Configure in the GUI the URL for KE data

dream/platform/__init__.py

@@ -20,6 +20,7 @@
 import sys
 import argparse
 import json
+import urllib
 import xlrd
 import traceback
 import multiprocessing
@@ -148,41 +149,44 @@ def getConfigurationDict():
 def runKnowledgeExtraction():
   parameter_dict = request.json['json']
 
-  # TODO: really run knowledge extraction and change values:
-
-  workbook = xlrd.open_workbook('dream/KnowledgeExtraction/Mockup_ProcessingTimes.xls')      #Using xlrd library opens the Excel document with the input data 
-  worksheets = workbook.sheet_names()
-  worksheet_ProcessingTimes = worksheets[0]   #It defines the worksheet_ProcessingTimes as the first sheet of the Excel file
-
-  A=Import_Excel()            #Call the Import_Excel object 
-  B=DistFittest()             #Call the Distribution Fitting object
-  ProcessingTimes= A.Input_data(worksheet_ProcessingTimes, workbook)  #Create a dictionary with the imported data from the Excel file
-
-  data = parameter_dict                            #It loads the file
-  nodes = data['nodes'] 
-
-  lista=[]
-  for (element_id, element) in nodes.iteritems():  #This loop appends in a list the id's of the json file
-    element['id'] = element_id 
-    lista.append(element ['id'])
-
-  for element in ProcessingTimes:             #This loop searches the elements of the Excel imported data and if these elements exist in json file append the distribution fitting results in a dictionary   
-    if element in lista:
-      fitDict=B.ks_test(ProcessingTimes[element])
-      aParameter=fitDict.get('aParameter')
-      bParameter=fitDict.get('bParameter')
-      distributionType=fitDict.get('distributionType')
-      aParameterValue=fitDict.get('aParameterValue')
-      bParameterValue=fitDict.get('bParameterValue')
-      dictToAdd={}
-      dictToAdd['distributionType']=distributionType
-      if aParameter:
-        dictToAdd[aParameter]=aParameterValue
-      if bParameter:
-        dictToAdd[bParameter]=bParameterValue
-      print dictToAdd
-      parameter_dict['nodes'][element]['processingTime']=dictToAdd
-  return jsonify(parameter_dict)
+  try:
+    workbook = xlrd.open_workbook(
+        file_contents=urllib.urlopen(parameter_dict['general']['ke_url']).read())
+    worksheets = workbook.sheet_names()
+    worksheet_ProcessingTimes = worksheets[0]   #It defines the worksheet_ProcessingTimes as the first sheet of the Excel file
+
+    A=Import_Excel()            #Call the Import_Excel object 
+    B=DistFittest()             #Call the Distribution Fitting object
+    ProcessingTimes= A.Input_data(worksheet_ProcessingTimes, workbook)  #Create a dictionary with the imported data from the Excel file
+
+    data = parameter_dict                            #It loads the file
+    nodes = data['nodes'] 
+
+    lista=[]
+    for (element_id, element) in nodes.iteritems():  #This loop appends in a list the id's of the json file
+      element['id'] = element_id 
+      lista.append(element ['id'])
+
+    for element in ProcessingTimes:             #This loop searches the elements of the Excel imported data and if these elements exist in json file append the distribution fitting results in a dictionary   
+      if element in lista:
+        fitDict=B.ks_test(ProcessingTimes[element])
+        aParameter=fitDict.get('aParameter')
+        bParameter=fitDict.get('bParameter')
+        distributionType=fitDict.get('distributionType')
+        aParameterValue=fitDict.get('aParameterValue')
+        bParameterValue=fitDict.get('bParameterValue')
+        dictToAdd={}
+        dictToAdd['distributionType']=distributionType
+        if aParameter:
+          dictToAdd[aParameter]=aParameterValue
+        if bParameter:
+          dictToAdd[bParameter]=bParameterValue
+        parameter_dict['nodes'][element]['processingTime']=dictToAdd
+    return jsonify(dict(success=True, data=parameter_dict))
+  except Exception, e:
+    tb = traceback.format_exc()
+    app.logger.error(tb)
+    return jsonify(dict(error=tb))
 
 def main(*args):
   parser = argparse.ArgumentParser(description='Launch the DREAM simulation platform.')

dream/platform/static/src/dream.js

@@ -252,11 +252,8 @@
       that.prepareDialogForGeneralProperties();
     };
 
-    /** Runs the simulation, and call the callback with results once the
-     * simulation is finished.
-     */
-    that.runSimulation = function (callback) {
-      // handle Dream.General properties (in another function maybe ?)
+    that.readGeneralPropertiesDialog = function () {
+      // handle Dream.General properties
       var prefix = "General-",
         properties = {}, prefixed_property_id;
 
@@ -271,7 +268,13 @@
           }
         });
       that.setGeneralProperties(properties);
+    }
 
+    /** Runs the simulation, and call the callback with results once the
+     * simulation is finished.
+     */
+    that.runSimulation = function (callback) {
+      that.readGeneralPropertiesDialog()
       $.ajax(
           '../runSimulation', {
           data: JSON.stringify({
@@ -285,6 +288,24 @@
         });
     };
 
+    /** Runs the knowledge extraction, and call the callback with results once the
+     * KE is finished.
+     */
+    that.runKnowledgeExtraction = function (callback) {
+      that.readGeneralPropertiesDialog()
+      $.ajax(
+          '../runKnowledgeExtraction', {
+          data: JSON.stringify({
+            json: that.getData()
+          }),
+          contentType: 'application/json',
+          type: 'POST',
+          success: function (data, textStatus, jqXHR) {
+            callback(data);
+          }
+        });
+    };
+
     that.displayResult = function (idx) {
       var active_tab = $("#reports").data("ui-tabs") ?
         $("#reports").tabs("option", "active") : 0;

dream/platform/static/src/dream_launcher.js

@@ -156,27 +156,21 @@
     // Enable "Run Knowledge Extraction" button
     $("#run_knowledge_extraction").button().click(
       function (e) {
-        $("#run_knowledge_extraction").button('disable');
         $("#ke_loading_spinner").show();
-        $.ajax(
-          '../runKnowledgeExtraction', {
-            data: JSON.stringify({
-              json: dream_instance.getData()
-            }),
-            contentType: 'application/json',
-            type: 'POST',
-            success: function (data, textStatus, jqXHR) {
-              loadData(data);
-              $("#ke_loading_spinner").hide();
-              $("#run_knowledge_extraction").button('enable');
-            },
-            error: function() {
+        $("#run_knowledge_extraction").button('disable');
+        $('#error').empty();
+        dream_instance.runKnowledgeExtraction(
+          function(data) {
               $("#ke_loading_spinner").hide();
               $("#run_knowledge_extraction").button('enable');
-            }
-        });
-      }
-    )
+              if (data['success']) {
+                loadData(data.data);
+              } else {
+                $("#error").text(data["error"]).show().effect('shake', 50);
+                console.error(data['error'])
+              }
+            });
+      });
 
     // Enable "Run Simulation" button
     $("#run_simulation").button().click(

dream/simulation/GUI/Default.py

@@ -151,6 +151,17 @@ schema = {
     "_class": "Dream.Property",
     "_default": "",
   },
+  "ke_url": {
+    "id": "ke_url",
+    "name": "URL for Knowledge Extraction Spreadsheet",
+    "description": "The URL for knowledge extraction to access its data"
+                   " for example "
+                   "http://git.erp5.org/gitweb/dream.git/blob_plain/HEAD:/dream/KnowledgeExtraction/Mockup_ProcessingTimes.xls",
+    "type": "string",
+    "_class": "Dream.Property",
+    "_default":
+    "http://git.erp5.org/gitweb/dream.git/blob_plain/HEAD:/dream/KnowledgeExtraction/Mockup_ProcessingTimes.xls",
+  },
   "batchNumberOfUnits": {
     "id": "batchNumberOfUnits",
     "type": "number",
@@ -319,6 +330,7 @@ class Simulation(object):
            schema["currentDate"],
            schema["trace"],
            schema["seed"],
+           schema["ke_url"],
         ],
         "gui": {
           'debug_json': 1,