├── babel.config.js
├── precision_recall_accuracy.png
├── .editorconfig
├── vue.config.js
├── .eslintrc.js
├── .gitignore
├── TODO.md
├── src
    ├── main.js
    ├── levels.js
    ├── App.vue
    ├── predictions.js
    ├── components
    │   ├── ConfusionTable.vue
    │   ├── ConfusedTile.vue
    │   ├── Chart.vue
    │   ├── ConfusionTableVisually.vue
    │   └── QuantityVisually.vue
    ├── datasets.js
    ├── metrics.js
    ├── All.vue
    └── Level.vue
├── LICENSE
├── package.json
├── README.md
├── notebooks
    └── sklearn_classifier_comparison.ipynb
└── assets
    └── datasets
        └── all.json


/babel.config.js:
--------------------------------------------------------------------------------
1 | module.exports = {
2 |   presets: [
3 |     '@vue/app'
4 |   ]
5 | }
6 | 


--------------------------------------------------------------------------------
/precision_recall_accuracy.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/stared/which-ml-are-you/HEAD/precision_recall_accuracy.png


--------------------------------------------------------------------------------
/.editorconfig:
--------------------------------------------------------------------------------
1 | [*.{js,jsx,ts,tsx,vue}]
2 | indent_style = space
3 | indent_size = 2
4 | trim_trailing_whitespace = true
5 | insert_final_newline = true
6 | 


--------------------------------------------------------------------------------
/vue.config.js:
--------------------------------------------------------------------------------
1 | module.exports = {
2 |   lintOnSave: true,
3 |   runtimeCompiler: true,
4 |   baseUrl: process.env.NODE_ENV === 'production'
5 |     ? '/which-ml-are-you/'
6 |     : '/'
7 | };
8 | 


--------------------------------------------------------------------------------
/.eslintrc.js:
--------------------------------------------------------------------------------
 1 | module.exports = {
 2 |   extends: [
 3 |     'eslint:recommended',
 4 |     'plugin:vue/recommended'
 5 |   ],
 6 |   rules: {
 7 |     // override/add rules settings here, such as:
 8 |     // 'vue/no-unused-vars': 'error'
 9 |     // "semi": ["error", "always"],
10 |   }
11 | }
12 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
 1 | .DS_Store
 2 | node_modules
 3 | /dist
 4 | 
 5 | # local env files
 6 | .env.local
 7 | .env.*.local
 8 | 
 9 | # Log files
10 | npm-debug.log*
11 | yarn-debug.log*
12 | yarn-error.log*
13 | 
14 | # Editor directories and files
15 | .idea
16 | .vscode
17 | *.suo
18 | *.ntvs*
19 | *.njsproj
20 | *.sln
21 | *.sw*
22 | 


--------------------------------------------------------------------------------
/TODO.md:
--------------------------------------------------------------------------------
 1 | # TODO
 2 | 
 3 | ## TODO
 4 | 
 5 | - [x] Dataset scale
 6 | - [ ] Mouseover etc
 7 | - [ ] Modularize predicted classes
 8 | - [ ] Train and validation
 9 | - [ ] More datasets (Iris)
10 | - [ ] Compare to algorithms
11 | - [ ] Level progression (now level selection is fine-ish)
12 | 
13 | ## Recently accomplished
14 | 
15 | - [x] Data loading
16 | - [x] Graphical false positive and negative
17 | 
18 | ## Also consider
19 | 
20 | - [ ] Maybe "Confusion Matrix Metrics" is worth a post on its own
21 | - [ ] Dropdown with https://mikerodham.github.io/vue-dropdowns/
22 | - [ ] Algorithms inside JS
23 | - [ ] Also a variant with ROC and AP curves
24 | 


--------------------------------------------------------------------------------
/src/main.js:
--------------------------------------------------------------------------------
 1 | import Vue from 'vue'
 2 | import App from './App.vue'
 3 | import All from './All.vue'
 4 | import Level from './Level.vue'
 5 | import VueRouter from 'vue-router'
 6 | 
 7 | Vue.config.productionTip = false
 8 | 
 9 | Vue.use(VueRouter);
10 | 
11 | const router = new VueRouter({
12 |   routes: [
13 |     { path: '/', component: All },
14 |     { path: '/lvl/:id', component: Level, props: true },
15 |     {
16 |       path: '*',
17 |       component: {
18 |         render (h) { return h('div', '404. Not Found.') }
19 |       }
20 |     }
21 |   ]
22 | });
23 | 
24 | new Vue({
25 |   router,
26 |   render: h => h(App)
27 | }).$mount('#app');
28 | 


--------------------------------------------------------------------------------
/src/levels.js:
--------------------------------------------------------------------------------
 1 | // directly or through datasets.js
 2 | // for now quick&dirty
 3 | 
 4 | import {
 5 |   fixedDatasets,
 6 |   fixedDatasetsTest
 7 | } from './datasets.js'
 8 | 
 9 | export const levels = [{
10 |     // linear
11 |     train: fixedDatasets[2],
12 |     validation: fixedDatasetsTest[2]
13 |   },
14 |   {
15 |     // moons
16 |     train: fixedDatasets[0],
17 |     validation: fixedDatasetsTest[0]
18 |   },
19 |   {
20 |     // circle
21 |     train: fixedDatasets[1],
22 |     validation: fixedDatasetsTest[1]
23 |   },
24 |   {
25 |     // xor
26 |     train: fixedDatasets[4],
27 |     validation: fixedDatasetsTest[4]
28 |   },
29 |   {
30 |     // spirals
31 |     train: fixedDatasets[3],
32 |     validation: fixedDatasetsTest[3]
33 |   },
34 | ];
35 | 


--------------------------------------------------------------------------------
/src/App.vue:
--------------------------------------------------------------------------------
 1 | <template>
 2 |   <div id="app">
 3 |     <ul class="menu">
 4 |       <li><router-link to="/">Playground</router-link></li>
 5 |       <li><router-link to="/lvl/1">Level 1</router-link></li>
 6 |     </ul>
 7 |     <router-view />
 8 |   </div>
 9 | </template>
10 | 
11 | <script>
12 | 
13 | export default {
14 |   name: 'App'
15 | }
16 | </script>
17 | 
18 | <style>
19 | #app {
20 |   font-family: 'Avenir', Helvetica, Arial, sans-serif;
21 |   -webkit-font-smoothing: antialiased;
22 |   -moz-osx-font-smoothing: grayscale;
23 |   text-align: center;
24 |   color: #2c3e50;
25 |   margin-top: 60px;
26 | }
27 | 
28 | ul.menu {
29 |   list-style-type: none;
30 |   margin: 0;
31 |   padding: 0;
32 |   background-color: #f1f1f1;
33 | }
34 | 
35 | .menu li {
36 |   display: inline;
37 | }
38 | 
39 | .menu li a {
40 |   display: inline;
41 |   color: #000;
42 |   padding: 8px 16px;
43 |   text-decoration: none;
44 | }
45 | 
46 | .menu li a:hover {
47 |   background-color: #555;
48 |   color: white;
49 | }
50 | 
51 | </style>
52 | 


--------------------------------------------------------------------------------
/src/predictions.js:
--------------------------------------------------------------------------------
 1 | import {predictions} from '../assets/predictions/all.json'
 2 | 
 3 | function closeEnough(v, w) {
 4 |   return Math.abs(v - w) < 0.05;
 5 | }
 6 | 
 7 | function findPrediction(tile, preds) {
 8 |   for (let i = 0; i < preds.length; ++i) {
 9 |     if (closeEnough(tile.x, preds[i].x) && closeEnough(tile.y, preds[i].y))
10 |       return +(preds[i].v > 0.5);
11 |   }
12 |   return 0;
13 | }
14 | 
15 | export function datasetHasPredictions(datasetName) {
16 |   return predictions[datasetName] !== undefined;
17 |   }
18 | 
19 | export function getPredictions(tiles, dataset, classifier) {
20 |   //// silent error messages are dangerous
21 |   // if (predictions[dataset] === undefined) {
22 |   //   console.log("No dataset");
23 |   //   return;
24 |   // }
25 |   // if (predictions[dataset][classifier] === undefined) {
26 |   //   console.log("No classifier");
27 |   //   return;
28 |   // }
29 |   const selectedPredictions = predictions[dataset][classifier];
30 |   tiles.forEach((d) => d.v = findPrediction(d, selectedPredictions));
31 | }
32 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2020 Piotr Migdał, Katarzyna Kańska
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/package.json:
--------------------------------------------------------------------------------
 1 | {
 2 |   "name": "which-ml",
 3 |   "version": "0.1.0",
 4 |   "private": true,
 5 |   "scripts": {
 6 |     "serve": "vue-cli-service serve",
 7 |     "build": "vue-cli-service build",
 8 |     "lint": "vue-cli-service lint"
 9 |   },
10 |   "dependencies": {
11 |     "d3-axis": "^1.0.12",
12 |     "d3-scale": "^2.1.2",
13 |     "d3-selection": "^1.4.0",
14 |     "vue": "^2.5.21",
15 |     "vue-router": "^3.0.2"
16 |   },
17 |   "devDependencies": {
18 |     "@vue/cli-plugin-babel": "^3.2.0",
19 |     "@vue/cli-plugin-eslint": "^3.3.0",
20 |     "@vue/cli-service": "^4.1.2",
21 |     "@vue/eslint-config-standard": "^4.0.0",
22 |     "babel-eslint": "^10.0.1",
23 |     "eslint": "^5.8.0",
24 |     "eslint-plugin-vue": "^5.0.0",
25 |     "vue-template-compiler": "^2.5.21",
26 |     "webpack": "^4.32.2"
27 |   },
28 |   "eslintConfig": {
29 |     "root": true,
30 |     "env": {
31 |       "node": true
32 |     },
33 |     "extends": [
34 |       "plugin:vue/essential",
35 |       "eslint:recommended",
36 |       "@vue/standard"
37 |     ],
38 |     "rules": {},
39 |     "parserOptions": {
40 |       "parser": "babel-eslint"
41 |     }
42 |   },
43 |   "postcss": {
44 |     "plugins": {
45 |       "autoprefixer": {}
46 |     }
47 |   },
48 |   "browserslist": [
49 |     "> 1%",
50 |     "last 2 versions",
51 |     "not ie <= 8"
52 |   ]
53 | }
54 | 


--------------------------------------------------------------------------------
/src/components/ConfusionTable.vue:
--------------------------------------------------------------------------------
 1 | <template>
 2 |   <table>
 3 |     <tbody>
 4 |       <tr>
 5 |         <th colspan="2" rowspan="2"/>
 6 |         <th colspan="3">Actual class</th>
 7 |       </tr>
 8 |       <tr>
 9 |         <th>Positive</th>
10 |         <th>Negative</th>
11 |       </tr>
12 |       <tr>
13 |         <th rowspan="3" style="height:6em;">
14 |           <div class="label-columns">Predicted<br> class</div>
15 |         </th>
16 |         <th>Positive</th>
17 |         <td>True Positives: {{ metrics.truePositives }}</td>
18 |         <td>False Positives: {{ metrics.falsePositives }}</td>
19 |       </tr>
20 |       <tr>
21 |         <th>Negative</th>
22 |         <td>False Negatives: {{ metrics.falseNegatives }}</td>
23 |         <td>True Negatives: {{ metrics.trueNegatives }}</td>
24 |       </tr>
25 |     </tbody>
26 |   </table>
27 | </template>
28 | 
29 | <script>
30 | 
31 | export default {
32 |   name: 'ConfusionTable',
33 |   props: {
34 |     metrics: {
35 |       type: Object,
36 |       default: () => ({
37 |         truePositives: 0,
38 |         falsePositives: 0,
39 |         falseNegatives: 0,
40 |         trueNegatives: 0,
41 |       })
42 |     }
43 |   },
44 |   methods: {
45 |   },
46 | 
47 | }
48 | 
49 | </script>
50 | 
51 | <style scoped>
52 | 
53 | .label-columns {
54 |   display: inline-block;
55 |   -ms-transform: rotate(-90deg);
56 |   -webkit-transform: rotate(-90deg);
57 |   transform: rotate(-90deg);
58 | }
59 | 
60 | </style>
61 | 


--------------------------------------------------------------------------------
/src/datasets.js:
--------------------------------------------------------------------------------
  1 | import {scaleLinear} from "d3-scale";
  2 | import {datasets} from '../assets/datasets/all.json'
  3 | 
  4 | const k = 10;
  5 | 
  6 | function range(size, startAt = 0) {
  7 |     return [...Array(size).keys()].map(i => i + startAt);
  8 | }
  9 | 
 10 | const scaleX = scaleLinear()
 11 |   .domain([0, k])
 12 |   .range([-1, 1]);
 13 | 
 14 | const scaleY = scaleLinear()
 15 |   .domain([0, k])
 16 |   .range([-1, 1]);
 17 | 
 18 | export const tiles = range(k * k)
 19 |   .map((i) => {
 20 |     return {
 21 |       x: scaleX(i % k),
 22 |       y: scaleY(Math.floor(i / k)),
 23 |       dx: scaleX(1) - scaleX(0),
 24 |       dy: scaleY(1) - scaleY(0),
 25 |       v: 0 // Math.random()
 26 |     };
 27 |   });
 28 | 
 29 | const generateSin = (n, wavenumber) => {
 30 |   return range(n)
 31 |     .map(() => {
 32 |       const x = 2 * Math.random() - 1;
 33 |       const y = 2 * Math.random() - 1;
 34 | 
 35 |       return {
 36 |         x: x,
 37 |         y: y,
 38 |         v: +(y < Math.sin(wavenumber * x))
 39 |       };
 40 |     });
 41 | }
 42 | 
 43 | const generateCircle = (n, radius) => {
 44 |   const rSq = Math.pow(radius, 2);
 45 |   return range(n)
 46 |     .map(() => {
 47 |       const x = 2 * Math.random() - 1;
 48 |       const y = 2 * Math.random() - 1;
 49 | 
 50 |       return {
 51 |         x: x,
 52 |         y: y,
 53 |         v: +(Math.pow(x, 2) + Math.pow(y, 2) < rSq)
 54 |       };
 55 |     });
 56 | }
 57 | 
 58 | export const generatedDatasets = [
 59 |   {name: "Sin4", points: generateSin(50, 4)},
 60 |   {name: "Sin4 Test", points: generateSin(50, 4)},
 61 |   {name: "Circle", points: generateCircle(50, 0.5)},
 62 |   {name: "Circle Test", points: generateCircle(50, 0.5)},
 63 |   {name: "Empty", points: []},
 64 | ];
 65 | 
 66 | const normalize = (data, ranges) => {
 67 | 
 68 |   const scaleX = scaleLinear()
 69 |     .domain([ranges.xmin, ranges.xmax])
 70 |     .range([-1, 1]);
 71 | 
 72 |   const scaleY = scaleLinear()
 73 |     .domain([ranges.ymin, ranges.ymax])
 74 |     .range([-1, 1]);
 75 | 
 76 |   return data.map((d) => ({
 77 |     x: scaleX(d.x),
 78 |     y: scaleY(d.y),
 79 |     v: d.v
 80 |   }));
 81 | };
 82 | 
 83 | export const fixedDatasets = datasets.map(
 84 |     (dataset) => ({
 85 |       name: dataset.name,
 86 |       points: normalize(dataset.data.train, dataset)
 87 |     })
 88 | );
 89 | 
 90 | export const fixedDatasetsTest = datasets.map(
 91 |     (dataset) => ({
 92 |       name: dataset.name + " Test",
 93 |       points: normalize(dataset.data.test, dataset)
 94 |     })
 95 | );
 96 | 
 97 | export const allDatasets = generatedDatasets
 98 |   .concat(fixedDatasets)
 99 |   .concat(fixedDatasetsTest);
100 | 


--------------------------------------------------------------------------------
/src/components/ConfusedTile.vue:
--------------------------------------------------------------------------------
  1 | <template>
  2 |   <g>
  3 |     <rect
  4 |       class="tile"
  5 |       :width="size"
  6 |       :height="size"
  7 |       :x="x"
  8 |       :y="y"
  9 |       :style="{fill: colorScheme[colorTile]}"
 10 |     />
 11 |     <circle
 12 |       v-for="(d, i) in pointsToShow"
 13 |       :key="i"
 14 |       class="point"
 15 |       :cx="x + scale(d.x)"
 16 |       :cy="y + scale(d.y)"
 17 |       :r="circleRadius"
 18 |       :style="{fill: colorScheme[colorPoint]}"
 19 |     />
 20 |   </g>
 21 | </template>
 22 | 
 23 | <script>
 24 | 
 25 | import {scaleLinear} from "d3-scale";
 26 | 
 27 | export default {
 28 |   name: 'ConfusionTable',
 29 |   props: {
 30 |     points: {
 31 |       type: Array,  // ([{x: 0, y: 0}, ...])
 32 |       default: () => ([])
 33 |     },
 34 |     n: {
 35 |       type: Number,
 36 |       default: 3
 37 |     },
 38 |     x: {
 39 |       type: Number,
 40 |       default: 0
 41 |     },
 42 |     y: {
 43 |       type: Number,
 44 |       default: 0
 45 |     },
 46 |     size: {
 47 |       type: Number,
 48 |       default: 20
 49 |     },
 50 |     contraction: {
 51 |       type: Number,
 52 |       default: 0.9,
 53 |     },
 54 |     circleRadius: {
 55 |       type: Number,
 56 |       default: 4,
 57 |     },
 58 |     tileMetrics: {
 59 |       type: String,
 60 |       default: "truePositives"
 61 |     },
 62 |     colorScheme: {
 63 |       type: Object,
 64 |       default: () => ({
 65 |         name: "RedGreen",
 66 |         negative: 'red',
 67 |         positive: 'green'
 68 |       })
 69 |     }
 70 |   },
 71 |   data: function() {
 72 |     return {
 73 |       scale: scaleLinear()
 74 |         .domain([-1/this.contraction, 1/this.contraction])
 75 |         .range([0, this.size])
 76 |     };
 77 |   },
 78 |   computed: {
 79 |     colorTile: function() {
 80 |       return {
 81 |         truePositives: "positive",
 82 |         falsePositives: "positive",
 83 |         falseNegatives: "negative",
 84 |         trueNegatives: "negative",
 85 |       }[this.tileMetrics];
 86 |     },
 87 |     colorPoint: function() {
 88 |       return {
 89 |         truePositives: "positive",
 90 |         falsePositives: "negative",
 91 |         falseNegatives: "positive",
 92 |         trueNegatives: "negative",
 93 |       }[this.tileMetrics];
 94 |     },
 95 |     pointsToShow: function() {
 96 |       if (this.points.length > 0) {
 97 |         return this.points;
 98 |       } else {
 99 |         // maybe also some semi-deterministic way?
100 |         return [...Array(this.n).keys()]  // range(n)
101 |         .map(() => ({
102 |           x: 2 * Math.random() - 1,
103 |           y: 2 * Math.random() - 1,
104 |         }))
105 |       }
106 |     }
107 |   },
108 | 
109 | }
110 | 
111 | </script>
112 | 
113 | <style scoped>
114 | 
115 | .tile {
116 |   cursor: pointer;
117 |   opacity: 0.15;
118 | }
119 | 
120 | .point {
121 |   stroke: white;
122 |   stroke-width: 1;
123 |   stroke-opacity: 0.8;
124 | }
125 | 
126 | </style>
127 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # Which Machine Learning algorithm are you?
 2 | 
 3 | A project by [Piotr Migdał](https://p.migdal.pl/) and Katarzyna Kańska. Work in progress. We learn Vue, so any feedback and code is appreciated.
 4 | 
 5 | ![Precision, recall and accuracy - visually](precision_recall_accuracy.png)
 6 | 
 7 | Inspirations:
 8 | 
 9 | * [Teaching Machine Learning](https://speakerdeck.com/pmigdal/teaching-machine-learning) and my general approach to teaching via exploration, see also:
10 |   - [Quantum Game with Photons](http://quantumgame.io/)
11 |   - [Quantum mechanics for high-school students](http://p.migdal.pl/2016/08/15/quantum-mechanics-for-high-school-students.html)
12 |   - [Starting deep learning hands-on: image classification on CIFAR-10	](https://deepsense.ai/deep-learning-hands-on-image-classification/)
13 |   - [In Browser AI](https://inbrowser.ai)
14 |   - The collaborative list of [Interactive Machine Learning, Deep Learning and Statistics websites](https://p.migdal.pl/interactive-machine-learning-list/)
15 | * [Classifier comparison - scikit](https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html)
16 | * Your Draw It series from The New York Times:
17 |   - [You Draw It: What Got Better or Worse During Obama’s Presidency](https://www.nytimes.com/interactive/2017/01/15/us/politics/you-draw-obama-legacy.html)
18 |   - [You Draw It: How Family Income Predicts Children’s College Chances](https://www.nytimes.com/interactive/2015/05/28/upshot/you-draw-it-how-family-income-affects-childrens-college-chances.html)
19 |   - [You Draw It: Just How Bad Is the Drug Overdose Epidemic?](https://www.nytimes.com/interactive/2017/04/14/upshot/drug-overdose-epidemic-you-draw-it.html)
20 | * [TensorFlow playground](https://playground.tensorflow.org/)
21 | * [Precision and recall - Wikipedia](https://en.wikipedia.org/wiki/Precision_and_recall)
22 |   * [This beautiful diagram](https://en.wikipedia.org/wiki/F1_score#/media/File:Precisionrecall.svg) less -
23 | [that diagram](https://en.wikipedia.org/wiki/Binary_classification#/media/File:Binary-classification-labeled.svg)
24 | 
25 | ## How to run it
26 | 
27 | It's a [Vue.js](https://vuejs.org/) project, so...
28 | 
29 | ###  Project setup
30 | ```
31 | npm install
32 | ```
33 | 
34 | ####  Compiles and hot-reloads for development
35 | ```
36 | npm run serve
37 | ```
38 | 
39 | ####  Compiles and minifies for production
40 | ```
41 | npm run build
42 | ```
43 | 
44 | #### Run your tests
45 | ```
46 | npm run test
47 | ```
48 | 
49 | #### Lints and fixes files
50 | ```
51 | npm run lint
52 | ```
53 | 
54 | #### Deploy to GitHub pages
55 | 
56 | First, install [push-dir](https://www.npmjs.com/package/push-dir). Then:
57 | 
58 | ```
59 | npm run build; push-dir --dir=dist --branch=gh-pages --cleanup
60 | ```
61 | 
62 | See [Deploy Vue to GitHub pages-the easy way!](https://medium.com/@codetheorist/vue-up-your-github-pages-the-right-way-955486220418). You need to set relative paths in `vue.config.js`.
63 | 
64 | #### Customize configuration
65 | See [Configuration Reference](https://cli.vuejs.org/config/).
66 | 


--------------------------------------------------------------------------------
/src/components/Chart.vue:
--------------------------------------------------------------------------------
  1 | <template>
  2 |   <svg
  3 |     class="chart"
  4 |     :width="width + 2 * margin"
  5 |     :height="height + 2 * margin"
  6 |   >
  7 |     <g>
  8 |       <circle
  9 |         v-for="(d, i) in points"
 10 |         :key="`point-${i}`"
 11 |         class="point"
 12 |         :cx="xScale(d.x)"
 13 |         :cy="yScale(d.y)"
 14 |         :r="4"
 15 |         :style="{fill: color(d.v)}"
 16 |       />
 17 |     </g>
 18 |     <g>
 19 |       <rect
 20 |         v-for="(d, i) in tiles"
 21 |         :key="i"
 22 |         class="tile"
 23 |         :x="xScale(d.x)"
 24 |         :y="yScale(d.y)"
 25 |         :width="sizeX"
 26 |         :height="sizeY"
 27 |         :style="{fill: color(d.v)}"
 28 |         @mousedown="tileMouseDown(d)"
 29 |         @mouseover="tileMouseOver(d)"
 30 |         @mouseup="tileMouseUp()"
 31 |       />
 32 |     </g>
 33 |     <g class="x-axis" />
 34 |     <g class="y-axis" />
 35 |   </svg>
 36 | </template>
 37 | 
 38 | <script>
 39 | import {select} from "d3-selection";
 40 | import {scaleLinear} from "d3-scale";
 41 | import {axisBottom, axisRight} from "d3-axis";
 42 | const d3 = { select, scaleLinear, axisBottom, axisRight };
 43 | 
 44 | export default {
 45 |   name: 'Chart',
 46 |   props: {
 47 |     points: {type: Array, default: () => ([])},
 48 |     tiles: {type: Array, default: () => ([{
 49 |       x: -1,
 50 |       y: -1,
 51 |       dx: 2,
 52 |       dy: 2,
 53 |       v: 0
 54 |     }])},
 55 |     width: {type: Number, default: 500},
 56 |     height: {type: Number, default: 500},
 57 |     margin: {type: Number, default: 50},
 58 |     colorScheme: {
 59 |       type: Object,
 60 |       default: () => ({
 61 |         name: "RedGreen",
 62 |         negative: 'red',
 63 |         positive: 'green'
 64 |       })
 65 |     },
 66 |     editable: {type: Boolean, default: true},
 67 |   },
 68 |   data: function () {
 69 |     return {
 70 |       isDown: false,
 71 |       brushValue: 1,
 72 |       xScale: d3.scaleLinear()
 73 |                 .domain([-1, 1])
 74 |                 .range([this.margin, this.margin + this.width]),
 75 |       yScale: d3.scaleLinear()
 76 |                 .domain([-1, 1])
 77 |                 .range([this.margin, this.margin + this.height])
 78 | 
 79 |     };
 80 |   },
 81 |   computed: {
 82 |     sizeX: function() {
 83 |       return this.xScale(this.tiles[0].dx) - this.xScale(0);
 84 |     },
 85 |     sizeY: function() {
 86 |       return this.yScale(this.tiles[0].dy) - this.yScale(0);
 87 |     },
 88 |     color: function() {
 89 |       return d3.scaleLinear()
 90 |         .domain([0, 0.5, 1.])
 91 |         .range([this.colorScheme.negative, 'white', this.colorScheme.positive]);
 92 |     },
 93 |   },
 94 |   mounted() {
 95 |     d3.select(this.$el).select("g.x-axis")
 96 |       .attr("transform", `translate(0,${this.margin + this.height})`)
 97 |       .call(d3.axisBottom(this.xScale));
 98 | 
 99 |     d3.select(this.$el).select("g.y-axis")
100 |       .attr("transform", `translate(${this.margin + this.width},0)`)
101 |       .call(d3.axisRight(this.yScale));
102 | 
103 |   },
104 |   methods: {
105 |     tileMouseDown: function(d) {
106 |       if (!this.editable) {
107 |         return;
108 |       }
109 |       this.isDown = true;
110 |       this.brushValue = 1 - d.v;
111 |       d.v = this.brushValue;
112 |     },
113 |     tileMouseOver: function(d) {
114 |       if (this.isDown) {
115 |         d.v = this.brushValue;
116 |       }
117 |     },
118 |     tileMouseUp: function() {
119 |       this.isDown = false;
120 |     },
121 |   },
122 | 
123 | }
124 | 
125 | </script>
126 | 
127 | <style scoped>
128 | 
129 | .tile {
130 |   cursor: pointer;
131 |   opacity: 0.15;
132 | }
133 | 
134 | .tile:hover {
135 |   opacity: 0.1;
136 | }
137 | 
138 | .point {
139 |   stroke: white;
140 |   stroke-width: 1;
141 |   stroke-opacity: 0.8;
142 | }
143 | 
144 | </style>
145 | 


--------------------------------------------------------------------------------
/src/components/ConfusionTableVisually.vue:
--------------------------------------------------------------------------------
  1 | <template>
  2 |   <svg
  3 |     width="450"
  4 |     height="250"
  5 |   >
  6 |     <text
  7 |       class="label-rows main-label"
  8 |       :style="rotatedTextStyle"
  9 |     >
 10 |       Predicted class
 11 |     </text>
 12 |     <text
 13 |       class="preds-label"
 14 |       :x="shiftX"
 15 |       :y="shiftY + spacing + tileSize / 2"
 16 |     >
 17 |       Positive
 18 |     </text>
 19 |     <text
 20 |       class="preds-label"
 21 |       :x="shiftX"
 22 |       :y="shiftY + 2 * spacing + 3 * tileSize / 2"
 23 |     >
 24 |       Negative
 25 |     </text>
 26 |     <text
 27 |       class="label-columns main-label"
 28 |       :x="shiftX + 3 * spacing / 2 + tileSize"
 29 |       :y="3 * spacing / 2"
 30 |     >
 31 |       Actual class
 32 |     </text>
 33 |     <text
 34 |       class="true-label"
 35 |       :x="shiftX + spacing + tileSize / 2"
 36 |       :y="shiftY"
 37 |     >
 38 |       Positive
 39 |     </text>
 40 |     <text
 41 |       class="true-label"
 42 |       :x="shiftX + 2 * spacing + 3 * tileSize / 2"
 43 |       :y="shiftY"
 44 |     >
 45 |       Negative
 46 |     </text>
 47 |     <g class="tiles">
 48 |       <ConfusedTile
 49 |         v-for="(quantity, i) in [`truePositives`, `falsePositives`, `falseNegatives`, `trueNegatives`]"
 50 |         :key="`numerator-${i}-${quantity}`"
 51 |         :n="metrics[quantity]"
 52 |         :points="metricsPoints[quantity]"
 53 |         :circleRadius="3"
 54 |         :size="tileSize"
 55 |         :x="shiftX + (i % 2 + 1) * spacing + (i % 2) * tileSize"
 56 |         :y="shiftY + (Math.floor(i / 2) + 1) * spacing + Math.floor(i / 2) * tileSize"
 57 |         :tileMetrics="quantity"
 58 |         :colorScheme="colorScheme"
 59 |       />
 60 |     </g>
 61 |   </svg>
 62 | </template>
 63 | 
 64 | <script>
 65 | 
 66 | import ConfusedTile from './ConfusedTile.vue';
 67 | 
 68 | export default {
 69 |   name: 'ConfusionTableVisually',
 70 |   components: {
 71 |     ConfusedTile
 72 |   },
 73 |   props: {
 74 |     tileSize: {
 75 |       type: Number,
 76 |       default: 50
 77 |     },
 78 |     spacing: {
 79 |       type: Number,
 80 |       default: 15
 81 |     },
 82 |     shiftX: {
 83 |       type: Number,
 84 |       default: 100
 85 |     },
 86 |     shiftY: {
 87 |       type: Number,
 88 |       default: 50
 89 |     },
 90 |     colorScheme: {
 91 |       type: Object,
 92 |       default: () => ({
 93 |         name: "RedGreen",
 94 |         negative: 'red',
 95 |         positive: 'green'
 96 |       })
 97 |     },
 98 |     metrics: {
 99 |       type: Object,
100 |       default: () => ({
101 |         truePositives: 0,
102 |         falsePositives: 0,
103 |         falseNegatives: 0,
104 |         trueNegatives: 0,
105 |       })
106 |     },
107 |     metricsPoints: {
108 |       type: Object,
109 |       default: () => ({
110 |         truePositives: [],
111 |         falsePositives: [],
112 |         falseNegatives: [],
113 |         trueNegatives: [],
114 |       })
115 |     },
116 |   },
117 |   computed: {
118 |     rotatedTextStyle: function() {
119 |       return {
120 |         transform : 'translate('
121 |           + this.spacing + 'px, '
122 |           + (this.shiftY + 3 * this.spacing / 2 + this.tileSize)
123 |           + 'px) rotate(-90deg)'};
124 |     },
125 |   },
126 | }
127 | 
128 | </script>
129 | 
130 | <style scoped>
131 | 
132 | .tiles {
133 |   text-anchor: end;
134 |   dominant-baseline: central;
135 | }
136 | 
137 | .label-rows {
138 |   text-anchor: middle;
139 |   dominant-baseline: central;
140 | }
141 | 
142 | .label-columns {
143 |   text-anchor: middle;
144 |   dominant-baseline: central;
145 | }
146 | 
147 | .preds-label {
148 |   text-anchor: end;
149 |   dominant-baseline: central;
150 | }
151 | 
152 | .true-label {
153 |   text-anchor: middle;
154 |   dominant-baseline: central;
155 | }
156 | 
157 | .main-label {
158 |   font-weight: bold;
159 | }
160 | 
161 | </style>
162 | 


--------------------------------------------------------------------------------
/src/components/QuantityVisually.vue:
--------------------------------------------------------------------------------
  1 | <template>
  2 |   <svg width="450" height="150">
  3 |     <text
  4 |       class="metrics-name"
  5 |       :x="shiftX"
  6 |       :y="tileSize + 2 * spacing">
  7 |       {{ formula.name }} =
  8 |     </text>
  9 |     <g class="numerator">
 10 |       <ConfusedTile
 11 |         v-for="(quantity, i) in formula.numerator"
 12 |         :key="`numerator-${i}-${quantity}`"
 13 |         :n="metrics[quantity]"
 14 |         :points="metricsPoints[quantity]"
 15 |         :circleRadius="3"
 16 |         :size="tileSize"
 17 |         :x="shiftX + spacing + (i + (maxLength - formula.numerator.length)/2) * tileSize"
 18 |         :y="spacing"
 19 |         :tileMetrics="quantity"
 20 |         :colorScheme="colorScheme"
 21 |       />
 22 |     </g>
 23 |     <line
 24 |       class="division-line"
 25 |       :x1="shiftX + spacing"
 26 |       :y1="tileSize + 2 * spacing"
 27 |       :x2="shiftX + spacing + maxLength * tileSize"
 28 |       :y2="tileSize + 2 * spacing"
 29 |     />
 30 |     <g class="denominator">
 31 |       <ConfusedTile
 32 |         v-for="(quantity, i) in formula.denominator"
 33 |         :key="`denominator-${i}-${quantity}`"
 34 |         :n="metrics[quantity]"
 35 |         :points="metricsPoints[quantity]"
 36 |         :circleRadius="3"
 37 |         :size="tileSize"
 38 |         :x="shiftX + spacing + (i + (maxLength - formula.denominator.length)/2) * tileSize"
 39 |         :y="tileSize + 3 * spacing"
 40 |         :tileMetrics="quantity"
 41 |         :colorScheme="colorScheme"
 42 |       />
 43 |     </g>
 44 |     <text
 45 |       class="value-label"
 46 |       :x="shiftX + 2 * spacing + maxLength * tileSize"
 47 |       :y="tileSize + 2 * spacing">
 48 |       = {{ valuePercent }}%
 49 |     </text>
 50 |   </svg>
 51 | </template>
 52 | 
 53 | <script>
 54 | 
 55 | import ConfusedTile from './ConfusedTile.vue';
 56 | 
 57 | export default {
 58 |   name: 'QuantityVisually',
 59 |   components: {
 60 |     ConfusedTile
 61 |   },
 62 |   props: {
 63 |     formula: {
 64 |       type: Object,
 65 |       default: () => ({
 66 |         name: "Precision",
 67 |         numerator: ["truePositives"],
 68 |         denominator: ["truePositives", "falsePositives"],
 69 |       })
 70 |     },
 71 |     tileSize: {
 72 |       type: Number,
 73 |       default: 50
 74 |     },
 75 |     spacing: {
 76 |       type: Number,
 77 |       default: 10
 78 |     },
 79 |     shiftX: {
 80 |       type: Number,
 81 |       default: 150
 82 |     },
 83 |     colorScheme: {
 84 |       type: Object,
 85 |       default: () => ({
 86 |         name: "RedGreen",
 87 |         negative: 'red',
 88 |         positive: 'green'
 89 |       })
 90 |     },
 91 |     metrics: {
 92 |       type: Object,
 93 |       default: () => ({
 94 |         truePositives: 0,
 95 |         falsePositives: 0,
 96 |         falseNegatives: 0,
 97 |         trueNegatives: 0,
 98 |       })
 99 |     },
100 |     metricsPoints: {
101 |       type: Object,
102 |       default: () => ({
103 |         truePositives: [],
104 |         falsePositives: [],
105 |         falseNegatives: [],
106 |         trueNegatives: [],
107 |       })
108 |     },
109 |   },
110 |   computed: {
111 |     maxLength: function() {
112 |       return Math.max(
113 |         this.formula.numerator.length,
114 |         this.formula.denominator.length
115 |       );
116 |     },
117 |     valuePercent: function() {
118 |       const m = this.metrics;
119 |       // use metricsPoints -> length in metrics not present?
120 | 
121 |       const x = this.formula.numerator
122 |         .map((quantity) => m[quantity])
123 |         .reduce((a, b) => a + b, 0);
124 | 
125 |       const y = this.formula.denominator
126 |         .map((quantity) => m[quantity])
127 |         .reduce((a, b) => a + b, 0);
128 | 
129 |       return (100 * x / y).toFixed(1);
130 |     },
131 |   },
132 | 
133 | }
134 | 
135 | </script>
136 | 
137 | <style scoped>
138 | 
139 | .metrics-name {
140 |   text-anchor: end;
141 |   dominant-baseline: central;
142 | }
143 | 
144 | .value-label {
145 |   text-anchor: start;
146 |   dominant-baseline: central;
147 | }
148 | 
149 | .division-line {
150 |   stroke: black;
151 |   stroke-width: 2px;
152 | }
153 | 
154 | </style>
155 | 


--------------------------------------------------------------------------------
/src/metrics.js:
--------------------------------------------------------------------------------
  1 | function isPointInsideTile(point, tile) {
  2 |   return tile.x <= point.x && point.x < tile.x + tile.dx
  3 |     && tile.y <= point.y && point.y < tile.y + tile.dy;
  4 | }
  5 | 
  6 | export function computeMetrics(points, tiles) {
  7 |   const confusionMatrix = [[0, 0], [0, 0]];
  8 |   points.forEach((point) => {
  9 |     tiles.forEach((tile) => {
 10 |       if (isPointInsideTile(point, tile)) {
 11 |         confusionMatrix[tile.v][point.v] += 1;
 12 |       }
 13 |     });
 14 |   });
 15 |   return {
 16 |     truePositives: confusionMatrix[1][1],
 17 |     falsePositives: confusionMatrix[1][0],
 18 |     falseNegatives: confusionMatrix[0][1],
 19 |     trueNegatives: confusionMatrix[0][0],
 20 |   }
 21 | }
 22 | 
 23 | export function splitByMetrics(points, tiles) {
 24 |   const confusionMatrixPoints = [[[], []], [[], []]];
 25 |   points.forEach((point) => {
 26 |     tiles.forEach((tile) => {
 27 |       if (isPointInsideTile(point, tile)) {
 28 |         confusionMatrixPoints[tile.v][point.v].push(point);
 29 |       }
 30 |     });
 31 |   });
 32 |   return {
 33 |     truePositives: confusionMatrixPoints[1][1],
 34 |     falsePositives: confusionMatrixPoints[1][0],
 35 |     falseNegatives: confusionMatrixPoints[0][1],
 36 |     trueNegatives: confusionMatrixPoints[0][0],
 37 |   }
 38 | }
 39 | 
 40 | export const metrics2acronym = {
 41 |   truePositive: "TP",
 42 |   falsePositives: "FP",
 43 |   falseNegatives: "FN",
 44 |   trueNegatives: "TN",
 45 | };
 46 | 
 47 | export const confusionMatrixMetrics = [
 48 |   // {
 49 |   //   name: "Condition positive",
 50 |   //   synonyms: ["(P)"],
 51 |   //   wiki: "",
 52 |   //   numerator: ["truePositives", "falseNegatives"],
 53 |   //   denominator: [1]
 54 |   // },
 55 |   // {
 56 |   //   name: "Condition negative",
 57 |   //   synonyms: ["(N)"],
 58 |   //   wiki: "",
 59 |   //   numerator: ["falsePositives", "trueNegatives"],
 60 |   //   denominator: [1]
 61 |   // },
 62 |   {
 63 |     name: "Precision",
 64 |     synonyms: ["Positive Predictive Value (PPV)"],
 65 |     wiki: "https://en.wikipedia.org/wiki/Precision_and_recall",
 66 |     numerator: ["truePositives"],
 67 |     denominator: ["truePositives", "falsePositives"]
 68 |   },
 69 |   {
 70 |     name: "Recall",
 71 |     synonyms: ["Sensitivity", "Hit rate", "True Positive Rate (TPR)"],
 72 |     wiki: "https://en.wikipedia.org/wiki/Precision_and_recall",
 73 |     numerator: ["truePositives"],
 74 |     denominator: ["truePositives", "falseNegatives"]
 75 |   },
 76 |   {
 77 |     name: "Specificity",
 78 |     synonyms: ["Selectivity", "True Negative Rate (TNR)"],
 79 |     wiki: "https://en.wikipedia.org/wiki/Sensitivity_and_specificity",
 80 |     numerator: ["trueNegatives"],
 81 |     denominator: ["falsePositives", "trueNegatives"]
 82 |   },
 83 |   {
 84 |     name: "Negative Predictive Value",
 85 |     synonyms: ["(NPV)"],
 86 |     wiki: "https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values",
 87 |     numerator: ["trueNegatives"],
 88 |     denominator: ["falseNegatives", "trueNegatives"]
 89 |   },
 90 |   {
 91 |     name: "False Negative Rate",
 92 |     synonyms: ["(FNR)", "Miss Rate"],
 93 |     wiki: "https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values",
 94 |     numerator: ["falseNegatives"],
 95 |     denominator: ["truePositives", "falseNegatives"]
 96 |   },
 97 |   {
 98 |     name: "False Positive Rate",
 99 |     synonyms: ["(FPR)", "Fall-out"],
100 |     wiki: null,
101 |     numerator: ["falsePositives"],
102 |     denominator: ["falsePositives", "trueNegatives"]
103 |   },
104 |   {
105 |     name: "False Discovery Rate",
106 |     synonyms: ["(FDR)"],
107 |     wiki: "https://en.wikipedia.org/wiki/False_discovery_rate",
108 |     numerator: ["falsePositives"],
109 |     denominator: ["truePositives", "falsePositives"]
110 |   },
111 |   {
112 |     name: "False Omission Rate",
113 |     synonyms: ["(FOR)"],
114 |     wiki: "https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values",
115 |     numerator: ["falseNegatives"],
116 |     denominator: ["falseNegatives", "trueNegatives"]
117 |   },
118 |   {
119 |     name: "Accuracy",
120 |     synonyms: ["(ACC)"],
121 |     wiki: "https://en.wikipedia.org/wiki/Accuracy_and_precision",
122 |     numerator: ["truePositives", "trueNegatives"],
123 |     denominator: ["truePositives", "falsePositives", "falseNegatives", "trueNegatives"]
124 |   },
125 |   {
126 |     name: "F1 score",
127 |     synonyms: [],
128 |     wiki: "https://en.wikipedia.org/wiki/F1_score",
129 |     numerator: ["truePositives", "truePositives"],
130 |     denominator: ["truePositives", "truePositives", "falsePositives", "falseNegatives"]
131 |   },
132 | ];
133 | 


--------------------------------------------------------------------------------
/src/All.vue:
--------------------------------------------------------------------------------
  1 | <template>
  2 |   <div id="all">
  3 |     <h1>Draw classification</h1>
  4 | 
  5 |     <div>
  6 |       <span>Choose dataset:</span>
  7 |       <select v-model="dataset">
  8 |         <option
  9 |           v-for="option in options"
 10 |           :key="option.name"
 11 |           :value="option"
 12 |         >
 13 |           {{ option.name }}
 14 |         </option>
 15 |       </select>
 16 |     </div>
 17 | 
 18 |     <Chart
 19 |       :points="dataset.points"
 20 |       :tiles="tiles"
 21 |       :width="500"
 22 |       :height="500"
 23 |       :colorScheme="selectedColorScheme"
 24 |     />
 25 | 
 26 |     <div>
 27 |       <span>Reset all to: </span>
 28 |       <button @click="resetSelection(0)">
 29 |         NO
 30 |       </button>
 31 |       <button @click="resetSelection(1)">
 32 |         YES
 33 |       </button>
 34 |       <button @click="resetSelectionRandom()">
 35 |         raNDoM
 36 |       </button>
 37 |     </div>
 38 |     <div v-if="datasetHasPredictions">
 39 |       <span>Classifier predicitions: </span>
 40 |       <button
 41 |         v-for="(classifier, i) in [`Nearest Neighbors`, `Linear SVM`, `RBF SVM`, `Gaussian Process`, `Decision Tree`, `Random Forest`, `Neural Net`, `AdaBoost`, `Naive Bayes`, `QDA`]"
 42 |         :key="`${i}-${classifier}`"
 43 |         @click="resetSelectionByClassifier(classifier)"
 44 |       >
 45 |         {{ classifier }}
 46 |       </button>
 47 |     </div>
 48 | 
 49 |     <div>
 50 |       <span>Choose color theme:</span>
 51 |       <select v-model="selectedColorScheme">
 52 |         <option
 53 |           v-for="colorScheme in colorSchemes"
 54 |           :key="colorScheme.name"
 55 |           :value="colorScheme"
 56 |         >
 57 |           {{ colorScheme.name }}
 58 |         </option>
 59 |       </select>
 60 |     </div>
 61 | 
 62 |     <QuantityVisually
 63 |       v-for="formula in confusionMatrixMetrics"
 64 |       :key="`qv-${formula.name}`"
 65 |       :formula="formula"
 66 |       :metrics="metrics"
 67 |       :metricsPoints="metricsPoints"
 68 |       :colorScheme="selectedColorScheme"
 69 |     />
 70 | 
 71 |     <ConfusionTable :metrics="metrics"/>
 72 |     <ConfusionTableVisually
 73 |       :metrics="metrics"
 74 |       :metricsPoints="metricsPoints"
 75 |       :colorScheme="selectedColorScheme"
 76 |     />
 77 |   </div>
 78 | </template>
 79 | 
 80 | <script>
 81 | 
 82 | import Chart from './components/Chart.vue'
 83 | import ConfusionTable from './components/ConfusionTable.vue'
 84 | import ConfusionTableVisually from './components/ConfusionTableVisually.vue'
 85 | import QuantityVisually from './components/QuantityVisually.vue'
 86 | import {computeMetrics, confusionMatrixMetrics, splitByMetrics} from './metrics.js';
 87 | import {tiles, allDatasets} from './datasets.js'
 88 | import {datasetHasPredictions, getPredictions} from './predictions.js'
 89 | 
 90 | export default {
 91 |   name: 'All',
 92 |   components: {
 93 |     Chart,
 94 |     ConfusionTable,
 95 |     QuantityVisually,
 96 |     ConfusionTableVisually
 97 |   },
 98 |   data: function () {
 99 |     return {
100 |       dataset: allDatasets[0],
101 |       points: [],
102 |       tiles: tiles,
103 |       options: allDatasets,
104 |       colorSchemes: [
105 |         {name: "RedGreen", negative: 'red', positive: 'green'},
106 |         {name: "RedGreenWiki", negative: "#F3796F", positive: "#9DDB73"},
107 |         {name: "TensorFlow", negative:  'rgb(245, 147, 34)', positive: 'rgb(8, 119, 189)'},
108 |         {name: "sklearn", negative:  'rgb(255, 0, 0)', positive: 'rgb(0, 0, 255)'},
109 |       ],
110 |       selectedColorScheme: {name: "RedGreen", negative: 'red', positive: 'green'},
111 |       confusionMatrixMetrics: confusionMatrixMetrics
112 |     };
113 |   },
114 |   computed: {
115 |     tilesUp: function() {
116 |       let counter = 0;
117 |       this.tiles.forEach(
118 |         (d) => counter += d.v
119 |       );
120 |       return counter;
121 |     },
122 |     metrics: function() {
123 |       return computeMetrics(this.dataset.points, this.tiles)
124 |     },
125 |     metricsPoints: function() {
126 |       return splitByMetrics(this.dataset.points, this.tiles)
127 |     },
128 |     datasetHasPredictions: function() {
129 |       return datasetHasPredictions(this.dataset.name);
130 |     },
131 |   },
132 |   methods: {
133 |     resetSelection: function(targetValue) {
134 |       this.tiles.forEach((d) => d.v = targetValue);
135 |     },
136 |     resetSelectionRandom: function() {
137 |       this.tiles.forEach((d) => d.v = +(Math.random() > 0.5));
138 |     },
139 |     resetSelectionByClassifier: function(classifierName) {
140 |       getPredictions(this.tiles, this.dataset.name, classifierName);
141 |     },
142 |   }
143 | }
144 | </script>
145 | 
146 | <style>
147 | #app {
148 |   font-family: 'Avenir', Helvetica, Arial, sans-serif;
149 |   -webkit-font-smoothing: antialiased;
150 |   -moz-osx-font-smoothing: grayscale;
151 |   text-align: center;
152 |   color: #2c3e50;
153 |   margin-top: 60px;
154 | }
155 | </style>
156 | 


--------------------------------------------------------------------------------
/src/Level.vue:
--------------------------------------------------------------------------------
  1 | <template>
  2 |   <div id="level">
  3 |     <h1>Level {{ id }}</h1>
  4 | 
  5 |     <ul class="menu">
  6 |       <li><router-link :to="'/lvl/' + Math.max(1, lvlId - 1)">Previous</router-link></li>
  7 |       <li><router-link :to="'/lvl/' + Math.min(levelsLength, lvlId + 1)">Next</router-link></li>
  8 |     </ul>
  9 | 
 10 |     <h2>Draw classification</h2>
 11 | 
 12 |     <p>({{ mode }} mode)<p>
 13 | 
 14 |     <Chart
 15 |       :points="level[this.mode].points"
 16 |       :tiles="tiles"
 17 |       :width="500"
 18 |       :height="500"
 19 |       :colorScheme="selectedColorScheme"
 20 |       :editable="mode == 'train'"
 21 |     />
 22 | 
 23 |     <div>
 24 |       <span>Reset all to: </span>
 25 |       <button @click="resetSelection(0)">
 26 |         NO
 27 |       </button>
 28 |       <button @click="resetSelection(1)">
 29 |         YES
 30 |       </button>
 31 |       <button @click="resetSelectionRandom()">
 32 |         raNDoM
 33 |       </button>
 34 |     </div>
 35 |     <div v-if="datasetHasPredictions">
 36 |       <span>Classifier predicitions: </span>
 37 |       <button
 38 |         v-for="(classifier, i) in [`Nearest Neighbors`, `Linear SVM`, `RBF SVM`, `Gaussian Process`, `Decision Tree`, `Random Forest`, `Neural Net`, `AdaBoost`, `Naive Bayes`, `QDA`]"
 39 |         :key="`${i}-${classifier}`"
 40 |         @click="resetSelectionByClassifier(classifier)"
 41 |       >
 42 |         {{ classifier }}
 43 |       </button>
 44 |     </div>
 45 | 
 46 |     <div>
 47 |       <button @click="setMode('validation')">
 48 |         Validate!
 49 |       </button>
 50 |     </div>
 51 | 
 52 |     <div class="row">
 53 |       <div class="column">
 54 |         <h3>Train results</h3>
 55 |         <ConfusionTableVisually
 56 |           :metrics="metrics"
 57 |           :metricsPoints="metricsPoints"
 58 |           :colorScheme="selectedColorScheme"
 59 |         />
 60 |         <QuantityVisually
 61 |           :formula="confusionMatrixMetrics.filter((d) => d.name == 'Accuracy')[0]"
 62 |           :metrics="metrics"
 63 |           :metricsPoints="metricsPoints"
 64 |           :colorScheme="selectedColorScheme"
 65 |         />
 66 |         <QuantityVisually
 67 |           :formula="confusionMatrixMetrics.filter((d) => d.name == 'Precision')[0]"
 68 |           :metrics="metrics"
 69 |           :metricsPoints="metricsPoints"
 70 |           :colorScheme="selectedColorScheme"
 71 |         />
 72 |         <QuantityVisually
 73 |           :formula="confusionMatrixMetrics.filter((d) => d.name == 'Recall')[0]"
 74 |           :metrics="metrics"
 75 |           :metricsPoints="metricsPoints"
 76 |           :colorScheme="selectedColorScheme"
 77 |         />
 78 |       </div>
 79 |       <div class="column" v-if="mode == 'validation'">
 80 |         <h3>Validation results</h3>
 81 |         <ConfusionTableVisually
 82 |           :metrics="metricsVal"
 83 |           :metricsPoints="metricsPointsVal"
 84 |           :colorScheme="selectedColorScheme"
 85 |         />
 86 |         <QuantityVisually
 87 |           :formula="confusionMatrixMetrics.filter((d) => d.name == 'Accuracy')[0]"
 88 |           :metrics="metricsVal"
 89 |           :metricsPoints="metricsPointsVal"
 90 |           :colorScheme="selectedColorScheme"
 91 |         />
 92 |         <QuantityVisually
 93 |           :formula="confusionMatrixMetrics.filter((d) => d.name == 'Precision')[0]"
 94 |           :metrics="metricsVal"
 95 |           :metricsPoints="metricsPointsVal"
 96 |           :colorScheme="selectedColorScheme"
 97 |         />
 98 |         <QuantityVisually
 99 |           :formula="confusionMatrixMetrics.filter((d) => d.name == 'Recall')[0]"
100 |           :metrics="metricsVal"
101 |           :metricsPoints="metricsPointsVal"
102 |           :colorScheme="selectedColorScheme"
103 |         />
104 |       </div>
105 |     </div>
106 | 
107 | 
108 | 
109 | 
110 |   </div>
111 | </template>
112 | 
113 | <script>
114 | 
115 | import Chart from './components/Chart.vue'
116 | import ConfusionTableVisually from './components/ConfusionTableVisually.vue'
117 | import QuantityVisually from './components/QuantityVisually.vue'
118 | import {computeMetrics, splitByMetrics, confusionMatrixMetrics} from './metrics.js';
119 | import {tiles} from './datasets.js'
120 | import {levels} from './levels.js'
121 | import {getPredictions, datasetHasPredictions} from './predictions.js';
122 | 
123 | 
124 | export default {
125 |   name: 'Level',
126 |   components: {
127 |     Chart,
128 |     ConfusionTableVisually,
129 |     QuantityVisually
130 |   },
131 |   props: {
132 |     id: {type: String, required: true},
133 |   },
134 |   data: function () {
135 |     return {
136 |       // level: levels[parseInt(this.id)],
137 |       mode: 'train',
138 |       levelsLength: levels.length,
139 |       tiles: tiles,
140 |       colorSchemes: [
141 |         {name: "RedGreen", negative: 'red', positive: 'green'},
142 |         {name: "RedGreenWiki", negative: "#F3796F", positive: "#9DDB73"},
143 |         {name: "TensorFlow", negative:  'rgb(245, 147, 34)', positive: 'rgb(8, 119, 189)'},
144 |         {name: "sklearn", negative:  'rgb(255, 0, 0)', positive: 'rgb(0, 0, 255)'},
145 |       ],
146 |       selectedColorScheme: {name: "RedGreen", negative: 'red', positive: 'green'},
147 |       confusionMatrixMetrics: confusionMatrixMetrics,
148 |     };
149 |   },
150 |   computed: {
151 |     level: function() {
152 |       return levels[parseInt(this.id) - 1];
153 |     },
154 |     lvlId: function() {
155 |       return parseInt(this.id);
156 |     },
157 |     metrics: function() {
158 |       return computeMetrics(this.level['train'].points, this.tiles)
159 |     },
160 |     metricsPoints: function() {
161 |       return splitByMetrics(this.level['train'].points, this.tiles)
162 |     },
163 |     metricsVal: function() {
164 |       return computeMetrics(this.level['validation'].points, this.tiles)
165 |     },
166 |     metricsPointsVal: function() {
167 |       return splitByMetrics(this.level['validation'].points, this.tiles)
168 |     },
169 |     datasetHasPredictions: function() {
170 |       return datasetHasPredictions(this.level.name);
171 |     },
172 |   },
173 |   watch: {
174 |     id: function() {
175 |       this.mode = 'train';
176 |       this.resetSelection(0);
177 |     }
178 |   },
179 |   methods: {
180 |     resetSelection: function(targetValue) {
181 |       this.tiles.forEach((d) => d.v = targetValue);
182 |     },
183 |     resetSelectionRandom: function() {
184 |       this.tiles.forEach((d) => d.v = +(Math.random() > 0.5));
185 |     },
186 |     resetSelectionByClassifier: function(classifierName) {
187 |       getPredictions(this.tiles, this.level.train.name, classifierName);
188 |     },
189 |     setMode: function(mode) {
190 |       this.mode = mode;
191 |     },
192 |   }
193 | }
194 | </script>
195 | 
196 | <style>
197 | #app {
198 |   font-family: 'Avenir', Helvetica, Arial, sans-serif;
199 |   -webkit-font-smoothing: antialiased;
200 |   -moz-osx-font-smoothing: grayscale;
201 |   text-align: center;
202 |   color: #2c3e50;
203 |   margin-top: 60px;
204 | }
205 | 
206 | .column {
207 |   float: left;
208 |   width: 50%;
209 | }
210 | 
211 | /* Clear floats after the columns */
212 | .row:after {
213 |   content: "";
214 |   display: table;
215 |   clear: both;
216 | }
217 | </style>
218 | 


--------------------------------------------------------------------------------
/notebooks/sklearn_classifier_comparison.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "code",
  5 |    "execution_count": null,
  6 |    "metadata": {},
  7 |    "outputs": [],
  8 |    "source": [
  9 |     "import numpy as np\n",
 10 |     "import matplotlib.pyplot as plt\n",
 11 |     "from matplotlib.colors import ListedColormap\n",
 12 |     "from sklearn.model_selection import train_test_split\n",
 13 |     "from sklearn.preprocessing import StandardScaler\n",
 14 |     "from sklearn.datasets import make_moons, make_circles, make_classification\n",
 15 |     "from sklearn.neural_network import MLPClassifier\n",
 16 |     "from sklearn.neighbors import KNeighborsClassifier\n",
 17 |     "from sklearn.svm import SVC\n",
 18 |     "from sklearn.gaussian_process import GaussianProcessClassifier\n",
 19 |     "from sklearn.gaussian_process.kernels import RBF\n",
 20 |     "from sklearn.tree import DecisionTreeClassifier\n",
 21 |     "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
 22 |     "from sklearn.naive_bayes import GaussianNB\n",
 23 |     "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis"
 24 |    ]
 25 |   },
 26 |   {
 27 |    "cell_type": "code",
 28 |    "execution_count": null,
 29 |    "metadata": {},
 30 |    "outputs": [],
 31 |    "source": [
 32 |     "h = .02  # step size in the mesh\n",
 33 |     "\n",
 34 |     "clf_names = [\"Nearest Neighbors\", \"Linear SVM\", \"RBF SVM\", \"Gaussian Process\",\n",
 35 |     "         \"Decision Tree\", \"Random Forest\", \"Neural Net\", \"AdaBoost\",\n",
 36 |     "         \"Naive Bayes\", \"QDA\"]\n",
 37 |     "\n",
 38 |     "classifiers = [\n",
 39 |     "    KNeighborsClassifier(3),\n",
 40 |     "    SVC(kernel=\"linear\", C=0.025, probability=True),\n",
 41 |     "    SVC(gamma=2, C=1, probability=True),\n",
 42 |     "    GaussianProcessClassifier(1.0 * RBF(1.0)),\n",
 43 |     "    DecisionTreeClassifier(max_depth=5),\n",
 44 |     "    RandomForestClassifier(max_depth=5, n_estimators=10, max_features=1),\n",
 45 |     "    MLPClassifier(alpha=1, max_iter=500),\n",
 46 |     "    AdaBoostClassifier(),\n",
 47 |     "    GaussianNB(),\n",
 48 |     "    QuadraticDiscriminantAnalysis()]"
 49 |    ]
 50 |   },
 51 |   {
 52 |    "cell_type": "code",
 53 |    "execution_count": null,
 54 |    "metadata": {},
 55 |    "outputs": [],
 56 |    "source": [
 57 |     "def twospirals(n_points, noise=.5):\n",
 58 |     "    \"\"\"\n",
 59 |     "     Returns the two spirals dataset.\n",
 60 |     "     https://glowingpython.blogspot.com/2017/04/solving-two-spirals-problem-with-keras.html\n",
 61 |     "    \"\"\"\n",
 62 |     "    n = np.sqrt(np.random.rand(n_points,1)) * 780 * (2*np.pi)/360\n",
 63 |     "    d1x = -np.cos(n)*n + np.random.rand(n_points,1) * noise\n",
 64 |     "    d1y = np.sin(n)*n + np.random.rand(n_points,1) * noise\n",
 65 |     "    return (np.vstack((np.hstack((d1x,d1y)),np.hstack((-d1x,-d1y)))), \n",
 66 |     "            np.hstack((np.zeros(n_points),np.ones(n_points))))"
 67 |    ]
 68 |   },
 69 |   {
 70 |    "cell_type": "code",
 71 |    "execution_count": null,
 72 |    "metadata": {},
 73 |    "outputs": [],
 74 |    "source": [
 75 |     "n_points = 100\n",
 76 |     "\n",
 77 |     "X, y = make_classification(n_samples=n_points, n_features=2, n_redundant=0, n_informative=2,\n",
 78 |     "                           random_state=1, n_clusters_per_class=1)\n",
 79 |     "rng = np.random.RandomState(42)\n",
 80 |     "X += 2 * rng.uniform(size=X.shape)\n",
 81 |     "linearly_separable = (X, y)\n",
 82 |     "\n",
 83 |     "rng = np.random.RandomState(0)\n",
 84 |     "X = rng.randn(n_points, 2)\n",
 85 |     "y = np.logical_xor(X[:, 0] > 0, X[:, 1] > 0)\n",
 86 |     "X += rng.uniform(size=X.shape)\n",
 87 |     "xor = (X, y.astype(int))\n",
 88 |     "\n",
 89 |     "X, y = twospirals(n_points)\n",
 90 |     "X += 2 *rng.uniform(size=X.shape)\n",
 91 |     "spirals = (X, y)\n",
 92 |     "\n",
 93 |     "datasets = [make_moons(n_samples=n_points, noise=0.3, random_state=0),\n",
 94 |     "            make_circles(n_samples=n_points, noise=0.2, factor=0.5, random_state=1),\n",
 95 |     "            linearly_separable,\n",
 96 |     "            spirals,\n",
 97 |     "            xor\n",
 98 |     "            ]"
 99 |    ]
100 |   },
101 |   {
102 |    "cell_type": "code",
103 |    "execution_count": null,
104 |    "metadata": {},
105 |    "outputs": [],
106 |    "source": [
107 |     "import json\n",
108 |     "\n",
109 |     "def get_dataset_dicts(X, y):\n",
110 |     "    return [{'x': x1, 'y': x2, 'v': c}\n",
111 |     "            for x1, x2, c in zip(X[:, 0].tolist(), X[:, 1].tolist(), y.reshape(-1).tolist())]\n",
112 |     "\n",
113 |     "def get_dataset(X_train, X_test, y_train, y_test, name, kwargs):\n",
114 |     "    return {    \n",
115 |     "        'name': name,\n",
116 |     "        'data': {\n",
117 |     "            'train': get_dataset_dicts(X_train, y_train),\n",
118 |     "            'test': get_dataset_dicts(X_test, y_test),\n",
119 |     "        },\n",
120 |     "        **kwargs\n",
121 |     "    }\n",
122 |     "\n",
123 |     "def save_dataset(X_train, X_test, y_train, y_test, name, kwargs):\n",
124 |     "    with open('dataset-{}.json'.format(name), 'w') as f:\n",
125 |     "        json.dump(\n",
126 |     "            get_dataset(X_train, X_test, y_train, y_test, name, kwargs),\n",
127 |     "            f, indent=2\n",
128 |     "        )\n",
129 |     "\n",
130 |     "def save_json(filename, data):\n",
131 |     "    with open('{}.json'.format(filename), 'w') as f:\n",
132 |     "        json.dump(data, f, indent=2)\n"
133 |    ]
134 |   },
135 |   {
136 |    "cell_type": "code",
137 |    "execution_count": null,
138 |    "metadata": {},
139 |    "outputs": [],
140 |    "source": [
141 |     "def scale_dataset(X):\n",
142 |     "    # scale to [-1, 1]\n",
143 |     "    for i in range(X.shape[1]):\n",
144 |     "        X[:, i] = 2. * (X[:, i] - X[:, i].min()) / (X[:, i].max() - X[:, i].min()) - 1.\n",
145 |     "    return X"
146 |    ]
147 |   },
148 |   {
149 |    "cell_type": "code",
150 |    "execution_count": null,
151 |    "metadata": {
152 |     "scrolled": false
153 |    },
154 |    "outputs": [],
155 |    "source": [
156 |     "ds_names = ['moons', 'circles', 'linear', 'spirals', 'xor']\n",
157 |     "\n",
158 |     "Zs = []\n",
159 |     "\n",
160 |     "figure = plt.figure(figsize=(27, 9))\n",
161 |     "i = 1\n",
162 |     "\n",
163 |     "predictions = {}\n",
164 |     "scaled_datasets = []\n",
165 |     "\n",
166 |     "# iterate over datasets\n",
167 |     "for ds_cnt, ds in enumerate(datasets):\n",
168 |     "    # preprocess dataset, split into training and test part\n",
169 |     "    X, y = ds\n",
170 |     "    X = StandardScaler().fit_transform(X)\n",
171 |     "    X = scale_dataset(X)\n",
172 |     "    \n",
173 |     "    X_train, X_test, y_train, y_test = \\\n",
174 |     "        train_test_split(X, y, test_size=.4, random_state=42)\n",
175 |     "\n",
176 |     "    x_min, x_max = X[:, 0].min(), X[:, 0].max()\n",
177 |     "    y_min, y_max = X[:, 1].min(), X[:, 1].max()\n",
178 |     "\n",
179 |     "    xx, yy = np.meshgrid(np.arange(-1, 1, 0.2),\n",
180 |     "                     np.arange(-1, 1, 0.2))\n",
181 |     "    \n",
182 |     "    scaled_datasets.append(get_dataset(\n",
183 |     "        X_train, X_test, y_train, y_test, ds_names[ds_cnt],\n",
184 |     "        {'xmin': x_min, 'xmax': x_max, 'ymin': y_min, 'ymax': y_max}\n",
185 |     "    ))\n",
186 |     "\n",
187 |     "    # just plot the dataset first\n",
188 |     "    cm = plt.cm.RdBu\n",
189 |     "    cm_bright = ListedColormap(['#FF0000', '#0000FF'])\n",
190 |     "    ax = plt.subplot(len(datasets), len(classifiers) + 1, i)\n",
191 |     "    if ds_cnt == 0:\n",
192 |     "        ax.set_title(\"Input data\")\n",
193 |     "    # Plot the training points\n",
194 |     "    ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright,\n",
195 |     "               edgecolors='k')\n",
196 |     "    # Plot the testing points\n",
197 |     "    ax.scatter(X_test[:, 0], X_test[:, 1], c=y_test, cmap=cm_bright, alpha=0.6,\n",
198 |     "               edgecolors='k')\n",
199 |     "    ax.set_xlim(xx.min(), xx.max())\n",
200 |     "    ax.set_ylim(yy.min(), yy.max())\n",
201 |     "    ax.set_xticks(())\n",
202 |     "    ax.set_yticks(())\n",
203 |     "    i += 1\n",
204 |     "\n",
205 |     "    Zs.append({})\n",
206 |     "    \n",
207 |     "    predictions[ds_names[ds_cnt]] = {}\n",
208 |     "    # iterate over classifiers\n",
209 |     "    for name, clf in zip(clf_names, classifiers):\n",
210 |     "        ax = plt.subplot(len(datasets), len(classifiers) + 1, i)\n",
211 |     "        clf.fit(X_train, y_train)\n",
212 |     "        score = clf.score(X_test, y_test)\n",
213 |     "\n",
214 |     "        # Plot the decision boundary. For that, we will assign a color to each\n",
215 |     "        # point in the mesh [x_min, x_max]x[y_min, y_max].\n",
216 |     "#         Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
217 |     "        Z = clf.predict_proba(np.c_[(xx + 0.1).ravel(), (yy + 0.1).ravel()])[:, 1]\n",
218 |     "        \n",
219 |     "        predictions[ds_names[ds_cnt]][name] = get_dataset_dicts(np.c_[xx.ravel(), yy.ravel()], Z)\n",
220 |     "\n",
221 |     "        # Put the result into a color plot\n",
222 |     "        Z = Z.reshape(xx.shape)\n",
223 |     "        ax.contourf(xx, yy, Z, cmap=cm, alpha=.8)\n",
224 |     "\n",
225 |     "        Zs[ds_cnt][name] = Z\n",
226 |     "        \n",
227 |     "        # Plot the training points\n",
228 |     "        ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright,\n",
229 |     "                   edgecolors='k')\n",
230 |     "        # Plot the testing points\n",
231 |     "        ax.scatter(X_test[:, 0], X_test[:, 1], c=y_test, cmap=cm_bright,\n",
232 |     "                   edgecolors='k', alpha=0.6)\n",
233 |     "\n",
234 |     "        ax.set_xlim(xx.min(), xx.max())\n",
235 |     "        ax.set_ylim(yy.min(), yy.max())\n",
236 |     "        ax.set_xticks(())\n",
237 |     "        ax.set_yticks(())\n",
238 |     "        if ds_cnt == 0:\n",
239 |     "            ax.set_title(name)\n",
240 |     "        ax.text(xx.max() - .3, yy.min() + .3, ('%.2f' % score).lstrip('0'),\n",
241 |     "                size=15, horizontalalignment='right')\n",
242 |     "        i += 1\n",
243 |     "\n",
244 |     "save_json('datasets', {'datasets': scaled_datasets})\n",
245 |     "save_json('predictions', {'predictions': predictions})\n",
246 |     "\n",
247 |     "plt.tight_layout()\n",
248 |     "plt.show()"
249 |    ]
250 |   },
251 |   {
252 |    "cell_type": "code",
253 |    "execution_count": null,
254 |    "metadata": {},
255 |    "outputs": [],
256 |    "source": [
257 |     "def compare(pred1, pred2):\n",
258 |     "    return np.sum(pred1 == pred2) / (pred1.shape[0] * pred2.shape[1])"
259 |    ]
260 |   },
261 |   {
262 |    "cell_type": "code",
263 |    "execution_count": null,
264 |    "metadata": {},
265 |    "outputs": [],
266 |    "source": [
267 |     "import itertools\n",
268 |     "import pandas as pd\n",
269 |     "\n",
270 |     "preds = Zs[0]\n",
271 |     "comparisons = pd.Series()\n",
272 |     "for clf1, clf2 in itertools.combinations(preds.keys(), 2):\n",
273 |     "    comparisons['{} vs {}'.format(clf1, clf2)] = compare(preds[clf1], preds[clf2])\n",
274 |     "\n",
275 |     "comparisons.sort_values()"
276 |    ]
277 |   }
278 |  ],
279 |  "metadata": {
280 |   "kernelspec": {
281 |    "display_name": "Python 3",
282 |    "language": "python",
283 |    "name": "python3"
284 |   },
285 |   "language_info": {
286 |    "codemirror_mode": {
287 |     "name": "ipython",
288 |     "version": 3
289 |    },
290 |    "file_extension": ".py",
291 |    "mimetype": "text/x-python",
292 |    "name": "python",
293 |    "nbconvert_exporter": "python",
294 |    "pygments_lexer": "ipython3",
295 |    "version": "3.5.2"
296 |   }
297 |  },
298 |  "nbformat": 4,
299 |  "nbformat_minor": 2
300 | }
301 | 


--------------------------------------------------------------------------------
/assets/datasets/all.json:
--------------------------------------------------------------------------------
   1 | {
   2 |   "datasets": [
   3 |     {
   4 |       "name": "moons",
   5 |       "ymax": 1.0,
   6 |       "xmax": 1.0,
   7 |       "data": {
   8 |         "test": [
   9 |           {
  10 |             "y": 0.18203365694264995,
  11 |             "x": -0.7467869182808023,
  12 |             "v": 0
  13 |           },
  14 |           {
  15 |             "y": 0.3149195542151335,
  16 |             "x": -0.5399640452323211,
  17 |             "v": 0
  18 |           },
  19 |           {
  20 |             "y": 0.44603418539086004,
  21 |             "x": -0.10610658469210454,
  22 |             "v": 0
  23 |           },
  24 |           {
  25 |             "y": 0.8567872358712652,
  26 |             "x": 0.28565477884220103,
  27 |             "v": 0
  28 |           },
  29 |           {
  30 |             "y": 0.08415853387682559,
  31 |             "x": 0.34009928391027366,
  32 |             "v": 0
  33 |           },
  34 |           {
  35 |             "y": -0.6855681940141051,
  36 |             "x": 0.33965299725433695,
  37 |             "v": 1
  38 |           },
  39 |           {
  40 |             "y": 0.3718192769057296,
  41 |             "x": 0.144619827768681,
  42 |             "v": 0
  43 |           },
  44 |           {
  45 |             "y": 0.7495222111702746,
  46 |             "x": -0.3252471714467493,
  47 |             "v": 0
  48 |           },
  49 |           {
  50 |             "y": 0.2654598716160219,
  51 |             "x": -0.4058810181608262,
  52 |             "v": 1
  53 |           },
  54 |           {
  55 |             "y": 0.5513796248761913,
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3068 |   ]
3069 | }


--------------------------------------------------------------------------------