diff --git a/__pycache__/run.cpython-38.pyc b/__pycache__/run.cpython-38.pyc index 57839a2..1971646 100644 Binary files a/__pycache__/run.cpython-38.pyc and b/__pycache__/run.cpython-38.pyc differ diff --git a/frontend/src/components/Main.vue b/frontend/src/components/Main.vue index 3a0916b..fcfcd95 100755 --- a/frontend/src/components/Main.vue +++ b/frontend/src/components/Main.vue @@ -338,9 +338,9 @@ export default Vue.extend({ //EventBus.$emit('emittedEventCallingGridSelection', this.OverviewResults) EventBus.$emit('callValidationData', this.OverviewResults) EventBus.$emit('callValidation') - EventBus.$emit('LegendPredictEnsem') EventBus.$emit('callAlgorithhms') - + EventBus.$emit('LegendPredict') + EventBus.$emit('LegendPredictEnsem') } }) .catch(error => { @@ -447,9 +447,9 @@ export default Vue.extend({ .then(response => { this.PredictSel = response.data.PredictSel console.log('Server successfully sent the predictions!') - EventBus.$emit('emittedEventCallingGrid', this.storeBothEnsCM[0]) EventBus.$emit('SendSelectedPointsToServerEvent', this.PredictSel) + EventBus.$emit('LegendPredict') }) .catch(error => { console.log(error) @@ -494,6 +494,7 @@ export default Vue.extend({ console.log('Server successfully sent the predictions!') EventBus.$emit('emittedEventCallingGrid', this.storeBothEnsCM[1]) EventBus.$emit('SendSelectedPointsToServerEvent', this.PredictSelEnsem) + EventBus.$emit('LegendPredict') }) .catch(error => { console.log(error) diff --git a/run.py b/run.py index 62c7908..3f1ab60 100644 --- a/run.py +++ b/run.py @@ -1214,6 +1214,9 @@ def PreprocessingPredEnsemble(): yDataSortedFirst = [] yDataSortedLast = [] + ResultsGatheredFirst = [0,0,0,0,0,0,0] + ResultsGatheredLast = [0,0,0,0,0,0,0] + for index, item in enumerate(yData): if (item == 1): if (len(predictionsKNN[index]) != 0): @@ -1268,7 +1271,7 @@ def PreprocessingPredEnsemble(): predictionsGradB = ResultsGatheredFirst[5] + ResultsGatheredLast[5] yDataSorted = yDataSortedFirst + yDataSortedLast - return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions] + return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions, ResultsGatheredLast[6], ResultsGatheredFirst[6]] def PreprocessingParam(): dicKNN = allParametersPerformancePerModel[1] @@ -4082,6 +4085,9 @@ def PreprocessingPredCM(): yDataSortedFirst = [] yDataSortedLast = [] + ResultsGatheredFirst = [0,0,0,0,0,0,0] + ResultsGatheredLast = [0,0,0,0,0,0,0] + for index, item in enumerate(yData): if (item == 1): if (len(predictionsKNN[index]) != 0): @@ -4135,7 +4141,7 @@ def PreprocessingPredCM(): predictionsGradB = ResultsGatheredFirst[5] + ResultsGatheredLast[5] yDataSorted = yDataSortedFirst + yDataSortedLast - return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions] + return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions, ResultsGatheredLast[6], ResultsGatheredFirst[6]] def PreprocessingPredCMSecond(): dicKNNCC = allParametersPerfCrossMutr[3] @@ -4241,6 +4247,9 @@ def PreprocessingPredCMSecond(): yDataSortedFirst = [] yDataSortedLast = [] + ResultsGatheredFirst = [0,0,0,0,0,0,0] + ResultsGatheredLast = [0,0,0,0,0,0,0] + for index, item in enumerate(yData): if (item == 1): if (len(predictionsKNN[index]) != 0): @@ -4294,7 +4303,7 @@ def PreprocessingPredCMSecond(): predictionsGradB = ResultsGatheredFirst[5] + ResultsGatheredLast[5] yDataSorted = yDataSortedFirst + yDataSortedLast - return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions] + return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions, ResultsGatheredLast[6], ResultsGatheredFirst[6]] def PreprocessingParamCM(): dicKNNC = allParametersPerfCrossMutr[1] @@ -4903,6 +4912,9 @@ def PreprocessingPredSel(SelectedIDs): yDataSortedFirst = [] yDataSortedLast = [] + ResultsGatheredFirst = [0,0,0,0,0,0,0] + ResultsGatheredLast = [0,0,0,0,0,0,0] + for index, item in enumerate(yData): if (item == 1): if (len(predictionsKNN[index]) != 0): @@ -4956,7 +4968,7 @@ def PreprocessingPredSel(SelectedIDs): predictionsGradB = ResultsGatheredFirst[5] + ResultsGatheredLast[5] yDataSorted = yDataSortedFirst + yDataSortedLast - return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions] + return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions, ResultsGatheredLast[6], ResultsGatheredFirst[6]] @cross_origin(origin='localhost',headers=['Content-Type','Authorization']) @app.route('/data/SendtoSeverSelIDs', methods=["GET", "POST"]) @@ -5076,6 +5088,9 @@ def PreprocessingPredSelEnsem(SelectedIDsEnsem): yDataSortedFirst = [] yDataSortedLast = [] + ResultsGatheredFirst = [0,0,0,0,0,0,0] + ResultsGatheredLast = [0,0,0,0,0,0,0] + for index, item in enumerate(yData): if (item == 1): if (len(predictionsKNN[index]) != 0): @@ -5130,7 +5145,7 @@ def PreprocessingPredSelEnsem(SelectedIDsEnsem): predictionsGradB = ResultsGatheredFirst[5] + ResultsGatheredLast[5] yDataSorted = yDataSortedFirst + yDataSortedLast - return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions] + return [predictionsKNN, predictionsLR, predictionsMLP, predictionsRF, predictionsGradB, predictions, ResultsGatheredLast[6], ResultsGatheredFirst[6]] @cross_origin(origin='localhost',headers=['Content-Type','Authorization']) @app.route('/data/SendtoSeverSelIDsEnsem', methods=["GET", "POST"])