Insert a new object that conducts basic transformation in a data sample

dream/KnowledgeExtraction/Transformations.py

+# ===========================================================================
+# Copyright 2013 University of Limerick
+#
+# This file is part of DREAM.
+#
+# DREAM is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Lesser General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# DREAM is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public License
+# along with DREAM.  If not, see <http://www.gnu.org/licenses/>.
+# ===========================================================================
+
+'''
+Created on 14 Nov 2013
+
+@author: Panos
+'''
+
+import rpy2.robjects as robjects
+
+#The BasicTransformations object
+class BasicTransformations:
+# A variety of transformations are calculated in this object
+    def sum(self, data):                      #calculates the sum of data sample
+        data=robjects.FloatVector(data)          ##The given list changes into float vector in order to be handled by RPy2
+        rsum = robjects.r['sum']           #Call sum function-R function
+        return rsum(data)[0]
+    
+    def scale(self, data):                    #centers around the mean and scales by the standard deviation (sd) 
+        data=robjects.FloatVector(data)
+        rscale = robjects.r['scale']        #Call scale - R function
+        return list(rscale(data))
+    
+    def cumsum(self,data):                  #returns the cumulative sum of data sample
+        data=robjects.FloatVector(data)
+        rcumsum = robjects.r['cumsum']        #Call cumsum - R function
+        return list(rcumsum(data))
+    
+    def cumprod(self,data):                  #returns the cumulative product of data sample
+        data=robjects.FloatVector(data)
+        rcumprod = robjects.r['cumprod']        #Call cumprod - R function
+        return list(rcumprod(data))
+    
+    def cummax(self,data):                  #returns the cumulative maximum of data sample
+        data=robjects.FloatVector(data)
+        rcummax = robjects.r['cummax']        #Call cummax - R function
+        return list(rcummax(data))
+     
+    def cummin(self,data):                   #returns the cumulative minimum of data sample
+        data=robjects.FloatVector(data)
+        rcummin = robjects.r['cummin']        #Call cummin - R function
+        return list(rcummin(data)) 
+    
+    def rev(self,data):                  #reverse the order of values in the data sample
+        data=robjects.FloatVector(data)
+        rrev = robjects.r['rev']        #Call rev - R function
+        return list(rrev(data))   
+        
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