From 7c09ec981c6e06af2e62d67a609eb53728267954 Mon Sep 17 00:00:00 2001
From: Jonathan Herman <hermanjl@cs.unc.edu>
Date: Thu, 27 Sep 2012 19:03:22 -0400
Subject: Added script to parse directory data, create CSVs for every chagned
 value.

This change also makes SchedTrace and OverheadTrace events configurable.
---
 parse/point.py | 135 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 135 insertions(+)
 create mode 100644 parse/point.py

(limited to 'parse/point.py')

diff --git a/parse/point.py b/parse/point.py
new file mode 100644
index 0000000..4343d03
--- /dev/null
+++ b/parse/point.py
@@ -0,0 +1,135 @@
+"""
+Too much duplicate code in this file
+"""
+
+import copy
+import numpy as np
+from enum import Enum
+from collections import defaultdict
+
+Type = Enum(['Min','Max','Avg','Var'])
+default_typemap = {Type.Max : {Type.Max : 1, Type.Min : 0, Type.Avg : 1, Type.Var : 1},
+                   Type.Min : {Type.Max : 1, Type.Min : 0, Type.Avg : 1, Type.Var : 1},
+                   Type.Avg : {Type.Max : 1, Type.Min : 0, Type.Avg : 1, Type.Var : 1}}
+
+def make_typemap():
+    return copy.deepcopy(default_typemap)
+
+def dict_str(adict, sep = "\n"):
+    return sep.join(["%s: %s" % (k, str(v)) for (k,v) in adict.iteritems()])
+
+class Measurement(object):
+    def __init__(self, id = None, kv = {}):
+        self.id = id
+        self.stats = {}
+        for k, v in kv.iteritems():
+            self[k] = v
+
+    def from_array(self,array):
+        array = np.array(array)
+        self[Type.Max] = array.max()
+        self[Type.Avg] = array.mean()
+        self[Type.Var] = array.var()
+        return self
+
+    def __check_type(self, type):
+        if not type in Type:
+            raise AttributeError("Not a valid type '%s'" % type)
+        
+    def __getitem__(self, type):
+        self.__check_type(type)
+        return self.stats[type]
+
+    def __iter__(self):
+        return self.stats.iteritems()
+
+    def __contains__(self, type):
+        self.__check_type(type)
+        return type in self.stats
+
+    def __setitem__(self, type, value):
+        self.__check_type(type)
+        self.stats[type] = value
+
+    def __str__(self):
+        return "<Measurement-%s> %s" % (self.id, dict_str(self.stats, " "))
+            
+
+class Summary(Measurement):
+    def __init__(self, id, measures, typemap = default_typemap):
+        super(Summary, self).__init__("Summary-%s" % id)
+
+        self.__check_types(measures, typemap)
+        self.__summarize(measures, typemap)
+
+    def __check_types(self, measures, typemap):
+        required_types = self.__get_required(typemap)
+        for m in measures:
+            for type in required_types:
+                if type not in m:
+                    raise ValueError("measurement '%s' missing type '%s'" %
+                                     (self.id, type))
+
+    def __summarize(self, measures, typemap):
+        for sum_type in Type:
+            self[sum_type] = Measurement(self.id)
+
+        def avg(vals):
+            return sum(vals) / len(vals)
+
+        for base_type in Type:
+            for sum_type, func in (Type.Min,min),(Type.Max,max),(Type.Avg, avg):
+                if typemap[sum_type][base_type]:
+                    val = func([m[base_type] for m in measures])
+                    self[sum_type][base_type] = val
+
+    def __get_required(self, typemap):
+        required = []
+        for base_type in Type:
+            matches = [t[base_type] for t in typemap.itervalues()]
+            if bool(sum(matches)):
+                required += [base_type]
+        return required
+
+class ExpPoint(object):
+    def __init__(self, id = "", init = {}):
+        self.stats = {}
+        for type, value in init.iteritems():
+            self[type] = value
+        self.id = id
+
+    def __check_val(self, obj):
+        if not isinstance(obj, Measurement):
+            raise AttributeError("Not a valid measurement '%s'" % obj)
+        
+    def __getitem__(self, type):
+        return self.stats[type]
+
+    def __iter__(self):
+        return self.stats.iteritems()
+
+    def __contains__(self, type):
+        return type in self.stats
+
+    def __setitem__(self, type, value):
+        self.__check_val(value)
+        self.stats[type] = value
+
+    def __str__(self):
+        return "<ExpPoint-%s>\n%s" % (self.id, dict_str(self.stats))
+
+    def get_stats(self):
+        return self.stats.keys()
+
+class SummaryPoint(ExpPoint):
+    def __init__(self, id, points, typemap = default_typemap):
+        super(SummaryPoint,self).__init__("Summary-%s" % id)
+
+        grouped = defaultdict(lambda : [])
+
+        for exp in points:
+            for name,measure in exp.stats.iteritems():
+                grouped[name] += [measure]
+
+        for key in grouped.iterkeys():
+            self[key] = Summary(key, grouped[key], typemap)
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