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def _q_iteration ( self , Q , Bpp_solver , Vm , Va , pq ) : dVm = - Bpp_solver . solve ( Q ) # Update voltage. Vm [ pq ] = Vm [ pq ] + dVm V = Vm * exp ( 1j * Va ) return V , Vm , Va
Performs a Q iteration updates Vm .
81
9
801
def fmsin ( N , fnormin = 0.05 , fnormax = 0.45 , period = None , t0 = None , fnorm0 = 0.25 , pm1 = 1 ) : if period == None : period = N if t0 == None : t0 = N / 2 pm1 = nx . sign ( pm1 ) fnormid = 0.5 * ( fnormax + fnormin ) delta = 0.5 * ( fnormax - fnormin ) phi = - pm1 * nx . arccos ( ( fnorm0 - fnormid ) / delta )...
Signal with sinusoidal frequency modulation .
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802
def _parse_rdf ( self , file ) : store = Graph ( ) store . parse ( file ) print len ( store )
Returns a case from the given file .
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803
def load_plugins ( group = 'metrics.plugin.10' ) : # on using entrypoints: # http://stackoverflow.com/questions/774824/explain-python-entry-points file_processors = [ ] build_processors = [ ] for ep in pkg_resources . iter_entry_points ( group , name = None ) : log . debug ( 'loading \'%s\'' , ep ) plugin = ep . load (...
Load and installed metrics plugins .
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def read_case ( input , format = None ) : # Map of data file types to readers. format_map = { "matpower" : MATPOWERReader , "psse" : PSSEReader , "pickle" : PickleReader } # Read case data. if format_map . has_key ( format ) : reader_klass = format_map [ format ] reader = reader_klass ( ) case = reader . read ( input )...
Returns a case object from the given input file object . The data format may be optionally specified .
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def detect_data_file ( input , file_name = "" ) : _ , ext = os . path . splitext ( file_name ) if ext == ".m" : line = input . readline ( ) # first line if line . startswith ( "function" ) : type = "matpower" logger . info ( "Recognised MATPOWER data file." ) elif line . startswith ( "Bus.con" or line . startswith ( "%...
Detects the format of a network data file according to the file extension and the header .
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806
def write ( self , file_or_filename , prog = None , format = 'xdot' ) : if prog is None : file = super ( DotWriter , self ) . write ( file_or_filename ) else : buf = StringIO . StringIO ( ) super ( DotWriter , self ) . write ( buf ) buf . seek ( 0 ) data = self . create ( buf . getvalue ( ) , prog , format ) if isinsta...
Writes the case data in Graphviz DOT language .
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807
def write_bus_data ( self , file , padding = " " ) : for bus in self . case . buses : attrs = [ '%s="%s"' % ( k , v ) for k , v in self . bus_attr . iteritems ( ) ] # attrs.insert(0, 'label="%s"' % bus.name) attr_str = ", " . join ( attrs ) file . write ( "%s%s [%s];\n" % ( padding , bus . name , attr_str ) )
Writes bus data to file .
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808
def write_branch_data ( self , file , padding = " " ) : attrs = [ '%s="%s"' % ( k , v ) for k , v in self . branch_attr . iteritems ( ) ] attr_str = ", " . join ( attrs ) for br in self . case . branches : file . write ( "%s%s -> %s [%s];\n" % ( padding , br . from_bus . name , br . to_bus . name , attr_str ) )
Writes branch data in Graphviz DOT language .
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def write_generator_data ( self , file , padding = " " ) : attrs = [ '%s="%s"' % ( k , v ) for k , v in self . gen_attr . iteritems ( ) ] attr_str = ", " . join ( attrs ) edge_attrs = [ '%s="%s"' % ( k , v ) for k , v in { } . iteritems ( ) ] edge_attr_str = ", " . join ( edge_attrs ) for g in self . case . generators ...
Write generator data in Graphviz DOT language .
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def create ( self , dotdata , prog = "dot" , format = "xdot" ) : import os , tempfile from dot2tex . dotparsing import find_graphviz # Map Graphviz executable names to their paths. progs = find_graphviz ( ) if progs is None : logger . warning ( "GraphViz executables not found." ) return None if not progs . has_key ( pr...
Creates and returns a representation of the graph using the Graphviz layout program given by prog according to the given format .
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811
def format ( file_metrics , build_metrics ) : def indent ( elem , level = 0 ) : i = "\n" + level * " " if len ( elem ) : if not elem . text or not elem . text . strip ( ) : elem . text = i + " " if not elem . tail or not elem . tail . strip ( ) : elem . tail = i for elem in elem : indent ( elem , level + 1 ) if not ele...
compute output in XML format .
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def ask ( message = 'Are you sure? [y/N]' ) : agree = False answer = raw_input ( message ) . lower ( ) if answer . startswith ( 'y' ) : agree = True return agree
Asks the user his opinion .
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813
def main ( prog_args = None ) : if prog_args is None : prog_args = sys . argv parser = optparse . OptionParser ( ) parser . usage = """Usage: %[prog] [options] [<path>]""" parser . add_option ( "-t" , "--test-program" , dest = "test_program" , default = "nose" , help = "specifies the test-program to use. Valid values" ...
What do you expect?
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814
def check_configuration ( self , file_path , test_program , custom_args ) : # checking filepath if not os . path . isdir ( file_path ) : raise InvalidFilePath ( "INVALID CONFIGURATION: file path %s is not a directory" % os . path . abspath ( file_path ) ) if not test_program in IMPLEMENTED_TEST_PROGRAMS : raise Invalid...
Checks if configuration is ok .
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815
def check_dependencies ( self ) : if self . test_program == 'nose' : try : import nose except ImportError : sys . exit ( 'Nosetests is not available on your system. Please install it and try to run it again' ) if self . test_program == 'py' : try : import py except : sys . exit ( 'py.test is not available on your syste...
Checks if the test program is available in the python environnement
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def get_cmd ( self ) : cmd = None if self . test_program in ( 'nose' , 'nosetests' ) : cmd = "nosetests %s" % self . file_path elif self . test_program == 'django' : executable = "%s/manage.py" % self . file_path if os . path . exists ( executable ) : cmd = "python %s/manage.py test" % self . file_path else : cmd = "dj...
Returns the full command to be executed at runtime
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817
def include ( self , path ) : for extension in IGNORE_EXTENSIONS : if path . endswith ( extension ) : return False parts = path . split ( os . path . sep ) for part in parts : if part in self . ignore_dirs : return False return True
Returns True if the file is not ignored
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818
def diff_list ( self , list1 , list2 ) : for key in list1 : if key in list2 and list2 [ key ] != list1 [ key ] : print key elif key not in list2 : print key
Extracts differences between lists . For debug purposes
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819
def run ( self , cmd ) : print datetime . datetime . now ( ) output = subprocess . Popen ( cmd , shell = True ) output = output . communicate ( ) [ 0 ] print output
Runs the appropriate command
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820
def loop ( self ) : while True : sleep ( 1 ) new_file_list = self . walk ( self . file_path , { } ) if new_file_list != self . file_list : if self . debug : self . diff_list ( new_file_list , self . file_list ) self . run_tests ( ) self . file_list = new_file_list
Main loop daemon .
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821
def format ( file_metrics , build_metrics ) : metrics = { 'files' : file_metrics } if build_metrics : metrics [ 'build' ] = build_metrics body = json . dumps ( metrics , sort_keys = True , indent = 4 ) + '\n' return body
compute output in JSON format .
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822
def split_linear_constraints ( A , l , u ) : ieq = [ ] igt = [ ] ilt = [ ] ibx = [ ] for i in range ( len ( l ) ) : if abs ( u [ i ] - l [ i ] ) <= EPS : ieq . append ( i ) elif ( u [ i ] > 1e10 ) and ( l [ i ] > - 1e10 ) : igt . append ( i ) elif ( l [ i ] <= - 1e10 ) and ( u [ i ] < 1e10 ) : ilt . append ( i ) elif (...
Returns the linear equality and inequality constraints .
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823
def dSbus_dV ( Y , V ) : I = Y * V diagV = spdiag ( V ) diagIbus = spdiag ( I ) diagVnorm = spdiag ( div ( V , abs ( V ) ) ) # Element-wise division. dS_dVm = diagV * conj ( Y * diagVnorm ) + conj ( diagIbus ) * diagVnorm dS_dVa = 1j * diagV * conj ( diagIbus - Y * diagV ) return dS_dVm , dS_dVa
Computes the partial derivative of power injection w . r . t . voltage .
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def dIbr_dV ( Yf , Yt , V ) : # nb = len(V) Vnorm = div ( V , abs ( V ) ) diagV = spdiag ( V ) diagVnorm = spdiag ( Vnorm ) dIf_dVa = Yf * 1j * diagV dIf_dVm = Yf * diagVnorm dIt_dVa = Yt * 1j * diagV dIt_dVm = Yt * diagVnorm # Compute currents. If = Yf * V It = Yt * V return dIf_dVa , dIf_dVm , dIt_dVa , dIt_dVm , If ...
Computes partial derivatives of branch currents w . r . t . voltage .
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def dSbr_dV ( Yf , Yt , V , buses , branches ) : nl = len ( branches ) nb = len ( V ) f = matrix ( [ l . from_bus . _i for l in branches ] ) t = matrix ( [ l . to_bus . _i for l in branches ] ) # Compute currents. If = Yf * V It = Yt * V Vnorm = div ( V , abs ( V ) ) diagVf = spdiag ( V [ f ] ) diagIf = spdiag ( If ) d...
Computes the branch power flow vector and the partial derivative of branch power flow w . r . t voltage .
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826
def dAbr_dV ( dSf_dVa , dSf_dVm , dSt_dVa , dSt_dVm , Sf , St ) : dAf_dPf = spdiag ( 2 * Sf . real ( ) ) dAf_dQf = spdiag ( 2 * Sf . imag ( ) ) dAt_dPt = spdiag ( 2 * St . real ( ) ) dAt_dQt = spdiag ( 2 * St . imag ( ) ) # Partial derivative of apparent power magnitude w.r.t voltage # phase angle. dAf_dVa = dAf_dPf * ...
Partial derivatives of squared flow magnitudes w . r . t voltage .
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def d2Sbus_dV2 ( Ybus , V , lam ) : n = len ( V ) Ibus = Ybus * V diaglam = spdiag ( lam ) diagV = spdiag ( V ) A = spmatrix ( mul ( lam , V ) , range ( n ) , range ( n ) ) B = Ybus * diagV C = A * conj ( B ) D = Ybus . H * diagV E = conj ( diagV ) * ( D * diaglam - spmatrix ( D * lam , range ( n ) , range ( n ) ) ) F ...
Computes 2nd derivatives of power injection w . r . t . voltage .
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828
def d2Ibr_dV2 ( Ybr , V , lam ) : nb = len ( V ) diaginvVm = spdiag ( div ( matrix ( 1.0 , ( nb , 1 ) ) , abs ( V ) ) ) Haa = spdiag ( mul ( - ( Ybr . T * lam ) , V ) ) Hva = - 1j * Haa * diaginvVm Hav = Hva Hvv = spmatrix ( [ ] , [ ] , [ ] , ( nb , nb ) ) return Haa , Hav , Hva , Hvv
Computes 2nd derivatives of complex branch current w . r . t . voltage .
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829
def d2Sbr_dV2 ( Cbr , Ybr , V , lam ) : nb = len ( V ) diaglam = spdiag ( lam ) diagV = spdiag ( V ) A = Ybr . H * diaglam * Cbr B = conj ( diagV ) * A * diagV D = spdiag ( mul ( ( A * V ) , conj ( V ) ) ) E = spdiag ( mul ( ( A . T * conj ( V ) ) , V ) ) F = B + B . T G = spdiag ( div ( matrix ( 1.0 , ( nb , 1 ) ) , a...
Computes 2nd derivatives of complex power flow w . r . t . voltage .
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830
def tocvx ( B ) : Bcoo = B . tocoo ( ) return spmatrix ( Bcoo . data , Bcoo . row . tolist ( ) , Bcoo . col . tolist ( ) )
Converts a sparse SciPy matrix into a sparse CVXOPT matrix .
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831
def doInteractions ( self , number = 1 ) : t0 = time . time ( ) for _ in range ( number ) : self . _oneInteraction ( ) elapsed = time . time ( ) - t0 logger . info ( "%d interactions executed in %.3fs." % ( number , elapsed ) ) return self . stepid
Directly maps the agents and the tasks .
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832
def exciter ( self , Xexc , Pexc , Vexc ) : exciters = self . exciters F = zeros ( Xexc . shape ) typ1 = [ e . generator . _i for e in exciters if e . model == CONST_EXCITATION ] typ2 = [ e . generator . _i for e in exciters if e . model == IEEE_DC1A ] # Exciter type 1: constant excitation F [ typ1 , : ] = 0.0 # Excite...
Exciter model .
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833
def governor ( self , Xgov , Pgov , Vgov ) : governors = self . governors omegas = 2 * pi * self . freq F = zeros ( Xgov . shape ) typ1 = [ g . generator . _i for g in governors if g . model == CONST_POWER ] typ2 = [ g . generator . _i for g in governors if g . model == GENERAL_IEEE ] # Governor type 1: constant power ...
Governor model .
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834
def generator ( self , Xgen , Xexc , Xgov , Vgen ) : generators = self . dyn_generators omegas = 2 * pi * self . freq F = zeros ( Xgen . shape ) typ1 = [ g . _i for g in generators if g . model == CLASSICAL ] typ2 = [ g . _i for g in generators if g . model == FOURTH_ORDER ] # Generator type 1: classical model omega = ...
Generator model .
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835
def _write_data ( self , file ) : self . write_case_data ( file ) file . write ( "Bus Data\n" ) file . write ( "-" * 8 + "\n" ) self . write_bus_data ( file ) file . write ( "\n" ) file . write ( "Branch Data\n" ) file . write ( "-" * 11 + "\n" ) self . write_branch_data ( file ) file . write ( "\n" ) file . write ( "G...
Writes case data to file in ReStructuredText format .
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def write_bus_data ( self , file ) : report = CaseReport ( self . case ) buses = self . case . buses col_width = 8 col_width_2 = col_width * 2 + 1 col1_width = 6 sep = "=" * 6 + " " + ( "=" * col_width + " " ) * 6 + "\n" file . write ( sep ) # Line one of column headers file . write ( "Name" . center ( col1_width ) + "...
Writes bus data to a ReST table .
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837
def write_how_many ( self , file ) : report = CaseReport ( self . case ) # Map component labels to attribute names components = [ ( "Bus" , "n_buses" ) , ( "Generator" , "n_generators" ) , ( "Committed Generator" , "n_online_generators" ) , ( "Load" , "n_loads" ) , ( "Fixed Load" , "n_fixed_loads" ) , ( "Despatchable L...
Writes component numbers to a table .
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838
def write_min_max ( self , file ) : report = CaseReport ( self . case ) col1_header = "Attribute" col1_width = 19 col2_header = "Minimum" col3_header = "Maximum" col_width = 22 sep = "=" * col1_width + " " + "=" * col_width + " " + "=" * col_width + "\n" # Row headers file . write ( sep ) file . write ( "%s" % col1_hea...
Writes minimum and maximum values to a table .
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839
def make_unique_name ( base , existing = [ ] , format = "%s_%s" ) : count = 2 name = base while name in existing : name = format % ( base , count ) count += 1 return name
Return a name unique within a context based on the specified name .
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840
def call_antlr4 ( arg ) : # pylint: disable=unused-argument, unused-variable antlr_path = os . path . join ( ROOT_DIR , "java" , "antlr-4.7-complete.jar" ) classpath = os . pathsep . join ( [ "." , "{:s}" . format ( antlr_path ) , "$CLASSPATH" ] ) generated = os . path . join ( ROOT_DIR , 'src' , 'pymoca' , 'generated'...
calls antlr4 on grammar file
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def setup_package ( ) : with open ( 'requirements.txt' , 'r' ) as req_file : install_reqs = req_file . read ( ) . split ( '\n' ) cmdclass_ = { 'antlr' : AntlrBuildCommand } cmdclass_ . update ( versioneer . get_cmdclass ( ) ) setup ( version = versioneer . get_version ( ) , name = 'pymoca' , maintainer = "James Goppert...
Setup the package .
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def body ( self , frame ) : master = Frame ( self ) master . pack ( padx = 5 , pady = 0 , expand = 1 , fill = BOTH ) title = Label ( master , text = "Buses" ) title . pack ( side = TOP ) bus_lb = self . bus_lb = Listbox ( master , selectmode = SINGLE , width = 10 ) bus_lb . pack ( side = LEFT ) for bus in self . case ....
Creates the dialog body . Returns the widget that should have initial focus .
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def solve ( self , solver_klass = None ) : # Start the clock. t0 = time ( ) # Build an OPF model with variables and constraints. om = self . _construct_opf_model ( self . case ) if om is None : return { "converged" : False , "output" : { "message" : "No Ref Bus." } } # Call the specific solver. # if self.opt["verbose"]...
Solves an optimal power flow and returns a results dictionary .
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844
def _construct_opf_model ( self , case ) : # Zero the case result attributes. self . case . reset ( ) base_mva = case . base_mva # Check for one reference bus. oneref , refs = self . _ref_check ( case ) if not oneref : #return {"status": "error"} None # Remove isolated components. bs , ln , gn = self . _remove_isolated...
Returns an OPF model .
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845
def _ref_check ( self , case ) : refs = [ bus . _i for bus in case . buses if bus . type == REFERENCE ] if len ( refs ) == 1 : return True , refs else : logger . error ( "OPF requires a single reference bus." ) return False , refs
Checks that there is only one reference bus .
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846
def _remove_isolated ( self , case ) : # case.deactivate_isolated() buses = case . connected_buses branches = case . online_branches gens = case . online_generators return buses , branches , gens
Returns non - isolated case components .
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847
def _pwl1_to_poly ( self , generators ) : for g in generators : if ( g . pcost_model == PW_LINEAR ) and ( len ( g . p_cost ) == 2 ) : g . pwl_to_poly ( ) return generators
Converts single - block piecewise - linear costs into linear polynomial .
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848
def _get_voltage_angle_var ( self , refs , buses ) : Va = array ( [ b . v_angle * ( pi / 180.0 ) for b in buses ] ) Vau = Inf * ones ( len ( buses ) ) Val = - Vau Vau [ refs ] = Va [ refs ] Val [ refs ] = Va [ refs ] return Variable ( "Va" , len ( buses ) , Va , Val , Vau )
Returns the voltage angle variable set .
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849
def _get_voltage_magnitude_var ( self , buses , generators ) : Vm = array ( [ b . v_magnitude for b in buses ] ) # For buses with generators initialise Vm from gen data. for g in generators : Vm [ g . bus . _i ] = g . v_magnitude Vmin = array ( [ b . v_min for b in buses ] ) Vmax = array ( [ b . v_max for b in buses ] ...
Returns the voltage magnitude variable set .
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850
def _get_pgen_var ( self , generators , base_mva ) : Pg = array ( [ g . p / base_mva for g in generators ] ) Pmin = array ( [ g . p_min / base_mva for g in generators ] ) Pmax = array ( [ g . p_max / base_mva for g in generators ] ) return Variable ( "Pg" , len ( generators ) , Pg , Pmin , Pmax )
Returns the generator active power set - point variable .
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def _get_qgen_var ( self , generators , base_mva ) : Qg = array ( [ g . q / base_mva for g in generators ] ) Qmin = array ( [ g . q_min / base_mva for g in generators ] ) Qmax = array ( [ g . q_max / base_mva for g in generators ] ) return Variable ( "Qg" , len ( generators ) , Qg , Qmin , Qmax )
Returns the generator reactive power variable set .
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852
def _nln_constraints ( self , nb , nl ) : Pmis = NonLinearConstraint ( "Pmis" , nb ) Qmis = NonLinearConstraint ( "Qmis" , nb ) Sf = NonLinearConstraint ( "Sf" , nl ) St = NonLinearConstraint ( "St" , nl ) return Pmis , Qmis , Sf , St
Returns non - linear constraints for OPF .
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853
def _const_pf_constraints ( self , gn , base_mva ) : ivl = array ( [ i for i , g in enumerate ( gn ) if g . is_load and ( g . q_min != 0.0 or g . q_max != 0.0 ) ] ) vl = [ gn [ i ] for i in ivl ] nvl = len ( vl ) ng = len ( gn ) Pg = array ( [ g . p for g in vl ] ) / base_mva Qg = array ( [ g . q for g in vl ] ) / base...
Returns a linear constraint enforcing constant power factor for dispatchable loads .
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854
def _voltage_angle_diff_limit ( self , buses , branches ) : nb = len ( buses ) if not self . ignore_ang_lim : iang = [ i for i , b in enumerate ( branches ) if ( b . ang_min and ( b . ang_min > - 360.0 ) ) or ( b . ang_max and ( b . ang_max < 360.0 ) ) ] iangl = array ( [ i for i , b in enumerate ( branches ) if b . an...
Returns the constraint on the branch voltage angle differences .
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def add_var ( self , var ) : if var . name in [ v . name for v in self . vars ] : logger . error ( "Variable set named '%s' already exists." % var . name ) return var . i1 = self . var_N var . iN = self . var_N + var . N - 1 self . vars . append ( var )
Adds a variable to the model .
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856
def get_var ( self , name ) : for var in self . vars : if var . name == name : return var else : raise ValueError
Returns the variable set with the given name .
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857
def linear_constraints ( self ) : if self . lin_N == 0 : return None , array ( [ ] ) , array ( [ ] ) A = lil_matrix ( ( self . lin_N , self . var_N ) , dtype = float64 ) l = - Inf * ones ( self . lin_N ) u = - l for lin in self . lin_constraints : if lin . N : # non-zero number of rows to add Ak = lin . A # A for kth l...
Returns the linear constraints .
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def add_constraint ( self , con ) : if isinstance ( con , LinearConstraint ) : N , M = con . A . shape if con . name in [ c . name for c in self . lin_constraints ] : logger . error ( "Constraint set named '%s' already exists." % con . name ) return False else : con . i1 = self . lin_N # + 1 con . iN = self . lin_N + N...
Adds a constraint to the model .
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def _solve ( self , x0 , A , l , u , xmin , xmax ) : # Indexes of constrained lines. il = [ i for i , ln in enumerate ( self . _ln ) if 0.0 < ln . rate_a < 1e10 ] nl2 = len ( il ) neqnln = 2 * self . _nb # no. of non-linear equality constraints niqnln = 2 * len ( il ) # no. of lines with constraints user_data = { "A" :...
Solves using the Interior Point OPTimizer .
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def doOutages ( self ) : assert len ( self . branchOutages ) == len ( self . market . case . branches ) weights = [ [ ( False , r ) , ( True , 1 - ( r ) ) ] for r in self . branchOutages ] for i , ln in enumerate ( self . market . case . branches ) : ln . online = weighted_choice ( weights [ i ] ) if ln . online == Fal...
Applies branch outtages .
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def reset_case ( self ) : for bus in self . market . case . buses : bus . p_demand = self . pdemand [ bus ] for task in self . tasks : for g in task . env . generators : g . p = task . env . _g0 [ g ] [ "p" ] g . p_max = task . env . _g0 [ g ] [ "p_max" ] g . p_min = task . env . _g0 [ g ] [ "p_min" ] g . q = task . en...
Returns the case to its original state .
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def doEpisodes ( self , number = 1 ) : for episode in range ( number ) : print "Starting episode %d." % episode # Initialise the profile cycle. if len ( self . profile . shape ) == 1 : # 1D array self . _pcycle = cycle ( self . profile ) else : assert self . profile . shape [ 0 ] >= number self . _pcycle = cycle ( self...
Do the given numer of episodes and return the rewards of each step as a list .
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def reset ( self ) : self . stepid = 0 for task , agent in zip ( self . tasks , self . agents ) : task . reset ( ) agent . module . reset ( ) agent . history . reset ( )
Sets initial conditions for the experiment .
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864
def _updatePropensities ( self , lastState , lastAction , reward ) : phi = self . recency for action in range ( self . module . numActions ) : carryOver = ( 1 - phi ) * self . module . getValue ( lastState , action ) experience = self . _experience ( lastState , action , lastAction , reward ) self . module . updateValu...
Update the propensities for all actions . The propensity for last action chosen will be updated using the feedback value that resulted from performing the action .
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865
def _forwardImplementation ( self , inbuf , outbuf ) : assert self . module propensities = self . module . getActionValues ( 0 ) summedProps = sum ( propensities ) probabilities = propensities / summedProps action = eventGenerator ( probabilities ) # action = drawIndex(probabilities) outbuf [ : ] = scipy . array ( [ ac...
Proportional probability method .
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866
def write ( self , file_or_filename ) : self . book = Workbook ( ) self . _write_data ( None ) self . book . save ( file_or_filename )
Writes case data to file in Excel format .
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867
def write_bus_data ( self , file ) : bus_sheet = self . book . add_sheet ( "Buses" ) for i , bus in enumerate ( self . case . buses ) : for j , attr in enumerate ( BUS_ATTRS ) : bus_sheet . write ( i , j , getattr ( bus , attr ) )
Writes bus data to an Excel spreadsheet .
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def write_branch_data ( self , file ) : branch_sheet = self . book . add_sheet ( "Branches" ) for i , branch in enumerate ( self . case . branches ) : for j , attr in enumerate ( BRANCH_ATTRS ) : branch_sheet . write ( i , j , getattr ( branch , attr ) )
Writes branch data to an Excel spreadsheet .
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def write_generator_data ( self , file ) : generator_sheet = self . book . add_sheet ( "Generators" ) for j , generator in enumerate ( self . case . generators ) : i = generator . bus . _i for k , attr in enumerate ( GENERATOR_ATTRS ) : generator_sheet . write ( j , 0 , i )
Write generator data to file .
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def write ( self , file_or_filename ) : if isinstance ( file_or_filename , basestring ) : file = open ( file_or_filename , "wb" ) else : file = file_or_filename self . writer = csv . writer ( file ) super ( CSVWriter , self ) . write ( file )
Writes case data as CSV .
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def write_case_data ( self , file ) : writer = self . _get_writer ( file ) writer . writerow ( [ "Name" , "base_mva" ] ) writer . writerow ( [ self . case . name , self . case . base_mva ] )
Writes the case data as CSV .
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def write_bus_data ( self , file ) : writer = self . _get_writer ( file ) writer . writerow ( BUS_ATTRS ) for bus in self . case . buses : writer . writerow ( [ getattr ( bus , attr ) for attr in BUS_ATTRS ] )
Writes bus data as CSV .
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def write_branch_data ( self , file ) : writer = self . _get_writer ( file ) writer . writerow ( BRANCH_ATTRS ) for branch in self . case . branches : writer . writerow ( [ getattr ( branch , a ) for a in BRANCH_ATTRS ] )
Writes branch data as CSV .
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def write_generator_data ( self , file ) : writer = self . _get_writer ( file ) writer . writerow ( [ "bus" ] + GENERATOR_ATTRS ) for g in self . case . generators : i = g . bus . _i writer . writerow ( [ i ] + [ getattr ( g , a ) for a in GENERATOR_ATTRS ] )
Write generator data as CSV .
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def run ( self ) : # Start the clock. t0 = time . time ( ) # Manage reactive power offers/bids. haveQ = self . _isReactiveMarket ( ) # Withhold offers/bids outwith optional price limits. self . _withholdOffbids ( ) # Convert offers/bids to pwl functions and update limits. self . _offbidToCase ( ) # Compute dispatch poi...
Computes cleared offers and bids .
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def _runOPF ( self ) : if self . decommit : solver = UDOPF ( self . case , dc = ( self . locationalAdjustment == "dc" ) ) elif self . locationalAdjustment == "dc" : solver = OPF ( self . case , dc = True ) else : solver = OPF ( self . case , dc = False , opt = { "verbose" : True } ) self . _solution = solver . solve ( ...
Computes dispatch points and LMPs using OPF .
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def encode ( self , o ) : # This doesn't pass the iterator directly to ''.join() because it # sucks at reporting exceptions. It's going to do this internally # anyway because it uses PySequence_Fast or similar. chunks = list ( self . iterencode ( o ) ) return '' . join ( chunks )
Return a JSON string representation of a Python data structure .
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def compute_file_metrics ( processors , language , key , token_list ) : # multiply iterator tli = itertools . tee ( token_list , len ( processors ) ) metrics = OrderedDict ( ) # reset all processors for p in processors : p . reset ( ) # process all tokens for p , tl in zip ( processors , tli ) : p . process_file ( lang...
use processors to compute file metrics .
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def load ( self , lemmatizer_path ) : self . lemmatizer = { } with io . open ( lemmatizer_path , encoding = 'utf-8' ) as data_file : raw = json . load ( data_file ) for entry in raw : self . lemmatizer [ entry [ "Form" ] ] = entry [ "Lemmas" ] self . apply_blacklist ( )
This methods load the IWNLP . Lemmatizer json file and creates a dictionary of lowercased forms which maps each form to its possible lemmas .
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def write ( self , file_or_filename ) : if isinstance ( file_or_filename , basestring ) : file = None try : file = open ( file_or_filename , "wb" ) except Exception , detail : logger . error ( "Error opening %s." % detail ) finally : if file is not None : self . _write_data ( file ) file . close ( ) else : file = file_...
Writes the case data to file .
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def performAction ( self , action ) : self . t += 1 super ( ProfitTask , self ) . performAction ( int ( action [ 0 ] ) ) self . samples += 1
The action vector is stripped and the only element is cast to integer and given to the super class .
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def addReward ( self , r = None ) : r = self . getReward ( ) if r is None else r # by default, the cumulative reward is just the sum over the episode if self . discount : self . cumulativeReward += power ( self . discount , self . samples ) * r else : self . cumulativeReward += r
A filtered mapping towards performAction of the underlying environment .
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def getV0 ( self , v_mag_guess , buses , generators , type = CASE_GUESS ) : if type == CASE_GUESS : Va = array ( [ b . v_angle * ( pi / 180.0 ) for b in buses ] ) Vm = array ( [ b . v_magnitude for b in buses ] ) V0 = Vm * exp ( 1j * Va ) elif type == FLAT_START : V0 = ones ( len ( buses ) ) elif type == FROM_INPUT : V...
Returns the initial voltage profile .
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def output_solution ( self , fd , z , z_est , error_sqrsum ) : col_width = 11 sep = ( "=" * col_width + " " ) * 4 + "\n" fd . write ( "State Estimation\n" ) fd . write ( "-" * 16 + "\n" ) fd . write ( sep ) fd . write ( "Type" . center ( col_width ) + " " ) fd . write ( "Name" . center ( col_width ) + " " ) fd . write ...
Prints comparison of measurements and their estimations .
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def run ( self ) : # Compute cleared offer/bid quantities from total dispatched quantity. self . _clearQuantities ( ) # Compute shift values to add to lam to get desired pricing. # lao, fro, lab, frb = self._first_rejected_last_accepted() # Clear offer/bid prices according to auction type. self . _clearPrices ( ) # sel...
Clears a set of bids and offers .
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def _clearQuantity ( self , offbids , gen ) : # Filter out offers/bids not applicable to the generator in question. gOffbids = [ offer for offer in offbids if offer . generator == gen ] # Offers/bids within valid price limits (not withheld). valid = [ ob for ob in gOffbids if not ob . withheld ] # Sort offers by price ...
Computes the cleared bid quantity from total dispatched quantity .
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def _clearPrices ( self ) : for offbid in self . offers + self . bids : if self . auctionType == DISCRIMINATIVE : offbid . clearedPrice = offbid . price elif self . auctionType == FIRST_PRICE : offbid . clearedPrice = offbid . lmbda else : raise ValueError
Clears prices according to auction type .
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def _clipPrices ( self ) : # Guarantee that cleared offer prices are >= offers. if self . guaranteeOfferPrice : for offer in self . offers : if offer . accepted and offer . clearedPrice < offer . price : offer . clearedPrice = offer . price # Guarantee that cleared bid prices are <= bids. if self . guaranteeBidPrice : ...
Clip cleared prices according to guarantees and limits .
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def wait_for_response ( client , timeout , path = '/' , expected_status_code = None ) : # We want time.monotonic on Pythons that have it, otherwise time.time will # have to do. get_time = getattr ( time , 'monotonic' , time . time ) deadline = get_time ( ) + timeout while True : try : # Don't care what the response is,...
Try make a GET request with an HTTP client against a certain path and return once any response has been received ignoring any errors .
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def request ( self , method , path = None , url_kwargs = None , * * kwargs ) : return self . _session . request ( method , self . _url ( path , url_kwargs ) , * * kwargs )
Make a request against a container .
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def options ( self , path = None , url_kwargs = None , * * kwargs ) : return self . _session . options ( self . _url ( path , url_kwargs ) , * * kwargs )
Sends an OPTIONS request .
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def head ( self , path = None , url_kwargs = None , * * kwargs ) : return self . _session . head ( self . _url ( path , url_kwargs ) , * * kwargs )
Sends a HEAD request .
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def post ( self , path = None , url_kwargs = None , * * kwargs ) : return self . _session . post ( self . _url ( path , url_kwargs ) , * * kwargs )
Sends a POST request .
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def iuwt_decomposition ( in1 , scale_count , scale_adjust = 0 , mode = 'ser' , core_count = 2 , store_smoothed = False , store_on_gpu = False ) : if mode == 'ser' : return ser_iuwt_decomposition ( in1 , scale_count , scale_adjust , store_smoothed ) elif mode == 'mp' : return mp_iuwt_decomposition ( in1 , scale_count , ...
This function serves as a handler for the different implementations of the IUWT decomposition . It allows the different methods to be used almost interchangeably .
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def iuwt_recomposition ( in1 , scale_adjust = 0 , mode = 'ser' , core_count = 1 , store_on_gpu = False , smoothed_array = None ) : if mode == 'ser' : return ser_iuwt_recomposition ( in1 , scale_adjust , smoothed_array ) elif mode == 'mp' : return mp_iuwt_recomposition ( in1 , scale_adjust , core_count , smoothed_array ...
This function serves as a handler for the different implementations of the IUWT recomposition . It allows the different methods to be used almost interchangeably .
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def ser_iuwt_decomposition ( in1 , scale_count , scale_adjust , store_smoothed ) : wavelet_filter = ( 1. / 16 ) * np . array ( [ 1 , 4 , 6 , 4 , 1 ] ) # Filter-bank for use in the a trous algorithm. # Initialises an empty array to store the coefficients. detail_coeffs = np . empty ( [ scale_count - scale_adjust , in1 ....
This function calls the a trous algorithm code to decompose the input into its wavelet coefficients . This is the isotropic undecimated wavelet transform implemented for a single CPU core .
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def ser_iuwt_recomposition ( in1 , scale_adjust , smoothed_array ) : wavelet_filter = ( 1. / 16 ) * np . array ( [ 1 , 4 , 6 , 4 , 1 ] ) # Filter-bank for use in the a trous algorithm. # Determines scale with adjustment and creates a zero array to store the output, unless smoothed_array is given. max_scale = in1 . shap...
This function calls the a trous algorithm code to recompose the input into a single array . This is the implementation of the isotropic undecimated wavelet transform recomposition for a single CPU core .
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def mp_iuwt_recomposition ( in1 , scale_adjust , core_count , smoothed_array ) : wavelet_filter = ( 1. / 16 ) * np . array ( [ 1 , 4 , 6 , 4 , 1 ] ) # Filter-bank for use in the a trous algorithm. # Determines scale with adjustment and creates a zero array to store the output, unless smoothed_array is given. max_scale ...
This function calls the a trous algorithm code to recompose the input into a single array . This is the implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores .
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def gpu_iuwt_recomposition ( in1 , scale_adjust , store_on_gpu , smoothed_array ) : wavelet_filter = ( 1. / 16 ) * np . array ( [ 1 , 4 , 6 , 4 , 1 ] , dtype = np . float32 ) # Filter-bank for use in the a trous algorithm. wavelet_filter = gpuarray . to_gpu_async ( wavelet_filter ) # Determines scale with adjustment an...
This function calls the a trous algorithm code to recompose the input into a single array . This is the implementation of the isotropic undecimated wavelet transform recomposition for a GPU .
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