From be02bc148a0ea08d45fb15a5abbe51d05ebc8f3e Mon Sep 17 00:00:00 2001
From: Nanguage <Nanguage@yahoo.com>
Date: Mon, 16 Oct 2023 23:15:23 +0800
Subject: [PATCH] update dataset viewer layout

---
 public/plugins/viewer.imjoy.html | 50 ++++++++++++++++++++
 src/views/DatasetView.vue        | 80 ++++++++++++++++++++++++++------
 2 files changed, 117 insertions(+), 13 deletions(-)
 create mode 100644 public/plugins/viewer.imjoy.html

diff --git a/public/plugins/viewer.imjoy.html b/public/plugins/viewer.imjoy.html
new file mode 100644
index 0000000..7aed062
--- /dev/null
+++ b/public/plugins/viewer.imjoy.html
@@ -0,0 +1,50 @@
+<config lang="json">
+{
+    "name": "ufish",
+    "type": "web-python",
+    "tags": [],
+    "flags": [],
+    "ui": "",
+    "version": "0.1.0",
+    "cover": "",
+    "description": "Plugin for read and view tiff files",
+    "icon": "extension",
+    "inputs": null,
+    "outputs": null,
+    "api_version": "0.1.8",
+    "env": "",
+    "permissions": [],
+    "requirements": ["tifffile"],
+    "dependencies": []
+}
+</config>
+
+<script lang="python">
+import tifffile
+
+class Plugin():
+    async def setup(self):
+        api.log("ufish plugin setup")
+        self.viewer = await api.createWindow(
+            src="https://kaibu.org/#/app",
+            window_id="kaibu-container"
+        )
+        self.image = None
+
+    def load_image_from_bytes(self, file_name, img_bytes):
+        _file = io.BytesIO(img_bytes)
+        _file.name = file_name
+        with tifffile.TiffFile(_file) as tif:
+            image = tif.asarray()
+        self.image = image
+
+    async def view_img_from_bytes(self, file_name, bytes_):
+        image = self.load_image_from_bytes(file_name, bytes_)
+        await self.viewer.view_image(image, name=file_name)
+        return image.shape
+
+    async def run(self, ctx):
+        pass
+
+api.export(Plugin())
+</script>
diff --git a/src/views/DatasetView.vue b/src/views/DatasetView.vue
index d87c6cd..36ecb0e 100644
--- a/src/views/DatasetView.vue
+++ b/src/views/DatasetView.vue
@@ -4,10 +4,29 @@
     Number of images: {{ csvData?.length }},
     spots: {{ csvData?.reduce((acc, cur) => acc + parseInt(cur.num_spots), 0) }}
   </div>
-  <div id="umap-container"></div>
-  <div id="viewer-container">
-    <div id="kaibu-container"></div>
-  </div>
+  <v-card id="viewer-container">
+    <v-card id="umap-card">
+      <div id="umap-container"></div>
+
+      <v-overlay
+        v-model="umapOverlay"
+        contained
+        class="align-center justify-center"
+      >
+        <v-progress-circular indeterminate color="primary"></v-progress-circular>
+      </v-overlay>
+    </v-card>
+    <v-card id="kaibu-card">
+      <div id="kaibu-container"></div>
+      <v-overlay
+        v-model="kaibuOverlay"
+        contained
+        class="align-center justify-center"
+      >
+        <v-progress-circular indeterminate color="primary"></v-progress-circular>
+      </v-overlay>
+    </v-card>
+  </v-card>
   <div class="text-panel">
     All data can be downloaded from <a href="https://huggingface.co/datasets/GangCaoLab/FISH_spots">this HuggingFace🤗 repo</a>!
   </div>
@@ -33,8 +52,19 @@ export default {
     umapCSVUrl: window.location.origin + "/data/dataset_umap.csv",
     csvData: null as Array<UMAPData> | null,
     viewer: null as any,
+    imgBaseURL: "https://huggingface.co/datasets/NaNg/TestData/resolve/main/FISH_spots/",
+    csvBaseURL: "https://huggingface.co/datasets/NaNg/TestData/resolve/main/FISH_spots/",
   }),
 
+  computed: {
+    kaibuOverlay() {
+      return this.viewer === null
+    },
+    umapOverlay() {
+      return this.csvData === null
+    }
+  },
+
   mounted() {
     this.loadUMAPCSV()
     this.loadViewer()
@@ -59,6 +89,24 @@ export default {
       }
     },
 
+    async onClickPoint(data: any) {
+      if (this.viewer === null) {
+        return
+      } else {
+        const point = data.points[0];
+        const imgName = point.text.split("<br>")[0].split(":</b> ")[1]
+        console.log(`You clicked on point: ${imgName} at position (x: ${point.x}, y: ${point.y})`)
+        //const imgURL = this.imgBaseURL + imgName
+        //await this.viewer.view_image(imgURL, { name: imgName, type: 'itk-vtk' })
+        const csvName = imgName.replace(".tif", ".csv")
+        const csvURL = this.csvBaseURL + csvName
+        const csvContent = await fetch(csvURL).then(resp => resp.text())
+        const csvData = csv.toObjects(csvContent)
+        const points = csvData.map((d: any) => [d['axis-0'], d['axis-1']])
+        await this.viewer.add_points(points, { name: csvName })
+      }
+    },
+
     async renderUMAP() {
       const data = this.csvData!
       const traces = {} as any
@@ -103,10 +151,7 @@ export default {
 
       const umapPlot = document.getElementById('umap-container') as any;
       
-      umapPlot.on('plotly_click', function(data: any){
-        const point = data.points[0];
-        alert(`You clicked on point at position (x: ${point.x}, y: ${point.y})`);
-      })
+      umapPlot.on('plotly_click', this.onClickPoint)
     }
   },
 
@@ -122,19 +167,28 @@ export default {
 </script>
 
 <style scoped>
+#umap-card {
+  width: 50%;
+  min-width: 400px;
+}
 #umap-container {
-  width: 70%;
-  min-width: 600px;
-  height: 800px;
+  height: 600px;
+}
+#kaibu-card {
+  width: 50%;
+  min-width: 400px;
 }
 #kaibu-container {
-  width: 90%;
+  width: 100%;
   height: 600px;
+  overflow: auto;
+  resize: both;
 }
 #viewer-container {
-  width: 100%;
+  width: 90%;
   display: flex;
   justify-content: center;
+  flex-wrap: wrap;
 }
 .text-panel {
   margin-top: 20px;