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src/b/i/biskit-2.4/Biskit/ProfileCollection.py   biskit(Download)
import mathUtils as M
from Biskit import EHandler
from Biskit.hist import density
 
 
            for j, key in enumerate(keys):
 
                h = density( self[key], nBins=bins, steps=steps, hist=hist,
                             range=histrange )
                x = h[:,0]

src/b/i/biskit-2.4/Biskit/Statistics/Density.py   biskit(Download)
        if values is not None:
 
            p = H.density(values, bins, steps = 0)
 
        self.store(p)

src/b/i/biskit-2.4/scripts/analysis/a_rmsd_vs_performance.py   biskit(Download)
from Biskit.tools import *
import biggles as B
from Biskit.hist import density
 
def use():
 
    a = concatenate( (delta_rms_1, delta_rms_2) )
    h = density( a, 20 )
    scale = max( h[:,1] ) / max( a )
    histogram = B.Curve( h[:,0], h[:,1] * scale )

src/b/i/biskit-2.4/scripts/analysis/a_foldX.py   biskit(Download)
    inset.y1.draw_subticks = 0
    inset.y2.draw_ticks = 0
    dens = Biskit.hist.density( e_val[i], 25 )
    inset.add( biggles.Curve( dens[:,1], dens[:,0], type='solid', width=2, color=spectrum[i] ))
    p_histogram += [ inset ]

src/b/i/biskit-2.4/Biskit/Statistics/lognormal.py   biskit(Download)
 
        if self.local:
            gnuplot.plot( H.density( N.array(cr) - ca, 100 ) )
 
            globals().update( locals() )

src/b/i/biskit-2.4/Biskit/Dock/ComplexTraj.py   biskit(Download)
        r = N.ravel( r )
        r = N.compress( r, r )
        gnuplot.plot( hist.density( r, 10 ) )