def __init__(self, params, finite_bounds=False, parent=None):
super(LimitsModel, self).__init__(parent)
self.params = params
self.finite_bounds = finite_bounds
self.varys = curvefitter.varys(self.params)
self.fitted_params = np.where(self.varys)[0]
self.names = curvefitter.names(self.params)
def __init__(self, params, finite_bounds=False, parent=None):
super(LimitsModel, self).__init__(parent)
self.params = params
self.finite_bounds = finite_bounds
self.varys = curvefitter.varys(self.params)
self.fitted_params = np.where(self.varys)[0]
self.names = curvefitter.names(self.params)
def add_layer(self, insertpoint):
params = self.params
values = curvefitter.values(params)
if not reflect.is_proper_abeles_input(values):
raise ValueError('The size of the parameter array passed'
' to reflectivity should be 4 * coefs[0] + 8')
oldlayers = int(values[0])
self.params['nlayers'].value = oldlayers + 1
self.beginInsertRows(QtCore.QModelIndex(), insertpoint + 1,
insertpoint + 1)
values = curvefitter.values(self.params)
varys = curvefitter.varys(self.params)
bounds = curvefitter.bounds(self.params)
#do the insertion
startP = 4 * insertpoint + 8
values = np.insert(values, startP, [0] * 4)
dummy = [varys.insert(startP, i) for i
in [True] * 4]
dummy = [bounds.insert(startP, i) for i
in [(None, None)] * 4]
bounds = np.array(bounds)
names = ReflectivityFitFunction.parameter_names(nparams=values.size)
#clear the parameters
map(self.params.pop, self.params.keys())
# reinsert parameters
parlist = zip(names,
values,
varys,
bounds.T[0],
bounds.T[1],
[None] * values.size)
for para in parlist:
self.params.add(*para)
self.endInsertRows()
def remove_layer(self, which_layer):
params = self.params
values = curvefitter.values(params)
if int(values[0]) == 0:
return False
if not reflect.is_proper_abeles_input(values):
raise ValueError('The size of the parameter array passed'
' to reflectivity should be 4 * coefs[0] + 8')
oldlayers = int(values[0])
self.beginRemoveRows(QtCore.QModelIndex(), which_layer, which_layer)
self.params['nlayers'].value = oldlayers - 1
startP = 4 * (which_layer - 1) + 8
#get rid of parameters we don't need anymore
names_lost = curvefitter.names(self.params)[startP: startP + 4]
map(self.params.pop, names_lost)
# but now we need to rejig parameters names
# the only way to do this is to pop them all and readd
values = curvefitter.values(self.params)
varys = curvefitter.varys(self.params)
bounds = np.array(curvefitter.bounds(self.params))
names = ReflectivityFitFunction.parameter_names(values.size)
map(self.params.pop, self.params.keys())
parlist = zip(names,
values,
varys,
bounds.T[0],
bounds.T[1],
[None] * values.size)
for para in parlist:
self.params.add(*para)
self.endRemoveRows()
