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 data(self, index, role=QtCore.Qt.DisplayRole):
if not index.isValid():
return False
row = index.row()
col = index.column()
names = curvefitter.names(self.params)
if row:
name = names[row - 1]
if role == QtCore.Qt.DisplayRole:
if col == 0:
if row == 0:
return str(len(self.params))
else:
return name
elif col == 1 and row > 0:
return str(self.params[name].value)
elif col == 2 and row > 0:
return str(self.params[name].min)
elif col == 3 and row > 0:
return str(self.params[name].max)
elif col == 4 and row > 0:
return str(self.params[name].expr)
if role == QtCore.Qt.CheckStateRole:
if row > 0 and col == 1:
if self.params[name].vary:
return QtCore.Qt.Unchecked
else:
return QtCore.Qt.Checked
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 rowcol_to_name(self, row, col, nlayers):
if row == 0 and col == 1:
param = 2
elif row == 0 and col == 2:
param = 3
elif row == nlayers + 1 and col == 1:
param = 4
elif row == nlayers + 1 and col == 2:
param = 5
elif row == nlayers + 1 and col == 3:
param = 7
else:
param = 4 * (row - 1) + col + 8
names = curvefitter.names(self.params)
return names[param]
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()
def setData(self, index, value, role=QtCore.Qt.EditRole):
row = index.row()
col = index.column()
names = curvefitter.names(self.params)
if row:
name = names[row - 1]
if role == QtCore.Qt.CheckStateRole:
if row > 0 and col == 1:
if value == QtCore.Qt.Checked:
self.params[name].vary = False
else:
self.params[name].vary = True
if role == QtCore.Qt.EditRole:
if row == 0 and col == 0:
currentparams = self.rowCount() - 1
validator = QtGui.QIntValidator()
voutput = validator.validate(value, 1)
if voutput[0] is QtGui.QValidator.State.Acceptable and int(voutput[1]) >= 0:
newparams = int(voutput[1])
if newparams == currentparams:
return True
if newparams > currentparams:
self.beginInsertRows(
QtCore.QModelIndex(),
currentparams + 1,
newparams)
if newparams < currentparams:
self.beginRemoveRows(
QtCore.QModelIndex(),
newparams + 1,
currentparams)
if newparams > currentparams:
for i in range(currentparams, newparams):
self.params.add('p%d'%i, 0, True, -np.inf, np.inf, None)
self.endInsertRows()
if newparams < currentparams:
remove_names = names[newparams:]
map(self.params.pop, remove_names)
self.endRemoveRows()
self.modelReset.emit()
if row > 0 and col in [1, 2, 3]:
validator = QtGui.QDoubleValidator()
voutput = validator.validate(value, 1)
if voutput[0] == QtGui.QValidator.State.Acceptable:
number = float(voutput[1])
else:
return False
if col == 1:
self.params[name].value = number
if col == 2:
self.params[name].min = number
if col == 3:
self.params[name].max = number
if row > 0 and col == 0:
#change a parameter name requires making a new dictionary
if not valid_symbol_name(value):
return False
p = Parameters()
param = self.params[name]
newparam = Parameter(value, param.value, param.vary,
param.min, param.max, param.expr)
for k, v in self.params.items():
if k == name:
p[value] = newparam
else:
p[k] = v
self.params = p
if row > 0 and col == 4:
#set an expression
param = self.params[name]
param.expr = value
self.dataChanged.emit(index, index)
return True
