def experiment(modelfile):
setup = GareflModel(modelfile)
M = [GareflExperiment(setup, k) for k in range(setup.num_models)]
names = setup.par_names()
low, high = setup.par_bounds()
value = setup.par_values()
pars = [
Parameter(v, name=s, bounds=(L, H))
for v, s, L, H in zip(value, names, low, high)
]
M[0]._pars = pars
return M
def __init__(self, A=1, xc=0, yc=0, g1=1, g2=1, theta=0, name=""):
self.A = Parameter(A, name=name + "A")
self.xc = Parameter(xc, name=name + "xc")
self.yc = Parameter(yc, name=name + "yc")
self.g1 = Parameter(g1, name=name + "g1")
self.g2 = Parameter(g2, name=name + "g2")
self.theta = Parameter(theta, name=name + "theta")
def __init__(self, A=1, xc=0, yc=0, s1=1, s2=1, theta=0, name=""):
self.A = Parameter(A, name=name + "A")
self.xc = Parameter(xc, name=name + "xc")
self.yc = Parameter(yc, name=name + "yc")
self.s1 = Parameter(s1, name=name + "s1")
self.s2 = Parameter(s2, name=name + "s2")
self.theta = Parameter(theta, name=name + "theta")
def experiment(modelfile, probes=None):
setup = GareflModel(modelfile)
if probes:
if len(probes) != setup.num_models:
raise ValueError("Number of datasets must match number of models")
M = [
GareflExperiment(setup, k, probe=probes[k])
for k in range(setup.num_models)
]
else:
M = [GareflExperiment(setup, k) for k in range(setup.num_models)]
names = setup.par_names()
low, high = setup.par_bounds()
value = setup.par_values()
pars = [
Parameter(v, name=s, bounds=(L, H))
for v, s, L, H in zip(value, names, low, high)
]
M[0]._pars = pars
return M
def __init__(self, C=0, name=""):
self.C = Parameter(C, name=name + "background")
