def POST(self):
expType = web.input()["type"]
name = web.input()["name"]
cerebro = CerebroModel.get()
cerebro.name = name
results = cerebro.runCurrentExperiment(expType, True)
return json.dumps(results)
def POST(self):
""" Get information about the current model at a specific timestep"""
cerebro = CerebroModel.get()
dataInput = dict(web.input())
data = cerebro.getDataAtTime(dataInput)
web.header("Content-Type", "application/json")
return json.dumps(data)
def POST(self):
expType = web.input()["type"]
name = web.input()["name"]
cerebro = CerebroModel.get()
cerebro.name = name
results = cerebro.runCurrentExperiment(expType, True)
return json.dumps(results)
def POST(self):
""" Get information about the current model at a specific timestep"""
cerebro = CerebroModel.get()
dataInput = dict(web.input())
data = cerebro.getDataAtTime(dataInput)
web.header("Content-Type", "application/json")
return json.dumps(data)
def POST(self):
""" Create a dataset from a function """
cerebro = CerebroModel.get()
fnText = web.input()["text"]
iterations = int(web.input()["iterations"])
cerebro.createProceduralDataset(fnText, iterations)
modelDesc = cerebro.getCurrentModelParams()
return pprint.pformat(modelDesc['modelParams'])
def POST(self):
""" Create a dataset from a function """
cerebro = CerebroModel.get()
fnText = web.input()["text"]
iterations = int(web.input()["iterations"])
cerebro.createProceduralDataset(fnText, iterations)
modelDesc = cerebro.getCurrentModelParams()
return pprint.pformat(modelDesc["modelParams"])
def GET(self):
""" FIXME: Right now, this returns the csv as a text file, so that the user
can use the "save file as" button """
cerebro = CerebroModel.get()
text = cerebro.getDescriptionText()
web.header("Content-Type", "text/plain")
web.header("Content-Disposition", "attachment; filename=description.py")
return text
def GET(self):
""" FIXME: Right now, this returns the csv as a text file, so that the user
can use the "save file as" button """
cerebro = CerebroModel.get()
text = cerebro.getDatasetText()
web.header("Content-Type", "text/plain")
web.header('Content-Disposition', "attachment; filename=data.csv")
return text
def POST(self):
""" Load a dataset/model from a description.py """
cerebro = CerebroModel.get()
params = web.input()
cerebro.loadDescriptionFile(
descriptionFile=params["experimentFile"],
subDescriptionFile=params["subExperimentFile"])
modelDesc = cerebro.getCurrentModelParams()
return pprint.pformat(modelDesc['modelParams'])
def POST(self):
""" Load a dataset/model from a description.py """
cerebro = CerebroModel.get()
params = web.input()
cerebro.loadDescriptionFile(
descriptionFile=params["experimentFile"], subDescriptionFile=params["subExperimentFile"]
)
modelDesc = cerebro.getCurrentModelParams()
return pprint.pformat(modelDesc["modelParams"])
def POST(self):
cerebro = CerebroModel.get()
returnData = json.dumps(cerebro.getLatestPredictions())
web.header("Content-Type", "application/json")
return returnData
def POST(self):
cerebro = CerebroModel.get()
cerebro.stopCurrentExperiment()
return ""
def POST(self):
newThreshold = web.input()["threshold"]
cerebro = CerebroModel.get()
results = cerebro.setClassifierThreshold(newThreshold)
return json.dumps(results)
def POST(self):
newThreshold = web.input()["threshold"]
cerebro = CerebroModel.get()
results = cerebro.setClassifierThreshold(newThreshold)
return json.dumps(results)
def POST(self):
cerebro = CerebroModel.get()
params = eval(web.input()['params'])
cerebro.setModelParams(params)
return
def POST(self):
cerebro = CerebroModel.get()
params = eval(web.input()["params"])
cerebro.setModelParams(params)
return
def POST(self):
cerebro = CerebroModel.get()
cerebro.stopCurrentExperiment()
return ""
def POST(self):
cerebro = CerebroModel.get()
returnData = json.dumps(cerebro.getLatestPredictions())
web.header("Content-Type", "application/json")
return returnData
def POST(self):
""" Save the currently used mongoDB for use later """
name = web.input()["name"]
cerebro = CerebroModel.get()
results = cerebro.setExperimentName(name)
return json.dumps(results)
def POST(self):
cerebro = CerebroModel.get()
predictedFieldname = web.input()['fieldname']
cerebro.setPredictedField(fieldname=predictedFieldname)
return ""
def POST(self):
""" Save the currently used mongoDB for use later """
name = web.input()["name"]
cerebro = CerebroModel.get()
results = cerebro.setExperimentName(name)
return json.dumps(results)
def POST(self):
cerebro = CerebroModel.get()
predictedFieldname = web.input()["fieldname"]
cerebro.setPredictedField(fieldname=predictedFieldname)
return ""
