diffpy.pdfgui/src/diffpy/pdfgui/control/pdfguimacros.py at cookie · diffpy/diffpy.pdfgui · GitHub

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#!/usr/bin/env python

##############################################################################

# PDFgui by DANSE Diffraction group

# Simon J. L. Billinge

# File coded by: Chris Farrow

# See AUTHORS.txt for a list of people who contributed.

# See LICENSE.txt for license information.

##############################################################################

"""Methods for macros used in pdfgui."""

from __future__ import print_function

import copy

import os

from diffpy.pdfgui.control.controlerrors import ControlValueError

from diffpy.pdfgui.control.fitdataset import FitDataSet

def makeRSeries(

control,

fit,

maxfirst=None,

maxlast=None,

maxstep=None,

minfirst=None,

minlast=None,

minstep=None,

"""Make an series of fits with an increasing r-range.

The new fits are appended to the end of any current fits in the control.

control -- The control object that will contain the fits

fit -- The prototype fit

maxfirst -- The first value of the maximum of the fit range

maxlast -- The last value of the maximum of the fit range

maxstep -- The step size of the maximum of the fit range

minfirst -- The first value of the minimum of the fit range

minlast -- The last value of the minimum of the fit range

minstep -- The step size of the minimum of the fit range

returns a list of the new fit organization objects

"""

# Check to see if the input values are correct.

# MIN-MIN: FIRST < LAST

if minfirst is not None and minlast is not None and not minfirst < minlast:

message = (

"The first value of the minimum (%.2f)\

\nmust be less than the last value of the\

\nminimum (%.2f)"

% (minfirst, minlast)

)

raise ControlValueError(message)

# MAX-MAX: FIRST < LAST

if maxfirst is not None and maxlast is not None and not maxfirst < maxlast:

message = (

"The first value of the maximum (%.2f)\

\nmust be less than the last value of the\

\nmaximum (%.2f)"

% (maxfirst, maxlast)

)

raise ControlValueError(message)

# MAX > MIN: FIRST-FIRST

if maxfirst is not None and minfirst is not None and not maxfirst > minfirst:

message = (

"The first value of the fit maximum (%.2f)\

\nmust be greater than first value of the fit\

\nminimum (%.2f)."

% (maxfirst, minfirst)

)

raise ControlValueError(message)

# MAX > MIN: LAST-LAST

if maxlast is not None and minlast is not None and not maxlast > minlast:

message = (

"The last value of the fit maximum (%.2f)\

\nmust be greater than last value of the fit\

\nminimum (%.2f)."

% (maxlast, minlast)

)

raise ControlValueError(message)

# STEP > 0

message = "Step size (%.2f) must be greater than 0."

if maxstep is not None and not maxstep > 0:

raise ControlValueError(message % maxstep)

if minstep is not None and not minstep > 0:

raise ControlValueError(message % minstep)

# Check to see that either max or min is fully specified

maxlist = [maxfirst, maxlast]

minlist = [minfirst, minlast]

if maxlist.count(None) == 1 or minlist.count(None) == 1:

raise ControlValueError("First and last values are partially specified")

if maxstep is None and minstep is None:

raise ControlValueError("Either minstep or maxstep must be specified.")

maxlist = []

minlist = []

if maxfirst is not None:

if maxstep is None:

maxstep = minstep

maxrange = int((maxlast - maxfirst) / (1.0 * maxstep) + 1)

maxlist = [maxfirst + i * maxstep for i in range(maxrange)]

if minfirst is not None:

if minstep is None:

minstep = maxstep

minrange = int((minlast - minfirst) / (1.0 * minstep) + 1)

minlist = [minfirst + i * minstep for i in range(minrange)]

# Resize the lists to the length of the shortest

serieslen = min(len(maxlist), len(minlist))

if serieslen != 0:

maxlist = maxlist[:serieslen]

minlist = minlist[:serieslen]

else:

serieslen = max(len(maxlist), len(minlist))

basename = fit.name

fits = []

newname = ""

lastname = ""

fitcopy = control.copy(fit)

# Duplicate the original fit and change the appropriate parameters.

for i in range(serieslen):

lastname = newname

# Loop over datasets

for ds in fitcopy.datasets:

if minlist:

fitrmin = minlist[i]

else:

fitrmin = ds.fitrmin

if maxlist:

fitrmax = maxlist[i]

else:

fitrmax = ds.fitrmax

# Check to see that the values are in bounds and sensical

if fitrmin < ds.rmin or fitrmin >= ds.rmax:

message = (

"Fit minimum (%.2f) is outside the data range\

\n[%.2f, %.2f].\

\nAdjust the range of the series."

% (fitrmin, ds.rmin, ds.rmax)

)

raise ControlValueError(message)

if fitrmax <= ds.rmin or fitrmax > ds.rmax:

message = (

"Fit maximum (%.2f) is outside the data range\

\n[%.2f, %.2f].\

\nAdjust the range of the series."

% (fitrmax, ds.rmin, ds.rmax)

)

raise ControlValueError(message)

if fitrmin >= fitrmax:

message = (

"Fit minimum (%.2f) is greater than the\

\nmaximum (%.2f).\

\nIncrease maxstep or reduce minstep."

% (fitrmin, fitrmax)

)

raise ControlValueError(message)

# Set the values if all is well

if minlist:

ds.fitrmin = fitrmin

if maxlist:

ds.fitrmax = fitrmax

# Set the parameters to the previous fit's name, if one exists.

if lastname:

parval = "=%s" % lastname

for par in fitcopy.parameters.values():

par.setInitial(parval)

# Now paste the copy into the control.

newname = "%s-(%.2f,%.2f)" % (basename, fitrmin, fitrmax)

o = control.paste(fitcopy, new_name=newname)

fits.append(o)

return [f.organization() for f in fits]

# Temperature Series

def makeTemperatureSeries(control, fit, paths, temperatures):

"""Make a temperature series.

control -- pdguicontrol instance

fit -- The template fit

paths -- list of path names of new datasets

temperatures -- list of temperatures corresponding to the datasets

returns a list of the new fit organization objects

"""

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)

doping = dataset.metadata.get("doping")

if doping is None:

doping = 0.0

newdataset.metadata["doping"] = doping

newdataset.constraints = copy.deepcopy(dataset.constraints)

# Set the chosen temperature

newdataset.metadata["temperature"] = temperatures[i]

# Add the dataset to the fitcopy

fitcopy.add(newdataset, None)

# 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-T%i=%g" % (fitbasename, i + 1, temperatures[i])

o = control.paste(fitcopy, new_name=fitnewname)

fits.append(o)

return [f.organization() for f in fits]

# Doping Series

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]

if __name__ == "__main__":

from diffpy.pdfgui.control.pdfguicontrol import PDFGuiControl

control = PDFGuiControl()

control.load("../../tests/testdata/ni.ddp")

fit = control.fits[0]

olist = makeRSeries(control, fit, 5, 20, 5)

print("\n".join(f[0].name for f in olist))

# End of file

diffpy.pdfgui/src/diffpy/pdfgui/control/pdfguimacros.py at cookie · diffpy/diffpy.pdfgui · GitHub

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