In [1]:

    

import nibabel as nb
import os
import numpy as np
import scipy.io as sio
import scipy.optimize
from Tkinter import Tk
from tkFileDialog import askdirectory
#import libtiff 
import matplotlib.pyplot as plt
from Tkinter import Tk
from tkFileDialog import askopenfilename
#import cv2
%matplotlib inline


    

In [2]:

    

# from http://stackoverflow.com/questions/3579568/choosing-a-file-in-python-with-simple-dialog
from Tkinter import Tk
from tkFileDialog import askopenfilename

Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
filename = askopenfilename() # show an "Open" dialog box and return the path to the selected file
print(filename)
Ua=sio.loadmat(filename)
Tvid=Ua['Time']
Tvid.shape


    

    




/media/test7/975/combo_2015-07-01-155610-0000Time.mat






    
Out[2]:





(1, 7607)

In [3]:

    

# from http://stackoverflow.com/questions/3579568/choosing-a-file-in-python-with-simple-dialog

Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
filename2 = askopenfilename() # show an "Open" dialog box and return the path to the selected file
print(filename2)
img1 = nb.load(filename2)
data = img1.get_data()
S=data.shape
S


    

    




/media/test7/975/combo_2015-07-01-155610-0000head.nii






    
Out[3]:





(12, 25, 7607, 1)

In [4]:

    

# Find end of onset of light and begining of offset (to align to behavior)


    

In [5]:

    

M=np.mean(np.mean(data,0),0)
M=M-np.min(M)
Mav=M.mean()
M=M/Mav


    

In [6]:

    

M.shape


    

    
Out[6]:





(7607, 1)

In [7]:

    

plt.plot(M)


    

    
Out[7]:





[<matplotlib.lines.Line2D at 0x7f29ecadf3d0>]






    

In [8]:

    

liston=[i for i in range(len(M)) if M[i]>0.7]
#liston[0]
max(liston)


    

    
Out[8]:





7139

In [9]:

    

def model(x,a,b,c,d):
    if x<a:
        return b
    elif x<c:
        return b+(x-a)*d
    else:
        return (c-a)*d+b


    

In [10]:

    

Ms=M[range(liston[0]-8,liston[0]+8)]-M[liston[0]-8]


    

In [11]:

    

def Sq(X):
    return sum([(model(i,X[0],X[1],X[2],X[3])-Ms[i])**2 for i in range(len(Ms))])


    

In [12]:

    

liston[0]-8


    

    
Out[12]:





976

In [13]:

    

res = scipy.optimize.minimize(Sq,x0=[7.2,0.00,8.2,1.2])


    

In [14]:

    

ON=liston[0]-8+res.x[2]
print(ON)


    

    




984.2

In [15]:

    

ONint=np.int(np.ceil(ON))
print(ONint)


    

    




985

In [16]:

    

plt.plot(np.squeeze(Ms),'+')
plt.plot(np.arange(0,len(Ms),0.1),[model(i,res.x[0],res.x[1],res.x[2],res.x[3]) for i in np.arange(0,len(Ms),0.1)])
plt.show()


    

In [17]:

    

len(M)


    

    
Out[17]:





7607

In [18]:

    

Ms=M[range(max(liston)-6,max(liston)+6)]


    

In [19]:

    

def Sq(X):
    return sum([(model(i,X[0],X[1],X[2],X[3])-Ms[i])**2 for i in range(len(Ms))])


    

In [20]:

    

res = scipy.optimize.minimize(Sq,x0=[5.8,1.2,7.2,-1])


    

In [21]:

    

OFF=liston[len(liston)-1]-6+res.x[0]
#OFF=liston[len(liston)-1]
print(OFF)
OFFint=np.int(np.floor(OFF))
print(OFFint)


    

    




7138.9182233
7138

In [22]:

    

plt.plot(np.squeeze(Ms),'+')
plt.plot(np.arange(0,len(Ms),0.1),[model(i,res.x[0],res.x[1],res.x[2],res.x[3]) for i in np.arange(0,len(Ms),0.1)])
plt.show()


    

In [23]:

    

print(ONint+1)
print(OFFint+1)
print(ON)
print(OFF)
print(OFFint-ONint)
print(OFF-ON)


    

    




986
7139
984.2
7138.9182233
6153
6154.7182233

In [24]:

    

Tvid=Tvid.T


    

In [25]:

    

TimeOn=[Tvid[i] for i in range(ONint,(OFFint+1))]


    

In [26]:

    

Tinit=(ON-(ONint-1))*(Tvid[ONint]-Tvid[ONint-1])+Tvid[ONint-1]


    

In [27]:

    

Toff=(OFF-OFFint)*(Tvid[OFFint+1]-Tvid[OFFint])+Tvid[OFFint]


    

In [28]:

    

Toff-Tinit


    

    
Out[28]:





array([ 62230.88310926])

In [31]:

    

np.mean((Tvid[100:(len(Tvid))])-np.array(Tvid[99:(len(Tvid)-1)]))


    

    
Out[31]:





10.097552684551708

In [32]:

    

np.std((Tvid[100:(len(Tvid))])-np.array(Tvid[99:(len(Tvid)-1)]))


    

    
Out[32]:





2.0163494558371267

In [33]:

    

#Ttest=np.array(Tvid.T[2:(len(Tvid.T))])-np.array(Tvid.T[1:(len(Tvid.T)-1)])
#plt.plot(Ttest)
#plt.axis([0,100,19.5,150])


    

In [34]:

    

TimeOnFinal=(np.array(TimeOn)-Tinit)/1000


    

In [35]:

    

np.max(TimeOnFinal)


    

    
Out[35]:





62.221702034505221

In [36]:

    

Fileout="".join(filename[i] for i in range(len(filename)-4))


    

In [37]:

    

OutFilename=Fileout+'OnVid.mat'


    

In [38]:

    

OutFilename


    

    
Out[38]:





'/media/test7/975/combo_2015-07-01-155610-0000TimeOnVid.mat'

In [39]:

    

sio.savemat(OutFilename, {'TimeFluoOnVid':TimeOnFinal,'ONint':ONint+1,'OFFint':OFFint+1})


    

In [ ]:

    




    

In [ ]: