Source Code for Module Biskit.hist

  1  ## Automatically adapted for numpy.oldnumeric Mar 26, 2007 by alter_code1.py 
  2   
  3  ## 
  4  ## Biskit, a toolkit for the manipulation of macromolecular structures 
  5  ## Copyright (C) 2004-2006 Wolfgang Rieping 
  6  ## 
  7  ## This program is free software; you can redistribute it and/or 
  8  ## modify it under the terms of the GNU General Public License as 
  9  ## published by the Free Software Foundation; either version 2 of the 
 10  ## License, or any later version. 
 11  ## 
 12  ## This program is distributed in the hope that it will be useful, 
 13  ## but WITHOUT ANY WARRANTY; without even the implied warranty of 
 14  ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU 
 15  ## General Public License for more details. 
 16  ## 
 17  ## You find a copy of the GNU General Public License in the file 
 18  ## license.txt along with this program; if not, write to the Free 
 19  ## Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. 
 20  ## 
 21   
 22  ## last $Author: graik $ 
 23  ## last $Date: 2007/03/26 18:40:40 $ 
 24  ## $Revision: 2.7 $ 
 25  """ 
 26  create a histogram from data 
 27  """ 
 28   
 29  import numpy.oldnumeric as Numeric 
 30   
 31   
 32 -def histogram(data, nbins, range = None): 
 33      """ 
 34      Create a histogram. 
 35      Comes from Konrad Hinsen: Scientific Python 
 36       
 37      @param data: data list or array 
 38      @type  data: [any] 
 39      @param nbins: number of bins 
 40      @type  nbins: int 
 41      @param range: data range to create histogram from (min val, max val) 
 42      @type  range: (float, float) OR None 
 43   
 44      @return: array (2 x len(data) ) with start of bin and witdh of bin.  
 45      @rtype: array 
 46      """ 
 47      data = Numeric.array(data, Numeric.Float) 
 48      if range is None: 
 49          min = Numeric.minimum.reduce(data) 
 50          max = Numeric.maximum.reduce(data) 
 51      else: 
 52          min, max = range 
 53          data = Numeric.repeat(data, 
 54                     Numeric.logical_and(Numeric.less_equal(data, max), 
 55                                         Numeric.greater_equal(data, min))) 
 56      bin_width = (max-min)/nbins 
 57      data = Numeric.floor((data - min)/bin_width).astype(Numeric.Int) 
 58      histo = Numeric.add.reduce(Numeric.equal( 
 59          Numeric.arange(nbins)[:,Numeric.NewAxis], data), -1) 
 60      histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data)) 
 61      bins = min + bin_width*(Numeric.arange(nbins)+0.5) 
 62      return Numeric.transpose(Numeric.array([bins, histo])) 
 63   
 64   
 65 -def density(x, nBins, range = None, steps = 1, hist = 0): 
 66      """ 
 67      returns the normalized histogram of x:: 
 68        density( data, nBins [,range=None, steps=1, hist=0|1] ) -> array 
 69         
 70      @param x: data list or array 
 71      @type  x: [any] 
 72      @param nBins: number of bins 
 73      @type  nBins: int 
 74      @param range: data range to create histogram from (min val, max val) 
 75      @type  range: (float, float) OR None 
 76      @param steps: 1: histogram appears as a discrete graph (default 1) 
 77      @type  steps: 1|0 
 78      @param hist: 0: normalize histogram (default 0) 
 79      @type  hist: 1|0 
 80       
 81      @return: array (2 x len(data) ) with start of bin and witdh of bin.  
 82      @rtype: array 
 83      """ 
 84      h = histogram(x, nBins, range) 
 85      binWidth = h[1,0] - h[0,0] 
 86   
 87      if not hist: 
 88          i = Numeric.sum(h)[1]*binWidth 
 89          h[:,1] = h[:,1]/i 
 90   
 91      if steps: 
 92          half = (h[1][0]-h[0][0])/2 
 93          l = [(h[0][0]-half,0)] 
 94   
 95          for row in h: 
 96              l.append((row[0]-half,row[1])) 
 97              l.append((row[0]+half,row[1])) 
 98   
 99          l.append((h[-1][0]+half,0)) 
100   
101          h = l 
102   
103      return Numeric.array(h) 
104   
105   
106  ############# 
107  ##  TESTING         
108  ############# 
109  import Biskit.test as BT 
110           
111 -class Test(BT.BiskitTest): 
112      """Test case""" 
113   
114 -    def test_hist( self ): 
115          """hist test""" 
116          self.x = Numeric.arange( 4, 12, 1.2 ) 
117          self.data = density( self.x, 3, hist=1 ) 
118   
119          self.assert_( Numeric.all( self.data == self.EXPECT) ) 
120   
121      EXPECT= Numeric.array([[  4. ,   0. ], 
122                             [  4. ,   2. ], 
123                             [  6.4,   2. ], 
124                             [  6.4,   2. ], 
125                             [  8.8,   2. ], 
126                             [  8.8,   3. ], 
127                             [ 11.2,   3. ], 
128                             [ 11.2,   0. ]]) 
129   
130   
131  if __name__ == '__main__': 
132   
133      BT.localTest() 
134