( contentline . value ) elif valueParam == "DATE-TIME" : try...
Convert a contentline s value into a date or date - time .
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def tzinfo_eq ( tzinfo1 , tzinfo2 , startYear = 2000 , endYear = 2020 ) : if tzinfo1 == tzinfo2 : return True elif tzinfo1 is None or tzinfo2 is None : return False def dt_test ( dt ) : if dt is None : return True return tzinfo1 . utcoffset ( dt ) == tzinfo2 . utcoffset ( dt ) if not dt_test ( datetime . datetime ( sta...
Compare offsets and DST transitions from startYear to endYear .
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def registerTzinfo ( obj , tzinfo ) : tzid = obj . pickTzid ( tzinfo ) if tzid and not getTzid ( tzid , False ) : registerTzid ( tzid , tzinfo ) return tzid
Register tzinfo if it s not already registered return its tzid .
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def pickTzid ( tzinfo , allowUTC = False ) : if tzinfo is None or ( not allowUTC and tzinfo_eq ( tzinfo , utc ) ) : return None if hasattr ( tzinfo , 'tzid' ) : return toUnicode ( tzinfo . tzid ) if hasattr ( tzinfo , 'zone' ) : return toUnicode ( tzinfo . zone ) elif hasattr ( tzinfo , '_tzid' ) : return toUnicode ( t...
Given a tzinfo class use known APIs to determine TZID or use tzname .
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def transformToNative ( obj ) : if not obj . isNative : object . __setattr__ ( obj , '__class__' , RecurringComponent ) obj . isNative = True return obj
Turn a recurring Component into a RecurringComponent .
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def generateImplicitParameters ( obj ) : if not hasattr ( obj , 'uid' ) : rand = int ( random . random ( ) * 100000 ) now = datetime . datetime . now ( utc ) now = dateTimeToString ( now ) host = socket . gethostname ( ) obj . add ( ContentLine ( 'UID' , [ ] , "{0} - {1}@{2}" . format ( now , rand , host ) ) )
Generate a UID if one does not exist .
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def transformToNative ( obj ) : if obj . isNative : return obj obj . isNative = True if obj . value == '' : return obj obj . value = obj . value obj . value = parseDtstart ( obj , allowSignatureMismatch = True ) if getattr ( obj , 'value_param' , 'DATE-TIME' ) . upper ( ) == 'DATE-TIME' : if hasattr ( obj , 'tzid_param...
Turn obj . value into a date or datetime .
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def transformFromNative ( obj ) : if type ( obj . value ) == datetime . date : obj . isNative = False obj . value_param = 'DATE' obj . value = dateToString ( obj . value ) return obj else : return DateTimeBehavior . transformFromNative ( obj )
Replace the date or datetime in obj . value with an ISO 8601 string .
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def transformFromNative ( obj ) : if obj . value and type ( obj . value [ 0 ] ) == datetime . date : obj . isNative = False obj . value_param = 'DATE' obj . value = ',' . join ( [ dateToString ( val ) for val in obj . value ] ) return obj else : if obj . isNative : obj . isNative = False transformed = [ ] tzid = None f...
Replace the date datetime or period tuples in obj . value with appropriate strings .
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def decode ( cls , line ) : if line . encoded : line . value = stringToTextValues ( line . value , listSeparator = cls . listSeparator ) line . encoded = False
Remove backslash escaping from line . value then split on commas .
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def generateImplicitParameters ( obj ) : try : obj . action except AttributeError : obj . add ( 'action' ) . value = 'AUDIO' try : obj . trigger except AttributeError : obj . add ( 'trigger' ) . value = datetime . timedelta ( 0 )
Create default ACTION and TRIGGER if they re not set .
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def transformToNative ( obj ) : if obj . isNative : return obj obj . isNative = True obj . value = obj . value if obj . value == '' : return obj else : deltalist = stringToDurations ( obj . value ) if len ( deltalist ) == 1 : obj . value = deltalist [ 0 ] return obj else : raise ParseError ( "DURATION must have a singl...
Turn obj . value into a datetime . timedelta .
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def transformFromNative ( obj ) : if not obj . isNative : return obj obj . isNative = False obj . value = timedeltaToString ( obj . value ) return obj
Replace the datetime . timedelta in obj . value with an RFC2445 string .
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def transformToNative ( obj ) : if obj . isNative : return obj value = getattr ( obj , 'value_param' , 'DURATION' ) . upper ( ) if hasattr ( obj , 'value_param' ) : del obj . value_param if obj . value == '' : obj . isNative = True return obj elif value == 'DURATION' : try : return Duration . transformToNative ( obj ) ...
Turn obj . value into a timedelta or datetime .
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def transformToNative ( obj ) : if obj . isNative : return obj obj . isNative = True if obj . value == '' : obj . value = [ ] return obj tzinfo = getTzid ( getattr ( obj , 'tzid_param' , None ) ) obj . value = [ stringToPeriod ( x , tzinfo ) for x in obj . value . split ( "," ) ] return obj
Convert comma separated periods into tuples .
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def transformFromNative ( cls , obj ) : if obj . isNative : obj . isNative = False transformed = [ ] for tup in obj . value : transformed . append ( periodToString ( tup , cls . forceUTC ) ) if len ( transformed ) > 0 : tzid = TimezoneComponent . registerTzinfo ( tup [ 0 ] . tzinfo ) if not cls . forceUTC and tzid is n...
Convert the list of tuples in obj . value to strings .
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def serializeFields ( obj , order = None ) : fields = [ ] if order is None : fields = [ backslashEscape ( val ) for val in obj ] else : for field in order : escapedValueList = [ backslashEscape ( val ) for val in toList ( getattr ( obj , field ) ) ] fields . append ( ',' . join ( escapedValueList ) ) return ';' . join ...
Turn an object s fields into a ; and seperated string .
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def toString ( val , join_char = '\n' ) : if type ( val ) in ( list , tuple ) : return join_char . join ( val ) return val
Turn a string or array value into a string .
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def transformToNative ( obj ) : if obj . isNative : return obj obj . isNative = True obj . value = Name ( ** dict ( zip ( NAME_ORDER , splitFields ( obj . value ) ) ) ) return obj
Turn obj . value into a Name .
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def transformFromNative ( obj ) : obj . isNative = False obj . value = serializeFields ( obj . value , NAME_ORDER ) return obj
Replace the Name in obj . value with a string .
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def transformToNative ( obj ) : if obj . isNative : return obj obj . isNative = True obj . value = Address ( ** dict ( zip ( ADDRESS_ORDER , splitFields ( obj . value ) ) ) ) return obj
Turn obj . value into an Address .
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def transformToNative ( obj ) : if obj . isNative : return obj obj . isNative = True obj . value = splitFields ( obj . value ) return obj
Turn obj . value into a list .
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def decode ( cls , line ) : if line . encoded : if 'BASE64' in line . singletonparams : line . singletonparams . remove ( 'BASE64' ) line . encoding_param = cls . base64string encoding = getattr ( line , 'encoding_param' , None ) if encoding : line . value = codecs . decode ( line . value . encode ( "utf-8" ) , "base64...
Remove backslash escaping from line . valueDecode line either to remove backslash espacing or to decode base64 encoding . The content line should contain a ENCODING = b for base64 encoding but Apple Addressbook seems to export a singleton parameter of BASE64 which does not match the 3 . 0 vCard spec . If we encouter th...
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def validate ( cls , obj , raiseException = False , complainUnrecognized = False ) : if not cls . allowGroup and obj . group is not None : err = "{0} has a group, but this object doesn't support groups" . format ( obj ) raise base . VObjectError ( err ) if isinstance ( obj , base . ContentLine ) : return cls . lineVali...
Check if the object satisfies this behavior s requirements .
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def pickNthWeekday ( year , month , dayofweek , hour , minute , whichweek ) : first = datetime . datetime ( year = year , month = month , hour = hour , minute = minute , day = 1 ) weekdayone = first . replace ( day = ( ( dayofweek - first . isoweekday ( ) ) % 7 + 1 ) ) for n in xrange ( whichweek - 1 , - 1 , - 1 ) : dt...
dayofweek == 0 means Sunday whichweek > 4 means last instance
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def deleteExtraneous ( component , ignore_dtstamp = False ) : for comp in component . components ( ) : deleteExtraneous ( comp , ignore_dtstamp ) for line in component . lines ( ) : if 'X-VOBJ-ORIGINAL-TZID' in line . params : del line . params [ 'X-VOBJ-ORIGINAL-TZID' ] if ignore_dtstamp and hasattr ( component , 'dts...
Recursively walk the component s children deleting extraneous details like X - VOBJ - ORIGINAL - TZID .
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def fillPelicanHole ( site , username , password , tstat_name , start_time , end_time ) : start = datetime . strptime ( start_time , _INPUT_TIME_FORMAT ) . replace ( tzinfo = pytz . utc ) . astimezone ( _pelican_time ) end = datetime . strptime ( end_time , _INPUT_TIME_FORMAT ) . replace ( tzinfo = pytz . utc ) . astim...
Fill a hole in a Pelican thermostat s data stream .
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def add_degree_days ( self , col = 'OAT' , hdh_cpoint = 65 , cdh_cpoint = 65 ) : if self . preprocessed_data . empty : data = self . original_data else : data = self . preprocessed_data data [ 'hdh' ] = data [ col ] over_hdh = data . loc [ : , col ] > hdh_cpoint data . loc [ over_hdh , 'hdh' ] = 0 data . loc [ ~ over_h...
Adds Heating & Cooling Degree Hours .
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def add_col_features ( self , col = None , degree = None ) : if not col and not degree : return else : if isinstance ( col , list ) and isinstance ( degree , list ) : if len ( col ) != len ( degree ) : print ( 'col len: ' , len ( col ) ) print ( 'degree len: ' , len ( degree ) ) raise ValueError ( 'col and degree shoul...
Exponentiate columns of dataframe .
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def standardize ( self ) : if self . preprocessed_data . empty : data = self . original_data else : data = self . preprocessed_data scaler = preprocessing . StandardScaler ( ) data = pd . DataFrame ( scaler . fit_transform ( data ) , columns = data . columns , index = data . index ) self . preprocessed_data = data
Standardize data .
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def normalize ( self ) : if self . preprocessed_data . empty : data = self . original_data else : data = self . preprocessed_data data = pd . DataFrame ( preprocessing . normalize ( data ) , columns = data . columns , index = data . index ) self . preprocessed_data = data
Normalize data .
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def add_time_features ( self , year = False , month = False , week = True , tod = True , dow = True ) : var_to_expand = [ ] if self . preprocessed_data . empty : data = self . original_data else : data = self . preprocessed_data if year : data [ "year" ] = data . index . year var_to_expand . append ( "year" ) if month ...
Add time features to dataframe .
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def split_data ( self ) : try : time_period1 = ( slice ( self . baseline_period [ 0 ] , self . baseline_period [ 1 ] ) ) self . baseline_in = self . original_data . loc [ time_period1 , self . input_col ] self . baseline_out = self . original_data . loc [ time_period1 , self . output_col ] if self . exclude_time_period...
Split data according to baseline and projection time period values .
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def linear_regression ( self ) : model = LinearRegression ( ) scores = [ ] kfold = KFold ( n_splits = self . cv , shuffle = True , random_state = 42 ) for i , ( train , test ) in enumerate ( kfold . split ( self . baseline_in , self . baseline_out ) ) : model . fit ( self . baseline_in . iloc [ train ] , self . baselin...
Linear Regression .
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def lasso_regression ( self ) : score_list = [ ] max_score = float ( '-inf' ) best_alpha = None for alpha in self . alphas : model = Lasso ( alpha = alpha , max_iter = 5000 ) model . fit ( self . baseline_in , self . baseline_out . values . ravel ( ) ) scores = [ ] kfold = KFold ( n_splits = self . cv , shuffle = True ...
Lasso Regression .
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def random_forest ( self ) : model = RandomForestRegressor ( random_state = 42 ) scores = [ ] kfold = KFold ( n_splits = self . cv , shuffle = True , random_state = 42 ) for i , ( train , test ) in enumerate ( kfold . split ( self . baseline_in , self . baseline_out ) ) : model . fit ( self . baseline_in . iloc [ train...
Random Forest .
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def run_models ( self ) : self . linear_regression ( ) self . lasso_regression ( ) self . ridge_regression ( ) self . elastic_net_regression ( ) self . random_forest ( ) self . ann ( ) best_model_index = self . max_scores . index ( max ( self . max_scores ) ) self . best_model_name = self . model_names [ best_model_ind...
Run all models .
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def custom_model ( self , func ) : y_pred = func ( self . baseline_in , self . baseline_out ) self . custom_metrics = { } self . custom_metrics [ 'r2' ] = r2_score ( self . baseline_out , y_pred ) self . custom_metrics [ 'mse' ] = mean_squared_error ( self . baseline_out , y_pred ) self . custom_metrics [ 'rmse' ] = ma...
Run custom model provided by user .
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def best_model_fit ( self ) : self . best_model . fit ( self . baseline_in , self . baseline_out ) self . y_true = self . baseline_out self . y_pred = self . best_model . predict ( self . baseline_in ) self . y_pred [ self . y_pred < 0 ] = 0 self . n_test = self . baseline_in . shape [ 0 ] self . k_test = self . baseli...
Fit data to optimal model and return its metrics .
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def correlation_plot ( self , data ) : fig = plt . figure ( Plot_Data . count ) corr = data . corr ( ) ax = sns . heatmap ( corr ) Plot_Data . count += 1 return fig
Create heatmap of Pearson s correlation coefficient .
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def baseline_projection_plot ( self , y_true , y_pred , baseline_period , projection_period , model_name , adj_r2 , data , input_col , output_col , model , site ) : fig = plt . figure ( Plot_Data . count ) if projection_period : nrows = len ( baseline_period ) + len ( projection_period ) / 2 else : nrows = len ( baseli...
Create baseline and projection plots .
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def get_thermostat_meter_data ( zone ) : meter_uri = zone2meter . get ( zone , "None" ) data = [ ] def cb ( msg ) : for po in msg . payload_objects : if po . type_dotted == ( 2 , 0 , 9 , 1 ) : m = msgpack . unpackb ( po . content ) data . append ( m [ 'current_demand' ] ) handle = c . subscribe ( meter_uri + "/signal/m...
This method subscribes to the output of the meter for the given zone . It returns a handler to call when you want to stop subscribing data which returns a list of the data readins over that time period
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def call_heat ( tstat ) : current_hsp , current_csp = tstat . heating_setpoint , tstat . cooling_setpoint current_temp = tstat . temperature tstat . write ( { 'heating_setpoint' : current_temp + 10 , 'cooling_setpoint' : current_temp + 20 , 'mode' : HEAT , } ) def restore ( ) : tstat . write ( { 'heating_setpoint' : cu...
Adjusts the temperature setpoints in order to call for heating . Returns a handler to call when you want to reset the thermostat
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def call_cool ( tstat ) : current_hsp , current_csp = tstat . heating_setpoint , tstat . cooling_setpoint current_temp = tstat . temperature tstat . write ( { 'heating_setpoint' : current_temp - 20 , 'cooling_setpoint' : current_temp - 10 , 'mode' : COOL , } ) def restore ( ) : tstat . write ( { 'heating_setpoint' : cu...
Adjusts the temperature setpoints in order to call for cooling . Returns a handler to call when you want to reset the thermostat
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def call_fan ( tstat ) : old_fan = tstat . fan tstat . write ( { 'fan' : not old_fan , } ) def restore ( ) : tstat . write ( { 'fan' : old_fan , } ) return restore
Toggles the fan
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def _load_csv ( self , file_name , folder_name , head_row , index_col , convert_col , concat_files ) : if file_name == "*" : if not os . path . isdir ( folder_name ) : raise OSError ( 'Folder does not exist.' ) else : file_name_list = sorted ( glob . glob ( folder_name + '*.csv' ) ) if not file_name_list : raise OSErro...
Load single csv file .
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def convert_to_utc ( time ) : if 'Z' in time : return time else : time_formatted = time [ : - 3 ] + time [ - 2 : ] dt = datetime . strptime ( time_formatted , '%Y-%m-%dT%H:%M:%S%z' ) dt = dt . astimezone ( timezone ( 'UTC' ) ) return dt . strftime ( '%Y-%m-%dT%H:%M:%SZ' )
Convert time to UTC
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def get_meter ( self , site , start , end , point_type = 'Green_Button_Meter' , var = "meter" , agg = 'MEAN' , window = '24h' , aligned = True , return_names = True ) : start = self . convert_to_utc ( start ) end = self . convert_to_utc ( end ) request = self . compose_MDAL_dic ( point_type = point_type , site = site ,...
Get meter data from MDAL .
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def get_tstat ( self , site , start , end , var = "tstat_temp" , agg = 'MEAN' , window = '24h' , aligned = True , return_names = True ) : start = self . convert_to_utc ( start ) end = self . convert_to_utc ( end ) point_map = { "tstat_state" : "Thermostat_Status" , "tstat_hsp" : "Supply_Air_Temperature_Heating_Setpoint...
Get thermostat data from MDAL .
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def compose_MDAL_dic ( self , site , point_type , start , end , var , agg , window , aligned , points = None , return_names = False ) : start = self . convert_to_utc ( start ) end = self . convert_to_utc ( end ) request = { } request [ 'Time' ] = { 'Start' : start , 'End' : end , 'Window' : window , 'Aligned' : aligned...
Create dictionary for MDAL request .
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def get_point_name ( self , context ) : metadata_table = self . parse_context ( context ) return metadata_table . apply ( self . strip_point_name , axis = 1 )
Get point name .
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def replace_uuid_w_names ( self , resp ) : col_mapper = self . get_point_name ( resp . context ) [ "?point" ] . to_dict ( ) resp . df . rename ( columns = col_mapper , inplace = True ) return resp
Replace the uuid s with names .
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def resample_data ( self , data , freq , resampler = 'mean' ) : if resampler == 'mean' : data = data . resample ( freq ) . mean ( ) elif resampler == 'max' : data = data . resample ( freq ) . max ( ) else : raise ValueError ( 'Resampler can be \'mean\' or \'max\' only.' ) return data
Resample dataframe .
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def interpolate_data ( self , data , limit , method ) : data = data . interpolate ( how = "index" , limit = limit , method = method ) return data
Interpolate dataframe .
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def remove_na ( self , data , remove_na_how ) : data = data . dropna ( how = remove_na_how ) return data
Remove NAs from dataframe .
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def remove_outlier ( self , data , sd_val ) : data = data . dropna ( ) data = data [ ( np . abs ( stats . zscore ( data ) ) < float ( sd_val ) ) . all ( axis = 1 ) ] return data
Remove outliers from dataframe .
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def remove_out_of_bounds ( self , data , low_bound , high_bound ) : data = data . dropna ( ) data = data [ ( data > low_bound ) . all ( axis = 1 ) & ( data < high_bound ) . all ( axis = 1 ) ] return data
Remove out of bound datapoints from dataframe .
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def _set_TS_index ( self , data ) : data . index = pd . to_datetime ( data . index , error = "ignore" ) for col in data . columns : data [ col ] = pd . to_numeric ( data [ col ] , errors = "coerce" ) return data
Convert index to datetime and all other columns to numeric
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def _utc_to_local ( self , data , local_zone = "America/Los_Angeles" ) : data . index = data . index . tz_localize ( pytz . utc ) . tz_convert ( local_zone ) data . index = data . index . tz_localize ( None ) return data
Adjust index of dataframe according to timezone that is requested by user .
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def _local_to_utc ( self , timestamp , local_zone = "America/Los_Angeles" ) : timestamp_new = pd . to_datetime ( timestamp , infer_datetime_format = True , errors = 'coerce' ) timestamp_new = timestamp_new . tz_localize ( local_zone ) . tz_convert ( pytz . utc ) timestamp_new = timestamp_new . strftime ( '%Y-%m-%d %H:%...
Convert local timestamp to UTC .
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def find_uuid ( self , obj , column_name ) : keys = obj . context . keys ( ) for i in keys : if column_name in obj . context [ i ] [ '?point' ] : uuid = i return i
Find uuid .
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def identify_missing ( self , df , check_start = True ) : data_missing = df . isnull ( ) * 1 col_name = str ( data_missing . columns [ 0 ] ) if check_start & data_missing [ col_name ] [ 0 ] == 1 : data_missing [ col_name ] [ 0 ] = 0 return data_missing , col_name
Identify missing data .
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def diff_boolean ( self , df , column_name = None , uuid = None , duration = True , min_event_filter = '3 hours' ) : if uuid == None : uuid = 'End' data_gaps = df [ ( df . diff ( ) == 1 ) | ( df . diff ( ) == - 1 ) ] . dropna ( ) data_gaps [ "duration" ] = abs ( data_gaps . index . to_series ( ) . diff ( periods = - 1 ...
takes the dataframe of missing values and returns a dataframe that indicates the length of each event where data was continuously missing
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def analyze_quality_table ( self , obj , low_bound = None , high_bound = None ) : data = obj . df N_rows = 3 N_cols = data . shape [ 1 ] d = pd . DataFrame ( np . zeros ( ( N_rows , N_cols ) ) , index = [ '% Missing' , 'AVG Length Missing' , 'Std dev. Missing' ] , columns = [ data . columns ] ) if low_bound : data = da...
Takes in an the object returned by the MDAL query and analyzes the quality of the data for each column in the df . Returns a df of data quality metrics
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def analyze_quality_graph ( self , obj ) : data = obj . df for i in range ( data . shape [ 1 ] ) : data_per_meter = data . iloc [ : , [ i ] ] data_missing , meter = self . identify_missing ( data_per_meter ) percentage = data_missing . sum ( ) / ( data . shape [ 0 ] ) * 100 print ( 'Percentage Missing of ' + meter + ' ...
Takes in an the object returned by the MDAL query and analyzes the quality of the data for each column in the df in the form of graphs . The Graphs returned show missing data events over time and missing data frequency during each hour of the day
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def clean_data ( self , resample = True , freq = 'h' , resampler = 'mean' , interpolate = True , limit = 1 , method = 'linear' , remove_na = True , remove_na_how = 'any' , remove_outliers = True , sd_val = 3 , remove_out_of_bounds = True , low_bound = 0 , high_bound = 9998 ) : data = self . original_data if resample : ...
Clean dataframe .
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def write_json ( self ) : with open ( self . results_folder_name + '/results-' + str ( self . get_global_count ( ) ) + '.json' , 'a' ) as f : json . dump ( self . result , f )
Dump data into json file .
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def site_analysis ( self , folder_name , site_install_mapping , end_date ) : def count_number_of_days ( site , end_date ) : start_date = site_install_mapping [ site ] start_date = start_date . split ( '-' ) start = date ( int ( start_date [ 0 ] ) , int ( start_date [ 1 ] ) , int ( start_date [ 2 ] ) ) end_date = end_da...
Summarize site data into a single table .
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def search ( self , file_name , imported_data = None ) : resample_freq = [ '15T' , 'h' , 'd' ] time_freq = { 'year' : [ True , False , False , False , False ] , 'month' : [ False , True , False , False , False ] , 'week' : [ False , False , True , False , False ] , 'tod' : [ False , False , False , True , False ] , 'do...
Run models on different data configurations .
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def clean_data ( self , data , rename_col = None , drop_col = None , resample = True , freq = 'h' , resampler = 'mean' , interpolate = True , limit = 1 , method = 'linear' , remove_na = True , remove_na_how = 'any' , remove_outliers = True , sd_val = 3 , remove_out_of_bounds = True , low_bound = 0 , high_bound = float ...
Cleans dataframe according to user specifications and stores result in self . cleaned_data .
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def prevmonday ( num ) : today = get_today ( ) lastmonday = today - timedelta ( days = today . weekday ( ) , weeks = num ) return lastmonday
Return unix SECOND timestamp of num mondays ago
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def med_filt ( x , k = 201 ) : if x . ndim > 1 : x = np . squeeze ( x ) med = np . median ( x ) assert k % 2 == 1 , "Median filter length must be odd." assert x . ndim == 1 , "Input must be one-dimensional." k2 = ( k - 1 ) // 2 y = np . zeros ( ( len ( x ) , k ) , dtype = x . dtype ) y [ : , k2 ] = x for i in range ( k...
Apply a length - k median filter to a 1D array x . Boundaries are extended by repeating endpoints .
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def preprocess_data ( self , data , hdh_cpoint = 65 , cdh_cpoint = 65 , col_hdh_cdh = None , col_degree = None , degree = None , standardize = False , normalize = False , year = False , month = False , week = False , tod = False , dow = False , save_file = True ) : if not isinstance ( data , pd . DataFrame ) : raise Sy...
Preprocesses dataframe according to user specifications and stores result in self . preprocessed_data .
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def model ( self , data , ind_col = None , dep_col = None , project_ind_col = None , baseline_period = [ None , None ] , projection_period = None , exclude_time_period = None , alphas = np . logspace ( - 4 , 1 , 30 ) , cv = 3 , plot = True , figsize = None , custom_model_func = None ) : if not isinstance ( data , pd . ...
Split data into baseline and projection periods run models on them and display metrics & plots .
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def make_dataframe ( result ) : import pandas as pd ret = { } if isinstance ( result , dict ) : if 'timeseries' in result : result = result [ 'timeseries' ] for uuid , data in result . items ( ) : df = pd . DataFrame ( data ) if len ( df . columns ) == 5 : df . columns = [ 'time' , 'min' , 'mean' , 'max' , 'count' ] el...
Turns the results of one of the data API calls into a pandas dataframe