hooke/plugin/massanalysis.py

   1 #!/usr/bin/env python
   2
   3 '''
   4 massanalysis.py
   5
   6 Global analysis of force curves with various parameters
   7
   8 Requires:
   9 libpeakspot.py
  10 flatfilts.py
  11 '''
  12
  13
  14 import libpeakspot as lps
  15 import libhookecurve as lhc
  16 import libhooke as lh
  17 import numpy as np
  18
  19 import csv
  20
  21 class massanalysisCommands:
  22
  23     def _plug_init(self):
  24         self.mass_variables={}
  25         self.interesting_variables=['curve','firstpeak_distance','lastpeak_distance','Npeaks','median_distance','mean_distance']
  26         self._clean_data()
  27
  28     def _clean_data(self):
  29         for variable in self.interesting_variables:
  30             self.mass_variables[variable]=[]
  31
  32     def peak_position_from_contact(self, item, locations):
  33         '''
  34         calculates X distance of a peak from the contact point
  35         '''
  36         item.identify(self.drivers)
  37
  38         real_positions=[]
  39         cut_index=self.find_contact_point()
  40
  41         #we assume the first is the plot with the force curve
  42         plot=item.curve.default_plots()[0]
  43         xret=plot.vectors[1][0]
  44
  45         start_x=xret[cut_index]
  46
  47         real_positions=[abs((xret[index])-(start_x)) for index in locations]
  48         #close all open files
  49         item.curve.close_all()
  50         #needed to avoid *big* memory leaks!
  51         del item.curve
  52         del item
  53         return real_positions
  54
  55     def do_maplist(self,args):
  56         '''
  57         MAPLIST
  58         (flatfilts.py)
  59         ----
  60         pass
  61         '''
  62         self._clean_data() #if we recall it, clean previous data!
  63         min_deviation=self.convfilt_config['mindeviation']
  64
  65
  66         c=0
  67         for item in self.current_list:
  68             try:
  69                 peak_location,peak_size=self.exec_has_peaks(item, min_deviation)
  70                 real_positions=self.peak_position_from_contact(item, peak_location)
  71
  72                 self.mass_variables['Npeaks'].append(len(peak_location))
  73
  74                 if len(peak_location) > 1:
  75                     self.mass_variables['firstpeak_distance'].append(min(real_positions))
  76                     self.mass_variables['lastpeak_distance'].append(max(real_positions))
  77
  78                     distancepeaks=[]
  79                     for index in range(len(real_positions)-1):
  80                         distancepeaks.append(real_positions[index+1]-real_positions[index])
  81                 else:
  82                     self.mass_variables['firstpeak_distance'].append(0)
  83                     self.mass_variables['lastpeak_distance'].append(0)
  84
  85                 if len(peak_location) > 2:
  86                     self.mass_variables['median_distance'].append(np.median(distancepeaks))
  87                     self.mass_variables['mean_distance'].append(np.mean(distancepeaks))
  88                 else:
  89                     self.mass_variables['median_distance'].append(0)
  90                     self.mass_variables['mean_distance'].append(0)
  91
  92                 print 'curve',c
  93             except SyntaxError:
  94                 print 'curve',c,'not mapped'
  95                 pass
  96
  97             c+=1
  98
  99     def do_plotmap(self,args):
 100         '''
 101         '''
 102         args=args.split()
 103         if len(args)>1:
 104             x=self.mass_variables[args[0]]
 105             y=self.mass_variables[args[1]]
 106         else:
 107             print 'Give me two arguments between those:'
 108             print self.interesting_variables
 109             return
 110
 111         scattermap=lhc.PlotObject()
 112         scattermap.vectors=[[]]
 113         scattermap.vectors[0].append(x)
 114         scattermap.vectors[0].append(y)
 115
 116         scattermap.units=[args[0],args[1]]
 117         scattermap.styles=['scatter']
 118         scattermap.destination=1
 119
 120         self._send_plot([scattermap])
 121
 122     def do_savemaps(self,args):
 123         '''
 124         args=filename
 125         '''
 126
 127         '''
 128         def csv_write_cols(data, f):
 129
 130             #from Bruno Desthuillers on comp.lang.python
 131
 132             writer = csv.writer(f)
 133             keys = data.keys()
 134             writer.writerow(dict(zip(keys,keys)))
 135             for row in zip(*data.values()):
 136                 writer.writerow(dict(zip(keys, row)))
 137         '''
 138
 139         f=open(args,'wb')
 140         lh.csv_write_dictionary(f,self.mass_variables)
 141         f.close()
 142
 143