├── .github └── workflows │ └── static.yml ├── .gitignore ├── README.md ├── about.html ├── css └── freelancer.css ├── data ├── multi-matshow │ ├── particle_0.npy │ ├── particle_1.npy │ ├── particle_2.npy │ ├── particle_3.npy │ ├── particle_4.npy │ ├── particle_5.npy │ ├── velocity_0.npy │ ├── velocity_1.npy │ ├── velocity_2.npy │ ├── velocity_3.npy │ ├── velocity_4.npy │ └── velocity_5.npy ├── single-3dplot-2.npy ├── single-scatter-4-adap-x.npy ├── single-scatter-4-adap-y.npy ├── single-scatter-4-value.npy ├── single-scatter-5-hist.npy └── single-scatter-5-pred.npy ├── fig ├── multi-matshow.jpg ├── readme │ ├── homepage.png │ ├── single-linear-1-page.png │ └── title-image.png ├── single-3dplot-1.jpg ├── single-3dplot-2.jpg ├── single-hist-horizon.jpg ├── single-hist-vertical.jpg ├── single-linear-1.jpg ├── single-linear-2.jpg ├── single-linear-3.jpg ├── single-scatter-1.jpg ├── single-scatter-2.jpg ├── single-scatter-3.jpg ├── single-scatter-4.jpg ├── single-scatter-5.jpg └── utils │ └── court.png ├── index.html ├── js ├── contact_me.js ├── freelancer.min.js └── jqBootstrapValidation.js ├── notebook ├── multi-matshow.ipynb ├── single-3dplot.ipynb ├── single-hist.ipynb ├── single-linear.ipynb └── single-scatter.ipynb ├── pages ├── multi-matshow.html ├── single-3dplot-1.html ├── single-3dplot-2.html ├── single-hist-horizontal.html ├── single-hist-vertical.html ├── single-lineplot-1.html ├── single-lineplot-2.html ├── single-lineplot-3.html ├── single-scatter-1.html ├── single-scatter-2.html ├── single-scatter-3.html ├── single-scatter-4.html └── single-scatter-5.html ├── posts.html └── vendor ├── bootstrap ├── css │ └── bootstrap.min.css └── js │ └── bootstrap.min.js ├── font-awesome ├── css │ └── font-awesome.min.css └── fonts │ └── fontawesome-webfont.woff2 └── jquery └── jquery.min.js /.github/workflows/static.yml: -------------------------------------------------------------------------------- 1 | # Simple workflow for deploying static content to GitHub Pages 2 | name: matplotlib-prefab 3 | 4 | on: 5 | # Runs on pushes targeting the default branch 6 | push: 7 | branches: ["main"] 8 | 9 | # Allows you to run this workflow manually from the Actions tab 10 | workflow_dispatch: 11 | 12 | # Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages 13 | permissions: 14 | contents: read 15 | pages: write 16 | id-token: write 17 | 18 | # Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued. 19 | # However, do NOT cancel in-progress runs as we want to allow these production deployments to complete. 20 | concurrency: 21 | group: "pages" 22 | cancel-in-progress: false 23 | 24 | jobs: 25 | # Single deploy job since we're just deploying 26 | deploy: 27 | environment: 28 | name: github-pages 29 | url: ${{ steps.deployment.outputs.page_url }} 30 | runs-on: ubuntu-latest 31 | steps: 32 | - name: Checkout 33 | uses: actions/checkout@v3 34 | - name: Setup Pages 35 | uses: actions/configure-pages@v3 36 | - name: Upload artifact 37 | uses: actions/upload-pages-artifact@v2 38 | with: 39 | # Upload entire repository 40 | path: '.' 41 | - name: Deploy to GitHub Pages 42 | id: deployment 43 | uses: actions/deploy-pages@v2 44 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | Matplotlib Prefab is a repository based on matplotlib package, which provides several matplotlib ploting templates for *line plot*, *hist plot*, *scatter plot*, and some complex plottings. You can check the website at [cbhua.github.io/matplotlib-prefab](https://cbhua.github.io/matplotlib-prefab/). 4 | 5 | ### 💡 Introduction 6 | 7 | I have a passion for creating visually appealing figures in publications. During my time writing papers, I often dedicated significant effort to crafting plots. In this repository, I've compiled some of my previous `matplotlib` plotting source code and have designed several templates for convenient reuse. I've chosen not to package this content due to the myriad of customizable parameters. Instead, I believe a template approach is more straightforward to modify and repurpose. I hope these templates inspire you and provide techniques to craft beautiful `matplotlib` figures. 8 | 9 | ### ⚙️ Environment 10 | 11 | I've aimed to keep dependencies to a minimum; thus, a basic combination of `matplotlib` and `numpy` should suffice. However, it's important to note that I've incorporated LaTeX font families and formatting. Therefore, you'll need to have [LaTeX](https://www.latex-project.org/get/) installed on your operating system. 12 | 13 | ``` 14 | Python Version: 3.10 (develop) 15 | Python Package: matplotlib 3.8 (support Latex text), numpy 16 | Other: to use the Latex illustration style, the Latex is required to be installed 17 | ``` 18 | 19 | ### 🔦 How to use 20 | 21 | You can easily go to the website: [cbhua.github.io/matplotlib-prefab](https://cbhua.github.io/matplotlib-prefab/) and see the example figures of each prefabs: 22 | 23 | 24 | 25 | You can click on the figure to view the associated template code. Most of the code for these figures is self-contained and can be run independently. However, a few require external data. For those instances, please refer to the accompanying notebook. 26 | 27 | 28 | 29 | You can also refer to the `notebook` directory to access Jupyter notebooks for those example figures and tailor them to your needs. 30 | 31 | ### 🔧 Structure 32 | 33 | ``` 34 | . 35 | ├── css - webpage 36 | ├── js - webpage 37 | ├── pages - webpage 38 | ├── vendor - webpage 39 | ├── data - some complex figures reauqired external data 40 | ├── fig - example figures 41 | ├── notebook - jupyter notebook for creating figures 42 | └── *.html - webpage 43 | ``` 44 | 45 | ### 🖼 Visualization Example 46 | 47 | **Line Plots**: [Jupyter notebook](https://github.com/cbhua/matplotlib-prefab/blob/main/notebook/single-linear.ipynb) 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | **Hist Plots**: [Jupyter notebook](https://github.com/cbhua/matplotlib-prefab/blob/main/notebook/single-hist.ipynb) 56 | 57 | 58 | 59 | 60 | 61 | **Scatter Plots**: [Jupyter notebook](https://github.com/cbhua/matplotlib-prefab/blob/main/notebook/single-scatter.ipynb) 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | **Complex Examples**: [3D Plots jupyter notebook](https://github.com/cbhua/matplotlib-prefab/blob/main/notebook/single-3dplot.ipynb), [Matshow jupyter notebook](https://github.com/cbhua/matplotlib-prefab/blob/main/notebook/multi-matshow.ipynb) 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | ### 📬 Contact 82 | 83 | If you have any question or find any bug, feel free to raise an issue. If you have ideas to contribute to this repo, welcome to pull request or contact cbhua@kaist.ac.kr. Thanks for interested to our work! 84 | -------------------------------------------------------------------------------- /about.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
Skip to main content
41 | 42 | 43 | 72 | 73 |
74 |
75 | 76 |

77 |
About the Matplotlib Prefab

78 |

79 | Matplotlib Prefab is a repository based on matplotlib package, which provides several matplotlib ploting templates for line plot, 80 | hist plot, scatter plot, and some complex plottings. You can see the GitHub repository at https://github.com/cbhua/matplotlib-prefab. 81 |

82 |
83 |

Introduction

84 |

85 | I have a passion for creating visually appealing figures in publications. During my time writing papers, I often dedicated significant effort to crafting plots. 86 | In this repository, I've compiled some of my previous `matplotlib` plotting source code and have designed several templates for convenient reuse. 87 | I've chosen not to package this content due to the myriad of customizable parameters. Instead, I believe a template approach is more straightforward to modify and repurpose. 88 | I hope these templates inspire you and provide techniques to craft beautiful `matplotlib` figures. 89 |

90 |
91 |

Environment

92 |

93 | I've aimed to keep dependencies to a minimum; thus, a basic combination of matplotlib and numpy should suffice. However, it's important to note that I've incorporated LaTeX font families and formatting. 94 | Therefore, you'll need to have LaTeX installed on your operating system. 95 |

96 | 

 97 | Python Version: 3.10 (develop)
 98 | Python Package: matplotlib 3.8 (support Latex text), numpy
 99 | Other: to use the Latex illustration style, the Latex is required to be installed
100 |
101 |
102 |

How to use

103 |

104 | You can easily go to the home page: cbhua.github.io/matplotlib-prefab and see the example figures of each prefabs: 105 |

106 | 107 |

108 | You can click on the figure to view the associated template code. Most of the code for these figures is self-contained and can be run independently. However, a few require external data. For those instances, please refer to the accompanying notebook. 109 |

110 | 111 |

112 | You can also refer to the GitHub notebook directory to access Jupyter notebooks for those example figures and tailor them to your needs. 113 |

114 |

115 | Have fun! 116 |

117 |
118 |
119 | 120 | 121 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 150 | 151 | 152 | -------------------------------------------------------------------------------- /css/freelancer.css: -------------------------------------------------------------------------------- 1 | /*! 2 | * Start Bootstrap - Freelancer v3.3.7+1 (http://startbootstrap.com/template-overviews/freelancer) 3 | * Copyright 2013-2016 Start Bootstrap 4 | * Licensed under MIT (https://github.com/BlackrockDigital/startbootstrap/blob/gh-pages/LICENSE) 5 | */ 6 | 7 | .container { 8 | margin-right: auto; 9 | margin-left: auto; 10 | max-width: 720px; /* or 950px */ 11 | } 12 | 13 | body { 14 | /* font-family: 'Lato', 'Helvetica Neue', Helvetica, Arial, sans-serif; */ 15 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 16 | overflow-x: hidden; 17 | line-height: 145%; 18 | height: 100%; 19 | background-color:#FAF8EC; 20 | color: #333333; 21 | font-size:12px; 22 | 23 | } 24 | p { 25 | font-size: 12px; 26 | } 27 | p.small { 28 | font-size: 12px; 29 | } 30 | a, 31 | a:hover, 32 | a:focus, 33 | a:active, 34 | a.active { 35 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 36 | color: #296FA3; 37 | font-weight: bold; 38 | } 39 | h1, 40 | h2, 41 | h3 { 42 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 43 | /* text-transform: uppercase; */ 44 | font-size: 16px; 45 | font-weight: bold; 46 | line-height: 145%; 47 | } 48 | h4 { 49 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 50 | /* text-transform: uppercase; */ 51 | font-size: 14px; 52 | font-weight: bold; 53 | } 54 | h5 { 55 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 56 | /* text-transform: uppercase; */ 57 | font-size: 12px; 58 | font-weight: bold; 59 | line-height: 145%; 60 | } 61 | h6 62 | hr.star-light, 63 | hr.star-primary { 64 | padding: 0; 65 | border: none; 66 | border-top: solid 5px; 67 | text-align: center; 68 | max-width: 250px; 69 | margin: 25px auto 30px; 70 | } 71 | hr.star-light:after, 72 | hr.star-primary:after { 73 | content: "\f005"; 74 | font-family: FontAwesome; 75 | display: inline-block; 76 | position: relative; 77 | top: -0.8em; 78 | font-size: 2em; 79 | padding: 0 0.25em; 80 | } 81 | hr.star-light { 82 | border-color: white; 83 | } 84 | hr.star-light:after { 85 | background-color: #18BC9C; 86 | color: white; 87 | } 88 | hr.star-primary { 89 | border-color: #2C3E50; 90 | } 91 | hr.star-primary:after { 92 | background-color: white; 93 | color: #2C3E50; 94 | } 95 | .img-centered { 96 | margin: 0 auto; 97 | } 98 | 99 | hr { 100 | border: 0; 101 | height: 1px; 102 | background-image: linear-gradient(to right, rgba(0, 0, 0, 0), rgba(0, 0, 0, 0.75), rgba(0, 0, 0, 0)); 103 | } 104 | 105 | ul { margin-top: 0px; 106 | margin-left: 0;} 107 | 108 | li { margin-top: 5px; margin-left: 0;} 109 | li.header {margin-top: 0px;} 110 | 111 | header { 112 | text-align: center; 113 | background: #FAF8EC; 114 | color: #333333; 115 | } 116 | header .container { 117 | padding-top: 100px; 118 | padding-bottom: 50px; 119 | } 120 | header img { 121 | display: block; 122 | margin: 0 auto 20px; 123 | } 124 | header .intro-text .name { 125 | display: block; 126 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 127 | /* text-transform: uppercase; */ 128 | font-weight: 700; 129 | font-size: 2em; 130 | } 131 | header .intro-text .skills { 132 | font-size: 1.25em; 133 | font-weight: 300; 134 | } 135 | @media (min-width: 768px) { 136 | header .container { 137 | padding-top: 200px; 138 | padding-bottom: 100px; 139 | } 140 | header .intro-text .name { 141 | font-size: 4.75em; 142 | } 143 | header .intro-text .skills { 144 | font-size: 1.75em; 145 | } 146 | } 147 | .navbar-custom { 148 | background: #FAF8EC; 149 | font-family: "Lucida Grande","Lucida Sans Unicode", Helvetica, Arial, sans-serif; 150 | /* text-transform: uppercase; */ 151 | font-weight: 500; 152 | border: none; 153 | } 154 | .navbar-custom .navbar-brand { 155 | color: #BB3322; 156 | font-weight: bold; 157 | text-align: center; 158 | } 159 | .navbar-custom .navbar-brand:hover { 160 | color: #BB3322; 161 | font-weight: bold; 162 | } 163 | .navbar-custom .navbar-nav { 164 | letter-spacing: 1px; 165 | } 166 | .navbar-custom .navbar-nav li a { 167 | color: #333333; 168 | } 169 | .navbar-custom .navbar-nav li a:hover { 170 | color: #BB3322; 171 | } 172 | .navbar-custom .navbar-nav li a:focus, 173 | .navbar-custom .navbar-nav li a:active { 174 | color: #333333; 175 | } 176 | .navbar-custom .navbar-nav li.active a { 177 | color: #BB3322; 178 | background: #FAF8EC; 179 | } 180 | .navbar-custom .navbar-nav li.active a:hover, 181 | .navbar-custom .navbar-nav li.active a:focus, 182 | .navbar-custom .navbar-nav li.active a:active { 183 | color: #333333; 184 | background: #FAF8EC; 185 | } 186 | section { 187 | padding: 80px 0; 188 | } 189 | section h2 { 190 | margin: 0; 191 | font-size: 3em; 192 | } 193 | section.success { 194 | background: #FAF8EC; 195 | color: #333333; 196 | } 197 | @media (max-width: 767px) { 198 | section { 199 | padding: 75px 0; 200 | } 201 | section.first { 202 | padding-top: 75px; 203 | } 204 | } 205 | #portfolio .portfolio-item { 206 | margin: 0 0 15px; 207 | right: 0; 208 | } 209 | #portfolio .portfolio-item .portfolio-link { 210 | display: block; 211 | position: relative; 212 | max-width: 400px; 213 | margin: 0 auto; 214 | } 215 | #portfolio .portfolio-item .portfolio-link .caption { 216 | background: rgba(24, 188, 156, 0.9); 217 | position: absolute; 218 | width: 100%; 219 | height: 100%; 220 | opacity: 0; 221 | transition: all ease 0.5s; 222 | -webkit-transition: all ease 0.5s; 223 | -moz-transition: all ease 0.5s; 224 | } 225 | #portfolio .portfolio-item .portfolio-link .caption:hover { 226 | opacity: 1; 227 | } 228 | #portfolio .portfolio-item .portfolio-link .caption .caption-content { 229 | position: absolute; 230 | width: 100%; 231 | height: 20px; 232 | font-size: 20px; 233 | text-align: center; 234 | top: 50%; 235 | margin-top: -12px; 236 | color: #333333; 237 | } 238 | #portfolio .portfolio-item .portfolio-link .caption .caption-content i { 239 | margin-top: -12px; 240 | } 241 | #portfolio .portfolio-item .portfolio-link .caption .caption-content h3, 242 | #portfolio .portfolio-item .portfolio-link .caption .caption-content h4 { 243 | margin: 0; 244 | } 245 | #portfolio * { 246 | z-index: 2; 247 | } 248 | @media (min-width: 767px) { 249 | #portfolio .portfolio-item { 250 | margin: 0 0 30px; 251 | } 252 | } 253 | .floating-label-form-group { 254 | position: relative; 255 | margin-bottom: 0; 256 | padding-bottom: 0.5em; 257 | border-bottom: 1px solid #eeeeee; 258 | } 259 | .floating-label-form-group input, 260 | .floating-label-form-group textarea { 261 | z-index: 1; 262 | position: relative; 263 | padding-right: 0; 264 | padding-left: 0; 265 | border: none; 266 | border-radius: 0; 267 | font-size: 1.5em; 268 | background: none; 269 | box-shadow: none !important; 270 | resize: none; 271 | } 272 | .floating-label-form-group label { 273 | display: block; 274 | z-index: 0; 275 | position: relative; 276 | top: 2em; 277 | margin: 0; 278 | font-size: 0.85em; 279 | line-height: 1.764705882em; 280 | vertical-align: middle; 281 | vertical-align: baseline; 282 | opacity: 0; 283 | -webkit-transition: top 0.3s ease,opacity 0.3s ease; 284 | -moz-transition: top 0.3s ease,opacity 0.3s ease; 285 | -ms-transition: top 0.3s ease,opacity 0.3s ease; 286 | transition: top 0.3s ease,opacity 0.3s ease; 287 | } 288 | .floating-label-form-group:not(:first-child) { 289 | padding-left: 14px; 290 | border-left: 1px solid #eeeeee; 291 | } 292 | .floating-label-form-group-with-value label { 293 | top: 0; 294 | opacity: 1; 295 | } 296 | .floating-label-form-group-with-focus label { 297 | color: #18BC9C; 298 | } 299 | form .row:first-child .floating-label-form-group { 300 | border-top: 1px solid #eeeeee; 301 | } 302 | footer { 303 | color: white; 304 | } 305 | footer h3 { 306 | margin-bottom: 30px; 307 | } 308 | footer .footer-above { 309 | padding-top: 50px; 310 | background-color: #2C3E50; 311 | } 312 | footer .footer-col { 313 | margin-bottom: 50px; 314 | } 315 | footer .footer-below { 316 | padding: 25px 0; 317 | background-color: #FAF8EC; 318 | color: #888888; 319 | font-size: 11px; 320 | line-height: 12px; 321 | } 322 | .btn-outline { 323 | color: white; 324 | font-size: 20px; 325 | border: solid 2px white; 326 | background: transparent; 327 | transition: all 0.3s ease-in-out; 328 | margin-top: 15px; 329 | } 330 | .btn-outline:hover, 331 | .btn-outline:focus, 332 | .btn-outline:active, 333 | .btn-outline.active { 334 | color: #18BC9C; 335 | background: white; 336 | border: solid 2px white; 337 | } 338 | .btn-primary { 339 | color: white; 340 | background-color: #2C3E50; 341 | border-color: #2C3E50; 342 | font-weight: 700; 343 | } 344 | .btn-primary:hover, 345 | .btn-primary:focus, 346 | .btn-primary:active, 347 | .btn-primary.active, 348 | .open .dropdown-toggle.btn-primary { 349 | color: white; 350 | background-color: #1a242f; 351 | border-color: #161f29; 352 | } 353 | .btn-primary:active, 354 | .btn-primary.active, 355 | .open .dropdown-toggle.btn-primary { 356 | background-image: none; 357 | } 358 | .btn-primary.disabled, 359 | .btn-primary[disabled], 360 | fieldset[disabled] .btn-primary, 361 | .btn-primary.disabled:hover, 362 | .btn-primary[disabled]:hover, 363 | fieldset[disabled] .btn-primary:hover, 364 | .btn-primary.disabled:focus, 365 | .btn-primary[disabled]:focus, 366 | fieldset[disabled] .btn-primary:focus, 367 | .btn-primary.disabled:active, 368 | .btn-primary[disabled]:active, 369 | fieldset[disabled] .btn-primary:active, 370 | .btn-primary.disabled.active, 371 | .btn-primary[disabled].active, 372 | fieldset[disabled] .btn-primary.active { 373 | background-color: #2C3E50; 374 | border-color: #2C3E50; 375 | } 376 | .btn-primary .badge { 377 | color: #2C3E50; 378 | background-color: white; 379 | } 380 | .btn-success { 381 | color: white; 382 | background-color: #18BC9C; 383 | border-color: #18BC9C; 384 | font-weight: 700; 385 | } 386 | .btn-success:hover, 387 | .btn-success:focus, 388 | .btn-success:active, 389 | .btn-success.active, 390 | .open .dropdown-toggle.btn-success { 391 | color: white; 392 | background-color: #128f76; 393 | border-color: #11866f; 394 | } 395 | .btn-success:active, 396 | .btn-success.active, 397 | .open .dropdown-toggle.btn-success { 398 | background-image: none; 399 | } 400 | .btn-success.disabled, 401 | .btn-success[disabled], 402 | fieldset[disabled] .btn-success, 403 | .btn-success.disabled:hover, 404 | .btn-success[disabled]:hover, 405 | fieldset[disabled] .btn-success:hover, 406 | .btn-success.disabled:focus, 407 | .btn-success[disabled]:focus, 408 | fieldset[disabled] .btn-success:focus, 409 | .btn-success.disabled:active, 410 | .btn-success[disabled]:active, 411 | fieldset[disabled] .btn-success:active, 412 | .btn-success.disabled.active, 413 | .btn-success[disabled].active, 414 | fieldset[disabled] .btn-success.active { 415 | background-color: #18BC9C; 416 | border-color: #18BC9C; 417 | } 418 | .btn-success .badge { 419 | color: #18BC9C; 420 | background-color: white; 421 | } 422 | .btn-social { 423 | display: inline-block; 424 | height: 50px; 425 | width: 50px; 426 | border: 2px solid white; 427 | border-radius: 100%; 428 | text-align: center; 429 | font-size: 20px; 430 | line-height: 45px; 431 | } 432 | .scroll-top { 433 | position: fixed; 434 | right: 2%; 435 | bottom: 2%; 436 | width: 50px; 437 | height: 50px; 438 | z-index: 1049; 439 | } 440 | .scroll-top .btn { 441 | font-size: 20px; 442 | width: 50px; 443 | height: 50px; 444 | border-radius: 100%; 445 | line-height: 28px; 446 | } 447 | .portfolio-modal .modal-content { 448 | border-radius: 0; 449 | background-clip: border-box; 450 | -webkit-box-shadow: none; 451 | box-shadow: none; 452 | border: none; 453 | min-height: 100%; 454 | padding: 100px 0; 455 | text-align: center; 456 | } 457 | .portfolio-modal .modal-content h2 { 458 | margin: 0; 459 | font-size: 3em; 460 | } 461 | .portfolio-modal .modal-content img { 462 | margin-bottom: 30px; 463 | } 464 | .portfolio-modal .modal-content .item-details { 465 | margin: 30px 0; 466 | } 467 | .portfolio-modal .close-modal { 468 | position: absolute; 469 | width: 75px; 470 | height: 75px; 471 | background-color: transparent; 472 | top: 25px; 473 | right: 25px; 474 | cursor: pointer; 475 | } 476 | .portfolio-modal .close-modal:hover { 477 | opacity: 0.3; 478 | } 479 | .portfolio-modal .close-modal .lr { 480 | height: 75px; 481 | width: 1px; 482 | margin-left: 35px; 483 | background-color: #2C3E50; 484 | transform: rotate(45deg); 485 | -ms-transform: rotate(45deg); 486 | /* IE 9 */ 487 | -webkit-transform: rotate(45deg); 488 | /* 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div#maincontent { 528 | outline: none; 529 | } 530 | 531 | div.paper-title { 532 | font-size: 12px; 533 | font-weight: bold; 534 | color: #606060 535 | } 536 | 537 | div.pub-year { 538 | font-size: 12px; 539 | line-height: 145%; 540 | margin-top: 10px; 541 | font-weight: bold; 542 | padding-bottom: 6px; 543 | border-bottom: 1px solid #888888; 544 | } 545 | div.sec { 546 | font-size: 14px; 547 | line-height: 18px; 548 | font-weight: bold; 549 | padding-bottom: 7px; 550 | border-bottom: 1px solid #888888; 551 | } 552 | -------------------------------------------------------------------------------- /data/multi-matshow/particle_0.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cbhua/matplotlib-prefab/a3f6dfb0be2a995d7713994f3a8bc909a64c98ff/data/multi-matshow/particle_0.npy -------------------------------------------------------------------------------- /data/multi-matshow/particle_1.npy: 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Line Plots
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80 |
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86 |
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97 |
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102 | 103 |
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107 | 108 | 109 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 140 | -------------------------------------------------------------------------------- /js/contact_me.js: -------------------------------------------------------------------------------- 1 | $(function() { 2 | 3 | $("#contactForm input,#contactForm textarea").jqBootstrapValidation({ 4 | preventSubmit: true, 5 | submitError: function($form, event, errors) { 6 | // additional error messages or events 7 | }, 8 | submitSuccess: function($form, event) { 9 | // Prevent spam click and default submit behaviour 10 | $("#btnSubmit").attr("disabled", true); 11 | event.preventDefault(); 12 | 13 | // get values from FORM 14 | var name = $("input#name").val(); 15 | var email = $("input#email").val(); 16 | var phone = $("input#phone").val(); 17 | var message = $("textarea#message").val(); 18 | var firstName = name; // For Success/Failure Message 19 | // Check for white space in name for Success/Fail message 20 | if (firstName.indexOf(' ') >= 0) { 21 | firstName = name.split(' ').slice(0, -1).join(' '); 22 | } 23 | $.ajax({ 24 | url: "././mail/contact_me.php", 25 | type: "POST", 26 | data: { 27 | name: name, 28 | phone: phone, 29 | email: email, 30 | message: message 31 | }, 32 | cache: false, 33 | success: function() { 34 | // Enable button & show success message 35 | $("#btnSubmit").attr("disabled", false); 36 | $('#success').html("
"); 37 | $('#success > .alert-success').html(""); 39 | $('#success > .alert-success') 40 | .append("Your message has been sent. "); 41 | $('#success > .alert-success') 42 | .append('
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | import seaborn as sns
 84 | from matplotlib import cm
 85 | 
 86 | # Use LaTeX font
 87 | plt.rcParams.update({'text.usetex': True})
 88 | 
 89 | # Figure font config
 90 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 91 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 92 | legend_font = {'family': 'Palatino Linotype', 'size': 12}
 93 | text_font = {'family': 'Palatino Linotype', 'size': 12}
 94 | 
 95 | # Load data
 96 | particle = []
 97 | velocity = []
 98 | for i in range(6):
 99 |     particle.append(np.load('../data/multi-matshow/particle_' + str(i) + '.npy'))
100 |     velocity.append(np.load('../data/multi-matshow/velocity_' + str(i) + '.npy')) X-4)**2 + (8 * Y - 4)**2))
101 | 
102 | # Plot
103 | fig, axs = plt.subplots(2, 3, figsize=(8, 6))
104 | 
105 | for idx in range(6):
106 |     i = idx // 3
107 |     j = idx % 3
108 | 
109 |     for particle_idx, (x, y) in enumerate(zip(particle[idx][:, 0], particle[idx][:, 1])):
110 |         axs[i, j].scatter(
111 |             x, y, 
112 |             marker='o',
113 |             color=cm.RdYlBu_r(velocity[idx][particle_idx])
114 |         )
115 |     
116 |     # Label and title
117 |     axs[i, j].get_xaxis().set_visible(False)
118 |     axs[i, j].get_yaxis().set_visible(False)
119 |     axs[i, j].set_title(f'$t={idx}$', fontdict=title_font)
120 | 
121 |     # Axis range
122 |     axs[i, j].set_xlim([0.5, 5.5])
123 |     axs[i, j].set_ylim([0.5, 4])
124 | 
125 | plt.tight_layout()
126 | plt.savefig('../fig/multi-matshow.jpg', dpi=300)
127 |
128 | 144 |
145 |
146 |
147 |
148 | 149 | 150 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | -------------------------------------------------------------------------------- /pages/single-3dplot-1.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 91 | 
 92 | # Generate data
 93 | X = np.linspace(0, 1, num=256, endpoint=True)
 94 | Y = np.linspace(0, 1, num=256, endpoint=True)
 95 | X, Y = np.meshgrid(X, Y)
 96 | R = np.sqrt(1 * ((8 * X-4)**2 + (8 * Y - 4)**2))
 97 | Z = 0.5 * np.sin(R)
 98 | 
 99 | # Plot
100 | ax = plt.figure(figsize=(8, 6)).add_subplot(projection='3d')
101 | 
102 | surf = ax.plot_surface(
103 |     X, Y, Z, 
104 |     cmap=cm.coolwarm, 
105 |     linewidth=1, 
106 |     antialiased=False, 
107 |     alpha=0.3
108 | )
109 | contour = ax.contour(
110 |     X, Y, Z, 
111 |     zdir='z', 
112 |     levels=8, 
113 |     offset=-1, 
114 |     cmap=cm.coolwarm, 
115 |     alpha=0.4
116 | )
117 | 
118 | ax.set_xlim(0, 1)
119 | ax.set_ylim(0, 1)
120 | ax.set_zlim(-1, 0.5)
121 | 
122 | ax.set_xlabel('x', fontdict=label_font)
123 | ax.set_ylabel('y', fontdict=label_font)
124 | ax.set_zlabel('z', fontdict=label_font)
125 | ax.set_title(
126 |     r'Ground Truth for $u(x, y) = \mathrm{sin}(((8x-4)^2+(8y-4)^2)^{1/2})$', 
127 |     fontdict=title_font
128 | )
129 | 
130 | ax.tick_params(axis='both', which='major', labelsize=12)
131 | ax.tick_params(axis='both', which='minor', labelsize=12)
132 | 
133 | labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
134 | [label.set_fontname('serif') for label in labels]
135 | 
136 | plt.tight_layout()
137 | plt.savefig('../fig/single-3dplot-1.jpg', dpi=300)
138 |
139 | 155 |
156 |
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159 | 160 | 161 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | -------------------------------------------------------------------------------- /pages/single-3dplot-2.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 91 | 
 92 | # Load data
 93 | value = np.load('../data/single-3dplot-2.npy')
 94 | 
 95 | x, y, z = np.meshgrid(
 96 |     np.linspace(0, 1, num=64, endpoint=True),
 97 |     np.linspace(0, 1, num=64, endpoint=True),
 98 |     np.linspace(0, 1, num=64, endpoint=True)
 99 | )
100 | 
101 | # Plot
102 | ax = plt.figure(figsize=(6, 6)).add_subplot(projection='3d')
103 | ax.scatter(x, y, z, s=3, c=value, cmap=cm.inferno, alpha=0.1)
104 | 
105 | ax.set_xlabel('x', fontdict=label_font)
106 | ax.set_ylabel('y', fontdict=label_font)
107 | ax.set_zlabel('z', fontdict=label_font)
108 | ax.set_title('Single 3D Plot 2', fontdict=title_font)
109 | 
110 | ax.tick_params(axis='both', which='major', labelsize=12)
111 | ax.tick_params(axis='both', which='minor', labelsize=12)
112 | 
113 | labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
114 | [label.set_fontname('serif') for label in labels]
115 | 
116 | plt.tight_layout()
117 | plt.savefig('../fig/single-3dplot-2.jpg', dpi=300)
118 |
119 | 135 |
136 |
137 |
138 |
139 | 140 | 141 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | -------------------------------------------------------------------------------- /pages/single-hist-horizontal.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 12}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 91 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 92 | legend_font = {'family': 'Palatino Linotype', 'size': 12}
 93 | 
 94 | # Generate data
 95 | item = [
 96 |     'Model 1',
 97 |     'Model 2',
 98 |     'Model 3',
 99 |     'Model 4',
100 |     'Model 5',
101 | ]
102 | 
103 | value = np.array([
104 |     [1, 1.5, 2, 2.5, 3], 
105 |     [0.2, 0.4, 0.6, 0.8, 1], 
106 |     [0.1, 0.1, 0.1, 0.1, 0.1] 
107 | ])
108 | 
109 | std = np.array([
110 |     [0.1, 0.15, 0.2, 0.25, 0.3], 
111 |     [0.05, 0.05, 0.05, 0.05, 0.05], 
112 |     [0, 0, 0, 0, 0] 
113 | ])
114 | 
115 | # Plot
116 | fig, ax = plt.subplots( 1, figsize=(4, 4))
117 | 
118 | # Config
119 | height = 0.5
120 | 
121 | ax.barh(
122 |     item, value[0], xerr=std[0], 
123 |     height=height, 
124 |     color=cm.Set2(0), 
125 |     label='Value 1',
126 |     capsize=2, 
127 | )
128 | ax.barh(
129 |     item, value[1], xerr=std[1], 
130 |     left=value[0],
131 |     height=height, 
132 |     color=cm.Set2(1), 
133 |     label='Value 2'
134 | )
135 | ax.barh(
136 |     item, value[2], xerr=std[2], 
137 |     left=value[0] + value[1],
138 |     height=height, 
139 |     color=cm.Set2(2), 
140 |     label='Value 2'
141 | )
142 | 
143 | # Label and title
144 | ax.set_xlabel('X Label', **label_font)
145 | ax.set_title('Single Hist Plot (Horizontal)', **title_font)
146 | 
147 | # Legend
148 | ax.legend(loc='lower right', prop=legend_font)
149 | 
150 | # Axis
151 | ax.tick_params(axis='both', which='major', labelsize=12)
152 | 
153 | # Grid
154 | ax.grid(axis='both', color='black', alpha=0.1)
155 | 
156 | plt.tight_layout()
157 | plt.savefig('../fig/single-hist-horizon.jpg', dpi=300)
158 |
159 | 175 |
176 |
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179 | 180 | 181 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | -------------------------------------------------------------------------------- /pages/single-hist-vertical.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 12}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 91 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 92 | legend_font = {'family': 'Palatino Linotype', 'size': 12}
 93 | 
 94 | # Generate data
 95 | item = [
 96 |     'Model 1',
 97 |     'Model 2',
 98 |     'Model 3',
 99 |     'Model 4',
100 |     'Model 5',
101 | ]
102 | 
103 | value = np.array([
104 |     [1, 1.5, 2, 2.5, 3], 
105 |     [0.2, 0.4, 0.6, 0.8, 1], 
106 |     [0.1, 0.1, 0.1, 0.1, 0.1] 
107 | ])
108 | 
109 | std = np.array([
110 |     [0.1, 0.15, 0.2, 0.25, 0.3], 
111 |     [0.05, 0.05, 0.05, 0.05, 0.05], 
112 |     [0, 0, 0, 0, 0] 
113 | ])
114 | 
115 | # Plot
116 | fig, ax = plt.subplots(1, figsize=(4, 4))
117 | 
118 | # Color list
119 | color = [cm.Set2(1)] + [cm.Set2(0)] * 4
120 | 
121 | ax.bar(
122 |     item, value[0], yerr=std[0], 
123 |     width=0.65, 
124 |     color=color, 
125 |     capsize=2, 
126 | )
127 | 
128 | # Label and title
129 | ax.set_ylabel('Y Label', **label_font)
130 | ax.set_title('Single Hist Plot (Vertical)', **title_font)
131 | 
132 | # Axis
133 | ax.tick_params(axis='both', which='major', labelsize=12)
134 | 
135 | # Grid
136 | ax.grid(axis='both', color='black', alpha=0.1)
137 | 
138 | plt.tight_layout()
139 | plt.savefig('../fig/single-hist-vertical.jpg', dpi=300)
140 |
141 | 157 |
158 |
159 |
160 |
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41 | 42 | 43 | 72 | 73 |
74 |
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77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 91 | legend_font = {'family': 'Palatino Linotype', 'size': 12}
 92 | text_font = {'family': 'Palatino Linotype', 'size': 12}
 93 | 
 94 | # Generate data
 95 | x = np.linspace(0, 10, 100)
 96 | y1 = x ** 2
 97 | y2 = x ** 2 * np.log(x)
 98 | y3 = x ** 3
 99 | 
100 | fig, ax = plt.subplots(1, figsize=(4, 4))
101 | 
102 | ax.plot(x, y1, color=cm.Set2(0), linestyle='-', linewidth=2)
103 | ax.plot(x, y2, color=cm.Set2(1), linestyle='-.', linewidth=2)
104 | ax.plot(x, y3, color='gray', linestyle='--', linewidth=2)
105 | 
106 | # Label and title
107 | ax.set_xlabel('X Lable', fontdict=label_font)
108 | ax.set_ylabel('Y Lable', fontdict=label_font)
109 | ax.set_title('Single Line Plot 1', fontdict=title_font)
110 | 
111 | # Text info
112 | ax.text(
113 |     4, 180, 
114 |     r'$O(n^3)$' + '\n(Method 1)',
115 |     fontdict=text_font,
116 |     color='gray',
117 |     verticalalignment='center', 
118 |     horizontalalignment='center'
119 | )
120 | ax.text(
121 |     7.3, 180, 
122 |     r'$O(n^2)\mathrm{log}n$' + '\n(Method 2)',
123 |     fontdict=text_font,
124 |     color=cm.Set2(1),
125 |     verticalalignment='center', 
126 |     horizontalalignment='center'
127 | )
128 | ax.text(
129 |     8, 25, 
130 |     r'$O(n^2)$' + '\n(Method 3)',
131 |     fontdict=text_font,
132 |     color=cm.Set2(0),
133 |     verticalalignment='center', 
134 |     horizontalalignment='center'
135 | )
136 | 
137 | # Ticks fontsize and font family
138 | ax.tick_params(axis='both', which='major', labelsize=14)
139 | labels = ax.get_xticklabels() + ax.get_yticklabels()
140 | [label.set_fontname('serif') for label in labels]
141 | 
142 | # Axis range
143 | ax.set_xlim(0, 10)
144 | ax.set_ylim(0, 200)
145 | 
146 | # Grid
147 | ax.grid(axis='both', color='black', alpha=0.1)
148 | 
149 | plt.tight_layout()
150 | plt.savefig('../fig/single-linear-1.jpg', dpi=300)
151 |
152 | 168 |
169 |
170 |
171 |
172 | 173 | 174 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | -------------------------------------------------------------------------------- /pages/single-lineplot-2.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 91 | legend_font = {'family': 'Palatino Linotype', 'size': 12}
 92 | text_font = {'family': 'Palatino Linotype', 'size': 12}
 93 | 
 94 | # Generate data
 95 | x = np.linspace(0, 10, 100) + 1
 96 | 
 97 | # Line plot
 98 | y1_mean = 1/x
 99 | y1_std = 0.3/x
100 | y2_mean = 0.6/x
101 | y2_std = 0.1/x
102 | 
103 | fig, ax = plt.subplots(1, figsize=(4, 4))
104 | 
105 | ax.plot(x, y1_mean, label='Model 1 Loss', color=cm.Set2(0), linestyle='-', linewidth=2)
106 | ax.plot(x, y2_mean, label='Model 2 Loss', color=cm.Set2(1), linestyle='-', linewidth=2)
107 | ax.fill_between(x, y1_mean - y1_std, y1_mean + y1_std, color=cm.Set2(0), alpha=0.2)
108 | ax.fill_between(x, y2_mean - y2_std, y2_mean + y2_std, color=cm.Set2(1), alpha=0.2)
109 | 
110 | # Label and title
111 | ax.set_xlabel('X Lable', fontdict=label_font)
112 | ax.set_ylabel('Y Lable', fontdict=label_font)
113 | ax.set_title('Single Line Plot 2', fontdict=title_font)
114 | 
115 | # Legend
116 | ax.legend(loc='upper right', prop=legend_font)
117 | 
118 | # Ticks fontsize and font family
119 | ax.tick_params(axis='both', which='major', labelsize=14)
120 | labels = ax.get_xticklabels() + ax.get_yticklabels()
121 | [label.set_fontname('serif') for label in labels]
122 | 
123 | # Axis range
124 | ax.set_xlim(1, 11)
125 | ax.set_ylim(0, 1)
126 | 
127 | # Grid
128 | ax.grid(axis='both', color='black', alpha=0.1)
129 | 
130 | plt.tight_layout()
131 | plt.savefig('../fig/single-linear-2.jpg', dpi=300)
132 |
133 | 149 |
150 |
151 |
152 |
153 | 154 | 155 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | -------------------------------------------------------------------------------- /pages/single-lineplot-3.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 91 | legend_font = {'family': 'Palatino Linotype', 'size': 12}
 92 | text_font = {'family': 'Palatino Linotype', 'size': 12}
 93 | 
 94 | # Generate data
 95 | x = np.linspace(0, 10, 100)
 96 | x11 = np.linspace(0, 5, 50)
 97 | x12 = np.linspace(5, 10, 50)
 98 | 
 99 | # Line plot
100 | y1 = x * (x - 5) * (x - 10)
101 | y2 = 0.25 * x * (x - 2.5) * (x - 10)
102 | y3 = 0.25 * x11 * (x11 - 7.5) * (x11 - 10)
103 | y4 = 0.25 * x12 * (x12 - 7.5) * (x12 - 10)
104 | 
105 | # Scatter nodes
106 | x2 = [0, 2.5, 5, 7.5, 10]
107 | x3 = np.linspace(0, 10, 10)
108 | 
109 | fig, ax = plt.subplots(1, figsize=(6, 3))
110 | 
111 | ax.plot(x, y1, color=cm.Set2(0), label='Model 1', linestyle='-',  linewidth=2)
112 | ax.plot(x, y2, color=cm.Set2(1), label='Model 2', linestyle='-.', linewidth=2)
113 | 
114 | ax.plot(x11, y3, color=cm.Set2(2), label='Model 3(1)', linestyle='--', linewidth=2)
115 | ax.plot(x12, y4, color=cm.Set2(3), label='Model 3(2)', linestyle='--', linewidth=2)
116 | ax.plot([5, 5], [-50, 50], color='gray', linestyle='--', linewidth=1)
117 | 
118 | # Fill between line and y=0
119 | ax.fill_between(x, y1, 0, color=cm.Set2(0), alpha=0.1)
120 | ax.fill_between(x, y2, 0, color=cm.Set2(1), alpha=0.1)
121 | 
122 | # Scatter nodes
123 | ax.scatter(x2, [0] * len(x2), label='Node 1', color=cm.Set1(1), marker='o', s=30)
124 | ax.scatter(x3, [0] * len(x3), label='Node 2', color='gray', marker='x', s=50)
125 | 
126 | # Legend
127 | handles, labels = ax.get_legend_handles_labels()
128 | fig.legend(handles, labels, loc='center left', ncol=1, bbox_to_anchor=(0.98, 0.5), prop=legend_font)
129 | 
130 | # Label and title
131 | ax.set_xlabel('X Lable', fontdict=label_font)
132 | ax.set_ylabel('Y Lable', fontdict=label_font)
133 | ax.set_title('Single Line Plot 3', fontdict=title_font)
134 | 
135 | # Ticks fontsize and font family
136 | ax.tick_params(axis='both', which='major', labelsize=14)
137 | labels = ax.get_xticklabels() + ax.get_yticklabels()
138 | [label.set_fontname('serif') for label in labels]
139 | 
140 | # Axis range
141 | ax.set_xlim(0, 10)
142 | ax.set_ylim(-50, 50)
143 | 
144 | # Grid
145 | ax.grid(axis='both', color='black', alpha=0.1)
146 | 
147 | plt.tight_layout()
148 | plt.savefig('../fig/single-linear-3.jpg', dpi=300, bbox_inches='tight')
149 |
150 | 166 |
167 |
168 |
169 |
170 | 171 | 172 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | -------------------------------------------------------------------------------- /pages/single-scatter-1.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 91 | legend_font = {'family': 'Palatino Linotype', 'size': 10}
 92 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 93 | 
 94 | # Generate data
 95 | x = [1, 2, 3, 4, 5]
 96 | y = [5, 4, 3, 2, 1]
 97 | 
 98 | label_list = ['Label 1', 'Label 2', 'Label 3', 'Label 4', 'Label 5']
 99 | marker_list = ['o', '^', 'P', '*', 's']
100 | 
101 | # Plot
102 | fig, ax = plt.subplots(1, figsize=(4, 4))
103 | 
104 | for i in range(len(x)):
105 |     ax.scatter(
106 |         x[i], y[i], 
107 |         color=cm.Set2(i), 
108 |         marker=marker_list[i], 
109 |         s=80
110 |     )
111 |     if i < 4: 
112 |         ax.text(
113 |             x[i] + 0.3, y[i], 
114 |             label_list[i], 
115 |             fontdict=text_font, 
116 |             color=cm.Set2(i), 
117 |             verticalalignment='center', 
118 |             horizontalalignment='left'
119 |         )
120 |     else:
121 |         ax.text(
122 |             x[i] - 0.3, y[i], 
123 |             label_list[i], 
124 |             fontdict=text_font, 
125 |             color=cm.Set2(i), 
126 |             verticalalignment='center', 
127 |             horizontalalignment='right'
128 |         )
129 | 
130 | # Label and title
131 | ax.set_xlabel('X Lable', fontdict=label_font)
132 | ax.set_ylabel('Y Lable', fontdict=label_font)
133 | ax.set_title('Single Scatter Plot 1', fontdict=title_font)
134 | 
135 | # Ticks fontsize and font family
136 | ax.tick_params(axis='both', which='major', labelsize=14)
137 | labels = ax.get_xticklabels() + ax.get_yticklabels()
138 | [label.set_fontname('serif') for label in labels]
139 | 
140 | # Grid
141 | ax.grid(axis='both', color='black', alpha=0.1)
142 | 
143 | plt.tight_layout()
144 | plt.savefig('../fig/single-scatter-1.jpg', dpi=300)
145 |
146 | 162 |
163 |
164 |
165 |
166 | 167 | 168 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | -------------------------------------------------------------------------------- /pages/single-scatter-2.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 91 | legend_font = {'family': 'Palatino Linotype', 'size': 10}
 92 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 93 | 
 94 | # Generate data
 95 | depot = [0.5, 0.5]
 96 | nodes_x, nodes_y = np.meshgrid(
 97 |     np.linspace(0, 1, 4), 
 98 |     np.linspace(0, 1, 4)
 99 | )
100 | node_prob = np.random.rand(4, 4)
101 | routing_x = [
102 |     [0.5, 0, 0, 0.33, 0.5],
103 |     [0.5, 0.66, 1, 1, 0.5],
104 |     [0.5, 1, 1, 0.66, 0.5],
105 |     [0.5, 0.33, 0, 0, 0.5]
106 | ]
107 | routing_y = [
108 |     [0.5, 0.66, 1, 1, 0.5],
109 |     [0.5, 1, 1, 0.66, 0.5],
110 |     [0.5, 0.33, 0, 0, 0.5],
111 |     [0.5, 0, 0, 0.33, 0.5]
112 | ]
113 | 
114 | # Plot
115 | fig, ax = plt.subplots(1, figsize=(4, 4))
116 | 
117 | # Scatter node
118 | ax.scatter(
119 |     nodes_x, nodes_y,
120 |     edgecolors='gray', 
121 |     facecolors='none', 
122 |     marker='o', 
123 |     linewidths=2,
124 |     s=50
125 | )
126 | ax.scatter(
127 |     depot[0], depot[1],
128 |     color=cm.Set2(1),
129 |     marker='s',
130 |     s=80
131 | )
132 | 
133 | # Plot node probability bar & text
134 | for idx, (x, y) in enumerate(zip(nodes_x.flatten(), nodes_y.flatten())):
135 |     prob = node_prob[idx // 4][idx % 4]
136 |     ax.add_patch(
137 |         plt.Rectangle(
138 |             (x - 0.005, y + 0.02),
139 |             0.01,
140 |             prob * 0.05,
141 |             edgecolor='gray',
142 |             facecolor='gray',
143 |             fill=True,
144 |         )
145 |     )
146 |     ax.text(
147 |         x, y - 0.025,
148 |         f"{prob:.2f}",
149 |         horizontalalignment="center",
150 |         verticalalignment="top",
151 |         fontsize=10,
152 |         color='gray',
153 |     )
154 | 
155 | # Text depot
156 | ax.text(
157 |     depot[0], depot[1] - 0.025,
158 |     f"Depot",
159 |     horizontalalignment="center",
160 |     verticalalignment="top",
161 |     fontsize=10,
162 |     color=cm.Set2(1),
163 | )
164 | 
165 | # Plot routing
166 | for routing_idx in range(4):
167 |     for path_idx in range(4):
168 |         src_x = routing_x[routing_idx][path_idx]
169 |         src_y = routing_y[routing_idx][path_idx]
170 |         dst_x = routing_x[routing_idx][path_idx + 1]
171 |         dst_y = routing_y[routing_idx][path_idx + 1]
172 |         ax.annotate(
173 |             "",
174 |             xy=(dst_x, dst_y),
175 |             xytext=(src_x, src_y),
176 |             arrowprops=dict(
177 |                 arrowstyle="-|>", 
178 |                 color=cm.Set2(routing_idx),
179 |                 lw=1.2,
180 |             ),
181 |             size=15,
182 |             annotation_clip=False,
183 |         )
184 | 
185 | # Axis range
186 | ax.set_xlim(-0.1, 1.1)
187 | ax.set_ylim(-0.1, 1.1)
188 | 
189 | # Label and title
190 | ax.set_xlabel('X Lable', fontdict=label_font)
191 | ax.set_ylabel('Y Lable', fontdict=label_font)
192 | ax.set_title('Single Scatter Plot 2', fontdict=title_font)
193 | 
194 | # Ticks fontsize and font family
195 | ax.tick_params(axis='both', which='major', labelsize=14)
196 | labels = ax.get_xticklabels() + ax.get_yticklabels()
197 | [label.set_fontname('serif') for label in labels]
198 | 
199 | # Grid
200 | ax.grid(axis='both', color='black', alpha=0.1)
201 | 
202 | plt.tight_layout()
203 | plt.savefig('../fig/single-scatter-2.jpg', dpi=300)
204 |
205 | 221 |
222 |
223 |
224 |
225 | 226 | 227 | 238 | 239 | 240 | 241 | 242 | 243 | 244 | 245 | 246 | 247 | 248 | 249 | 250 | 251 | 252 | 253 | 254 | 255 | 256 | 257 | 258 | -------------------------------------------------------------------------------- /pages/single-scatter-3.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | from matplotlib import cm
 84 | 
 85 | # Use LaTeX font
 86 | plt.rcParams.update({'text.usetex': True})
 87 | 
 88 | # Figure font config
 89 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 90 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 91 | legend_font = {'family': 'Palatino Linotype', 'size': 10}
 92 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 93 | 
 94 | # Generate data
 95 | x = np.linspace(0, 1, 10)
 96 | y1 = [0.55] * 6 + [0.65, 0.80, 0.95, 1.2]
 97 | y2 = [0.45] * 6 + [0.35, 0.20, 0.05, -0.2]
 98 | 
 99 | y1 = np.array(y1)
100 | y2 = np.array(y2)
101 | 
102 | err1_x = np.random.rand(10) * 0.05 - 0.025 
103 | err1_y = np.random.rand(10) * 0.05 - 0.025
104 | err2_x = np.random.rand(10) * 0.05 - 0.025
105 | err2_y = np.random.rand(10) * 0.05 - 0.025
106 | 
107 | # Plot
108 | import matplotlib.patches as patches
109 | 
110 | fig, ax = plt.subplots(1, figsize=(3, 3))
111 | 
112 | # Plot history
113 | ax.plot( x[:4], y1[:4], label='History', color=cm.Set2(2), marker='o', lw=2, markersize=5)
114 | ax.plot( x[:4], y2[:4], color=cm.Set2(2), marker='o', lw=2, markersize=5)
115 | 
116 | # Plot future ground truth
117 | ax.plot( x[4:], y1[4:], label='Future GT', color=cm.Set2(1), marker='o', lw=2, markersize=5)
118 | ax.plot( x[4:], y2[4:], color=cm.Set2(1), marker='o', lw=2, markersize=5)
119 | 
120 | # Connection
121 | ax.plot( [x[3], x[4]], [y1[3], y1[4]], color=cm.Set2(1), lw=2, ls='-')
122 | ax.plot( [x[3], x[4]], [y2[3], y2[4]], color=cm.Set2(1), lw=2, ls='-')
123 | 
124 | # Plot future prediction
125 | ax.plot(x[4:]+err1_x[4:], y1[4:]+err1_y[4:], label='Future Pred', color=cm.Set2(0), marker='o', lw=2, markersize=5)
126 | ax.plot(x[4:]+err2_x[4:], y2[4:]+err2_y[4:], color=cm.Set2(0), marker='o', lw=2, markersize=5)
127 | 
128 | # Connection
129 | ax.plot([x[3], x[4]+err1_x[4]], [y1[3], y1[4]+err1_y[4]], color=cm.Set2(0), lw=2, ls='-')
130 | ax.plot([x[3], x[4]+err2_x[4]], [y2[3], y2[4]+err2_y[4]], color=cm.Set2(0), lw=2, ls='-')
131 | 
132 | # Add map items
133 | ax.add_patch(patches.Rectangle((-0.1, 0.6), 0.6, 0.6, edgecolor='grey', 
134 |                                facecolor='lightgrey', lw=1, fill=True,))
135 | ax.add_patch(patches.Rectangle((-0.1, -0.1), 0.6, 0.5, edgecolor='grey', 
136 |                                facecolor='lightgrey', lw=1, fill=True,))
137 | ax.add_patch(patches.Polygon([(0.7, 0.5), (1.1, 1.1), (1.1, -0.1)], 
138 |                              edgecolor='grey', facecolor='lightgrey', lw=1, fill=True,))
139 | 
140 | # Text infomation
141 | ax.text(
142 |     0.7, 0.9,
143 |     'Agent 1',
144 |     fontdict=text_font,
145 |     color='black',
146 |     verticalalignment='center', 
147 |     horizontalalignment='center'
148 | )
149 | ax.text(
150 |     0.7, 0.1,
151 |     'Agent 2',
152 |     fontdict=text_font,
153 |     color='black',
154 |     verticalalignment='center', 
155 |     horizontalalignment='center'
156 | )
157 | 
158 | # Legend
159 | ax.legend(loc='lower left', prop=legend_font)
160 | 
161 | # Axis range
162 | ax.set_xlim(0, 1)
163 | ax.set_ylim(0, 1)
164 | 
165 | # Label and title
166 | ax.get_xaxis().set_visible(False)
167 | ax.get_yaxis().set_visible(False)
168 | ax.set_title('Single Scatter Plot 3', fontdict=title_font)
169 | 
170 | plt.tight_layout()
171 | plt.savefig('../fig/single-scatter-3.jpg', dpi=300)
172 |
173 | 189 |
190 |
191 |
192 |
193 | 194 | 195 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | -------------------------------------------------------------------------------- /pages/single-scatter-4.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import numpy as np
 82 | import matplotlib.pyplot as plt
 83 | import matplotlib.patches as patches
 84 | from matplotlib import cm
 85 | 
 86 | # Use LaTeX font
 87 | plt.rcParams.update({'text.usetex': True})
 88 | 
 89 | # Figure font config
 90 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 91 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 92 | legend_font = {'family': 'Palatino Linotype', 'size': 10}
 93 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 94 | 
 95 | # Load data
 96 | value = np.load('../data/single-scatter-4-value.npy')
 97 | x = np.linspace(0, 256, 18, endpoint=True)
 98 | y = np.linspace(0, 256, 18, endpoint=True)
 99 | 
100 | # Plot
101 | fig, ax = plt.subplots(1, figsize=(3, 3))
102 | 
103 | # Plot background value
104 | ax.matshow(value, cmap=cm.RdGy, alpha=0.8)
105 | 
106 | # Collocation Point
107 | for i in x:
108 |     for j in y:
109 |         ax.scatter(i, j, color='black', marker='.', s=5)
110 | 
111 | # Mesh
112 | for i in range(17):
113 |     for j in range(17):
114 |         ax.plot([x[i], x[i+1]], [y[j], y[j]], color='black', linewidth=0.5)
115 |         ax.plot([x[i], x[i]], [x[j], y[j+1]], color='black', linewidth=0.5)
116 | 
117 | # Axis range
118 | ax.set_xlim(0, 256)
119 | ax.set_ylim(0, 256)
120 | ax.invert_yaxis()
121 | 
122 | # Label and title
123 | ax.get_xaxis().set_visible(False)
124 | ax.get_yaxis().set_visible(False)
125 | ax.set_title('Single Scatter Plot 4', fontdict=title_font)
126 | 
127 | plt.tight_layout()
128 | plt.savefig('../fig/single-scatter-4.jpg', dpi=300)
129 |
130 | 146 |
147 |
148 |
149 |
150 | 151 | 152 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 | 180 | 181 | 182 | 183 | -------------------------------------------------------------------------------- /pages/single-scatter-5.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 |
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41 | 42 | 43 | 72 | 73 |
74 |
75 |
76 |
77 | 78 |

79 | 

 80 | # Packages
 81 | import cv2 as cv
 82 | import numpy as np
 83 | import matplotlib.pyplot as plt
 84 | import matplotlib.patches as patches
 85 | from matplotlib import cm
 86 | 
 87 | # Use LaTeX font
 88 | plt.rcParams.update({'text.usetex': True})
 89 | 
 90 | # Figure font config
 91 | label_font = {'fontfamily': 'Arial Black', 'fontsize': 14}
 92 | title_font = {'fontfamily': 'Arial Black', 'fontsize': 16}
 93 | legend_font = {'family': 'Palatino Linotype', 'size': 10}
 94 | text_font = {'family': 'Palatino Linotype', 'fontsize': 12}
 95 | 
 96 | # Load data
 97 | # Note: shape = [num_step, num_agent, position]
 98 | # last agent is the basketball
 99 | hist = np.load('../data/single-scatter-5-hist.npy')
100 | pred = np.load('../data/single-scatter-5-pred.npy')
101 | 
102 | # Scale the data
103 | hist[..., 0] = hist[..., 0] * 15
104 | hist[..., 1] = hist[..., 1] * 8
105 | pred[..., 0] = pred[..., 0] * 15
106 | pred[..., 1] = pred[..., 1] * 8
107 | 
108 | # Plot
109 | fig, ax = plt.subplots(1, figsize=(5, 5))
110 | 
111 | # Plot the beckground court
112 | img = cv.imread('../fig/utils/court.png')
113 | img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
114 | ax.imshow(img, extent=[0, 15, 0, 8], alpha=0.6)
115 | 
116 | # Scatter history trajectory
117 | ax.plot(hist[:, :5, 0], hist[:, :5, 1], label='History Team 1', color=cm.Set2(3), 
118 |         marker='o', lw=2, markersize=5, alpha=0.7)
119 | ax.plot(hist[:, 5:-1, 0], hist[:, 5:-1, 1], label='History Team 2', color=cm.Set2(2), 
120 |         marker='o', lw=2, markersize=5, alpha=0.7)
121 | 
122 | # Scatter future trajectory
123 | ax.plot(pred[:, :5, 0], pred[:, :5, 1], label='Future Team 1', color=cm.Set2(1), 
124 |         marker='o', lw=2, markersize=5, alpha=0.7)
125 | ax.plot(pred[:, 5:-1, 0], pred[:, 5:-1, 1], label='Future Team 2', color=cm.Set2(0), 
126 |         marker='o', lw=2, markersize=5, alpha=0.7)
127 | 
128 | # Scatter the basketball
129 | ax.plot(hist[:, -1, 0], hist[:, -1, 1], label='Basketball', color=cm.Set1(0), 
130 |         marker='^', lw=2, markersize=5, alpha=0.7)
131 | ax.plot(pred[:, -1, 0], pred[:, -1, 1], color=cm.Set1(0), 
132 |         marker='^', lw=2, markersize=5, alpha=0.7)
133 | 
134 | # Connect history and future
135 | ax.plot([hist[0, :5, 0], pred[-1, :5, 0]], [hist[0, :5, 1], pred[-1, :5, 1]], 
136 |         color=cm.Set2(1), lw=2, ls='-', alpha=0.7)
137 | ax.plot([hist[0, 5:-1, 0], pred[-1, 5:-1, 0]], [hist[0, 5:-1, 1], pred[-1, 5:-1, 1]], 
138 |         color=cm.Set2(0), lw=2, ls='-', alpha=0.7)
139 | ax.plot([hist[0, -1, 0], pred[-1, -1, 0]], [hist[0, -1, 1], pred[-1, -1, 1]], 
140 |         color=cm.Set1(0), lw=2, ls='-', alpha=0.7)
141 | 
142 | # Label and title
143 | ax.get_xaxis().set_visible(False)
144 | ax.get_yaxis().set_visible(False)
145 | ax.set_title('Single Scatter Plot 5', fontdict=title_font)
146 | 
147 | # Legend
148 | handles, labels = ax.get_legend_handles_labels()
149 | labels = dict(zip(labels, handles))
150 | fig.legend(labels.values(), labels.keys(), loc='lower center', ncol=3, bbox_to_anchor=(0.5, 0.12), prop=legend_font)
151 | 
152 | plt.tight_layout()
153 | plt.savefig('../fig/single-scatter-5.jpg', dpi=300)
154 |
155 | 171 |
172 |
173 |
174 |
175 | 176 | 177 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | -------------------------------------------------------------------------------- /posts.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Matplotlib Prefabs 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | 32 | 33 | 34 | 35 |
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69 |
70 |

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71 |

72 | [TBD] Some posts about the prefabs. We will update this page soon. 73 |

74 |
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