from walnutclient import * #objWalnutClient= walnutclient(5001,'localhost',selProject.ModelMap.RawXML) strDataFolder = "/home/chandan/chandan/code/brainscience/" strRootFolder = "/home/chandan/chandan/code/brainscience/" strAppFolder = "curious/" strModelFolder = 'curiousWorkbench/test/models/' strModelFile = 'model1.txt' strDataFile ='Test_003_1_WordList.csv' inputModelFile = strRootFolder + strAppFolder + strModelFolder + strModelFile strInputDataFile = strDataFolder + strDataFile fo = open(inputModelFile,'r') strRawModelXML = fo.read() objwalnutclient = walnutclient(5001, 'localhost',strRawModelXML ) runValue = objwalnutclient.runNetworkWithFile(strInputDataFile, 'CSV',True,False,False,True) print runValue['returnValue']
def getWalnutResponse(self, trainValue):
strRawModelXML = self.getModelFile()
objWalnutClient= walnutclient(5001,'localhost',strRawModelXML)
runValue = objWalnutClient.runNetworkWithValue(trainValue, False,False,False,True)
return runValue
def trainProject(request, project_id):
dataFileList = DataFile.objects.order_by('-LastUpdated')
strMsg = ""
selProject=get_object_or_404(Project, pk=project_id)
objWalnutClient= walnutclient(5001,'localhost',selProject.ModelMap.RawXML)
if 'trainForValue' in request.POST:
trainValue=request.POST["txtTrain"]
if trainValue.strip() !='':
runValueList=None
modelMap = selProject.ModelMap
runValue = objWalnutClient.runNetworkWithValue(trainValue, False,False,False,True)
predictionGraph = runValue["PredictionGraph"]
#FormattedReturn=formatPrediction(0, returnValue)
template = loader.get_template('curiousWorkbench/trainProject.html')
predictionGraphImagePath = drawPredictionGraph(predictionGraph)
context = RequestContext(request, {
'project' : selProject,
'modelMap': modelMap,
'runValue':runValue["returnValue"],
'strMsg':runValue["strMsg"],
'predictionGraphImagePath':predictionGraphImagePath,
'dataFileList': dataFileList,
})
else:
modelMap = selProject.ModelMap
template = loader.get_template('curiousWorkbench/trainProject.html')
context = RequestContext(request, {
'project' : selProject,
'modelMap': modelMap,
'runValue':'',
'strMsg':'',
'predictionGraphImagePath':'',
'dataFileList': dataFileList,
})
elif 'trainWithFile' in request.POST:
if request.POST["rdoDataFile"] != "0":
trainValueFile=request.POST["rdoDataFile"]
runValue = objWalnutClient.runNetworkWithFile(trainValueFile,'CSV',True,False,False,True)
else:
runValue = {"returnValue":"No File Selected","strMsg":""}
selProject=get_object_or_404(Project, pk=project_id)
modelMap = selProject.ModelMap
template = loader.get_template('curiousWorkbench/trainProject.html')
context = RequestContext(request, {
'project' : selProject,
'modelMap': modelMap,
'runValue':runValue['returnValue'],
'strMsg':runValue['strMsg'],
'dataFileList': dataFileList
})
elif 'resetProject' in request.POST:
returnV = objWalnutClient.resetTraining()
#objNetwork = Network()
#objNetwork.resetTraining(project_id)
selProject=get_object_or_404(Project, pk=project_id)
modelMap = selProject.ModelMap
template = loader.get_template('curiousWorkbench/trainProject.html')
context = RequestContext(request, {
'project' : selProject,
'modelMap': modelMap,
'runValue':"--",
'strMsg':"",
'dataFileList': dataFileList
})
else:
selProject=get_object_or_404(Project, pk=project_id)
modelMap = selProject.ModelMap
template = loader.get_template('curiousWorkbench/trainProject.html')
context = RequestContext(request, {
'project' : selProject,
'modelMap': modelMap,
'runValue':"--",
'strMsg':"",
'dataFileList': dataFileList,
})
return HttpResponse(template.render(context))