mcutils/xray/example_main_tiox.py

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from __future__ import print_function,division
import numpy as np
import pylab as plt
import mcutils as mc
import mcutils.xray as xray
from mcutils.xray import id9
id9 = xray.id9
# use npz files (they can handle more stuff (list of arrays,unicode) than h5py)
id9.storage_extension = '.npz'
#id9.storage_extension = '.h5'
def azav(folder,nQ=1500,force=False,saveChi=True,
poni='auto',storageFile='auto',mask=470):
if isinstance(mask,int):
files = xray.utils.getFiles(folder,"*.edf*")
img = xray.azav.pyFAIread(files[0])
temp = np.ones_like(img,dtype=bool)
temp[:mask] = False
mask = temp
return id9.doFolder_azav(folder,nQ=nQ,force=force,mask=mask,saveChi=saveChi,
poni=poni,storageFile=storageFile)
def datared(folder,monitor=(1,5),showPlot=True,**kw):
data,diffs = id9.doFolder_dataRed(folder,monitor=monitor,**kw)
if showPlot: xray.utils.plotdiffs(diffs.q,diffs.data,t=diffs.scan)
return data,diffs
def doall(folder,force=False):
azav(folder,force=force)
return datared(folder)
def plotCalc(scale=1):
fold = "../tiox/calculated_patterns/"
q,i=readtxt(fold + "alpha500K.xye.q")
plt.plot(q,i*scale,label="alpha")
q,i=readtxt(fold + "beta290K.xye.q")
plt.plot(q,i*scale,label="beta")
q,i=readtxt(fold + "lambda.xye.q")
plt.plot(q,i*scale,label="lambda")