final adjustments of plotting, panles, etc.

Projects/Superalgos/Plugins/Learning-Mines/Masters.json

@@ -1 +1 @@
-{"type":"Learning Mine","name":"Masters","config":"{ \n\"codeName\": \"Masters\"\n}","project":"Superalgos","learningBots":[{"type":"Learning Bot","name":"Low Frequency","config":"{\n\"codeName\": \"Low-Frequency\"\n}","project":"Superalgos","processes":[{"type":"Process Definition","name":"Learning","config":"{\n    \"codeName\": \"Learning\",\n    \"sessionRunWaitTime\": 5000,\n    \"retryWaitTime\": 10000,\n    \"framework\": {\n      \"name\": \"Low-Frequency-Learning-Process\"\n    }\n  }","project":"Superalgos","processOutput":{"type":"Process Output","name":"New Process Output","project":"Superalgos","outputDatasets":[],"outputDatasetFolders":[{"type":"Output Dataset Folder","name":"Learning Engine","project":"Superalgos","outputDatasets":[],"outputDatasetFolders":[{"type":"Output Dataset Folder","name":"Learning Episode","project":"Superalgos","outputDatasets":[{"type":"Output Dataset","name":"Multi-Period-Market Learning Episode Counters","project":"Superalgos","id":"c0de6b69-60e2-4574-890a-35743f75c569","savedPayload":{"position":{"x":10770.578330127608,"y":18237.318563914418},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"ac1bc967-9c9f-47f0-8815-535abd7cb777"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Learning Episode Counters","project":"Superalgos","id":"da23a8ff-8b3d-4caa-a27c-f59352911212","savedPayload":{"position":{"x":10647.18050284652,"y":18202.991870096994},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Daily","id":"6881069e-a4d1-4b41-892f-557d2031adea"}}},{"type":"Output Dataset","name":"Multi-Period-Market Learning Episode Statistics","project":"Superalgos","id":"dfdcb71e-c123-429e-bc2d-cf33963378d6","savedPayload":{"position":{"x":10538.452101828116,"y":18135.29046318318},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"8408c316-e04d-4b0d-8c81-1bf3b4126894"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Learning Episode Statistics","project":"Superalgos","id":"fa9e000d-199c-4ed4-b10f-6c586bfc2fa5","savedPayload":{"position":{"x":10453.201655490207,"y":18039.69910852537},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Daily","id":"553a0b49-2a61-41c4-ac95-f762051c1cab"}}},{"type":"Output Dataset","name":"Multi-Period-Market Episode Candle","project":"Superalgos","id":"a9a7b1fe-ecff-4d08-bd3b-297e4263c703","savedPayload":{"position":{"x":10398.335647991167,"y":17923.962049174253},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"a08a3974-75ac-4a2b-bc09-f80547a61381"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Episode Candle","project":"Superalgos","id":"d80bea92-bca6-4826-aa32-34bc7c13f952","savedPayload":{"position":{"x":10378.298996957856,"y":17797.455613363665},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Daily","id":"46221186-fff7-4333-a087-a32a649e9ce8"}}},{"type":"Output Dataset","name":"Multi-Period-Market Distance To Learning Event","project":"Superalgos","id":"0b8ef0c4-c7a9-48cf-9f9b-e48d32f5ed27","savedPayload":{"position":{"x":10394.71495269444,"y":17670.42860016024},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"0d746a41-6726-41fd-9312-862b6835b8ba"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Distance To Learning Event","project":"Superalgos","id":"a8951035-4bf1-4d0d-8666-879b2c481b6d","savedPayload":{"position":{"x":10446.25359209659,"y":17553.171982714983},"targetPosition":{"x":10828.2531163121,"y":177Line truncated
+{"type":"Learning Mine","name":"Masters","config":"{ \n\"codeName\": \"Masters\"\n}","project":"Superalgos","learningBots":[{"type":"Learning Bot","name":"Low Frequency","config":"{\n\"codeName\": \"Low-Frequency\"\n}","project":"Superalgos","processes":[{"type":"Process Definition","name":"Learning","config":"{\n    \"codeName\": \"Learning\",\n    \"sessionRunWaitTime\": 5000,\n    \"retryWaitTime\": 10000,\n    \"framework\": {\n      \"name\": \"Low-Frequency-Learning-Process\"\n    }\n  }","project":"Superalgos","processOutput":{"type":"Process Output","name":"New Process Output","project":"Superalgos","outputDatasets":[],"outputDatasetFolders":[{"type":"Output Dataset Folder","name":"Learning Engine","project":"Superalgos","outputDatasets":[],"outputDatasetFolders":[{"type":"Output Dataset Folder","name":"Learning Episode","project":"Superalgos","outputDatasets":[{"type":"Output Dataset","name":"Multi-Period-Market Learning Episode Counters","project":"Superalgos","id":"c0de6b69-60e2-4574-890a-35743f75c569","savedPayload":{"position":{"x":10770.578330127608,"y":18237.318563914418},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"ac1bc967-9c9f-47f0-8815-535abd7cb777"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Learning Episode Counters","project":"Superalgos","id":"da23a8ff-8b3d-4caa-a27c-f59352911212","savedPayload":{"position":{"x":10647.18050284652,"y":18202.991870096994},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Daily","id":"6881069e-a4d1-4b41-892f-557d2031adea"}}},{"type":"Output Dataset","name":"Multi-Period-Market Learning Episode Statistics","project":"Superalgos","id":"dfdcb71e-c123-429e-bc2d-cf33963378d6","savedPayload":{"position":{"x":10538.452101828116,"y":18135.29046318318},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"8408c316-e04d-4b0d-8c81-1bf3b4126894"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Learning Episode Statistics","project":"Superalgos","id":"fa9e000d-199c-4ed4-b10f-6c586bfc2fa5","savedPayload":{"position":{"x":10453.201655490207,"y":18039.69910852537},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Daily","id":"553a0b49-2a61-41c4-ac95-f762051c1cab"}}},{"type":"Output Dataset","name":"Multi-Period-Market Episode Candle","project":"Superalgos","id":"a9a7b1fe-ecff-4d08-bd3b-297e4263c703","savedPayload":{"position":{"x":10398.335647991167,"y":17923.962049174253},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"a08a3974-75ac-4a2b-bc09-f80547a61381"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Episode Candle","project":"Superalgos","id":"d80bea92-bca6-4826-aa32-34bc7c13f952","savedPayload":{"position":{"x":10378.298996957856,"y":17797.455613363665},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Daily","id":"46221186-fff7-4333-a087-a32a649e9ce8"}}},{"type":"Output Dataset","name":"Multi-Period-Market Distance To Learning Event","project":"Superalgos","id":"0b8ef0c4-c7a9-48cf-9f9b-e48d32f5ed27","savedPayload":{"position":{"x":10394.71495269444,"y":17670.42860016024},"targetPosition":{"x":10828.2531163121,"y":17791.02984678326},"floatingObject":{"isPinned":false,"isFrozen":false,"isCollapsed":false,"angleToParent":2,"distanceToParent":3,"arrangementStyle":0},"uiObject":{},"referenceParent":{"type":"Dataset Definition","name":"Multi-Period-Market","id":"0d746a41-6726-41fd-9312-862b6835b8ba"}}},{"type":"Output Dataset","name":"Multi-Period-Daily Distance To Learning Event","project":"Superalgos","id":"a8951035-4bf1-4d0d-8666-879b2c481b6d","savedPayload":{"position":{"x":10446.25359209659,"y":17553.171982714983},"targetPosition":{"x":10828.2531163121,"y":177Line truncated

Projects/Superalgos/TS/Bot-Modules/Learning-Bot/Low-Frequency-Learning/LearningRecords.js

@@ -45,10 +45,6 @@ exports.newSuperalgosBotModulesLearningRecords = function (processIndex) {
             let product = dataset.parentNode
             let outputDatasetArray = outputDatasetsMap.get(product.config.codeName)
 
-            if (product.config.codeName === 'Predictions') {
-                let a = 1
-            }
-
             if (TS.projects.superalgos.globals.processVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).TRADING_PROCESSING_DAILY_FILES === true && dataset.config.type === 'Daily Files') {
                 persistRecords()
             }

Projects/Superalgos/UI/Function-Libraries/LearningSessionFunctions.js

@@ -119,6 +119,8 @@ function newSuperalgosFunctionLibraryLearningSessionFunctions() {
             'Serial Number->Identifier->Begin->End->Begin Rate->End Rate->Strategy Name->Status->Exit Type->' +
             'Balance->Begin Balance->End Balance->' +
             'Index->Situation Name->Formula->Periods->' + 
+            'Features->Feature->Begin->End->Feature Value->'+ 
+            'Labels->Label->Begin->End->Label Value->'+ 
             'Predictions->Prediction->Begin->End->Prediction Value->'
 
         let learningEngine = UI.projects.superalgos.functionLibraries.protocolNode.getProtocolNode(node.learningEngineReference.payload.referenceParent, false, true, true, false, false, lightingPath)

Projects/Superalgos/UI/Spaces/Panel-Space/PlotterPanel.js

@@ -3,7 +3,7 @@ function newPlotterPanel() {
     const MODULE_NAME = 'Plotter Panel'
     const ERROR_LOG = true
     const logger = newWebDebugLog()
-    
+
 
     let thisObject = {
         fitFunction: undefined,
@@ -23,6 +23,7 @@ function newPlotterPanel() {
     let currentRecord
     let upDownButton
     let panelNode
+    let recordSet = new Map()
 
     return thisObject
 
@@ -34,6 +35,7 @@ function newPlotterPanel() {
 
         heightFactor = undefined
         currentRecord = undefined
+        recordSet = undefined
         upDownButton.finalize()
         upDownButton = undefined
         panelNode = undefined
@@ -79,6 +81,20 @@ function newPlotterPanel() {
 
     function onRecordChange(pCurrentRecord) {
         currentRecord = pCurrentRecord
+
+        if (currentRecord === undefined) {
+            recordSet = new Map()
+            return
+        }
+        if (currentRecord.index !== undefined) {
+            /*
+            There is a situation when we expect to receive many records
+            that are part of a set. We will know when when we detect the 
+            property index. In that situation we will build the recordset 
+            by adding each record to a Map by index.
+            */
+            recordSet.set(currentRecord.index, currentRecord)
+        }
     }
 
     function draw() {