# -*- coding: utf-8 -*-
"""
Created on Mon Jun 25 17:45:50 2012
This file is part of SLOTH - stick/like object tracking in high-resolution.
Copyright (C) 2012 Monika Kauer
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
@author: Monika Kauer
"""
from sloth import image_processing as ip
from sloth import vectorial
from sloth import data_reader
from sloth import image_analyser_defs as iad
import pylab
import array
import numpy as np
from scipy import stats, sqrt
[docs]def show_movie(filename,fps=0.1, start=0):
"""dispays nd2 movie from start to end"""
image_file=ip.MyImageFile(filename, dual_color=True)
image = image_file.get_frame(0)
f=pylab.figure()
pylab.ion()
end=image_file.number_frames
m=pylab.imshow(image,interpolation='nearest', cmap="gray")
pylab.draw()
for frame in range(start, end):
image = image_file.get_frame(frame)
m.set_data(image)
pylab.draw()
f.canvas.flush_events()
print frame
#time.sleep(1)
[docs]def make_kymo(data,filename_movie, framerate, twocolor):
"""produces a kymograph from tip data and movie"""
image_file=ip.MyImageFile(filename_movie, dual_color=twocolor)
tip1x=data[0]
tip1y=data[1]
tip2x=data[2]
tip2y=data[3]
length1=data[4]
length2=data[5]
kymo=[]
if tip1x==[] or tip2x==[] or tip1y==[] or tip2y==[]:
return 0,0,[],[]
l1max=int(max(length1)) #calculate maximal length
l2max=int(max(length2))
shift=20 #how far is MT from borders
midpoint=(vectorial.Vector(tip1x[0],tip1y[0])+vectorial.Vector(tip2x[0],tip2y[0]))*0.5
l0=abs(vectorial.Vector(tip1x[0],tip1y[0])-vectorial.Vector(tip2x[0],tip2y[0]))
for frame in range(0,max([len(length1),len(length2)])):
image = image_file.get_frame(frame)
linear_image = array.array("H", image.tostring())
direction1=vectorial.Vector(tip1x[frame],tip1y[frame])-midpoint
profile1=ip.end_profile2(linear_image,image.shape[0],midpoint,direction1.normalize(),l1max+shift)
direction2=vectorial.Vector(tip2x[frame],tip2y[frame])-midpoint
profile2=ip.end_profile2(linear_image,image.shape[0],midpoint,direction2.normalize(),l2max+shift+int(l0/2))
profile=profile1[::-1]+profile2
kymo.append(profile)
#post processing to get it to image format
if len(kymo)>0:
pylab.imshow(kymo, cmap="gray", interpolation="nearest")
len1=map(lambda x: -x+shift+l1max,length1)
len2=map(lambda x: x+shift+l1max,length2)
pylab.hold(True)
pylab.plot(len1,range(len(length1)),'-', color='red')
pylab.plot(len2,range(len(length2)),'-', color='blue')
[docs]def growth_speed(length1,framerate, linreg=False, start=0, end=10000, output=True):
'''input is length data as read in read data'''
fit1=[]
a_1=0
stderr1=0
#create time in ms
time1=np.arange(0,len(length1)*framerate,framerate)
if start or end:
time1=time1[start:end]
length1=length1[start:end]
if linreg:
(a_1,b_1,r1,p1,stderr1)=stats.linregress(time1,length1)
#correct standard error, wrong definition in stats package
stderr1=sqrt(1./(len(time1)-2)*a_1**2*(1-r1**2)/r1**2)
print(' growth velocity length1: %.2f +-%.2f um/min \n ' % (a_1*60,stderr1*60))
for i in time1:
fit1.append(a_1*i+b_1)
if output:
fig=pylab.figure(103,figsize=(8,5))
pylab.ion()
pylab.plot(time1/framerate,length1,'-', label='length1')
if linreg:
pylab.plot(time1/framerate,fit1)
#pylab.legend()
pylab.xlabel('index of data')
pylab.ylabel('length in nm')
pylab.title('Current velocity: %.2f +- %.2f um/min'%(a_1*60,stderr1*60))
pylab.draw()
fig.canvas.flush_events()
#this is velocity in um/min
a_1=a_1*60
stderr1=stderr1*60
return a_1,stderr1
