00001 __copyright__ = """
00002 Copyright 2008 Sean Ross-Ross
00003 """
00004 __license__ = """
00005 This file is part of SLIMpy .
00006
00007 SLIMpy is free software: you can redistribute it and/or modify
00008 it under the terms of the GNU Lesser General Public License as published by
00009 the Free Software Foundation, either version 3 of the License, or
00010 (at your option) any later version.
00011
00012 SLIMpy is distributed in the hope that it will be useful,
00013 but WITHOUT ANY WARRANTY; without even the implied warranty of
00014 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
00015 GNU Lesser General Public License for more details.
00016
00017 You should have received a copy of the GNU Lesser General Public License
00018 along with SLIMpy . If not, see <http://www.gnu.org/licenses/>.
00019 """
00020
00021
00022 from numpy import ceil
00023
00024 def curverat(curvec1,curvec2,cutv):
00025 """
00026 --latex
00027 This approach is based on rescaling the weighting vectors ( $w_{1}$
00028 or $w_{2}$ ) in such a way that after the application of the rescaled vectors for soft
00029 thresholding a certain percentage (the n relatively largest coefficients) remain in
00030 the thresholded vector per scale or globally.
00031 The operation is based on the following steps:
00032 \\begin{enumerate}
00033 \\item Initialize a vector of the size of the to be thresholded and thresholding
00034 vector
00035 \\item Calculate the ratio ( rat = curvec1 / curvec2 ) over the total vector.
00036 \\item Sort rat in descending order to evaluate for the coefficients mainly con-
00037 tributing to curvec1
00038 \\item Take the value of the sorted rat vector defined by an initial percentage of
00039 values you want to keep cutv.
00040 \\end{enumerate}
00041 """
00042 temp = curvec1 / curvec2
00043 sorted_temp = abs(temp).real().sort()
00044 cutoff = int( ceil(len(sorted_temp.getSpace())*cutv) )
00045 scaling=sorted_temp[cutoff]
00046
00047 return scaling
00048
