def get_system_error(FCLfile, valData, Nmax=None, inDataMFs='tri', outDataMFs='tri', errorType='crispSoS'):
"""
determines the system error as calculated by the validation data
FCLfile - FCL file path/name to build FRBS
valData is validation data in format: [quant_inputs, qual_inputs, outputData]
with each data item {['function', 'var'] : [min,max]} (or [val])
inDataMFs and outDataMFs - type of MFs for inputs and outputs in data
errorType is type of error
nMax is the max number of points from the data to use
"""
q = 0 #0 for quant data, 1 or qual data
allErrors_comb = []
#load fuzzy system
inputs, outputs, rulebase, AND_operator, OR_operator, aggregator, implication, defuzz = build_fuzz_system(FCLfile)
sys = Fuzzy_System(inputs, outputs, rulebase, AND_operator, OR_operator, aggregator, implication, defuzz)
allErrors = [] #list of all errors
i = 0 #counter
for data_item in valData: #for each data item
valIns = {}
valOuts = {}
for inKey in data_item[q]: #for each input key build selected MF
[inXs, inYs] = fuzzyOps.rangeToMF(data_item[q][inKey], inDataMFs)
valIns['_'.join(inKey)] = [inXs, inYs] #addinput MF to input dict to build inputs for system
if outDataMFs <> 'sing':
[outXs, outYs] = fuzzyOps.rangeToMF(data_item[2], outDataMFs)
valOuts = [outXs, outYs] #data outputs
elif outDataMFs =='sing': #singleton output MF: [avg]
dAvg = sum(data_item[2])/len(data_item[2])
valOuts = dAvg #data outputs
valOuts = [outXs, outYs] #data outputs
sysOuts = sys.run(valIns) #get system output
if errorType == 'crispSoS': #capture crisp errors
allErrors.append(dAvg - sysOuts.itervalues().next())
if errorType == 'fuzzy': #capture fuzzy error
allErrors.append( fuzErrorInt([outXs, outYs], sysOuts.itervalues().next())**2 )
i = i+1
if Nmax <> None: #check for Nmax exceeded
if i > Nmax: break
if errorType == 'crispSoS': #sum squares of errors and divide by 2N (Simon 2002)
allErrors = [x**2 for x in allErrors]
error = (sum(allErrors)/(len(allErrors)))**0.5
elif errorType == 'fuzzy': #get a fuzzy error measure
error = (sum(allErrors)/(len(allErrors)))**0.5
return error
def get_rule(data_item):
#get degrees (firing strengths) of each rule
ants = {} #antecedents of each rule in form ['function', 'var'] : ('ling', degree) where degree is firing strengths
for inKey in inputMFs: #for each input key
if not fuzzyDataFlag:
[inXs, inYs] = fuzzyOps.rangeToMF(data_item[q][inKey], inDataMFs) #build input MF
else:
[inXs, inYs] = data_item[q][inKey]
max_fs = ('none', 0.0) #keep track of MF with maximum firing strength
for ling in inputMFs[inKey]: #for each MF in the input
#with Timer() as t:
fs_x,fs_y = fuzz.fuzzy_and(inputMFs[inKey][ling][0],inputMFs[inKey][ling][1], inXs, inYs)
#print '----------> AND time:', t.msecs, 'ms for input:', inKey, 'at length', len(fs_y)
fs = max(fs_y) #get firing strength of data point and given antecedent MF
if fs > max_fs[1]: max_fs = (ling,fs)
if max_fs[0] <> 'none':
ants[inKey + (max_fs[0],)] = max_fs[1] #append rule with highest firing strength to antecedent
if len(ants) > 0:
rule_deg = reduce(operator.mul, [ants[k] for k in ants]) #use to calc "degree" or strength of each rule
else:
rule_deg = 0.0
# repeat for outputs
conts = {} #consequents of each rule in form output : ('ling', degree)
for outKey in outputMFs: #for each output key
if not fuzzyDataFlag:
[outXs, outYs] = fuzzyOps.rangeToMF(data_item[2], outDataMFs) #build outputMF
else:
[outXs, outYs] = data_item[2]
max_fs = ('none', 0.0) #keep track of MF with maximum firing strength
for ling in outputMFs[outKey]: #for each MF in the input
#with Timer() as t:
fs_x, fs_y = fuzz.fuzzy_and(outputMFs[outKey][ling][0], outputMFs[outKey][ling][1], outXs, outYs)
#print '----------> AND output time:', t.msecs, 'ms'
fs = max(fs_y) #get firing strength of data point and given antecedent MF
if fs > max_fs[1]: max_fs = (ling,fs)
conts[(outKey,) + (max_fs[0],)] = max_fs[1] #append rule with highest firing strength to antecedent
if len(conts) > 0:
rule_deg = rule_deg * reduce(operator.mul, [conts[k] for k in conts]) #use to calc "degree" or strength of each rule
else: rule_deg = 0.0
return [ants, conts, rule_deg]
def fuzzifyData(dataFile, outputKey, inMFtype='gauss', outMFtype='gauss'):
fuzzData = []
for point in dataFile:
fuzIn = {} #create input MFs for each input
for inp in point[q]:
#create singleton input MFs
mean = sum(point[q][inp])/len(point[q][inp]) #get mean of range (single value)
fuzIn[inp[0]+'_'+inp[1]] = fuzzyOps.rangeToMF([mean], inMFtype)
fuzOut = {}
fuzOut[outputKey] = fuzzyOps.rangeToMF(point[2], outMFtype)
fuzzData.append([fuzIn, fuzOut])
return fuzzData
def fuzzifyData(dataFile, outputKey, inMFtype='gauss', outMFtype='gauss'):
fuzzData = []
for point in dataFile:
fuzIn = {} #create input MFs for each input
for inp in point[q]:
#create singleton input MFs
mean = sum(point[q][inp]) / len(
point[q][inp]) #get mean of range (single value)
fuzIn[inp[0] + '_' + inp[1]] = fuzzyOps.rangeToMF([mean], inMFtype)
fuzOut = {}
fuzOut[outputKey] = fuzzyOps.rangeToMF(point[2], outMFtype)
fuzzData.append([fuzIn, fuzOut])
return fuzzData
def runFramework(opts): #run each option set
#print opts
#Evaluate phi
_VLT_w = getInputs(None, 'VL_SYS_TYPE', 'w', opts)[0] #VL_SYS_TYPE_w :
VLT_w = fuzzyOps.rangeToMF(_VLT_w, 'gauss')
_VLT_ed = getInputs(None, 'VL_SYS_TYPE', 'e_d', opts)[0] #VL_SYS_TYPE_e_d
VLT_ed = fuzzyOps.rangeToMF(_VLT_ed, 'gauss')
_VLP_w = getInputs(None, 'VL_SYS_PROP', 'w', opts)[0] #VL_SYS_PROP_w
VLP_w= fuzzyOps.rangeToMF(_VLP_w, 'gauss')
_VLTe_w = getInputs(None, 'VL_SYS_TECH', 'w', opts)[0] #VL_SYS_TECH_w
VLTe_w = fuzzyOps.rangeToMF(_VLTe_w, 'gauss')
_FSP_phi = getInputs(None, 'FWD_SYS_PROP', 'phi', opts)[0] #FWD_SYS_PROP_phi
FSP_phi = fuzzyOps.rangeToMF(_FSP_phi, 'gauss')
_FSP_etap = getInputs(None, 'FWD_SYS_PROP', 'eta_p', opts)[0]#FWD_SYS_PROP_eta_p : FWD system prop efficiency
FSP_etap = fuzzyOps.rangeToMF(_FSP_etap, 'gauss')
_FST_TP = getInputs(None, 'FWD_SYS_TYPE', 'TP', opts)[0] #FWD_SYS_TYPE_TP
FST_TP = fuzzyOps.rangeToMF(_FST_TP, 'gauss')
_WST_phi = getInputs(None, 'WING_SYS_TYPE', 'phi', opts)[0] #WING_SYS_TYPE_phi
WST_phi = fuzzyOps.rangeToMF(_WST_phi, 'gauss')
_WST_WS = getInputs(None, 'WING_SYS_TYPE', 'WS', opts)[0] #WING_SYS_TYPE_WS : WING system wing loading
WST_WS = fuzzyOps.rangeToMF(_WST_WS, 'gauss')
_WST_LD = getInputs(None, 'WING_SYS_TYPE', 'LD', opts)[0] #WING_SYS_TYPE_LD
WST_LD = fuzzyOps.rangeToMF(_WST_LD, 'gauss')
_EST_phi = getInputs(None, 'ENG_SYS_TYPE', 'phi', opts)[0] #ENG_SYS_TYPE_phi
EST_phi = fuzzyOps.rangeToMF(_EST_phi, 'gauss')
_EST_SFC = getInputs(None, 'ENG_SYS_TYPE', 'SFC', opts)[0] #ENG_SYS_TYPE_SFC
EST_SFC = fuzzyOps.rangeToMF(_EST_SFC, 'gauss')
_VLTe_phi = getInputs(None, 'VL_SYS_TECH', 'phi', opts)[0]
VLTe_phi = fuzzyOps.rangeToMF(_VLTe_phi, 'gauss')#'VL_SYS_TECH_phi'
_VLD_phi = getInputs(None, 'VL_SYS_DRV', 'phi', opts)[0]
VLD_phi = fuzzyOps.rangeToMF(_VLD_phi, 'gauss')#'VL_SYS_DRV_phi'
_VLT_TP = getInputs(None, 'VL_SYS_TYPE', 'TP', opts)[0]
VLT_TP = fuzzyOps.rangeToMF(_VLT_TP, 'gauss')#'VL_SYS_TYPE_TP'
_VLT_phi = getInputs(None, 'VL_SYS_TYPE', 'phi', opts)[0]
VLT_phi = fuzzyOps.rangeToMF(_VLT_phi, 'gauss')#'VL_SYS_TYPE_phi'
_VLP_phi = getInputs(None, 'VL_SYS_PROP', 'phi', opts)[0]
VLP_phi = fuzzyOps.rangeToMF(_VLP_phi, 'gauss')#'VL_SYS_PROP_phi'
_FSD_etad = getInputs(None, 'FWD_SYS_DRV', 'eta_d', opts)[0]
FSD_etad = fuzzyOps.rangeToMF(_FSD_etad, 'gauss')#FWD_SYS_DRV', 'eta_d'
_FST_phi = getInputs(None, 'FWD_SYS_TYPE', 'phi', opts)[0]
FST_phi = fuzzyOps.rangeToMF(_FST_phi, 'gauss')#FWD_SYS_TYPE', 'phi'
_VLTe_f = getInputs(None, 'VL_SYS_TECH', 'f', opts)[0]
VLTe_f = fuzzyOps.rangeToMF(_VLTe_f, 'gauss')#VL_SYS_TECH', 'f'
_VLT_f = getInputs(None, 'VL_SYS_TYPE', 'f', opts)[0]
VLT_f = fuzzyOps.rangeToMF(_VLT_f, 'gauss') #VL_SYS_TYPE', 'f'
_VLTe_LD = getInputs(None, 'VL_SYS_TECH', 'LD', opts)[0]
VLTe_LD = fuzzyOps.rangeToMF(_VLTe_LD, 'gauss')#VL_SYS_TECH', 'LD'
_WST_f = getInputs(None, 'WING_SYS_TYPE', 'f', opts)[0]
WST_f = fuzzyOps.rangeToMF(_WST_f, 'gauss') #WING_SYS_TYPE', 'f'
output_phi = phi_sys.run( { 'VL_SYS_TECH_phi': VLTe_phi,
'FWD_SYS_DRV_eta_d': FSD_etad,
'FWD_SYS_TYPE_phi': FST_phi,
'VL_SYS_TECH_f': VLTe_f,
'FWD_SYS_PROP_eta_p': FSP_etap,
'VL_SYS_TECH_w': VLTe_w,
'VL_SYS_TYPE_f': VLT_f,
'VL_SYS_TECH_LD': VLTe_LD,
'WING_SYS_TYPE_LD': WST_LD,
'FWD_SYS_TYPE_TP': FST_TP,
'VL_SYS_TYPE_w': VLT_w,
'WING_SYS_TYPE_f': WST_f,
'VL_SYS_PROP_w': VLP_w,
'VL_SYS_TYPE_phi': VLT_phi,
'VL_SYS_PROP_phi': VLP_phi, })
sysOut_phi = output_phi['sys_phi']
#Evaluate FoM
_ed = getInputs(None, 'VL_SYS_TYPE', 'e_d', opts)[0] #download
ed = fuzzyOps.rangeToMF(_ed, 'gauss')
_sigma = getInputs(None, 'VL_SYS_PROP', 'sigma', opts)[0] #solidity
sigma = fuzzyOps.rangeToMF(_sigma, 'gauss')
#_w = getInputs('VL_SYS', None, 'w', opts) #diskloading (average)
#_w = [np.average([x[0] for x in _w]), np.average([x[1] for x in _w])]
_w1 = getInputs(None, 'VL_SYS_TYPE', 'w', opts)[0] #solidity
_w2 = getInputs(None, 'VL_SYS_PROP', 'w', opts)[0] #solidity
_w3 = getInputs(None, 'VL_SYS_TECH', 'w', opts)[0] #solidity
_w = [max(_w3[0], np.average([_w1[0], _w2[0]])), min(_w3[1], np.average([_w1[1], _w2[1]])) ]
sigma = fuzzyOps.rangeToMF(_sigma, 'gauss')
w = fuzzyOps.rangeToMF(_w, 'gauss')
_eta = getInputs(None, 'VL_SYS_DRV', 'eta_d', opts)[0] #drive efficiency
eta = fuzzyOps.rangeToMF(_eta, 'gauss')
output_FM = FM_sys.run({'DATA_e_d': ed, 'DATA_sigma': sigma, 'DATA_w': w, 'DATA_eta': eta})
sysOut_FoM = output_FM['sys_FoM']
#Evaluate L/D
_f = getInputs(None, None, 'f', opts) #get drag (intersection)
_f = [np.average([x[0] for x in _f]), np.average([x[1] for x in _f])]
f = fuzzyOps.rangeToMF(_f, 'trap')
_LDw = getInputs(None, 'WING_SYS_TYPE', 'LD', opts)[0]
_LDvt = getInputs(None, 'VL_SYS_TECH', 'LD', opts)[0]
_LD = [max([_LDw[0], _LDvt[0]]), min([_LDw[1], _LDvt[1]])]
LD = fuzzyOps.rangeToMF(_LD, 'trap')
output_LD = LoD_sys.run({'SYSTEM_f': f, 'WING_LoD': LD})
sysOut_LD = output_LD['sys_LoD']
#Evaluate eta_P
_FST_etap = getInputs(None, 'FWD_SYS_TYPE', 'eta_p', opts)[0]# : FWD system type efficiency
_FSD_etap = getInputs(None, 'FWD_SYS_DRV', 'eta_p', opts)[0]# : FWD system type efficiency
_FWD_etap = [max( [_FST_etap[0], _FSP_etap[0], _FSD_etap[0]] ), min( [_FST_etap[1], _FSP_etap[1], _FSD_etap[1]] )]
FWD_etap = fuzzyOps.rangeToMF(_FWD_etap, 'trap')
_FSD_etad = getInputs(None, 'FWD_SYS_DRV', 'eta_d', opts)[0]# : FWD drive efficiency
FSD_etad = fuzzyOps.rangeToMF(_FSD_etad, 'trap')
output_etaP = etaP_sys.run({'FWD_SYS_eta_p': FWD_etap,
'FWD_DRV_eta_d' : FSD_etad, })
sysOut_etaP = output_etaP['sys_etaP']
# Evaluate RF Methods
inR = [1,9]
outR = [0.85, 0.5]
sysPHI = quantify(output_phi['sys_phi'], inR, outR) #quantify phi
outR = [0.75,0.35]
quantSFC = quantify(EST_SFC, inR, outR) #quantify phi
VL_SYS_TYPE = opts[0]
FWD_SYS_TYPE = opts[6]
if FWD_SYS_TYPE == 2:
T = 1 #tiling VL
else:
if VL_SYS_TYPE < 4:
T = 2 #compound
if VL_SYS_TYPE == 4 or VL_SYS_TYPE == 5:
T = 3 #other
if VL_SYS_TYPE == 6:
T = 1 #tilting tailsitter
SYSTYPE = fuzzyOps.rangeToMF([T,T], 'gauss')
###
#print "w:", _w, " WS:", _WST_WS, " etad:", _eta, " e_d:", _ed, " type:", T
###
output_GWT = GWT_sys.run({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
'SYS_type': SYSTYPE,})# 'SYS_tech': SYSTECH,}) #'SYS_jet': SYSJET})
sysOut_GWT = output_GWT['sys_GWT']
output_Pin = Pin_sys.run({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
'SYS_type': SYSTYPE,})# 'SYS_tech': SYSTECH,}) #'SYS_jet': SYSJET})
sysOut_Pin = output_Pin['sys_Pinst']
#Pin_sys.test([({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
# 'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
# 'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
# 'SYS_type': SYSTYPE,}, output_Pin) ], plotPoints=1)
output_VH = VH_sys.run({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
'SYS_type': SYSTYPE,})# 'SYS_tech': SYSTECH,})# 'SYS_jet': SYSJET})
sysOut_VH = output_VH['sys_VH']
#output_eWT = eWT_sys.run({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
# 'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
# 'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, 'SYS_dragX': f,
# 'SYS_type': SYSTYPE, 'SYS_tech': SYSTECH, 'SYS_jet': SYSJET})
#results[system_options.index(opts)].append(output_eWT['sys_eWT'])
return sysOut_phi, sysOut_FoM, sysOut_LD, sysOut_etaP, sysOut_GWT, sysOut_Pin, sysOut_VH
def runFramework(opts): #run each option set
#print opts
#Evaluate phi
_VLT_w = getInputs(None, 'VL_SYS_TYPE', 'w', opts)[0] #VL_SYS_TYPE_w :
VLT_w = fuzzyOps.rangeToMF(_VLT_w, 'gauss')
_VLT_ed = getInputs(None, 'VL_SYS_TYPE', 'e_d', opts)[0] #VL_SYS_TYPE_e_d
VLT_ed = fuzzyOps.rangeToMF(_VLT_ed, 'gauss')
_VLP_w = getInputs(None, 'VL_SYS_PROP', 'w', opts)[0] #VL_SYS_PROP_w
VLP_w = fuzzyOps.rangeToMF(_VLP_w, 'gauss')
_VLTe_w = getInputs(None, 'VL_SYS_TECH', 'w', opts)[0] #VL_SYS_TECH_w
VLTe_w = fuzzyOps.rangeToMF(_VLTe_w, 'gauss')
_FSP_phi = getInputs(None, 'FWD_SYS_PROP', 'phi',
opts)[0] #FWD_SYS_PROP_phi
FSP_phi = fuzzyOps.rangeToMF(_FSP_phi, 'gauss')
_FSP_etap = getInputs(
None, 'FWD_SYS_PROP', 'eta_p',
opts)[0] #FWD_SYS_PROP_eta_p : FWD system prop efficiency
FSP_etap = fuzzyOps.rangeToMF(_FSP_etap, 'gauss')
_FST_TP = getInputs(None, 'FWD_SYS_TYPE', 'TP', opts)[0] #FWD_SYS_TYPE_TP
FST_TP = fuzzyOps.rangeToMF(_FST_TP, 'gauss')
_WST_phi = getInputs(None, 'WING_SYS_TYPE', 'phi',
opts)[0] #WING_SYS_TYPE_phi
WST_phi = fuzzyOps.rangeToMF(_WST_phi, 'gauss')
_WST_WS = getInputs(None, 'WING_SYS_TYPE', 'WS',
opts)[0] #WING_SYS_TYPE_WS : WING system wing loading
WST_WS = fuzzyOps.rangeToMF(_WST_WS, 'gauss')
_WST_LD = getInputs(None, 'WING_SYS_TYPE', 'LD',
opts)[0] #WING_SYS_TYPE_LD
WST_LD = fuzzyOps.rangeToMF(_WST_LD, 'gauss')
_EST_phi = getInputs(None, 'ENG_SYS_TYPE', 'phi',
opts)[0] #ENG_SYS_TYPE_phi
EST_phi = fuzzyOps.rangeToMF(_EST_phi, 'gauss')
_EST_SFC = getInputs(None, 'ENG_SYS_TYPE', 'SFC',
opts)[0] #ENG_SYS_TYPE_SFC
EST_SFC = fuzzyOps.rangeToMF(_EST_SFC, 'gauss')
_VLTe_phi = getInputs(None, 'VL_SYS_TECH', 'phi', opts)[0]
VLTe_phi = fuzzyOps.rangeToMF(_VLTe_phi, 'gauss') #'VL_SYS_TECH_phi'
_VLD_phi = getInputs(None, 'VL_SYS_DRV', 'phi', opts)[0]
VLD_phi = fuzzyOps.rangeToMF(_VLD_phi, 'gauss') #'VL_SYS_DRV_phi'
_VLT_TP = getInputs(None, 'VL_SYS_TYPE', 'TP', opts)[0]
VLT_TP = fuzzyOps.rangeToMF(_VLT_TP, 'gauss') #'VL_SYS_TYPE_TP'
_VLT_phi = getInputs(None, 'VL_SYS_TYPE', 'phi', opts)[0]
VLT_phi = fuzzyOps.rangeToMF(_VLT_phi, 'gauss') #'VL_SYS_TYPE_phi'
_VLP_phi = getInputs(None, 'VL_SYS_PROP', 'phi', opts)[0]
VLP_phi = fuzzyOps.rangeToMF(_VLP_phi, 'gauss') #'VL_SYS_PROP_phi'
_FSD_etad = getInputs(None, 'FWD_SYS_DRV', 'eta_d', opts)[0]
FSD_etad = fuzzyOps.rangeToMF(_FSD_etad, 'gauss') #FWD_SYS_DRV', 'eta_d'
_FST_phi = getInputs(None, 'FWD_SYS_TYPE', 'phi', opts)[0]
FST_phi = fuzzyOps.rangeToMF(_FST_phi, 'gauss') #FWD_SYS_TYPE', 'phi'
_VLTe_f = getInputs(None, 'VL_SYS_TECH', 'f', opts)[0]
VLTe_f = fuzzyOps.rangeToMF(_VLTe_f, 'gauss') #VL_SYS_TECH', 'f'
_VLT_f = getInputs(None, 'VL_SYS_TYPE', 'f', opts)[0]
VLT_f = fuzzyOps.rangeToMF(_VLT_f, 'gauss') #VL_SYS_TYPE', 'f'
_VLTe_LD = getInputs(None, 'VL_SYS_TECH', 'LD', opts)[0]
VLTe_LD = fuzzyOps.rangeToMF(_VLTe_LD, 'gauss') #VL_SYS_TECH', 'LD'
_WST_f = getInputs(None, 'WING_SYS_TYPE', 'f', opts)[0]
WST_f = fuzzyOps.rangeToMF(_WST_f, 'gauss') #WING_SYS_TYPE', 'f'
output_phi = phi_sys.run({
'VL_SYS_TECH_phi': VLTe_phi,
'FWD_SYS_DRV_eta_d': FSD_etad,
'FWD_SYS_TYPE_phi': FST_phi,
'VL_SYS_TECH_f': VLTe_f,
'FWD_SYS_PROP_eta_p': FSP_etap,
'VL_SYS_TECH_w': VLTe_w,
'VL_SYS_TYPE_f': VLT_f,
'VL_SYS_TECH_LD': VLTe_LD,
'WING_SYS_TYPE_LD': WST_LD,
'FWD_SYS_TYPE_TP': FST_TP,
'VL_SYS_TYPE_w': VLT_w,
'WING_SYS_TYPE_f': WST_f,
'VL_SYS_PROP_w': VLP_w,
'VL_SYS_TYPE_phi': VLT_phi,
'VL_SYS_PROP_phi': VLP_phi,
})
sysOut_phi = output_phi['sys_phi']
#Evaluate FoM
_ed = getInputs(None, 'VL_SYS_TYPE', 'e_d', opts)[0] #download
ed = fuzzyOps.rangeToMF(_ed, 'gauss')
_sigma = getInputs(None, 'VL_SYS_PROP', 'sigma', opts)[0] #solidity
sigma = fuzzyOps.rangeToMF(_sigma, 'gauss')
#_w = getInputs('VL_SYS', None, 'w', opts) #diskloading (average)
#_w = [np.average([x[0] for x in _w]), np.average([x[1] for x in _w])]
_w1 = getInputs(None, 'VL_SYS_TYPE', 'w', opts)[0] #solidity
_w2 = getInputs(None, 'VL_SYS_PROP', 'w', opts)[0] #solidity
_w3 = getInputs(None, 'VL_SYS_TECH', 'w', opts)[0] #solidity
_w = [
max(_w3[0], np.average([_w1[0], _w2[0]])),
min(_w3[1], np.average([_w1[1], _w2[1]]))
]
sigma = fuzzyOps.rangeToMF(_sigma, 'gauss')
w = fuzzyOps.rangeToMF(_w, 'gauss')
_eta = getInputs(None, 'VL_SYS_DRV', 'eta_d', opts)[0] #drive efficiency
eta = fuzzyOps.rangeToMF(_eta, 'gauss')
output_FM = FM_sys.run({
'DATA_e_d': ed,
'DATA_sigma': sigma,
'DATA_w': w,
'DATA_eta': eta
})
sysOut_FoM = output_FM['sys_FoM']
#Evaluate L/D
_f = getInputs(None, None, 'f', opts) #get drag (intersection)
_f = [np.average([x[0] for x in _f]), np.average([x[1] for x in _f])]
f = fuzzyOps.rangeToMF(_f, 'trap')
_LDw = getInputs(None, 'WING_SYS_TYPE', 'LD', opts)[0]
_LDvt = getInputs(None, 'VL_SYS_TECH', 'LD', opts)[0]
_LD = [max([_LDw[0], _LDvt[0]]), min([_LDw[1], _LDvt[1]])]
LD = fuzzyOps.rangeToMF(_LD, 'trap')
output_LD = LoD_sys.run({'SYSTEM_f': f, 'WING_LoD': LD})
sysOut_LD = output_LD['sys_LoD']
#Evaluate eta_P
_FST_etap = getInputs(None, 'FWD_SYS_TYPE', 'eta_p',
opts)[0] # : FWD system type efficiency
_FSD_etap = getInputs(None, 'FWD_SYS_DRV', 'eta_p',
opts)[0] # : FWD system type efficiency
_FWD_etap = [
max([_FST_etap[0], _FSP_etap[0], _FSD_etap[0]]),
min([_FST_etap[1], _FSP_etap[1], _FSD_etap[1]])
]
FWD_etap = fuzzyOps.rangeToMF(_FWD_etap, 'trap')
_FSD_etad = getInputs(None, 'FWD_SYS_DRV', 'eta_d',
opts)[0] # : FWD drive efficiency
FSD_etad = fuzzyOps.rangeToMF(_FSD_etad, 'trap')
output_etaP = etaP_sys.run({
'FWD_SYS_eta_p': FWD_etap,
'FWD_DRV_eta_d': FSD_etad,
})
sysOut_etaP = output_etaP['sys_etaP']
# Evaluate RF Methods
inR = [1, 9]
outR = [0.85, 0.5]
sysPHI = quantify(output_phi['sys_phi'], inR, outR) #quantify phi
outR = [0.75, 0.35]
quantSFC = quantify(EST_SFC, inR, outR) #quantify phi
VL_SYS_TYPE = opts[0]
FWD_SYS_TYPE = opts[6]
if FWD_SYS_TYPE == 2:
T = 1 #tiling VL
else:
if VL_SYS_TYPE < 4:
T = 2 #compound
if VL_SYS_TYPE == 4 or VL_SYS_TYPE == 5:
T = 3 #other
if VL_SYS_TYPE == 6:
T = 1 #tilting tailsitter
SYSTYPE = fuzzyOps.rangeToMF([T, T], 'gauss')
###
#print "w:", _w, " WS:", _WST_WS, " etad:", _eta, " e_d:", _ed, " type:", T
###
output_GWT = GWT_sys.run({
'SYSTEM_QUANT_PHI': sysPHI,
'VL_SYS_w': w,
'WING_SYS_TYPE_WS': WST_WS,
'sys_etaP': output_etaP['sys_etaP'],
'VL_SYS_DRV_eta_d': eta,
'sys_FoM': output_FM['sys_FoM'],
'VL_SYS_e_d': ed,
'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
'SYS_type': SYSTYPE,
}) # 'SYS_tech': SYSTECH,}) #'SYS_jet': SYSJET})
sysOut_GWT = output_GWT['sys_GWT']
output_Pin = Pin_sys.run({
'SYSTEM_QUANT_PHI': sysPHI,
'VL_SYS_w': w,
'WING_SYS_TYPE_WS': WST_WS,
'sys_etaP': output_etaP['sys_etaP'],
'VL_SYS_DRV_eta_d': eta,
'sys_FoM': output_FM['sys_FoM'],
'VL_SYS_e_d': ed,
'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
'SYS_type': SYSTYPE,
}) # 'SYS_tech': SYSTECH,}) #'SYS_jet': SYSJET})
sysOut_Pin = output_Pin['sys_Pinst']
#Pin_sys.test([({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
# 'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
# 'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
# 'SYS_type': SYSTYPE,}, output_Pin) ], plotPoints=1)
output_VH = VH_sys.run({
'SYSTEM_QUANT_PHI': sysPHI,
'VL_SYS_w': w,
'WING_SYS_TYPE_WS': WST_WS,
'sys_etaP': output_etaP['sys_etaP'],
'VL_SYS_DRV_eta_d': eta,
'sys_FoM': output_FM['sys_FoM'],
'VL_SYS_e_d': ed,
'ENG_SYS_TYPE_SFC': quantSFC, #'SYS_dragX': f,
'SYS_type': SYSTYPE,
}) # 'SYS_tech': SYSTECH,})# 'SYS_jet': SYSJET})
sysOut_VH = output_VH['sys_VH']
#output_eWT = eWT_sys.run({ 'SYSTEM_QUANT_PHI': sysPHI , 'VL_SYS_w': w, 'WING_SYS_TYPE_WS': WST_WS,
# 'sys_etaP': output_etaP['sys_etaP'], 'VL_SYS_DRV_eta_d': eta, 'sys_FoM': output_FM['sys_FoM'],
# 'VL_SYS_e_d': ed, 'ENG_SYS_TYPE_SFC': quantSFC, 'SYS_dragX': f,
# 'SYS_type': SYSTYPE, 'SYS_tech': SYSTECH, 'SYS_jet': SYSJET})
#results[system_options.index(opts)].append(output_eWT['sys_eWT'])
return sysOut_phi, sysOut_FoM, sysOut_LD, sysOut_etaP, sysOut_GWT, sysOut_Pin, sysOut_VH
#build inputs
fig1, ax1 = plt.subplots(figsize=(7, 7))
fig2, ax2 = plt.subplots(nrows=len(ps_inputs) / 2, ncols=2)
for alt in ps_inputs:
#union of drag evals
f = [
max(alt[1][0], alt[2][0], alt[3][0], alt[4][0]),
min(alt[1][1], alt[2][1], alt[3][1], alt[4][1])
]
print alt[0], f
#SYSTEM_f_x = np.arange(0.9*f[0], 1.1*f[1], (1.1*f[1]-0.9*f[0])/100.0)
#SYSTEM_f = fuzz.trapmf(SYSTEM_f_x, [f[0],f[0],f[1],f[1]]) #trap input MFS
#SYSTEM_f = fuzz.trimf(SYSTEM_f_x, [f[0],0.5*(f[0]+f[1]),f[1]]) #tri input MFS
SYSTEM_f = fuzzyOps.rangeToMF(f, 'trap')
LoD = [min(alt[6]), max(alt[6])]
#WING_LoD_x = np.arange(0.9*LoD[0], 1.1*LoD[1], (1.1*LoD[1]-0.8*LoD[0])/100.0)
#WING_LoD = fuzz.trapmf(WING_LoD_x, [LoD[0],LoD[0],LoD[1],LoD[1]]) #trap input MFS
#WING_LoD = fuzz.trimf(WING_LoD_x, [LoD[0],0.5*(LoD[0]+LoD[1]),LoD[1]]) #tri input MFS
WING_LoD = fuzzyOps.rangeToMF(LoD, 'trap')
output = sys.run({
'SYSTEM_f': SYSTEM_f,
'WING_LoD': WING_LoD
},
TESTMODE=True)
output = output['sys_LoD']
#plot ranges from max alpha cuts
outRange = fuzzyOps.alpha_at_val(output[0], output[1])
def getError(truthData, system, inMF='sing', outMF='sing', sysOutType='crisp', errType='dist'):
"""
Get a system's error against a set of truth data.
------INPUTS------
truthData - list
truth data to compare system output to in form:
[Quant Input, Qual Input, Output]
with inputs as {('input'): [values], ('input'): [values], ... }
and outputs as [output value(s)]
system : module
instance of system to get error on
inMF : string
type of MF to use for input data ('sing', 'tri', 'trap', 'gauss')
outMF : string
type of MF to use for output data ('sing', 'tri', 'trap', 'gauss')
sysOutType : string
type of output to use from system ('crisp' or 'fuzzy')
converts fuzzy outputs to crisp via 'centroid' defuzzification
errType : string
type of fuzzy error measurement to use ('int' : integration type, 'ac' : alpha-cut type)
------OUTPUTS------
error : list
list of [truth, output, errors]
"""
q = 0 #use quantitative data
#Turn Data to MFs
for point in truthData:
for inp in point[q]: #create input MFs for each input
#if type(point[q][inp]) <> list: point[q][inp] = [point[q][inp]]
if len(point[q][inp]) == 1 and inMF == 'sing': #for crisp inputs don't get singleton MF yet
point[q][inp] = point[q][inp][0]
else:
if not hasattr(point[q][inp][0], '__iter__'): #if not already fuzzy
point[q][inp] = fuzzyOps.rangeToMF(point[q][inp], inMF)
if not hasattr(point[2][0],'__iter__'): #if not already fuzzy
point[2] = fuzzyOps.rangeToMF(point[2], outMF) #create output MFs
#Get system responses to data
i = 0
for point in truthData:
i = i + 1
if not isinstance(point[0].keys()[0], str): #if data inputs are ('system', 'input')
inputs = {key[0]+"_"+key[1]:point[0][key] for key in point[0]}
else: #if data inputs are ('system_input')
inputs = point[0]
output = system.run(inputs)
if isinstance(output, dict): output = output.itervalues().next()
point.append(output)
error = [] #track error for output
for point in truthData:
#get error
if not outMF=='sing' and not sysOutType == 'crisp': #if both output and data are fuzzy
if errType == 'dist':
err = fuzDistAC(point[2], point[3]) #inflate error if can't solve for it
elif errType == 'int':
err = fuzErrorInt(point[2], point[3])
elif errType == 'ac':
p_err, s_err = fuzErrorAC(point[2], point[3]) #get position and spread error
err = p_err + 0.5*s_err
elif outMF=='sing' and sysOutType=='crisp': #if both output and data are crisp
err = point[2] - point[3]
elif not outDataMFs=='sing' and isinstance(output, float): #if both output is fuzzy and data is crisp
raise ValueError('You have not created a case for this yet')
elif outDataMFs=='sing' and isinstance(output, list): #if both output is crisp and data is fuzzy
raise ValueError('You have not created a case for this yet')
error.append([point[2], point[3], err])
return error
('VL_SYS_PROP', 'w'),
('VL_SYS_TYPE', 'phi'),
('VL_SYS_PROP', 'phi'), ]
inRanges = {inp[0]+"_"+inp[1] : input_ranges[inp[1]] for inp in inputList} #set exact inputs
outRanges = {'sys_phi' : output_ranges['sys_phi'] }
#Turn data into fuzzy MFs
fuzzData = []
for point in combinedData:
fuzIn = {} #create input MFs for each input
for inp in point[q]:
#create singleton input MFs
mean = sum(point[q][inp])/len(point[q][inp]) #get mean of range (single value)
fuzIn[inp[0]+'_'+inp[1]] = fuzzyOps.rangeToMF([mean], 'gauss')
fuzOut = {} #create trapezoidal output MFs
fuzOut['sys_phi'] = fuzzyOps.rangeToMF(point[2], 'gauss')
fuzzData.append([fuzIn, fuzOut])
############### TRAINING CASES ###############
############### TRAINING CASES ###############
maxIter = 35
xConverge = 0.001
## TRAINING CASE 1:
nData = (300, 0.15) #data to use, holdback rate
nNodes = (200, 30, 40) #hidden nodes, input gran, output gran
"SFC_quant": 7,
"type": 8,
},
outputCols={"sys_VH": 26},
)
q = 0 # use first (quant inputs)
# turn data into fuzzy MFs
fuzzData = []
for point in combData:
fuzIn = {} # create input MFs for each input
for inp in point[q]:
# create singleton input MFs
mean = sum(point[q][inp]) / len(point[q][inp]) # get mean of range (single value)
fuzIn[inp[0] + "_" + inp[1]] = fuzzyOps.rangeToMF([mean], "gauss")
fuzOut = {}
fuzOut["sys_VH"] = fuzzyOps.rangeToMF(point[2], "gauss")
fuzzData.append([fuzIn, fuzOut])
sys.train(
fuzzData, holdback=0.05, LR=0.1, M=0.05, maxIterations=170, xConverge=0.005, interactive=False, combError=True
)
sys.write_weights("FCL_files/RFdata_DFES_VH_40_250_50.nwf") # write network weight file
# sys.test(random.sample(fuzzData,100), plotPoints=10)
"""
## RF TEST ###
inRanges = { 'DATA_phi': [0.5, 0.95],
'DATA_w': [1.0, 150.0],
outputCols={'sys_VH': 26})
### Pinst
plt.figure()
for dat in combData_Pin[:]:
if dat[2][0] == dat[2][1]: r = 0.01 * dat[2][0]
else: r = dat[2][1] - dat[2][0]
xs = np.arange(dat[2][0] - r, dat[2][1] + r, r / 20)
mean = sum(dat[2]) / 2.0
std = r / 3.0
#h = list(np.random.normal(mean, std, size=200))
#alldata = alldata + h
ys = stats.norm.pdf(xs, mean, std)
ys = [y / max(ys) for y in ys]
#plt.plot(xs, ys, c='b', alpha=0.2)
fx, fy = fuzzyOps.rangeToMF(dat[2], 'gauss')
plt.plot(fx, fy, c='b', alpha=0.25)
plt.xlabel('Power Installed (shp)')
plt.xlim([1000, 14000])
plt.ylabel('Membership')
"""
plt.figure()
### GWT
alldata = []
for dat in combData_GWT[:]:
if dat[2][0] == dat[2][1]: r = 0.1*dat[2][0]
else: r = dat[2][1] - dat[2][0]
#print dat[2][0]-r, dat[2][1]+r, r
#if dat[0] == dat[2][1]: xs = np.arange(dat[2][0]-r, dat[2][1]+r, r/5.0)
xs = np.arange(dat[2][0]-r, dat[2][1]+r, r/20.0)
#build inputs
fig1, ax1 = plt.subplots(figsize=(7, 7))
fig2, ax2 = plt.subplots(nrows=len(ps_inputs)/2, ncols=2)
for alt in ps_inputs:
#union of drag evals
f = [max(alt[1][0], alt[2][0], alt[3][0], alt[4][0]),
min(alt[1][1], alt[2][1], alt[3][1], alt[4][1])]
print alt[0], f
#SYSTEM_f_x = np.arange(0.9*f[0], 1.1*f[1], (1.1*f[1]-0.9*f[0])/100.0)
#SYSTEM_f = fuzz.trapmf(SYSTEM_f_x, [f[0],f[0],f[1],f[1]]) #trap input MFS
#SYSTEM_f = fuzz.trimf(SYSTEM_f_x, [f[0],0.5*(f[0]+f[1]),f[1]]) #tri input MFS
SYSTEM_f = fuzzyOps.rangeToMF(f, 'trap')
LoD = [min(alt[6]), max(alt[6])]
#WING_LoD_x = np.arange(0.9*LoD[0], 1.1*LoD[1], (1.1*LoD[1]-0.8*LoD[0])/100.0)
#WING_LoD = fuzz.trapmf(WING_LoD_x, [LoD[0],LoD[0],LoD[1],LoD[1]]) #trap input MFS
#WING_LoD = fuzz.trimf(WING_LoD_x, [LoD[0],0.5*(LoD[0]+LoD[1]),LoD[1]]) #tri input MFS
WING_LoD = fuzzyOps.rangeToMF(LoD, 'trap')
output = sys.run({'SYSTEM_f': SYSTEM_f,
'WING_LoD': WING_LoD }, TESTMODE=True)
output = output['sys_LoD']
#plot ranges from max alpha cuts
outRange = fuzzyOps.alpha_at_val(output[0], output[1])
#calculate overlap
mean = sum(point[q][inp])/len(point[q][inp]) #get mean of range (single value)
fuzIn[inp[0]+'_'+inp[1]] = fuzzyOps.rangeToMF([mean], 'gauss')
fuzOut = {} #create trapezoidal output MFs
fuzOut['sys_FoM'] = fuzzyOps.rangeToMF(point[2], 'gauss')
fuzzData.append([fuzIn, fuzOut])
"""
fuzzData_tri = []
for point in combData:
fuzIn = {} #create input MFs for each input
for inp in point[q]:
#create singleton input MFs
mean = sum(point[q][inp])/len(point[q][inp]) #get mean of range (single value)
fuzIn[inp[0]+'_'+inp[1]] = fuzzyOps.rangeToMF([mean], 'tri')
fuzOut = {} #create trapezoidal output MFs
fuzOut['sys_FoM'] = fuzzyOps.rangeToMF(point[2], 'tri')
fuzzData_tri.append([fuzIn, fuzOut])
fuzzData_trap = []
for point in combData:
fuzIn = {} #create input MFs for each input
for inp in point[q]:
#create singleton input MFs
mean = sum(point[q][inp])/len(point[q][inp]) #get mean of range (single value)
fuzIn[inp[0]+'_'+inp[1]] = fuzzyOps.rangeToMF([mean], 'trap')
'SFC_quant': 7,
'type': 8
},
outputCols={'sys_VH': 26})
q = 0 #use first (quant inputs)
# turn data into fuzzy MFs
fuzzData = []
for point in combData:
fuzIn = {} #create input MFs for each input
for inp in point[q]:
#create singleton input MFs
mean = sum(point[q][inp]) / len(
point[q][inp]) #get mean of range (single value)
fuzIn[inp[0] + '_' + inp[1]] = fuzzyOps.rangeToMF([mean], 'gauss')
fuzOut = {}
fuzOut['sys_VH'] = fuzzyOps.rangeToMF(point[2], 'gauss')
fuzzData.append([fuzIn, fuzOut])
sys.train(fuzzData,
holdback=0.05,
LR=0.1,
M=0.05,
maxIterations=170,
xConverge=0.005,
interactive=False,
combError=True)
sys.write_weights(
'FCL_files/RFdata_DFES_VH_40_250_50.nwf') #write network weight file
def execute(self):
#print "Getting: ", [self.option1, self.option2, self.option3, self.option4, self.option5, self.option6, self.option7, self.option8, self.option9]
#if no data read in, read it in.
if len(self.data) == 0:
self.read_fuzzy_data()
#set options from individual functional attibutes
self.options = [int(self.option1), int(self.option2), int(self.option3),
int(self.option4), int(self.option5), int(self.option6),
int(self.option7), int(self.option8), int(self.option9)]
#print "Morph Opts:", self.options
#print 'Building input list from', len(self.data), 'lines of data...'
#get all inputs for selected options
#[ system, aspect, varname, [min,max], quant_option, qual_option ] for each line
var_list = []
for line in self.data:
var_list.append([ line[0], line[1], line[3], line[4], \
line[self.options[self.ASPECT_list.index(line[1])]+4], \
line[self.options[self.ASPECT_list.index(line[1])]+10] ])
### CALCULATE INPUTS: (all use quant data: qual data => q = 10)
q = 4 #for quant data, qual data in q=5
""" PHI SYSTEM: """
fuzzInType = 'gauss'
#VL_SYS_TYPE_phi:
_x = next( var[q] for var in var_list if all((var[2] == 'phi', var[1] == 'VL_SYS_TYPE')) )
self.VL_SYS_TYPE_phi = fuzzyOps.rangeToMF(_x, fuzzInType)
#VL_SYS_TYPE_w :
_x = next( var[q] for var in var_list if all((var[2] == 'w', var[1] == 'VL_SYS_TYPE')) )
self.VL_SYS_TYPE_w = fuzzyOps.rangeToMF(_x, fuzzInType)
#VL_SYS_TYPE_f
_x = next( var[q] for var in var_list if all((var[2] == 'f', var[1] == 'VL_SYS_TYPE')) )
self.VL_SYS_TYPE_f = fuzzyOps.rangeToMF(_x, fuzzInType)
#'VL_SYS_PROP_phi'
_x = next( var[q] for var in var_list if all((var[2] == 'phi', var[1] == 'VL_SYS_PROP')) )
self.VL_SYS_PROP_phi = fuzzyOps.rangeToMF(_x, fuzzInType)
#'VL_SYS_PROP_w'
_x = next( var[q] for var in var_list if all((var[2] == 'w', var[1] == 'VL_SYS_PROP')) )
self.VL_SYS_PROP_w = fuzzyOps.rangeToMF(_x, fuzzInType)
#'VL_SYS_TECH_phi'
_x = next( var[q] for var in var_list if all((var[2] == 'phi', var[1] == 'VL_SYS_TECH')) )
self.VL_SYS_TECH_phi = fuzzyOps.rangeToMF(_x, fuzzInType)
#'VL_SYS_TECH_w'
_x = next( var[q] for var in var_list if all((var[2] == 'w', var[1] == 'VL_SYS_TECH')) )
self.VL_SYS_TECH_w = fuzzyOps.rangeToMF(_x, fuzzInType)
#'VL_SYS_TECH_f'
_x = next( var[q] for var in var_list if all((var[2] == 'f', var[1] == 'VL_SYS_TECH')) )
self.VL_SYS_TECH_f = fuzzyOps.rangeToMF(_x, fuzzInType)
#'VL_SYS_TECH_LD'
_x = next( var[q] for var in var_list if all((var[2] == 'LD', var[1] == 'VL_SYS_TECH')) )
self.VL_SYS_TECH_LD = fuzzyOps.rangeToMF(_x, fuzzInType)
#FWD_SYS_PROP_eta_p : FWD system prop efficiency
_x = next( var[q] for var in var_list if all((var[2] == 'eta_p', var[1] == 'FWD_SYS_PROP')) )
self.FWD_SYS_PROP_eta_p = fuzzyOps.rangeToMF(_x, fuzzInType)
#FWD_SYS_DRV_eta_d : FWD drive efficiency
_x = next( var[q] for var in var_list if all((var[2] == 'eta_d', var[1] == 'FWD_SYS_DRV')) )
self.FWD_SYS_DRV_eta_d = fuzzyOps.rangeToMF(_x, fuzzInType)
#FWD_SYS_TYPE_phi
_x = next( var[q] for var in var_list if all((var[2] == 'phi', var[1] == 'FWD_SYS_TYPE')) )
self.FWD_SYS_TYPE_phi = fuzzyOps.rangeToMF(_x, fuzzInType)
#FWD_SYS_TYPE_TP
_x = next( var[q] for var in var_list if all((var[2] == 'TP', var[1] == 'FWD_SYS_TYPE')) )
self.FWD_SYS_TYPE_TP = fuzzyOps.rangeToMF(_x, fuzzInType)
#WING_SYS_TYPE_LD
_x = next( var[q] for var in var_list if all((var[2] == 'LD', var[1] == 'WING_SYS_TYPE')) )
self.WING_SYS_TYPE_LD = fuzzyOps.rangeToMF(_x, fuzzInType)
#WING_SYS_TYPE_f : WING system wing loading
_x = next( var[q] for var in var_list if all((var[2] == 'f', var[1] == 'WING_SYS_TYPE')) )
self.WING_SYS_TYPE_f = fuzzyOps.rangeToMF(_x, fuzzInType)
#ENG_SYS_TYPE_SFC
_x = next( var[q] for var in var_list if all((var[2] == 'SFC', var[1] == 'ENG_SYS_TYPE')) )
self.ENG_SYS_TYPE_SFC = fuzzyOps.rangeToMF(_x, fuzzInType)
""" LoD SYSTEM: """
fuzzInType = 'trap'
# SYSTEM_f : average system flat plate drag (fuzzy gauss)
_f = [var[q] for var in var_list if (var[2] == 'f') ]
data_range = [np.average([v[0] for v in _f]), np.average([v[1] for v in _f])] #get union
self.SYSTEM_f = fuzzyOps.rangeToMF(data_range, fuzzInType)
#WING_LoD : union of all LoD values (fuzzy gauss)
_ld = [var[q] for var in var_list if var[2] == 'LD']
data_range = [max([v[0] for v in _ld]), min([v[1] for v in _ld])] #get union
self.WING_LoD = fuzzyOps.rangeToMF(data_range, fuzzInType)
""" FOM SYSTEM: """
fuzzInType = 'gauss'
#VL_SYS_w
#_x = [var[q] for var in var_list if all((var[2] == 'w', var[0] == 'VL_SYS'))]
#_x = [ np.average([x[0] for x in _x]), np.average([x[1] for x in _x]) ]
_x1 = next( var[q] for var in var_list if all((var[2] == 'w', var[1] == 'VL_SYS_TYPE')) )
_x2 = next( var[q] for var in var_list if all((var[2] == 'w', var[1] == 'VL_SYS_PROP')) )
_x3 = next( var[q] for var in var_list if all((var[2] == 'w', var[1] == 'VL_SYS_TECH')) )
_x = [ max(np.average([_x1[0],_x2[0]]), _x3[0]), min(np.average([_x1[1],_x2[1]]),_x3[1]) ]
self.VL_SYS_w = fuzzyOps.rangeToMF(_x, fuzzInType)
_w = _x
#VL_SYS_PROP_sigma
_x = next( var[q] for var in var_list if all((var[2] == 'sigma', var[1] == 'VL_SYS_PROP')) )
self.VL_SYS_PROP_sigma = fuzzyOps.rangeToMF(_x, fuzzInType)
#x_2 = _x
#VL_SYS_e_d
_x = next( var[q] for var in var_list if all((var[2] == 'e_d', var[1] == 'VL_SYS_TYPE')) )
self.VL_SYS_e_d = fuzzyOps.rangeToMF(_x, fuzzInType)
_ed = _x
#VL_SYS_DRV_eta_d
_x = next( var[q] for var in var_list if all((var[2] == 'eta_d', var[1] == 'VL_SYS_DRV')) )
self.VL_SYS_DRV_eta_d = fuzzyOps.rangeToMF(_x, fuzzInType)
_eta = _x
#print 'w: %s, sigma: %s, e_d: %s, eta_d: %s' % (x_1, x_2, x_3, x_4)
""" etaP SYSTEM: """
fuzzInType = 'trap'
# FWD_SYS_eta_p : intersection of forward system propulsive efficiencies
_f = [var[q] for var in var_list if all((var[2] == 'eta_p', var[0] == 'FWD_SYS')) ]
data_range = [max([v[0] for v in _f]), min([v[1] for v in _f])] #get union
data_range = sorted(data_range)
self.FWD_SYS_eta_p = fuzzyOps.rangeToMF(data_range, fuzzInType)
#FWD_SYS_eta_d : foward system drive efficiency
_etad = next( var[q] for var in var_list if all((var[2] == 'eta_d', var[1] == 'FWD_SYS_DRV')) )
self.FWD_DRV_eta_d = fuzzyOps.rangeToMF(_etad, fuzzInType)
""" RF SYSTEMs (GWT/Pinst/VH): """
# SYSTEM_QUANT_PHI
# (from phi system)
# NEEDS TO BE QUANTIFIED
# VL_SYS_w
# self.VL_SYS_w (already calculatd with FoM system)
# WING_SYS_TYPE_WS : WING system wing loading
_x = next( var[q] for var in var_list if all((var[2] == 'WS', var[1] == 'WING_SYS_TYPE')) )
self.WING_SYS_TYPE_WS = fuzzyOps.rangeToMF(_x, 'gauss')
# sys_etaP: system propulsive efficiency
# (from etaP system)
# VL_SYS_DRV_eta_d : VL system drive efficiency
# VL_SYS_DRV_eta_d (already calcualted with FoM system)
# sys_FoM: system Figure of Merit
# (from FoM system)
# VL_SYS_e_d
# self.VL_SYS_e_d (already calcualted with FoM system)
# ENG_SYS_TYPE_SFC
# self.ENG_SYS_TYPE_SFC (already calcualted with phi system)
# NEEDS TO BE QUANTIFIED?
# SYS_TYPE (1-tilt, 2-compound, 3-other)
VL_SYS_TYPE = int(self.option1)
FWD_SYS_TYPE = int(self.option7)
if FWD_SYS_TYPE == 2:
T = 1 #tiling VL
else:
if VL_SYS_TYPE < 4:
T = 2 #compound
if VL_SYS_TYPE == 4 or VL_SYS_TYPE == 5:
T = 3 #other
if VL_SYS_TYPE == 6:
T = 1 #tilting tailsitter
self.SYS_type = fuzzyOps.rangeToMF([T,T], 'gauss')
# SYS_TECH (0 - None, 1 - varRPM, 2 - varDiameter, 3 - stop rotor, 4 - autogyro) (switch 2-3)
VL_SYS_TECH = int(self.option4)
if VL_SYS_TECH == 2: T = 3
elif VL_SYS_TECH == 3: T = 2
else: T = VL_SYS_TECH
self.SYS_tech = fuzzyOps.rangeToMF([T,T], 'gauss')
if self.passthrough == 1: #catch for incompatible options
return None
### Pinst
plt.figure()
for dat in combData_Pin[:]:
if dat[2][0] == dat[2][1]:
r = 0.01 * dat[2][0]
else:
r = dat[2][1] - dat[2][0]
xs = np.arange(dat[2][0] - r, dat[2][1] + r, r / 20)
mean = sum(dat[2]) / 2.0
std = r / 3.0
# h = list(np.random.normal(mean, std, size=200))
# alldata = alldata + h
ys = stats.norm.pdf(xs, mean, std)
ys = [y / max(ys) for y in ys]
# plt.plot(xs, ys, c='b', alpha=0.2)
fx, fy = fuzzyOps.rangeToMF(dat[2], "gauss")
plt.plot(fx, fy, c="b", alpha=0.25)
plt.xlabel("Power Installed (shp)")
plt.xlim([1000, 14000])
plt.ylabel("Membership")
"""
plt.figure()
### GWT
alldata = []
for dat in combData_GWT[:]:
if dat[2][0] == dat[2][1]: r = 0.1*dat[2][0]
else: r = dat[2][1] - dat[2][0]
FWD_DRV_eta_d = fuzzyOps.rangeToMF(alt[3], 'trap')
output = sys.run({'FWD_SYS_eta_p': FWD_SYS_eta_d,
'FWD_DRV_eta_d' : FWD_DRV_eta_d, },
TESTMODE=True)
output = output['sys_etaP']
"""
#build inputs
fig1, ax1 = plt.subplots(figsize=(7, 7))
fig2, ax2 = plt.subplots(nrows=len(ps_inputs) / 2, ncols=2)
for alt in ps_inputs:
#get data
etaP = [max([alt[1][0], alt[2][0]]), min([alt[1][1], alt[2][1]])]
FWD_SYS_eta_p = fuzzyOps.rangeToMF(etaP, 'trap')
FWD_DRV_eta_d = fuzzyOps.rangeToMF(alt[3], 'trap')
output = sys.run(
{
'FWD_SYS_eta_p': FWD_SYS_eta_p,
'FWD_DRV_eta_d': FWD_DRV_eta_d,
},
TESTMODE=False)
output = output['sys_etaP']
#plot ranges from max alpha cuts
outRange = fuzzyOps.alpha_at_val(output[0], output[1])
IND_asses = alt[6]
#calculate overlap
def get_system_error(FCLfile,
valData,
Nmax=None,
inDataMFs='tri',
outDataMFs='tri',
errorType='crispSoS'):
"""
determines the system error as calculated by the validation data
FCLfile - FCL file path/name to build FRBS
valData is validation data in format: [quant_inputs, qual_inputs, outputData]
with each data item {['function', 'var'] : [min,max]} (or [val])
inDataMFs and outDataMFs - type of MFs for inputs and outputs in data
errorType is type of error
nMax is the max number of points from the data to use
"""
q = 0 #0 for quant data, 1 or qual data
allErrors_comb = []
#load fuzzy system
inputs, outputs, rulebase, AND_operator, OR_operator, aggregator, implication, defuzz = build_fuzz_system(
FCLfile)
sys = Fuzzy_System(inputs, outputs, rulebase, AND_operator, OR_operator,
aggregator, implication, defuzz)
allErrors = [] #list of all errors
i = 0 #counter
for data_item in valData: #for each data item
valIns = {}
valOuts = {}
for inKey in data_item[q]: #for each input key build selected MF
[inXs, inYs] = fuzzyOps.rangeToMF(data_item[q][inKey], inDataMFs)
valIns['_'.join(inKey)] = [
inXs, inYs
] #addinput MF to input dict to build inputs for system
if outDataMFs <> 'sing':
[outXs, outYs] = fuzzyOps.rangeToMF(data_item[2], outDataMFs)
valOuts = [outXs, outYs] #data outputs
elif outDataMFs == 'sing': #singleton output MF: [avg]
dAvg = sum(data_item[2]) / len(data_item[2])
valOuts = dAvg #data outputs
valOuts = [outXs, outYs] #data outputs
sysOuts = sys.run(valIns) #get system output
if errorType == 'crispSoS': #capture crisp errors
allErrors.append(dAvg - sysOuts.itervalues().next())
if errorType == 'fuzzy': #capture fuzzy error
allErrors.append(
fuzErrorInt([outXs, outYs],
sysOuts.itervalues().next())**2)
i = i + 1
if Nmax <> None: #check for Nmax exceeded
if i > Nmax: break
if errorType == 'crispSoS': #sum squares of errors and divide by 2N (Simon 2002)
allErrors = [x**2 for x in allErrors]
error = (sum(allErrors) / (len(allErrors)))**0.5
elif errorType == 'fuzzy': #get a fuzzy error measure
error = (sum(allErrors) / (len(allErrors)))**0.5
return error
Pin_sys = DFES(inRanges, outRanges_Pin, 'sigmoid', 250, 30, 50, inputOrder=inOrder)
Pin_sys.read_weights('FCL_files/DFES_RF/BEST/RFdata20Aug_DFES_Pin_30_250_50.nwf')#'FCL_files/DFES_RF/BEST/RFdata20Aug_DFES_Pin_30_250_50.nwf') #read network weight foil
VH_sys = DFES(inRanges, outRanges_VH, 'sigmoid', 250, 40, 50, inputOrder=inOrder)
VH_sys.read_weights('FCL_files/DFES_RF/BEST/RFdata20Aug_DFES_VH_40_250_50.nwf') #read network weight foil
results = [[] for opt in system_options] #save results
## RUN SYSTEMS:
for opts in system_options: #for each option
#Evaluate phi
_VLT_w = getInputs(None, 'VL_SYS_TYPE', 'w', opts)[0] #VL_SYS_TYPE_w :
VLT_w = fuzzyOps.rangeToMF(_VLT_w, 'gauss')
_VLT_ed = getInputs(None, 'VL_SYS_TYPE', 'e_d', opts)[0] #VL_SYS_TYPE_e_d
VLT_ed = fuzzyOps.rangeToMF(_VLT_ed, 'gauss')
_VLP_w = getInputs(None, 'VL_SYS_PROP', 'w', opts)[0] #VL_SYS_PROP_w
VLP_w= fuzzyOps.rangeToMF(_VLP_w, 'gauss')
_VLTe_w = getInputs(None, 'VL_SYS_TECH', 'w', opts)[0] #VL_SYS_TECH_w
VLTe_w = fuzzyOps.rangeToMF(_VLTe_w, 'gauss')
_FSP_phi = getInputs(None, 'FWD_SYS_PROP', 'phi', opts)[0] #FWD_SYS_PROP_phi
FSP_phi = fuzzyOps.rangeToMF(_FSP_phi, 'gauss')
_FSP_etap = getInputs(None, 'FWD_SYS_PROP', 'eta_p', opts)[0]#FWD_SYS_PROP_eta_p : FWD system prop efficiency
FSP_etap = fuzzyOps.rangeToMF(_FSP_etap, 'gauss')
'sigmoid',
250,
40,
50,
inputOrder=inOrder)
VH_sys.read_weights('FCL_files/DFES_RF/BEST/RFdata20Aug_DFES_VH_40_250_50.nwf'
) #read network weight foil
results = [[] for opt in system_options] #save results
## RUN SYSTEMS:
for opts in system_options: #for each option
#Evaluate phi
_VLT_w = getInputs(None, 'VL_SYS_TYPE', 'w', opts)[0] #VL_SYS_TYPE_w :
VLT_w = fuzzyOps.rangeToMF(_VLT_w, 'gauss')
_VLT_ed = getInputs(None, 'VL_SYS_TYPE', 'e_d', opts)[0] #VL_SYS_TYPE_e_d
VLT_ed = fuzzyOps.rangeToMF(_VLT_ed, 'gauss')
_VLP_w = getInputs(None, 'VL_SYS_PROP', 'w', opts)[0] #VL_SYS_PROP_w
VLP_w = fuzzyOps.rangeToMF(_VLP_w, 'gauss')
_VLTe_w = getInputs(None, 'VL_SYS_TECH', 'w', opts)[0] #VL_SYS_TECH_w
VLTe_w = fuzzyOps.rangeToMF(_VLTe_w, 'gauss')
_FSP_phi = getInputs(None, 'FWD_SYS_PROP', 'phi',
opts)[0] #FWD_SYS_PROP_phi
FSP_phi = fuzzyOps.rangeToMF(_FSP_phi, 'gauss')
_FSP_etap = getInputs(
