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")