for opts in newsys_options: #for each option
sysOut_phi, sysOut_FoM, sysOut_LD, sysOut_etaP, sysOut_GWT, sysOut_Pin, sysOut_VH = runFramework(
opts)
results_new[newsys_options.index(opts)].append(sysOut_phi)
results_new[newsys_options.index(opts)].append(sysOut_FoM)
results_new[newsys_options.index(opts)].append(sysOut_LD)
results_new[newsys_options.index(opts)].append(sysOut_etaP)
results_new[newsys_options.index(opts)].append(sysOut_GWT)
results_new[newsys_options.index(opts)].append(sysOut_Pin)
results_new[newsys_options.index(opts)].append(sysOut_VH)
for i in range(len(results)):
print system_names[i]
print "Objective FPoS Centroid"
fpos1 = fuzzyOps.fuzzyPOS(results[i][0][0], results[i][0][1],
goalVals['sys_phi'])
cent = fuzz.defuzz(np.array(results[i][0][0]), np.array(results[i][0][1]),
'centroid')
print "Phi: %.3f %.3f" % (fpos1, cent)
fpos2 = fuzzyOps.fuzzyPOS(results[i][1][0],
results[i][1][1],
goalVals['sys_FoM'],
plot=False)
cent = fuzz.defuzz(np.array(results[i][1][0]), np.array(results[i][1][1]),
'centroid')
print "FoM: %.3f %.3f" % (fpos2, cent)
fpos3 = fuzzyOps.fuzzyPOS(results[i][2][0], results[i][2][1],
goalVals['sys_LoD'])
cent = fuzz.defuzz(np.array(results[i][2][0]), np.array(results[i][2][1]),
'centroid')
print "L/D: %.3f %.3f" % (fpos3, cent)
for opts in newsys_options: #for each option
sysOut_phi, sysOut_FoM, sysOut_LD, sysOut_etaP, sysOut_GWT, sysOut_Pin, sysOut_VH = runFramework(opts)
results_new[newsys_options.index(opts)].append(sysOut_phi)
results_new[newsys_options.index(opts)].append(sysOut_FoM)
results_new[newsys_options.index(opts)].append(sysOut_LD)
results_new[newsys_options.index(opts)].append(sysOut_etaP)
results_new[newsys_options.index(opts)].append(sysOut_GWT)
results_new[newsys_options.index(opts)].append(sysOut_Pin)
results_new[newsys_options.index(opts)].append(sysOut_VH)
for i in range(len(results)):
print system_names[i]
print "Objective FPoS Centroid"
fpos1 = fuzzyOps.fuzzyPOS(results[i][0][0],results[i][0][1], goalVals['sys_phi'])
cent = fuzz.defuzz(np.array(results[i][0][0]),np.array(results[i][0][1]), 'centroid')
print "Phi: %.3f %.3f" % (fpos1, cent)
fpos2 = fuzzyOps.fuzzyPOS(results[i][1][0],results[i][1][1], goalVals['sys_FoM'], plot=False)
cent = fuzz.defuzz(np.array(results[i][1][0]),np.array(results[i][1][1]), 'centroid')
print "FoM: %.3f %.3f" % (fpos2, cent)
fpos3 = fuzzyOps.fuzzyPOS(results[i][2][0],results[i][2][1], goalVals['sys_LoD'])
cent = fuzz.defuzz(np.array(results[i][2][0]),np.array(results[i][2][1]), 'centroid')
print "L/D: %.3f %.3f" % (fpos3, cent)
fpos4 = fuzzyOps.fuzzyPOS(results[i][3][0],results[i][3][1], goalVals['sys_etaP'])
cent = fuzz.defuzz(np.array(results[i][3][0]),np.array(results[i][3][1]), 'centroid')
print "etaP: %.3f %.3f" % (fpos4, cent)
fpos5 = fuzzyOps.fuzzyPOS(results[i][5][0],results[i][5][1], goalVals['sys_Pin'], direction='min')
cent = fuzz.defuzz(np.array(results[i][5][0]),np.array(results[i][5][1]), 'centroid')
print "Pin: %.3f %.3f" % (fpos5, cent)
print "TOTAL: %.3f" % min(fpos1,fpos2,fpos3,fpos4,fpos5)
def execute(self):
"""
Translate fuzzy inputs to crisp values to optimize system.
"""
inputs = [self.fuzzSys_in_1, self.fuzzSys_in_2, self.fuzzSys_in_3,
self.fuzzSys_in_4, self.fuzzSys_in_5, self.fuzzSys_in_6,
self.fuzzSys_in_7, self.fuzzSys_in_8, self.fuzzSys_in_9]
outs = [[self.response_1][0], [self.response_2][0], self.response_3,
self.response_4, self.response_5, self.response_6,
self.response_7, self.response_8, self.response_9]
outs_r = [self.response_1_r, self.response_2_r, self.response_3_r,
self.response_4_r, self.response_5_r, self.response_6_r,
self.response_7_r, self.response_8_r, self.response_9_r]
if self.passthrough == 1:
if self.printResults == 1: print "Incompatible combo found..."
self.response_1 = 0.0 #phi
self.response_1_r = 0.0
self.response_1_POS = -1.0
self.response_2 = 0.0 #FoM
self.response_2_r = 0.0
self.response_2_POS = -1.0
self.response_3 = 0.0 #LoD
self.response_3_r = 0.0
self.response_3_POS = -1.0
self.response_4 = 0.0 #etaP
self.response_4_r = 0.0
self.response_4_POS = -1.0
self.response_5 = 0.0 #GWT
self.response_5_r = 0.0
self.response_5_POS = -1.0
self.response_6 = -99999.0 #P
self.response_6_r = 0.0
self.response_6_POS = 0.0
self.response_7 = 0.0 #VH
self.response_7_r = 0.0
self.response_7_POS = -1.0
return None
else:
#get alpha cuts for crisp responses and ranges
for i in range(len(inputs)):
if inputs[i].mf_key <> '':
if len(inputs[i].mf_dict[inputs[i].mf_key]) == 1: #crisp value
self.ranges_out[inputs[i].mf_key] = [inputs[i].mf_dict[inputs[i].mf_key][0], inputs[i].mf_dict[inputs[i].mf_key][0]]
elif len(inputs[i].mf_dict[inputs[i].mf_key]) == 2: #fuzzy function
self.ranges_out[inputs[i].mf_key] = fuzzyOps.alpha_cut(self.alpha_val, inputs[i].mf_dict[inputs[i].mf_key])
#capture results for crisp measures
if self.ranges_out[inputs[i].mf_key] <> None: y = self.ranges_out[inputs[i].mf_key]
else: y = [0.0, 0.0]
if inputs[i].mf_key == 'sys_phi':
self.response_1 = fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_1 = self.response_1 * math.exp(-self.incompatCount)**0.5
self.response_1_r = max(y) - min(y)
self.response_1_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_phi'])
if inputs[i].mf_key == 'sys_FoM':
self.response_2 = fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_2 = self.response_2 * math.exp(-self.incompatCount)**0.5
self.response_2_r = max(y) - min(y)
#if self.response_2 < 0.6:
# self.response_2_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_FoM'], direction='max', plot=True)
self.response_2_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_FoM'])
if inputs[i].mf_key == 'sys_LoD':
self.response_3 = fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_2 = self.response_3 * math.exp(-self.incompatCount)**0.5
self.response_3_r = max(y) - min(y)
self.response_3_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_LoD'])
if inputs[i].mf_key == 'sys_etaP':
self.response_4 = fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_4 = self.response_4 * math.exp(-self.incompatCount)**0.5
self.response_4_r = max(y) - min(y)
self.response_4_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_etaP'])
if inputs[i].mf_key == 'sys_GWT': #invert GWT to maximize all
self.response_5 = fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_5 = self.response_5 * math.exp(-self.incompatCount)**0.5
self.response_5_r = max(y) - min(y)
self.response_5_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_GWT'], direction='min')
if inputs[i].mf_key == 'sys_P': #invert GWT to maximize all
self.response_6 = 0.0-fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_6 = self.response_6 * math.exp(-self.incompatCount)**0.5
self.response_6_r = max(y) - min(y)
self.response_6_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_Pin'], direction='min')
if inputs[i].mf_key == 'sys_VH': #invert GWT to maximize all
self.response_7 = fuzz.defuzz(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]),'centroid')
self.response_7 = self.response_7 * math.exp(-self.incompatCount)**0.5
self.response_7_r = max(y) - min(y)
self.response_7_POS = fuzzyOps.fuzzyPOS(inputs[i].mf_dict[inputs[i].mf_key][0],np.array(inputs[i].mf_dict[inputs[i].mf_key][1]), self.goalVals['sys_VH'])
self.fuzzyPOS = self.response_1_POS*self.response_2_POS*self.response_3_POS*self.response_4_POS*self.response_6_POS
if self.printResults == 1: #print results
print "Alternative:", self.passthrough, ":",
print "PHI: %.1f, (%.3f)" % (self.response_1, self.response_1_POS),
print " FoM: %.3f, (%.3f)" % (self.response_2, self.response_2_POS),
print " L/D: %.1f, (%.3f)" % (self.response_3, self.response_3_POS),
print " etaP: %.3f, (%.3f)" % (self.response_4, self.response_4_POS),
print " GWT: %.0f, (%.3f)" % (self.response_5, self.response_5_POS),
print " Pinst: %.0f, (%.3f)" % (self.response_6, self.response_6_POS),
print " VH: %.0f, (%.3f)" % (self.response_7, self.response_7_POS),
print " FPOS: %.3f" % self.fuzzyPOS
#plotting for testing
if self.PLOTMODE == 1: #plot results
plt.figure()
i=1
for r in inputs:
plt.subplot(3,2,i)
if r.mf_key <> '':
if len(r.mf_dict[r.mf_key]) == 1: #crisp value
pass#self.ranges_out[r.mf_key] = [r.mf_dict[r.mf_key][0], r.mf_dict[r.mf_key][1]]
elif len(r.mf_dict[r.mf_key]) == 2: #fuzzy function
plt.plot(r.mf_dict[r.mf_key][0],r.mf_dict[r.mf_key][1])
i = i + 1
plt.show()