3 """Plugin regarding general velocity clamp measurements
6 from hooke.libhooke import WX_GOOD, ClickedPoint
8 wxversion.select(WX_GOOD)
9 from wx import PostEvent
17 warnings.simplefilter('ignore',np.RankWarning)
20 class generalvclampCommands(object):
27 def do_distance(self,args):
31 Measure the distance (in nm) between two points.
32 For a standard experiment this is the delta X distance.
33 For a force clamp experiment this is the delta Y distance (actually becomes
38 if self.current.curve.experiment == 'clamp':
39 print 'You wanted to use zpiezo perhaps?'
42 dx,unitx,dy,unity=self._delta(set=1)
43 print str(dx*(10**9))+' nm'
44 to_dump='distance '+self.current.path+' '+str(dx*(10**9))+' nm'
45 self.outlet.push(to_dump)
48 def do_force(self,args):
52 Measure the force difference (in pN) between two points
56 if self.current.curve.experiment == 'clamp':
57 print 'This command makes no sense for a force clamp experiment.'
59 dx,unitx,dy,unity=self._delta(set=1)
60 print str(dy*(10**12))+' pN'
61 to_dump='force '+self.current.path+' '+str(dy*(10**12))+' pN'
62 self.outlet.push(to_dump)
65 def do_forcebase(self,args):
69 Measures the difference in force (in pN) between a point and a baseline
70 took as the average between two points.
72 The baseline is fixed once for a given curve and different force measurements,
73 unless the user wants it to be recalculated
75 Syntax: forcebase [rebase]
76 rebase: Forces forcebase to ask again the baseline
77 max: Instead of asking for a point to measure, asks for two points and use
78 the maximum peak in between
80 rebase=False #if true=we select rebase
81 maxpoint=False #if true=we measure the maximum peak
83 plot=self._get_displayed_plot()
84 whatset=1 #fixme: for all sets
85 if 'rebase' in args or (self.basecurrent != self.current.path):
91 print 'Select baseline'
92 self.basepoints=self._measure_N_points(N=2, whatset=whatset)
93 self.basecurrent=self.current.path
96 print 'Select two points'
97 points=self._measure_N_points(N=2, whatset=whatset)
98 boundpoints=[points[0].index, points[1].index]
101 y=min(plot.vectors[whatset][1][boundpoints[0]:boundpoints[1]])
103 print 'Chosen interval not valid. Try picking it again. Did you pick the same point as begin and end of interval?'
105 print 'Select point to measure'
106 points=self._measure_N_points(N=1, whatset=whatset)
107 #whatplot=points[0].dest
108 y=points[0].graph_coords[1]
110 #fixme: code duplication
111 boundaries=[self.basepoints[0].index, self.basepoints[1].index]
113 to_average=plot.vectors[whatset][1][boundaries[0]:boundaries[1]] #y points to average
115 avg=np.mean(to_average)
117 print str(forcebase*(10**12))+' pN'
118 to_dump='forcebase '+self.current.path+' '+str(forcebase*(10**12))+' pN'
119 self.outlet.push(to_dump)
121 def plotmanip_multiplier(self, plot, current):
123 Multiplies all the Y values of an SMFS curve by a value stored in the 'force_multiplier'
124 configuration variable. Useful for calibrations and other stuff.
128 if current.curve.experiment != 'smfs':
131 #only one set is present...
132 if len(self.plots[0].vectors) != 2:
136 if (self.config['force_multiplier']==1):
139 for i in range(len(plot.vectors[0][1])):
140 plot.vectors[0][1][i]=plot.vectors[0][1][i]*self.config['force_multiplier']
142 for i in range(len(plot.vectors[1][1])):
143 plot.vectors[1][1][i]=plot.vectors[1][1][i]*self.config['force_multiplier']
148 def plotmanip_flatten(self, plot, current, customvalue=False):
150 Subtracts a polynomial fit to the non-contact part of the curve, as to flatten it.
151 the best polynomial fit is chosen among polynomials of degree 1 to n, where n is
152 given by the configuration file or by the customvalue.
154 customvalue= int (>0) --> starts the function even if config says no (default=False)
158 if current.curve.experiment != 'smfs':
161 #only one set is present...
162 if len(self.plots[0].vectors) != 2:
165 #config is not flatten, and customvalue flag is false too
166 if (not self.config['flatten']) and (not customvalue):
173 max_cycles=customvalue
175 max_cycles=self.config['flatten'] #Using > 1 usually doesn't help and can give artefacts. However, it could be useful too.
177 contact_index=self.find_contact_point()
179 valn=[[] for item in range(max_exponent)]
180 yrn=[0.0 for item in range(max_exponent)]
181 errn=[0.0 for item in range(max_exponent)]
183 #Check if we have a proper numerical value
187 #Loudly and annoyingly complain if it's not a number, then fallback to zero
188 print '''Warning: flatten value is not a number!
189 Use "set flatten" or edit hooke.conf to set it properly
193 for i in range(int(max_cycles)):
195 x_ext=plot.vectors[0][0][contact_index+delta_contact:]
196 y_ext=plot.vectors[0][1][contact_index+delta_contact:]
197 x_ret=plot.vectors[1][0][contact_index+delta_contact:]
198 y_ret=plot.vectors[1][1][contact_index+delta_contact:]
199 for exponent in range(max_exponent):
201 valn[exponent]=sp.polyfit(x_ext,y_ext,exponent)
202 yrn[exponent]=sp.polyval(valn[exponent],x_ret)
203 errn[exponent]=sp.sqrt(sum((yrn[exponent]-y_ext)**2)/float(len(y_ext)))
205 print 'Cannot flatten!'
209 best_exponent=errn.index(min(errn))
212 ycorr_ext=y_ext-yrn[best_exponent]+y_ext[0] #noncontact part
213 yjoin_ext=np.array(plot.vectors[0][1][0:contact_index+delta_contact]) #contact part
215 ycorr_ret=y_ret-yrn[best_exponent]+y_ext[0] #noncontact part
216 yjoin_ret=np.array(plot.vectors[1][1][0:contact_index+delta_contact]) #contact part
218 ycorr_ext=np.concatenate((yjoin_ext, ycorr_ext))
219 ycorr_ret=np.concatenate((yjoin_ret, ycorr_ret))
221 plot.vectors[0][1]=list(ycorr_ext)
222 plot.vectors[1][1]=list(ycorr_ret)
227 def do_slope(self,args):
231 Measures the slope of a delimited chunk on the return trace.
232 The chunk can be delimited either by two manual clicks, or have
233 a fixed width, given as an argument.
235 Syntax: slope [width]
236 The facultative [width] parameter specifies how many
237 points will be considered for the fit. If [width] is
238 specified, only one click will be required.
239 (c) Marco Brucale, Massimo Sandal 2008
242 # Reads the facultative width argument
248 # Decides between the two forms of user input, as per (args)
250 # Gets the Xs of two clicked points as indexes on the current curve vector
251 print 'Click twice to delimit chunk'
252 points=self._measure_N_points(N=2,whatset=1)
254 print 'Click once on the leftmost point of the chunk (i.e.usually the peak)'
255 points=self._measure_N_points(N=1,whatset=1)
257 slope=self._slope(points,fitspan)
259 # Outputs the relevant slope parameter
262 to_dump='slope '+self.current.path+' '+str(slope)
263 self.outlet.push(to_dump)
265 def _slope(self,points,fitspan):
266 # Calls the function linefit_between
267 parameters=[0,0,[],[]]
269 clickedpoints=[points[0].index,points[1].index]
272 clickedpoints=[points[0].index-fitspan,points[0].index]
275 parameters=self.linefit_between(clickedpoints[0],clickedpoints[1])
277 print 'Cannot fit. Did you click twice the same point?'
280 # Outputs the relevant slope parameter
282 print str(parameters[0])
283 to_dump='slope '+self.curve.path+' '+str(parameters[0])
284 self.outlet.push(to_dump)
286 # Makes a vector with the fitted parameters and sends it to the GUI
287 xtoplot=parameters[2]
291 ytoplot.append((x*parameters[0])+parameters[1])
293 clickvector_x, clickvector_y=[], []
295 clickvector_x.append(item.graph_coords[0])
296 clickvector_y.append(item.graph_coords[1])
298 lineplot=self._get_displayed_plot(0) #get topmost displayed plot
300 lineplot.add_set(xtoplot,ytoplot)
301 lineplot.add_set(clickvector_x, clickvector_y)
304 if lineplot.styles==[]:
305 lineplot.styles=[None,None,None,'scatter']
307 lineplot.styles+=[None,'scatter']
308 if lineplot.colors==[]:
309 lineplot.colors=[None,None,'black',None]
311 lineplot.colors+=['black',None]
314 self._send_plot([lineplot])
319 def linefit_between(self,index1,index2,whatset=1):
321 Creates two vectors (xtofit,ytofit) slicing out from the
322 current return trace a portion delimited by the two indexes
324 Then does a least squares linear fit on that slice.
325 Finally returns [0]=the slope, [1]=the intercept of the
326 fitted 1st grade polynomial, and [2,3]=the actual (x,y) vectors
328 (c) Marco Brucale, Massimo Sandal 2008
330 # Translates the indexes into two vectors containing the x,y data to fit
331 xtofit=self.plots[0].vectors[whatset][0][index1:index2]
332 ytofit=self.plots[0].vectors[whatset][1][index1:index2]
334 # Does the actual linear fitting (simple least squares with numpy.polyfit)
336 linefit=np.polyfit(xtofit,ytofit,1)
338 return (linefit[0],linefit[1],xtofit,ytofit)