def binning(magic_channel,ylow,yhigh,spm3path,tifpath,fileroot,scannum,*omitfile):
#    """
#    This will rebin tif files using user input parameters.
#    binning(magic_channel,ylow,yhigh,spm3path,tifpath,fileroot,scannum,*omitfile):
#    binning(126,50,210,'C:\Users\Slot7_Kourtis','C:\Users\slot7','21Nov2021',338,'C:\Users\omit.txt')
#    The last input, omit.txt, is optional.
#    magic_channel: focal channel of the elastic line on the lambda detector
#    ylow, yhigh: where the summation on the lambda begins and ends in the analyzer chi direction
#    spm3path: path giving location of spm3 file
#    tifpath: path giving location of tif files generated by lambda
#    fileroot: root name of file, is used to generate spm3 and tif file names
#    scannum: scan number to be rebinned
#    omitfile: xy coordinates of lambda pixels to be omitted from scan, if any.
#    If a pixel is permanently on or wonky in any way this is a way to exclude it from the data
#    Output two columns: Energy and spectra
#    """
    
    from os import listdir
    from os.path import isfile, join
    import matplotlib.pyplot as plt
    import numpy as np
    from PIL import Image
    import re
    #import matplotlib.pyplot as plt

    #define region of interest horizontally
    # Do some calculations
    # AnalyzerProperties
    ##################
# Read EB from spm3 file also first and last energies of the scan, Ei and Ef

    tifstring='_scan'+str(scannum)+'_'
    tiffiles=[]
    for f in listdir(tifpath):
        if isfile(join(tifpath,f)) and (tifstring in f) and (fileroot in f):
            tiffiles.append(f)
    if len(tiffiles)==0:
        print('Tif files not found\n')
#####################
    spm3file=spm3path+'\\'+fileroot+'.spm3'
    try:
        f=open(spm3file,'r')
    except IOError:
        print("Error: spm3 File does not appear to exist")
        print("Was looking for "+spm3file)
    foundscan=0
    foundEi=0
    for line in f:
        if line.startswith('#S '+str(scannum)):
           foundscan=1
           print('found the scan '+ spm3file)
           continue
        if foundscan:
            if line.startswith('#C Analyzer EB'):
                splits=line.split(' ');
                EB=float(splits[-1])
                print('EB is ',EB)
                continue
            if line.startswith('#C Rowland radius'):
                splits=line.split(' ');
                R=float(splits[-1])
                print('R is ',R)
                continue
            if line.startswith(tuple('0123456789')) and foundEi==0:
                splits=line.split(' ')
                Ei=float(splits[0])
                foundEi=1
                continue
            if line=='\n' and foundEi==1:
                break
            if foundEi==1:
                splits=line.split(' ')
                Ef=float(splits[0])
    f.close()
    ##################
    EB=EB*1e3 # backscattering energy in eV
    RefE=1e3*(Ei+Ef)/2 # Energy  in eV
    thetaB=np.arcsin(EB/(RefE));
    dEdr=(1/np.tan(thetaB))*RefE/(2*R) #eV/mm
    micronsperchannel=25 #microns
    mmperchannel=micronsperchannel/1e3
    dEdchan=dEdr*mmperchannel/1e3 #keV/channel

    xwidth=np.ceil(1.5*1e3/micronsperchannel) #number of channels for a 1.5 mm analyzer


    # Create the energy array
    Energy=np.arange(Ei,Ef,(Ef-Ei)/len(tiffiles))
    # create bin edges
    dE=Energy[1]-Energy[0]
    binedges=Energy-dE/2
    binedges=np.append(binedges,Energy[-1]+dE/2)

    # deltaE is relative energy of the columns on the lambda (strips on mythen)
    deltaE=(-1)*np.arange(-int(np.floor(xwidth/2)),int(np.floor(xwidth/2)))*dEdchan
    # scan is initializing a scan in the correct length
    scan=np.zeros(Energy.shape)
    A=np.zeros(Energy.shape)
    xomit=np.empty((0,0),int)
    yomit=np.empty((0,0),int)
    if omitfile:
        print('there is a file of points that should be omitted\n')
        try:
            ff=open(omitfile[0])
        except IOError:
            print("Error: file does not appear to exist")
            print("Was looking for "+omitfile)
        

        for line in ff:
            coordinates=line.split()
            if len(coordinates)>2:
                print('More than 2 numbers per line in omit file\n')
                print('Line 1 is: ',coordinates)
            xomit=np.append(xomit,np.array([int(coordinates[0])-1]))
            yomit=np.append(yomit,np.array([int(coordinates[1])-1]))

    if len(tiffiles)==0:
        print("Can not find any tif files")
        print("Was looking here: "+tifpath)
    # Finally, go through and combine the data
    for i, file in zip(range(len(tiffiles)),tiffiles):
        # io.imread returns an nd array
        # below, reduce size a little to throw out excess data
        img=plt.imread(tifpath+'\\'+file)
        img[xomit,yomit]=0
        img=img[ylow:yhigh,magic_channel-int(np.floor(xwidth/2)):magic_channel+int(np.floor(xwidth/2))]
        # below, throw out data with counts above 3000 as noise
        img[img>3000]=0
        img=np.sum(img,axis=0)
        # below find out what energy each point in the (now 1d array) img corresponds to
        stripE=deltaE+Energy[i]
        # Which point on the scan does each element in img belong to.
        # indexassignments is the bin that each element of img belongs to.
        
        indexassignments=np.digitize(stripE,binedges)
        for j in range(len(indexassignments)):
            currentbin=indexassignments[j]
            if currentbin>len(scan)-1:
                continue
            scan[currentbin]=scan[currentbin]+img[j]
            A[currentbin]=A[currentbin]+1

    Energy=np.delete(Energy,[0])
    scan=np.delete(scan,[0])
    A=np.delete(A,[0])

    output=np.transpose(np.stack((Energy,scan)))
    Energy=(Energy)*1e3
#    plt.plot(Energy,scan)
#    plt.show()
    return output