Revision 8ae5bfc17ec019fcc8ec7e4627442646e52cc3c5 authored by ulbrica on 19 April 2021, 10:56:22 UTC, committed by GitHub on 19 April 2021, 10:56:22 UTC
1 parent 0166b40
Raw File
calcium-analysis
print "ready"

#import sys
#sys.setrecursionlimit(5000)

import numpy as np
import math
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure
from PIL import Image
from scipy.ndimage import gaussian_filter
import Tkinter as tk
import tkFileDialog 
import os


print "steady"
np.warnings.filterwarnings('ignore')

###############
## -- GUI -- ##
###############

## ++ choose file ++ ##
root1 = tk.Tk()
root1.filename = tkFileDialog.askopenfilename()
filename = root1.filename
#print filename                                         # whole path & *.tif

directory = os.path.split(filename)[0]
directory = str (directory)
#print directory                                        # whole path without *.tif

baseFolder = os.path.abspath(os.path.join(directory, os.pardir))

rawdataFolder = os.path.basename(directory)             # no path only name of previous file
stopFolder = rawdataFolder.find("raw")
folder = rawdataFolder[0:stopFolder-1]



## ++ choose 2PM & binning ++ ##
v = tk.IntVar()
v.set(1)

options = [
    ("old 2PM + binning1 [153]",153),
    ("old 2PM + binning2 [76]",  76),
    ("new 2PM + binning1 [455]",455),
    ("new 2PM + binning2 [227]",227)
    ]

def ShowChoice():
    global timesteps                 # == number of images in time stack
    timesteps = v.get()


for txt, val in options:
    tk.Radiobutton(root1, 
                text=txt,
                padx = 20, 
                variable=v, 
                command=ShowChoice,
                value=val).pack(anchor=tk.W)

button = tk.Button(root1,text="OK", fg="red", command=root1.destroy)
button.pack(side="bottom")

root1.mainloop()

print "    ", timesteps, "timesteps"
    

### ++ tip sigma & offset ++ ##
root2 = tk.Tk()

sigma = 2
offset = 10
thresh = 0
def show_entry_fields():
    global sigma, offset, thresh
    sigma = e1.get()
    sigma = int(sigma)
    offset = e2.get()
    offset = int(offset)
    thresh = e3.get()
    thresh = int(thresh)

tk.Label(root2, text="gaussian blur: sigma = [2]").grid(row = 0)
tk.Label(root2, text="number of steps used for offset [10]:").grid(row = 1)
tk.Label(root2, text="threshold - pixelvalue in SUM-image [0]:").grid(row = 2)

e1 = tk.Entry(root2)
e2 = tk.Entry(root2)
e3 = tk.Entry(root2)

e1.grid(row = 0, column = 1)
e2.grid(row = 1, column = 1)
e3.grid(row = 2, column = 1)

tk.Button(root2, text='use', command=show_entry_fields).grid(row=3, column=1, sticky=tk.W, pady=4)
tk.Button(root2, text='OK', fg="red", command=root2.destroy).grid(row=3, column=0, sticky=tk.W, pady=4)

root2.mainloop()

print "     sigma = ", sigma
print "     offset = ", offset
print "     threshold = ", thresh
print "go "


### ++ choose running variable ++ ##

root4 = tk.Tk()
tk.Label(root4, text = "Which part in filename is running?").grid(row=0, column=0, columnspan=3, sticky=tk.W, pady=4)

substring = [["none", 0, 0],
             ["Time Time", 5, 8],
             ["Axis0000", 18, 5],
             ["xyz-Table Upright Z", 18, 5],
             ["C00", 0, 3]]

def runV():
    global AA
    AA = [var1.get(), var2.get(), var3.get(), var4.get(), var5.get()]
    AA = np.asarray([index for index, value in enumerate(AA) if value == 1])
    print ""
    print "running variables:"
    for ii in range(len(AA)): print "   ", substring[AA[ii]][0]

tauName = ""
realName = ""
imagName = ""
def imaris_yes():
    global tauName, realName, imagName, AA, tausi
    tauName = "Ch222"
    realName = "Ch000"
    imagName = "Ch111"
    tausi = 1000
    print "for Imaris"
    runV()
    
def imaris_no():
    global tauName, realName, imagName, tausi
    tauName = "tauImage"
    realName = "real"
    imagName = "imag"
    tausi = 1
    runV()

var1 = tk.IntVar()
tk.Checkbutton(root4, text=substring[0][0], variable=var1).grid(row=1, sticky=tk.W)

var2 = tk.IntVar()
tk.Checkbutton(root4, text=substring[1][0], variable=var2).grid(row=2, sticky=tk.W)

var3 = tk.IntVar()
tk.Checkbutton(root4, text=substring[2][0], variable=var3).grid(row=3, sticky=tk.W)

var4 = tk.IntVar()
tk.Checkbutton(root4, text=substring[3][0], variable=var4).grid(row=4, sticky=tk.W)

var5 = tk.IntVar()
tk.Checkbutton(root4, text=substring[4][0], variable=var5).grid(row=5, sticky=tk.W)

tk.Label(root4, text = "Do you plan to use IMARIS?").grid(row=8, columnspan=3, sticky=tk.W, pady=4)

tk.Button(root4, text='yes', command=imaris_yes).grid(row=9, column = 0, sticky=tk.W, pady=4)
tk.Button(root4, text='no', command=imaris_no).grid(row=9, column = 1, sticky=tk.W, pady=4)
tk.Button(root4, text='Ok', fg="red", command=root4.destroy).grid(row=9, column = 2, sticky=tk.W, pady=4)

tk.mainloop()



fq = 80E6                                    # modulation frequence [Hz]
w = 2*math.pi*fq

def reS(tau):
    return 1/(1+(w*tau)**2)

def imS(tau):
    return w*tau/(1+(w*tau)**2)


################################
## -- NAD(P)H finger print -- ##
################################
tau_free = 0.450E-9         # free NAD(P)H  in ns,  middle of free region

tau_MDH = 1.2400E-9         # malate dehydrogenase (NADH bound to)
tau_HADH = 1.360E-9
tau_LDH = 1.600E-9          # lactate dehydrogenase
tau_G6PDH = 2.005E-9        # NADPH
tau_SDH_1 = 2.010E-9        # sorbitol dehydrogenase (NADH)
tau_GAPDH = 2.050E-9        #Glyceraldehyde 3-phosphate dehydrogenase
#tau_GPDH1 = 2.070E-9
tau_IDH = 2.170E-9          # Isocitrate dehydrogenase
tau_SDH_2 = 2.260E-9        # sorbitol dehydrogenase (NADPH)
tau_CTBP1_PDH = 2.470E-9
#tau_PDH = 2.470E-9
tau_iNOS = 2.550E-9
tau_ADH = 2.600E-9          # alcohol dehydrogenase

tau_NOX = 3.650E-9          # NADPH

list_tau = (tau_free, tau_MDH, tau_HADH, tau_LDH, tau_G6PDH, tau_SDH_1, tau_GAPDH, tau_IDH, tau_SDH_2, tau_CTBP1_PDH, tau_iNOS, tau_ADH, tau_NOX)
labels_tau = ('free', 'MDH', 'HADH', 'LDH', 'G6PDH', 'SDH (NADH)', 'GAPDH', 'IDH', 'SDH (NADPH)', 'CTBP1/PDH', 'iNOS', 'ADH', 'NOX')
#colors_tau = ((0,0.5,0.4), (1,1,0), (1,0.6,0), (0,1,1), (0,0.2,0.6), (0.5,0,0.5), (1,0,0), (0,0,0), (1,0,1), (0,0,0.5), (0,1,0), (0,0,1), (0.5,0.5,0), (0.5,0,0), (0,0.5,0))
#colors_tau = colors_tau = ((0.0, 0.0, 1.0), (0.0, 0.518, 0.0), (0.0, 0.675, 0.322), (0.0, 0.914, 0.082), (0.0, 1.0, 0.0), (0.514, 1.0, 0.0), (0.859, 1.0, 0.0), (1.0, 1.0, 0.0), (1.0, 1.0, 0.498), (1.0, 1.0, 0.651), (1.0, 0.957, 0.0), (1.0, 0.714, 0.0), (1.0, 0.553, 0.0), (1.0, 0.0, 0.0))
colors_tau = colors_tau = ((0.0, 0.0, 1.0), (0.0, 0.518, 0.0), (0.0, 0.675, 0.322), (0.0, 0.914, 0.082), (0.0, 1.0, 0.0), (0.514, 1.0, 0.0), (0.859, 1.0, 0.0), (1.0, 1.0, 0.0), (1.0, 1.0, 0.498), (1.0, 0.957, 0.0), (1.0, 0.714, 0.0), (1.0, 0.553, 0.0), (1.0, 0.0, 0.0))
def fingerprint():
    for num in range(0,len(list_tau)):     
        ax.plot(reS(list_tau[num]), imS(list_tau[num]), marker='o', markersize=8, color=colors_tau[num], linestyle='none', label=labels_tau[num])

        
#####################################
## --  define ploting functions -- ##
#####################################
fs = 15          #fontsize plot

def enzymRegion():
    ## -- enzym region -- ##
    rEnzy = []
    iEnzy = []
    for x in range(77, 108):
        rEnzy.append((1+math.cos(math.radians(x)))/2)
        iEnzy.append((math.sin(math.radians(x)))/2)
   
    ax.plot(rEnzy, iEnzy, 'k-', linewidth=5)
    
    
def NADPHscale():
    ## -- free -- ##
    ax.plot(reS(tau_free), imS(tau_free), 'ko')
    ax.text(reS(tau_free), imS(tau_free), "free",  va = 'bottom', ha = 'left', rotation = 45, fontsize=fs)
    
    ## -- meta. enzymes -- ##
    tau_enzyM = 2026E-12                 # middle of enzym region
    ax.text(reS(tau_enzyM)-0.11, imS(tau_enzyM)+0.02, "meta. enzymes",  va = 'bottom', ha = 'left', fontsize=fs)
    
    ## -- NOX region -- ##
    tau_oxi = 3650E-12                  # s; NAD(P)H oxidase
    
    ax.plot(reS(tau_oxi), imS(tau_oxi), 'ko')
    ax.text(reS(tau_oxi)-0.01, imS(tau_oxi)+0.01, "NOX",  va = 'bottom', ha = 'left', rotation = 45, fontsize=fs)

    ax.plot()

    
def FRETscale_CertNL():
    tau_quen = 693E-12          # CerT-NL; Rinnenthal et al, 2013
    tau_unquen = 2225E-12

    ax.plot(reS(tau_quen), imS(tau_quen), 'ko')
    ax.text(reS(tau_quen), imS(tau_quen), "quen.",  verticalalignment = 'bottom', horizontalalignment = 'left', rotation = 45, fontsize=fs)
    ax.plot(reS(tau_unquen), imS(tau_unquen), 'ko')
    ax.text(reS(tau_unquen), imS(tau_unquen), "unquen.",  verticalalignment = 'bottom', horizontalalignment = 'left', rotation = 45, fontsize=fs)

    ax.plot()

    
def FRETscale_TNXXL():
       
#    tau_quen = 1260E-12         # TN-XXL; Griesbeck et al
#    tau_unquen = 2110E-12 

    # TN-XXL; Griesbeck et al
    tau_quen = 735E-12           # tau1 from suppl tab 1 ECFP
    tau_inter = 1260E-12         # from text
    tau_unquen = 2350E-12        # tau_ave from suppl tab 1 ECFP  

    ax.plot(reS(tau_quen), imS(tau_quen), 'ko')
    ax.text(reS(tau_quen), imS(tau_quen), "quen.",  verticalalignment = 'bottom', horizontalalignment = 'left', rotation = 45, fontsize=fs)

    ax.plot(reS(tau_inter), imS(tau_inter), 'ko')
    ax.text(reS(tau_inter), imS(tau_inter), "inter.",  verticalalignment = 'bottom', horizontalalignment = 'left', rotation = 45, fontsize=fs)
    
    ax.plot(reS(tau_unquen), imS(tau_unquen), 'ko')
    ax.text(reS(tau_unquen), imS(tau_unquen), "unquen.",  verticalalignment = 'bottom', horizontalalignment = 'left', rotation = 45, fontsize=fs)

    
def tauMark():
#    tau_mark = (0.001E-9, 1E-9, 2E-9, 3E-9, 4E-9, 5E-9, 6E-9, 7E-9, 8E-9, 9E-9, 10E-9)
    tau_mark = (0.001E-9, 1E-9, 2E-9, 3E-9, 4E-9, 5E-9, 6E-9, 7E-9, 8E-9, 9E-9, 10E-9, 11E-9, 12E-9, 13E-9, 14E-9, 15E-9)
    tau_text = ("0ns", "1ns", "2ns", "3ns", "4ns", "5ns", "6ns", "7ns", "8ns", "9ns", "10ns")
    
    for index in range(len(tau_mark)):
        ax.plot(reS(tau_mark[index]), imS(tau_mark[index]), marker='o', markersize=7, color='#bebebe', linestyle='none')
        #ax.text(reS(tau_mark[index])+0.01, imS(tau_mark[index])+0.001, tau_text[index],  verticalalignment = 'bottom', horizontalalignment = 'left', fontsize=12, color='#bebebe')
 
    #ax.plot([0, reS(tau_free)], [0, imS(tau_free)], color=(0,1,0), linestyle='-') 
        
#    ax.plot(reS(tau_free), imS(tau_free), 'ko')
#    ax.text(reS(tau_free), imS(tau_free), "free",  va = 'bottom', ha = 'left', rotation = 45, fontsize=fs)
    
#    ax.plot([reS(tau_free), reS(tau_LDH)], [imS(tau_free), imS(tau_LDH)], color=(0,1,1), linestyle='-') 
#    
#    ax.plot(reS(tau_LDH), imS(tau_LDH), 'co')
#    ax.text(reS(tau_LDH)+0.01, imS(tau_LDH)+0.01, "LDH",  va = 'bottom', ha = 'left', fontsize=12)
    
#    ax.plot(reS(tau_MDH), imS(tau_MDH), 'ro')
#    ax.text(reS(tau_MDH), imS(tau_MDH), "MDH",  va = 'bottom', ha = 'left', fontsize=12)
    
    ax.plot()
 
    
def layout():
    global real, imag, scale
    real = []
    imag = []
    for x in range(0, 180):
        real.append((1+math.cos(math.radians(x)))/2)
        imag.append((math.sin(math.radians(x)))/2)
        
    ax.plot(real, imag, 'k-')
    ax.set_xlim(0, 1)
    ax.set_ylim(0, 0.6)
    
    ax.set_xlabel('real', fontsize=fs)
    ax.set_ylabel('imaginary', fontsize=fs)

    if scale == 1:
        NADPHscale()
        enzymRegion()
 

    elif scale == 2:
        NADPHscale()
        fingerprint()
        
    elif scale == 3:
        FRETscale_CertNL()
        
    elif scale == 4:
        FRETscale_TNXXL() 
        
    elif scale == 5:
        tauMark()
        
    else: pass


def contour():
    global upCL, lowCL, cf, counts1, levels, extent
    if n == 0:
        upCL = e.get()
        upCL = int(upCL)

        lowCL = e2.get()
        lowCL = int(lowCL)                
    else:
        upCL
        lowCL
    
    canvas=FigureCanvasTkAgg(fig,master=root4)
    canvas.get_tk_widget().grid(row=6,column=0, columnspan = 4)
    ax.clear()

    counts1, ybins1, xbins1 = np.histogram2d(eTAU[:,1], eTAU[:,0], bins=80)
    extent = [xbins1.min(), xbins1.max(), ybins1.min(), ybins1.max()]
    levels = np.arange(lowCL, upCL, 0.01*upCL)
    cf = ax.contour(counts1, levels, linewidths = 1, cmap='plasma', extent = extent)
    
    layout()
    

def dots():
    global upCL, lowCL, cf, counts1, levels, extent
    if n == 0:
        upCL = e.get()
        upCL = int(upCL)

        lowCL = e2.get()
        lowCL = int(lowCL)                
    else:
        upCL
        lowCL
    
    canvas=FigureCanvasTkAgg(fig,master=root4)
    canvas.get_tk_widget().grid(row=6,column=0, columnspan = 4)
    ax.clear()
    
#    if scale == 2:
#        ax.plot(eTAU[:,0], eTAU[:,1], color = 'k', marker='.', linestyle='none', markersize=0.7, zorder=-1)
#    else:
    ax.plot(eTAU[:,0], eTAU[:,1], color = '#130789', marker='.', linestyle='none', markersize=0.7, zorder=-1)
        
    
    counts1, ybins1, xbins1 = np.histogram2d(eTAU[:,1], eTAU[:,0], bins=80)
    extent = [xbins1.min(), xbins1.max(), ybins1.min(), ybins1.max()]
    levels = np.arange(100, upCL, 10)
    
#    if scale == 2:
#        cf = ax.contourf(counts1, levels, linewidths = 1, cmap='gist_gray', extent = extent)
#    else:
    cf = ax.contourf(counts1, levels, linewidths = 1, cmap='plasma', extent = extent)
    
    layout()

 
#########################
## -- image read-in -- ##
#########################
allfiles = [f for f in os.listdir(directory) if os.path.isfile(os.path.join(directory, f))]

for n in range(0,len(allfiles)):     
    print ""
    print "wait, I'm reading stack ", n, "..."
    
    st = allfiles[n]
    stop_dateC = st.find("_DC-TCSPC")
#    stop_dateC = st.find("_TDC")
    if stop_dateC < 0:
        dateCells = st[0:-4]
    else:
        dateCells = st[9:stop_dateC]

        
    if substring[AA[0]][0] == "none":
        uStrich = ""
    else: uStrich = "_"

    crt = ""
    for ix in range(len(AA)):
        start = st.find(substring[AA[ix]][0]) + substring[AA[ix]][1]
        stop = start + substring[AA[ix]][2]
        #print st.find(substring[AA[ix]][0]), start, stop, st[start:stop], 
        crt +=  "_" + st[start:stop]
        
    
    print "     ", dateCells + crt
    print ""

    img = Image.open(directory + '/' + allfiles[n])
    shape = img.convert('F')
    shape = np.asarray(shape)
    shape = shape.shape
    
    ## -- without mask -- ##
    mask = np.ones(shape)
    
    ## -- predefined IJ-mask -- ##
    ##imgM = Image.open("conva_800nm_P0_BB30_woDC_TDC_maskIJ.tif")
    ##mask = imgM.convert('F')
    ##mask = np.asarray(mask)
    
    signal = []
    signalG = []
    meanG = []
    mean = []
    for k in range(0,timesteps):
        img.seek(k)
        data = img.convert('F')
        signal.append(np.array(data))
        g = 1000*(gaussian_filter(data, sigma=sigma)*mask)
        signalG.append(np.array(g))
        meanG.append(np.average(signalG[k]))
     
    S = np.array(signal)
    S = np.sum(S, axis=0)

    
    sumFile = baseFolder + '/' + str(folder) + '_unblurredSUM/'  
    if not os.path.exists(sumFile):      
        os.makedirs(sumFile)
        
    img00 = Image.fromarray(S)
    img00.save(sumFile + dateCells + crt + uStrich + 'unblurSUM.tif')

   
    N = np.array(signalG[0:offset])         # average of first 10 images in stack as offset --> subtracted
#    N = 0
    N = np.average(N)
    N = np.ones(shape)*N
    
    datalist = (np.array(signalG)-N)*np.greater(np.array(signalG)-N,0)*np.greater(S, thresh)    #subtracts noise & negative values = 0 & thresholds
  
    
    #############################################
    ## -- sampling time and used datapoints -- ##
    #############################################
    dt = 12.24E-9/timesteps
    t = []
    for k in range(0, timesteps):
        t.append(k*dt)
    
    A = []
    for k in range(meanG.index(max(meanG)), timesteps):
        A.append(datalist[k])
    
    
    ##########################
    ## -- phasor approach -- ##
    ###########################
    Re = []
    Im = []
    TAU = []
    for k in range(len(A)):
        Re.append(A[k]*math.cos(w*t[k]))
        Im.append(A[k]*math.sin(w*t[k]))
    
    DFTr = (sum(Re)/sum(A))*np.greater(sum(Re),0)
    DFTi = (sum(Im)/sum(A))*np.greater(sum(Im),0)
    TAU = (1/w)*(DFTi/DFTr)*1E12                            # lifetime in [ps]
    
    
    #####################
    ## -- tau image -- ##       --> tau in ps
    #####################
#    upper = 15000.0              # upper border of tau
#    lower = 10.0                # lower border of tau
    tau = TAU#*(np.less(TAU,upper)*np.greater(TAU,lower)*mask)
        
    analyFile = baseFolder + '/' + str(folder) + '_analy_sig' + str(sigma) + '-off' + str(offset) + '-th' + str(thresh)

    tauFile = analyFile + '/tauImages/'   
    if not os.path.exists(tauFile):      
        os.makedirs(tauFile)
        
    img1 = Image.fromarray(tau)                                             #tauImage
    img1.save(tauFile + dateCells + crt + uStrich + tauName + '.tif')
    
    
    #######################
    ## -- phasor plot -- ##
    #######################
    RE = DFTr#*(np.less(TAU,upper)*np.greater(TAU,lower)*mask)
    IM = DFTi#*(np.less(TAU,upper)*np.greater(TAU,lower)*mask)
    
    realFile =  analyFile + '/real/'
    if not os.path.exists(realFile):      
        os.makedirs(realFile)  

    real = Image.fromarray(RE*tausi)         # real part image
    real.save(realFile + dateCells + crt + uStrich + realName + '.tif')
    
    
    imagFile =  analyFile + '/imag/'
    if not os.path.exists(imagFile):      
        os.makedirs(imagFile)  

    imag = Image.fromarray(IM*tausi)         # imag part image
    imag.save(imagFile + dateCells + crt + uStrich + imagName + '.tif')

    
    eTAU = []                           # removes zeros from matrix & forms matrix to 1D
    for y in range (len(RE)):
        for x in range (len(RE[0])):
            if RE[y][x] != 0 and IM[y][x] != 0 and np.isnan(TAU[y][x]) == False:
                eTAU.append((RE[y][x], IM[y][x], x, y, tau[y][x]))
            else: pass
    
    eTAU = np.asarray(eTAU)
    
        
    ### -- contoured 2d histogram -- ###
    root4=tk.Tk()
    
    fig = Figure(figsize=(5,3))
    ax=fig.add_axes([0,0,1,1])

    
    v = tk.IntVar()
    v.set(1)
    
    options = [
        ("NAD(P)H",1),
        ("NAD(P)H with enzyms",2),
        ("FRET (CerT-NL)",3),
        ("FRET (TN-XXL)",4),
        ("tau 0-20ns",5),
        ("no scale",6)
        ]
    
    def ShowChoice():
        global scale
        scale = v.get()
        print scale
        
    def close():
        root4.destroy()

    if n == 0:   
        tk.Label(root4, text = "Tipp contour levels in phasorPlot").grid(row=0, column=0, columnspan=4, sticky=tk.W, pady=4)
        
        tk.Label(root4, text = "lower level (e.g. 0): ").grid(row=1, column=0, sticky=tk.W, pady=4)
        e2 = tk.Entry(root4, width = 10)
        e2.grid(row=1, column=2)
        
        tk.Label(root4, text = "upper level (e.g. 500): ").grid(row=2, column=0, sticky=tk.W, pady=4)
        e = tk.Entry(root4, width = 10)
        e.grid(row=2, column=2)
            
        tk.Radiobutton(root4, text=options[0][0], variable=v, command=ShowChoice, value=options[0][1]).grid(row = 3, column = 0)
        tk.Radiobutton(root4, text=options[1][0], variable=v, command=ShowChoice, value=options[1][1]).grid(row = 3, column = 1)
        tk.Radiobutton(root4, text=options[2][0], variable=v, command=ShowChoice, value=options[2][1]).grid(row = 4, column = 0)
        tk.Radiobutton(root4, text=options[3][0], variable=v, command=ShowChoice, value=options[3][1]).grid(row = 4, column = 1)
        tk.Radiobutton(root4, text=options[4][0], variable=v, command=ShowChoice, value=options[4][1]).grid(row = 5, column = 0)
        tk.Radiobutton(root4, text=options[5][0], variable=v, command=ShowChoice, value=options[5][1]).grid(row = 5, column = 1)
        
        tk.Label(root4, text = "Select your preferred plot type:").grid(row=6, column=0, columnspan=5, sticky=tk.W, pady=5)
        
        plotbutton=tk.Button(master=root4, text="contour", command=contour)
        plotbutton.grid(row=7, column=1)
        
        plotbutton=tk.Button(master=root4, text="dots", command=dots)
        plotbutton.grid(row=7, column=2)
        
        OKbutton=tk.Button(master=root4, text="OK", fg="red", command=root4.destroy)
        OKbutton.grid(row=7, column=32)
        
        tk.mainloop()
    
    else:
        contour() or dots()
        close()
    
    fig.gca().set_aspect('equal', adjustable='box')         # scales plot axis
    
    if contour == True:
        fig.colorbar(cf, ax=ax, shrink = 0.8)
    else: pass
        
    plotFile = analyFile + '/phasorPlots_enzyLUT/'  
    if not os.path.exists(plotFile):      
        os.makedirs(plotFile)
    
#    ax.legend(bbox_to_anchor=(0,1.02,1,0.2), loc="lower left", mode="expand", borderaxespad=0, ncol=3, numpoints=1, scatterpoints = 1)
    fig.savefig(plotFile  + dateCells + crt + uStrich + 'phasorPlot.png', dpi = 300, bbox_inches='tight')#, transparent=True)
    
    img.close()

print ""
print "Finished!!"
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