Insert new example wikth parallel stations

dream/KnowledgeExtraction/KEtool_examples/TwoParallelStations/JSON_TwoParallelStations.json

+{
+  "capacity_by_project_spreadsheet": [
+    [
+      "Project Name", 
+      "Sequence", 
+      "Capacity Requirements"
+    ], 
+    [
+      null, 
+      null, 
+      null
+    ]
+  ], 
+  "capacity_by_station_spreadsheet": [
+    [
+      "Machine", 
+      "Day 0", 
+      "Day 1", 
+      "Day 2", 
+      "Day 3", 
+      null
+    ], 
+    [
+      null, 
+      null, 
+      null, 
+      null, 
+      null, 
+      null
+    ]
+  ], 
+  "edges": {
+    "con_10": [
+      "Q1", 
+      "St1", 
+      {}
+    ], 
+    "con_15": [
+      "Q1", 
+      "St2", 
+      {}
+    ], 
+    "con_20": [
+      "St1", 
+      "E1", 
+      {}
+    ], 
+    "con_25": [
+      "St2", 
+      "E1", 
+      {}
+    ], 
+    "con_5": [
+      "S1", 
+      "Q1", 
+      {}
+    ]
+  }, 
+  "general": {
+    "confidenceLevel": 0.95, 
+    "currentDate": "2014/06/16", 
+    "ke_url": "http://git.erp5.org/gitweb/dream.git/blob_plain/HEAD:/dream/KnowledgeExtraction/Mockup_Processingtimes.xls", 
+    "maxSimTime": 100, 
+    "numberOfReplications": 10, 
+    "processTimeout": 10, 
+    "seed": "", 
+    "throughputTarget": 10, 
+    "trace": "No"
+  }, 
+  "nodes": {
+    "E1": {
+      "_class": "Dream.Exit", 
+      "element_id": "DreamNode_5", 
+      "name": "Exit"
+    }, 
+    "Q1": {
+      "_class": "Dream.Queue", 
+      "capacity": 1, 
+      "element_id": "DreamNode_2", 
+      "name": "Queue", 
+      "schedulingRule": "FIFO"
+    }, 
+    "S1": {
+      "_class": "Dream.BatchSource", 
+      "batchNumberOfUnits": 80, 
+      "element_id": "DreamNode_1", 
+      "entity": "Dream.Batch", 
+      "interarrivalTime": {
+        "distributionType": "Fixed", 
+        "mean": 1
+      }, 
+      "name": "Source"
+    }, 
+    "St1": {
+      "_class": "Dream.BatchScrapMachine", 
+      "element_id": "DreamNode_3", 
+      "failures": {
+      }, 
+      "name": "Milling1", 
+      "processingTime": {
+        "distributionType": "Fixed", 
+        "max": "", 
+        "mean": 0.75, 
+        "min": "", 
+        "stdev": ""
+      }
+    }, 
+    "St2": {
+      "_class": "Dream.BatchScrapMachine", 
+      "element_id": "DreamNode_4", 
+      "failures": {
+      }, 
+      "name": "Milling2", 
+      "processingTime": {
+        "distributionType": "Fixed", 
+        "max": "", 
+        "mean": 0.75, 
+        "min": "", 
+        "stdev": ""
+      }
+    }
+  }, 
+  "preference": {
+    "coordinates": {
+      "E1": {
+        "left": 0.838470725910555, 
+        "top": 0.5011550303652008
+      }, 
+      "Q1": {
+        "left": 0.28592454969899506, 
+        "top": 0.4898081240173095
+      }, 
+      "S1": {
+        "left": 0.053083038762682624, 
+        "top": 0.48224351978538194
+      }, 
+      "St1": {
+        "left": 0.5199724933344594, 
+        "top": 0.22882927801580868
+      }, 
+      "St2": {
+        "left": 0.5157499788874278, 
+        "top": 0.7243108552070638
+      }
+    }
+  }, 
+  "shift_spreadsheet": [
+    [
+      "Day", 
+      "Machines", 
+      "Start", 
+      "End"
+    ], 
+    [
+      null, 
+      null, 
+      null, 
+      null
+    ]
+  ], 
+  "wip_part_spreadsheet": [
+    [
+      "Order ID", 
+      "Due Date", 
+      "Priority", 
+      "Project Manager", 
+      "Part", 
+      "Part Type", 
+      "Sequence", 
+      "Processing Times", 
+      "Prerequisites Parts"
+    ], 
+    [
+      null, 
+      null, 
+      null, 
+      null, 
+      null, 
+      null, 
+      null, 
+      null, 
+      null
+    ]
+  ]
+}
\ No newline at end of file

dream/KnowledgeExtraction/KEtool_examples/TwoParallelStations/TwoParallelStations_example.py

+'''
+Created on 20 Jun 2014
+
+@author: Panos
+'''
+# ===========================================================================
+# 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/>.
+# ===========================================================================
+
+from DistributionFitting import DistFittest
+from DistributionFitting import Distributions
+from ImportExceldata import Import_Excel
+from ExcelOutput import Output
+from ReplaceMissingValues import HandleMissingValues
+import xlrd
+import json
+import dream.simulation.LineGenerationJSON as ManPyMain #import ManPy main JSON script
+
+#Read from the given directory the Excel document with the input data
+workbook = xlrd.open_workbook('inputData.xls')
+worksheets = workbook.sheet_names()
+worksheet_ProcessingTimes = worksheets[0]     #Define the worksheet with the Processing times data
+
+inputData = Import_Excel()                              #Call the Python object Import_Excel
+ProcessingTimes = inputData.Input_data(worksheet_ProcessingTimes, workbook)   #Create the Processing Times dictionary with key Machines 1,2 and values the processing time data
+
+##Get from the above dictionaries the M1 key and define the following lists with data 
+M1_ProcTime = ProcessingTimes.get('M1',[])         
+M2_ProcTime = ProcessingTimes.get('M2',[])  
+
+#Call the HandleMissingValues object and replace the missing values in the lists with the mean of the non-missing values
+misValues =HandleMissingValues()
+M1_ProcTime = misValues.ReplaceWithMean(M1_ProcTime)
+M2_ProcTime = misValues.ReplaceWithMean(M2_ProcTime)
+
+MLE = Distributions()      #Call the Distributions object (Maximum Likelihood Estimation - MLE)
+KS = DistFittest()      #Call the DistFittest object  (Kolmoghorov-Smirnov test)
+
+M1ProcTime_dist = KS.ks_test(M1_ProcTime)
+M2ProcTime_dist = MLE.Normal_distrfit(M2_ProcTime)
+
+#======================= Output preparation: output the updated values in the JSON file of this example ================================#
+jsonFile = open('JSON_TwoParallelStations.json','r')      #It opens the JSON file 
+data = json.load(jsonFile)                                                              #It loads the file
+jsonFile.close()
+nodes = data.get('nodes',[])                                                         #It creates a variable that holds the 'nodes' dictionary
+
+for element in nodes:
+    processingTime = nodes[element].get('processingTime',{})        #It creates a variable that gets the element attribute 'processingTime'
+        
+    if element == 'St1':
+        nodes['St1']['processingTime'] = M1ProcTime_dist         #It checks using if syntax if the element is 'M1'
+    elif element == 'St2':
+        nodes['St2']['processingTime'] = M2ProcTime_dist         #It checks using if syntax if the element is 'M2'
+      
+    
+    jsonFile = open('JSON_ParallelStations_Output.json',"w")     #It opens the JSON file
+    jsonFile.write(json.dumps(data, indent=True))                                           #It writes the updated data to the JSON file 
+    jsonFile.close()                                                                        #It closes the file
+
+#=================== Calling the ExcelOutput object, outputs the outcomes of the statistical analysis in xls files ==========================#
+export=Output()
+
+export.PrintStatisticalMeasures(M1_ProcTime,'M1_ProcTime_StatResults.xls')   
+export.PrintStatisticalMeasures(M2_ProcTime,'M2_ProcTime_StatResults.xls')
+
+export.PrintDistributionFit(M1_ProcTime,'M1_ProcTime_DistFitResults.xls')
+export.PrintDistributionFit(M2_ProcTime,'M2_ProcTime_DistFitResults.xls')
+
+#calls ManPy main script with the input
+simulationOutput=ManPyMain.main(input_data=json.dumps(data))
+# save the simulation output
+jsonFile = open('ManPyOutput.json',"w")     #It opens the JSON file
+jsonFile.write(simulationOutput)                                           #It writes the updated data to the JSON file 
+jsonFile.close()                                                                        #It closes the file
+