auto_fit_nm = number of nm to fit before the peak maximum, for WLC (if usepoints false)
auto_fit_points = number of points to fit before the peak maximum, for WLC (if usepoints true)
- baseline_clicks = 0: automatic baseline
- 1: decide baseline with a single click and length defined in auto_left_baseline
- 2: let user click points of baseline
+ baseline_clicks = -1: no baseline, f=0 at the contact point (whether hand-picked or automatically found)\r
+ 0: automatic baseline
+ 1: decide baseline with a single click and length defined in auto_left_baseline
+ 2: let user click points of baseline
auto_left_baseline = length in nm to use as baseline from the right point (if baseline_clicks=0 , 1)
auto_right_baseline = distance in nm of peak-most baseline point from last peak (if baseline_clicks = 0)
'''
plot: plot to use
backwards: if true, finds a point backwards.
'''
+ whatset=1 #FIXME: should be decidable
x_vect=plot.vectors[1][0]
c=0
contact_point_index=contact_point.index
self.wlccontact_point=contact_point
self.wlccontact_index=contact_point.index
- self.wlccurrent=self.current.path
+ self.wlccurrent=self.current.path\r
return contact_point, contact_point_index
def find_current_peaks():
#initialize output data vectors
c_lengths=[]
p_lengths=[]
+ sigma_c_lengths=[]
+ sigma_p_lengths=[]
forces=[]
slopes=[]
peak_location, peak_size = find_current_peaks()
+ if len(peak_location) == 0:
+ print 'No peaks to fit.'
+ return
+
fitplot=copy.deepcopy(displayed_plot)
#Pick up force baseline
if rebase:
- clicks=self.config['baseline_clicks']
+ clicks=self.config['baseline_clicks']\r
if clicks==0:
self.basepoints=[]
base_index_0=peak_location[-1]+fit_interval_nm(peak_location[-1], displayed_plot, self.config['auto_right_baseline'],False)
boundaries=[self.basepoints[0].index, self.basepoints[1].index]
boundaries.sort()
to_average=displayed_plot.vectors[1][1][boundaries[0]:boundaries[1]] #y points to average
- avg=np.mean(to_average)
-
+ avg=np.mean(to_average)\r
+ \r
+ clicks=self.config['baseline_clicks']\r
+ if clicks==-1:\r
+ try:\r
+ avg=displayed_plot.vectors[1][1][contact_point_index]
+ except:\r
+ avg=displayed_plot.vectors[1][1][cindex]
for peak in peak_location:
#WLC FITTING
if abs(peak_point.index-other_fit_point.index) < 2:
continue
- params, yfit, xfit, fit_errors = self.wlc_fit(points, displayed_plot.vectors[1][0], displayed_plot.vectors[1][1], pl_value, T)
+ params, yfit, xfit, fit_errors = self.wlc_fit(points, displayed_plot.vectors[1][0], displayed_plot.vectors[1][1], pl_value, T, return_errors=True)
#Measure forces
if len(params)==1: #if we did choose 1-value fit
p_lengths.append(pl_value)
c_lengths.append(params[0]*(1.0e+9))
+ sigma_p_lengths.append(0)
+ sigma_c_lengths.append(fit_errors[0]*(1.0e+9))
forces.append(abs(y-avg)*(1.0e+12))
slopes.append(slope)
#Add WLC fit lines to plot
fitplot.add_set(xfit,yfit)
if len(fitplot.styles)==0:
fitplot.styles=[]
+ fitplot.colors=[]
else:
fitplot.styles.append(None)
- else:
+ fitplot.colors.append(None)
+ else: #2-value fit
p_leng=params[1]*(1.0e+9)
#check if persistent length makes sense. otherwise, discard peak.
if p_leng>self.config['auto_min_p'] and p_leng<self.config['auto_max_p']:
p_lengths.append(p_leng)
c_lengths.append(params[0]*(1.0e+9))
+ sigma_c_lengths.append(fit_errors[0]*(1.0e+9))
+ sigma_p_lengths.append(fit_errors[1]*(1.0e+9))
forces.append(abs(y-avg)*(1.0e+12))
slopes.append(slope)
fitplot.add_set(xfit,yfit)
if len(fitplot.styles)==0:
fitplot.styles=[]
+ fitplot.colors=[]
else:
fitplot.styles.append(None)
+ fitplot.colors.append(None)
else:
pass
#add basepoints to fitplot
fitplot.add_set([self.basepoints[0].graph_coords[0],self.basepoints[1].graph_coords[0]],[self.basepoints[0].graph_coords[1],self.basepoints[1].graph_coords[1]])
fitplot.styles.append('scatter')
-
+ fitplot.colors.append(None)
#Show wlc fits and peak locations
self._send_plot([fitplot])
#self.do_peaks('')
+ print 'Measurements for all peaks detected:'
+ print 'contour (nm)', c_lengths
+ print 'sigma contour (nm)',sigma_c_lengths
+ print 'p (nm)',p_lengths
+ print 'sigma p (nm)',sigma_p_lengths
+ print 'forces (pN)',forces
+ print 'slopes (N/m)',slopes
#Ask the user what peaks to ignore from analysis.
print 'Peaks to ignore (0,1...n from contact point,return to take all)'
p_lengths[i]=None
forces[i]=None
slopes[i]=None
+ sigma_c_lengths[i]=None
+ sigma_p_lengths[i]=None
except:
print 'Bad input, taking all...'
#Clean data vectors from ignored peaks
+ #FIXME:code duplication
c_lengths=[item for item in c_lengths if item != None]
p_lengths=[item for item in p_lengths if item != None]
forces=[item for item in forces if item != None]
slopes=[item for item in slopes if item != None]
+ sigma_c_lengths=[item for item in sigma_c_lengths if item != None]
+ sigma_p_lengths=[item for item in sigma_p_lengths if item != None]
+
+ print 'Measurements for chosen peaks:'
print 'contour (nm)',c_lengths
+ print 'sigma contour (nm)',sigma_c_lengths
print 'p (nm)',p_lengths
+ print 'sigma p (nm)',sigma_p_lengths
print 'forces (pN)',forces
print 'slopes (N/m)',slopes
f=open(self.autofile,'w+')
f.write('Analysis started '+time.asctime()+'\n')
f.write('----------------------------------------\n')
- f.write('; Contour length (nm) ; Persistence length (nm) ; Max.Force (pN) ; Slope (N/m) \n')
+ f.write('; Contour length (nm) ; Persistence length (nm) ; Max.Force (pN) ; Slope (N/m) ; Sigma contour (nm) ; Sigma persistence (nm)\n')
f.close()
print 'Saving...'
f.write(self.current.path+'\n')
for i in range(len(c_lengths)):
- f.write(' ; '+str(c_lengths[i])+' ; '+str(p_lengths[i])+' ; '+str(forces[i])+' ; '+str(slopes[i])+'\n')
+ f.write(' ; '+str(c_lengths[i])+' ; '+str(p_lengths[i])+' ; '+str(forces[i])+' ; '+str(slopes[i])+' ; '+str(sigma_c_lengths[i])+' ; '+str(sigma_p_lengths[i])+'\n')
f.close()
self.do_note('autopeak')
projects / hooke.git / blobdiff