def mc_test(fname=None):
import sampler
global xmin, xmax, shape, scale, gshape, gscale, kappa, loc, dim, kappa0
global fsamp
global fscan
global fsamplines
global fscanlines
global check_prob
check_prob = True
shape = 2.120
scale = 9.767
gshape = 10
gscale = .2
kappa = 1
kappa0 = 1
loc = -0.1
dim = 1
xmin = np.array([0])
xmax = np.array([50])
allns = [[20]]
# dim = 2
# xmin = np.array([0,-pi+0.001])
# xmax = np.array([30,pi-0.001])
# allns = [[5,9],[11,9],[21,9] , [100,100] ]
dim = 4
xmin = np.array([1, -pi, 0, 0])
xmax = np.array([30, pi, 6, 6])
# allns = [ [2,2,3,3], [3,3,3,3], [4,4,3,3], [4,4,4,4], [8,8,6,6] ,[10,10,8,8] ]
# allns = [ [4,4,3,3], [8,8,6,6] , [16,16,12,12] ]
# allns = [[2,2,3,3] ]
# allns = [ [3,3,3,3], [4,4,4,4] ]
allns = [[16, 16, 16, 16]]
# allns = [[6,6,4,4], [6,6,6,6]]
sctx = sampler.Context(dim)
if (fname != None):
fsamplines = file(fname).readlines()
ll = len(fsamplines) - 1
allns = [[ll]] ## hopefully just tricks code below
for ns in allns:
if (fname == None):
fname = "mc_samples"
for d in ns:
fname += "%d" % d
fname += ".out"
fsamplines = file(fname).readlines()
fsamplines = fsamplines[1:]
fsamplines = [[float(x) for x in ln.split()] for ln in fsamplines]
lsum2 = int_mc4_cumulative(sctx, ns, 10)
print ns, lsum2
def test_convergence(fname, use_prob, field_idx, minsamp, maxsamp, incr):
sctx = sampler.Context()
nsamp = minsamp
foutname = "%s.conv" % (fname)
fout = file(foutname, "w")
while (nsamp < maxsamp):
onedat = final_load_calc(sctx, fname, use_prob, field_idx, nsamp)
fout.write("%d %e %e\n" % (onedat[0], onedat[1], onedat[2]))
nsamp += incr
fout.close()
def rundlcs():
"""
run the whole process, including startup and shutdown
to do:
parse input
create load cases
create app assembly
create dispatcher
send cases and app to dispatcher
run cases
collect and save output
"""
options, arg = get_options()
ctrl = parse_input(options.main_input, options)
# ctrl will be just the input, but broken up into separate categories, e.g.
# ctrl.cases, ctrl.app, ctrl.dispatch, ...
if (options.cluster_allocator):
cluster = ClusterAllocator()
RAM.insert_allocator(0, cluster)
### using "factory" functions to create specific subclasses (e.g. distinguish between FAST and HAWC2)
# Then we use these to create the cases...
cases = create_load_cases(ctrl.cases, options)
# and a turbine
turbine = create_turbine(ctrl.turbine)
# and the appropriate wind code wrapper...
aerocode = create_aerocode_wrapper(ctrl.aerocode, options)
# and the appropriate dispatcher...
dispatcher = create_dlc_dispatcher(ctrl.dispatcher)
### After this point everything should be generic, all appropriate subclass object created
dispatcher.presetup_workflow(
aerocode, turbine,
cases) # just makes sure parts are there when configure() is called
dispatcher.configure()
# Now tell the dispatcher to (setup and ) run the cases using the aerocode on the turbine.
# calling configure() is done inside run().
if (not options.norun):
dispatcher.run()
# TODO: more complexity will be needed for difference between "run now" and "run later" cases.
dispatcher.collect_output(ctrl.output)
sctx = sampler.Context()
field_idx = 20 # = RootMyc1Std
final_load_calc(sctx, "dlcproto.out", not dispatcher.raw_cases, field_idx)
from openruniec import final_load_calc as flc import sampler sctx = sampler.Context() [cnt, lsum, psum] = flc(sctx, "dlcproto.out", True, 20)
def collect_output(self, output_params):
print "RUNS ARE DONE:"
sctx = sampler.Context()
if (self.run_dakota):
print "DAKOTA done, see dakota_tabular.dat"
else:
fields = [
'RootMxc1', 'RootMyc1', 'LSSGagMya', 'LSSGagMza', 'YawBrMxp',
'YawBrMyp', 'TwrBsMxt', 'TwrBsMyt', 'Fair1Ten', 'Fair2Ten',
'Fair3Ten', 'Anch1Ten', 'Anch2Ten', 'Anch3Ten'
]
print "collecting output from copied-back files (not from case recorder), see %s" % output_params[
'main_output_file']
fout = file(output_params['main_output_file'], "w")
# fout.write( "#Vs Hs Tp WaveDir, TwrBsMxt \n")
fout.write("#Vs Hs Tp WaveDir Prob")
for f in fields:
fout.write(" %s " % f)
for f in fields:
fout.write(" %sStd " % f)
fout.write("\n")
fail_count = [0 for i in 2 * range(len(fields))]
for fullcase in self.runcases:
case = fullcase._inputs['runner.input']
results_dir = os.path.join(self.aerocode.basedir, case.name)
myfast = self.aerocode.runfast.rawfast
# fout.write( "%.2f %.2f %.2f %.2f %.2f\n" % (case.ws, case.fst_params['WaveHs'], case.fst_params['WaveTp'],case.fst_params['WaveDir'], myfast.getMaxOutputValue('TwrBsMxt', directory=results_dir))) ### this may not exist, just an example
x = [
case.ws, case.fst_params['WaveDir'],
case.fst_params['WaveHs'], case.fst_params['WaveTp']
]
x[1] *= pi / 180.0 ## sampler works in radians, and different order than we print results (because PG is an idiot!)
prob = sctx.calc_prob(x)
print "got ", x, " prob= ", prob
vals = myfast.getMaxOutputValues(fields, directory=results_dir)
stdvals = myfast.getMaxOutputValueStdDevs(
fields, directory=results_dir)
# vals = []
# stdvals = []
for i in range(len(fields)):
# vstr = fields[i]
# val = myfast.getMaxOutputValue(vstr, directory=results_dir)
# stdval = myfast.getMaxOutputValueStdDev(vstr, directory=results_dir)
val = vals[i]
stdval = stdvals[i]
if (val != None):
vals.append(val)
else:
fail_count[i] += 1
vals[i] = -99999.9999
if (stdval != None):
stdvals.append(stdval)
else:
fail_count[len(fields) + i] += 1
stdvals[i] = -99999.9999
fout.write("%.16e %.16e %.16e %.16e %.16e" %
(case.ws, case.fst_params['WaveHs'],
case.fst_params['WaveTp'],
case.fst_params['WaveDir'], prob))
for i in range(len(fields)):
v = vals[i]
fout.write(" %.6e " % v)
for i in range(len(fields)):
v = stdvals[i]
fout.write(" %.6e " % v)
fout.write("\n")
### this may not exist, just an example
# fout.write( "%.2f %.2f\n" % (case.ws, myfast.getMaxOutputValue('TwrBsMxt', directory=results_dir))) ### this may not exist, just an example
print "ran %d cases, failcounts:" % len(self.runcases)
print fields, fields
print fail_count
def run_fast():
import sampler
global xmin, xmax, shape, scale, gshape, gscale, kappa, loc, dim, kappa0
global fsamp
global fscan
global fsamplines
global fscanlines
shape = 2.120
scale = 9.767
gshape = 10
gscale = .2
kappa = 1
kappa0 = 1
loc = -0.1
dim = 1
xmin = np.array([0])
xmax = np.array([50])
allns = [[20]]
# dim = 2
# xmin = np.array([0,-pi+0.001])
# xmax = np.array([30,pi-0.001])
# allns = [[5,9],[11,9],[21,9] , [100,100] ]
dim = 4
xmin = np.array([1, -pi, 0, 0])
xmax = np.array([30, pi, 6, 6])
# allns = [ [2,2,3,3], [3,3,3,3], [4,4,3,3], [4,4,4,4], [8,8,6,6] ,[10,10,8,8] ]
# allns = [ [4,4,3,3], [8,8,6,6] , [16,16,12,12] ]
# ns = [16,16,16,16]
ns = [10, 10, 8, 8]
# allns = [ [3,3,3,3], [4,4,4,4] ]
# allns = [ [10,10,8,8] ]
# allns = [[6,6,4,4], [6,6,6,6]]
sctx = sampler.Context(dim)
## this code will go off a single ns that we can subdivide later, ie do one big run, then mine it.
# these params generate big MC we can also consider sequentially
# setup the samples for both MC and brute force
base1 = "mc_samples"
tag = ""
for d in ns:
tag += "%d" % d
fname1 = base1 + tag + ".txt"
fsamp = file(fname1, "w")
fsamp.write("Vhub WaveDir Hs Tp\n")
base2 = "int_samples"
fname2 = base2 + tag + ".txt"
fscan = file(fname2, "w")
fscan.write("Vhub WaveDir Hs Tp\n")
# will compute the test integral, but mainly write the samples
lsum1 = int_det4(sctx, ns, True, False)
lsum2 = int_mc4(sctx, ns, True, False)
fsamp.close()
fscan.close()
print "for TEST integral:", ns, lsum1, lsum2
# now actually do the runs, by calling openruniec.py
os.system("python openruniec.py -i %s -p" % fname1)
os.system("cp dlcproto.out %s.out" % (base1 + tag))
os.system("python openruniec.py -i %s -p" % fname2)
os.system("cp dlcproto.out %s.out" % (base2 + tag))
# now compute the integrals
fname1 = base1 + tag + ".out"
fsamplines = file(fname1).readlines()
fsamplines = fsamplines[1:]
fsamplines = [[float(x) for x in ln.split()] for ln in fsamplines]
fname2 = base2 + tag + ".out"
fscanlines = file(fname2).readlines()
fscanlines = fscanlines[1:]
fscanlines = [[float(x) for x in ln.split()] for ln in fscanlines]
# will compute the real integral, by reading the samples
lsum1 = int_det4(sctx, ns, False, True)
lsum2 = int_mc4(sctx, ns, False, True)
print "for REAL integral:", ns, lsum1, lsum2
def int_test(fnamein=None, head=None, tail=None):
import sampler
global xmin, xmax, shape, scale, gshape, gscale, kappa, loc, dim, kappa0
global fsamp
global fscan
global fsamplines
global fscanlines
shape = 2.120
scale = 9.767
gshape = 10
gscale = .2
kappa = 1
kappa0 = 1
loc = -0.1
dim = 1
xmin = np.array([0])
xmax = np.array([50])
allns = [[20]]
# dim = 2
# xmin = np.array([0,-pi+0.001])
# xmax = np.array([30,pi-0.001])
# allns = [[5,9],[11,9],[21,9] , [100,100] ]
dim = 4
xmin = np.array([1, -pi, 0, 0])
xmax = np.array([30, pi, 6, 6])
# allns = [ [2,2,3,3], [3,3,3,3], [4,4,3,3], [4,4,4,4], [8,8,6,6] ,[10,10,8,8] ]
# allns = [ [4,4,3,3], [8,8,6,6] , [16,16,12,12] ]
# allns = [[2,2,3,3] ]
# allns = [ [3,3,3,3], [4,4,4,4] ]
allns = [[16, 16, 16, 16]]
# allns = [[6,6,4,4], [6,6,6,6]]
sctx = sampler.Context(dim)
allns = [[4, 4, 4, 4], [6, 6, 4, 4], [6, 6, 6, 6], [8, 8, 6, 6],
[8, 8, 8, 8], [10, 10, 8, 8], [16, 16, 12, 12], [16, 16, 16, 16]]
#int_samples101088.out int_samples2222.out int_samples3333.out int_samples4444.out int_samples6666.out int_samples8888.out
#int_samples16161616.out int_samples2233.out int_samples4433.out int_samples6644.out int_samples8866.out
allns = [[4, 4, 4, 4], [6, 6, 4, 4], [6, 6, 6, 6], [8, 8, 6, 6],
[8, 8, 8, 8], [10, 10, 8, 8], [16, 16, 16, 16]]
allns = [[20, 20, 20, 20]]
for ns in allns:
if (fnamein != None):
fname = fnamein
else:
if (head == None):
fname = "int_samples"
else:
fname = head
for d in ns:
fname += "%d" % d
if (tail == None):
fname += ".out"
else:
fname += tail
# print "reading from ", fname, " ns = ", ns
fscanlines = file(fname).readlines()
fscanlines = fscanlines[1:]
fscanlines = [[float(x) for x in ln.split()] for ln in fscanlines]
res = int_det4_cumulative(sctx, ns, 1)
print ns, prod(ns), res
def real_test(write=False, read=False):
import sampler
global xmin, xmax, shape, scale, gshape, gscale, kappa, loc, dim, kappa0
global fsamp
global fscan
global fsamplines
global fscanlines
shape = 2.120
scale = 9.767
gshape = 10
gscale = .2
kappa = 1
kappa0 = 1
loc = -0.1
dim = 1
xmin = np.array([0])
xmax = np.array([50])
allns = [[20]]
# dim = 2
# xmin = np.array([0,-pi+0.001])
# xmax = np.array([30,pi-0.001])
# allns = [[5,9],[11,9],[21,9] , [100,100] ]
dim = 4
xmin = np.array([1, -pi, 0, 0])
xmax = np.array([30, pi, 6, 6])
# allns = [ [2,2,2,2], [2,2,3,3], [3,3,3,3], [4,4,3,3], [4,4,4,4], [6,6,4,4],[6,6,6,6],[8,8,6,6],
# [8,8,8,8],[10,10,8,8],[10,10,10,10],[12,12,12,12],[16,16,12,12],[16,16,16,16]]
# allns = [ [4,4,3,3], [8,8,6,6] , [16,16,12,12] ]
# allns = [[2,2,3,3] ]
# allns = [ [3,3,3,3], [4,4,4,4] ]
# allns = [ [10,10,8,8] ]
allns = [[20, 20, 20, 20]]
sctx = sampler.Context(dim)
for ns in allns:
if (write):
fname = "mc_samples"
for d in ns:
fname += "%d" % d
fname += ".txt"
fsamp = file(fname, "w")
fsamp.write("Vhub WaveDir Hs Tp\n")
fname = "int_samples"
for d in ns:
fname += "%d" % d
fname += ".txt"
fscan = file(fname, "w")
fscan.write("Vhub WaveDir Hs Tp\n")
if (read):
fname = "mc_samples"
for d in ns:
fname += "%d" % d
fname += ".out"
fsamplines = file(fname).readlines()
fsamplines = fsamplines[1:]
fsamplines = [[float(x) for x in ln.split()] for ln in fsamplines]
fname = "int_samples"
for d in ns:
fname += "%d" % d
fname += ".out"
fscanlines = file(fname).readlines()
fscanlines = fscanlines[1:]
fscanlines = [[float(x) for x in ln.split()] for ln in fscanlines]
lsum1 = int_det4(sctx, ns, write, read)
lsum2 = int_mc4(sctx, ns, write, read)
print ns, lsum1, lsum2
# print ns, lsum2
if (write):
fsamp.close()
fscan.close()