def checkConfiguration(self):
"""Verify that the dopant and base are elements.
More detailed checking is done in the control method.
"""
from diffpy.pdfgui.control.controlerrors import ControlValueError
from diffpy.pdffit2 import is_element
base = self.textCtrlBaseElement.GetValue()
dopant = self.textCtrlDopant.GetValue()
# Make sure that the base and dopant are actual elements
base = base.title()
dopant = dopant.title()
if not is_element(base):
raise ControlValueError("'%s' is not an element!"%base)
if not is_element(dopant):
raise ControlValueError("'%s' is not an element!"%dopant)
return
def checkConfiguration(self):
"""Verify that the dopant and base are elements.
More detailed checking is done in the control method.
"""
from diffpy.pdfgui.control.controlerrors import ControlValueError
from diffpy.pdffit2 import is_element
base = self.textCtrlBaseElement.GetValue()
dopant = self.textCtrlDopant.GetValue()
# Make sure that the base and dopant are actual elements
base = base.title()
dopant = dopant.title()
if not is_element(base):
raise ControlValueError("'%s' is not an element!" % base)
if not is_element(dopant):
raise ControlValueError("'%s' is not an element!" % dopant)
return
def applyCellChange(self, i, j, value):
"""Update an atom according to a change in a cell.
i -- cell position
j -- cell position
value -- new value
"""
if not self.mainFrame or self.structure is None: return
# The element name
if j == 0:
value = value.title()
if not is_element(value): return
self.structure[i].element = value # element
return value
# Other entries
# ignore the change if the value is not valid
try:
value = float(value)
if value == "": value = 0.0
if j == 1:
self.structure[i].xyz[0] = value # x
elif j == 2:
self.structure[i].xyz[1] = value # y
elif j == 3:
self.structure[i].xyz[2] = value # z
elif j == 4:
self.structure[i].U[0,0] = value # U(1,1)
elif j == 5:
self.structure[i].U[1,1] = value # U(2,2)
elif j == 6:
self.structure[i].U[2,2] = value # U(3,3)
elif j == 7:
self.structure[i].U[0,1] = self.structure[i].U[1,0] = value # U(1,2)
elif j == 8:
self.structure[i].U[0,2] = self.structure[i].U[2,0] = value # U(1,3)
elif j == 9:
self.structure[i].U[1,2] = self.structure[i].U[2,1] = value # U(2,3)
elif j == 10:
self.structure[i].occupancy = value # occupancy
self.mainFrame.needsSave()
return value
except ValueError:
return
def applyCellChange(self, i, j, value):
"""Update an atom according to a change in a cell.
i -- cell position
j -- cell position
value -- new value
"""
if not self.mainFrame or self.structure is None: return
# The element name
if j == 0:
value = value.title()
if not is_element(value): return
self.structure[i].element = value # element
return value
# Other entries
# ignore the change if the value is not valid
try:
value = float(value)
if value == "": value = 0.0
if j == 1:
self.structure[i].xyz[0] = value # x
elif j == 2:
self.structure[i].xyz[1] = value # y
elif j == 3:
self.structure[i].xyz[2] = value # z
elif j == 4:
self.structure[i].U[0,0] = value # U(1,1)
elif j == 5:
self.structure[i].U[1,1] = value # U(2,2)
elif j == 6:
self.structure[i].U[2,2] = value # U(3,3)
elif j == 7:
self.structure[i].U[0,1] = self.structure[i].U[1,0] = value # U(1,2)
elif j == 8:
self.structure[i].U[0,2] = self.structure[i].U[2,0] = value # U(1,3)
elif j == 9:
self.structure[i].U[1,2] = self.structure[i].U[2,1] = value # U(2,3)
elif j == 10:
self.structure[i].occupancy = value # occupancy
self.mainFrame.needsSave()
return value
except ValueError:
return
def makeDopingSeries(control, fit, base, dopant, paths, doping):
"""Make a temperature series.
control -- pdguicontrol instance
fit -- The template fit
base -- Name of the base element
dopant -- Name of the dopant element
paths -- list of path names of new datasets
doping -- list of doping values corresponding to the datasets
returns a list of the new fit organization objects
"""
from diffpy.pdffit2 import is_element
# Make sure that base and dopant are elements
base = base.title()
dopant = dopant.title()
if not is_element(base):
raise ControlValueError("'%s' is not an element!"%base)
if not is_element(dopant):
raise ControlValueError("'%s' is not an element!"%dopant)
# Make sure that base and dopant are in the structure file(s)
hasBase = False
hasDopant = False
for S in fit.strucs:
for atom in S:
if atom.element == base:
hasBase = True
if atom.element == dopant:
hasDopant = True
if hasBase and hasDopant: break
if not hasBase:
message = "The template structure does not contain the base atom."
raise ControlValueError(message)
if not hasDopant:
message = "The template structure does not contain the dopant atom."
raise ControlValueError(message)
# Make sure we're only replacing a single dataset
if len(fit.datasets) != 1:
message = "Can't apply macro to fits with multiple datasets."
raise ControlValueError(message)
fits = []
# holds all of the other information about the dataset
fitbasename = fit.name
fitnewname = fit.name
fitlastname = fit.name
dataset = fit.datasets[0]
for i in range(len(paths)):
filename = paths[i]
fitlastname = fitnewname
fitcopy = control.copy(fit)
# Get rid of the old dataset
temp = fitcopy.datasets[0]
fitcopy.remove(temp)
# Configure the new dataset
dsname = os.path.basename(filename)
newdataset = FitDataSet(dsname)
newdataset.readObs(filename)
newdataset.qdamp = dataset.qdamp
newdataset.qbroad = dataset.qbroad
newdataset.dscale = dataset.dscale
newdataset.fitrmin = dataset.fitrmin
newdataset.fitrmax = dataset.fitrmax
rstep = dataset.fitrstep
st = dataset.getFitSamplingType()
newdataset.setFitSamplingType(st, rstep)
temperature = dataset.metadata.get("temperature")
if temperature is None: temperature = 300.0
newdataset.metadata["temperature"] = temperature
newdataset.constraints = copy.deepcopy(dataset.constraints)
# Set the chosen temperature
newdataset.metadata["doping"] = doping[i]
# Add the dataset to the fitcopy
fitcopy.add(newdataset, None)
# Update the doping information in the structures
for S in fitcopy.strucs:
for A in S:
if A.element == dopant:
A.occupancy = doping[i]
if A.element == base:
A.occupancy = 1-doping[i]
# Set the parameters to the previous fit's name, if one exists.
if fitlastname:
parval = "=%s" % fitlastname
for par in fitcopy.parameters.values():
par.setInitial(parval)
# Now paste the copy into the control.
fitnewname = "%s-%1.4f" % (fitbasename, doping[i])
o = control.paste(fitcopy, new_name = fitnewname)
fits.append(o)
return [f.organization() for f in fits]
def makeDopingSeries(control, fit, base, dopant, paths, doping):
"""Make a temperature series.
control -- pdguicontrol instance
fit -- The template fit
base -- Name of the base element
dopant -- Name of the dopant element
paths -- list of path names of new datasets
doping -- list of doping values corresponding to the datasets
returns a list of the new fit organization objects
"""
from diffpy.pdffit2 import is_element
# Make sure that base and dopant are elements
base = base.title()
dopant = dopant.title()
if not is_element(base):
raise ControlValueError("'%s' is not an element!" % base)
if not is_element(dopant):
raise ControlValueError("'%s' is not an element!" % dopant)
# Make sure that base and dopant are in the structure file(s)
hasBase = False
hasDopant = False
for S in fit.strucs:
for atom in S:
if atom.element == base:
hasBase = True
if atom.element == dopant:
hasDopant = True
if hasBase and hasDopant: break
if not hasBase:
message = "The template structure does not contain the base atom."
raise ControlValueError(message)
if not hasDopant:
message = "The template structure does not contain the dopant atom."
raise ControlValueError(message)
# Make sure we're only replacing a single dataset
if len(fit.datasets) != 1:
message = "Can't apply macro to fits with multiple datasets."
raise ControlValueError(message)
fits = []
# holds all of the other information about the dataset
fitbasename = fit.name
fitnewname = fit.name
fitlastname = fit.name
dataset = fit.datasets[0]
for i in range(len(paths)):
filename = paths[i]
fitlastname = fitnewname
fitcopy = control.copy(fit)
# Get rid of the old dataset
temp = fitcopy.datasets[0]
fitcopy.remove(temp)
# Configure the new dataset
dsname = os.path.basename(filename)
newdataset = FitDataSet(dsname)
newdataset.readObs(filename)
newdataset.qdamp = dataset.qdamp
newdataset.qbroad = dataset.qbroad
newdataset.dscale = dataset.dscale
newdataset.fitrmin = dataset.fitrmin
newdataset.fitrmax = dataset.fitrmax
rstep = dataset.fitrstep
st = dataset.getFitSamplingType()
newdataset.setFitSamplingType(st, rstep)
temperature = dataset.metadata.get("temperature")
if temperature is None: temperature = 300.0
newdataset.metadata["temperature"] = temperature
newdataset.constraints = copy.deepcopy(dataset.constraints)
# Set the chosen temperature
newdataset.metadata["doping"] = doping[i]
# Add the dataset to the fitcopy
fitcopy.add(newdataset, None)
# Update the doping information in the structures
for S in fitcopy.strucs:
for A in S:
if A.element == dopant:
A.occupancy = doping[i]
if A.element == base:
A.occupancy = 1 - doping[i]
# Set the parameters to the previous fit's name, if one exists.
if fitlastname:
parval = "=%s" % fitlastname
for par in fitcopy.parameters.values():
par.setInitial(parval)
# Now paste the copy into the control.
fitnewname = "%s-%1.4f" % (fitbasename, doping[i])
o = control.paste(fitcopy, new_name=fitnewname)
fits.append(o)
return [f.organization() for f in fits]
