Merge pull request #67 from cinxdy/master

[FEAT] Implement my analysis Backend & Service module & Click button …

fe-backend/models/myAnalysis.js

@@ -0,0 +1,14 @@
+const mongoose = require("mongoose");
+const Schema = mongoose.Schema;
+const chartSchema = new Schema({
+  userEmail: String,
+  keyword: String,
+  savedDate: Date,
+  analysisDate: Date,
+  chartImg: String,
+  activity: String,
+  jsonDocId: Number,
+},{collection: 'myAnalysis'});
+
+const conn = require("../connection/textMiningConn");
+module.exports = conn.model("myAnalysis", chartSchema);

fe-backend/module/textMiningQuery.js

@@ -5,11 +5,11 @@ const router = express.Router();
 
 router.post("/uploadDict", uploadDict);
 router.post("/getPreprocessedData",getPreprocessedData);
+router.post("/uploadChart", uploadChart);
 
 const usersDict = require("../models/usersDict");
 const preprocessing = require("../models/preprocessing");
-
-
+const myAnalysis = require("../models/myAnalysis");
 
 async function uploadDict(req, res) {
     let userEmail = req.body.userEmail;
@@ -71,5 +71,44 @@ async function uploadDict(req, res) {
           .json(new Res(false, "successfully saved doc HashKeys", null));
       });
   }
+
+  async function uploadChart(req, res) {
+    if(req.body.userEmail == null  || req.body.chartImg == null) 
+    return res.status(400).json(
+      new Res(false, "Request body does not exist",null)
+    );
+
+    // console.log('req',req);
+    // let doc = {
+    //   'userEmail': req.body.userEmail,
+    //   'keyword': req.body.keyword,
+    //   'savedDate': req.body.savedDate,
+    //   'analysisDate': req.body.savedDate,
+    //   'chartImg': req.body.chartImg,
+    //   'activity': req.body.activity,
+    //   'jsonDocId': req.body.jsonDocId,
+    // };
+    let doc=req.body;
+
+    myAnalysis.findOneAndUpdate(
+      { $and: [{ userEmail: req.body.userEmail },{ analysisDate: req.body.analysisDate},]},
+        {"$set":doc},
+        { upsert: true, returnNewDocument: true }
+      ).then((result)=>{
+          console.log("successfully uploaded");
+          return res
+            .status(200)
+            .json(
+              new Res(true, "successfully uploaded",null)
+            );
+      }).catch((err) => {
+        console.log(err);
+        return res
+          .status(400)
+          .json(
+            new Res(false, "Upload to mongo DB Failed",null)
+          );;
+      });
+  }
 
 module.exports = router;

package.json

@@ -51,6 +51,7 @@
     "react-modal": "^3.14.3",
     "rxjs": "~6.6.3",
     "rxjs-compat": "^6.6.3",
+    "save-svg-as-png": "^1.4.17",
     "sunburst-chart": "^1.11.2",
     "tslib": "^2.0.3",
     "uikit": "^3.6.5",

src/app/features/article-analysis/components/analysis/analysis.component.html

@@ -149,7 +149,11 @@
   <figure id="scatter"></figure>
   <figure id="tree"></figure>
   <figure id="ldavis"></figure>
-  </section>
+
+  <button (click)="saveSvg()" *ngIf="isDataAnalysised">분석함 저장</button>
+  <button (click)="downloadPng()" *ngIf="isDataAnalysised">차트 이미지 다운로드</button>
+
+</section>
 
   </section>
 </div>