replace the use of scipy by rpy2

dream/simulation/Globals.py

@@ -33,7 +33,6 @@ import xlwt
 import xlrd
 from random import Random, expovariate, gammavariate, normalvariate
 from SimPy.Simulation import now
-import scipy.stats as stat
 
 # ===========================================================================
 # globals
@@ -257,7 +256,7 @@ def countQueueMetrics(argumentDict={}):
 
 
 # =======================================================================
-# Helper function to calculate the min, max and average values of a serie
+# Helper function to calculate the confidence intervals of a serie.
 # =======================================================================
 def getConfidenceIntervals(value_list):
     from Globals import G
@@ -266,8 +265,10 @@ def getConfidenceIntervals(value_list):
         return { 'lb': value_list[0],
                  'ub': value_list[0],
                  'avg': value_list[0], }
-    bayes_mvs = stat.bayes_mvs(value_list, G.confidenceLevel)
-    return { 'lb': bayes_mvs[0][1][0],
-             'ub': bayes_mvs[0][1][1],
-             'avg': bayes_mvs[0][0], }
+    from dream.KnowledgeExtraction.ConfidenceIntervals import Intervals
+    import numpy
+    lb, ub = Intervals().ConfidIntervals(value_list, G.confidenceLevel)
+    return {'lb': lb,
+            'ub': ub,
+            'avg': numpy.mean(value_list) }
 

dream/simulation/LineGenerationCMSD.py

@@ -30,25 +30,6 @@ import logging
 logger = logging.getLogger("dream.platform")
 
 
-try:
-  import scipy
-except ImportError:
-  class scipy:
-    class stats:
-      @staticmethod
-      def bayes_mvs(*args, **kw):
-        warn("Scipy is missing, using fake implementation")
-        serie, confidence = args
-        import numpy
-        mean = numpy.mean(serie), (numpy.min(serie), numpy.max(serie))
-        var = 0, (0, 0)
-        std = 0, (0, 0) 
-        return mean, var, std
-  import sys
-  sys.modules['scipy.stats'] = scipy.stats
-  sys.modules['scipy'] = scipy
-  logger.error("Scipy cannot be imported, using dummy implementation")
-
 from SimPy.Simulation import activate, initialize, simulate, now, infinity
 from Globals import G 
 from Source import Source

dream/simulation/LineGenerationJSON.py

@@ -33,24 +33,6 @@ from warnings import warn
 import logging
 logger = logging.getLogger("dream.platform")
 
-try:
-  import scipy
-except ImportError:
-  class scipy:
-    class stats:
-      @staticmethod
-      def bayes_mvs(*args, **kw):
-        warn("Scipy is missing, using fake implementation")
-        serie, confidence = args
-        import numpy
-        mean = numpy.mean(serie), (numpy.min(serie), numpy.max(serie))
-        var = 0, (0, 0)
-        std = 0, (0, 0) 
-        return mean, var, std
-  import sys
-  sys.modules['scipy.stats'] = scipy.stats
-  sys.modules['scipy'] = scipy
-  logger.error("Scipy cannot be imported, using dummy implementation")
 
 # By default numpy just prints on stderr when there's an error. We do not want
 # to hide errors.