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def FDMT ( data , f_min , f_max , maxDT , dataType ) : """This function implements the FDMT algorithm . Input : Input visibility array ( nints , nbl , nchan , npol ) f _ min , f _ max are the base - band begin and end frequencies . The frequencies should be entered in MHz maxDT - the maximal delay ( in time bins ) of the maximal dispersion . Appears in the paper as N _ { \ Delta } A typical input is maxDT = N _ f dataType - a valid numpy dtype . reccomended : either int32 , or int64. Output : The dispersion measure transform of the Input matrix . The output dimensions are [ Input . shape [ 1 ] , maxDT ] For details , see algorithm 1 in Zackay & Ofek ( 2014)"""
nint , nbl , nchan , npol = data . shape niters = int ( np . log2 ( nchan ) ) assert nchan in 2 ** np . arange ( 30 ) and nint in 2 ** np . arange ( 30 ) , "Input dimensions must be a power of 2" logger . info ( 'Input data dimensions: {0}' . format ( data . shape ) ) data = FDMT_initialization ( data , f_min , f_max , maxDT , dataType ) logger . info ( 'Iterating {0} times to calculate to maxDT of {1}' . format ( niters , maxDT ) ) for i_t in range ( 1 , niters + 1 ) : data = FDMT_iteration ( data , maxDT , nchan , f_min , f_max , i_t , dataType ) [ nint , dT , nbl , nchan , npol ] = data . shape assert nchan == 1 , 'Channel axis should have length 1 after all FDMT iterations.' # put dT axis first and remove chan axis return np . rollaxis ( data [ : , : , : , 0 , : ] , 1 )
def _get_dvs_infrastructure_traffic_resources ( dvs_name , dvs_infra_traffic_ress ) : '''Returns a list of dict representations of the DVS infrastructure traffic resource dvs _ name The name of the DVS dvs _ infra _ traffic _ ress The DVS infrastructure traffic resources'''
log . trace ( 'Building the dicts of the DVS \'%s\' infrastructure ' 'traffic resources' , dvs_name ) res_dicts = [ ] for res in dvs_infra_traffic_ress : res_dict = { 'key' : res . key , 'limit' : res . allocationInfo . limit , 'reservation' : res . allocationInfo . reservation } if res . allocationInfo . shares : res_dict . update ( { 'num_shares' : res . allocationInfo . shares . shares , 'share_level' : res . allocationInfo . shares . level } ) res_dicts . append ( res_dict ) return res_dicts
def arch_to_personality ( arch ) : """Determine the process personality corresponding to the architecture"""
if isinstance ( arch , bytes ) : arch = unicode ( arch ) return _lxc . arch_to_personality ( arch )
def _parseAtNamespace ( self , src ) : """namespace : @ namespace S * [ IDENT S * ] ? [ STRING | URI ] S * ' ; ' S *"""
src = self . _parseSCDOCDC ( src ) while isAtRuleIdent ( src , 'namespace' ) : ctxsrc = src src = stripAtRuleIdent ( src ) namespace , src = self . _getStringOrURI ( src ) if namespace is None : nsPrefix , src = self . _getIdent ( src ) if nsPrefix is None : raise self . ParseError ( '@namespace expected an identifier or a URI' , src , ctxsrc ) namespace , src = self . _getStringOrURI ( src . lstrip ( ) ) if namespace is None : raise self . ParseError ( '@namespace expected a URI' , src , ctxsrc ) else : nsPrefix = None src = src . lstrip ( ) if src [ : 1 ] != ';' : raise self . ParseError ( '@namespace expected a terminating \';\'' , src , ctxsrc ) src = src [ 1 : ] . lstrip ( ) self . cssBuilder . atNamespace ( nsPrefix , namespace ) src = self . _parseSCDOCDC ( src ) return src
def service_desks ( self ) : """Get a list of ServiceDesk Resources from the server visible to the current authenticated user . : rtype : List [ ServiceDesk ]"""
url = self . _options [ 'server' ] + '/rest/servicedeskapi/servicedesk' headers = { 'X-ExperimentalApi' : 'opt-in' } r_json = json_loads ( self . _session . get ( url , headers = headers ) ) projects = [ ServiceDesk ( self . _options , self . _session , raw_project_json ) for raw_project_json in r_json [ 'values' ] ] return projects
def _setable_set_ ( name , self , func ) : "Used to set the attribute a single time using the given function ."
setattr ( self . _attr_data_ , name , func ( ) ) if hasattr ( self . _attr_func_ , name ) : delattr ( self . _attr_func_ , name ) setattr ( type ( self ) , name , property ( functools . partial ( self . _simple_get_ , name ) ) )
def generate ( cls ) : """Generates a random : class : ` ~ SigningKey ` object . : rtype : : class : ` ~ SigningKey `"""
return cls ( libnacl . randombytes ( libnacl . crypto_sign_SEEDBYTES ) , encoder = encoding . RawEncoder , )
def rule_metric_names ( self ) : """Returns the rule metric names of the association rules . Only if implements AssociationRulesProducer . : return : the metric names : rtype : list"""
if not self . check_type ( self . jobject , "weka.associations.AssociationRulesProducer" ) : return None return string_array_to_list ( javabridge . call ( self . jobject , "getRuleMetricNames" , "()[Ljava/lang/String;" ) )
def plotF0 ( fromTuple , toTuple , mergeTupleList , fnFullPath ) : '''Plots the original data in a graph above the plot of the dtw ' ed data'''
_matplotlibCheck ( ) plt . hold ( True ) fig , ( ax0 ) = plt . subplots ( nrows = 1 ) # Old data plot1 = ax0 . plot ( fromTuple [ 0 ] , fromTuple [ 1 ] , color = 'red' , linewidth = 2 , label = "From" ) plot2 = ax0 . plot ( toTuple [ 0 ] , toTuple [ 1 ] , color = 'blue' , linewidth = 2 , label = "To" ) ax0 . set_title ( "Plot of F0 Morph" ) plt . ylabel ( 'Pitch (hz)' ) plt . xlabel ( 'Time (s)' ) # Merge data colorValue = 0 colorStep = 255.0 / len ( mergeTupleList ) for timeList , valueList in mergeTupleList : colorValue += colorStep hexValue = "#%02x0000" % int ( 255 - colorValue ) if int ( colorValue ) == 255 : ax0 . plot ( timeList , valueList , color = hexValue , linewidth = 1 , label = "Merged line, final iteration" ) else : ax0 . plot ( timeList , valueList , color = hexValue , linewidth = 1 ) plt . legend ( loc = 1 , borderaxespad = 0. ) # plt . legend ( [ plot1 , plot2 , plot3 ] , [ " From " , " To " , " Merged line " ] ) plt . savefig ( fnFullPath , dpi = 300 , bbox_inches = 'tight' ) plt . close ( fig )
def next ( self ) : """Returns the next input from this input reader , a record . Returns : The next input from this input reader in the form of a record read from an LevelDB file . Raises : StopIteration : The ordered set records has been exhausted ."""
while True : if not hasattr ( self , "_cur_handle" ) or self . _cur_handle is None : # If there are no more files , StopIteration is raised here self . _cur_handle = super ( _GoogleCloudStorageRecordInputReader , self ) . next ( ) if not hasattr ( self , "_record_reader" ) or self . _record_reader is None : self . _record_reader = records . RecordsReader ( self . _cur_handle ) try : start_time = time . time ( ) content = self . _record_reader . read ( ) ctx = context . get ( ) if ctx : operation . counters . Increment ( COUNTER_IO_READ_BYTES , len ( content ) ) ( ctx ) operation . counters . Increment ( COUNTER_IO_READ_MSEC , int ( ( time . time ( ) - start_time ) * 1000 ) ) ( ctx ) return content except EOFError : self . _cur_handle = None self . _record_reader = None
def change_engine_password ( self , password ) : """Change Engine password for engines on allowed list . : param str password : password for engine level : raises ModificationFailed : failed setting password on engine : return : None"""
self . make_request ( ModificationFailed , method = 'update' , resource = 'change_engine_password' , params = { 'password' : password } )
def resolve ( self , cfg , addr , func_addr , block , jumpkind ) : """Resolves jump tables . : param cfg : A CFG instance . : param int addr : IRSB address . : param int func _ addr : The function address . : param pyvex . IRSB block : The IRSB . : return : A bool indicating whether the indirect jump is resolved successfully , and a list of resolved targets : rtype : tuple"""
project = self . project # short - hand self . _max_targets = cfg . _indirect_jump_target_limit # Perform a backward slicing from the jump target b = Blade ( cfg . graph , addr , - 1 , cfg = cfg , project = project , ignore_sp = False , ignore_bp = False , max_level = 3 , base_state = self . base_state ) stmt_loc = ( addr , DEFAULT_STATEMENT ) if stmt_loc not in b . slice : return False , None load_stmt_loc , load_stmt , load_size = None , None , None stmts_to_remove = [ stmt_loc ] stmts_adding_base_addr = [ ] # type : list [ JumpTargetBaseAddr ] # All temporary variables that hold indirect addresses loaded out of the memory # Obviously , load _ stmt . tmp must be here # if there are additional data transferring statements between the Load statement and the base - address - adding # statement , all _ addr _ holders will have more than one temporary variables # Here is an example : # IRSB 0x4c64c4 # + 06 | t12 = LDle : I32 ( t7) # + 07 | t11 = 32Sto64 ( t12) # + 10 | t2 = Add64(0x00000571df0 , t11) # all _ addr _ holders will be { ( 0x4c64c4 , 11 ) : AddressTransferringTypes . SignedExtension32to64, # (0x4c64c4 , 12 ) ; AddressTransferringTypes . Assignment , all_addr_holders = OrderedDict ( ) while True : preds = list ( b . slice . predecessors ( stmt_loc ) ) if len ( preds ) != 1 : return False , None block_addr , stmt_idx = stmt_loc = preds [ 0 ] block = project . factory . block ( block_addr , backup_state = self . base_state ) . vex stmt = block . statements [ stmt_idx ] if isinstance ( stmt , ( pyvex . IRStmt . WrTmp , pyvex . IRStmt . Put ) ) : if isinstance ( stmt . data , ( pyvex . IRExpr . Get , pyvex . IRExpr . RdTmp ) ) : # data transferring stmts_to_remove . append ( stmt_loc ) if isinstance ( stmt , pyvex . IRStmt . WrTmp ) : all_addr_holders [ ( stmt_loc [ 0 ] , stmt . tmp ) ] = AddressTransferringTypes . Assignment continue elif isinstance ( stmt . data , pyvex . IRExpr . ITE ) : # data transferring # t16 = if ( t43 ) ILGop _ Ident32 ( LDle ( t29 ) ) else 0x0000c844 # > t44 = ITE ( t43 , t16,0x0000c844) stmts_to_remove . append ( stmt_loc ) if isinstance ( stmt , pyvex . IRStmt . WrTmp ) : all_addr_holders [ ( stmt_loc [ 0 ] , stmt . tmp ) ] = AddressTransferringTypes . Assignment continue elif isinstance ( stmt . data , pyvex . IRExpr . Unop ) : if stmt . data . op == 'Iop_32Sto64' : # data transferring with conversion # t11 = 32Sto64 ( t12) stmts_to_remove . append ( stmt_loc ) if isinstance ( stmt , pyvex . IRStmt . WrTmp ) : all_addr_holders [ ( stmt_loc [ 0 ] , stmt . tmp ) ] = AddressTransferringTypes . SignedExtension32to64 continue elif stmt . data . op == 'Iop_64to32' : # data transferring with conversion # t24 = 64to32 ( t21) stmts_to_remove . append ( stmt_loc ) if isinstance ( stmt , pyvex . IRStmt . WrTmp ) : all_addr_holders [ ( stmt_loc [ 0 ] , stmt . tmp ) ] = AddressTransferringTypes . Truncation64to32 continue elif stmt . data . op == 'Iop_32Uto64' : # data transferring with conversion # t21 = 32Uto64 ( t22) stmts_to_remove . append ( stmt_loc ) if isinstance ( stmt , pyvex . IRStmt . WrTmp ) : all_addr_holders [ ( stmt_loc [ 0 ] , stmt . tmp ) ] = AddressTransferringTypes . UnsignedExtension32to64 continue elif isinstance ( stmt . data , pyvex . IRExpr . Binop ) and stmt . data . op . startswith ( 'Iop_Add' ) : # GitHub issue # 1289 , a S390X binary # jump _ label = & jump _ table + * ( jump _ table [ index ] ) # IRSB 0x4007c0 # 00 | - - - - - IMark ( 0x4007c0 , 4 , 0 ) - - - - - # + 01 | t0 = GET : I32(212) # + 02 | t1 = Add32 ( t0,0xfffff ) # 03 | PUT ( 352 ) = 0x000003 # 04 | t13 = 32Sto64 ( t0) # 05 | t6 = t13 # 06 | PUT ( 360 ) = t6 # 07 | PUT ( 368 ) = 0xfffff # 08 | PUT ( 376 ) = 0x00000 # 09 | PUT ( 212 ) = t1 # 10 | PUT ( ia ) = 0x000004007c4 # 11 | - - - - - IMark ( 0x4007c4 , 6 , 0 ) - - - - - # + 12 | t14 = 32Uto64 ( t1) # + 13 | t8 = t14 # + 14 | t16 = CmpLE64U ( t8,0x00000b ) # + 15 | t15 = 1Uto32 ( t16) # + 16 | t10 = t15 # + 17 | t11 = CmpNE32 ( t10,0x00000) # + 18 | if ( t11 ) { PUT ( offset = 336 ) = 0x4007d4 ; Ijk _ Boring } # Next : 0x4007ca # IRSB 0x4007d4 # 00 | - - - - - IMark ( 0x4007d4 , 6 , 0 ) - - - - - # + 01 | t8 = GET : I64 ( r2) # + 02 | t7 = Shr64 ( t8,0x3d ) # + 03 | t9 = Shl64 ( t8,0x03) # + 04 | t6 = Or64 ( t9 , t7) # + 05 | t11 = And64 ( t6,0x000007fffff8) # 06 | - - - - - IMark ( 0x4007da , 6 , 0 ) - - - - - # 07 | PUT ( r1 ) = 0x00000400a50 # 08 | PUT ( ia ) = 0x000004007e0 # 09 | - - - - - IMark ( 0x4007e0 , 6 , 0 ) - - - - - # + 10 | t12 = Add64(0x00000400a50 , t11) # + 11 | t16 = LDbe : I64 ( t12) # 12 | PUT ( r2 ) = t16 # 13 | - - - - - IMark ( 0x4007e6 , 4 , 0 ) - - - - - # + 14 | t17 = Add64(0x00000400a50 , t16) # + Next : t17 # Special case : a base address is added to the loaded offset before jumping to it . if isinstance ( stmt . data . args [ 0 ] , pyvex . IRExpr . Const ) and isinstance ( stmt . data . args [ 1 ] , pyvex . IRExpr . RdTmp ) : stmts_adding_base_addr . append ( JumpTargetBaseAddr ( stmt_loc , stmt , stmt . data . args [ 1 ] . tmp , base_addr = stmt . data . args [ 0 ] . con . value ) ) stmts_to_remove . append ( stmt_loc ) elif isinstance ( stmt . data . args [ 0 ] , pyvex . IRExpr . RdTmp ) and isinstance ( stmt . data . args [ 1 ] , pyvex . IRExpr . Const ) : stmts_adding_base_addr . append ( JumpTargetBaseAddr ( stmt_loc , stmt , stmt . data . args [ 0 ] . tmp , base_addr = stmt . data . args [ 1 ] . con . value ) ) stmts_to_remove . append ( stmt_loc ) elif isinstance ( stmt . data . args [ 0 ] , pyvex . IRExpr . RdTmp ) and isinstance ( stmt . data . args [ 1 ] , pyvex . IRExpr . RdTmp ) : # one of the tmps must be holding a concrete value at this point stmts_adding_base_addr . append ( JumpTargetBaseAddr ( stmt_loc , stmt , stmt . data . args [ 0 ] . tmp , tmp_1 = stmt . data . args [ 1 ] . tmp ) ) stmts_to_remove . append ( stmt_loc ) else : # not supported pass continue elif isinstance ( stmt . data , pyvex . IRExpr . Load ) : # Got it ! load_stmt , load_stmt_loc , load_size = stmt , stmt_loc , block . tyenv . sizeof ( stmt . tmp ) // self . project . arch . byte_width stmts_to_remove . append ( stmt_loc ) elif isinstance ( stmt , pyvex . IRStmt . LoadG ) : # Got it ! # this is how an ARM jump table is translated to VEX # > t16 = if ( t43 ) ILGop _ Ident32 ( LDle ( t29 ) ) else 0x0000c844 load_stmt , load_stmt_loc , load_size = stmt , stmt_loc , block . tyenv . sizeof ( stmt . dst ) // self . project . arch . byte_width stmts_to_remove . append ( stmt_loc ) break if load_stmt_loc is None : # the load statement is not found return False , None # If we ' re just reading a constant , don ' t bother with the rest of this mess ! if isinstance ( load_stmt , pyvex . IRStmt . WrTmp ) : if type ( load_stmt . data . addr ) is pyvex . IRExpr . Const : # It ' s directly loading from a constant address # e . g . , # ldr r0 , = main + 1 # blx r0 # It ' s not a jump table , but we resolve it anyway jump_target_addr = load_stmt . data . addr . con . value jump_target = cfg . _fast_memory_load_pointer ( jump_target_addr ) if jump_target is None : l . info ( "Constant indirect jump at %#08x points outside of loaded memory to %#08x" , addr , jump_target_addr ) return False , None l . info ( "Resolved constant indirect jump from %#08x to %#08x" , addr , jump_target_addr ) ij = cfg . indirect_jumps [ addr ] ij . jumptable = False ij . resolved_targets = set ( [ jump_target ] ) return True , [ jump_target ] elif isinstance ( load_stmt , pyvex . IRStmt . LoadG ) : if type ( load_stmt . addr ) is pyvex . IRExpr . Const : # It ' s directly loading from a constant address # e . g . , # 4352c SUB R1 , R11 , # 0x1000 # 43530 LDRHI R3 , = loc _ 45450 # 43540 MOV PC , R3 # It ' s not a jump table , but we resolve it anyway # Note that this block has two branches : One goes to 45450 , the other one goes to whatever the original # value of R3 is . Some intensive data - flow analysis is required in this case . jump_target_addr = load_stmt . addr . con . value jump_target = cfg . _fast_memory_load_pointer ( jump_target_addr ) l . info ( "Resolved constant indirect jump from %#08x to %#08x" , addr , jump_target_addr ) ij = cfg . indirect_jumps [ addr ] ij . jumptable = False ij . resolved_targets = set ( [ jump_target ] ) return True , [ jump_target ] # Well , we have a real jumptable to resolve ! # If we ' re just reading a constant , don ' t bother with the rest of this mess ! if isinstance ( load_stmt , pyvex . IRStmt . WrTmp ) : if type ( load_stmt . data . addr ) is pyvex . IRExpr . Const : # It ' s directly loading from a constant address # e . g . , # ldr r0 , = main + 1 # blx r0 # It ' s not a jump table , but we resolve it anyway jump_target_addr = load_stmt . data . addr . con . value jump_target = cfg . _fast_memory_load_pointer ( jump_target_addr ) if not jump_target : # . . . except this constant looks like a jumpout ! l . info ( "Constant indirect jump directed out of the binary at #%08x" , addr ) return False , [ ] l . info ( "Resolved constant indirect jump from %#08x to %#08x" , addr , jump_target_addr ) ij = cfg . indirect_jumps [ addr ] ij . jumptable = False ij . resolved_targets = set ( [ jump_target ] ) return True , [ jump_target ] elif isinstance ( load_stmt , pyvex . IRStmt . LoadG ) : if type ( load_stmt . addr ) is pyvex . IRExpr . Const : # It ' s directly loading from a constant address # e . g . , # 4352c SUB R1 , R11 , # 0x1000 # 43530 LDRHI R3 , = loc _ 45450 # 43540 MOV PC , R3 # It ' s not a jump table , but we resolve it anyway # Note that this block has two branches : One goes to 45450 , the other one goes to whatever the original # value of R3 is . Some intensive data - flow analysis is required in this case . jump_target_addr = load_stmt . addr . con . value jump_target = cfg . _fast_memory_load_pointer ( jump_target_addr ) l . info ( "Resolved constant indirect jump from %#08x to %#08x" , addr , jump_target_addr ) ij = cfg . indirect_jumps [ addr ] ij . jumptable = False ij . resolved_targets = set ( [ jump_target ] ) return True , [ jump_target ] # skip all statements before the load statement # We want to leave the final loaded value as symbolic , so we can # get the full range of possibilities b . slice . remove_nodes_from ( stmts_to_remove ) # Debugging output if l . level == logging . DEBUG : self . _dbg_repr_slice ( b ) # Get all sources sources = [ n_ for n_ in b . slice . nodes ( ) if b . slice . in_degree ( n_ ) == 0 ] # Create the annotated CFG annotatedcfg = AnnotatedCFG ( project , None , detect_loops = False ) annotatedcfg . from_digraph ( b . slice ) # pylint : disable = too - many - nested - blocks for src_irsb , _ in sources : # Use slicecutor to execute each one , and get the address # We simply give up if any exception occurs on the way start_state = self . _initial_state ( src_irsb ) # Keep IP symbolic to avoid unnecessary concretization start_state . options . add ( o . KEEP_IP_SYMBOLIC ) start_state . options . add ( o . NO_IP_CONCRETIZATION ) # be quiet ! ! ! ! ! start_state . options . add ( o . SYMBOL_FILL_UNCONSTRAINED_REGISTERS ) start_state . options . add ( o . SYMBOL_FILL_UNCONSTRAINED_MEMORY ) # any read from an uninitialized segment should be unconstrained if self . _bss_regions : bss_memory_read_bp = BP ( when = BP_BEFORE , enabled = True , action = self . _bss_memory_read_hook ) start_state . inspect . add_breakpoint ( 'mem_read' , bss_memory_read_bp ) # FIXME : # this is a hack : for certain architectures , we do not initialize the base pointer , since the jump table on # those architectures may use the bp register to store value if not self . project . arch . name in { 'S390X' } : start_state . regs . bp = start_state . arch . initial_sp + 0x2000 self . _cached_memread_addrs . clear ( ) init_registers_on_demand_bp = BP ( when = BP_BEFORE , enabled = True , action = self . _init_registers_on_demand ) start_state . inspect . add_breakpoint ( 'mem_read' , init_registers_on_demand_bp ) # Create the slicecutor simgr = self . project . factory . simulation_manager ( start_state , resilience = True ) slicecutor = Slicecutor ( annotatedcfg , force_taking_exit = True ) simgr . use_technique ( slicecutor ) simgr . use_technique ( Explorer ( find = load_stmt_loc [ 0 ] ) ) # Run it ! try : simgr . run ( ) except KeyError as ex : # This is because the program slice is incomplete . # Blade will support more IRExprs and IRStmts l . debug ( "KeyError occurred due to incomplete program slice." , exc_info = ex ) continue # Get the jumping targets for r in simgr . found : try : whitelist = annotatedcfg . get_whitelisted_statements ( r . addr ) last_stmt = annotatedcfg . get_last_statement_index ( r . addr ) succ = project . factory . successors ( r , whitelist = whitelist , last_stmt = last_stmt ) except ( AngrError , SimError ) : # oops there are errors l . warning ( 'Cannot get jump successor states from a path that has reached the target. Skip it.' ) continue all_states = succ . flat_successors + succ . unconstrained_successors if not all_states : l . warning ( "Slicecutor failed to execute the program slice. No output state is available." ) continue state = all_states [ 0 ] # Just take the first state self . _cached_memread_addrs . clear ( ) # clear the cache to save some memory ( and avoid confusion when # debugging ) # Parse the memory load statement and get the memory address of where the jump table is stored jumptable_addr = self . _parse_load_statement ( load_stmt , state ) if jumptable_addr is None : continue # sanity check and necessary pre - processing if stmts_adding_base_addr : assert len ( stmts_adding_base_addr ) == 1 # Making sure we are only dealing with one operation here jump_base_addr = stmts_adding_base_addr [ 0 ] if jump_base_addr . base_addr_available : addr_holders = { ( jump_base_addr . stmt_loc [ 0 ] , jump_base_addr . tmp ) } else : addr_holders = { ( jump_base_addr . stmt_loc [ 0 ] , jump_base_addr . tmp ) , ( jump_base_addr . stmt_loc [ 0 ] , jump_base_addr . tmp_1 ) } if len ( set ( all_addr_holders . keys ( ) ) . intersection ( addr_holders ) ) != 1 : # for some reason it ' s trying to add a base address onto a different temporary variable that we # are not aware of . skip . continue if not jump_base_addr . base_addr_available : # we need to decide which tmp is the address holder and which tmp holds the base address addr_holder = next ( iter ( set ( all_addr_holders . keys ( ) ) . intersection ( addr_holders ) ) ) if jump_base_addr . tmp_1 == addr_holder [ 1 ] : # swap the two tmps jump_base_addr . tmp , jump_base_addr . tmp_1 = jump_base_addr . tmp_1 , jump_base_addr . tmp # Load the concrete base address jump_base_addr . base_addr = state . solver . eval ( state . scratch . temps [ jump_base_addr . tmp_1 ] ) all_targets = [ ] total_cases = jumptable_addr . _model_vsa . cardinality if total_cases > self . _max_targets : # We resolved too many targets for this indirect jump . Something might have gone wrong . l . debug ( "%d targets are resolved for the indirect jump at %#x. It may not be a jump table. Try the " "next source, if there is any." , total_cases , addr ) continue # Or alternatively , we can ask user , which is meh . . . # jump _ base _ addr = int ( raw _ input ( " please give me the jump base addr : " ) , 16) # total _ cases = int ( raw _ input ( " please give me the total cases : " ) ) # jump _ target = state . solver . SI ( bits = 64 , lower _ bound = jump _ base _ addr , upper _ bound = jump _ base _ addr + # ( total _ cases - 1 ) * 8 , stride = 8) jump_table = [ ] min_jumptable_addr = state . solver . min ( jumptable_addr ) max_jumptable_addr = state . solver . max ( jumptable_addr ) # Both the min jump target and the max jump target should be within a mapped memory region # i . e . , we shouldn ' t be jumping to the stack or somewhere unmapped if ( not project . loader . find_segment_containing ( min_jumptable_addr ) or not project . loader . find_segment_containing ( max_jumptable_addr ) ) : if ( not project . loader . find_section_containing ( min_jumptable_addr ) or not project . loader . find_section_containing ( max_jumptable_addr ) ) : l . debug ( "Jump table %#x might have jump targets outside mapped memory regions. " "Continue to resolve it from the next data source." , addr ) continue # Load the jump table from memory for idx , a in enumerate ( state . solver . eval_upto ( jumptable_addr , total_cases ) ) : if idx % 100 == 0 and idx != 0 : l . debug ( "%d targets have been resolved for the indirect jump at %#x..." , idx , addr ) target = cfg . _fast_memory_load_pointer ( a , size = load_size ) all_targets . append ( target ) # Adjust entries inside the jump table if stmts_adding_base_addr : stmt_adding_base_addr = stmts_adding_base_addr [ 0 ] base_addr = stmt_adding_base_addr . base_addr conversion_ops = list ( reversed ( list ( v for v in all_addr_holders . values ( ) if v is not AddressTransferringTypes . Assignment ) ) ) if conversion_ops : invert_conversion_ops = [ ] for conversion_op in conversion_ops : if conversion_op is AddressTransferringTypes . SignedExtension32to64 : lam = lambda a : ( a | 0xffffffff00000000 ) if a >= 0x80000000 else a elif conversion_op is AddressTransferringTypes . UnsignedExtension32to64 : lam = lambda a : a elif conversion_op is AddressTransferringTypes . Truncation64to32 : lam = lambda a : a & 0xffffffff else : raise NotImplementedError ( "Unsupported conversion operation." ) invert_conversion_ops . append ( lam ) all_targets_copy = all_targets all_targets = [ ] for target_ in all_targets_copy : for lam in invert_conversion_ops : target_ = lam ( target_ ) all_targets . append ( target_ ) mask = ( 2 ** self . project . arch . bits ) - 1 all_targets = [ ( target + base_addr ) & mask for target in all_targets ] # Finally . . . all targets are ready illegal_target_found = False for target in all_targets : # if the total number of targets is suspicious ( it usually implies a failure in applying the # constraints ) , check if all jump targets are legal if len ( all_targets ) in { 0x100 , 0x10000 } and not self . _is_jumptarget_legal ( target ) : l . info ( "Jump target %#x is probably illegal. Try to resolve indirect jump at %#x from the next " "source." , target , addr ) illegal_target_found = True break jump_table . append ( target ) if illegal_target_found : continue l . info ( "Resolved %d targets from %#x." , len ( all_targets ) , addr ) # write to the IndirectJump object in CFG ij = cfg . indirect_jumps [ addr ] if total_cases > 1 : # It can be considered a jump table only if there are more than one jump target ij . jumptable = True ij . jumptable_addr = state . solver . min ( jumptable_addr ) ij . resolved_targets = set ( jump_table ) ij . jumptable_entries = jump_table else : ij . jumptable = False ij . resolved_targets = set ( jump_table ) return True , all_targets l . info ( "Could not resolve indirect jump %#x in funtion %#x." , addr , func_addr ) return False , None
def segment_intersection1 ( start0 , end0 , start1 , end1 , s ) : """Image for : func : ` . segment _ intersection ` docstring ."""
if NO_IMAGES : return line0 = bezier . Curve . from_nodes ( stack1d ( start0 , end0 ) ) line1 = bezier . Curve . from_nodes ( stack1d ( start1 , end1 ) ) ax = line0 . plot ( 2 ) line1 . plot ( 256 , ax = ax ) ( x_val , ) , ( y_val , ) = line0 . evaluate ( s ) ax . plot ( [ x_val ] , [ y_val ] , color = "black" , marker = "o" ) ax . axis ( "scaled" ) save_image ( ax . figure , "segment_intersection1.png" )
def normalized ( self ) : """Returns the unit quaternion corresponding to the same rotation as this one ."""
magnitude = self . magnitude ( ) return Quaternion ( self . x / magnitude , self . y / magnitude , self . z / magnitude , self . w / magnitude )
def u2ver ( self ) : """Get the major / minor version of the urllib2 lib . @ return : The urllib2 version . @ rtype : float"""
try : part = u2 . __version__ . split ( '.' , 1 ) n = float ( '.' . join ( part ) ) return n except Exception as e : log . exception ( e ) return 0
def remove_trailing_string ( content , trailing ) : """Strip trailing component ` trailing ` from ` content ` if it exists . Used when generating names from view classes ."""
if content . endswith ( trailing ) and content != trailing : return content [ : - len ( trailing ) ] return content
def load_log ( args ) : """Load a ` logging . Logger ` object . Arguments args : ` argparse . Namespace ` object Namespace containing required settings : { ` args . debug ` , ` args . verbose ` , and ` args . log _ filename ` } . Returns log : ` logging . Logger ` object"""
from astrocats . catalog . utils import logger # Determine verbosity ( ' None ' means use default ) log_stream_level = None if args . debug : log_stream_level = logger . DEBUG elif args . verbose : log_stream_level = logger . INFO # Create log log = logger . get_logger ( stream_level = log_stream_level , tofile = args . log_filename ) log . _verbose = args . verbose log . _debug = args . debug return log
def _GetDirectory ( self ) : """Retrieves a directory . Returns : TARDirectory : a directory or None if not available ."""
if self . entry_type != definitions . FILE_ENTRY_TYPE_DIRECTORY : return None return TARDirectory ( self . _file_system , self . path_spec )
def get_tc_arguments ( parser ) : """Append test case arguments to parser . : param parser : ArgumentParser : return : ArgumentParser"""
group2 = parser . add_argument_group ( 'Test case arguments' ) group2 . add_argument ( '--log' , default = os . path . abspath ( "./log" ) , help = 'Store logs to specific path. Filename will be ' '<path>/<testcase>_D<dutNumber>.log' ) group2 . add_argument ( '-s' , '--silent' , action = 'store_true' , dest = 'silent' , default = False , help = 'Silent mode, only prints results' ) group2 . add_argument ( '-v' , "--verbose" , dest = 'verbose' , default = 0 , help = "increase output verbosity, max 2 times." , action = "count" ) group2 . add_argument ( '-w' , action = 'store_true' , dest = 'cloud' , default = False , help = 'Store results to a cloud service.' ) group2 . add_argument ( '--with_logs' , action = 'store_true' , dest = 'with_logs' , default = False , help = "Store bench.log to cloud db after run." ) group2 . add_argument ( '--reset' , dest = 'reset' , action = 'store' , nargs = '?' , const = True , help = 'reset device before executing test cases' ) group2 . add_argument ( '--iface' , help = "Used NW sniffer interface name" ) group2 . add_argument ( '--bin' , help = "Used specific binary for DUTs, when process is in use. " "NOTE: Does not affect duts which specify their own binaries." ) group2 . add_argument ( '--tc_cfg' , help = 'Testcase Configuration file' ) group2 . add_argument ( '--type' , help = 'Overrides DUT type.' , choices = [ 'hardware' , 'process' , "serial" , "mbed" ] ) group2 . add_argument ( '--platform_name' , help = 'Overrides used platform. Must be found in allowed_platforms in ' 'dut configuration if allowed_platforms is defined and non-empty.' , default = None ) group2 . add_argument ( '--putty' , dest = 'putty' , action = 'store_true' , default = False , help = 'Open putty after TC executed' ) group2 . add_argument ( '--skip_setup' , action = 'store_true' , default = False , help = 'Skip TC setUp phase' ) group2 . add_argument ( '--skip_case' , action = 'store_true' , default = False , help = 'Skip TC body phase' ) group2 . add_argument ( '--skip_teardown' , action = 'store_true' , default = False , help = 'Skip TC tearDown phase' ) group2 . add_argument ( '--valgrind' , action = 'store_true' , default = False , help = 'Analyse nodes with valgrind (linux only)' ) group2 . add_argument ( '--valgrind_tool' , help = 'Valgrind tool to use.' , choices = [ 'memcheck' , 'callgrind' , 'massif' ] ) group2 . add_argument ( '--valgrind_extra_params' , default = '' , help = 'Additional command line parameters to valgrind.' ) # only one of the - - valgrind _ text or - - valgrind _ console is allowed valgrind_group = parser . add_mutually_exclusive_group ( ) valgrind_group . add_argument ( '--valgrind_text' , action = 'store_true' , default = False , help = 'Output as Text. Default: xml format' ) valgrind_group . add_argument ( '--valgrind_console' , dest = 'valgrind_console' , action = 'store_true' , default = False , help = 'Output as Text to console. Default: xml format' ) group2 . add_argument ( '--valgrind_track_origins' , action = 'store_true' , default = False , help = 'Show origins of undefined values. Default: false; ' 'Used only if the Valgrind tool is memcheck' ) group2 . add_argument ( '--use_sniffer' , dest = 'use_sniffer' , action = 'store_true' , default = False , help = 'Use Sniffer' ) group2 . add_argument ( '--my_duts' , dest = "my_duts" , help = 'Use only some of duts. e.g. --my_duts 1,3' ) group2 . add_argument ( '--pause_ext' , action = 'store_true' , dest = "pause_when_external_dut" , default = False , help = 'Pause when external device command happens' ) # only one of the - - gdb , - - gdbs or - - vgdb is allowed gdb_group = parser . add_mutually_exclusive_group ( ) gdb_group . add_argument ( '--gdb' , type = int , help = 'Run specific process node with gdb (debugger). e.g. --gdb 1' ) gdb_group . add_argument ( '--gdbs' , type = int , help = 'Run specific process node with gdbserver ' '(debugger). e.g. --gdbs 1' ) gdb_group . add_argument ( '--vgdb' , type = int , help = 'Run specific process node with vgdb ' '(debugger under valgrind). e.g. --vgdb 1' ) group2 . add_argument ( '--gdbs-port' , dest = 'gdbs_port' , type = int , default = 2345 , help = 'select gdbs port' ) group2 . add_argument ( '--pre-cmds' , dest = 'pre_cmds' , help = 'Send extra commands right after DUT connection' ) group2 . add_argument ( '--post-cmds' , dest = 'post_cmds' , help = 'Send extra commands right before terminating dut connection.' ) group2 . add_argument ( '--baudrate' , dest = 'baudrate' , type = int , help = 'Use user defined serial baudrate (when serial device is in use)' ) group2 . add_argument ( '--serial_timeout' , type = float , default = 0.01 , help = 'User defined serial timeout (default 0.01)' ) group2 . add_argument ( '--serial_xonxoff' , action = 'store_true' , default = False , help = 'Use software flow control' ) group2 . add_argument ( '--serial_rtscts' , action = 'store_true' , default = False , help = 'Use Hardware flow control' ) group2 . add_argument ( '--serial_ch_size' , type = int , default = - 1 , help = 'use chunck mode with size N when writing to serial port. ' '(default N=-1: ' 'use pre-defined mode, N=0: normal, N<0: chunk-mode with size N' ) group2 . add_argument ( '--serial_ch_delay' , dest = 'ch_mode_ch_delay' , type = float , help = 'User defined delay between characters. ' 'Used only when serial_ch_size>0. (default 0.01)' ) group2 . add_argument ( '--nobuf' , help = "Do not use stdio buffers in node process." ) group2 . add_argument ( '--kill_putty' , action = 'store_true' , help = 'Kill old putty/kitty processes' ) # only one of the - - forceflash , - - forceflash _ once is allowed forceflash_group = parser . add_mutually_exclusive_group ( ) forceflash_group . add_argument ( '--forceflash' , action = 'store_true' , default = False , help = 'Force flashing of hardware device if binary is given. ' 'Defaults to False' ) forceflash_group . add_argument ( '--forceflash_once' , action = 'store_true' , default = False , help = 'Force flashing of hardware device if ' 'binary is given, but only once. Defaults to False' ) forceflash_group . add_argument ( "--skip_flash" , default = False , action = "store_true" , help = "Skip flashing hardware devices during this run." ) group2 . add_argument ( '--interface' , dest = 'interface' , default = 'eth0' , help = 'Network interface used in tests, unless the testcase specifies ' 'which one to use. Defaults to eth0' ) return parser
def main ( pos , bobj = None ) : """: param pos : A dictionary with { ' latitude ' : 8.12 , ' longitude ' : 42.6} : param bobj : An object which has a ' get ' method and returns a dictionary ."""
city , distance = get_city ( pos , bobj ) city = get_city_from_file ( city [ 'linenr' ] ) print ( "The city '%s' is about %0.2fkm away from your location %s" % ( city [ 'asciiname' ] , distance / 1000.0 , str ( pos ) ) ) for key , value in sorted ( city . items ( ) ) : print ( "%s: %s" % ( key , value ) )
def get_size ( self ) : """see doc in Term class"""
self . curses . setupterm ( ) return self . curses . tigetnum ( 'cols' ) , self . curses . tigetnum ( 'lines' )
def get_feature_state_for_scope ( self , feature_id , user_scope , scope_name , scope_value ) : """GetFeatureStateForScope . [ Preview API ] Get the state of the specified feature for the given named scope : param str feature _ id : Contribution id of the feature : param str user _ scope : User - Scope at which to get the value . Should be " me " for the current user or " host " for all users . : param str scope _ name : Scope at which to get the feature setting for ( e . g . " project " or " team " ) : param str scope _ value : Value of the scope ( e . g . the project or team id ) : rtype : : class : ` < ContributedFeatureState > < azure . devops . v5_0 . feature _ management . models . ContributedFeatureState > `"""
route_values = { } if feature_id is not None : route_values [ 'featureId' ] = self . _serialize . url ( 'feature_id' , feature_id , 'str' ) if user_scope is not None : route_values [ 'userScope' ] = self . _serialize . url ( 'user_scope' , user_scope , 'str' ) if scope_name is not None : route_values [ 'scopeName' ] = self . _serialize . url ( 'scope_name' , scope_name , 'str' ) if scope_value is not None : route_values [ 'scopeValue' ] = self . _serialize . url ( 'scope_value' , scope_value , 'str' ) response = self . _send ( http_method = 'GET' , location_id = 'dd291e43-aa9f-4cee-8465-a93c78e414a4' , version = '5.0-preview.1' , route_values = route_values ) return self . _deserialize ( 'ContributedFeatureState' , response )
def ned ( simulated_array , observed_array , replace_nan = None , replace_inf = None , remove_neg = False , remove_zero = False ) : """Compute the normalized Euclidian distance between the simulated and observed data in vector space . . . image : : / pictures / NED . png * * Range * * 0 ≤ NED < inf , smaller is better . * * Notes * * Also sometimes referred to as the squared L2 - norm . Parameters simulated _ array : one dimensional ndarray An array of simulated data from the time series . observed _ array : one dimensional ndarray An array of observed data from the time series . replace _ nan : float , optional If given , indicates which value to replace NaN values with in the two arrays . If None , when a NaN value is found at the i - th position in the observed OR simulated array , the i - th value of the observed and simulated array are removed before the computation . replace _ inf : float , optional If given , indicates which value to replace Inf values with in the two arrays . If None , when an inf value is found at the i - th position in the observed OR simulated array , the i - th value of the observed and simulated array are removed before the computation . remove _ neg : boolean , optional If True , when a negative value is found at the i - th position in the observed OR simulated array , the i - th value of the observed AND simulated array are removed before the computation . remove _ zero : boolean , optional If true , when a zero value is found at the i - th position in the observed OR simulated array , the i - th value of the observed AND simulated array are removed before the computation . Returns float The normalized euclidean distance value . Examples > > > import HydroErr as he > > > import numpy as np > > > sim = np . array ( [ 5 , 7 , 9 , 2 , 4.5 , 6.7 ] ) > > > obs = np . array ( [ 4.7 , 6 , 10 , 2.5 , 4 , 7 ] ) > > > he . ned ( sim , obs ) 0.2872053604165771 References - Kennard , M . J . , Mackay , S . J . , Pusey , B . J . , Olden , J . D . , & Marsh , N . ( 2010 ) . Quantifying uncertainty in estimation of hydrologic metrics for ecohydrological studies . River Research and Applications , 26(2 ) , 137-156."""
# Checking and cleaning the data simulated_array , observed_array = treat_values ( simulated_array , observed_array , replace_nan = replace_nan , replace_inf = replace_inf , remove_neg = remove_neg , remove_zero = remove_zero ) a = observed_array / np . mean ( observed_array ) b = simulated_array / np . mean ( simulated_array ) return np . linalg . norm ( a - b )
def append_variables ( self , samples_like , sort_labels = True ) : """Create a new sampleset with the given variables with values added . Not defined for empty sample sets . Note that when ` sample _ like ` is a : obj : ` . SampleSet ` , the data vectors and info are ignored . Args : samples _ like : Samples to add to the sample set . Should either be a single sample or should match the length of the sample set . See : func : ` . as _ samples ` for what is allowed to be ` samples _ like ` . sort _ labels ( bool , optional , default = True ) : If true , returned : attr : ` . SampleSet . variables ` will be in sorted - order . Note that mixed types are not sortable in which case the given order will be maintained . Returns : : obj : ` . SampleSet ` : A new sample set with the variables / values added . Examples : > > > sampleset = dimod . SampleSet . from _ samples ( [ { ' a ' : - 1 , ' b ' : + 1 } , . . . { ' a ' : + 1 , ' b ' : + 1 } ] , . . . dimod . SPIN , . . . energy = [ - 1.0 , 1.0 ] ) > > > new = sampleset . append _ variables ( { ' c ' : - 1 } ) > > > print ( new ) a b c energy num _ oc . 0 - 1 + 1 - 1 - 1.0 1 1 + 1 + 1 - 1 1.0 1 [ ' SPIN ' , 2 rows , 2 samples , 3 variables ] Add variables from another sampleset to the original above . Note that the energies do not change . > > > another = dimod . SampleSet . from _ samples ( [ { ' c ' : - 1 , ' d ' : + 1 } , . . . { ' c ' : + 1 , ' d ' : + 1 } ] , . . . dimod . SPIN , . . . energy = [ - 2.0 , 1.0 ] ) > > > new = sampleset . append _ variables ( another ) > > > print ( new ) a b c d energy num _ oc . 0 - 1 + 1 - 1 + 1 - 1.0 1 1 + 1 + 1 + 1 + 1 1.0 1 [ ' SPIN ' , 2 rows , 2 samples , 4 variables ]"""
samples , labels = as_samples ( samples_like ) num_samples = len ( self ) # we don ' t handle multiple values if samples . shape [ 0 ] == num_samples : # we don ' t need to do anything , it ' s already the correct shape pass elif samples . shape [ 0 ] == 1 and num_samples : samples = np . repeat ( samples , num_samples , axis = 0 ) else : msg = ( "mismatched shape. The samples to append should either be " "a single sample or should match the length of the sample " "set. Empty sample sets cannot be appended to." ) raise ValueError ( msg ) # append requires the new variables to be unique variables = self . variables if any ( v in variables for v in labels ) : msg = "Appended samples cannot contain variables in sample set" raise ValueError ( msg ) new_variables = list ( variables ) + labels new_samples = np . hstack ( ( self . record . sample , samples ) ) return type ( self ) . from_samples ( ( new_samples , new_variables ) , self . vartype , info = copy . deepcopy ( self . info ) , # make a copy sort_labels = sort_labels , ** self . data_vectors )
def swd_read32 ( self , offset ) : """Gets a unit of ` ` 32 ` ` bits from the input buffer . Args : self ( JLink ) : the ` ` JLink ` ` instance offset ( int ) : the offset ( in bits ) from which to start reading Returns : The integer read from the input buffer ."""
value = self . _dll . JLINK_SWD_GetU32 ( offset ) return ctypes . c_uint32 ( value ) . value
def _update_project ( self , request , data ) : """Update project info"""
domain_id = identity . get_domain_id_for_operation ( request ) try : project_id = data [ 'project_id' ] # add extra information if keystone . VERSIONS . active >= 3 : EXTRA_INFO = getattr ( settings , 'PROJECT_TABLE_EXTRA_INFO' , { } ) kwargs = dict ( ( key , data . get ( key ) ) for key in EXTRA_INFO ) else : kwargs = { } return api . keystone . tenant_update ( request , project_id , name = data [ 'name' ] , description = data [ 'description' ] , enabled = data [ 'enabled' ] , domain = domain_id , ** kwargs ) except exceptions . Conflict : msg = _ ( 'Project name "%s" is already used.' ) % data [ 'name' ] self . failure_message = msg return except Exception as e : LOG . debug ( 'Project update failed: %s' , e ) exceptions . handle ( request , ignore = True ) return
def post ( self ) : """API endpoint to push transactions to the Federation . Return : A ` ` dict ` ` containing the data about the transaction ."""
parser = reqparse . RequestParser ( ) parser . add_argument ( 'mode' , type = parameters . valid_mode , default = 'broadcast_tx_async' ) args = parser . parse_args ( ) mode = str ( args [ 'mode' ] ) pool = current_app . config [ 'bigchain_pool' ] # ` force ` will try to format the body of the POST request even if the # ` content - type ` header is not set to ` application / json ` tx = request . get_json ( force = True ) try : tx_obj = Transaction . from_dict ( tx ) except SchemaValidationError as e : return make_error ( 400 , message = 'Invalid transaction schema: {}' . format ( e . __cause__ . message ) ) except ValidationError as e : return make_error ( 400 , 'Invalid transaction ({}): {}' . format ( type ( e ) . __name__ , e ) ) with pool ( ) as bigchain : try : bigchain . validate_transaction ( tx_obj ) except ValidationError as e : return make_error ( 400 , 'Invalid transaction ({}): {}' . format ( type ( e ) . __name__ , e ) ) else : status_code , message = bigchain . write_transaction ( tx_obj , mode ) if status_code == 202 : response = jsonify ( tx ) response . status_code = 202 return response else : return make_error ( status_code , message )
def is_uniform ( keys , axis = semantics . axis_default ) : """returns true if all keys have equal multiplicity"""
index = as_index ( keys , axis ) return index . uniform
def main ( ) : """Provide the program ' s entry point when directly executed ."""
if len ( sys . argv ) < 2 : print ( "Usage: {} SCOPE..." . format ( sys . argv [ 0 ] ) ) return 1 authenticator = prawcore . TrustedAuthenticator ( prawcore . Requestor ( "prawcore_refresh_token_example" ) , os . environ [ "PRAWCORE_CLIENT_ID" ] , os . environ [ "PRAWCORE_CLIENT_SECRET" ] , os . environ [ "PRAWCORE_REDIRECT_URI" ] , ) state = str ( random . randint ( 0 , 65000 ) ) url = authenticator . authorize_url ( "permanent" , sys . argv [ 1 : ] , state ) print ( url ) client = receive_connection ( ) data = client . recv ( 1024 ) . decode ( "utf-8" ) param_tokens = data . split ( " " , 2 ) [ 1 ] . split ( "?" , 1 ) [ 1 ] . split ( "&" ) params = { key : value for ( key , value ) in [ token . split ( "=" ) for token in param_tokens ] } if state != params [ "state" ] : send_message ( client , "State mismatch. Expected: {} Received: {}" . format ( state , params [ "state" ] ) , ) return 1 elif "error" in params : send_message ( client , params [ "error" ] ) return 1 authorizer = prawcore . Authorizer ( authenticator ) authorizer . authorize ( params [ "code" ] ) send_message ( client , "Refresh token: {}" . format ( authorizer . refresh_token ) ) return 0
def calc_fwhm_moffat ( self , arr1d , medv = None , moffat_fn = None ) : """FWHM calculation on a 1D array by using least square fitting of a Moffat function on the data . arr1d is a 1D array cut in either X or Y direction on the object ."""
if moffat_fn is None : moffat_fn = self . moffat N = len ( arr1d ) X = np . array ( list ( range ( N ) ) ) Y = arr1d # Fitting works more reliably if we do the following # a . subtract sky background if medv is None : medv = get_median ( Y ) Y = Y - medv maxv = Y . max ( ) # b . clamp to 0 . . max ( of the sky subtracted field ) Y = Y . clip ( 0 , maxv ) # Fit a moffat p0 = [ 0 , N - 1 , 2 , maxv ] # Inital guess # Distance to the target function errfunc = lambda p , x , y : moffat_fn ( x , p ) - y # noqa # Least square fit to the gaussian with self . lock : # NOTE : without this mutex , optimize . leastsq causes a fatal error # sometimes - - it appears not to be thread safe . # The error is : # " SystemError : null argument to internal routine " # " Fatal Python error : GC object already tracked " p1 , success = optimize . leastsq ( errfunc , p0 [ : ] , args = ( X , Y ) ) if not success : raise IQCalcError ( "FWHM moffat fitting failed" ) mu , width , power , maxv = p1 width = np . abs ( width ) self . logger . debug ( "mu=%f width=%f power=%f maxv=%f" % ( mu , width , power , maxv ) ) fwhm = 2.0 * width * np . sqrt ( 2.0 ** ( 1.0 / power ) - 1.0 ) # some routines choke on numpy values and need " pure " Python floats # e . g . when marshalling through a remote procedure interface fwhm = float ( fwhm ) mu = float ( mu ) width = float ( width ) power = float ( power ) maxv = float ( maxv ) res = Bunch . Bunch ( fwhm = fwhm , mu = mu , width = width , power = power , maxv = maxv , fit_fn = moffat_fn , fit_args = [ mu , width , power , maxv ] ) return res
def _close_open_date_ranges ( self , record ) : """If a date range is missing the start or end date , close it by copying the date from the existing value ."""
date_ranges = ( ( 'beginDate' , 'endDate' ) , ) for begin , end in date_ranges : if begin in record and end in record : return elif begin in record : record [ end ] = record [ begin ] elif end in record : record [ begin ] = record [ end ]
def file_md5 ( file_name ) : '''Generate an MD5 hash of the specified file . @ file _ name - The file to hash . Returns an MD5 hex digest string .'''
md5 = hashlib . md5 ( ) with open ( file_name , 'rb' ) as f : for chunk in iter ( lambda : f . read ( 128 * md5 . block_size ) , b'' ) : md5 . update ( chunk ) return md5 . hexdigest ( )
async def AddPendingResources ( self , addcharmwithauthorization , entity , resources ) : '''addcharmwithauthorization : AddCharmWithAuthorization entity : Entity resources : typing . Sequence [ ~ CharmResource ] Returns - > typing . Union [ _ ForwardRef ( ' ErrorResult ' ) , typing . Sequence [ str ] ]'''
# map input types to rpc msg _params = dict ( ) msg = dict ( type = 'Resources' , request = 'AddPendingResources' , version = 1 , params = _params ) _params [ 'AddCharmWithAuthorization' ] = addcharmwithauthorization _params [ 'Entity' ] = entity _params [ 'Resources' ] = resources reply = await self . rpc ( msg ) return reply
def check ( self , item_id ) : """Check if an analysis is complete : type item _ id : int : param item _ id : task _ id to check . : rtype : bool : return : Boolean indicating if a report is done or not ."""
response = self . _request ( "tasks/view/{id}" . format ( id = item_id ) ) if response . status_code == 404 : # probably an unknown task id return False try : content = json . loads ( response . content . decode ( 'utf-8' ) ) status = content [ 'task' ] [ "status" ] if status == 'completed' or status == "reported" : return True except ValueError as e : raise sandboxapi . SandboxError ( e ) return False
def find_atoms_within_distance ( atoms , cutoff_distance , point ) : """Returns atoms within the distance from the point . Parameters atoms : [ ampal . atom ] A list of ` ampal . atoms ` . cutoff _ distance : float Maximum distance from point . point : ( float , float , float ) Reference point , 3D coordinate . Returns filtered _ atoms : [ ampal . atoms ] ` atoms ` list filtered by distance ."""
return [ x for x in atoms if distance ( x , point ) <= cutoff_distance ]
def pp_event ( seq ) : """Returns pretty representation of an Event or keypress"""
if isinstance ( seq , Event ) : return str ( seq ) # Get the original sequence back if seq is a pretty name already rev_curses = dict ( ( v , k ) for k , v in CURSES_NAMES . items ( ) ) rev_curtsies = dict ( ( v , k ) for k , v in CURTSIES_NAMES . items ( ) ) if seq in rev_curses : seq = rev_curses [ seq ] elif seq in rev_curtsies : seq = rev_curtsies [ seq ] pretty = curtsies_name ( seq ) if pretty != seq : return pretty return repr ( seq ) . lstrip ( 'u' ) [ 1 : - 1 ]
def optimize ( population , toolbox , ngen , archive = None , stats = None , verbose = False , history = None ) : """Optimize a population of individuals . : param population : : param toolbox : : param mut _ prob : : param ngen : : param archive : : param stats : : param verbose : : param history : : return :"""
start = time . time ( ) if history is not None : history . update ( population ) logbook = tools . Logbook ( ) logbook . header = [ 'gen' , 'nevals' , 'cpu_time' ] + ( stats . fields if stats else [ ] ) render_fitness ( population , toolbox , history ) record_information ( population , stats , start , archive , logbook , verbose ) for gen in range ( 1 , ngen + 1 ) : offspring = generate_next_population ( population , toolbox ) render_fitness ( offspring , toolbox , history ) population = offspring record_information ( population , stats , start , archive , logbook , verbose ) return population , logbook , history
def get ( self , value ) : """Returns the VRF configuration as a resource dict . Args : value ( string ) : The vrf name to retrieve from the running configuration . Returns : A Python dict object containing the VRF attributes as key / value pairs ."""
config = self . get_block ( 'vrf definition %s' % value ) if not config : return None response = dict ( vrf_name = value ) response . update ( self . _parse_rd ( config ) ) response . update ( self . _parse_description ( config ) ) config = self . get_block ( 'no ip routing vrf %s' % value ) if config : response [ 'ipv4_routing' ] = False else : response [ 'ipv4_routing' ] = True config = self . get_block ( 'no ipv6 unicast-routing vrf %s' % value ) if config : response [ 'ipv6_routing' ] = False else : response [ 'ipv6_routing' ] = True return response
def modsplit ( s ) : """Split importable"""
if ':' in s : c = s . split ( ':' ) if len ( c ) != 2 : raise ValueError ( "Syntax error: {s}" ) return c [ 0 ] , c [ 1 ] else : c = s . split ( '.' ) if len ( c ) < 2 : raise ValueError ( "Syntax error: {s}" ) return '.' . join ( c [ : - 1 ] ) , c [ - 1 ]
def updateTitle ( self ) : """Updates the Title of this widget according to how many parameters are currently in the model"""
title = 'Auto Parameters ({})' . format ( self . paramList . model ( ) . rowCount ( ) ) self . titleChange . emit ( title ) self . setWindowTitle ( title )
def _plot_methods ( self ) : """A dictionary with mappings from plot method to their summary"""
ret = { } for attr in filter ( lambda s : not s . startswith ( "_" ) , dir ( self ) ) : obj = getattr ( self , attr ) if isinstance ( obj , PlotterInterface ) : ret [ attr ] = obj . _summary return ret
def get_process_by_its_id ( self , process_type_id , expand = None ) : """GetProcessByItsId . [ Preview API ] Get a single process of a specified ID . : param str process _ type _ id : : param str expand : : rtype : : class : ` < ProcessInfo > < azure . devops . v5_0 . work _ item _ tracking _ process . models . ProcessInfo > `"""
route_values = { } if process_type_id is not None : route_values [ 'processTypeId' ] = self . _serialize . url ( 'process_type_id' , process_type_id , 'str' ) query_parameters = { } if expand is not None : query_parameters [ '$expand' ] = self . _serialize . query ( 'expand' , expand , 'str' ) response = self . _send ( http_method = 'GET' , location_id = '02cc6a73-5cfb-427d-8c8e-b49fb086e8af' , version = '5.0-preview.2' , route_values = route_values , query_parameters = query_parameters ) return self . _deserialize ( 'ProcessInfo' , response )
def _get_relationship_data ( self ) : """Get useful data for relationship management"""
relationship_field = request . path . split ( '/' ) [ - 1 ] . replace ( '-' , '_' ) if relationship_field not in get_relationships ( self . schema ) : raise RelationNotFound ( "{} has no attribute {}" . format ( self . schema . __name__ , relationship_field ) ) related_type_ = self . schema . _declared_fields [ relationship_field ] . type_ related_id_field = self . schema . _declared_fields [ relationship_field ] . id_field model_relationship_field = get_model_field ( self . schema , relationship_field ) return relationship_field , model_relationship_field , related_type_ , related_id_field
def camelCaseToDashName ( camelCase ) : '''camelCaseToDashName - Convert a camel case name to a dash - name ( like paddingTop to padding - top ) @ param camelCase < str > - A camel - case string @ return < str > - A dash - name'''
camelCaseList = list ( camelCase ) ret = [ ] for ch in camelCaseList : if ch . isupper ( ) : ret . append ( '-' ) ret . append ( ch . lower ( ) ) else : ret . append ( ch ) return '' . join ( ret )
def generic_method_not_allowed ( * args ) : """Creates a Lambda Service Generic MethodNotAllowed Response Parameters args list List of arguments Flask passes to the method Returns Flask . Response A response object representing the GenericMethodNotAllowed Error"""
exception_tuple = LambdaErrorResponses . MethodNotAllowedException return BaseLocalService . service_response ( LambdaErrorResponses . _construct_error_response_body ( LambdaErrorResponses . LOCAL_SERVICE_ERROR , "MethodNotAllowedException" ) , LambdaErrorResponses . _construct_headers ( exception_tuple [ 0 ] ) , exception_tuple [ 1 ] )
def listobs ( vis ) : """Textually describe the contents of a measurement set . vis ( str ) The path to the dataset . Returns A generator of lines of human - readable output Errors can only be detected by looking at the output . Example : : from pwkit . environments . casa import tasks for line in tasks . listobs ( ' mydataset . ms ' ) : print ( line )"""
def inner_list ( sink ) : try : ms = util . tools . ms ( ) ms . open ( vis ) ms . summary ( verbose = True ) ms . close ( ) except Exception as e : sink . post ( b'listobs failed: %s' % e , priority = b'SEVERE' ) for line in util . forkandlog ( inner_list ) : info = line . rstrip ( ) . split ( '\t' , 3 ) # date , priority , origin , message if len ( info ) > 3 : yield info [ 3 ] else : yield ''
def check ( mod ) : """Check the parsed ASDL tree for correctness . Return True if success . For failure , the errors are printed out and False is returned ."""
v = Check ( ) v . visit ( mod ) for t in v . types : if t not in mod . types and not t in builtin_types : v . errors += 1 uses = ", " . join ( v . types [ t ] ) print ( 'Undefined type {}, used in {}' . format ( t , uses ) ) return not v . errors
def _copy ( self , other , copy_func ) : """Copies the contents of another ParsableOctetString object to itself : param object : Another instance of the same class : param copy _ func : An reference of copy . copy ( ) or copy . deepcopy ( ) to use when copying lists , dicts and objects"""
super ( ParsableOctetString , self ) . _copy ( other , copy_func ) self . _bytes = other . _bytes self . _parsed = copy_func ( other . _parsed )
def _CheckIsDevice ( self , file_entry ) : """Checks the is _ device find specification . Args : file _ entry ( FileEntry ) : file entry . Returns : bool : True if the file entry matches the find specification , False if not ."""
if definitions . FILE_ENTRY_TYPE_DEVICE not in self . _file_entry_types : return False return file_entry . IsDevice ( )
def execCommand ( g , command , timeout = 10 ) : """Executes a command by sending it to the rack server Arguments : g : hcam _ drivers . globals . Container the Container object of application globals command : ( string ) the command ( see below ) Possible commands are : start : starts a run stop : stops a run abort : aborts a run online : bring ESO control server online and power up hardware off : put ESO control server in idle state and power down standby : server can communicate , but child processes disabled reset : resets the NGC controller front end Returns True / False according to whether the command succeeded or not ."""
if not g . cpars [ 'hcam_server_on' ] : g . clog . warn ( 'execCommand: servers are not active' ) return False try : url = g . cpars [ 'hipercam_server' ] + command g . clog . info ( 'execCommand, command = "' + command + '"' ) response = urllib . request . urlopen ( url , timeout = timeout ) rs = ReadServer ( response . read ( ) , status_msg = False ) g . rlog . info ( 'Server response =\n' + rs . resp ( ) ) if rs . ok : g . clog . info ( 'Response from server was OK' ) return True else : g . clog . warn ( 'Response from server was not OK' ) g . clog . warn ( 'Reason: ' + rs . err ) return False except urllib . error . URLError as err : g . clog . warn ( 'execCommand failed' ) g . clog . warn ( str ( err ) ) return False
def raise_api_exceptions ( function , * args , ** kwargs ) : """Raise client side exception ( s ) when present in the API response . Returned data is not modified ."""
try : return_value = function ( * args , ** kwargs ) except errors . HTTPException as exc : if exc . _raw . status_code != 400 : # pylint : disable = W0212 raise # Unhandled HTTPErrors try : # Attempt to convert v1 errors into older format ( for now ) data = exc . _raw . json ( ) # pylint : disable = W0212 assert len ( data ) == 2 return_value = { 'errors' : [ ( data [ 'reason' ] , data [ 'explanation' ] , '' ) ] } except Exception : raise exc if isinstance ( return_value , dict ) : if return_value . get ( 'error' ) == 304 : # Not modified exception raise errors . NotModified ( return_value ) elif return_value . get ( 'errors' ) : error_list = [ ] for error_type , msg , value in return_value [ 'errors' ] : if error_type in errors . ERROR_MAPPING : if error_type == 'RATELIMIT' : args [ 0 ] . evict ( args [ 1 ] ) error_class = errors . ERROR_MAPPING [ error_type ] else : error_class = errors . APIException error_list . append ( error_class ( error_type , msg , value , return_value ) ) if len ( error_list ) == 1 : raise error_list [ 0 ] else : raise errors . ExceptionList ( error_list ) return return_value
def subject_sequence_retriever ( fasta_handle , b6_handle , e_value , * args , ** kwargs ) : """Returns FASTA entries for subject sequences from BLAST hits Stores B6 / M8 entries with E - Values below the e _ value cutoff . Then iterates through the FASTA file and if an entry matches the subject of an B6 / M8 entry , it ' s sequence is extracted and returned as a FASTA entry plus the E - Value . Args : fasta _ handle ( file ) : FASTA file handle , can technically be any iterable that returns FASTA " lines " b6 _ handle ( file ) : B6 / M8 file handle , can technically be any iterable that returns B6 / M8 " lines " e _ value ( float ) : Max E - Value of entry to return * args : Variable length argument list for b6 _ iter * * kwargs : Arbitrary keyword arguments for b6 _ iter Yields : FastaEntry : class containing all FASTA data Example : Note : These doctests will not pass , examples are only in doctest format as per convention . bio _ utils uses pytests for testing . > > > fasta _ handle = open ( ' test . fasta ' ) > > > b6 _ handle = open ( ' test . b6 ' ) > > > for entry in subject _ sequence _ retriever ( fasta _ handle , . . . b6 _ handle , 1e5) . . . print ( entry . sequence ) # Print aligned subject sequence"""
filtered_b6 = defaultdict ( list ) for entry in b6_evalue_filter ( b6_handle , e_value , * args , ** kwargs ) : filtered_b6 [ entry . subject ] . append ( ( entry . subject_start , entry . subject_end , entry . _evalue_str ) ) for fastaEntry in fasta_iter ( fasta_handle ) : if fastaEntry . id in filtered_b6 : for alignment in filtered_b6 [ fastaEntry . id ] : start = alignment [ 0 ] - 1 end = alignment [ 1 ] - 1 # Get subject sequence if start < end : subject_sequence = fastaEntry . sequence [ start : end ] elif start > end : subject_sequence = fastaEntry . sequence [ end : start ] [ : : - 1 ] else : subject_sequence = fastaEntry . sequence [ start ] fastaEntry . sequence = subject_sequence # Add E - value to FASTA / Q header if fastaEntry . description == '' : fastaEntry . description = 'E-value: ' else : fastaEntry . description += ' E-value: ' fastaEntry . description += alignment [ 2 ] yield fastaEntry
def _download ( self , dstFile ) : """Download this resource from its URL to the given file object . : type dstFile : io . BytesIO | io . FileIO"""
for attempt in retry ( predicate = lambda e : isinstance ( e , HTTPError ) and e . code == 400 ) : with attempt : with closing ( urlopen ( self . url ) ) as content : buf = content . read ( ) contentHash = hashlib . md5 ( buf ) assert contentHash . hexdigest ( ) == self . contentHash dstFile . write ( buf )
def get_preparation_cmd ( user , permissions , path ) : """Generates the command lines for adjusting a volume ' s ownership and permission flags . Returns an empty list if there is nothing to adjust . : param user : User to set ownership for on the path via ` ` chown ` ` . : type user : unicode | str | int | dockermap . functional . AbstractLazyObject : param permissions : Permission flags to set via ` ` chmod ` ` . : type permissions : unicode | str | dockermap . functional . AbstractLazyObject : param path : Path to adjust permissions on . : type path : unicode | str : return : Iterator over resulting command strings . : rtype : collections . Iterable [ unicode | str ]"""
r_user = resolve_value ( user ) r_permissions = resolve_value ( permissions ) if user : yield chown ( r_user , path ) if permissions : yield chmod ( r_permissions , path )
def validate ( self , model = None , context = None ) : """Validate model and return validation result object : param model : object or dict : param context : object , dict or None : return : shiftschema . result . Result"""
# inject with settings result = Result ( translator = self . translator , locale = self . locale ) # validate state state_result = self . validate_state ( model , context = context ) result . merge ( state_result ) # validate simple properties props_result = self . validate_properties ( model , context = context ) result . merge ( props_result ) # validate nested entity properties entities_result = self . validate_entities ( model , context = context ) result . merge ( entities_result ) # validate collection properties collections_result = self . validate_collections ( model , context = context ) result . merge ( collections_result ) # and return return result
def _final_frame_length ( header , final_frame_bytes ) : """Calculates the length of a final ciphertext frame , given a complete header and the number of bytes of ciphertext in the final frame . : param header : Complete message header object : type header : aws _ encryption _ sdk . structures . MessageHeader : param int final _ frame _ bytes : Bytes of ciphertext in the final frame : rtype : int"""
final_frame_length = 4 # Sequence Number End final_frame_length += 4 # Sequence Number final_frame_length += header . algorithm . iv_len # IV final_frame_length += 4 # Encrypted Content Length final_frame_length += final_frame_bytes # Encrypted Content final_frame_length += header . algorithm . auth_len # Authentication Tag return final_frame_length
def sample ( self , initial_pos , num_samples , stepsize = None , return_type = 'dataframe' ) : """Method to return samples using No U Turn Sampler Parameters initial _ pos : A 1d array like object Vector representing values of parameter position , the starting state in markov chain . num _ samples : int Number of samples to be generated stepsize : float , defaults to None The stepsize for proposing new values of position and momentum in simulate _ dynamics If None , then will be choosen suitably return _ type : string ( dataframe | recarray ) Return type for samples , either of ' dataframe ' or ' recarray ' . Defaults to ' dataframe ' Returns sampled : A pandas . DataFrame or a numpy . recarray object depending upon return _ type argument Examples > > > from pgmpy . sampling import NoUTurnSampler as NUTS , GradLogPDFGaussian , LeapFrog > > > from pgmpy . factors . continuous import GaussianDistribution as JGD > > > import numpy as np > > > mean = np . array ( [ 0 , 0 , 0 ] ) > > > covariance = np . array ( [ [ 6 , 0.7 , 0.2 ] , [ 0.7 , 3 , 0.9 ] , [ 0.2 , 0.9 , 1 ] ] ) > > > model = JGD ( [ ' x ' , ' y ' , ' z ' ] , mean , covariance ) > > > sampler = NUTS ( model = model , grad _ log _ pdf = GradLogPDFGaussian , simulate _ dynamics = LeapFrog ) > > > samples = sampler . sample ( initial _ pos = np . array ( [ 1 , 1 , 1 ] ) , num _ samples = 10, . . . stepsize = 0.4 , return _ type = ' dataframe ' ) > > > samples x y z 0 1.00000 1.00000 1.00000 1 1.760756 0.271543 - 0.613309 2 1.883387 0.990745 - 0.611720 3 0.980812 0.340336 - 0.916283 4 0.781338 0.647220 - 0.948640 5 0.040308 - 1.391406 0.412201 6 1.179549 - 1.450552 1.105216 7 1.100320 - 1.313926 1.207815 8 1.484520 - 1.349247 0.768599 9 0.934942 - 1.894589 0.471772"""
initial_pos = _check_1d_array_object ( initial_pos , 'initial_pos' ) _check_length_equal ( initial_pos , self . model . variables , 'initial_pos' , 'model.variables' ) if stepsize is None : stepsize = self . _find_reasonable_stepsize ( initial_pos ) types = [ ( var_name , 'float' ) for var_name in self . model . variables ] samples = np . zeros ( num_samples , dtype = types ) . view ( np . recarray ) samples [ 0 ] = tuple ( initial_pos ) position_m = initial_pos for i in range ( 1 , num_samples ) : # Genrating sample position_m = self . _sample ( position_m , stepsize ) samples [ i ] = tuple ( position_m ) return _return_samples ( return_type , samples )
def get_sqla_query ( # sqla self , groupby , metrics , granularity , from_dttm , to_dttm , filter = None , # noqa is_timeseries = True , timeseries_limit = 15 , timeseries_limit_metric = None , row_limit = None , inner_from_dttm = None , inner_to_dttm = None , orderby = None , extras = None , columns = None , order_desc = True , prequeries = None , is_prequery = False , ) : """Querying any sqla table from this common interface"""
template_kwargs = { 'from_dttm' : from_dttm , 'groupby' : groupby , 'metrics' : metrics , 'row_limit' : row_limit , 'to_dttm' : to_dttm , 'filter' : filter , 'columns' : { col . column_name : col for col in self . columns } , } template_kwargs . update ( self . template_params_dict ) template_processor = self . get_template_processor ( ** template_kwargs ) db_engine_spec = self . database . db_engine_spec orderby = orderby or [ ] # For backward compatibility if granularity not in self . dttm_cols : granularity = self . main_dttm_col # Database spec supports join - free timeslot grouping time_groupby_inline = db_engine_spec . time_groupby_inline cols = { col . column_name : col for col in self . columns } metrics_dict = { m . metric_name : m for m in self . metrics } if not granularity and is_timeseries : raise Exception ( _ ( 'Datetime column not provided as part table configuration ' 'and is required by this type of chart' ) ) if not groupby and not metrics and not columns : raise Exception ( _ ( 'Empty query?' ) ) metrics_exprs = [ ] for m in metrics : if utils . is_adhoc_metric ( m ) : metrics_exprs . append ( self . adhoc_metric_to_sqla ( m , cols ) ) elif m in metrics_dict : metrics_exprs . append ( metrics_dict . get ( m ) . get_sqla_col ( ) ) else : raise Exception ( _ ( "Metric '{}' is not valid" . format ( m ) ) ) if metrics_exprs : main_metric_expr = metrics_exprs [ 0 ] else : main_metric_expr , label = literal_column ( 'COUNT(*)' ) , 'ccount' main_metric_expr = self . make_sqla_column_compatible ( main_metric_expr , label ) select_exprs = [ ] groupby_exprs_sans_timestamp = OrderedDict ( ) if groupby : select_exprs = [ ] for s in groupby : if s in cols : outer = cols [ s ] . get_sqla_col ( ) else : outer = literal_column ( f'({s})' ) outer = self . make_sqla_column_compatible ( outer , s ) groupby_exprs_sans_timestamp [ outer . name ] = outer select_exprs . append ( outer ) elif columns : for s in columns : select_exprs . append ( cols [ s ] . get_sqla_col ( ) if s in cols else self . make_sqla_column_compatible ( literal_column ( s ) ) ) metrics_exprs = [ ] groupby_exprs_with_timestamp = OrderedDict ( groupby_exprs_sans_timestamp . items ( ) ) if granularity : dttm_col = cols [ granularity ] time_grain = extras . get ( 'time_grain_sqla' ) time_filters = [ ] if is_timeseries : timestamp = dttm_col . get_timestamp_expression ( time_grain ) select_exprs += [ timestamp ] groupby_exprs_with_timestamp [ timestamp . name ] = timestamp # Use main dttm column to support index with secondary dttm columns if db_engine_spec . time_secondary_columns and self . main_dttm_col in self . dttm_cols and self . main_dttm_col != dttm_col . column_name : time_filters . append ( cols [ self . main_dttm_col ] . get_time_filter ( from_dttm , to_dttm ) ) time_filters . append ( dttm_col . get_time_filter ( from_dttm , to_dttm ) ) select_exprs += metrics_exprs labels_expected = [ c . _df_label_expected for c in select_exprs ] select_exprs = db_engine_spec . make_select_compatible ( groupby_exprs_with_timestamp . values ( ) , select_exprs ) qry = sa . select ( select_exprs ) tbl = self . get_from_clause ( template_processor ) if not columns : qry = qry . group_by ( * groupby_exprs_with_timestamp . values ( ) ) where_clause_and = [ ] having_clause_and = [ ] for flt in filter : if not all ( [ flt . get ( s ) for s in [ 'col' , 'op' ] ] ) : continue col = flt [ 'col' ] op = flt [ 'op' ] col_obj = cols . get ( col ) if col_obj : is_list_target = op in ( 'in' , 'not in' ) eq = self . filter_values_handler ( flt . get ( 'val' ) , target_column_is_numeric = col_obj . is_num , is_list_target = is_list_target ) if op in ( 'in' , 'not in' ) : cond = col_obj . get_sqla_col ( ) . in_ ( eq ) if '<NULL>' in eq : cond = or_ ( cond , col_obj . get_sqla_col ( ) == None ) # noqa if op == 'not in' : cond = ~ cond where_clause_and . append ( cond ) else : if col_obj . is_num : eq = utils . string_to_num ( flt [ 'val' ] ) if op == '==' : where_clause_and . append ( col_obj . get_sqla_col ( ) == eq ) elif op == '!=' : where_clause_and . append ( col_obj . get_sqla_col ( ) != eq ) elif op == '>' : where_clause_and . append ( col_obj . get_sqla_col ( ) > eq ) elif op == '<' : where_clause_and . append ( col_obj . get_sqla_col ( ) < eq ) elif op == '>=' : where_clause_and . append ( col_obj . get_sqla_col ( ) >= eq ) elif op == '<=' : where_clause_and . append ( col_obj . get_sqla_col ( ) <= eq ) elif op == 'LIKE' : where_clause_and . append ( col_obj . get_sqla_col ( ) . like ( eq ) ) elif op == 'IS NULL' : where_clause_and . append ( col_obj . get_sqla_col ( ) == None ) # noqa elif op == 'IS NOT NULL' : where_clause_and . append ( col_obj . get_sqla_col ( ) != None ) # noqa if extras : where = extras . get ( 'where' ) if where : where = template_processor . process_template ( where ) where_clause_and += [ sa . text ( '({})' . format ( where ) ) ] having = extras . get ( 'having' ) if having : having = template_processor . process_template ( having ) having_clause_and += [ sa . text ( '({})' . format ( having ) ) ] if granularity : qry = qry . where ( and_ ( * ( time_filters + where_clause_and ) ) ) else : qry = qry . where ( and_ ( * where_clause_and ) ) qry = qry . having ( and_ ( * having_clause_and ) ) if not orderby and not columns : orderby = [ ( main_metric_expr , not order_desc ) ] for col , ascending in orderby : direction = asc if ascending else desc if utils . is_adhoc_metric ( col ) : col = self . adhoc_metric_to_sqla ( col , cols ) qry = qry . order_by ( direction ( col ) ) if row_limit : qry = qry . limit ( row_limit ) if is_timeseries and timeseries_limit and groupby and not time_groupby_inline : if self . database . db_engine_spec . inner_joins : # some sql dialects require for order by expressions # to also be in the select clause - - others , e . g . vertica , # require a unique inner alias inner_main_metric_expr = self . make_sqla_column_compatible ( main_metric_expr , 'mme_inner__' ) inner_groupby_exprs = [ ] inner_select_exprs = [ ] for gby_name , gby_obj in groupby_exprs_sans_timestamp . items ( ) : inner = self . make_sqla_column_compatible ( gby_obj , gby_name + '__' ) inner_groupby_exprs . append ( inner ) inner_select_exprs . append ( inner ) inner_select_exprs += [ inner_main_metric_expr ] subq = select ( inner_select_exprs ) . select_from ( tbl ) inner_time_filter = dttm_col . get_time_filter ( inner_from_dttm or from_dttm , inner_to_dttm or to_dttm , ) subq = subq . where ( and_ ( * ( where_clause_and + [ inner_time_filter ] ) ) ) subq = subq . group_by ( * inner_groupby_exprs ) ob = inner_main_metric_expr if timeseries_limit_metric : ob = self . _get_timeseries_orderby ( timeseries_limit_metric , metrics_dict , cols , ) direction = desc if order_desc else asc subq = subq . order_by ( direction ( ob ) ) subq = subq . limit ( timeseries_limit ) on_clause = [ ] for gby_name , gby_obj in groupby_exprs_sans_timestamp . items ( ) : # in this case the column name , not the alias , needs to be # conditionally mutated , as it refers to the column alias in # the inner query col_name = db_engine_spec . make_label_compatible ( gby_name + '__' ) on_clause . append ( gby_obj == column ( col_name ) ) tbl = tbl . join ( subq . alias ( ) , and_ ( * on_clause ) ) else : if timeseries_limit_metric : orderby = [ ( self . _get_timeseries_orderby ( timeseries_limit_metric , metrics_dict , cols , ) , False , ) ] # run subquery to get top groups subquery_obj = { 'prequeries' : prequeries , 'is_prequery' : True , 'is_timeseries' : False , 'row_limit' : timeseries_limit , 'groupby' : groupby , 'metrics' : metrics , 'granularity' : granularity , 'from_dttm' : inner_from_dttm or from_dttm , 'to_dttm' : inner_to_dttm or to_dttm , 'filter' : filter , 'orderby' : orderby , 'extras' : extras , 'columns' : columns , 'order_desc' : True , } result = self . query ( subquery_obj ) dimensions = [ c for c in result . df . columns if c not in metrics and c in groupby_exprs_sans_timestamp ] top_groups = self . _get_top_groups ( result . df , dimensions , groupby_exprs_sans_timestamp ) qry = qry . where ( top_groups ) return SqlaQuery ( sqla_query = qry . select_from ( tbl ) , labels_expected = labels_expected )
def __get_function_by_pattern ( self , pattern ) : """Return first function whose name * contains * the string ` pattern ` . : param func : partial function name ( ex . key _ pair ) : return : list function that goes with it ( ex . list _ key _ pairs )"""
function_names = [ name for name in dir ( self . driver ) if pattern in name ] if function_names : name = function_names [ 0 ] if len ( function_names ) > 1 : log . warn ( "Several functions match pattern `%s`: %r -- using first one!" , pattern , function_names ) return getattr ( self . driver , name ) else : # no such function raise AttributeError ( "No function name contains `{0}` in class `{1}`" . format ( pattern , self . __class__ . __name__ ) )
def do_publish ( broker , cmd , f , when , res , meta , * args , ** kwargs ) : """Implement the publish so it can be called outside the decorator"""
publish_command = functools . partial ( broker . publish , topic = command_types . COMMAND ) call_args = _get_args ( f , args , kwargs ) if when == 'before' : broker . logger . info ( "{}: {}" . format ( f . __qualname__ , { k : v for k , v in call_args . items ( ) if str ( k ) != 'self' } ) ) command_args = dict ( zip ( reversed ( inspect . getfullargspec ( cmd ) . args ) , reversed ( inspect . getfullargspec ( cmd ) . defaults or [ ] ) ) ) # TODO ( artyom , 20170927 ) : we are doing this to be able to use # the decorator in Instrument class methods , in which case # self is effectively an instrument . # To narrow the scope of this hack , we are checking if the # command is expecting instrument first . if 'instrument' in inspect . getfullargspec ( cmd ) . args : # We are also checking if call arguments have ' self ' and # don ' t have instruments specified , in which case # instruments should take precedence . if 'self' in call_args and 'instrument' not in call_args : call_args [ 'instrument' ] = call_args [ 'self' ] command_args . update ( { key : call_args [ key ] for key in ( set ( inspect . getfullargspec ( cmd ) . args ) & call_args . keys ( ) ) } ) if meta : command_args [ 'meta' ] = meta payload = cmd ( ** command_args ) message = { ** payload , '$' : when } if when == 'after' : message [ 'return' ] = res publish_command ( message = { ** payload , '$' : when } )
def decode_union ( self , data_type , obj ) : """The data _ type argument must be a Union . See json _ compat _ obj _ decode ( ) for argument descriptions ."""
val = None if isinstance ( obj , six . string_types ) : # Handles the shorthand format where the union is serialized as only # the string of the tag . tag = obj if data_type . definition . _is_tag_present ( tag , self . caller_permissions ) : val_data_type = data_type . definition . _get_val_data_type ( tag , self . caller_permissions ) if not isinstance ( val_data_type , ( bv . Void , bv . Nullable ) ) : raise bv . ValidationError ( "expected object for '%s', got symbol" % tag ) if tag == data_type . definition . _catch_all : raise bv . ValidationError ( "unexpected use of the catch-all tag '%s'" % tag ) elif not self . strict and data_type . definition . _catch_all : tag = data_type . definition . _catch_all else : raise bv . ValidationError ( "unknown tag '%s'" % tag ) elif isinstance ( obj , dict ) : tag , val = self . decode_union_dict ( data_type , obj ) else : raise bv . ValidationError ( "expected string or object, got %s" % bv . generic_type_name ( obj ) ) return data_type . definition ( tag , val )
def enrich_json_objects_by_object_type ( request , value ) : """Take the given value and start enrichment by object _ type . The va Args : request ( django . http . request . HttpRequest ) : request which is currently processed value ( dict | list | django . db . models . Model ) : in case of django . db . models . Model object ( or list of these objects ) , to _ json method is invoked Returns : dict | list"""
time_start_globally = time ( ) if isinstance ( value , list ) : json = [ x . to_json ( ) if hasattr ( x , "to_json" ) else x for x in value ] else : if isinstance ( value , dict ) : json = value else : json = value . to_json ( ) objects , nested = _collect_json_objects ( json , by = 'object_type' ) for enricher_info in _get_OBJECT_TYPE_ENRICHER_ORDER ( ) : if len ( enricher_info [ 'object_types' ] ) > 0 : enricher_objects = flatten ( [ objects . get ( object_type , [ ] ) for object_type in enricher_info [ 'object_types' ] ] ) enricher_nested = any ( [ nested . get ( object_type , False ) for object_type in enricher_info [ 'object_types' ] ] ) else : enricher_objects = flatten ( objects . values ( ) ) enricher_nested = any ( nested . values ( ) ) if len ( enricher_objects ) > 0 : time_start = time ( ) enricher_info [ 'enricher' ] ( request , enricher_objects , enricher_nested ) LOGGER . debug ( 'enrichment "{}" took {} seconds' . format ( enricher_info [ 'enricher_name' ] , time ( ) - time_start ) ) if not enricher_info [ 'pure' ] : # if the enricher modified object types we must collect objects # again objects , nested = _collect_json_objects ( json , by = 'object_type' ) LOGGER . debug ( 'The whole enrichment of json objects by their object_type took {} seconds.' . format ( time ( ) - time_start_globally ) ) return json
def _set_ciphers ( self ) : """Sets up the allowed ciphers . By default this matches the set in util . ssl _ . DEFAULT _ CIPHERS , at least as supported by macOS . This is done custom and doesn ' t allow changing at this time , mostly because parsing OpenSSL cipher strings is going to be a freaking nightmare ."""
ciphers = ( Security . SSLCipherSuite * len ( CIPHER_SUITES ) ) ( * CIPHER_SUITES ) result = Security . SSLSetEnabledCiphers ( self . context , ciphers , len ( CIPHER_SUITES ) ) _assert_no_error ( result )
def generate ( engine , database , models , ** kwargs ) : '''Generate the migrations by introspecting the db'''
validate_args ( engine , database , models ) generator = Generator ( engine , database , models ) generator . run ( )
def binary_search ( a , k ) : """Do a binary search in an array of objects ordered by ' . key ' returns the largest index for which : a [ i ] . key < = k like c + + : a . upperbound ( k ) - -"""
first , last = 0 , len ( a ) while first < last : mid = ( first + last ) >> 1 if k < a [ mid ] . key : last = mid else : first = mid + 1 return first - 1
def apply_upgrade ( self , upgrade ) : """Apply a upgrade and register that it was successful . A upgrade may throw a RuntimeError , if an unrecoverable error happens . : param upgrade : A single upgrade"""
self . _setup_log_prefix ( plugin_id = upgrade . name ) try : # Nested due to Python 2.4 try : upgrade . do_upgrade ( ) self . register_success ( upgrade ) except RuntimeError as e : msg = [ "Upgrade error(s):" ] for m in e . args : msg . append ( " (-) %s" % m ) logger = self . get_logger ( ) logger . error ( "\n" . join ( msg ) ) raise RuntimeError ( "Upgrade '%s' failed. Your installation is in an" " inconsistent state. Please manually review the upgrade " "and resolve inconsistencies." % upgrade [ 'id' ] ) finally : self . _teardown_log_prefix ( )
def is_function_or_method ( obj ) : """Check if an object is a function or method . Args : obj : The Python object in question . Returns : True if the object is an function or method ."""
return inspect . isfunction ( obj ) or inspect . ismethod ( obj ) or is_cython ( obj )
def list_vms ( self , allow_clone = False ) : """Gets VirtualBox VM list ."""
vbox_vms = [ ] result = yield from self . execute ( "list" , [ "vms" ] ) for line in result : if len ( line ) == 0 or line [ 0 ] != '"' or line [ - 1 : ] != "}" : continue # Broken output ( perhaps a carriage return in VM name ) vmname , _ = line . rsplit ( ' ' , 1 ) vmname = vmname . strip ( '"' ) if vmname == "<inaccessible>" : continue # ignore inaccessible VMs extra_data = yield from self . execute ( "getextradata" , [ vmname , "GNS3/Clone" ] ) if allow_clone or len ( extra_data ) == 0 or not extra_data [ 0 ] . strip ( ) == "Value: yes" : # get the amount of RAM info_results = yield from self . execute ( "showvminfo" , [ vmname , "--machinereadable" ] ) ram = 0 for info in info_results : try : name , value = info . split ( '=' , 1 ) if name . strip ( ) == "memory" : ram = int ( value . strip ( ) ) break except ValueError : continue vbox_vms . append ( { "vmname" : vmname , "ram" : ram } ) return vbox_vms
def get_data_disk_size ( vm_ , swap , linode_id ) : '''Return the size of of the data disk in MB . . versionadded : : 2016.3.0'''
disk_size = get_linode ( kwargs = { 'linode_id' : linode_id } ) [ 'TOTALHD' ] root_disk_size = config . get_cloud_config_value ( 'disk_size' , vm_ , __opts__ , default = disk_size - swap ) return disk_size - root_disk_size - swap
def create_manifest_from_s3_files ( self ) : """To create a manifest db for the current : return :"""
for k in self . s3 . list_objects ( Bucket = self . sitename ) [ 'Contents' ] : key = k [ "Key" ] files = [ ] if key not in [ self . manifest_file ] : files . append ( key ) self . _set_manifest_data ( files )
def scroll_from_element ( self , on_element , xoffset , yoffset ) : """Touch and scroll starting at on _ element , moving by xoffset and yoffset . : Args : - on _ element : The element where scroll starts . - xoffset : X offset to scroll to . - yoffset : Y offset to scroll to ."""
self . _actions . append ( lambda : self . _driver . execute ( Command . TOUCH_SCROLL , { 'element' : on_element . id , 'xoffset' : int ( xoffset ) , 'yoffset' : int ( yoffset ) } ) ) return self
def distances_indices_sorted ( self , points , sign = False ) : """Computes the distances from the plane to each of the points . Positive distances are on the side of the normal of the plane while negative distances are on the other side . Indices sorting the points from closest to furthest is also computed . : param points : Points for which distances are computed : param sign : Whether to add sign information in the indices sorting the points distances : return : Distances from the plane to the points ( positive values on the side of the normal to the plane , negative values on the other side ) , as well as indices of the points from closest to furthest . For the latter , when the sign parameter is True , items of the sorting list are given as tuples of ( index , sign ) ."""
distances = [ np . dot ( self . normal_vector , pp ) + self . d for pp in points ] indices = sorted ( range ( len ( distances ) ) , key = lambda k : np . abs ( distances [ k ] ) ) if sign : indices = [ ( ii , int ( np . sign ( distances [ ii ] ) ) ) for ii in indices ] return distances , indices
def set_widget ( self , canvas_w ) : """Call this method with the widget that will be used for the display ."""
self . logger . debug ( "set widget canvas_w=%s" % canvas_w ) self . pgcanvas = canvas_w
def disconnect ( self , receipt = None , headers = None , ** keyword_headers ) : """Disconnect from the server . : param str receipt : the receipt to use ( once the server acknowledges that receipt , we ' re officially disconnected ; optional - if not specified a unique receipt id will be generated ) : param dict headers : a map of any additional headers the broker requires : param keyword _ headers : any additional headers the broker requires"""
if not self . transport . is_connected ( ) : log . debug ( 'Not sending disconnect, already disconnected' ) return headers = utils . merge_headers ( [ headers , keyword_headers ] ) rec = receipt or utils . get_uuid ( ) headers [ HDR_RECEIPT ] = rec self . set_receipt ( rec , CMD_DISCONNECT ) self . send_frame ( CMD_DISCONNECT , headers )
def check ( self , value , major ) : """Check whether the value is between the minimum and maximum . Raise a ValueError if it is not ."""
if self . _min is not None and value < self . _min : raise ValueError ( "Integer %d is lower than minimum %d." % ( value , self . _min ) ) if self . _max is not None and value > self . _max : raise ValueError ( "Integer %d is higher than maximum %d." % ( value , self . _max ) )
def parse_addr ( text ) : "Parse a 1 - to 3 - part address spec ."
if text : parts = text . split ( ':' ) length = len ( parts ) if length == 3 : return parts [ 0 ] , parts [ 1 ] , int ( parts [ 2 ] ) elif length == 2 : return None , parts [ 0 ] , int ( parts [ 1 ] ) elif length == 1 : return None , '' , int ( parts [ 0 ] ) return None , None , None
def flip_ctrlpts_u ( ctrlpts , size_u , size_v ) : """Flips a list of 1 - dimensional control points from u - row order to v - row order . * * u - row order * * : each row corresponds to a list of u values * * v - row order * * : each row corresponds to a list of v values : param ctrlpts : control points in u - row order : type ctrlpts : list , tuple : param size _ u : size in u - direction : type size _ u : int : param size _ v : size in v - direction : type size _ v : int : return : control points in v - row order : rtype : list"""
new_ctrlpts = [ ] for i in range ( 0 , size_u ) : for j in range ( 0 , size_v ) : temp = [ float ( c ) for c in ctrlpts [ i + ( j * size_u ) ] ] new_ctrlpts . append ( temp ) return new_ctrlpts
def get_slice ( im , center , size , pad = 0 ) : r"""Given a ` ` center ` ` location and ` ` radius ` ` of a feature , returns the slice object into the ` ` im ` ` that bounds the feature but does not extend beyond the image boundaries . Parameters im : ND - image The image of the porous media center : array _ like The coordinates of the center of the feature of interest size : array _ like or scalar The size of the feature in each direction . If a scalar is supplied , this implies the same size in all directions . pad : scalar or array _ like The amount to pad onto each side of the slice . The default is 0 . A scalar value will increase the slice size equally in all directions , while an array the same shape as ` ` im . shape ` ` can be passed to pad a specified amount in each direction . Returns slices : list A list of slice objects , each indexing into one dimension of the image ."""
p = sp . ones ( shape = im . ndim , dtype = int ) * sp . array ( pad ) s = sp . ones ( shape = im . ndim , dtype = int ) * sp . array ( size ) slc = [ ] for dim in range ( im . ndim ) : lower_im = sp . amax ( ( center [ dim ] - s [ dim ] - p [ dim ] , 0 ) ) upper_im = sp . amin ( ( center [ dim ] + s [ dim ] + 1 + p [ dim ] , im . shape [ dim ] ) ) slc . append ( slice ( lower_im , upper_im ) ) return slc
def nodes_of_class ( self , klass , skip_klass = None ) : """Get the nodes ( including this one or below ) of the given type . : param klass : The type of node to search for . : type klass : builtins . type : param skip _ klass : A type of node to ignore . This is useful to ignore subclasses of : attr : ` klass ` . : type skip _ klass : builtins . type : returns : The node of the given type . : rtype : iterable ( NodeNG )"""
if isinstance ( self , klass ) : yield self if skip_klass is None : for child_node in self . get_children ( ) : yield from child_node . nodes_of_class ( klass , skip_klass ) return for child_node in self . get_children ( ) : if isinstance ( child_node , skip_klass ) : continue yield from child_node . nodes_of_class ( klass , skip_klass )
def _encode ( self , sources : mx . nd . NDArray , source_length : int ) -> Tuple [ List [ ModelState ] , mx . nd . NDArray ] : """Returns a ModelState for each model representing the state of the model after encoding the source . : param sources : Source ids . Shape : ( batch _ size , bucket _ key , num _ factors ) . : param source _ length : Bucket key . : return : List of ModelStates and the estimated reference length based on ratios averaged over models ."""
model_states = [ ] ratios = [ ] for model in self . models : state , ratio = model . run_encoder ( sources , source_length ) model_states . append ( state ) if ratio is not None : ratios . append ( ratio ) # num _ seq takes batch _ size and beam _ size into account num_seq = model_states [ 0 ] . states [ 0 ] . shape [ 0 ] if self . constant_length_ratio > 0.0 : # override all ratios with the constant value length_ratios = mx . nd . full ( val = self . constant_length_ratio , shape = ( num_seq , 1 ) , ctx = self . context ) else : if len ( ratios ) > 0 : # some model predicted a ratio ? # average the ratios over the models that actually we able to predict them length_ratios = mx . nd . mean ( mx . nd . stack ( * ratios , axis = 1 ) , axis = 1 ) else : length_ratios = mx . nd . zeros ( ( num_seq , 1 ) , ctx = self . context ) encoded_source_length = self . models [ 0 ] . encoder . get_encoded_seq_len ( source_length ) return model_states , length_ratios * encoded_source_length
def keep_vertices ( self , indices_to_keep , ret_kept_faces = False ) : '''Keep the given vertices and discard the others , and any faces to which they may belong . If ` ret _ kept _ faces ` is ` True ` , return the original indices of the kept faces . Otherwise return ` self ` for chaining .'''
import numpy as np if self . v is None : return indices_to_keep = np . array ( indices_to_keep , dtype = np . uint32 ) initial_num_verts = self . v . shape [ 0 ] if self . f is not None : initial_num_faces = self . f . shape [ 0 ] f_indices_to_keep = self . all_faces_with_verts ( indices_to_keep , as_boolean = True ) # Why do we test this ? Don ' t know . But we do need to test it before we # mutate self . v . vn_should_update = self . vn is not None and self . vn . shape [ 0 ] == initial_num_verts vc_should_update = self . vc is not None and self . vc . shape [ 0 ] == initial_num_verts self . v = self . v [ indices_to_keep ] if vn_should_update : self . vn = self . vn [ indices_to_keep ] if vc_should_update : self . vc = self . vc [ indices_to_keep ] if self . f is not None : v_old_to_new = np . zeros ( initial_num_verts , dtype = int ) f_old_to_new = np . zeros ( initial_num_faces , dtype = int ) v_old_to_new [ indices_to_keep ] = np . arange ( len ( indices_to_keep ) , dtype = int ) self . f = v_old_to_new [ self . f [ f_indices_to_keep ] ] f_old_to_new [ f_indices_to_keep ] = np . arange ( self . f . shape [ 0 ] , dtype = int ) else : # Make the code below work , in case there is somehow degenerate # segm even though there are no faces . f_indices_to_keep = [ ] if self . segm is not None : new_segm = { } for segm_name , segm_faces in self . segm . items ( ) : faces = np . array ( segm_faces , dtype = int ) valid_faces = faces [ f_indices_to_keep [ faces ] ] if len ( valid_faces ) : new_segm [ segm_name ] = f_old_to_new [ valid_faces ] self . segm = new_segm if new_segm else None if hasattr ( self , '_raw_landmarks' ) and self . _raw_landmarks is not None : self . recompute_landmarks ( ) return np . nonzero ( f_indices_to_keep ) [ 0 ] if ret_kept_faces else self
def is_done ( self ) : """True if the last two moves were Pass or if the position is at a move greater than the max depth ."""
return self . position . is_game_over ( ) or self . position . n >= FLAGS . max_game_length
def delete_feature ( self , dataset , fid ) : """Removes a feature from a dataset . Parameters dataset : str The dataset id . fid : str The feature id . Returns HTTP status code ."""
uri = URITemplate ( self . baseuri + '/{owner}/{did}/features/{fid}' ) . expand ( owner = self . username , did = dataset , fid = fid ) return self . session . delete ( uri )
def daterange ( start_date , end_date ) : """Yield one date per day from starting date to ending date . Args : start _ date ( date ) : starting date . end _ date ( date ) : ending date . Yields : date : a date for each day within the range ."""
for n in range ( int ( ( end_date - start_date ) . days ) ) : yield start_date + timedelta ( n )
def get_endpoints ( ) : """get all endpoints known on the Ariane server : return :"""
LOGGER . debug ( "EndpointService.get_endpoints" ) params = SessionService . complete_transactional_req ( None ) if params is None : if MappingService . driver_type != DriverFactory . DRIVER_REST : params = { 'OPERATION' : 'getEndpoints' } args = { 'properties' : params } else : args = { 'http_operation' : 'GET' , 'operation_path' : '' } else : if MappingService . driver_type != DriverFactory . DRIVER_REST : params [ 'OPERATION' ] = 'getEndpoints' args = { 'properties' : params } else : args = { 'http_operation' : 'GET' , 'operation_path' : '' , 'parameters' : params } response = EndpointService . requester . call ( args ) if MappingService . driver_type != DriverFactory . DRIVER_REST : response = response . get ( ) ret = None if response . rc == 0 : ret = [ ] for endpoint in response . response_content [ 'endpoints' ] : ret . append ( Endpoint . json_2_endpoint ( endpoint ) ) elif response . rc != 404 : err_msg = 'EndpointService.get_endpoints - Problem while getting nodes. ' 'Reason: ' + str ( response . response_content ) + ' - ' + str ( response . error_message ) + " (" + str ( response . rc ) + ")" LOGGER . warning ( err_msg ) if response . rc == 500 and ArianeMappingOverloadError . ERROR_MSG in response . error_message : raise ArianeMappingOverloadError ( "EndpointService.get_endpoints" , ArianeMappingOverloadError . ERROR_MSG ) # traceback . print _ stack ( ) return ret
def minion_config ( opts , vm_ ) : '''Return a minion ' s configuration for the provided options and VM'''
# Don ' t start with a copy of the default minion opts ; they ' re not always # what we need . Some default options are Null , let ' s set a reasonable default minion = { 'master' : 'salt' , 'log_level' : 'info' , 'hash_type' : 'sha256' , } # Now , let ' s update it to our needs minion [ 'id' ] = vm_ [ 'name' ] master_finger = salt . config . get_cloud_config_value ( 'master_finger' , vm_ , opts ) if master_finger is not None : minion [ 'master_finger' ] = master_finger minion . update ( # Get ANY defined minion settings , merging data , in the following order # 1 . VM config # 2 . Profile config # 3 . Global configuration salt . config . get_cloud_config_value ( 'minion' , vm_ , opts , default = { } , search_global = True ) ) make_master = salt . config . get_cloud_config_value ( 'make_master' , vm_ , opts ) if 'master' not in minion and make_master is not True : raise SaltCloudConfigError ( 'A master setting was not defined in the minion\'s configuration.' ) # Get ANY defined grains settings , merging data , in the following order # 1 . VM config # 2 . Profile config # 3 . Global configuration minion . setdefault ( 'grains' , { } ) . update ( salt . config . get_cloud_config_value ( 'grains' , vm_ , opts , default = { } , search_global = True ) ) return minion
def _split_params ( tag_prefix , tag_suffix ) : "Split comma - separated tag _ suffix [ : - 1 ] and map with _ maybe _ int"
if tag_suffix [ - 1 : ] != ')' : raise ValueError , "unbalanced parenthesis in type %s%s" % ( tag_prefix , tag_suffix ) return map ( _maybe_int , tag_suffix [ : - 1 ] . split ( ',' ) )
def convert ( values , source_measure_or_unit_abbreviation , target_measure_or_unit_abbreviation ) : """Convert a value or a list of values from an unit to another one . The two units must represent the same physical dimension ."""
source_dimension = get_dimension_by_unit_measure_or_abbreviation ( source_measure_or_unit_abbreviation ) target_dimension = get_dimension_by_unit_measure_or_abbreviation ( target_measure_or_unit_abbreviation ) if source_dimension == target_dimension : source = JSONObject ( { } ) target = JSONObject ( { } ) source . unit_abbreviation , source . factor = _parse_unit ( source_measure_or_unit_abbreviation ) target . unit_abbreviation , target . factor = _parse_unit ( target_measure_or_unit_abbreviation ) source . unit_data = get_unit_by_abbreviation ( source . unit_abbreviation ) target . unit_data = get_unit_by_abbreviation ( target . unit_abbreviation ) source . conv_factor = JSONObject ( { 'lf' : source . unit_data . lf , 'cf' : source . unit_data . cf } ) target . conv_factor = JSONObject ( { 'lf' : target . unit_data . lf , 'cf' : target . unit_data . cf } ) if isinstance ( values , float ) : # If values is a float = > returns a float return ( source . conv_factor . lf / target . conv_factor . lf * ( source . factor * values ) + ( source . conv_factor . cf - target . conv_factor . cf ) / target . conv_factor . lf ) / target . factor elif isinstance ( values , list ) : # If values is a list of floats = > returns a list of floats return [ ( source . conv_factor . lf / target . conv_factor . lf * ( source . factor * value ) + ( source . conv_factor . cf - target . conv_factor . cf ) / target . conv_factor . lf ) / target . factor for value in values ] else : raise HydraError ( "Unit conversion: dimensions are not consistent." )
def _hook_variable_gradient_stats ( self , var , name , log_track ) : """Logs a Variable ' s gradient ' s distribution statistics next time backward ( ) is called on it ."""
if not isinstance ( var , torch . autograd . Variable ) : cls = type ( var ) raise TypeError ( 'Expected torch.Variable, not {}.{}' . format ( cls . __module__ , cls . __name__ ) ) handle = self . _hook_handles . get ( name ) if handle is not None and self . _torch_hook_handle_is_valid ( handle ) : raise ValueError ( 'A hook has already been set under name "{}"' . format ( name ) ) def _callback ( grad , log_track ) : if not log_track_update ( log_track ) : return self . log_tensor_stats ( grad . data , name ) handle = var . register_hook ( lambda grad : _callback ( grad , log_track ) ) self . _hook_handles [ name ] = handle return handle
def visit_Assign ( self , node ) : """Implement assignment walker . Parse class properties defined via the property ( ) function"""
# [ [ [ cog # cog . out ( " print ( pcolor ( ' Enter assign visitor ' , ' magenta ' ) ) " ) # [ [ [ end ] ] ] # Class - level assignment may also be a class attribute that is not # a managed attribute , record it anyway , no harm in doing so as it # is not attached to a callable if self . _in_class ( node ) : element_full_name = self . _pop_indent_stack ( node , "prop" ) code_id = ( self . _fname , node . lineno ) self . _processed_line = node . lineno self . _callables_db [ element_full_name ] = { "name" : element_full_name , "type" : "prop" , "code_id" : code_id , "last_lineno" : None , } self . _reverse_callables_db [ code_id ] = element_full_name # [ [ [ cog # code = " " " # print ( # pcolor ( # ' Visiting property { 0 } @ { 1 } ' . format ( # element _ full _ name , code _ id [ 1] # ' green ' # cog . out ( code ) # [ [ [ end ] ] ] # Get property actions self . generic_visit ( node )
def rm ( self , index ) : """Handles the ' r ' command . : index : Index of the item to remove ."""
if self . model . exists ( index ) : self . model . remove ( index )
def spht ( ssphere , nmax = None , mmax = None ) : """Transforms ScalarPatternUniform object * ssphere * into a set of scalar spherical harmonics stored in ScalarCoefs . Example : : > > > p = spherepy . random _ patt _ uniform ( 6 , 8) > > > c = spherepy . spht ( p ) > > > spherepy . pretty _ coefs ( c ) Args : ssphere ( ScalarPatternUniform ) : The pattern to be transformed . nmax ( int , optional ) : The maximum number of * n * values required . If a value isn ' t passed , * nmax * is the number of rows in ssphere minus one . mmax ( int , optional ) : The maximum number of * m * values required . If a value isn ' t passed , * mmax * is half the number of columns in ssphere minus one . Returns : ScalarCoefs : The object containing the coefficients of the scalar spherical harmonic transform . Raises : ValueError : If * nmax * and * mmax * are too large or * mmax * > * nmax * ."""
if nmax == None : nmax = ssphere . nrows - 2 mmax = int ( ssphere . ncols / 2 ) - 1 elif mmax == None : mmax = nmax if mmax > nmax : raise ValueError ( err_msg [ 'nmax_g_mmax' ] ) if nmax >= ssphere . nrows - 1 : raise ValueError ( err_msg [ 'nmax_too_lrg' ] ) if mmax >= ssphere . ncols / 2 : raise ValueError ( err_msg [ 'mmax_too_lrg' ] ) dnrows = ssphere . _dsphere . shape [ 0 ] ncols = ssphere . _dsphere . shape [ 1 ] if np . mod ( ncols , 2 ) == 1 : raise ValueError ( err_msg [ 'ncols_even' ] ) fdata = np . fft . fft2 ( ssphere . _dsphere ) / ( dnrows * ncols ) ops . fix_even_row_data_fc ( fdata ) fdata_extended = np . zeros ( [ dnrows + 2 , ncols ] , dtype = np . complex128 ) ops . pad_rows_fdata ( fdata , fdata_extended ) ops . sin_fc ( fdata_extended ) N = nmax + 1 ; NC = N + mmax * ( 2 * N - mmax - 1 ) ; sc = np . zeros ( NC , dtype = np . complex128 ) # check if we are using c extended versions of the code or not if use_cext : csphi . fc_to_sc ( fdata_extended , sc , nmax , mmax ) else : sc = pysphi . fc_to_sc ( fdata_extended , nmax , mmax ) return ScalarCoefs ( sc , nmax , mmax )
def find_nth_digit ( n ) : """find the nth digit of given number . 1 . find the length of the number where the nth digit is from . 2 . find the actual number where the nth digit is from 3 . find the nth digit and return"""
length = 1 count = 9 start = 1 while n > length * count : n -= length * count length += 1 count *= 10 start *= 10 start += ( n - 1 ) / length s = str ( start ) return int ( s [ ( n - 1 ) % length ] )
def init_prov_graph ( self ) : """Initialize PROV graph with all we know at the start of the recording"""
try : # Use git2prov to get prov on the repo repo_prov = check_output ( [ 'node_modules/git2prov/bin/git2prov' , 'https://github.com/{}/{}/' . format ( self . user , self . repo ) , 'PROV-O' ] ) . decode ( "utf-8" ) repo_prov = repo_prov [ repo_prov . find ( '@' ) : ] # glogger . debug ( ' Git2PROV output : { } ' . format ( repo _ prov ) ) glogger . debug ( 'Ingesting Git2PROV output into RDF graph' ) with open ( 'temp.prov.ttl' , 'w' ) as temp_prov : temp_prov . write ( repo_prov ) self . prov_g . parse ( 'temp.prov.ttl' , format = 'turtle' ) except Exception as e : glogger . error ( e ) glogger . error ( "Couldn't parse Git2PROV graph, continuing without repo PROV" ) pass self . prov_g . add ( ( self . agent , RDF . type , self . prov . Agent ) ) self . prov_g . add ( ( self . entity_d , RDF . type , self . prov . Entity ) ) self . prov_g . add ( ( self . activity , RDF . type , self . prov . Activity ) ) # entity _ d self . prov_g . add ( ( self . entity_d , self . prov . wasGeneratedBy , self . activity ) ) self . prov_g . add ( ( self . entity_d , self . prov . wasAttributedTo , self . agent ) ) # later : entity _ d genereated at time ( when we know the end time ) # activity self . prov_g . add ( ( self . activity , self . prov . wasAssociatedWith , self . agent ) ) self . prov_g . add ( ( self . activity , self . prov . startedAtTime , Literal ( datetime . now ( ) ) ) )
def _init_user_stub ( self , ** stub_kwargs ) : """Initializes the user stub using nosegae config magic"""
# do a little dance to keep the same kwargs for multiple tests in the same class # because the user stub will barf if you pass these items into it # stub = user _ service _ stub . UserServiceStub ( * * stub _ kw _ args ) # TypeError : _ _ init _ _ ( ) got an unexpected keyword argument ' USER _ IS _ ADMIN ' task_args = stub_kwargs . copy ( ) self . testbed . setup_env ( overwrite = True , USER_ID = task_args . pop ( 'USER_ID' , 'testuser' ) , USER_EMAIL = task_args . pop ( 'USER_EMAIL' , 'testuser@example.org' ) , USER_IS_ADMIN = task_args . pop ( 'USER_IS_ADMIN' , '1' ) ) self . testbed . init_user_stub ( ** task_args )
def get_memory_usage ( self ) : """Get data about the virtual memory usage of the holder . : returns : Memory usage data : rtype : dict Example : > > > holder . get _ memory _ usage ( ) > > > ' nb _ arrays ' : 12 , # The holder contains the variable values for 12 different periods > > > ' nb _ cells _ by _ array ' : 100 , # There are 100 entities ( e . g . persons ) in our simulation > > > ' cell _ size ' : 8 , # Each value takes 8B of memory > > > ' dtype ' : dtype ( ' float64 ' ) # Each value is a float 64 > > > ' total _ nb _ bytes ' : 10400 # The holder uses 10.4kB of virtual memory > > > ' nb _ requests ' : 24 # The variable has been computed 24 times > > > ' nb _ requests _ by _ array ' : 2 # Each array stored has been on average requested twice"""
usage = dict ( nb_cells_by_array = self . population . count , dtype = self . variable . dtype , ) usage . update ( self . _memory_storage . get_memory_usage ( ) ) if self . simulation . trace : usage_stats = self . simulation . tracer . usage_stats [ self . variable . name ] usage . update ( dict ( nb_requests = usage_stats [ 'nb_requests' ] , nb_requests_by_array = usage_stats [ 'nb_requests' ] / float ( usage [ 'nb_arrays' ] ) if usage [ 'nb_arrays' ] > 0 else np . nan ) ) return usage
def elements ( self ) : """Return a list of the elements which are not None"""
elements = [ ] for el in ct : if isinstance ( el [ 1 ] , datapoint . Element . Element ) : elements . append ( el [ 1 ] ) return elements
def initialize ( self , init = None , ctx = None , default_init = initializer . Uniform ( ) , force_reinit = False ) : """Initializes parameter and gradient arrays . Only used for : py : class : ` NDArray ` API . Parameters init : Initializer The initializer to use . Overrides : py : meth : ` Parameter . init ` and default _ init . ctx : Context or list of Context , defaults to : py : meth : ` context . current _ context ( ) ` . Initialize Parameter on given context . If ctx is a list of Context , a copy will be made for each context . . . note : : Copies are independent arrays . User is responsible for keeping their values consistent when updating . Normally : py : class : ` gluon . Trainer ` does this for you . default _ init : Initializer Default initializer is used when both : py : func : ` init ` and : py : meth : ` Parameter . init ` are ` ` None ` ` . force _ reinit : bool , default False Whether to force re - initialization if parameter is already initialized . Examples > > > weight = mx . gluon . Parameter ( ' weight ' , shape = ( 2 , 2 ) ) > > > weight . initialize ( ctx = mx . cpu ( 0 ) ) > > > weight . data ( ) [ [ - 0.01068833 0.01729892] [ 0.02042518 - 0.01618656 ] ] < NDArray 2x2 @ cpu ( 0 ) > > > > weight . grad ( ) [ [ 0 . 0 . ] [ 0 . 0 . ] ] < NDArray 2x2 @ cpu ( 0 ) > > > > weight . initialize ( ctx = [ mx . gpu ( 0 ) , mx . gpu ( 1 ) ] ) > > > weight . data ( mx . gpu ( 0 ) ) [ [ - 0.00873779 - 0.02834515] [ 0.05484822 - 0.06206018 ] ] < NDArray 2x2 @ gpu ( 0 ) > > > > weight . data ( mx . gpu ( 1 ) ) [ [ - 0.00873779 - 0.02834515] [ 0.05484822 - 0.06206018 ] ] < NDArray 2x2 @ gpu ( 1 ) >"""
if self . _data is not None and not force_reinit : warnings . warn ( "Parameter '%s' is already initialized, ignoring. " "Set force_reinit=True to re-initialize." % self . name , stacklevel = 2 ) return self . _data = self . _grad = None if ctx is None : ctx = [ context . current_context ( ) ] if isinstance ( ctx , Context ) : ctx = [ ctx ] if init is None : init = default_init if self . init is None else self . init if not self . shape or np . prod ( self . shape ) <= 0 : if self . _allow_deferred_init : self . _deferred_init = ( init , ctx , default_init , None ) return raise ValueError ( "Cannot initialize Parameter '%s' because it has " "invalid shape: %s." % ( self . name , str ( self . shape ) ) ) self . _deferred_init = ( init , ctx , default_init , None ) self . _finish_deferred_init ( )
def get_node_attributes ( self , node ) : """Given a node , get a dictionary with copies of that node ' s attributes . : param node : reference to the node to retrieve the attributes of . : returns : dict - - copy of each attribute of the specified node . : raises : ValueError - - No such node exists ."""
if not self . has_node ( node ) : raise ValueError ( "No such node exists." ) attributes = { } for attr_name , attr_value in self . _node_attributes [ node ] . items ( ) : attributes [ attr_name ] = copy . copy ( attr_value ) return attributes
def check_version ( self , timeout = 2 , strict = False , topics = [ ] ) : """Attempt to guess the broker version . Note : This is a blocking call . Returns : version tuple , i . e . ( 0 , 10 ) , ( 0 , 9 ) , ( 0 , 8 , 2 ) , . . ."""
timeout_at = time . time ( ) + timeout log . info ( 'Probing node %s broker version' , self . node_id ) # Monkeypatch some connection configurations to avoid timeouts override_config = { 'request_timeout_ms' : timeout * 1000 , 'max_in_flight_requests_per_connection' : 5 } stashed = { } for key in override_config : stashed [ key ] = self . config [ key ] self . config [ key ] = override_config [ key ] # kafka kills the connection when it doesn ' t recognize an API request # so we can send a test request and then follow immediately with a # vanilla MetadataRequest . If the server did not recognize the first # request , both will be failed with a ConnectionError that wraps # socket . error ( 32 , 54 , or 104) from kafka . protocol . admin import ApiVersionRequest , ListGroupsRequest from kafka . protocol . commit import OffsetFetchRequest , GroupCoordinatorRequest test_cases = [ # All cases starting from 0.10 will be based on ApiVersionResponse ( ( 0 , 10 ) , ApiVersionRequest [ 0 ] ( ) ) , ( ( 0 , 9 ) , ListGroupsRequest [ 0 ] ( ) ) , ( ( 0 , 8 , 2 ) , GroupCoordinatorRequest [ 0 ] ( 'kafka-python-default-group' ) ) , ( ( 0 , 8 , 1 ) , OffsetFetchRequest [ 0 ] ( 'kafka-python-default-group' , [ ] ) ) , ( ( 0 , 8 , 0 ) , MetadataRequest [ 0 ] ( topics ) ) , ] for version , request in test_cases : if not self . connect_blocking ( timeout_at - time . time ( ) ) : raise Errors . NodeNotReadyError ( ) f = self . send ( request ) # HACK : sleeping to wait for socket to send bytes time . sleep ( 0.1 ) # when broker receives an unrecognized request API # it abruptly closes our socket . # so we attempt to send a second request immediately # that we believe it will definitely recognize ( metadata ) # the attempt to write to a disconnected socket should # immediately fail and allow us to infer that the prior # request was unrecognized mr = self . send ( MetadataRequest [ 0 ] ( topics ) ) selector = self . config [ 'selector' ] ( ) selector . register ( self . _sock , selectors . EVENT_READ ) while not ( f . is_done and mr . is_done ) : selector . select ( 1 ) for response , future in self . recv ( ) : future . success ( response ) selector . close ( ) if f . succeeded ( ) : if isinstance ( request , ApiVersionRequest [ 0 ] ) : # Starting from 0.10 kafka broker we determine version # by looking at ApiVersionResponse api_versions = self . _handle_api_version_response ( f . value ) version = self . _infer_broker_version_from_api_versions ( api_versions ) log . info ( 'Broker version identifed as %s' , '.' . join ( map ( str , version ) ) ) log . info ( 'Set configuration api_version=%s to skip auto' ' check_version requests on startup' , version ) break # Only enable strict checking to verify that we understand failure # modes . For most users , the fact that the request failed should be # enough to rule out a particular broker version . if strict : # If the socket flush hack did not work ( which should force the # connection to close and fail all pending requests ) , then we # get a basic Request Timeout . This is not ideal , but we ' ll deal if isinstance ( f . exception , Errors . RequestTimedOutError ) : pass # 0.9 brokers do not close the socket on unrecognized api # requests ( bug . . . ) . In this case we expect to see a correlation # id mismatch elif ( isinstance ( f . exception , Errors . CorrelationIdError ) and version == ( 0 , 10 ) ) : pass elif six . PY2 : assert isinstance ( f . exception . args [ 0 ] , socket . error ) assert f . exception . args [ 0 ] . errno in ( 32 , 54 , 104 ) else : assert isinstance ( f . exception . args [ 0 ] , ConnectionError ) log . info ( "Broker is not v%s -- it did not recognize %s" , version , request . __class__ . __name__ ) else : raise Errors . UnrecognizedBrokerVersion ( ) for key in stashed : self . config [ key ] = stashed [ key ] return version