def write_sensitivity(io, h5):
# If more than one variable, display sensitivity.
# Curves have indexed variables, so skip them.
if len(h5['/input/params']) > 1 and ['[' in x for x in h5[uqtype]].count(False):
for v in h5[uqtype]:
if '[' in v:
# curve. skip it.
continue
desc = h5['/output/data/%s' % v].attrs['label']
sens = unpickle(h5['/%s/%s/sensitivity' % (uqtype, v)].value)
hist = io['output.histogram(sens-%s)' % v]
hist['about.label'] = desc
hist['about.uqtype'] = 'Sensitivity'
hist['about.type'] = 'scatter'
hist['xaxis.label'] = 'Parameters'
hist['yaxis.label'] = 'Sensitivity'
pts = ''
for name in sens:
n = name[0]
try:
n = h5['/input/params/%s' % n].attrs['label']
except:
pass
pts += "\"%s\" %s\n" % (n, name[1]['ustar'])
hist['component.xy'] = pts
def write_summary(io, h5):
outstr = StringIO.StringIO()
write_params(h5, outstr)
uqtype = h5.attrs['UQtype']
for v in h5[uqtype]:
if '[' in v:
# It is a curve. Ignore.
continue
desc = h5['%s/%s' % (uqtype, v)].attrs['description']
print("QoI: %s (%s)" % (v, desc), file=outstr)
rs = unpickle(h5['/%s/%s/response' % (uqtype, v)].value)
if type(rs) == puq.response.ResponseFunc:
print("\nv=%s\n" % rs.eqn, file=outstr)
print("SURROGATE MODEL ERROR:{:6.3g}%".format(rs.rmse()[1]), file=outstr)
sens = puq.unpickle(h5['/%s/%s/sensitivity' % (uqtype, v)].value)
max_name_len = max(map(len, [p[0] for p in sens]))
print("\nSENSITIVITY:", file=outstr)
print("Var%s u* dev" % (' '*(max_name_len)), file=outstr)
print('-'*(28+max_name_len), file=outstr)
for item in sens:
pad = ' '*(max_name_len - len(item[0]))
print("{}{} {:10.4g} {:10.4g}".format(pad, item[0],
item[1]['ustar'], item[1]['std']), file=outstr)
print('-'*(28+max_name_len), file=outstr)
print(file=outstr)
iostr = io['output.string(UQ Summary)']
iostr['about.label'] = 'UQ Summary'
iostr['current'] = outstr.getvalue()
outstr.close()
def _calibrate(self, hf):
ovar = get_output_names(hf)[0]
method = hf.attrs['UQtype']
rs = unpickle(hf["/%s/%s/response" % (method, ovar)].value)
# print "Calling calibrate from sweep"
self.psweep.params, self.psweep.kde = calibrate(self.psweep.params, self.caldata, self.err, rs.eval)
def load_internal(name):
debug(name)
try:
name = name[0]
except:
name = ''
h5, fname = open_hdf5_file(name)
if 'private' in h5:
val = h5['private/sweep'].value
else:
# backwards compatibility
val = h5['input/sweep'].value
if type(val) != str:
val = val.decode('UTF-8')
sw = unpickle(val)
sw.fname = os.path.splitext(fname)[0]
h5.close()
sw.psweep._sweep = sw
if hasattr(sw.psweep, 'reinit'):
sw.psweep.reinit()
return sw
def _calibrate(self, hf):
ovar = get_output_names(hf)[0]
method = hf.attrs['UQtype']
rs = unpickle(hf["/%s/%s/response" % (method, ovar)].value)
# print "Calling calibrate from sweep"
self.psweep.params, self.psweep.kde = calibrate(self.psweep.params, self.caldata, self.err, rs.eval)
def load_internal(name):
debug(name)
try:
name = name[0]
except:
name = ''
h5, fname = open_hdf5_file(name)
if 'private' in h5:
val = h5['private/sweep'].value
else:
# backwards compatibility
val = h5['input/sweep'].value
if type(val) != str:
val = val.decode('UTF-8')
sw = unpickle(val)
sw.fname = os.path.splitext(fname)[0]
h5.close()
sw.psweep._sweep = sw
if hasattr(sw.psweep, 'reinit'):
sw.psweep.reinit()
return sw
def write_responses(io, h5):
uqtype = h5.attrs['UQtype']
for v in h5[uqtype]:
print("write_responses", v)
if '[' in v:
# It is a curve. Ignore.
continue
try:
desc = h5['%s/%s' % (uqtype, v)].attrs['description']
except:
desc = ''
try:
label = h5['%s/%s' % (uqtype, v)].attrs['label']
except:
label = ''
rsp = h5['/%s/%s/response' % (uqtype, v)].value
rout = io['output.response(%s)' % v]
rout['value'] = rsp
rout['about.description'] = desc
rout['about.label'] = label
rout['about.uqtype'] = 'Response'
rs = unpickle(rsp)
rout['variables'] = ' '.join([str(p.name) for p in rs.params])
labels = ' '.join([repr(str(p.label)) for p in rs.params])
rout['labels'] = labels.replace("'", '"')
if type(rs) == puq.response.ResponseFunc:
rout['equation'] = rs.eqn
rout['rmse'] = "{:6.3g}".format(rs.rmse()[1])
rout['data'] = rs.data
def get_params(hf):
"""get_params(hf)
Returns a list of arrays of input parameter values.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
"""
return [unpickle(hf['/input/params'][p].value) for p in hf['/input/params']]
def get_params(hf):
"""get_params(hf)
Returns a list of arrays of input parameter values.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
"""
return [unpickle(hf['/input/params'][p].value) for p in hf['/input/params']]
def load_from_hdf5(name):
h5 = h5py.File(name, 'r+')
sw = unpickle(h5['private/sweep'].value)
sw.fname = os.path.splitext(name)[0]
h5.close()
sw.psweep._sweep = sw
if hasattr(sw.psweep, 'reinit'):
sw.psweep.reinit()
return sw
def plot_resp2(dout, resp, name1, name2, rlabel):
print("plot_resp2", name1, name2, rlabel)
numpoints = 50
resp = unpickle(resp)
for p in resp.params:
if p.name == name1:
v1 = p
elif p.name == name2:
v2 = p
x = np.linspace(*v1.pdf.range, num=numpoints)
y = np.linspace(*v2.pdf.range, num=numpoints)
pts = np.array([(b, a) for a, b in product(y, x)])
allpts = np.empty((numpoints**2, len(resp.vars)))
for i, v in enumerate(resp.vars):
if v[0] == v1.name:
allpts[:, i] = pts[:, 0]
elif v[0] == v2.name:
allpts[:, i] = pts[:, 1]
else:
allpts[:, i] = np.mean(v[1])
pts = np.array(resp.evala(allpts))
print('plot_resp2 returns array of', pts.shape)
# mesh
mesh = xml.SubElement(dout, 'mesh', {'id': 'm2d'})
about = xml.SubElement(mesh, 'about')
label = xml.SubElement(about, 'label')
label.text = '2D Mesh'
xml.SubElement(mesh, 'dim').text = '2'
xml.SubElement(mesh, 'hide').text = 'yes'
grid = xml.SubElement(mesh, 'grid')
xaxis = xml.SubElement(grid, 'xaxis')
xml.SubElement(xaxis, 'numpoints').text = str(numpoints)
xml.SubElement(xaxis, 'min').text = str(v1.pdf.range[0])
xml.SubElement(xaxis, 'max').text = str(v1.pdf.range[1])
yaxis = xml.SubElement(grid, 'yaxis')
xml.SubElement(yaxis, 'numpoints').text = str(numpoints)
xml.SubElement(yaxis, 'min').text = str(v2.pdf.range[0])
xml.SubElement(yaxis, 'max').text = str(v2.pdf.range[1])
# field
field = xml.SubElement(dout, 'field', {'id': 'f2d'})
about = xml.SubElement(field, 'about')
xml.SubElement(xml.SubElement(about, 'xaxis'), 'label').text = v1.label
xml.SubElement(xml.SubElement(about, 'yaxis'), 'label').text = v2.label
xml.SubElement(about, 'label').text = rlabel
comp = xml.SubElement(field, 'component')
xml.SubElement(comp, 'mesh').text = 'output.mesh(m2d)'
xml.SubElement(about, 'view').text = 'heightmap'
pts = ' '.join(map(str, pts.ravel('F').tolist()))
xml.SubElement(comp, 'values').text = pts
def get_response(hf, var):
"""get_response(hf, var)
Returns the response function for an output variable.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Output variable name.
"""
psweep = hf.attrs['UQtype']
return unpickle(hf['/%s/%s/response' % (psweep, var)].value)
def get_response(hf, var):
"""get_response(hf, var)
Returns the response function for an output variable.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Output variable name.
"""
psweep = hf.attrs['UQtype']
return unpickle(hf['/%s/%s/response' % (psweep, var)].value)
def test_add_norm_dist():
sw = run('./vel_add.py')
sw.run(fname, overwrite=True)
sw.analyze()
h5 = h5py.File(fname)
tv = unpickle(h5['/smolyak/total_velocity/response'].value)
s1, s2 = unpickle(h5['/smolyak/v1/sensitivity'].value)
assert (s2[0] == 'v2')
assert (s2[1]['ustar'] == 0)
s1, s2 = unpickle(h5['/smolyak/v2/sensitivity'].value)
assert (s2[0] == 'v1')
assert (s2[1]['ustar'] == 0)
pdf = tv.pdf()
assert (allclose(pdf.mean, 110., atol=.03))
dev = math.sqrt(13)
assert (allclose(pdf.dev, dev, atol=.1))
h5.close()
os.remove(fname)
def test_add_norm_dist():
sw = run('./vel_add.py')
sw.run(fname, overwrite=True)
sw.analyze()
h5 = h5py.File(fname)
tv = unpickle(h5['/smolyak/total_velocity/response'].value)
s1, s2 = unpickle(h5['/smolyak/v1/sensitivity'].value)
assert(s2[0] == 'v2')
assert(s2[1]['ustar'] == 0)
s1, s2 = unpickle(h5['/smolyak/v2/sensitivity'].value)
assert(s2[0] == 'v1')
assert(s2[1]['ustar'] == 0)
pdf = tv.pdf()
assert(allclose(pdf.mean, 110., atol=.03))
dev = math.sqrt(13)
assert(allclose(pdf.dev, dev, atol=.1))
h5.close()
os.remove(fname)
def load_internal(name):
debug(name)
try:
name = name[0]
except:
name = ''
h5, fname = open_hdf5_file(name)
# in 201, switched to private/sweep
if 'private' in h5:
sw = unpickle(h5['private/sweep'].value)
else:
sw = unpickle(h5['input/sweep'].value)
sw.fname = os.path.splitext(fname)[0]
h5.close()
sw.psweep._sweep = sw
if hasattr(sw.psweep, 'reinit'):
sw.psweep.reinit()
return sw
def param_description(hf, var):
"""param_description(hf, var)
Returns the description of an input variable. If the
description is empty, returns the variable name.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Input parameter name.
"""
desc = unpickle(hf['/input/params/%s' % var].value).description
if desc:
return desc
return var
def test_add_unif_dist():
sw = run_uniform(progname)
sw.run(fname, overwrite=True)
sw.analyze()
h5 = h5py.File(fname)
tv = unpickle(h5['/smolyak/total_velocity/response'].value)
s1, s2 = unpickle(h5['/smolyak/v1/sensitivity'].value)
assert(s2[0] == 'v2')
assert(s2[1]['ustar'] == 0)
s1, s2 = unpickle(h5['/smolyak/v2/sensitivity'].value)
assert(s2[0] == 'v1')
assert(s2[1]['ustar'] == 0)
pdf = tv.pdf()
assert(allclose(pdf.mean, 110., atol=.2))
# 5.88784057755
dev = math.sqrt((20*20 + 4*4) / 12.0)
assert(allclose(pdf.dev, dev, atol=.2))
h5.close()
os.remove(fname)
def param_description(hf, var):
"""param_description(hf, var)
Returns the description of an input variable. If the
description is empty, returns the variable name.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Input parameter name.
"""
desc = unpickle(hf['/input/params/%s' % var].value).description
if desc:
return desc
return var
def get_params(hf):
"""get_params(hf)
Returns a list of arrays of input parameter values.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
"""
plist = []
for p in hf['/input/params']:
val = hf['/input/params'][p].value
if type(val) != str:
val = val.decode('UTF-8')
plist.append(unpickle(val))
return plist
def get_params(hf):
"""get_params(hf)
Returns a list of arrays of input parameter values.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
"""
plist = []
for p in hf['/input/params']:
val = hf['/input/params'][p].value
if type(val) != str:
val = val.decode('UTF-8')
plist.append(unpickle(val))
return plist
def param_description(hf, var):
"""param_description(hf, var)
Returns the description of an input variable. If the
description is empty, returns the variable name.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Input parameter name.
"""
val = hf['/input/params/%s' % var].value
if type(val) != str:
val = val.decode('UTF-8')
val = unpickle(val)
desc = val.description
if desc:
return desc
return var
def param_description(hf, var):
"""param_description(hf, var)
Returns the description of an input variable. If the
description is empty, returns the variable name.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Input parameter name.
"""
val = hf['/input/params/%s' % var].value
if type(val) != str:
val = val.decode('UTF-8')
val = unpickle(val)
desc = val.description
if desc:
return desc
return var
def _dump_hdf5(self, grp, line, job, mjob):
debug("Dump %s : %s" % (job, line))
global _vcache, _dcache
# old format used single quotes.
if line.startswith("{'"):
line = line.replace("'", '"')
x = unpickle(line)
v = x['value']
n = x['name']
if n not in _vcache:
if isinstance(v, ndarray):
_vcache[n] = np.empty([mjob] + list(v.shape))
else:
_vcache[n] = np.empty((mjob))
_vcache[n].fill(np.nan)
_dcache[n] = x['desc']
_vcache[n][job] = v
def get_sensitivity(hf, var):
"""get_sensitivity(hf, var).
Returns the sensitivity indices for var in a dictionary with keys equal to
parameter names and values consisting of dictionaries with keys equal to sensitivity indices.
The keys in the sub dictionaries will vary depending on the type of sensitivity analysis
(Smolyak or Morris) but will contain at least 'ustar' and 'std'. Morris also contains 'u' and
'ustar_conf95'.
Args:
hf: An open HDF5 filehandle or a string containing the HDF5
filename to use.
var: Output variable name.
"""
psweep = hf.attrs['UQtype']
if not '/%s/%s/sensitivity' % (psweep, var) in hf:
print("Sensitivity indices weren't compute for output '{}'".format(var))
raise ValueError
return unpickle(hf['/%s/%s/sensitivity' % (psweep, var)].value)
def _dump_hdf5(self, grp, line, job, mjob):
debug("Dump %s : %s" % (job, line))
global _vcache, _dcache
# old format used single quotes.
if line.startswith("{'"):
line = line.replace("'", '"')
x = unpickle(line)
v = x['value']
n = x['name']
if not n in _vcache:
if isinstance(v, ndarray):
_vcache[n] = np.empty([mjob] + list(v.shape))
else:
_vcache[n] = np.empty((mjob))
_vcache[n].fill(np.nan)
_dcache[n] = x['desc']
_vcache[n][job] = v
def plot_pdf_acurve(io, h5, acurves, vname, percent):
"""
This function plots the probability curves for parametric
PDFs.
"""
print('plot_pdf_acurve %s %s' % (vname, percent))
label = None
prev_pts = None # last set of points
poly = []
for vindex in sorted(acurves[vname].keys()):
if label is None:
label = h5['/output/data/%s[%d]' % (vname, vindex)].attrs['label']
f1 = unpickle(h5['/output/data/%s[%d]' % (vname, vindex)].attrs['curve'])
bpts = add_pts(f1, percent)
# first data set? Just remember it.
if prev_pts is None:
prev_pts = bpts
continue
pts = np.array((prev_pts, bpts)).ravel().reshape(-1, 2)
hull = ConvexHull(pts, qhull_options='Pp')
p1 = Polygon([hull.points[v] for v in hull.vertices])
poly.append(p1)
prev_pts = bpts
u = unary_union(poly)
curve = io['output.curve(curve_pdf-%s-%s)' % (vname, percent)]
if percent == 0:
curve['about.label'] = "mean"
else:
curve['about.label'] = "middle %s%%" % percent
curve['about.group'] = label
curve['about.uqtype'] = 'Probability'
curve['component.xy'] = np.array(u.exterior.xy)
h5 = h5py.File(sys.argv[1], 'r+')
io = Rappture.PyXml('run_uq.xml')
# curves built from pdfs
pcurves = {}
xvals = {}
acurves = {}
reg1 = re.compile('([ \da-zA-Z_]+)\[([ \d]+)\]')
uqtype = h5.attrs['UQtype']
for v in h5[uqtype]:
print('v=', v)
rsp = h5['/%s/%s/response' % (uqtype, v)].value
rs = unpickle(rsp)
pdf = rs.pdf(fit=False)
odata = h5['/output/data/%s' % v]
# For curves built from pdfs, just put them in a dict for now
if 'x' in odata.attrs:
matches = reg1.findall(v)
vname, vindex = matches[0]
print('CURVE: vname=%s vindex=%s' % (vname, vindex))
vindex = int(vindex)
if vname not in pcurves:
pcurves[vname] = {}
xvals[vname] = {}
xvals[vname][vindex] = odata.attrs['x']
pcurves[vname][vindex] = pdf
elif 'curve' in odata.attrs:
def _calibrate(self, hf):
ovar = get_output_names(hf)[0]
rs = unpickle(hf["/smolyak/%s/response" % ovar].value)
self.psweep.params = calibrate(self.psweep.params, self.caldata,
self.err, rs.eval)
from puq import NormalParameter, UniformParameter, Sweep, RapptureHost, Smolyak
import numpy as np
from puq.jpickle import unpickle
# Redirect stdout and stderr to files for debugging.
sys.stdout = open("uq_debug.out", 'w')
sys.stderr = open("uq_debug.err", 'w')
print(sys.argv)
pid, varlist, uq_type, args = sys.argv[1:]
dfile = "driver%s.xml" % pid
cvsname = "params%s.csv" % pid
hname = "puq_%s.hdf5" % pid
varlist = unpickle(varlist)
print("varlist=", varlist)
v = {}
units = {}
for p in varlist:
name, _units, dist = p
name = str(name)
units[name] = str(_units)
if dist[0] == u'gaussian':
try:
kwargs = dist[3]
except:
kwargs = {}
v[name] = NormalParameter(name,
name,
def plot(sweep, h5, opt, params=[]):
if opt.v:
opt.v = [s.strip() for s in opt.v.split(',')]
if not opt.l:
opt.k = True
method = string.lower(sweep.psweep.__class__.__name__)
if opt.r:
for vname in h5[method]:
if not opt.v or vname in opt.v:
print("Plotting Response Surface for %s" % vname)
desc = h5[method][vname].attrs['description']
rsv = h5[method][vname]['response'].value
rs = unpickle(rsv)
p = rs.plot()
if desc and desc != vname:
plt.title(desc)
else:
plt.title("Response Function for %s" % vname)
plot_customize(opt, p, 'response-%s' % vname)
else:
if opt.psamples:
psamples = get_psamples_from_csv(sweep, h5, opt.samples)
else:
psamples = None
for vname in h5[method]:
if not opt.v or vname in opt.v:
print("plotting PDF for %s" % vname)
desc = h5[method][vname].attrs['description']
if 'samples' in h5[method][vname]:
# response surface already sampled. Just calculate pdf.
data = h5[method][vname]['samples'].value
if opt.k:
p = ExperimentalPDF(data, fit=True).plot()
if opt.l:
p = ExperimentalPDF(data, fit=False).plot()
else:
rsv = h5[method][vname]['response'].value
rs = unpickle(rsv)
data = None
if opt.k:
pdf, data = rs.pdf(fit=True, params=params, psamples=psamples, return_samples=True)
p = pdf.plot()
if opt.l:
if data is not None:
p = ExperimentalPDF(data, fit=False).plot()
else:
pdf, data = rs.pdf(fit=False, params=params, psamples=psamples, return_samples=True)
p = pdf.plot()
h5[method][vname]['samples'] = data
if 'pdf' not in h5[method][vname]:
h5[method][vname]['pdf'] = pickle(pdf)
plt.xlabel(vname)
if desc and desc != vname:
plt.title("PDF for %s" % desc)
else:
plt.title("PDF for %s" % vname)
plot_customize(opt, p, 'pdf-%s' % vname)
def plot_resp1(dout, resp, name, rlabel):
print('plot_resp1', name, rlabel)
numpoints = 100
resp = unpickle(resp)
var = None
for index, p in enumerate(resp.params):
if p.name == name:
var = p
break
if var is None:
print("plot_resp1 error: name %s not recognized" % name)
return
data = resp.data
print('data=', repr(data))
for ind, p in enumerate(resp.params):
if ind == index:
continue
m = p.pdf.mean
means = np.isclose(m, data[:, ind], rtol=1e-6, atol=1e-12)
data = data[means]
print("vars=", resp.vars)
print("data=", repr(data))
curve = xml.SubElement(dout, 'curve', {'id': 'response'})
about = xml.SubElement(curve, 'about')
xml.SubElement(about, 'label').text = rlabel
xml.SubElement(about, 'group').text = rlabel
xaxis = xml.SubElement(curve, 'xaxis')
xml.SubElement(xaxis, 'label').text = var.label
yaxis = xml.SubElement(curve, 'yaxis')
xml.SubElement(yaxis, 'label').text = rlabel
x = np.linspace(*var.pdf.range, num=numpoints)
allpts = np.empty((numpoints, len(resp.params)))
for i, v in enumerate(resp.params):
if v.name == var.name:
allpts[:, i] = x
else:
allpts[:, i] = np.mean(v.pdf.mean)
pts = resp.evala(allpts)
xy = '\n'.join([' '.join(map(repr, a)) for a in zip(x, pts)])
comp = xml.SubElement(curve, 'component')
xml.SubElement(comp, 'xy').text = xy
# scatter plot sampled data on response surface
curve = xml.SubElement(dout, 'curve', {'id': 'scatter'})
about = xml.SubElement(curve, 'about')
xml.SubElement(about, 'label').text = 'Data Points'
xml.SubElement(about, 'group').text = rlabel
xml.SubElement(about, 'type').text = 'scatter'
comp = xml.SubElement(curve, 'component')
xy = '\n'.join([' '.join(map(repr, a)) for a in zip(data[:, index], data[:, -1])])
xml.SubElement(comp, 'xy').text = xy
def plot(sweep, h5, opt, params=[]):
if opt.v:
opt.v = [s.strip() for s in opt.v.split(',')]
if not opt.l:
opt.k = True
method = string.lower(sweep.psweep.__class__.__name__)
if opt.r:
for vname in h5[method]:
if not opt.v or vname in opt.v:
print "Plotting Response Surface for %s" % vname
desc = h5[method][vname].attrs['description']
rsv = h5[method][vname]['response'].value
rs = unpickle(rsv)
p = rs.plot()
if desc and desc != vname:
plt.title(desc)
else:
plt.title("Response Function for %s" % vname)
plot_customize(opt, p, 'response-%s' % vname)
else:
if opt.psamples:
psamples = get_psamples_from_csv(sweep, h5, opt.samples)
else:
psamples = None
for vname in h5[method]:
if not opt.v or vname in opt.v:
print "plotting PDF for %s" % vname
desc = h5[method][vname].attrs['description']
if 'samples' in h5[method][vname]:
# response surface already sampled. Just calculate pdf.
data = h5[method][vname]['samples'].value
if opt.k:
p = ExperimentalPDF(data, fit=True).plot()
if opt.l:
p = ExperimentalPDF(data, fit=False).plot()
else:
rsv = h5[method][vname]['response'].value
rs = unpickle(rsv)
data = None
if opt.k:
pdf, data = rs.pdf(fit=True,
params=params,
psamples=psamples,
return_samples=True)
p = pdf.plot()
if opt.l:
if data is not None:
p = ExperimentalPDF(data, fit=False).plot()
else:
pdf, data = rs.pdf(fit=False,
params=params,
psamples=psamples,
return_samples=True)
p = pdf.plot()
h5[method][vname]['samples'] = data
if not 'pdf' in h5[method][vname]:
h5[method][vname]['pdf'] = pickle(pdf)
plt.xlabel(vname)
if desc and desc != vname:
plt.title("PDF for %s" % desc)
else:
plt.title("PDF for %s" % vname)
plot_customize(opt, p, 'pdf-%s' % vname)
