def __init__(self, name):
"""Define the generator.
Note that a ProfileGenerator needs a name passed in the initializer.
This makes it so the generator can be referenced by name when it is
part of a FitContribution.
Here we create the Parameters for the calculation.
A -- The amplitude
x0 -- The center
sigma -- The width
"""
# This initializes various parts of the generator
ProfileGenerator.__init__(self, name)
# Here we create new Parameters using the '_newParameter' method of
# ProfileGenerator. The signature is
# _newParameter(name, value).
# See the API for full details.
self._newParameter('A', 1.0)
self._newParameter('x0', 0.0)
self._newParameter('sigma', 1.0)
return
def __init__(self, name):
ProfileGenerator.__init__(self, name)
self._newParameter("wavelength", 10.0)
self._newParameter("center", 2.0)
self._newParameter("cos_coef", .1)
self._newParameter("sin_coef", .1)
self._newParameter("left_std", 5.)
self._newParameter("right_std", 5.0)
return
def processMetaData(self):
"""Process the metadata once it gets set."""
ProfileGenerator.processMetaData(self)
for name in self.__class__._parnames:
val = self.meta.get(name)
if val is not None:
par = self.get(name)
par.setValue(val)
return
def __init__(self, name):
"""Define our generator.
In this example we will keep count of how many times the calculation
gets performed. The 'count' attribute will be used to store the count.
"""
ProfileGenerator.__init__(self, name)
# Count the calls
self.count = 0
return
def __init__(self, name):
"""Define our generator.
In this example we will keep count of how many times the calculation
gets performed. The 'count' attribute will be used to store the count.
"""
ProfileGenerator.__init__(self, name)
# Count the calls
self.count = 0
return
def __init__(self, name = "pdf"):
"""Initialize the generator."""
ProfileGenerator.__init__(self, name)
self._phase = None
self.stru = None
self.meta = {}
self._lastr = None
self._calc = None
self._pool = None
return
def __init__(self, name="pdf"):
"""Initialize the generator."""
ProfileGenerator.__init__(self, name)
self._phase = None
self.stru = None
self.meta = {}
self._lastr = numpy.empty(0)
self._calc = None
self._pool = None
return
def __init__(self, name="pdf"):
"""Initialize the generator."""
ProfileGenerator.__init__(self, name)
self._pdfprofile = None
# self.xscale = 1.0
# self.yscale = 1.0
self.meta = {'xscale':1.0,
'yscale':1.0}
self._lastr = None
self._setCalculator()
return
def _validate(self):
"""Validate my state.
This validates that the phase is not None.
This performs ProfileGenerator validations.
Raises AttributeError if validation fails.
"""
# FIXME
if self._pdfprofile is None:
raise AttributeError("_pdfprofile is None")
ProfileGenerator._validate(self)
return
def _validate(self):
"""Validate my state.
This validates that the phase is not None.
This performs ProfileGenerator validations.
Raises SrFitError if validation fails.
"""
if self._calc is None:
raise SrFitError("_calc is None")
if self._phase is None:
raise SrFitError("_phase is None")
ProfileGenerator._validate(self)
return
def _validate(self):
"""Validate my state.
This validates that the phase is not None.
This performs ProfileGenerator validations.
Raises SrFitError if validation fails.
"""
if self._calc is None:
raise SrFitError("_calc is None")
if self._phase is None:
raise SrFitError("_phase is None")
ProfileGenerator._validate(self)
return
def processMetaData(self):
"""Process the metadata once it gets set."""
ProfileGenerator.processMetaData(self)
stype = self.meta.get("stype")
if stype is not None:
self.setScatteringType(stype)
qmax = self.meta.get("qmax")
if qmax is not None:
self.setQmax(qmax)
qmin = self.meta.get("qmin")
if qmin is not None:
self.setQmin(qmin)
for name in self.__class__._parnames:
val = self.meta.get(name)
if val is not None:
par = self.get(name)
par.setValue(val)
return
def processMetaData(self):
"""Process the metadata once it gets set."""
ProfileGenerator.processMetaData(self)
stype = self.meta.get("stype")
if stype is not None:
self.setScatteringType(stype)
qmax = self.meta.get("qmax")
if qmax is not None:
self.setQmax(qmax)
qmin = self.meta.get("qmin")
if qmin is not None:
self.setQmin(qmin)
for name in self.__class__._parnames:
val = self.meta.get(name)
if val is not None:
par = self.get(name)
par.setValue(val)
return
def __init__(self, name, model):
"""Initialize the generator.
name -- A name for the SASGenerator
model -- SASModel object this adapts.
"""
ProfileGenerator.__init__(self, name)
self._model = model
# Wrap normal parameters
for parname in model.params:
par = SASParameter(parname, model)
self.addParameter(par)
# Wrap dispersion parameters
for parname in model.dispersion:
name = parname + "_width"
parname += ".width"
par = SASParameter(name, model, parname)
self.addParameter(par)
return
def __init__(self, name, model):
"""Initialize the generator.
name -- A name for the SASGenerator
model -- SASModel object this adapts.
"""
ProfileGenerator.__init__(self, name)
self._model = model
# Wrap normal parameters
for parname in model.params:
par = SASParameter(parname, model)
self.addParameter(par)
# Wrap dispersion parameters
for parname in model.dispersion:
name = parname + "_width"
parname += ".width"
par = SASParameter(name, model, parname)
self.addParameter(par)
return
def __init__(self, name):
ProfileGenerator.__init__(self, name)
self._newParameter("wavelength", 20.0)
self._newParameter("cos_coef", .1)
self._newParameter("sin_coef", .1)
return
