# Data Visualization NTNU 資料視覺化 ##### [Back to Note Overview](https://hackmd.io/@NTNUCSIE112/NTNUNote) {%hackmd @sophie8909/pink_theme %} ###### tags: `DV` <!-- tag順序 [課程] [學期][系 必選] or [學程 學程名(不含學程的 e.g. 大師創業)][學校] --> <!-- 記得加到 Note Overview --> ## Score ## Syllabus - 0908 - 00_Introduction(Syllabus) - 0915 - D3 - 01 Before D3 - VISUAL DESIGN - 01_Introduction - 02_WhatWhyHow - SCIVIS - 01 Scivis Introduction - 02 BasicVisAndParaview - 0922 - D3 - 02 Selecting & 03 Data Binding檔案 - VISUAL DESIGN - 03 MarkChannel <!-- - date - D3 - xxx - VISUAL DESIGN - xxx - SCIVIS - xxx --> ## Visual Design Note ### 02 What, Why, How ### 03 Mark Channel - Visual Encoding - Marks - Channels - Magnitude - Ordered Attributes - Identify - Categorical Attributes - Seoarability - Popout - Grouping - containment - connection - identity channels ## 04 Color ![](https://i.imgur.com/iFPWdN3.png) ![](https://i.imgur.com/mEatR2k.png) ## SCIVIS Note - ![](https://i.imgur.com/CmNTwXl.png) 1. yes 2. yes 3. yes 4. no - ![](https://i.imgur.com/M9hPeLY.png) - In some local space region, data values change a lot. But, data values in some other local regions do not. - more accurately represent the dataset values - ~~By using complex grid structure (e.g. curvlinear grid), It allows us not to store all data attributes (e.g. temperature, pressure...) at all grid points~~ - Save storage - S02-04: The user provides a dataset with the longitude and latitude of found meteorite. The user is interested in knowing which country has been hit most time by meteorites. What "actions" may need to complete the tasks? - S04-01: If you know values at vertices A, B, and C, which one is the correct equation to calculate the value at P (by interpolation)?![](https://i.imgur.com/POGkq1C.png) - S04-02: Calculate the value at P by interpolation? ![](https://i.imgur.com/EcEOkfG.png) ### 1027 - S07-03: Which statements are correct? - [x] Adjacency matrix can represent both network and tree structure dataset - [x] The order of row and column matters when using adjacency matrix - [ ] Treemap can represent network dataset - [x] Treemap cannot show the intermediate nodes - [ ] Adjacency matrix is good for path tracing in a network data - [ ] Node-link diagram has better scalability than adjacency matrix ### 1103 - S08-01: What are the differences between figures in each pair (from A and B)? The dataset in each pair is the same.![](https://i.imgur.com/kUjdOi4.png) - (A) order of marks (B) alignment point - S08-02: order user's expected response time of each action from short to long? 1. mouse over a mark and a tooltip popout 2. click on a mark to popout small window for detailed information 3. input a number in a dialog to update views in the visual tool #### SciVis - S08-01: We use the two transfer function to render the two images. Can you guess, the image at right-hand side is rendered by which transfer function (top or bottom?)![](https://i.imgur.com/pevU1IX.png) - bottom - S08-02: Match A B C D E F by the order of 0 1 2 3 4 5 ![](https://i.imgur.com/i9GL48R.png) - A: air - B: tissue - C: bone - D: aie and tissue boundary - E: tissue and bone boundary - F: air and bone boundary ### 1110 #### SciVis - S10-1: Match them by (A) (B) and (C) order. (each black curve is a path) ![](https://i.imgur.com/DgzIIaz.png) - (A) streakline - (B) timeline - (C) pathline - S10-02: If we have the a following vector field and release a particle at position [0.5, 0.5]. Use Euler's Method to trace the particle for 2 steps (set delta t to 1), answer the position after two steps. Red: vector on the grid point. Black: coordinate ![](https://i.imgur.com/AgbUww7.png)\] ### 1124 ![](https://i.imgur.com/dCnd02b.png) ## Note(Midterm) - VisualDesign: from the first week to 08_Manipulate - SciVis: from the first week to 10_VectorFieldVis-NumericalIntegration ### Visual Design #### 02 what 前面那個 what attribute type 分類可能有 應該是會有 // 02 07 loop which pro 02 16 data abs 02 26 which is what #### 03 mark 頻道 p12 channel 14 19 popout group point // 03 05~12 12's table 03 14 03 separ popout group #### 04 2/3 color 8 11 color map 12 reason poor 23 25 color map fit // 04 03 three part of color 04 08 match 04 11 color map reason 04 12 why rainbow poor 04 15 what is dis 04 20, 21 04 23 interaction 04 25 color map fit #### 05 read table fit what chart // 05 how to readm pro&cons #### 06 12 13/14 25 // 06 same as 05 #### 07 1/2/3 pros and cons 5 pros and cons 8 edge cross 36 tree map // 07 same as 05 #### 08 4 what 12 animatd transition what need 21 responsiveness // 08 same as 05, why animation, responsiveness ### SciVis #### 01 01 what data model look like, grid cell 01 14 struct grid pro&cons 01 20 different type #### 02 02 how to compute 10 #### 03 4 5 what is var cell ... 14 pros and cons // 03 how to compute, no hydr blablabla #### 04 要會算內插 #### 05 要會算 isovalue 應該不會要算isosurface 不會有什麼model那個 #### 06 #### 07 Back to front front to back #### 08 猜transfer function 的代表 17 20 // 08 transfer function, how to read 2d hist, boundry #### 09 四種line 算path // 09 vector field, ? #### 10 22 115 14