import numpy as np
import matplotlib
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
import collections
import scipy 
import scipy.interpolate 
import glob
import csv
from scipy import optimize
from scipy import stats	
from scipy import interpolate
from Tkinter import *
import tkMessageBox
from itertools import repeat
import csv
from matplotlib.backends.backend_pdf import PdfPages

#set up the GUI labels
master = Tk()
master.wm_title('ELISA Control Charts')
Label(master, text="Tag for Included (control)").grid(row=0)
Label(master, text="Tag for Excluded (test)").grid(row=1)
Label(master, text="Row data begins").grid(row=2)
Label(master, text="Column (Conc)").grid(row=3)
Label(master, text="Column (OD)").grid(row=4)
# Create the user entries
e1 = Entry(master)
e2 = Entry(master)
e3 = Entry(master)
e4 = Entry(master)
e5 = Entry(master)
e1.grid(row=0, column=1)
e2.grid(row=1, column=1)
e3.grid(row=2, column=1)
e4.grid(row=3, column=1)
e5.grid(row=4, column=1)

def graphs():
	global fig1
	global fig2
	#set up the figures
	fig1=plt.figure(1)
	fig1.suptitle('Complete Standard Curve', fontsize=14, fontweight='bold')
	ax1=plt.subplot2grid((6,6), (0,0), colspan=4, rowspan=2)

	ax2=plt.subplot2grid((6,6), (2,0), colspan=2)
	ax3=plt.subplot2grid((6,6), (2,2), colspan=2)
	ax4=plt.subplot2grid((6,6), (3,0), colspan=2)
	ax5=plt.subplot2grid((6,6), (3,2), colspan=2)
	ax6=plt.subplot2grid((6,6), (4,0), colspan=2)
	ax7=plt.subplot2grid((6,6), (4,2), colspan=2)
	ax8=plt.subplot2grid((6,6), (5,0), colspan=2)
	ax9=plt.subplot2grid((6,6), (5,2), colspan=2)

	#create empty lists to be filled in the loops
	count=0
	fnames=[]
	y11=[]
	y22=[]
	y33=[]
	y44=[]
	y55=[]
	y66=[]
	y77=[]
	y88=[]
	meanind1=[]
	meanind2=[]
	meanind3=[]
	meanind4=[]
	meanind5=[]
	meanind6=[]
	meanind7=[]
	meanind8=[]
	y1d2mean=[]
	y2d2mean=[]
	y3d2mean=[]
	y4d2mean=[]
	y5d2mean=[]
	y6d2mean=[]
	y7d2mean=[]
	y8d2mean=[]

	fnamese=[]
	counte=0
	y11e=[]
	y22e=[]
	y33e=[]
	y44e=[]
	y55e=[]
	y66e=[]
	y77e=[]
	y88e=[]
	meanind1e=[]
	meanind2e=[]
	meanind3e=[]
	meanind4e=[]
	meanind5e=[]
	meanind6e=[]
	meanind7e=[]
	meanind8e=[]

	#convert the userinputs to integers
	userinput1=e1.get()
	userinput2=e2.get()
	userinput3=e3.get()
	userinput3=int(userinput3)
	userinput4=e4.get()
	userinput4=int(userinput4)
	userinput5=e5.get()
	userinput5=int(userinput5)
	#standards loop
	for files in glob.glob("*%s.csv"%(userinput1)) :
		count=count+1
		fnames.append(files)
		array=np.genfromtxt(files, delimiter=',', skip_header=userinput3-1, usecols=(userinput4-1,userinput5-1))

		#slice the array
		array1=array[0:3]
		# take out the concentration values
		conc1=array1[:,0]
		#fill in the blank values
		conc1 = conc1[np.logical_not(np.isnan(conc1))]
		inds1=np.where(np.isnan(array1))
		array1[inds1]=np.take(conc1, inds1[1])
		#take the mean of the ODs
		mean1=np.mean(array1, axis=0)
		#pull out the values for the main graph
		x1=array1[:,0]
		y1=array1[:,1]	
		#append the values into the empty list
		y11.append(y1)
		meanind1.append(mean1)

		array2=array[3:6]
		conc2=array2[:,0]
		conc2 = conc2[np.logical_not(np.isnan(conc2))]
		inds2=np.where(np.isnan(array2))
		array2[inds2]=np.take(conc2, inds2[1])
		mean2=np.mean(array2, axis=0)
		x2=array2[:,0]
		y2=array2[:,1]	
		y22.append(y2)
		meanind2.append(mean2)

		array3=array[6:9]
		conc3=array3[:,0]
		conc3 = conc3[np.logical_not(np.isnan(conc3))]
		inds3=np.where(np.isnan(array3))
		array3[inds3]=np.take(conc3, inds3[1])
		mean3=np.mean(array3, axis=0)
		x3=array3[:,0]
		y3=array3[:,1]
		y33.append(y3)
		meanind3.append(mean3)

		array4=array[9:12]
		conc4=array4[:,0]
		conc4 = conc4[np.logical_not(np.isnan(conc4))]
		inds4=np.where(np.isnan(array4))
		array4[inds4]=np.take(conc4, inds4[1])
		mean4=np.mean(array4, axis=0)
		x4=array4[:,0]
		y4=array4[:,1]
		y44.append(y4)
		meanind4.append(mean4)
		
		array5=array[12:15]
		conc5=array5[:,0]
		conc5 = conc5[np.logical_not(np.isnan(conc5))]
		inds5=np.where(np.isnan(array5))
		array5[inds5]=np.take(conc5, inds5[1])
		mean5=np.mean(array5, axis=0)
		x5=array5[:,0]
		y5=array5[:,1]
		y55.append(y5)
		meanind5.append(mean5)

		array6=array[15:18]
		conc6=array6[:,0]
		conc6 = conc6[np.logical_not(np.isnan(conc6))]
		inds6=np.where(np.isnan(array6))
		array6[inds6]=np.take(conc6, inds6[1])
		mean6=np.mean(array6, axis=0)
		x6=array6[:,0]
		y6=array6[:,1]
		y66.append(y6)
		meanind6.append(mean6)

		array7=array[18:21]
		conc7=array7[:,0]
		conc7 = conc7[np.logical_not(np.isnan(conc7))]
		inds7=np.where(np.isnan(array7))
		array7[inds7]=np.take(conc7, inds7[1])
		mean7=np.mean(array7, axis=0)
		x7=array7[:,0]
		y7=array7[:,1]
		y77.append(y7)
		meanind7.append(mean7)
		
		array8=array[21:24]
		conc8=array8[:,0]
		conc8 = conc8[np.logical_not(np.isnan(conc8))]
		inds8=np.where(np.isnan(array8))
		array8[inds8]=np.take(conc8, inds8[1])
		mean8=np.mean(array8, axis=0)
		x8=array8[:,0]
		y8=array8[:,1]
		y88.append(y8)
		meanind8.append(mean8)

		x=np.concatenate((x1, x2, x3, x4, x5, x6, x7, x8), axis=0)
		y=np.concatenate((y1, y2, y3, y4, y5, y6, y7, y8), axis=0)
		ax1.plot(x,y, 'ko', markersize=5)

	# test loop
	if userinput2=='none':
		print 'no test group'
	else:
		for files in glob.glob("*%s.csv"%(userinput2)) :
			counte=counte+1
			fnamese.append(files)
			arraye=np.genfromtxt(files, delimiter=',', skip_header=7, usecols=(1,4))

			array1e=arraye[0:3]
			conc1e=array1e[:,0]
			conc1e = conc1e[np.logical_not(np.isnan(conc1e))]
			inds1e=np.where(np.isnan(array1e))
			array1e[inds1e]=np.take(conc1e, inds1e[1])
			mean1e=np.mean(array1e, axis=0)
			x1e=array1e[:,0]
			y1e=array1e[:,1]	
			y11e.append(y1e)
			meanind1e.append(mean1e)

			array2e=arraye[3:6]
			conc2e=array2e[:,0]
			conc2e = conc2e[np.logical_not(np.isnan(conc2e))]
			inds2e=np.where(np.isnan(array2e))
			array2e[inds2e]=np.take(conc2e, inds2e[1])
			mean2e=np.mean(array2e, axis=0)
			x2e=array2e[:,0]
			y2e=array2e[:,1]	
			y22e.append(y2e)
			meanind2e.append(mean2e)

			array3e=arraye[6:9]
			conc3e=array3e[:,0]
			conc3e = conc3e[np.logical_not(np.isnan(conc3e))]
			inds3e=np.where(np.isnan(array3e))
			array3e[inds3e]=np.take(conc3e, inds3e[1])
			mean3e=np.mean(array3e, axis=0)
			x3e=array3e[:,0]
			y3e=array3e[:,1]	
			y33e.append(y3e)
			meanind3e.append(mean3e)

			array4e=arraye[9:12]
			conc4e=array4e[:,0]
			conc4e = conc4e[np.logical_not(np.isnan(conc4e))]
			inds4e=np.where(np.isnan(array4e))
			array4e[inds4e]=np.take(conc4e, inds4e[1])
			mean4e=np.mean(array4e, axis=0)
			x4e=array4e[:,0]
			y4e=array4e[:,1]	
			y44e.append(y4e)
			meanind4e.append(mean4e)

			array5e=arraye[12:15]
			conc5e=array5e[:,0]
			conc5e = conc5e[np.logical_not(np.isnan(conc5e))]
			inds5e=np.where(np.isnan(array5e))
			array5e[inds5e]=np.take(conc5e, inds5e[1])
			mean5e=np.mean(array5e, axis=0)
			x5e=array5e[:,0]
			y5e=array5e[:,1]	
			y55e.append(y5e)
			meanind5e.append(mean5e)

			array6e=arraye[15:18]
			conc6e=array6e[:,0]
			conc6e = conc6e[np.logical_not(np.isnan(conc6e))]
			inds6e=np.where(np.isnan(array6e))
			array6e[inds6e]=np.take(conc6e, inds6e[1])
			mean6e=np.mean(array6e, axis=0)
			x6e=array6e[:,0]
			y6e=array6e[:,1]	
			y66e.append(y6e)
			meanind6e.append(mean6e)

			array7e=arraye[18:21]
			conc7e=array7e[:,0]
			conc7e = conc7e[np.logical_not(np.isnan(conc7e))]
			inds7e=np.where(np.isnan(array7e))
			array7e[inds7e]=np.take(conc7e, inds7e[1])
			mean7e=np.mean(array7e, axis=0)
			x7e=array7e[:,0]
			y7e=array7e[:,1]	
			y77e.append(y7e)
			meanind7e.append(mean7e)

			array8e=arraye[21:24]
			conc8e=array8e[:,0]
			conc8e = conc8e[np.logical_not(np.isnan(conc8e))]
			inds8e=np.where(np.isnan(array8e))
			array8e[inds8e]=np.take(conc8e, inds8e[1])
			mean8e=np.mean(array8e, axis=0)
			x8e=array8e[:,0]
			y8e=array8e[:,1]	
			y88e.append(y8e)
			meanind8e.append(mean8e)
			
			x=np.concatenate((x1e, x2e, x3e, x4e, x5e, x6e, x7e, x8e))
			y=np.concatenate((y1e, y2e, y3e, y4e, y5e, y6e, y7e, y8e))
			ax1.plot(x,y, 'mo', markersize=5)

	#format the file names for printing in the terminal, and create a count for the x axis of the control charts
	fnames=[x for item in fnames for x in repeat(item, 3)]
	length=len(fnames)
	xmask1=list(range(length/3))
	labels=[fnames]
	printable=np.array(fnames[0::3])
	printcount=np.array(list(range(len(printable))))
	key=np.column_stack((printcount, printable))
	print 'Standards Key'
	print key

	fnamese=[x for item in fnamese for x in repeat(item, 3)]
	lengthe=len(fnamese)
	xmask1e=list(range(lengthe/3))
	labelse=[fnamese]
	printablee=np.array(fnamese[0::3])
	printcounte=np.array(list(range(len(printablee))))
	keye=np.column_stack((printcounte, printablee))
	print 'Test Key'
	print keye

	#take the final means, then plot everything
	mean1tot=np.mean(y11)
	y11=np.array(y11)
	SD1=np.std(y11)
	y11=y11.reshape(length,)
	meanind1=np.array(meanind1)
	meanind1=meanind1[ :,1]
	ax2.plot(xmask1, meanind1, 'ko', markersize=7)
	ax2.plot(xmask1, meanind1, 'k')
	ax2.axhline(y=mean1tot)
	ax2.axhline(y=(mean1tot+SD1*2), color='g', linewidth=2)
	ax2.axhline(y=(mean1tot-SD1*2), color='g', linewidth=2)
	ax2.axhline(y=(mean1tot+SD1*3), color='r', linewidth=2)
	ax2.axhline(y=(mean1tot-SD1*3), color='r', linewidth=2)

	mean1tote=np.mean(y11e)
	y11e=np.array(y11e)
	y11e=y11e.reshape(lengthe,)
	meanind1e=np.array(meanind1e)

	if userinput2 =='none':
		pass
	else:
		ax2.plot(xmask1e, meanind1e[ :,1], 'mo')
		ax2.plot(xmask1e, meanind1e[ :,1], 'm')

	mean2tot=np.mean(y22)
	y22=np.array(y22)
	SD2=np.std(y22)
	y22=y22.reshape(length,)
	meanind2=np.array(meanind2)
	meanind2=meanind2[ :,1]
	ax3.plot(xmask1, meanind2, 'ko', markersize=7)
	ax3.plot(xmask1, meanind2, 'k')
	ax3.axhline(y=mean2tot)
	ax3.axhline(y=(mean2tot+SD2*2), color='g', linewidth=2)
	ax3.axhline(y=(mean2tot-SD2*2), color='g', linewidth=2)
	ax3.axhline(y=(mean2tot+SD2*3), color='r', linewidth=2)
	ax3.axhline(y=(mean2tot-SD2*3), color='r', linewidth=2)

	mean2tote=np.mean(y22e)
	y22e=np.array(y22e)
	y22e=y22e.reshape(lengthe,)
	meanind2e=np.array(meanind2e)
	if userinput2 =='none':
		pass
	else:
		ax3.plot(xmask1e, meanind2e[ :,1], 'm')
		ax3.plot(xmask1e, meanind2e[ :,1], 'mo')

	mean3tot=np.mean(y33)
	y33=np.array(y33)
	SD3=np.std(y33)
	y33=y33.reshape(length,)
	meanind3=np.array(meanind3)
	meanind3=meanind3[ :,1]
	ax4.plot(xmask1, meanind3, 'ko', markersize=7)
	ax4.plot(xmask1, meanind3, 'k', linewidth=2)
	ax4.axhline(y=mean3tot)
	ax4.axhline(y=(mean3tot+SD3*2), color='g', linewidth=2)
	ax4.axhline(y=(mean3tot-SD3*2), color='g', linewidth=2)
	ax4.axhline(y=(mean3tot+SD3*3), color='r', linewidth=2)
	ax4.axhline(y=(mean3tot-SD3*3), color='r', linewidth=2)

	mean3tote=np.mean(y33e)
	y33e=np.array(y33e)
	y33e=y33e.reshape(lengthe,)
	meanind3e=np.array(meanind3e)
	if userinput2 =='none':
		pass
	else:
		ax4.plot(xmask1e, meanind3e[ :,1], 'mo')
		ax4.plot(xmask1e, meanind3e[ :,1], 'm')

	mean4tot=np.mean(y44)
	y44=np.array(y44)
	SD4=np.std(y44)
	y44=y44.reshape(length,)
	meanind4=np.array(meanind4)
	meanind4=meanind4[ :,1]
	ax5.plot(xmask1, meanind4, 'ko', markersize=7)
	ax5.plot(xmask1, meanind4, 'k', linewidth=2)
	ax5.axhline(y=mean4tot)
	ax5.axhline(y=(mean4tot+SD4*2), color='g', linewidth=2)
	ax5.axhline(y=(mean4tot-SD4*2), color='g', linewidth=2)
	ax5.axhline(y=(mean4tot+SD4*3), color='r', linewidth=2)
	ax5.axhline(y=(mean4tot-SD4*3), color='r', linewidth=2)

	mean4tote=np.mean(y44e)
	y44e=np.array(y44e)
	y44e=y44e.reshape(lengthe,)
	meanind4e=np.array(meanind4e)
	if userinput2 =='none':
		pass
	else:
		ax5.plot(xmask1e, meanind4e[ :,1], 'mo')
		ax5.plot(xmask1e, meanind4e[ :,1], 'm')

	mean5tot=np.mean(y55)
	y55=np.array(y55)
	SD5=np.std(y55)
	y55=y55.reshape(length,)
	meanind5=np.array(meanind5)
	meanind5=meanind5[ :,1]
	ax6.plot(xmask1, meanind5, 'ko', markersize=7)
	ax6.plot(xmask1, meanind5, 'k')
	ax6.axhline(y=mean5tot)
	ax6.axhline(y=(mean5tot+SD5*2), color='g', linewidth=2)
	ax6.axhline(y=(mean5tot-SD5*2), color='g', linewidth=2)
	ax6.axhline(y=(mean5tot+SD5*3), color='r', linewidth=2)
	ax6.axhline(y=(mean5tot-SD5*3), color='r', linewidth=2)

	mean5tote=np.mean(y55e)
	y55e=np.array(y55e)
	y55e=y55e.reshape(lengthe,)
	meanind5e=np.array(meanind5e)
	if userinput2 =='none':
		pass
	else:
		ax6.plot(xmask1e, meanind5e[ :,1], 'mo')
		ax6.plot(xmask1e, meanind5e[ :,1], 'm')

	mean6tot=np.mean(y66)
	y66=np.array(y66)
	SD6=np.std(y66)
	y66=y66.reshape(length,)
	meanind6=np.array(meanind6)
	meanind6=meanind6[ :,1]
	ax7.plot(xmask1, meanind6, 'ko', markersize=7)
	ax7.plot(xmask1, meanind6, 'k')
	ax7.axhline(y=mean6tot)
	ax7.axhline(y=(mean6tot+SD6*2), color='g', linewidth=2)
	ax7.axhline(y=(mean6tot-SD6*2), color='g', linewidth=2)
	ax7.axhline(y=(mean6tot+SD6*3), color='r', linewidth=2)
	ax7.axhline(y=(mean6tot-SD6*3), color='r', linewidth=2)

	mean6tote=np.mean(y66e)
	y66e=np.array(y66e)
	y66e=y66e.reshape(lengthe,)
	meanind6e=np.array(meanind6e)
	if userinput2 =='none':
		pass
	else:
		ax7.plot(xmask1e, meanind6e[ :,1], 'mo')
		ax7.plot(xmask1e, meanind6e[ :,1], 'm')

	mean7tot=np.mean(y77)
	y77=np.array(y77)
	SD7=np.std(y77)
	y77=y77.reshape(length,)
	meanind7=np.array(meanind7)
	meanind7=meanind7[ :,1]
	ax8.plot(xmask1, meanind7, 'ko', markersize=7)
	ax8.plot(xmask1, meanind7, 'k')
	ax8.axhline(y=mean7tot)
	ax8.axhline(y=(mean7tot+SD7*2), color='g', linewidth=2)
	ax8.axhline(y=(mean7tot-SD7*2), color='g', linewidth=2)
	ax8.axhline(y=(mean7tot+SD7*3), color='r', linewidth=2)
	ax8.axhline(y=(mean7tot-SD7*3), color='r', linewidth=2)

	mean7tote=np.mean(y77e)
	y77e=np.array(y77e)
	y77e=y77e.reshape(lengthe,)
	meanind7e=np.array(meanind7e)
	if userinput2 =='none':
		pass
	else:
		ax8.plot(xmask1e, meanind7e[ :,1], 'mo')
		ax8.plot(xmask1e, meanind7e[ :,1], 'm')

	mean8tot=np.mean(y88)
	y88=np.array(y88)
	SD8=np.std(y88)
	y88=y88.reshape(length,)
	meanind8=np.array(meanind8)
	meanind8=meanind8[ :,1]
	ax9.plot(xmask1, meanind8, 'ko', markersize=7)
	ax9.plot(xmask1, meanind8, 'k')
	ax9.axhline(y=mean8tot)
	ax9.axhline(y=(mean8tot+SD8*2), color='g', linewidth=2)
	ax9.axhline(y=(mean8tot-SD8*2), color='g', linewidth=2)
	ax9.axhline(y=(mean8tot+SD8*3), color='r', linewidth=2)
	ax9.axhline(y=(mean8tot-SD8*3), color='r', linewidth=2)

	mean8tote=np.mean(y88e)
	y88e=np.array(y88e)
	y88e=y88e.reshape(lengthe,)
	meanind8e=np.array(meanind8e)
	if userinput2 =='none':
		pass
	else:
		ax9.plot(xmask1e, meanind8e[ :,1], 'mo')
		ax9.plot(xmask1e, meanind8e[ :,1], 'm')

	ax1.set_xlabel('Optical Density')
	ax1.set_ylabel('OD')
	ax2.set_ylabel('OD')
	ax4.set_ylabel('OD')
	ax6.set_ylabel('OD')
	ax8.set_ylabel('OD')
	ax2.set_xlabel('%s ug/mL' %conc1)
	ax3.set_xlabel('%s ug/mL'%conc2)
	ax4.set_xlabel('%s ug/mL'%conc3)
	ax5.set_xlabel('%s ug/mL'%conc4)
	ax6.set_xlabel('%s ug/mL'%conc5)
	ax7.set_xlabel('%s ug/mL'%conc6)
	ax8.set_xlabel('%s ug/mL'%conc7)
	ax9.set_xlabel('%s ug/mL'%conc8)

	out21=[np.where(np.logical_or(meanind1>mean1tot+SD1*2, meanind1<mean1tot-SD1*2))]
	out31=[np.where(np.logical_or(meanind1>mean1tot+SD1*3, meanind1<mean1tot-SD1*3))]
	out21fnames=np.take(printable, out21)
	out31fnames=np.take(printable, out31)
	if userinput2 =='none':
		pass
	else:
		out21e=[np.where(np.logical_or(meanind1e[ :,1]>mean1tot+SD2*2, meanind1e[ :,1]<mean1tot-SD1*2))]
		out21fnamese=np.take(printablee, out21e)
		print "Test set outside 2SD at %s: \n %s"%(conc1, out21fnamese)
		out31e=[np.where(np.logical_or(meanind1e[ :,1]>mean1tot+SD2*3, meanind1e[ :,1]<mean1tot-SD1*3))]
		out31fnamese=np.take(printablee, out31e)
		print "Test set outside 3SD at %s: \n %s"%(conc1, out31fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc1, out21fnames)	
	print "Control set outside 3SD at %s: \n %s"%(conc1, out31fnames)

	out22=[np.where(np.logical_or(meanind2>mean2tot+SD2*2, meanind2<mean2tot-SD2*2))]
	out22fnames=np.take(printable, out22)
	out32=[np.where(np.logical_or(meanind2>mean2tot+SD2*3, meanind2<mean2tot-SD2*3))]
	out32fnames=np.take(printable, out32)
	if userinput2 =='none':
		pass
	else:
		out22e=[np.where(np.logical_or(meanind2e[ :,1]>mean2tot+SD2*2, meanind2e[ :,1]<mean2tot-SD2*2))]
		out22fnamese=np.take(printablee, out22e)
		print "Test set outside 2SD at %s: \n %s"%(conc2, out22fnamese)
		out32e=[np.where(np.logical_or(meanind2e[ :,1]>mean2tot+SD2*3, meanind2e[ :,1]<mean2tot-SD2*3))]
		out32fnamese=np.take(printablee, out32e)
		print "Test set outside 3SD at %s: \n %s"%(conc2, out32fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc2, out22fnames)	
	print "Control set outside 3SD at %s: \n %s"%(conc2, out32fnames)

	out23=[np.where(np.logical_or(meanind3>mean3tot+SD3*2, meanind3<mean3tot-SD3*2))]
	out23fnames=np.take(printable, out23)
	out33=[np.where(np.logical_or(meanind3>mean3tot+SD3*3, meanind3<mean3tot-SD3*3))]
	out33fnames=np.take(printable, out33)
	if userinput2 =='none':
		pass
	else:
		out23e=[np.where(np.logical_or(meanind3e[ :,1]>mean3tot+SD3*2, meanind3e[ :,1]<mean3tot-SD3*2))]
		out23fnamese=np.take(printablee, out23e)
		print "Test set outside 2SD at %s: \n %s"%(conc3, out23fnamese)
		out33e=[np.where(np.logical_or(meanind3e[ :,1]>mean3tot+SD3*3, meanind3e[ :,1]<mean3tot-SD3*3))]
		out33fnamese=np.take(printablee, out33e)
		print "Test set outside 3SD at %s: \n %s"%(conc3, out33fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc3, out23fnames)
	print "Control set outside 3SD at %s: \n %s"%(conc3, out33fnames)

	out24=[np.where(np.logical_or(meanind4>mean4tot+SD4*2, meanind4<mean4tot-SD4*2))]
	out24fnames=np.take(printable, out24)
	out34=[np.where(np.logical_or(meanind4>mean4tot+SD4*3, meanind4<mean4tot-SD4*3))]
	out34fnames=np.take(printable, out34)
	if userinput2 =='none':
		pass
	else:
		out24e=[np.where(np.logical_or(meanind4e[ :,1]>mean4tot+SD4*2, meanind4e[ :,1]<mean4tot-SD4*2))]
		out24fnamese=np.take(printablee, out24e)
		print "Test set outside 2SD at %s: \n %s"%(conc4, out24fnamese)
		out34e=[np.where(np.logical_or(meanind4e[ :,1]>mean4tot+SD4*3, meanind4e[ :,1]<mean4tot-SD4*3))]
		out34fnamese=np.take(printablee, out34e)
		print "Test set outside 3SD at %s: \n %s"%(conc4, out34fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc4, out24fnames)
	print "Control set outside 3SD at %s: \n %s"%(conc4, out34fnames)

	out25=[np.where(np.logical_or(meanind5>mean5tot+SD5*2, meanind5<mean5tot-SD5*2))]
	out25fnames=np.take(printable, out25)
	out35=[np.where(np.logical_or(meanind5>mean5tot+SD5*3, meanind5<mean5tot-SD5*3))]
	out35fnames=np.take(printable, out35)
	if userinput2 =='none':
		pass
	else:
		out25e=[np.where(np.logical_or(meanind5e[ :,1]>mean5tot+SD5*2, meanind5e[ :,1]<mean5tot-SD5*2))]
		out25fnamese=np.take(printablee, out25e)
		print "Test set outside 2SD at %s: \n %s"%(conc5, out25fnamese)
		out35e=[np.where(np.logical_or(meanind5e[ :,1]>mean5tot+SD5*3, meanind5e[ :,1]<mean5tot-SD5*3))]
		out35fnamese=np.take(printablee, out35e)
		print "Test set outside 3SD at %s: \n %s"%(conc5, out35fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc5, out25fnames)
	print "Control set outside 3SD at %s: \n %s"%(conc5, out35fnames)

	out26=[np.where(np.logical_or(meanind6>mean6tot+SD6*2, meanind6<mean6tot-SD6*2))]
	out26fnames=np.take(printable, out26)
	out36=[np.where(np.logical_or(meanind6>mean6tot+SD6*3, meanind6<mean6tot-SD6*3))]
	out36fnames=np.take(printable, out36)
	if userinput2 =='none':
		pass
	else:
		out26e=[np.where(np.logical_or(meanind6e[ :,1]>mean6tot+SD6*2, meanind6e[ :,1]<mean6tot-SD6*2))]
		out26fnamese=np.take(printablee, out26e)
		print "Test set outside 2SD at %s: \n %s"%(conc6, out26fnamese)
		out36e=[np.where(np.logical_or(meanind6e[ :,1]>mean6tot+SD6*3, meanind6e[ :,1]<mean6tot-SD6*3))]
		out36fnamese=np.take(printablee, out36e)
		print "Test set outside 3SD at %s: \n %s"%(conc6, out36fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc6, out26fnames)
	print "Control set outside 3SD at %s: \n %s"%(conc6, out36fnames)

	out27=[np.where(np.logical_or(meanind7>mean7tot+SD7*2, meanind7<mean7tot-SD7*2))]
	out27fnames=np.take(printable, out27)
	out37=[np.where(np.logical_or(meanind7>mean7tot+SD7*3, meanind7<mean7tot-SD7*3))]
	out37fnames=np.take(printable, out37)
	if userinput2 =='none':
		pass
	else:
		out27e=[np.where(np.logical_or(meanind7e[ :,1]>mean7tot+SD7*2, meanind7e[ :,1]<mean7tot-SD7*2))]
		out27fnamese=np.take(printablee, out27e)
		print "Test set outside 2SD at %s: \n %s"%(conc7, out27fnamese)
		out37e=[np.where(np.logical_or(meanind7e[ :,1]>mean7tot+SD7*3, meanind7e[ :,1]<mean7tot-SD7*3))]
		out37fnamese=np.take(printablee, out37e)
		print "Test set outside 3SD at %s: \n %s"%(conc7, out37fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc7, out27fnames)
	print "Control set outside 3SD at %s: \n %s"%(conc7, out37fnames)

	out28=[np.where(np.logical_or(meanind8>mean8tot+SD8*2, meanind8<mean8tot-SD8*2))]
	out28fnames=np.take(printable, out28)
	out38=[np.where(np.logical_or(meanind8>mean8tot+SD8*3, meanind8<mean8tot-SD8*3))]
	out38fnames=np.take(printable, out38)
	if userinput2 =='none':
		pass
	else:
		out28e=[np.where(np.logical_or(meanind8e[ :,1]>mean8tot+SD8*2, meanind8e[ :,1]<mean8tot-SD8*2))]
		out28fnamese=np.take(printablee, out28e)
		print "Test set outside 2SD at %s: \n %s"%(conc8, out28fnamese)
		out38e=[np.where(np.logical_or(meanind8e[ :,1]>mean8tot+SD8*3, meanind8e[ :,1]<mean8tot-SD8*3))]
		out38fnamese=np.take(printablee, out38e)
		print "Test set outside 3SD at %s: \n %s"%(conc8, out38fnamese)
	print "Control set outside 2SD at %s: \n %s"%(conc8, out28fnames)
	print "Control set outside 3SD at %s: \n %s"%(conc8, out38fnames)

	fig1.tight_layout()
	fig1.subplots_adjust(wspace=2.5, hspace=1)
	plt.show()
	fig1.savefig('Control charts')

	#coeffeints of variance
	cv1=(SD1/mean1tot)*100
	cv2=(SD2/mean2tot)*100
	cv3=(SD3/mean3tot)*100
	cv4=(SD4/mean4tot)*100
	cv5=(SD5/mean5tot)*100
	cv6=(SD6/mean6tot)*100
	cv7=(SD7/mean7tot)*100
	cv8=(SD8/mean8tot)*100

	conclist=[conc1, conc2, conc3, conc4, conc5, conc6, conc7, conc8]
	meanlist=[mean1tot, mean2tot,mean3tot,mean4tot,mean5tot,mean6tot,mean7tot,mean8tot]
	sdlist=[SD1,SD2,SD3,SD4,SD5,SD6,SD7,SD8]
	cvlist=[cv1,cv2,cv3,cv4,cv5,cv6,cv7,cv8]

	filename='ELISASTATS.csv'
	header=['Concentration', 'Mean OD', 'SD', 'CV']
	rows=map(None, conclist, meanlist, sdlist, cvlist)
	with open(filename, 'wb') as f:
		writer=csv.writer(f)
		writer.writerow(header)
		for row in rows:
			writer.writerow(row)

def popup():
	tkMessageBox.showinfo(
		"Help",
		"Tag must appear immediately prior to the .csv \n Example: if the included tag is 'good', and test tag is 'test' \n appropriate file naming could be Plate1good.csv and Plate1test.csv \n For more help, see user manual")


Button(master, text='Run', command=graphs).grid(row=5, column=0, sticky=W, pady=4)
Button(master, text='Tags help', command=popup).grid(row=5, column=4, sticky=W, pady=4)

mainloop()