def resilquant(approach, mdl):
endclasses, mdlhists = fp.run_approach(mdl, approach)
reshists, diffs, summaries = rp.compare_hists(mdlhists)
fmea = rp.make_summfmea(endclasses, approach)
fmea2 = rp.make_phasefmea(endclasses, approach)
util = sum(fmea['expected cost'])
expdegtimes = rp.make_expdegtimeheatmap(reshists, endclasses)
return util, expdegtimes, fmea, fmea2
def prune_app(app, mdl):
endclasses, mdlhists = fp.run_approach(mdl, app)
newscenids = dict.fromkeys(app.scenids.keys())
for modeinphase in app.scenids:
costs = np.array(
[endclasses[scen]['cost'] for scen in app.scenids[modeinphase]])
fullint = np.mean(costs)
errs = abs(fullint - costs)
mins = np.where(errs == errs.min())[0]
newscenids[modeinphase] = [
app.scenids[modeinphase][mins[int(len(mins) / 2)]]
]
return newscenids
})
app_jf3 = SampleApproach(mdl, jointfaults={'faults': 3, 'jointfuncs': True})
#note that faults above level 4 aren't made here because the rate is so low that it rounds to zero
app_jf5 = SampleApproach(mdl, jointfaults={'faults': 5})
app_list = SampleApproach(mdl,
jointfaults={
'faults': [(('ImportEE', 'inf_v'),
('ImportWater', 'no_wat'))],
'pcond':
0.1
})
endclasses, mdlhists = fp.run_approach(mdl, app_jf5)
fmea = rp.make_phasefmea(endclasses, app_jf5).sort_values('expected cost',
ascending=False)
fmea_small = rp.make_summfmea(endclasses, app_jf5).sort_values('expected cost',
ascending=False)
endclasses, mdlhists = fp.run_approach(mdl, app_jf2)
#rp.plot_samplecosts(app_jf2, endclasses, joint=True)
reshists, diffs, summaries = rp.compare_hists(mdlhists)
mdlhist = {
'nominal':
mdlhists['nominal'],
'faulty':
sys.path.append('../')
import numpy as np
import quadpy
import fmdtools.faultprop as fp
import fmdtools.resultproc as rp
from ex_pump import * #required to import entire module
import time
#mdl = Pump(params={'repair', 'ee', 'water', 'delay'})
mdl = Pump(params={'water'}) # should give identical utilities
mdl = Pump()
app_full_plin = SampleApproach(mdl, defaultsamp={'samp': 'fullint'})
endclasses, mdlhists = fp.run_approach(mdl, app_full_plin)
fmea = rp.make_phasefmea(endclasses, app_full_plin)
rp.plot_samplecost(app_full_plin,
endclasses, ('ExportWater', 'block'),
samptype='fullint')
app_full_plin.prune_scenarios(endclasses, samptype='piecewise')
endclasses_plin, mdlhists_plin = fp.run_approach(mdl, app_full_plin)
fmea_plin = rp.make_phasefmea(endclasses_plin, app_full_plin)
rp.plot_samplecost(app_full_plin,
endclasses_plin, ('ExportWater', 'block'),
samptype='pruned piecewise-linear')
app_full_sing = SampleApproach(mdl, defaultsamp={'samp': 'fullint'})
app_full_sing.prune_scenarios(endclasses, samptype='bestpt')
tab = rp.make_samptimetable(app_multipt.sampletimes)
app_short = SampleApproach(mdl,
faults=[('ImportEE', 'inf_v')],
defaultsamp={
'samp': 'evenspacing',
'numpts': 3
})
#newscenids = prune_app(app_full, mdl)
#endclasses, mdlhists = fp.run_approach(mdl, app_full)
#rp.plot_samplecosts(app_full, endclasses)
endclasses, mdlhists = fp.run_approach(mdl, app_quad)
rp.plot_samplecosts(app_quad, endclasses)
endclasses_full, mdlhists = fp.run_approach(mdl, app_full)
rp.plot_samplecosts(app_full, endclasses_full)
#endclasses, mdlhists = fp.run_approach(mdl, app_fullp)
#rp.plot_samplecosts(app_fullp, endclasses)
costovertime = rp.find_costovertime(endclasses_full, app_full)
rp.plot_costovertime(endclasses_full, app_full)
rp.plot_costovertime(endclasses_full, app_full, costtype='cost')
endclasses, mdlhists = fp.run_approach(mdl, app_maxlike)
rp.plot_samplecosts(app_maxlike, endclasses)
sys.path.append('../')
import fmdtools.faultprop as fp
import fmdtools.resultproc as rp
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from quad_mdl import *
import time
#scenlist=fp.listinitfaults(graph, mdl.times)
mdl = Quadrotor()
app = SampleApproach(mdl)
endclasses, mdlhists = fp.run_approach(mdl, app)
simplefmea = rp.make_simplefmea(endclasses)
summfmea = rp.make_summfmea(endclasses, app)
# =============================================================================
#endresults1, resgraph, flowhist3, ghist3=fp.runnominal(mdl, track={'DOFs','Dir1', 'Env1', 'Force_LG'})
#fp.showgraph(resgraph, showfaultlabels=False)
#fp.plotflowhist(flowhist3, 'N/A', time=0)
##
## #Check various scenarios individually
##
endresults, resgraph, mdlhist = fp.run_one_fault(mdl,
'DistEE',
'short',
time=5,
staged=True,