usepoints : fit interval by number of points instead than by nanometers
+ noflatten : does not use the "flatten" plot manipulator
+
When you first issue the command, it will ask for the filename. If you are giving the filename
of an existing file, autopeak will resume it and append measurements to it. If you are giving
a new filename, it will create the file and append to it until you close Hooke.
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)
+ 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
self.wlccurrent=self.current.path
return contact_point, contact_point_index
- def find_current_peaks():
+ def find_current_peaks(noflatten):
#Find peaks.
defplot=self.current.curve.default_plots()[0]
- flatten=self._find_plotmanip('flatten') #Extract flatten plotmanip
- defplot=flatten(defplot, self.current, customvalue=1) #Flatten curve before feeding it to has_peaks
+ if not noflatten:
+ flatten=self._find_plotmanip('flatten') #Extract flatten plotmanip
+ defplot=flatten(defplot, self.current, customvalue=1) #Flatten curve before feeding it to has_peaks
peak_location,peak_size=self.has_peaks(defplot, self.convfilt_config['mindeviation'])
return peak_location, peak_size
-
-
-
-
+
#default fit etc. variables
pl_value=None
T=self.config['temperature']
slope_span=int(self.config['auto_slope_span'])
delta_force=10
rebase=False #if true=we select rebase
+ noflatten=False #if true=we avoid flattening
#initialize output data vectors
c_lengths=[]
p_lengths=[]
+ sigma_c_lengths=[]
+ sigma_p_lengths=[]
forces=[]
slopes=[]
if 'rebase' in args or (self.basecurrent != self.current.path):
rebase=True
+ if 'noflatten' in args:
+ noflatten=True
+
#--Custom persistent length / custom temperature
for arg in args.split():
#look for a persistent length argument.
#--END COMMAND LINE PARSING--
- peak_location, peak_size = find_current_peaks()
+ peak_location, peak_size = find_current_peaks(noflatten)
+
+ if len(peak_location) == 0:
+ print 'No peaks to fit.'
+ return
fitplot=copy.deepcopy(displayed_plot)
to_average=displayed_plot.vectors[1][1][boundaries[0]:boundaries[1]] #y points to average
avg=np.mean(to_average)
+ clicks=self.config['baseline_clicks']
+ if clicks==-1:
+ try:
+ avg=displayed_plot.vectors[1][1][contact_point_index]
+ except:
+ 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 = 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
#check fitted data and, if right, add peak to the measurement
#FIXME: code duplication
if len(params)==1: #if we did choose 1-value fit
- p_lengths.append(params[1]*(1.0e+9))
+ 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