예제 #1
0
        /// <summary>
        /// Using supplied 'Raster' data it will call each currently active model and return there predictions.
        /// </summary>
        /// <param name="raster">Raster of image to predict. .</param>
        /// <param name="instrumentData">Instrument data that was recorded with the 'raster' .</param>
        /// <param name="imageFileName">Name of the image file.</param>
        /// <param name="model1Predictions">The model1 predictions.</param>
        /// <param name="model2Predictions">The model2 predictions.</param>
        /// <param name="runLog">The run log.</param>
        public static void  MakePredictions(PicesRaster raster,
                                            InstrumentData instrumentData,
                                            String imageFileName,
                                            ref PicesPredictionList model1Predictions,
                                            ref PicesPredictionList model2Predictions,
                                            PicesRunLog runLog
                                            )
        {
            model1Predictions = null;
            model2Predictions = null;
            if (!ModelsAreAvailable())
            {
                return;
            }

            ParsedImageFileName pifn = PicesFeatureVector.ParseImageFileName(imageFileName);
            String sipperFileName    = pifn.sipperFileName;
            uint   scanLineNum       = pifn.scanLineNum;

            PicesFeatureVector fv = new PicesFeatureVector(raster, imageFileName, null, runLog);

            if (instrumentData != null)
            {
                fv.AddInstrumentData(instrumentData.Depth(),
                                     instrumentData.Salinity(),
                                     instrumentData.Oxygen(),
                                     instrumentData.Fluorescence()
                                     );
            }
            else
            {
                PicesDataBase       dbConn = PicesDataBase.GetGlobalDatabaseManagerNewInstance(runLog);
                PicesInstrumentData pid    = dbConn.InstrumentDataGetByScanLine(sipperFileName, scanLineNum);
                if (pid != null)
                {
                    fv.AddInstrumentData(pid);
                }
                pid = null;
                dbConn.Close();
                dbConn = null;
            }

            if (model1 != null)
            {
                model1Predictions = model1.PredictProbabilities(fv);
            }

            if (model2 != null)
            {
                model2Predictions = model2.PredictProbabilities(fv);
            }

            fv = null;

            return;
        } /* MakePredictions */
예제 #2
0
        } /* MakePredictions */

        public static void  MakePredictions(PicesRaster raster,
                                            ref PicesPrediction model1Prediction1,
                                            ref PicesPrediction model1Prediction2,
                                            ref PicesPrediction model2Prediction1,
                                            ref PicesPrediction model2Prediction2,
                                            PicesRunLog runLog
                                            )
        {
            String imageFileName = raster.FileName;

            ParsedImageFileName pifn = PicesFeatureVector.ParseImageFileName(imageFileName);
            String sipperFileName    = pifn.sipperFileName;
            uint   scanLineNum       = pifn.scanLineNum;

            PicesFeatureVector fv = new PicesFeatureVector(raster, imageFileName, null, runLog);

            {
                PicesDataBase       dbConn = PicesDataBase.GetGlobalDatabaseManagerNewInstance(runLog);
                PicesInstrumentData pid    = dbConn.InstrumentDataGetByScanLine(sipperFileName, scanLineNum);
                if (pid != null)
                {
                    fv.AddInstrumentData(pid);
                }
                pid = null;
                dbConn.Close();
                dbConn = null;
            }

            MakePredictions(fv,
                            ref model1Prediction1,
                            ref model1Prediction2,
                            ref model2Prediction1,
                            ref model2Prediction2,
                            runLog
                            );
            fv = null;
        }