├── .github ├── FUNDING.yml └── workflows │ ├── ci.yml │ └── test.yml ├── .gitignore ├── .pre-commit-config.yaml ├── LICENSE ├── README.md ├── doc ├── Documentation_Part_1.ipynb └── doc-requirements.txt ├── poetry.lock ├── pyproject.toml ├── pytest.ini ├── test ├── test_mini_interpreter.py ├── test_mini_parser.py ├── test_pattern.py └── test_py_vortex.py └── vortex ├── __init__.py ├── boot.py ├── cli.py ├── control.py ├── euclid.py ├── gui.py ├── mini ├── __init__.py ├── grammar.py └── interpreter.py ├── pattern.py ├── repl.py ├── res └── fonts │ ├── FiraCode-Bold.ttf │ ├── FiraCode-Light.ttf │ ├── FiraCode-Medium.ttf │ ├── FiraCode-Regular.ttf │ ├── FiraCode-Retina.ttf │ ├── FiraCode-SemiBold.ttf │ └── iosevka-term-regular.ttf ├── stream.py ├── utils.py └── vortex.py /.github/FUNDING.yml: -------------------------------------------------------------------------------- 1 | open_collective: tidalcycles 2 | -------------------------------------------------------------------------------- /.github/workflows/ci.yml: -------------------------------------------------------------------------------- 1 | # This workflow will install Python dependencies and run tests with a variety of Python versions 2 | # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions 3 | 4 | name: CI 5 | 6 | on: 7 | push: 8 | branches: [ "main" ] 9 | pull_request: 10 | branches: [ "main" ] 11 | 12 | jobs: 13 | build: 14 | 15 | runs-on: ubuntu-latest 16 | strategy: 17 | fail-fast: false 18 | matrix: 19 | python-version: ["3.8", "3.9", "3.10"] 20 | 21 | steps: 22 | - uses: actions/checkout@v3 23 | - name: Set up Python ${{ matrix.python-version }} 24 | uses: actions/setup-python@v3 25 | with: 26 | python-version: ${{ matrix.python-version }} 27 | - name: Install system dependencies 28 | run: | 29 | sudo apt install liblo-dev 30 | - name: Install Poetry 31 | run: | 32 | python -m pip install --upgrade poetry==1.3.2 33 | - name: Install all dependencies 34 | run: | 35 | poetry install 36 | - name: Run tests 37 | run: | 38 | poetry run pytest 39 | -------------------------------------------------------------------------------- /.github/workflows/test.yml: -------------------------------------------------------------------------------- 1 | # This workflow will install Python dependencies and run tests except on branch 'main' where CI action is used 2 | # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions 3 | 4 | name: Vortex Tests 5 | 6 | on: 7 | push: 8 | branches: 9 | - '**' # matches every branch 10 | - '!main' # excludes main 11 | 12 | jobs: 13 | build: 14 | 15 | runs-on: ubuntu-latest 16 | strategy: 17 | fail-fast: false 18 | matrix: 19 | python-version: ["3.10"] 20 | 21 | steps: 22 | - uses: actions/checkout@v3 23 | - name: Set up Python ${{ matrix.python-version }} 24 | uses: actions/setup-python@v3 25 | with: 26 | python-version: ${{ matrix.python-version }} 27 | - name: Install system dependencies 28 | run: | 29 | sudo apt install liblo-dev 30 | - name: Install Poetry 31 | run: | 32 | python -m pip install --upgrade poetry==1.3.2 33 | - name: Install all dependencies 34 | run: | 35 | poetry install 36 | - name: Run tests 37 | run: | 38 | poetry run pytest 39 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | 131 | #Pycharm 132 | .idea 133 | 134 | # text editor temp files 135 | *~ 136 | \#*\# 137 | .\#* 138 | -------------------------------------------------------------------------------- /.pre-commit-config.yaml: -------------------------------------------------------------------------------- 1 | # See https://pre-commit.com for more information 2 | # See https://pre-commit.com/hooks.html for more hooks 3 | repos: 4 | - 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Vortex: Algorithmic pattern experiments in Python 2 | 3 | Moved to https://codeberg.org/uzu/vortex/ 4 | -------------------------------------------------------------------------------- /doc/Documentation_Part_1.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "51e519ce-1ba5-4ea1-b3f5-76b35fa057ba", 6 | "metadata": {}, 7 | "source": [ 8 | "# Step-by-Step documentation\n", 9 | "## Part I: Time, TimeSpan, Event\n", 10 | "\n", 11 | "This notebook is meant for anyone to better understand the underlying structures which are used in vortex, and to a larger extent in Tidal.
\n", 12 | "Beware that there may be some differences, but at least, this aims to cover the current `vortex`implementation in Python hoping to explain it a bit more at low-level
\n", 13 | "There are a couple crucial class in vortex, namely Time, TimeSpan, and Event, we will go through in details about how they work.
\n", 14 | "Part II will focus on Pattern only" 15 | ] 16 | }, 17 | { 18 | "cell_type": "code", 19 | "execution_count": 1, 20 | "id": "f3ca40fc-1e9f-4db7-9a1d-0465d71bde7b", 21 | "metadata": {}, 22 | "outputs": [], 23 | "source": [ 24 | "from vortex import *" 25 | ] 26 | }, 27 | { 28 | "cell_type": "markdown", 29 | "id": "4f18ae15-562d-42d6-b03c-7a64b328765a", 30 | "metadata": {}, 31 | "source": [ 32 | "# Time\n", 33 | "Time class is a subclass of fraction. While instanciating a Time object, you can specify it by either one or two floats.
\n", 34 | "If you do so with two numbers, then the fraction is simply the ratio of them
\n", 35 | "If you create it with only one number, it translates it into a fraction
\n", 36 | "Apparently, irrationals does work too (probably rounded)" 37 | ] 38 | }, 39 | { 40 | "cell_type": "code", 41 | "execution_count": 2, 42 | "id": "9959c6b5-9d78-4766-b7dc-f49af92a46ee", 43 | "metadata": {}, 44 | "outputs": [ 45 | { 46 | "data": { 47 | "text/plain": [ 48 | "Time(1, 2)" 49 | ] 50 | }, 51 | "execution_count": 2, 52 | "metadata": {}, 53 | "output_type": "execute_result" 54 | } 55 | ], 56 | "source": [ 57 | "Time(1,2)" 58 | ] 59 | }, 60 | { 61 | "cell_type": "code", 62 | "execution_count": 3, 63 | "id": "0b8cf0f6-b523-4329-8733-33430352f797", 64 | "metadata": {}, 65 | "outputs": [ 66 | { 67 | "data": { 68 | "text/plain": [ 69 | "Time(1, 2)" 70 | ] 71 | }, 72 | "execution_count": 3, 73 | "metadata": {}, 74 | "output_type": "execute_result" 75 | } 76 | ], 77 | "source": [ 78 | "Time(0.5)" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 4, 84 | "id": "12fee21f-7f08-4dfc-b246-424aad575ee8", 85 | "metadata": {}, 86 | "outputs": [ 87 | { 88 | "data": { 89 | "text/plain": [ 90 | "Time(8893444981951847, 72057594037927936)" 91 | ] 92 | }, 93 | "execution_count": 4, 94 | "metadata": {}, 95 | "output_type": "execute_result" 96 | } 97 | ], 98 | "source": [ 99 | "Time(0.12342134234)" 100 | ] 101 | }, 102 | { 103 | "cell_type": "code", 104 | "execution_count": 5, 105 | "id": "fafc9372-6c4d-4bf4-9c24-65c451413a68", 106 | "metadata": {}, 107 | "outputs": [ 108 | { 109 | "data": { 110 | "text/plain": [ 111 | "Time(884279719003555, 281474976710656)" 112 | ] 113 | }, 114 | "execution_count": 5, 115 | "metadata": {}, 116 | "output_type": "execute_result" 117 | } 118 | ], 119 | "source": [ 120 | "from math import pi\n", 121 | "Time(pi)" 122 | ] 123 | }, 124 | { 125 | "cell_type": "markdown", 126 | "id": "e1b73273-c268-46e6-a877-e3a3f598dfc8", 127 | "metadata": {}, 128 | "source": [ 129 | "## Methods\n", 130 | "\n", 131 | "Time Class has currently 3 methods, `sam`, `next_sam` and `whole_cycle`.
\n", 132 | "Sam refers to indian music, where *sam* is the denomination of the first beat of the cycle.
\n", 133 | "Trivially, `next_sam` is the first beat of the next cycle
\n", 134 | "And whole_duration is a TimeSpan (see below) of a whole cycle
" 135 | ] 136 | }, 137 | { 138 | "cell_type": "markdown", 139 | "id": "2113a7d4-b1d8-43ad-943c-be2781689ff9", 140 | "metadata": {}, 141 | "source": [ 142 | "### sam" 143 | ] 144 | }, 145 | { 146 | "cell_type": "code", 147 | "execution_count": 6, 148 | "id": "3f15d486-d86e-4ad9-83ca-303205ec4d75", 149 | "metadata": {}, 150 | "outputs": [ 151 | { 152 | "data": { 153 | "text/plain": [ 154 | "Time(0, 1)" 155 | ] 156 | }, 157 | "execution_count": 6, 158 | "metadata": {}, 159 | "output_type": "execute_result" 160 | } 161 | ], 162 | "source": [ 163 | "Time(0.43).sam()" 164 | ] 165 | }, 166 | { 167 | "cell_type": "markdown", 168 | "id": "a441bbc2-81b2-42e5-bca7-d7f70a534d6d", 169 | "metadata": {}, 170 | "source": [ 171 | "### next_sam" 172 | ] 173 | }, 174 | { 175 | "cell_type": "code", 176 | "execution_count": 7, 177 | "id": "74a1c64a-8ad8-49aa-b1be-8c46c1003399", 178 | "metadata": {}, 179 | "outputs": [ 180 | { 181 | "data": { 182 | "text/plain": [ 183 | "Fraction(1, 1)" 184 | ] 185 | }, 186 | "execution_count": 7, 187 | "metadata": {}, 188 | "output_type": "execute_result" 189 | } 190 | ], 191 | "source": [ 192 | "Time(0.43).next_sam()" 193 | ] 194 | }, 195 | { 196 | "cell_type": "markdown", 197 | "id": "82599445-e8cf-42c4-b7dd-b3a07236b17e", 198 | "metadata": {}, 199 | "source": [ 200 | "### whole_cycle" 201 | ] 202 | }, 203 | { 204 | "cell_type": "code", 205 | "execution_count": 8, 206 | "id": "13e3175e-9508-4459-af80-e1f5ef60f263", 207 | "metadata": {}, 208 | "outputs": [ 209 | { 210 | "data": { 211 | "text/plain": [ 212 | "TimeSpan(Time(0, 1), Time(1, 1))" 213 | ] 214 | }, 215 | "execution_count": 8, 216 | "metadata": {}, 217 | "output_type": "execute_result" 218 | } 219 | ], 220 | "source": [ 221 | "Time(0.42).whole_cycle()" 222 | ] 223 | }, 224 | { 225 | "cell_type": "code", 226 | "execution_count": 9, 227 | "id": "ab2f7876-03c7-4497-a93d-d73170afba7f", 228 | "metadata": {}, 229 | "outputs": [ 230 | { 231 | "data": { 232 | "text/plain": [ 233 | "TimeSpan(Time(-3, 1), Time(-2, 1))" 234 | ] 235 | }, 236 | "execution_count": 9, 237 | "metadata": {}, 238 | "output_type": "execute_result" 239 | } 240 | ], 241 | "source": [ 242 | "Time(-2.3).whole_cycle()" 243 | ] 244 | }, 245 | { 246 | "cell_type": "markdown", 247 | "id": "c808cd9a-6666-4420-8dc6-c7ccb33926df", 248 | "metadata": {}, 249 | "source": [ 250 | "# TimeSpan\n", 251 | "As introduced right above, TimeSpan represents a structure that has a certain duration
\n", 252 | "It is commonly used in Event, as will be talked about later.\n", 253 | "It has 2 attributes: `begin` and `end` and 3 methods `spanCycles`, `withTime` and `sect`
\n", 254 | "We will not count `maybeSect` here since it is just a method for dealing with sect corner cases.
\n", 255 | "TimeSpan `begin` and `end` attributes are themselves `Time` objects.
\n", 256 | "In theory, nothing restricts them to be such like $begin > end$ but in practive it is not the case.
" 257 | ] 258 | }, 259 | { 260 | "cell_type": "code", 261 | "execution_count": 10, 262 | "id": "75a6878f-b010-4152-afea-07d53c47618e", 263 | "metadata": {}, 264 | "outputs": [ 265 | { 266 | "data": { 267 | "text/plain": [ 268 | "TimeSpan(Time(-3602879701896397, 36028797018963968), Time(3602879701896397, 4503599627370496))" 269 | ] 270 | }, 271 | "execution_count": 10, 272 | "metadata": {}, 273 | "output_type": "execute_result" 274 | } 275 | ], 276 | "source": [ 277 | "TimeSpan(-0.1, 0.8)" 278 | ] 279 | }, 280 | { 281 | "cell_type": "code", 282 | "execution_count": 11, 283 | "id": "bff9f883-af09-41f0-a2dc-962abbcb96bd", 284 | "metadata": {}, 285 | "outputs": [ 286 | { 287 | "data": { 288 | "text/plain": [ 289 | "TimeSpan(Time(1, 8), Time(1, 4))" 290 | ] 291 | }, 292 | "execution_count": 11, 293 | "metadata": {}, 294 | "output_type": "execute_result" 295 | } 296 | ], 297 | "source": [ 298 | "TimeSpan(1/8, 1/4)" 299 | ] 300 | }, 301 | { 302 | "cell_type": "markdown", 303 | "id": "e8877ab1-e4c0-4604-9be5-09afb03b4b5a", 304 | "metadata": {}, 305 | "source": [ 306 | "## Methods\n", 307 | "\n", 308 | "TimeSpan has some critical methods relevant to how Patterns are working, and are used extensively in vortex.
\n", 309 | "`spanCycles` allows for a TimeSpan to extend its values to its nearest sam and next_sam.
\n", 310 | "`withtime` allows to apply a function to the begining and the end values of a TimeSpan, basically it allows for a Pattern to modify the duration of an Event (for example) or to the moment it is queried.
\n", 311 | "`sect` is also really useful when querying a pattern, to determine the duration of event within a given cycle.
\n", 312 | "These are just examples of how they can be used, to have a better understanding but they are no such strict rules and everything is possible." 313 | ] 314 | }, 315 | { 316 | "cell_type": "markdown", 317 | "id": "f08491cd-be4c-4146-99a4-0485e0af5a24", 318 | "metadata": {}, 319 | "source": [ 320 | "### span_cycles" 321 | ] 322 | }, 323 | { 324 | "cell_type": "code", 325 | "execution_count": 12, 326 | "id": "eaddaccd-62ef-46c1-b271-0da6442d981b", 327 | "metadata": {}, 328 | "outputs": [ 329 | { 330 | "data": { 331 | "text/plain": [ 332 | "[TimeSpan(Time(0, 1), Time(1, 1))]" 333 | ] 334 | }, 335 | "execution_count": 12, 336 | "metadata": {}, 337 | "output_type": "execute_result" 338 | } 339 | ], 340 | "source": [ 341 | "TimeSpan(0,1).span_cycles()" 342 | ] 343 | }, 344 | { 345 | "cell_type": "code", 346 | "execution_count": 13, 347 | "id": "0e62d20e-44fc-4670-8d33-dbf4f394e3ef", 348 | "metadata": {}, 349 | "outputs": [ 350 | { 351 | "data": { 352 | "text/plain": [ 353 | "[TimeSpan(Time(-1, 4), Time(0, 1)), TimeSpan(Time(0, 1), Time(3, 4))]" 354 | ] 355 | }, 356 | "execution_count": 13, 357 | "metadata": {}, 358 | "output_type": "execute_result" 359 | } 360 | ], 361 | "source": [ 362 | "TimeSpan(-0.25, 0.75).span_cycles()" 363 | ] 364 | }, 365 | { 366 | "cell_type": "code", 367 | "execution_count": 14, 368 | "id": "ec850b9f-afb4-4189-b858-696b4da37971", 369 | "metadata": {}, 370 | "outputs": [ 371 | { 372 | "data": { 373 | "text/plain": [ 374 | "[TimeSpan(Time(-9, 4), Time(-2, 1)),\n", 375 | " TimeSpan(Time(-2, 1), Time(-1, 1)),\n", 376 | " TimeSpan(Time(-1, 1), Time(0, 1)),\n", 377 | " TimeSpan(Time(0, 1), Time(1, 1)),\n", 378 | " TimeSpan(Time(1, 1), Time(2, 1)),\n", 379 | " TimeSpan(Time(2, 1), Time(3, 1)),\n", 380 | " TimeSpan(Time(3, 1), Time(3884354678607053, 1125899906842624))]" 381 | ] 382 | }, 383 | "execution_count": 14, 384 | "metadata": {}, 385 | "output_type": "execute_result" 386 | } 387 | ], 388 | "source": [ 389 | "TimeSpan(-2.25, 3.45).span_cycles()" 390 | ] 391 | }, 392 | { 393 | "cell_type": "markdown", 394 | "id": "7df256cf-50ac-4acc-8bd2-633495b0bd5d", 395 | "metadata": {}, 396 | "source": [ 397 | "### with_time" 398 | ] 399 | }, 400 | { 401 | "cell_type": "code", 402 | "execution_count": 15, 403 | "id": "0a86122f-816c-440b-8c2b-4407bba2df5e", 404 | "metadata": {}, 405 | "outputs": [ 406 | { 407 | "data": { 408 | "text/plain": [ 409 | "TimeSpan(Time(1, 2), Time(5, 2))" 410 | ] 411 | }, 412 | "execution_count": 15, 413 | "metadata": {}, 414 | "output_type": "execute_result" 415 | } 416 | ], 417 | "source": [ 418 | "TimeSpan(0.25, 1.25).with_time(lambda x: x*2)" 419 | ] 420 | }, 421 | { 422 | "cell_type": "markdown", 423 | "id": "62ba47d1-1dd5-450e-ada7-f044db9d1cf3", 424 | "metadata": {}, 425 | "source": [ 426 | "Ok, let's stop a bit here and understand what's happening.
\n", 427 | "We are defining a lambda function that apply the operation multiply by 2 on each element of the TimeSpan, such that 0.25 and 1.25 become 0.5 and 2.5
\n", 428 | "If you are not comfortable with `lambda` syntax, you can simply declare you function the standard way and pass it to `withTime` in such way:" 429 | ] 430 | }, 431 | { 432 | "cell_type": "code", 433 | "execution_count": 16, 434 | "id": "2bb5c359-08d5-4030-b6e0-0a6c5c3df96a", 435 | "metadata": {}, 436 | "outputs": [ 437 | { 438 | "data": { 439 | "text/plain": [ 440 | "TimeSpan(Time(1, 2), Time(5, 2))" 441 | ] 442 | }, 443 | "execution_count": 16, 444 | "metadata": {}, 445 | "output_type": "execute_result" 446 | } 447 | ], 448 | "source": [ 449 | "def multiply_by_2(x):\n", 450 | " return x * 2\n", 451 | "\n", 452 | "TimeSpan(0.25, 1.25).with_time(multiply_by_2)" 453 | ] 454 | }, 455 | { 456 | "cell_type": "markdown", 457 | "id": "d7ed2a8f-5322-4d93-98f0-dd856fc0ae6d", 458 | "metadata": {}, 459 | "source": [ 460 | "And the result is exactly the same." 461 | ] 462 | }, 463 | { 464 | "cell_type": "markdown", 465 | "id": "1fa63336-6149-4847-ba86-35466fcda273", 466 | "metadata": {}, 467 | "source": [ 468 | "### sect" 469 | ] 470 | }, 471 | { 472 | "cell_type": "markdown", 473 | "id": "b1465450-8c18-433c-bbde-77ecb7c12ff0", 474 | "metadata": {}, 475 | "source": [ 476 | "If you need to know what is the TimeSpan common to 2 different TimeSpans, you can just use `sect` " 477 | ] 478 | }, 479 | { 480 | "cell_type": "code", 481 | "execution_count": 17, 482 | "id": "9bcc93cd-8426-40a4-9c2a-e6bd16d6d87b", 483 | "metadata": {}, 484 | "outputs": [ 485 | { 486 | "data": { 487 | "text/plain": [ 488 | "TimeSpan(Time(1, 2), Time(3, 4))" 489 | ] 490 | }, 491 | "execution_count": 17, 492 | "metadata": {}, 493 | "output_type": "execute_result" 494 | } 495 | ], 496 | "source": [ 497 | "TimeSpan(0, 0.75).sect(TimeSpan(0.5, 1.5))" 498 | ] 499 | }, 500 | { 501 | "cell_type": "code", 502 | "execution_count": 18, 503 | "id": "dbf422a5-3541-4976-bb5f-d09a3cbb73b6", 504 | "metadata": {}, 505 | "outputs": [ 506 | { 507 | "data": { 508 | "text/plain": [ 509 | "TimeSpan(Time(1, 2), Time(3, 4))" 510 | ] 511 | }, 512 | "execution_count": 18, 513 | "metadata": {}, 514 | "output_type": "execute_result" 515 | } 516 | ], 517 | "source": [ 518 | "TimeSpan(0.5, 1.75).sect(TimeSpan(0, 0.75))" 519 | ] 520 | }, 521 | { 522 | "cell_type": "markdown", 523 | "id": "fff4e695-b00c-4523-92fb-23a7cd49ddea", 524 | "metadata": {}, 525 | "source": [ 526 | "If they do not overlap, then the result is None" 527 | ] 528 | }, 529 | { 530 | "cell_type": "code", 531 | "execution_count": 19, 532 | "id": "f8bd340b-28c7-473b-a981-9a214bfacf12", 533 | "metadata": {}, 534 | "outputs": [ 535 | { 536 | "data": { 537 | "text/plain": [ 538 | "True" 539 | ] 540 | }, 541 | "execution_count": 19, 542 | "metadata": {}, 543 | "output_type": "execute_result" 544 | } 545 | ], 546 | "source": [ 547 | "no_overlap = TimeSpan(0, 0.75).sect(TimeSpan(1.5, 2))\n", 548 | "no_overlap is None" 549 | ] 550 | }, 551 | { 552 | "cell_type": "markdown", 553 | "id": "44479ab3-3984-45ea-8629-15e55a5fefcc", 554 | "metadata": {}, 555 | "source": [ 556 | "# Event" 557 | ] 558 | }, 559 | { 560 | "cell_type": "markdown", 561 | "id": "71e6cc37-be2e-4a70-a9be-c75701ceaeb1", 562 | "metadata": {}, 563 | "source": [ 564 | "Everythin in TIdal is an event, and Pattern (don't worry will get to it) modifies them.
\n", 565 | "Then, the scheduler who is responsible to making happen event with regards to Time, queries then and make them alive,
\n", 566 | "An event is composed of three different constituents: \n", 567 | "- a whole (a TimeSpan instance) which represents the duration an event is active, regardless of the query \n", 568 | "- a part (a TimeSpan instance) which represents the duration an event is active, during the TimeSpan of the cycle it is queried\n", 569 | "- a value (a string, a number, etc... ) which identifies it. Think of it as a key.\n", 570 | "\n", 571 | "Event possesses methods `withSpan`, `withValue` and `hasOnset`. These methods modifies with functions the differents constituents of an Event" 572 | ] 573 | }, 574 | { 575 | "cell_type": "code", 576 | "execution_count": 20, 577 | "id": "463d6026-b0db-46cd-8920-82de5ec89dc1", 578 | "metadata": {}, 579 | "outputs": [ 580 | { 581 | "data": { 582 | "text/plain": [ 583 | "Event(TimeSpan(Time(1, 4), Time(5, 4)), TimeSpan(Time(1, 2), Time(3, 4)), 'hello')" 584 | ] 585 | }, 586 | "execution_count": 20, 587 | "metadata": {}, 588 | "output_type": "execute_result" 589 | } 590 | ], 591 | "source": [ 592 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\")" 593 | ] 594 | }, 595 | { 596 | "cell_type": "code", 597 | "execution_count": 21, 598 | "id": "4f6fae5e-04d6-4834-9a72-c135d504f05c", 599 | "metadata": {}, 600 | "outputs": [ 601 | { 602 | "data": { 603 | "text/plain": [ 604 | "Event(TimeSpan(Time(1, 4), Time(5, 4)), TimeSpan(Time(1, 2), Time(3, 4)), 2)" 605 | ] 606 | }, 607 | "execution_count": 21, 608 | "metadata": {}, 609 | "output_type": "execute_result" 610 | } 611 | ], 612 | "source": [ 613 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), 2)" 614 | ] 615 | }, 616 | { 617 | "cell_type": "markdown", 618 | "id": "fdf932fb-9f81-4f3b-a3a5-ca0375482ab1", 619 | "metadata": {}, 620 | "source": [ 621 | "### with_span" 622 | ] 623 | }, 624 | { 625 | "cell_type": "code", 626 | "execution_count": 22, 627 | "id": "533ef3e1-a1fa-4702-9713-0b3c89938a5f", 628 | "metadata": {}, 629 | "outputs": [ 630 | { 631 | "data": { 632 | "text/plain": [ 633 | "Event(TimeSpan(Time(9, 4), Time(13, 4)), TimeSpan(Time(5, 2), Time(11, 4)), 'hello')" 634 | ] 635 | }, 636 | "execution_count": 22, 637 | "metadata": {}, 638 | "output_type": "execute_result" 639 | } 640 | ], 641 | "source": [ 642 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").with_span(lambda span: span.with_time(lambda x: x+2))" 643 | ] 644 | }, 645 | { 646 | "cell_type": "markdown", 647 | "id": "e567c52b-ce11-41fd-a466-99566c41f2b8", 648 | "metadata": {}, 649 | "source": [ 650 | "Ok, just a moment of relfexion here. Even though `withSpan` takes a function as a parameter, it cannot take *any* function.
\n", 651 | "For this to be working, this function has to be a method *known* to TimeSpan (i.e. spanCycles, withTime or sect).
\n", 652 | "For example, this does not work (unless the + operator is overloaded for class TimeSpan - which is not the case atm)." 653 | ] 654 | }, 655 | { 656 | "cell_type": "code", 657 | "execution_count": 23, 658 | "id": "9ef427c1-933f-4946-b68c-e962a72d0b0e", 659 | "metadata": {}, 660 | "outputs": [], 661 | "source": [ 662 | "# This does not work !!!\n", 663 | "# Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").withSpan(lambda x: x+2)" 664 | ] 665 | }, 666 | { 667 | "cell_type": "markdown", 668 | "id": "69387157-bd17-4cc2-b6b0-f9de5a021f22", 669 | "metadata": {}, 670 | "source": [ 671 | "Also, be aware that any var pass to lambda will work, we use `span` here for convenience but it could be *anything*
" 672 | ] 673 | }, 674 | { 675 | "cell_type": "code", 676 | "execution_count": 24, 677 | "id": "5af94bd6-273f-4665-8da5-0ee3f36f2110", 678 | "metadata": {}, 679 | "outputs": [ 680 | { 681 | "data": { 682 | "text/plain": [ 683 | "Event(TimeSpan(Time(9, 4), Time(13, 4)), TimeSpan(Time(5, 2), Time(11, 4)), 'hello')" 684 | ] 685 | }, 686 | "execution_count": 24, 687 | "metadata": {}, 688 | "output_type": "execute_result" 689 | } 690 | ], 691 | "source": [ 692 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").with_span(lambda x: x.with_time(lambda x: x+2))" 693 | ] 694 | }, 695 | { 696 | "cell_type": "code", 697 | "execution_count": 25, 698 | "id": "cea79855-4aeb-402c-b067-d981dfcd6687", 699 | "metadata": {}, 700 | "outputs": [ 701 | { 702 | "data": { 703 | "text/plain": [ 704 | "Event([TimeSpan(Time(1, 4), Time(1, 1)), TimeSpan(Time(1, 1), Time(5, 4))], [TimeSpan(Time(1, 2), Time(3, 4))], 'hello')" 705 | ] 706 | }, 707 | "execution_count": 25, 708 | "metadata": {}, 709 | "output_type": "execute_result" 710 | } 711 | ], 712 | "source": [ 713 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").with_span(lambda span: span.span_cycles())" 714 | ] 715 | }, 716 | { 717 | "cell_type": "code", 718 | "execution_count": 26, 719 | "id": "1872bdc0-e618-4b47-aa40-a04759b99e01", 720 | "metadata": {}, 721 | "outputs": [ 722 | { 723 | "data": { 724 | "text/plain": [ 725 | "Event(TimeSpan(Time(1, 4), Time(5, 4)), TimeSpan(Time(1, 2), Time(3, 4)), 'hello')" 726 | ] 727 | }, 728 | "execution_count": 26, 729 | "metadata": {}, 730 | "output_type": "execute_result" 731 | } 732 | ], 733 | "source": [ 734 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").with_span(lambda span: span.sect(TimeSpan(0,2)))" 735 | ] 736 | }, 737 | { 738 | "cell_type": "markdown", 739 | "id": "e4773602-6627-43b7-9ae2-b7476b191df9", 740 | "metadata": {}, 741 | "source": [ 742 | "### with_value" 743 | ] 744 | }, 745 | { 746 | "cell_type": "code", 747 | "execution_count": 27, 748 | "id": "35b886fb-a89a-4445-bde1-8278b74b38d2", 749 | "metadata": {}, 750 | "outputs": [ 751 | { 752 | "data": { 753 | "text/plain": [ 754 | "Event(TimeSpan(Time(1, 4), Time(5, 4)), TimeSpan(Time(1, 2), Time(3, 4)), 'HELLO')" 755 | ] 756 | }, 757 | "execution_count": 27, 758 | "metadata": {}, 759 | "output_type": "execute_result" 760 | } 761 | ], 762 | "source": [ 763 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").with_value(lambda x: x.upper())" 764 | ] 765 | }, 766 | { 767 | "cell_type": "code", 768 | "execution_count": 28, 769 | "id": "5cf01a11-7f62-4e9e-91e2-40963a0c98e3", 770 | "metadata": {}, 771 | "outputs": [ 772 | { 773 | "data": { 774 | "text/plain": [ 775 | "Event(TimeSpan(Time(1, 4), Time(5, 4)), TimeSpan(Time(1, 2), Time(3, 4)), 12)" 776 | ] 777 | }, 778 | "execution_count": 28, 779 | "metadata": {}, 780 | "output_type": "execute_result" 781 | } 782 | ], 783 | "source": [ 784 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), 10).with_value(lambda x: x + 2)" 785 | ] 786 | }, 787 | { 788 | "cell_type": "markdown", 789 | "id": "594b9c31-901f-415d-8aba-2f0b85470c86", 790 | "metadata": {}, 791 | "source": [ 792 | "### has_onset" 793 | ] 794 | }, 795 | { 796 | "cell_type": "code", 797 | "execution_count": 29, 798 | "id": "aa068a49-4711-45fd-a4e1-338d5f1a6295", 799 | "metadata": {}, 800 | "outputs": [ 801 | { 802 | "data": { 803 | "text/plain": [ 804 | "False" 805 | ] 806 | }, 807 | "execution_count": 29, 808 | "metadata": {}, 809 | "output_type": "execute_result" 810 | } 811 | ], 812 | "source": [ 813 | "Event(TimeSpan(0.25, 1.25), TimeSpan(0.5, 0.75), \"hello\").has_onset()" 814 | ] 815 | }, 816 | { 817 | "cell_type": "code", 818 | "execution_count": 30, 819 | "id": "fdfe3c9a-e8aa-4f9c-9efb-ee3654f5c154", 820 | "metadata": {}, 821 | "outputs": [ 822 | { 823 | "data": { 824 | "text/plain": [ 825 | "True" 826 | ] 827 | }, 828 | "execution_count": 30, 829 | "metadata": {}, 830 | "output_type": "execute_result" 831 | } 832 | ], 833 | "source": [ 834 | "Event(TimeSpan(0.5, 1.25), TimeSpan(0.5, 0.75), \"hello\").has_onset()" 835 | ] 836 | } 837 | ], 838 | "metadata": { 839 | "kernelspec": { 840 | "display_name": "Python 3 (ipykernel)", 841 | "language": "python", 842 | "name": "python3" 843 | }, 844 | "language_info": { 845 | "codemirror_mode": { 846 | "name": "ipython", 847 | "version": 3 848 | }, 849 | "file_extension": ".py", 850 | "mimetype": "text/x-python", 851 | "name": "python", 852 | "nbconvert_exporter": "python", 853 | "pygments_lexer": "ipython3", 854 | "version": "3.9.7" 855 | } 856 | }, 857 | "nbformat": 4, 858 | "nbformat_minor": 5 859 | } 860 | -------------------------------------------------------------------------------- /doc/doc-requirements.txt: -------------------------------------------------------------------------------- 1 | jupyterlab==3.2.4 2 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "tidalvortex" 3 | version = "0.1.0-alpha.0" 4 | description = "Python port of TidalCycles" 5 | authors = ["Tidal Cyclists "] 6 | repository = "https://github.com/tidalcycles/vortex" 7 | license = "GPL-3.0-or-later" 8 | packages = [ 9 | { include = "vortex" } 10 | ] 11 | 12 | [tool.poetry.dependencies] 13 | python = ">=3.8,<3.11" 14 | parsy = "^1.4.0" 15 | LinkPython = "^0.1.1" 16 | pyliblo3 = "^0.13.0" 17 | ipython = "^8.4.0" 18 | parsimonious = "^0.9.0" 19 | pyqt6 = "^6.4.2" 20 | pyqt6-qscintilla = "^2.13.4" 21 | 22 | [tool.poetry.dev-dependencies] 23 | pytest = "^7.1.2" 24 | pytest-cov = "^3.0.0" 25 | pytest-reorder = "^0.1.1" 26 | pre-commit = "^2.20.0" 27 | black = "22.6.0" 28 | isort = "5.10.1" 29 | pytest-watch = "^4.2.0" 30 | pytest-benchmark = "^3.4.1" 31 | 32 | [tool.poetry.scripts] 33 | vortex = 'vortex.cli:run' 34 | 35 | [build-system] 36 | requires = ["poetry-core>=1.0.0"] 37 | build-backend = "poetry.core.masonry.api" 38 | -------------------------------------------------------------------------------- /pytest.ini: -------------------------------------------------------------------------------- 1 | [pytest] 2 | addopts = --benchmark-disable 3 | -------------------------------------------------------------------------------- /test/test_mini_interpreter.py: -------------------------------------------------------------------------------- 1 | import pytest 2 | 3 | from vortex.mini import mini 4 | from vortex.pattern import ( 5 | Pattern, 6 | TimeSpan, 7 | cat, 8 | choose_cycles, 9 | degrade, 10 | fast, 11 | polyrhythm, 12 | pure, 13 | silence, 14 | slow, 15 | slowcat, 16 | stack, 17 | timecat, 18 | ) 19 | 20 | 21 | @pytest.mark.parametrize( 22 | "input_code,query_span,expected_pat", 23 | [ 24 | # numbers 25 | ("45", None, pure(45)), 26 | ("-2.", None, pure(-2.0)), 27 | ("4.64", None, pure(4.64)), 28 | ("-3", None, pure(-3)), 29 | # words 30 | ("foo", None, pure("foo")), 31 | ("Bar", None, pure("Bar")), 32 | # rest 33 | ("~", None, silence()), 34 | # modifiers 35 | ("bd*2", None, fast(2, "bd")), 36 | ("bd/3", None, slow(3, "bd")), 37 | ("hh?", None, degrade("hh")), 38 | ("hh??", None, degrade(degrade("hh"))), 39 | ( 40 | "hh!!??", 41 | None, 42 | degrade(degrade(cat("hh", "hh", "hh"))), 43 | ), 44 | # sequences 45 | ("bd sd", None, cat("bd", "sd")), 46 | ("bd hh sd", None, cat("bd", "hh", "sd")), 47 | ("hh@2", None, pure("hh")), 48 | ("bd hh@2", None, timecat((1, "bd"), (2, "hh"))), 49 | ("bd hh@3 sd@2", None, timecat((1, "bd"), (3, "hh"), (2, "sd"))), 50 | ("hh!", None, cat("hh", "hh")), 51 | ("hh!!", None, cat("hh", "hh", "hh")), 52 | ("bd! cp", None, cat("bd", "bd", "cp")), 53 | ( 54 | "bd! hh? ~ sd/2 cp*3", 55 | None, 56 | timecat( 57 | (1, "bd"), 58 | (1, "bd"), 59 | (1, degrade("hh")), 60 | (1, silence()), 61 | (1, slow(2, "sd")), 62 | (1, fast(3, "cp")), 63 | ), 64 | ), 65 | ("bd | sd", TimeSpan(0, 10), choose_cycles("bd", "sd")), 66 | ( 67 | "[bd [~ sd]] cp", 68 | None, 69 | cat(polyrhythm(["bd", polyrhythm([silence(), "sd"])]), "cp"), 70 | ), 71 | ( 72 | "{a b c, D E}%2", 73 | TimeSpan(0, 3), 74 | slowcat( 75 | stack(cat("a", "b"), cat("D", "E")), 76 | stack(cat("c", "a"), cat("D", "E")), 77 | stack(cat("b", "c"), cat("D", "E")), 78 | ), 79 | ), 80 | ("", TimeSpan(0, 3), mini("{a b, c d e}%1")), 81 | ("bd(3,8)", None, pure("bd").euclid(3, 8)), 82 | ("bd(3,8,2)", None, pure("bd").euclid(3, 8, 2)), 83 | ("bd(<3 5>,8,<2 4>)", None, pure("bd").euclid(slowcat(3, 5), 8, slowcat(2, 4))), 84 | ("bd _ _ sd", None, mini("bd@3 sd")), 85 | ("bd cp . sd", None, polyrhythm([cat("bd", "cp"), "sd"])), 86 | ("bd*<2 3 4>", TimeSpan(0, 4), pure("bd").fast(slowcat(2, 3, 4))), 87 | ("bd/[2 3]", TimeSpan(0, 4), pure("bd").slow(cat(2, 3))), 88 | ], 89 | ) 90 | def test_eval(input_code, query_span, expected_pat): 91 | pat = mini(input_code) 92 | assert isinstance(pat, Pattern) 93 | if not query_span: 94 | query_span = TimeSpan(0, 1) 95 | assert sorted(pat.query(query_span)) == sorted(expected_pat.query(query_span)) 96 | 97 | 98 | # @pytest.mark.parametrize( 99 | # "test_input,expected", 100 | # [ 101 | # # words 102 | # ("bd ", []), 103 | # ("bd#32", []), 104 | # ("drum_sound", []), 105 | # # sequences 106 | # ("bd bd", []), 107 | # ("bd bd bd ", []), 108 | # # modifiers 109 | # ("drum_sound/4", []), 110 | # ("sn*4 cp!4 bd@8 hh/3", []), 111 | # ("sn%4", []), # doesn't work in tidal but works here 112 | # ("sn*(3/5)", []), # scalar (fraction) argument of '*' 113 | # ("sn:35 sn:2 sn", []), # scalar (fraction) argument of '*' 114 | # # brackets 115 | # (" [ bd ] ", []), 116 | # ("[bd#32]", []), 117 | # ("[ bd bd bd ]", []), 118 | # ("[bd@3 ]", []), 119 | # # bracket modifiers 120 | # ("[bd#32@3 ]@3", []), 121 | # ("[-1.000!3 ]@3", []), 122 | # ("[-1.000!3 bd@3 ]@3", []), 123 | # # nesting 124 | # ("[[bd#32@3 ]]", []), 125 | # ("[ [bd@3 ]@3 bd ]", []), 126 | # (" [[ bd@3 ]@3] ", []), 127 | # (" [[ 0.3333@3 ]@3] ", []), 128 | # (" [[ bd@3 ]@3 bd!2]!3 ", []), 129 | # # deeper nesting 130 | # (" [ bd bd [bd bd]@3 [bd [bd bd]!3 ] ]", []), 131 | # (" [ bd bd [bd bd] [bd [bd bd] ] ]", []), 132 | # (" [ bd bd [bd bd] [bd [bd bd] ] ]@3", []), 133 | # (" [ bd [bd [bd [bd [bd [bd]]]]]]", []), 134 | # # angle brackets 135 | # ("< bd cp hh >", []), 136 | # ("< bd cp >", []), 137 | # ("< bd cp !2 >!3", []), 138 | # # curly brackets 139 | # ("{ bd cp bd }", []), 140 | # ("{ bd cp bd }%4", []), 141 | # ("{ bd cp {bd cp sn}%5 }%4", []), 142 | # # bracket mixtures 143 | # ("{ bd [bd hh ] }", []), 144 | # # euclidean 145 | # (" bd(3,8) ", []), 146 | # (" cp( 3,8, 2) ", []), 147 | # ("bd(3,4) cp( 3,8, 2) ", []), 148 | # (" cp( 3,8)!2 ", []), 149 | # (" cp( 3,8, 2)!2 ", []), 150 | # (" [bd cp ](3,8) ", []), 151 | # # patterned euclidean 152 | # ( 153 | # "bd(3 5 2/3, 5)", 154 | # [], 155 | # ), # works but i think 3/2 is a fraction, not a slow-modified element 156 | # ( 157 | # "bd(3 5 <2 3>, <5 7 4>)", 158 | # [], 159 | # ), # works but i don't undertand how we can pattern numbers yet. 160 | # # euclidean bracket mixtures 161 | # ( 162 | # "{ bd(3,7) [bd hh(3,5) ] }", 163 | # [], 164 | # ), 165 | # # stacks 166 | # ("[bd, bd bd bd]", []), 167 | # ("[bd, bd bd bd, cp cp cp cp]", []), 168 | # ("[bd, [cp cp]!2, [sn sn sn]]", []), 169 | # ("[bd, [bd bd] bd [sn bd hh] hh hh ]", []), 170 | # # euclidan in stacks 171 | # ("[bd, cp(3,8) ]", []), 172 | # ("[bd,cp(3,8)]", []), 173 | # ("[bd, cp(3,8) sn(5,8) ]", []), 174 | # ("[bd, cp(3,8) sn!3 sn, cp ]", []), 175 | # ("[bd, cp(3,8), cp(5, 19) ]", []), 176 | # ("[bd, cp(3,8), bd(3,2,4), cp(5, 19) ]", []), 177 | # ("[bd, cp(3,8), bd(3 ,<3 8>,4), cp(5, 19) ]", []), 178 | # # nested stacks 179 | # ("[bd, [cp, sn!5] ]", []), 180 | # ("[bd, cp [cp*2, sn!5] ]", []), 181 | # pytest.param( 182 | # " [[ (3/8)@3 ]@3] ", [], marks=pytest.mark.xfail 183 | # ), # fails because number elements aren't handled yet. 184 | # pytest.param( 185 | # "[(-1.000/32)@3 ]@3", [], marks=pytest.mark.xfail 186 | # ), # fails because number elements aren't handled yet. 187 | # ], 188 | # ) 189 | # def test_parse(benchmark, test_input, expected): 190 | # # FIXME: Assert expected output 191 | # assert benchmark(grammar.parse, test_input) 192 | 193 | 194 | # @pytest.mark.parametrize( 195 | # "test_input,expected", 196 | # [ 197 | # ("bd", pure("bd")), 198 | # ("bd sd", cat(pure("bd"), pure("sd"))), 199 | # ("drum_sound/4", pure("drum_sound").slow(4)), 200 | # ], 201 | # ) 202 | # def test_eval(test_input, expected): 203 | # assert mini(test_input).first_cycle() == expected.first_cycle() 204 | -------------------------------------------------------------------------------- /test/test_mini_parser.py: -------------------------------------------------------------------------------- 1 | import pytest 2 | 3 | from vortex.mini import parse_mini 4 | 5 | 6 | @pytest.mark.parametrize( 7 | "input_code,expected_ast", 8 | [ 9 | # numbers 10 | ( 11 | "45", 12 | { 13 | "type": "sequence", 14 | "elements": [ 15 | { 16 | "type": "element", 17 | "value": {"type": "number", "value": 45}, 18 | "modifiers": [], 19 | } 20 | ], 21 | }, 22 | ), 23 | ( 24 | "-2.", 25 | { 26 | "type": "sequence", 27 | "elements": [ 28 | { 29 | "type": "element", 30 | "value": {"type": "number", "value": -2.0}, 31 | "modifiers": [], 32 | } 33 | ], 34 | }, 35 | ), 36 | ( 37 | "4.64", 38 | { 39 | "type": "sequence", 40 | "elements": [ 41 | { 42 | "type": "element", 43 | "value": {"type": "number", "value": 4.64}, 44 | "modifiers": [], 45 | } 46 | ], 47 | }, 48 | ), 49 | ( 50 | "-3", 51 | { 52 | "type": "sequence", 53 | "elements": [ 54 | { 55 | "type": "element", 56 | "value": {"type": "number", "value": -3}, 57 | "modifiers": [], 58 | } 59 | ], 60 | }, 61 | ), 62 | # words 63 | ( 64 | "foo", 65 | { 66 | "type": "sequence", 67 | "elements": [ 68 | { 69 | "type": "element", 70 | "value": {"type": "word", "value": "foo", "index": 0}, 71 | "modifiers": [], 72 | } 73 | ], 74 | }, 75 | ), 76 | ( 77 | "Bar:2", 78 | { 79 | "type": "sequence", 80 | "elements": [ 81 | { 82 | "type": "element", 83 | "value": {"type": "word", "value": "Bar", "index": 2}, 84 | "modifiers": [], 85 | } 86 | ], 87 | }, 88 | ), 89 | # rest 90 | ( 91 | "~", 92 | { 93 | "type": "sequence", 94 | "elements": [ 95 | {"type": "element", "value": {"type": "rest"}, "modifiers": []} 96 | ], 97 | }, 98 | ), 99 | # modifiers 100 | ( 101 | "bd*2", 102 | { 103 | "type": "sequence", 104 | "elements": [ 105 | { 106 | "type": "element", 107 | "value": {"type": "word", "value": "bd", "index": 0}, 108 | "modifiers": [ 109 | { 110 | "type": "modifier", 111 | "op": "fast", 112 | "value": { 113 | "type": "element", 114 | "value": {"type": "number", "value": 2}, 115 | "modifiers": [], 116 | }, 117 | } 118 | ], 119 | } 120 | ], 121 | }, 122 | ), 123 | ( 124 | "bd/3", 125 | { 126 | "type": "sequence", 127 | "elements": [ 128 | { 129 | "type": "element", 130 | "value": {"type": "word", "value": "bd", "index": 0}, 131 | "modifiers": [ 132 | { 133 | "type": "modifier", 134 | "op": "slow", 135 | "value": { 136 | "type": "element", 137 | "value": {"type": "number", "value": 3}, 138 | "modifiers": [], 139 | }, 140 | } 141 | ], 142 | } 143 | ], 144 | }, 145 | ), 146 | ( 147 | "hh?", 148 | { 149 | "type": "sequence", 150 | "elements": [ 151 | { 152 | "type": "element", 153 | "value": {"type": "word", "value": "hh", "index": 0}, 154 | "modifiers": [ 155 | { 156 | "type": "modifier", 157 | "op": "degrade", 158 | "value": { 159 | "type": "degrade_arg", 160 | "op": "count", 161 | "value": 1, 162 | }, 163 | } 164 | ], 165 | } 166 | ], 167 | }, 168 | ), 169 | ( 170 | "hh???", 171 | { 172 | "type": "sequence", 173 | "elements": [ 174 | { 175 | "type": "element", 176 | "value": {"type": "word", "value": "hh", "index": 0}, 177 | "modifiers": [ 178 | { 179 | "type": "modifier", 180 | "op": "degrade", 181 | "value": { 182 | "type": "degrade_arg", 183 | "op": "count", 184 | "value": 3, 185 | }, 186 | } 187 | ], 188 | } 189 | ], 190 | }, 191 | ), 192 | ( 193 | "hh?4", 194 | { 195 | "type": "sequence", 196 | "elements": [ 197 | { 198 | "type": "element", 199 | "value": {"type": "word", "value": "hh", "index": 0}, 200 | "modifiers": [ 201 | { 202 | "type": "modifier", 203 | "op": "degrade", 204 | "value": { 205 | "type": "degrade_arg", 206 | "op": "count", 207 | "value": 4, 208 | }, 209 | } 210 | ], 211 | } 212 | ], 213 | }, 214 | ), 215 | ( 216 | "hh?4??", 217 | { 218 | "type": "sequence", 219 | "elements": [ 220 | { 221 | "type": "element", 222 | "value": {"type": "word", "value": "hh", "index": 0}, 223 | "modifiers": [ 224 | { 225 | "type": "modifier", 226 | "op": "degrade", 227 | "value": { 228 | "type": "degrade_arg", 229 | "op": "count", 230 | "value": 6, 231 | }, 232 | } 233 | ], 234 | } 235 | ], 236 | }, 237 | ), 238 | ( 239 | "hh??0.87", 240 | { 241 | "type": "sequence", 242 | "elements": [ 243 | { 244 | "type": "element", 245 | "value": {"type": "word", "value": "hh", "index": 0}, 246 | "modifiers": [ 247 | { 248 | "type": "modifier", 249 | "op": "degrade", 250 | "value": { 251 | "type": "degrade_arg", 252 | "op": "value", 253 | "value": 0.87, 254 | }, 255 | } 256 | ], 257 | } 258 | ], 259 | }, 260 | ), 261 | ( 262 | "hh!", 263 | { 264 | "type": "sequence", 265 | "elements": [ 266 | { 267 | "type": "element", 268 | "value": {"type": "word", "value": "hh", "index": 0}, 269 | "modifiers": [{"type": "modifier", "op": "repeat", "count": 1}], 270 | } 271 | ], 272 | }, 273 | ), 274 | ( 275 | "hh!!!", 276 | { 277 | "type": "sequence", 278 | "elements": [ 279 | { 280 | "type": "element", 281 | "value": {"type": "word", "value": "hh", "index": 0}, 282 | "modifiers": [{"type": "modifier", "op": "repeat", "count": 3}], 283 | } 284 | ], 285 | }, 286 | ), 287 | ( 288 | "hh!4", 289 | { 290 | "type": "sequence", 291 | "elements": [ 292 | { 293 | "type": "element", 294 | "value": {"type": "word", "value": "hh", "index": 0}, 295 | "modifiers": [{"type": "modifier", "op": "repeat", "count": 4}], 296 | } 297 | ], 298 | }, 299 | ), 300 | ( 301 | "hh!4!!", 302 | { 303 | "type": "sequence", 304 | "elements": [ 305 | { 306 | "type": "element", 307 | "value": {"type": "word", "value": "hh", "index": 0}, 308 | "modifiers": [{"type": "modifier", "op": "repeat", "count": 6}], 309 | } 310 | ], 311 | }, 312 | ), 313 | ( 314 | "hh@2", 315 | { 316 | "type": "sequence", 317 | "elements": [ 318 | { 319 | "type": "element", 320 | "value": {"type": "word", "value": "hh", "index": 0}, 321 | "modifiers": [{"type": "modifier", "op": "weight", "value": 2}], 322 | } 323 | ], 324 | }, 325 | ), 326 | ( 327 | "hh!!??!", 328 | { 329 | "type": "sequence", 330 | "elements": [ 331 | { 332 | "type": "element", 333 | "value": {"type": "word", "value": "hh", "index": 0}, 334 | "modifiers": [ 335 | {"type": "modifier", "op": "repeat", "count": 2}, 336 | {"type": "modifier", "op": "repeat", "count": 1}, 337 | { 338 | "type": "modifier", 339 | "op": "degrade", 340 | "value": { 341 | "type": "degrade_arg", 342 | "op": "count", 343 | "value": 2, 344 | }, 345 | }, 346 | ], 347 | } 348 | ], 349 | }, 350 | ), 351 | ( 352 | "hh!/2?!", 353 | { 354 | "type": "sequence", 355 | "elements": [ 356 | { 357 | "type": "element", 358 | "value": {"type": "word", "value": "hh", "index": 0}, 359 | "modifiers": [ 360 | {"type": "modifier", "op": "repeat", "count": 1}, 361 | { 362 | "type": "modifier", 363 | "op": "slow", 364 | "value": { 365 | "type": "element", 366 | "value": {"type": "number", "value": 2}, 367 | "modifiers": [ 368 | { 369 | "type": "modifier", 370 | "op": "repeat", 371 | "count": 1, 372 | }, 373 | { 374 | "type": "modifier", 375 | "op": "degrade", 376 | "value": { 377 | "type": "degrade_arg", 378 | "op": "count", 379 | "value": 1, 380 | }, 381 | }, 382 | ], 383 | }, 384 | }, 385 | ], 386 | } 387 | ], 388 | }, 389 | ), 390 | # sequences 391 | ( 392 | "bd sd", 393 | { 394 | "type": "sequence", 395 | "elements": [ 396 | { 397 | "type": "element", 398 | "value": {"type": "word", "value": "bd", "index": 0}, 399 | "modifiers": [], 400 | }, 401 | { 402 | "type": "element", 403 | "value": {"type": "word", "value": "sd", "index": 0}, 404 | "modifiers": [], 405 | }, 406 | ], 407 | }, 408 | ), 409 | ( 410 | "bd hh sd", 411 | { 412 | "type": "sequence", 413 | "elements": [ 414 | { 415 | "type": "element", 416 | "value": {"type": "word", "value": "bd", "index": 0}, 417 | "modifiers": [], 418 | }, 419 | { 420 | "type": "element", 421 | "value": {"type": "word", "value": "hh", "index": 0}, 422 | "modifiers": [], 423 | }, 424 | { 425 | "type": "element", 426 | "value": {"type": "word", "value": "sd", "index": 0}, 427 | "modifiers": [], 428 | }, 429 | ], 430 | }, 431 | ), 432 | ( 433 | "bd! hh? ~ sd/2 cp*3", 434 | { 435 | "type": "sequence", 436 | "elements": [ 437 | { 438 | "type": "element", 439 | "value": {"type": "word", "value": "bd", "index": 0}, 440 | "modifiers": [{"type": "modifier", "op": "repeat", "count": 1}], 441 | }, 442 | { 443 | "type": "element", 444 | "value": {"type": "word", "value": "hh", "index": 0}, 445 | "modifiers": [ 446 | { 447 | "type": "modifier", 448 | "op": "degrade", 449 | "value": { 450 | "type": "degrade_arg", 451 | "op": "count", 452 | "value": 1, 453 | }, 454 | } 455 | ], 456 | }, 457 | {"type": "element", "value": {"type": "rest"}, "modifiers": []}, 458 | { 459 | "type": "element", 460 | "value": {"type": "word", "value": "sd", "index": 0}, 461 | "modifiers": [ 462 | { 463 | "type": "modifier", 464 | "op": "slow", 465 | "value": { 466 | "type": "element", 467 | "value": {"type": "number", "value": 2}, 468 | "modifiers": [], 469 | }, 470 | } 471 | ], 472 | }, 473 | { 474 | "type": "element", 475 | "value": {"type": "word", "value": "cp", "index": 0}, 476 | "modifiers": [ 477 | { 478 | "type": "modifier", 479 | "op": "fast", 480 | "value": { 481 | "type": "element", 482 | "value": {"type": "number", "value": 3}, 483 | "modifiers": [], 484 | }, 485 | } 486 | ], 487 | }, 488 | ], 489 | }, 490 | ), 491 | # polyrhythms 492 | ( 493 | "[bd sd] hh", 494 | { 495 | "type": "sequence", 496 | "elements": [ 497 | { 498 | "type": "element", 499 | "value": { 500 | "type": "polyrhythm", 501 | "seqs": [ 502 | { 503 | "type": "sequence", 504 | "elements": [ 505 | { 506 | "type": "element", 507 | "value": { 508 | "type": "word", 509 | "value": "bd", 510 | "index": 0, 511 | }, 512 | "modifiers": [], 513 | }, 514 | { 515 | "type": "element", 516 | "value": { 517 | "type": "word", 518 | "value": "sd", 519 | "index": 0, 520 | }, 521 | "modifiers": [], 522 | }, 523 | ], 524 | } 525 | ], 526 | }, 527 | "modifiers": [], 528 | }, 529 | { 530 | "type": "element", 531 | "value": {"type": "word", "value": "hh", "index": 0}, 532 | "modifiers": [], 533 | }, 534 | ], 535 | }, 536 | ), 537 | # random sequence 538 | ( 539 | "bd | sd cp", 540 | { 541 | "type": "random_sequence", 542 | "elements": [ 543 | { 544 | "type": "sequence", 545 | "elements": [ 546 | { 547 | "type": "element", 548 | "value": {"type": "word", "value": "bd", "index": 0}, 549 | "modifiers": [], 550 | } 551 | ], 552 | }, 553 | { 554 | "type": "sequence", 555 | "elements": [ 556 | { 557 | "type": "element", 558 | "value": {"type": "word", "value": "sd", "index": 0}, 559 | "modifiers": [], 560 | }, 561 | { 562 | "type": "element", 563 | "value": {"type": "word", "value": "cp", "index": 0}, 564 | "modifiers": [], 565 | }, 566 | ], 567 | }, 568 | ], 569 | }, 570 | ), 571 | ( 572 | "bd _ _ sd", 573 | { 574 | "type": "sequence", 575 | "elements": [ 576 | { 577 | "type": "element", 578 | "value": {"type": "word", "value": "bd", "index": 0}, 579 | "modifiers": [{"type": "modifier", "op": "weight", "value": 3}], 580 | }, 581 | { 582 | "type": "element", 583 | "value": {"type": "word", "value": "sd", "index": 0}, 584 | "modifiers": [], 585 | }, 586 | ], 587 | }, 588 | ), 589 | ("bd sd . cp . hh*2", parse_mini("[bd sd] [cp] [hh*2]")), 590 | ( 591 | "bd*<2 3 4>", 592 | { 593 | "type": "sequence", 594 | "elements": [ 595 | { 596 | "type": "element", 597 | "value": {"type": "word", "value": "bd", "index": 0}, 598 | "modifiers": [ 599 | { 600 | "type": "modifier", 601 | "op": "fast", 602 | "value": { 603 | "type": "element", 604 | "value": { 605 | "type": "polymeter", 606 | "seqs": [ 607 | { 608 | "type": "sequence", 609 | "elements": [ 610 | { 611 | "type": "element", 612 | "value": { 613 | "type": "number", 614 | "value": 2, 615 | }, 616 | "modifiers": [], 617 | }, 618 | { 619 | "type": "element", 620 | "value": { 621 | "type": "number", 622 | "value": 3, 623 | }, 624 | "modifiers": [], 625 | }, 626 | { 627 | "type": "element", 628 | "value": { 629 | "type": "number", 630 | "value": 4, 631 | }, 632 | "modifiers": [], 633 | }, 634 | ], 635 | } 636 | ], 637 | "steps": 1, 638 | }, 639 | "modifiers": [], 640 | }, 641 | } 642 | ], 643 | } 644 | ], 645 | }, 646 | ), 647 | ], 648 | ) 649 | def test_parse(input_code, expected_ast): 650 | ast = parse_mini(input_code) 651 | assert ast == expected_ast 652 | -------------------------------------------------------------------------------- /test/test_pattern.py: -------------------------------------------------------------------------------- 1 | import math 2 | from itertools import groupby 3 | 4 | from vortex.control import ( 5 | s, 6 | speed, 7 | n, 8 | create_param, 9 | create_params) 10 | 11 | from vortex.pattern import ( 12 | Event, 13 | TimeSpan, 14 | choose, 15 | choose_cycles, 16 | choose_with, 17 | fast, 18 | fastcat, 19 | irand, 20 | perlin, 21 | pure, 22 | rand, 23 | randcat, 24 | rev, 25 | saw, 26 | slowcat, 27 | stack, 28 | timecat, 29 | wchoose, 30 | wchoose_with, 31 | ) 32 | 33 | 34 | def assert_equal_patterns(input, expected, span=None): 35 | """Assert patterns by queyring them and comparing events""" 36 | if not span: 37 | span = TimeSpan(0, 1) 38 | assert sorted(input.query(span)) == sorted(expected.query(span)) 39 | 40 | 41 | def test_add(): 42 | assert_equal_patterns(pure(3) + 2, pure(5)) 43 | assert_equal_patterns(3 + pure(5), pure(8)) 44 | 45 | 46 | def test_sub(): 47 | assert_equal_patterns(pure(3) - 1.5, pure(1.5)) 48 | assert_equal_patterns(3 - pure(1), pure(2)) 49 | 50 | 51 | def test_mul(): 52 | assert_equal_patterns(pure(3) * 2, pure(6)) 53 | assert_equal_patterns(10 * pure(3), pure(30)) 54 | 55 | 56 | def test_truediv(): 57 | assert_equal_patterns(pure(3) / 0.5, pure(6)) 58 | assert_equal_patterns(3 / pure(2), pure(3 / 2)) 59 | 60 | 61 | def test_floordiv(): 62 | assert_equal_patterns(pure(3) // 2, pure(1)) 63 | assert_equal_patterns(3 // pure(5), pure(0)) 64 | 65 | 66 | def test_mod(): 67 | assert_equal_patterns(pure(7) % 5, pure(2)) 68 | assert_equal_patterns(3 % pure(2), pure(1)) 69 | 70 | 71 | def test_pow(): 72 | assert_equal_patterns(pure(3) ** 2, pure(9)) 73 | assert_equal_patterns(2 ** pure(4), pure(16)) 74 | 75 | 76 | def test_superimpose(): 77 | assert_equal_patterns( 78 | pure("bd").superimpose(lambda p: p.fast(3)), 79 | stack(pure("bd"), pure("bd").fast(3)), 80 | ) 81 | 82 | 83 | def test_layer(): 84 | basepat = fastcat(pure("bd"), pure("sd")) 85 | assert_equal_patterns( 86 | basepat.layer(rev, lambda p: p.fast(2)), 87 | stack(basepat.rev(), basepat.fast(2)), 88 | ) 89 | 90 | 91 | def test_iter(): 92 | assert_equal_patterns( 93 | fastcat(pure("bd"), pure("hh"), pure("sn"), pure("cp")).iter(4), 94 | slowcat( 95 | fastcat(pure("bd"), pure("hh"), pure("sn"), pure("cp")), 96 | fastcat(pure("hh"), pure("sn"), pure("cp"), pure("bd")), 97 | fastcat(pure("sn"), pure("cp"), pure("bd"), pure("hh")), 98 | fastcat(pure("cp"), pure("bd"), pure("hh"), pure("sn")), 99 | ), 100 | span=TimeSpan(0, 4), 101 | ) 102 | 103 | 104 | def test_reviter(): 105 | assert_equal_patterns( 106 | fastcat(pure("bd"), pure("hh"), pure("sn"), pure("cp")).reviter(4), 107 | slowcat( 108 | fastcat(pure("bd"), pure("hh"), pure("sn"), pure("cp")), 109 | fastcat(pure("cp"), pure("bd"), pure("hh"), pure("sn")), 110 | fastcat(pure("sn"), pure("cp"), pure("bd"), pure("hh")), 111 | fastcat(pure("hh"), pure("sn"), pure("cp"), pure("bd")), 112 | ), 113 | span=TimeSpan(0, 4), 114 | ) 115 | 116 | 117 | def test_fastgap(): 118 | assert fastcat(pure("bd"), pure("sd")).fastgap(4).first_cycle() == [ 119 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), "bd"), 120 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), "sd"), 121 | ] 122 | 123 | 124 | def test_compress(): 125 | assert fastcat(pure("bd"), pure("sd")).compress(1 / 4, 3 / 4).first_cycle() == [ 126 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), "bd"), 127 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), "sd"), 128 | ] 129 | 130 | 131 | def test_compress_invalid_span(): 132 | assert pure("bd").fast(4).compress(1, 2).first_cycle() == [] 133 | assert pure("bd").fast(4).compress(-1, 0).first_cycle() == [] 134 | 135 | 136 | def test_compress_floats(): 137 | assert fastcat(pure("bd"), pure("sd")).compress(1 / 4, 3 / 4).first_cycle() == [ 138 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), "bd"), 139 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), "sd"), 140 | ] 141 | 142 | 143 | def test_timecat(): 144 | assert timecat((3, pure("bd").fast(4)), (1, pure("hh").fast(8))).first_cycle() == [ 145 | Event(TimeSpan(0, (3 / 16)), TimeSpan(0, (3 / 16)), "bd"), 146 | Event(TimeSpan((3 / 16), 3 / 8), TimeSpan((3 / 16), 3 / 8), "bd"), 147 | Event(TimeSpan(3 / 8, (9 / 16)), TimeSpan(3 / 8, (9 / 16)), "bd"), 148 | Event(TimeSpan((9 / 16), 3 / 4), TimeSpan((9 / 16), 3 / 4), "bd"), 149 | Event(TimeSpan(3 / 4, (25 / 32)), TimeSpan(3 / 4, (25 / 32)), "hh"), 150 | Event(TimeSpan((25 / 32), (13 / 16)), TimeSpan((25 / 32), (13 / 16)), "hh"), 151 | Event(TimeSpan((13 / 16), (27 / 32)), TimeSpan((13 / 16), (27 / 32)), "hh"), 152 | Event(TimeSpan((27 / 32), 7 / 8), TimeSpan((27 / 32), 7 / 8), "hh"), 153 | Event(TimeSpan(7 / 8, (29 / 32)), TimeSpan(7 / 8, (29 / 32)), "hh"), 154 | Event(TimeSpan((29 / 32), (15 / 16)), TimeSpan((29 / 32), (15 / 16)), "hh"), 155 | Event(TimeSpan((15 / 16), (31 / 32)), TimeSpan((15 / 16), (31 / 32)), "hh"), 156 | Event(TimeSpan((31 / 32), 1), TimeSpan((31 / 32), 1), "hh"), 157 | ] 158 | 159 | 160 | def test_striate(): 161 | assert s(fastcat("bd", "sd")).striate(4).first_cycle() == [ 162 | Event( 163 | TimeSpan(0, 1 / 8), 164 | TimeSpan(0, 1 / 8), 165 | {"s": "bd", "begin": 0.0, "end": 0.25}, 166 | ), 167 | Event( 168 | TimeSpan(1 / 8, 1 / 4), 169 | TimeSpan(1 / 8, 1 / 4), 170 | {"s": "sd", "begin": 0.0, "end": 0.25}, 171 | ), 172 | Event( 173 | TimeSpan(1 / 4, 3 / 8), 174 | TimeSpan(1 / 4, 3 / 8), 175 | {"s": "bd", "begin": 0.25, "end": 0.5}, 176 | ), 177 | Event( 178 | TimeSpan(3 / 8, 1 / 2), 179 | TimeSpan(3 / 8, 1 / 2), 180 | {"s": "sd", "begin": 0.25, "end": 0.5}, 181 | ), 182 | Event( 183 | TimeSpan(1 / 2, 5 / 8), 184 | TimeSpan(1 / 2, 5 / 8), 185 | {"s": "bd", "begin": 0.5, "end": 0.75}, 186 | ), 187 | Event( 188 | TimeSpan(5 / 8, 3 / 4), 189 | TimeSpan(5 / 8, 3 / 4), 190 | {"s": "sd", "begin": 0.5, "end": 0.75}, 191 | ), 192 | Event( 193 | TimeSpan(3 / 4, 7 / 8), 194 | TimeSpan(3 / 4, 7 / 8), 195 | {"s": "bd", "begin": 0.75, "end": 1.0}, 196 | ), 197 | Event( 198 | TimeSpan(7 / 8, 1), 199 | TimeSpan(7 / 8, 1), 200 | {"s": "sd", "begin": 0.75, "end": 1.0}, 201 | ), 202 | ] 203 | 204 | 205 | def test_range(): 206 | assert_equal_patterns(saw().range(2, 7), saw() * (7 - 2) + 2) 207 | 208 | 209 | def test_rangex(): 210 | assert_equal_patterns( 211 | saw().rangex(2, 7), saw().range(math.log(2), math.log(7)).fmap(math.exp) 212 | ) 213 | 214 | 215 | def test_rand(): 216 | assert rand().segment(4).first_cycle() == [ 217 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), 0.3147844299674034), 218 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), 0.6004995740950108), 219 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), 0.1394200474023819), 220 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), 0.3935417253524065), 221 | ] 222 | 223 | 224 | def test_irand(): 225 | assert irand(8).segment(4).first_cycle() == [ 226 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), 2), 227 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), 4), 228 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), 1), 229 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), 3), 230 | ] 231 | 232 | 233 | def test_perlin(): 234 | assert perlin().segment(4).first_cycle() == [ 235 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), 0.008311405901167745), 236 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), 0.1424947878645071), 237 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), 0.3752773577048174), 238 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), 0.5094607396681567), 239 | ] 240 | 241 | 242 | def test_perlin_with(): 243 | assert perlin(saw() * 4).segment(2).first_cycle() == [ 244 | Event(TimeSpan(0, 1 / 2), TimeSpan(0, 1 / 2), 0.5177721455693245), 245 | Event(TimeSpan(1 / 2, 1), TimeSpan(1 / 2, 1), 0.8026083502918482), 246 | ] 247 | 248 | 249 | def test_choose(): 250 | assert choose("a", "b", "c").segment(4).first_cycle() == [ 251 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), "a"), 252 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), "b"), 253 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), "a"), 254 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), "b"), 255 | ] 256 | 257 | 258 | def test_choose_with(): 259 | assert choose_with(perlin(), *range(8)).segment(4).first_cycle() == [ 260 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), 0), 261 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), 1), 262 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), 3), 263 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), 4), 264 | ] 265 | 266 | 267 | def test_choose_distribution(): 268 | values = [e.value for e in choose("a", "b", "c", "d").segment(100).first_cycle()] 269 | values_groupedby_count = {k: len(list(v)) for k, v in groupby(sorted(values))} 270 | # Check recurrence of values with uniform random distribution (each item should be around 25~) 271 | assert values_groupedby_count == {"a": 23, "b": 30, "c": 24, "d": 23} 272 | 273 | 274 | def test_wchoose(): 275 | assert wchoose(("a", 1), ("e", 0.5), ("g", 2), ("c", 1)).segment( 276 | 4 277 | ).first_cycle() == [ 278 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), "e"), 279 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), "g"), 280 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), "a"), 281 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), "g"), 282 | ] 283 | 284 | 285 | def test_wchoose_with(): 286 | assert wchoose_with( 287 | rand().late(100), ("a", 1), ("e", 0.5), ("g", 2), ("c", 1) 288 | ).segment(4).first_cycle() == [ 289 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 4), "a"), 290 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(1 / 4, 1 / 2), "g"), 291 | Event(TimeSpan(1 / 2, 3 / 4), TimeSpan(1 / 2, 3 / 4), "c"), 292 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 1), "a"), 293 | ] 294 | 295 | 296 | def test_wchoose_distribution(): 297 | values = [ 298 | e.value 299 | for e in wchoose(("a", 1), ("e", 0.5), ("g", 2), ("c", 1)) 300 | .segment(100) 301 | .first_cycle() 302 | ] 303 | values_groupedby_count = {k: len(list(v)) for k, v in groupby(sorted(values))} 304 | # Check recurrence of values based on weights and uniform random distribution 305 | # a =~ 20, e =~ 10, g =~ 50, c =~ 20 306 | assert values_groupedby_count == {"a": 22, "e": 10, "g": 48, "c": 20} 307 | 308 | 309 | def test_choose_cycles(): 310 | assert choose_cycles("bd", "sd", "hh").query(TimeSpan(0, 10)) == [ 311 | Event(TimeSpan(0, 1), TimeSpan(0, 1), "bd"), 312 | Event(TimeSpan(1, 2), TimeSpan(1, 2), "sd"), 313 | Event(TimeSpan(2, 3), TimeSpan(2, 3), "sd"), 314 | Event(TimeSpan(3, 4), TimeSpan(3, 4), "sd"), 315 | Event(TimeSpan(4, 5), TimeSpan(4, 5), "hh"), 316 | Event(TimeSpan(5, 6), TimeSpan(5, 6), "bd"), 317 | Event(TimeSpan(6, 7), TimeSpan(6, 7), "bd"), 318 | Event(TimeSpan(7, 8), TimeSpan(7, 8), "sd"), 319 | Event(TimeSpan(8, 9), TimeSpan(8, 9), "sd"), 320 | Event(TimeSpan(9, 10), TimeSpan(9, 10), "bd"), 321 | ] 322 | 323 | 324 | def test_randcat(): 325 | assert randcat("bd", "sd", "hh").query(TimeSpan(0, 10)) == choose_cycles( 326 | "bd", "sd", "hh" 327 | ).query(TimeSpan(0, 10)) 328 | 329 | 330 | def test_degrade(): 331 | assert_equal_patterns( 332 | pure("sd").fast(8).degrade(), pure("sd").fast(8).degrade_by(0.5, rand()) 333 | ) 334 | 335 | 336 | def test_degrade_by(): 337 | assert pure("sd").fast(8).degrade_by(0.75).first_cycle() == [ 338 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), "sd"), 339 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), "sd"), 340 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), "sd"), 341 | ] 342 | 343 | 344 | def test_degrade_by_diff_rand(): 345 | assert pure("sd").fast(8).degrade_by(0.5, rand().late(100)).first_cycle() == [ 346 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), "sd"), 347 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), "sd"), 348 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), "sd"), 349 | ] 350 | 351 | 352 | def test_undegrade(): 353 | assert_equal_patterns( 354 | pure("sd").fast(8).undegrade(), pure("sd").fast(8).undegrade_by(0.5, rand()) 355 | ) 356 | 357 | 358 | def test_undegrade_by(): 359 | assert pure("sd").fast(8).undegrade_by(0.25).first_cycle() == [ 360 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), "sd") 361 | ] 362 | 363 | 364 | def test_undegrade_by_diff_rand(): 365 | assert pure("sd").fast(8).undegrade_by(0.5, rand().late(100)).first_cycle() == [ 366 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), "sd"), 367 | Event(TimeSpan(1 / 4, 3 / 8), TimeSpan(1 / 4, 3 / 8), "sd"), 368 | Event(TimeSpan(5 / 8, 3 / 4), TimeSpan(5 / 8, 3 / 4), "sd"), 369 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), "sd"), 370 | Event(TimeSpan(7 / 8, 1), TimeSpan(7 / 8, 1), "sd"), 371 | ] 372 | 373 | 374 | def test_sometimes(): 375 | assert s("bd").fast(8).sometimes(lambda p: p << speed(2)).first_cycle() == [ 376 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), {"speed": 2, "s": "bd"}), 377 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), {"s": "bd"}), 378 | Event(TimeSpan(1 / 4, 3 / 8), TimeSpan(1 / 4, 3 / 8), {"s": "bd"}), 379 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), {"s": "bd"}), 380 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), {"s": "bd"}), 381 | Event(TimeSpan(5 / 8, 3 / 4), TimeSpan(5 / 8, 3 / 4), {"speed": 2, "s": "bd"}), 382 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), {"s": "bd"}), 383 | Event(TimeSpan(7 / 8, 1), TimeSpan(7 / 8, 1), {"s": "bd"}), 384 | ] 385 | 386 | 387 | def test_sometimes_by(): 388 | assert s("bd").fast(8).sometimes_by( 389 | 0.75, lambda p: p << speed(3) 390 | ).first_cycle() == [ 391 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), {"speed": 3, "s": "bd"}), 392 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), {"s": "bd"}), 393 | Event(TimeSpan(1 / 4, 3 / 8), TimeSpan(1 / 4, 3 / 8), {"speed": 3, "s": "bd"}), 394 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), {"speed": 3, "s": "bd"}), 395 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), {"s": "bd"}), 396 | Event(TimeSpan(5 / 8, 3 / 4), TimeSpan(5 / 8, 3 / 4), {"speed": 3, "s": "bd"}), 397 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), {"s": "bd"}), 398 | Event(TimeSpan(7 / 8, 1), TimeSpan(7 / 8, 1), {"speed": 3, "s": "bd"}), 399 | ] 400 | 401 | 402 | def test_sometimes_pre(): 403 | assert s("bd").fast(8).sometimes_pre(fast(2)).first_cycle() == [ 404 | Event(TimeSpan(1 / 16, 1 / 8), TimeSpan(1 / 16, 1 / 8), {"s": "bd"}), 405 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), {"s": "bd"}), 406 | Event(TimeSpan(1 / 4, 5 / 16), TimeSpan(1 / 4, 5 / 16), {"s": "bd"}), 407 | Event(TimeSpan(1 / 4, 3 / 8), TimeSpan(1 / 4, 3 / 8), {"s": "bd"}), 408 | Event(TimeSpan(5 / 16, 3 / 8), TimeSpan(5 / 16, 3 / 8), {"s": "bd"}), 409 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), {"s": "bd"}), 410 | Event(TimeSpan(7 / 16, 1 / 2), TimeSpan(7 / 16, 1 / 2), {"s": "bd"}), 411 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), {"s": "bd"}), 412 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), {"s": "bd"}), 413 | Event(TimeSpan(13 / 16, 7 / 8), TimeSpan(13 / 16, 7 / 8), {"s": "bd"}), 414 | Event(TimeSpan(7 / 8, 15 / 16), TimeSpan(7 / 8, 15 / 16), {"s": "bd"}), 415 | Event(TimeSpan(7 / 8, 1), TimeSpan(7 / 8, 1), {"s": "bd"}), 416 | ] 417 | 418 | 419 | def test_sometimes_pre_by(): 420 | assert s("bd").fast(8).sometimes_pre_by(0.25, fast(2)).first_cycle() == [ 421 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), {"s": "bd"}), 422 | Event(TimeSpan(1 / 4, 3 / 8), TimeSpan(1 / 4, 3 / 8), {"s": "bd"}), 423 | Event(TimeSpan(5 / 16, 3 / 8), TimeSpan(5 / 16, 3 / 8), {"s": "bd"}), 424 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), {"s": "bd"}), 425 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), {"s": "bd"}), 426 | Event(TimeSpan(5 / 8, 3 / 4), TimeSpan(5 / 8, 3 / 4), {"s": "bd"}), 427 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), {"s": "bd"}), 428 | Event(TimeSpan(7 / 8, 1), TimeSpan(7 / 8, 1), {"s": "bd"}), 429 | ] 430 | 431 | 432 | def test_somecycles(): 433 | assert s("sd").fast(2).somecycles(lambda p: p << speed(3)).query( 434 | TimeSpan(0, 4) 435 | ) == [ 436 | Event(TimeSpan(0, 1 / 2), TimeSpan(0, 1 / 2), {"speed": 3, "s": "sd"}), 437 | Event(TimeSpan(1 / 2, 1), TimeSpan(1 / 2, 1), {"speed": 3, "s": "sd"}), 438 | Event(TimeSpan(1, 3 / 2), TimeSpan(1, 3 / 2), {"s": "sd"}), 439 | Event(TimeSpan(3 / 2, 2 / 1), TimeSpan(3 / 2, 2 / 1), {"s": "sd"}), 440 | Event(TimeSpan(2 / 1, 5 / 2), TimeSpan(2 / 1, 5 / 2), {"speed": 3, "s": "sd"}), 441 | Event(TimeSpan(5 / 2, 3 / 1), TimeSpan(5 / 2, 3 / 1), {"speed": 3, "s": "sd"}), 442 | Event(TimeSpan(3 / 1, 7 / 2), TimeSpan(3 / 1, 7 / 2), {"s": "sd"}), 443 | Event(TimeSpan(7 / 2, 4 / 1), TimeSpan(7 / 2, 4 / 1), {"s": "sd"}), 444 | ] 445 | 446 | 447 | def test_somecycles_by(): 448 | assert s("sd").fast(2).somecycles_by(0.03, lambda p: p << speed(3)).query( 449 | TimeSpan(0, 6) 450 | ) == [ 451 | Event(TimeSpan(0, 1 / 2), TimeSpan(0, 1 / 2), {"speed": 3, "s": "sd"}), 452 | Event(TimeSpan(1 / 2, 1), TimeSpan(1 / 2, 1), {"speed": 3, "s": "sd"}), 453 | Event(TimeSpan(1, 3 / 2), TimeSpan(1, 3 / 2), {"s": "sd"}), 454 | Event(TimeSpan(3 / 2, 2 / 1), TimeSpan(3 / 2, 2 / 1), {"s": "sd"}), 455 | Event(TimeSpan(2 / 1, 5 / 2), TimeSpan(2 / 1, 5 / 2), {"s": "sd"}), 456 | Event(TimeSpan(5 / 2, 3 / 1), TimeSpan(5 / 2, 3 / 1), {"s": "sd"}), 457 | Event(TimeSpan(3 / 1, 7 / 2), TimeSpan(3 / 1, 7 / 2), {"s": "sd"}), 458 | Event(TimeSpan(7 / 2, 4 / 1), TimeSpan(7 / 2, 4 / 1), {"s": "sd"}), 459 | Event(TimeSpan(4 / 1, 9 / 2), TimeSpan(4 / 1, 9 / 2), {"s": "sd"}), 460 | Event(TimeSpan(9 / 2, 5 / 1), TimeSpan(9 / 2, 5 / 1), {"s": "sd"}), 461 | Event(TimeSpan(5 / 1, 11 / 2), TimeSpan(5 / 1, 11 / 2), {"s": "sd"}), 462 | Event(TimeSpan(11 / 2, 6 / 1), TimeSpan(11 / 2, 6 / 1), {"s": "sd"}), 463 | ] 464 | 465 | 466 | def test_struct(): 467 | assert pure("bd").struct(fastcat(1, 1, 0, 1, 0, 0, 1, 0)).first_cycle() == [ 468 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), "bd"), 469 | Event(TimeSpan(1 / 8, 1 / 4), TimeSpan(1 / 8, 1 / 4), "bd"), 470 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), "bd"), 471 | Event(TimeSpan(3 / 4, 7 / 8), TimeSpan(3 / 4, 7 / 8), "bd"), 472 | ] 473 | 474 | 475 | def test_mask(): 476 | assert s(fastcat("bd", "sd", "hh", "cp")).mask( 477 | fastcat(1, 1, 0, 1, 0, 0, 1, 0) 478 | ).first_cycle() == [ 479 | Event(TimeSpan(0, 1 / 4), TimeSpan(0, 1 / 8), {"s": "bd"}), 480 | Event(TimeSpan(0, 1 / 4), TimeSpan(1 / 8, 1 / 4), {"s": "bd"}), 481 | Event(TimeSpan(1 / 4, 1 / 2), TimeSpan(3 / 8, 1 / 2), {"s": "sd"}), 482 | Event(TimeSpan(3 / 4, 1), TimeSpan(3 / 4, 7 / 8), {"s": "cp"}), 483 | ] 484 | 485 | 486 | def test_euclid(): 487 | assert s("sd").euclid(fastcat(3, 5), 8, fastcat(0, 1)).first_cycle() == [ 488 | Event(TimeSpan(0, 1 / 8), TimeSpan(0, 1 / 8), {"s": "sd"}), 489 | Event(TimeSpan(3 / 8, 1 / 2), TimeSpan(3 / 8, 1 / 2), {"s": "sd"}), 490 | Event(TimeSpan(1 / 2, 5 / 8), TimeSpan(1 / 2, 5 / 8), {"s": "sd"}), 491 | Event(TimeSpan(5 / 8, 3 / 4), TimeSpan(5 / 8, 3 / 4), {"s": "sd"}), 492 | Event(TimeSpan(7 / 8, 1), TimeSpan(7 / 8, 1), {"s": "sd"}), 493 | ] 494 | 495 | 496 | def test_app_left(): 497 | assert saw().segment(1).query(TimeSpan(0, 0.25)) == [ 498 | Event(TimeSpan(0, 1), TimeSpan(0, 1 / 4), 0.5) 499 | ] 500 | 501 | def test_rshift(): 502 | assert_equal_patterns( 503 | s("a") >> n("0 1"), 504 | s("a").combine_right(n("0 1")) 505 | ) 506 | assert_equal_patterns( 507 | s("a").n("0 1"), 508 | s("a").combine_right(n("0 1")) 509 | ) 510 | 511 | def test_lshift(): 512 | assert_equal_patterns( 513 | s("a") << n("0 1"), 514 | s("a").combine_left(n("0 1")) 515 | ) 516 | 517 | def test_create_param(): 518 | _foo = create_param('foo') 519 | assert _foo(5).first_cycle() == [ 520 | Event(TimeSpan(0, 1), TimeSpan(0, 1), {"foo": 5}) 521 | ] 522 | 523 | def test_create_params(): 524 | _foo, _bar = create_params(['foo', 'bar']) 525 | assert (_foo(17) >> _bar(42)).first_cycle() == [ 526 | Event(TimeSpan(0, 1), TimeSpan(0, 1), {"foo": 17, "bar": 42}) 527 | ] 528 | assert s('bd').foo(17).bar(42).first_cycle() == [ 529 | Event(TimeSpan(0, 1), TimeSpan(0, 1), {"s": "bd", "foo": 17, "bar": 42}) 530 | ] 531 | -------------------------------------------------------------------------------- /test/test_py_vortex.py: -------------------------------------------------------------------------------- 1 | from fractions import Fraction 2 | 3 | import pytest 4 | 5 | import vortex as pyt 6 | 7 | 8 | @pytest.fixture 9 | def multi_list(): 10 | return [[1, 2, 3], [4, 5, 6]] 11 | 12 | 13 | # Utilities 14 | def test_concat(multi_list): 15 | flat_list = pyt.flatten(multi_list) 16 | assert flat_list == [1, 2, 3, 4, 5, 6] 17 | 18 | 19 | def test_remove_none(multi_list): 20 | multi_list[0].append(None) 21 | no_none_list = pyt.remove_nones(multi_list[0]) 22 | assert list(no_none_list) == [1, 2, 3] 23 | 24 | 25 | # Time Class tests 26 | def test_sam(): 27 | a = Fraction(3, 2).sam() 28 | assert a == 1 29 | a = Fraction(3, 2).next_sam() 30 | assert a == 2 31 | 32 | 33 | def test_whole_cycle(): 34 | a = Fraction(3, 2).whole_cycle() 35 | assert a.begin == 1 36 | assert a.end == 2 37 | 38 | 39 | # TimeSpan Class tests 40 | def test_intersection(): 41 | a = pyt.TimeSpan(1, 4) 42 | span = a.intersection(pyt.TimeSpan(3, 6)) 43 | assert span.begin == pyt.TimeSpan(3, 4).begin 44 | assert span.end == pyt.TimeSpan(3, 4).end 45 | a = pyt.TimeSpan(1, 2) 46 | try: 47 | span = a.intersection(pyt.TimeSpan(3, 6)) 48 | except ValueError as v: 49 | assert ( 50 | str(v) 51 | == "TimeSpan TimeSpan(Time(1, 1), Time(2, 1)) and TimeSpan TimeSpan(Time(3, 1), Time(6, 1)) do not intersect" 52 | ) 53 | 54 | 55 | def test_with_time(): 56 | a = pyt.TimeSpan(1, 4) 57 | wt = a.with_time(lambda x: x * 2) 58 | assert wt.begin == pyt.TimeSpan(2, 8).begin 59 | assert wt.end == pyt.TimeSpan(2, 8).end 60 | 61 | 62 | def test_span_cycles(): 63 | a = pyt.TimeSpan(0.25, 2.5) 64 | sc = a.span_cycles() 65 | print(sc) 66 | assert sc[0].begin == a.begin 67 | assert sc[0].end == Fraction(1) 68 | assert sc[1].begin == Fraction(1) 69 | assert sc[1].end == Fraction(2) 70 | assert sc[2].begin == Fraction(2) 71 | assert sc[2].end == a.end 72 | 73 | 74 | # Event Class tests 75 | def test_event_span(): 76 | e = pyt.Event(0.25, 0.5, 1) 77 | ws = e.with_span(lambda x: x * 2) 78 | assert ws.whole == 0.5 79 | assert ws.part == 1 80 | assert ws.value == 1 81 | 82 | 83 | def test_event_value(): 84 | e = pyt.Event(pyt.TimeSpan(0, 1), pyt.TimeSpan(0.25, 0.5), 1) 85 | ws = e.with_value(lambda x: x * 2) 86 | print(ws) 87 | print(ws.whole) 88 | print(ws.whole.begin) 89 | assert ws.whole.begin == 0 90 | assert ws.whole.end == 1 91 | assert ws.part.begin == 0.25 92 | assert ws.part.end == 0.5 93 | assert ws.value == 2 94 | 95 | 96 | def test_has_onset(): 97 | e = pyt.Event(pyt.TimeSpan(0.5, 1.5), pyt.TimeSpan(0.5, 1), "hello") 98 | assert e.has_onset 99 | -------------------------------------------------------------------------------- /vortex/__init__.py: -------------------------------------------------------------------------------- 1 | import contextlib 2 | import importlib 3 | 4 | import pkg_resources 5 | 6 | try: 7 | # Change here if project is renamed and does not equal the package name 8 | package_name = "tidalvortex" 9 | __version__ = pkg_resources.get_distribution(package_name).version 10 | except pkg_resources.DistributionNotFound: # pragma: no cover 11 | __version__ = "unknown" 12 | 13 | 14 | from .control import * 15 | from .mini import mini, parse_mini 16 | from .pattern import * 17 | from .utils import * 18 | from .vortex import * 19 | 20 | 21 | @contextlib.contextmanager 22 | def vortex_dsl(): 23 | """ 24 | Create a Vortex DSL context, with a default LinkClock and some functions for 25 | managing Streams 26 | 27 | Returns 28 | ------- 29 | ModuleType 30 | Vortex DSL module 31 | 32 | """ 33 | # Import DSL module and get variables 34 | mod = importlib.import_module("vortex.boot") 35 | locals = vars(mod) 36 | 37 | # Start clock 38 | clock = locals["_default_clock"] 39 | clock.start() 40 | 41 | yield mod 42 | 43 | # We're exiting context, so stop clock thread 44 | clock.stop() 45 | -------------------------------------------------------------------------------- /vortex/boot.py: -------------------------------------------------------------------------------- 1 | from vortex import * 2 | from vortex.stream import LinkClock, SuperDirtStream 3 | 4 | _default_clock = LinkClock(bpm=120) 5 | __streams = {} 6 | 7 | 8 | def p(key, pattern=None): 9 | if key not in __streams: 10 | __streams[key] = SuperDirtStream(name=key) 11 | _default_clock.subscribe(__streams[key]) 12 | if pattern: 13 | __streams[key].pattern = pattern 14 | return __streams[key] 15 | 16 | 17 | def hush(): 18 | for stream in __streams.values(): 19 | stream.pattern = silence 20 | _default_clock.unsubscribe(stream) 21 | __streams.clear() 22 | 23 | 24 | class __Streams: 25 | def __setitem__(self, key, value): 26 | p(key, value) 27 | 28 | 29 | d = __Streams() 30 | -------------------------------------------------------------------------------- /vortex/cli.py: -------------------------------------------------------------------------------- 1 | """ 2 | Vortex REPL console script 3 | """ 4 | 5 | import argparse 6 | import logging 7 | import sys 8 | 9 | from vortex import __version__ 10 | from vortex.gui import start_gui 11 | from vortex.repl import start_repl 12 | 13 | _logger = logging.getLogger(__name__) 14 | 15 | 16 | def parse_args(args): 17 | """Parse command line parameters 18 | 19 | Args: 20 | args (List[str]): command line parameters as list of strings 21 | (for example ``["--help"]``). 22 | 23 | Returns: 24 | :obj:`argparse.Namespace`: command line parameters namespace 25 | """ 26 | parser = argparse.ArgumentParser(description="Start Vortex editor or REPL") 27 | 28 | parser.add_argument( 29 | "--gui", 30 | default=True, 31 | action="store_true", 32 | help="Start a GUI code editor", 33 | ) 34 | parser.add_argument( 35 | "--cli", 36 | dest="gui", 37 | action="store_false", 38 | help="Start the command line interpreter", 39 | ) 40 | 41 | parser.add_argument( 42 | "--version", 43 | action="version", 44 | version="pyvortex {ver}".format(ver=__version__), 45 | ) 46 | parser.add_argument( 47 | "-v", 48 | "--verbose", 49 | dest="loglevel", 50 | help="set loglevel to INFO", 51 | action="store_const", 52 | const=logging.INFO, 53 | ) 54 | parser.add_argument( 55 | "-vv", 56 | "--very-verbose", 57 | dest="loglevel", 58 | help="set loglevel to DEBUG", 59 | action="store_const", 60 | const=logging.DEBUG, 61 | ) 62 | return parser.parse_args(args) 63 | 64 | 65 | def setup_logging(loglevel): 66 | """Setup basic logging 67 | 68 | Args: 69 | loglevel (int): minimum loglevel for emitting messages 70 | """ 71 | logformat = "[%(asctime)s] %(levelname)s:%(name)s:%(message)s" 72 | logging.basicConfig( 73 | level=loglevel, stream=sys.stdout, format=logformat, datefmt="%Y-%m-%d %H:%M:%S" 74 | ) 75 | 76 | 77 | def main(args): 78 | """Wrapper allowing :func:`fib` to be called with string arguments in a CLI fashion 79 | 80 | Instead of returning the value from :func:`fib`, it prints the result to the 81 | ``stdout`` in a nicely formatted message. 82 | 83 | Args: 84 | args (List[str]): command line parameters as list of strings 85 | (for example ``["--verbose", "42"]``). 86 | """ 87 | args = parse_args(args) 88 | setup_logging(args.loglevel) 89 | 90 | if args.gui: 91 | start_gui() 92 | else: 93 | start_repl() 94 | 95 | 96 | def run(): 97 | """Calls :func:`main` passing the CLI arguments extracted from :obj:`sys.argv` 98 | 99 | This function can be used as entry point to create console scripts with setuptools. 100 | """ 101 | main(sys.argv[1:]) 102 | 103 | 104 | if __name__ == "__main__": 105 | run() 106 | -------------------------------------------------------------------------------- /vortex/control.py: -------------------------------------------------------------------------------- 1 | import sys 2 | 3 | from .pattern import * 4 | 5 | # Create functions for making control patterns (patterns of dictionaries) 6 | 7 | generic_params = [ 8 | ("s", "s", "sound"), 9 | ("s", "toArg", "for internal sound routing"), 10 | # ("f", "from", "for internal sound routing"), <- TODO - 'from' is a reserved word in python.. 11 | ("f", "to", "for internal sound routing"), 12 | ( 13 | "f", 14 | "accelerate", 15 | "a pattern of numbers that speed up (or slow down) samples while they play.", 16 | ), 17 | ("f", "amp", "like @gain@, but linear."), 18 | ( 19 | "f", 20 | "attack", 21 | "a pattern of numbers to specify the attack time (in seconds) of an envelope applied to each sample.", 22 | ), 23 | ( 24 | "f", 25 | "bandf", 26 | "a pattern of numbers from 0 to 1. Sets the center frequency of the band-pass filter.", 27 | ), 28 | ( 29 | "f", 30 | "bandq", 31 | "a pattern of anumbers from 0 to 1. Sets the q-factor of the band-pass filter.", 32 | ), 33 | ( 34 | "f", 35 | "begin", 36 | "a pattern of numbers from 0 to 1. Skips the beginning of each sample, e.g. `0.25` to cut off the first quarter from each sample.", 37 | ), 38 | ("f", "legato", "controls the amount of overlap between two adjacent sounds"), 39 | ("f", "clhatdecay", ""), 40 | ( 41 | "f", 42 | "crush", 43 | "bit crushing, a pattern of numbers from 1 (for drastic reduction in bit-depth) to 16 (for barely no reduction).", 44 | ), 45 | ( 46 | "f", 47 | "coarse", 48 | "fake-resampling, a pattern of numbers for lowering the sample rate, i.e. 1 for original 2 for half, 3 for a third and so on.", 49 | ), 50 | ("i", "channel", "choose the channel the pattern is sent to in superdirt"), 51 | ( 52 | "i", 53 | "cut", 54 | "In the style of classic drum-machines, `cut` will stop a playing sample as soon as another samples with in same cutgroup is to be played. An example would be an open hi-hat followed by a closed one, essentially muting the open.", 55 | ), 56 | ( 57 | "f", 58 | "cutoff", 59 | "a pattern of numbers from 0 to 1. Applies the cutoff frequency of the low-pass filter.", 60 | ), 61 | ("f", "cutoffegint", ""), 62 | ("f", "decay", ""), 63 | ( 64 | "f", 65 | "delay", 66 | "a pattern of numbers from 0 to 1. Sets the level of the delay signal.", 67 | ), 68 | ( 69 | "f", 70 | "delayfeedback", 71 | "a pattern of numbers from 0 to 1. Sets the amount of delay feedback.", 72 | ), 73 | ( 74 | "f", 75 | "delaytime", 76 | "a pattern of numbers from 0 to 1. Sets the length of the delay.", 77 | ), 78 | ("f", "detune", ""), 79 | ("f", "djf", "DJ filter, below 0.5 is low pass filter, above is high pass filter."), 80 | ( 81 | "f", 82 | "dry", 83 | "when set to `1` will disable all reverb for this pattern. See `room` and `size` for more information about reverb.", 84 | ), 85 | ( 86 | "f", 87 | "end", 88 | "the same as `begin`, but cuts the end off samples, shortening them; e.g. `0.75` to cut off the last quarter of each sample.", 89 | ), 90 | ( 91 | "f", 92 | "fadeTime", 93 | "Used when using begin/end or chop/striate and friends, to change the fade out time of the 'grain' envelope.", 94 | ), 95 | ( 96 | "f", 97 | "fadeInTime", 98 | "As with fadeTime, but controls the fade in time of the grain envelope. Not used if the grain begins at position 0 in the sample.", 99 | ), 100 | ("f", "freq", ""), 101 | ( 102 | "f", 103 | "gain", 104 | "a pattern of numbers that specify volume. Values less than 1 make the sound quieter. Values greater than 1 make the sound louder. For the linear equivalent, see @amp@.", 105 | ), 106 | ("f", "gate", ""), 107 | ("f", "hatgrain", ""), 108 | ( 109 | "f", 110 | "hcutoff", 111 | "a pattern of numbers from 0 to 1. Applies the cutoff frequency of the high-pass filter. Also has alias @hpf@", 112 | ), 113 | ( 114 | "f", 115 | "hold", 116 | "a pattern of numbers to specify the hold time (in seconds) of an envelope applied to each sample. Only takes effect if `attack` and `release` are also specified.", 117 | ), 118 | ( 119 | "f", 120 | "hresonance", 121 | "a pattern of numbers from 0 to 1. Applies the resonance of the high-pass filter. Has alias @hpq@", 122 | ), 123 | ("f", "lagogo", ""), 124 | ("f", "lclap", ""), 125 | ("f", "lclaves", ""), 126 | ("f", "lclhat", ""), 127 | ("f", "lcrash", ""), 128 | ("f", "leslie", ""), 129 | ("f", "lrate", ""), 130 | ("f", "lsize", ""), 131 | ("f", "lfo", ""), 132 | ("f", "lfocutoffint", ""), 133 | ("f", "lfodelay", ""), 134 | ("f", "lfoint", ""), 135 | ("f", "lfopitchint", ""), 136 | ("f", "lfoshape", ""), 137 | ("f", "lfosync", ""), 138 | ("f", "lhitom", ""), 139 | ("f", "lkick", ""), 140 | ("f", "llotom", ""), 141 | ( 142 | "f", 143 | "lock", 144 | "A pattern of numbers. Specifies whether delaytime is calculated relative to cps. When set to 1, delaytime is a direct multiple of a cycle.", 145 | ), 146 | ( 147 | "f", 148 | "loop", 149 | "loops the sample (from `begin` to `end`) the specified number of times.", 150 | ), 151 | ("f", "lophat", ""), 152 | ("f", "lsnare", ""), 153 | ("f", "n", "The note or sample number to choose for a synth or sampleset"), 154 | ("f", "note", "The note or pitch to play a sound or synth with"), 155 | ("f", "degree", ""), 156 | ("f", "mtranspose", ""), 157 | ("f", "ctranspose", ""), 158 | ("f", "harmonic", ""), 159 | ("f", "stepsPerOctave", ""), 160 | ("f", "octaveR", ""), 161 | ( 162 | "f", 163 | "nudge", 164 | "Nudges events into the future by the specified number of seconds. Negative numbers work up to a point as well (due to internal latency)", 165 | ), 166 | ("i", "octave", ""), 167 | ("f", "offset", ""), 168 | ("f", "ophatdecay", ""), 169 | ( 170 | "i", 171 | "orbit", 172 | "a pattern of numbers. An `orbit` is a global parameter context for patterns. Patterns with the same orbit will share hardware output bus offset and global effects, e.g. reverb and delay. The maximum number of orbits is specified in the superdirt startup, numbers higher than maximum will wrap around.", 173 | ), 174 | ("f", "overgain", ""), 175 | ("f", "overshape", ""), 176 | ( 177 | "f", 178 | "pan", 179 | "a pattern of numbers between 0 and 1, from left to right (assuming stereo), once round a circle (assuming multichannel)", 180 | ), 181 | ( 182 | "f", 183 | "panspan", 184 | "a pattern of numbers between -inf and inf, which controls how much multichannel output is fanned out (negative is backwards ordering)", 185 | ), 186 | ( 187 | "f", 188 | "pansplay", 189 | "a pattern of numbers between 0.0 and 1.0, which controls the multichannel spread range (multichannel only)", 190 | ), 191 | ( 192 | "f", 193 | "panwidth", 194 | "a pattern of numbers between 0.0 and inf, which controls how much each channel is distributed over neighbours (multichannel only)", 195 | ), 196 | ( 197 | "f", 198 | "panorient", 199 | "a pattern of numbers between -1.0 and 1.0, which controls the relative position of the centre pan in a pair of adjacent speakers (multichannel only)", 200 | ), 201 | ("f", "pitch1", ""), 202 | ("f", "pitch2", ""), 203 | ("f", "pitch3", ""), 204 | ("f", "portamento", ""), 205 | ("f", "rate", "used in SuperDirt softsynths as a control rate or 'speed'"), 206 | ( 207 | "f", 208 | "release", 209 | "a pattern of numbers to specify the release time (in seconds) of an envelope applied to each sample.", 210 | ), 211 | ( 212 | "f", 213 | "resonance", 214 | "a pattern of numbers from 0 to 1. Specifies the resonance of the low-pass filter.", 215 | ), 216 | ("f", "room", "a pattern of numbers from 0 to 1. Sets the level of reverb."), 217 | ("f", "sagogo", ""), 218 | ("f", "sclap", ""), 219 | ("f", "sclaves", ""), 220 | ("f", "scrash", ""), 221 | ("f", "semitone", ""), 222 | ( 223 | "f", 224 | "shape", 225 | "wave shaping distortion, a pattern of numbers from 0 for no distortion up to 1 for loads of distortion.", 226 | ), 227 | ( 228 | "f", 229 | "size", 230 | "a pattern of numbers from 0 to 1. Sets the perceptual size (reverb time) of the `room` to be used in reverb.", 231 | ), 232 | ("f", "slide", ""), 233 | ( 234 | "f", 235 | "speed", 236 | "a pattern of numbers which changes the speed of sample playback, i.e. a cheap way of changing pitch. Negative values will play the sample backwards!", 237 | ), 238 | ("f", "squiz", ""), 239 | ("f", "stutterdepth", ""), 240 | ("f", "stuttertime", ""), 241 | ("f", "sustain", ""), 242 | ("f", "timescale", ""), 243 | ("f", "timescalewin", ""), 244 | ("f", "tomdecay", ""), 245 | ( 246 | "s", 247 | "unit", 248 | 'used in conjunction with `speed`, accepts values of "r" (rate, default behavior), "c" (cycles), or "s" (seconds). Using `unit "c"` means `speed` will be interpreted in units of cycles, e.g. `speed "1"` means samples will be stretched to fill a cycle. Using `unit "s"` means the playback speed will be adjusted so that the duration is the number of seconds specified by `speed`.', 249 | ), 250 | ("f", "velocity", ""), 251 | ("f", "vcfegint", ""), 252 | ("f", "vcoegint", ""), 253 | ("f", "voice", ""), 254 | ( 255 | "s", 256 | "vowel", 257 | "formant filter to make things sound like vowels, a pattern of either `a`, `e`, `i`, `o` or `u`. Use a rest (`~`) for no effect.", 258 | ), 259 | ("f", "waveloss", ""), 260 | ("f", "dur", ""), 261 | ("f", "modwheel", ""), 262 | ("f", "expression", ""), 263 | ("f", "sustainpedal", ""), 264 | ( 265 | "f", 266 | "tremolodepth", 267 | "Tremolo Audio DSP effect | params are 'tremolorate' and 'tremolodepth'", 268 | ), 269 | ( 270 | "f", 271 | "tremolorate", 272 | "Tremolo Audio DSP effect | params are 'tremolorate' and 'tremolodepth'", 273 | ), 274 | ( 275 | "f", 276 | "phaserdepth", 277 | "Phaser Audio DSP effect | params are 'phaserrate' and 'phaserdepth'", 278 | ), 279 | ( 280 | "f", 281 | "phaserrate", 282 | "Phaser Audio DSP effect | params are 'phaserrate' and 'phaserdepth'", 283 | ), 284 | ("f", "fshift", "frequency shifter"), 285 | ("f", "fshiftnote", "frequency shifter"), 286 | ("f", "fshiftphase", "frequency shifter"), 287 | ("f", "triode", "tube distortion"), 288 | ("f", "krush", "shape/bass enhancer"), 289 | ("f", "kcutoff", ""), 290 | ("f", "octer", "octaver effect"), 291 | ("f", "octersub", "octaver effect"), 292 | ("f", "octersubsub", "octaver effect"), 293 | ("f", "ring", "ring modulation"), 294 | ("f", "ringf", "ring modulation"), 295 | ("f", "ringdf", "ring modulation"), 296 | ("f", "distort", "noisy fuzzy distortion"), 297 | ("f", "freeze", "Spectral freeze"), 298 | ("f", "xsdelay", ""), 299 | ("f", "tsdelay", ""), 300 | ("f", "real", "Spectral conform"), 301 | ("f", "imag", ""), 302 | ("f", "enhance", "Spectral enhance"), 303 | ("f", "partials", ""), 304 | ("f", "comb", "Spectral comb"), 305 | ("f", "smear", "Spectral smear"), 306 | ("f", "scram", "Spectral scramble"), 307 | ("f", "binshift", "Spectral binshift"), 308 | ("f", "hbrick", "High pass sort of spectral filter"), 309 | ("f", "lbrick", "Low pass sort of spectral filter"), 310 | ("f", "midichan", ""), 311 | ("f", "control", ""), 312 | ("f", "ccn", ""), 313 | ("f", "ccv", ""), 314 | ("f", "polyTouch", ""), 315 | ("f", "midibend", ""), 316 | ("f", "miditouch", ""), 317 | ("f", "ctlNum", ""), 318 | ("f", "frameRate", ""), 319 | ("f", "frames", ""), 320 | ("f", "hours", ""), 321 | ("s", "midicmd", ""), 322 | ("f", "minutes", ""), 323 | ("f", "progNum", ""), 324 | ("f", "seconds", ""), 325 | ("f", "songPtr", ""), 326 | ("f", "uid", ""), 327 | ("f", "val", ""), 328 | ("f", "cps", ""), 329 | ] 330 | 331 | controls = [] 332 | 333 | module_obj = sys.modules[__name__] 334 | 335 | # This had to go in its own function, for weird scoping reasons.. 336 | def make_control(name): 337 | def ctrl(*args): 338 | return sequence(*[reify(arg) for arg in args]).fmap(lambda v: {name: v}) 339 | 340 | def ctrl_pattern(self, *args): 341 | return self >> sequence(*[reify(arg) for arg in args]).fmap(lambda v: {name: v}) 342 | 343 | # setattr(Pattern, name, lambda pat: Pattern(reify(pat).fmap(lambda v: {name: v}).query)) 344 | setattr(module_obj, name, ctrl) 345 | setattr(Pattern, name, ctrl_pattern) 346 | 347 | return ctrl 348 | 349 | 350 | for t, name, desc in generic_params: 351 | make_control(name) 352 | 353 | def create_param(name): 354 | """ Creates a new control function with the given name """ 355 | return make_control(name) 356 | 357 | def create_params(names): 358 | """ Creates a new control functions from the given list of names """ 359 | return [make_control(name) for name in names] 360 | 361 | sound = s 362 | -------------------------------------------------------------------------------- /vortex/euclid.py: -------------------------------------------------------------------------------- 1 | from typing import List 2 | 3 | from .utils import flatten 4 | 5 | 6 | def bjorklund(k: int, n: int, safe=True) -> List[int]: 7 | """Applies Bjorklund's algorithm for generating an euclidean rhythm sequence""" 8 | 9 | if not safe: 10 | if k > n: 11 | raise ValueError("k should be <= n") 12 | if k < 0 or n < 0: 13 | raise ValueError("k and n should be non-negative integers") 14 | 15 | # Instead of throwing exception, make sure `n` and `k are valid by taking 16 | # the absolute value of `n`` and `k % n` respectively. 17 | n = abs(n) 18 | k = abs(k % n) 19 | 20 | if n == 0 or k == 0: 21 | return [] 22 | 23 | bins = [[1] for _ in range(k)] 24 | if n == k: 25 | return flatten(bins) 26 | remainders = [[0] for _ in range(n - k)] 27 | 28 | while len(remainders) > 1: 29 | new_remainders = [] 30 | for i, bin in enumerate(bins): 31 | if not remainders: 32 | new_remainders.append(bin) 33 | else: 34 | bin += remainders.pop(0) 35 | bins[i] = bin 36 | 37 | if new_remainders: 38 | bins = bins[: -len(new_remainders)] 39 | remainders = new_remainders 40 | 41 | return flatten(bins + remainders) 42 | -------------------------------------------------------------------------------- /vortex/gui.py: -------------------------------------------------------------------------------- 1 | import glob 2 | import logging 3 | import os 4 | import sys 5 | import time 6 | 7 | import pkg_resources 8 | from PyQt6.Qsci import * 9 | from PyQt6.QtCore import * 10 | from PyQt6.QtGui import * 11 | from PyQt6.QtWidgets import * 12 | 13 | from vortex import __version__, vortex_dsl 14 | 15 | _logger = logging.getLogger(__name__) 16 | 17 | RES_DIR = pkg_resources.resource_filename("vortex", "res") 18 | FONTS_DIR = os.path.join(RES_DIR, "fonts") 19 | HIGHLIGHT_INDICATOR_ID = 0 20 | 21 | DEFAULT_FONT_FAMILY = "Fira Code" 22 | DEFAULT_CODE = r"""# this is an example code 23 | 24 | # some block 25 | 26 | ## 27 | # another block 28 | # 29 | 30 | p("test", s(stack("gabba*4", "cp*3").every(3, fast(2))) 31 | >> speed("2 3") 32 | >> room(0.5) 33 | >> size(0.8) 34 | ) 35 | 36 | ## 37 | # equivalent block 38 | # 39 | 40 | d["test"] = s(stack("gabba*4", "cp*3").every(3, fast(2))) 41 | .speed("2 3") 42 | .room(0.5) 43 | .size(0.8) 44 | 45 | 46 | hush() 47 | 48 | """.replace( 49 | "\n", "\r\n" 50 | ) 51 | 52 | 53 | class HighlightLines(QRunnable): 54 | def __init__(self, editor, range, interval=0.1): 55 | super().__init__() 56 | self.editor = editor 57 | self.range = range 58 | self.interval = interval 59 | 60 | def run(self): 61 | start, end = self.range 62 | editor = self.editor 63 | 64 | line, index = editor.getCursorPosition() 65 | editor.setSelection(start, 0, end, 0) 66 | editor.setSelectionBackgroundColor(QColor("#ff00ff00")) 67 | editor.setSelectionForegroundColor(QColor("#ff000000")) 68 | 69 | _logger.info("Wait") 70 | time.sleep(self.interval) 71 | 72 | # TODO: Should clear from 0 to end of document, just in case... 73 | # editor.clearIndicatorRange(start, 0, end, 0, HIGHLIGHT_INDICATOR_ID) 74 | # editor.setCursorPosition(line, index) 75 | editor.resetSelectionBackgroundColor() 76 | editor.resetSelectionForegroundColor() 77 | 78 | _logger.info("Done") 79 | 80 | 81 | class VortexMainWindow(QMainWindow): 82 | def __init__(self, dsl_module): 83 | super(VortexMainWindow, self).__init__() 84 | 85 | self._dsl_module = dsl_module 86 | 87 | # Define the geometry of the main window 88 | # self.setGeometry(400, 100, 800, 600) 89 | self.setFixedSize(1280, 800) 90 | self.setWindowTitle(f"Vortex {__version__}") 91 | 92 | # Create frame and layout 93 | self._frame = QFrame(self) 94 | self._frame.setStyleSheet("QWidget { background-color: #ffeaeaea }") 95 | self._layout = QVBoxLayout() 96 | self._frame.setLayout(self._layout) 97 | self.setCentralWidget(self._frame) 98 | 99 | self._editorFont = QFont() 100 | self._editorFont.setPointSize(16) 101 | self._editorFont.setFamily(DEFAULT_FONT_FAMILY) 102 | 103 | # Create and configure Editor 104 | self._editor = QsciScintilla() 105 | self._editor.setText(DEFAULT_CODE) 106 | self._editor.setUtf8(True) 107 | self._editor.setIndentationsUseTabs(False) 108 | self._editor.setAutoIndent(True) 109 | self._editor.setTabIndents(True) 110 | self._editor.setTabWidth(4) 111 | self._editor.setIndentationGuides(True) 112 | self._editor.setCaretLineVisible(True) 113 | self._editor.setCaretLineBackgroundColor(QColor("#1fff0000")) 114 | self._editor.setCaretWidth(3) 115 | self._editor.setMarginType(0, QsciScintilla.MarginType.NumberMargin) 116 | self._editor.setMarginWidth(0, "000") 117 | self._editor.setMarginsForegroundColor(QColor("#ff888888")) 118 | 119 | # Create Python Lexer 120 | self._lexer = QsciLexerPython(self._editor) 121 | self._lexer.setFont(self._editorFont) 122 | self._editor.setLexer(self._lexer) 123 | 124 | self._editor.indicatorDefine( 125 | QsciScintilla.IndicatorStyle.FullBoxIndicator, HIGHLIGHT_INDICATOR_ID 126 | ) 127 | 128 | # Commands and shortcuts 129 | commands = self._editor.standardCommands() 130 | command = commands.boundTo(Qt.KeyboardModifier.ControlModifier.value | Qt.Key.Key_Return.value) 131 | # Clear the default 132 | if command is not None: 133 | command.setKey(0) 134 | shortcut = QShortcut(Qt.KeyboardModifier.ControlModifier.value | Qt.Key.Key_Return.value, self._editor) 135 | shortcut.activated.connect(self.evaluate_block) 136 | 137 | # Add editor to layout 138 | self._layout.addWidget(self._editor) 139 | 140 | self.show() 141 | 142 | def evaluate_block(self): 143 | code, (start, end) = self.get_current_block() 144 | if code: 145 | _logger.info(f"Eval: '{code}'") 146 | try: 147 | exec(code, vars(self._dsl_module)) 148 | except (TypeError, AttributeError) as e: 149 | _logger.info("error: %s", str(e)) 150 | # self.highlight_block(start, end) 151 | 152 | def get_current_block(self): 153 | text = self._editor.text() 154 | lines = text.split("\n") 155 | line, _ = self._editor.getCursorPosition() 156 | if not lines[line].strip(): 157 | return "", (line, line) 158 | start_line = line 159 | for i in reversed(range(0, line)): 160 | if not lines[i].strip(): 161 | start_line = i + 1 162 | break 163 | end_line = line 164 | for i in range(line, len(lines)): 165 | if not lines[i].strip(): 166 | end_line = i 167 | break 168 | _logger.debug("Block between lines %d and %d", start_line, end_line) 169 | block = "\n".join(lines[start_line : end_line + 1]) 170 | return block, (start_line, end_line) 171 | 172 | def highlight_block(self, start_line, end_line): 173 | pool = QThreadPool.globalInstance() 174 | runnable = HighlightLines(self._editor, (start_line, end_line)) 175 | pool.start(runnable) 176 | 177 | 178 | def load_fonts(): 179 | font_files = glob.glob(os.path.join(FONTS_DIR, "*")) 180 | for font_file in font_files: 181 | font = QFontDatabase.addApplicationFont(font_file) 182 | if font == -1: 183 | _logger.warn("Failed to load font %s", font_file) 184 | 185 | 186 | def start_gui(): 187 | app = QApplication(sys.argv) 188 | QApplication.setStyle(QStyleFactory.create("Fusion")) 189 | 190 | load_fonts() 191 | 192 | with vortex_dsl() as module: 193 | window = VortexMainWindow(dsl_module=module) 194 | app.exec() 195 | -------------------------------------------------------------------------------- /vortex/mini/__init__.py: -------------------------------------------------------------------------------- 1 | import pprint 2 | 3 | from vortex.mini.grammar import grammar 4 | from vortex.mini.interpreter import MiniInterpreter, MiniVisitor 5 | 6 | visitor = MiniVisitor() 7 | interpreter = MiniInterpreter() 8 | 9 | 10 | def parse_mini(code): 11 | raw_ast = grammar.parse(code) 12 | return visitor.visit(raw_ast) 13 | 14 | 15 | def mini(code, print_ast=False): 16 | ast = parse_mini(code) 17 | if print_ast: 18 | pprint.pp(ast) 19 | return interpreter.eval(ast) 20 | -------------------------------------------------------------------------------- /vortex/mini/grammar.py: -------------------------------------------------------------------------------- 1 | """ 2 | Mini-notation grammar for Vortex. 3 | 4 | Grammar is defined using the PEG parsing library `parsimonious`. 5 | 6 | Given the set of rules and definitions (grammar) defined in this file, calling 7 | `grammar.parse(mn)` generates an abstract syntax tree (AST) for a given input 8 | mini-notation string named `mn`. 9 | 10 | Printing the tree object shows the generated ASTs. e.g.: 11 | 12 | ``` 13 | tree = grammar.parse("bd(3, 8) cp") 14 | ``` 15 | 16 | yields the following (truncated) AST, which can be pretty-printed with: 17 | 18 | ``` 19 | print(tree.prettily()) 20 | ``` 21 | 22 | ``` 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | ... 32 | 33 | 34 | 35 | 36 | 37 | 38 | ``` 39 | 40 | The parsimonious README (https://github.com/erikrose/parsimonious) was all I 41 | needed to get started writing a 'port' of the TidalCycles mini-notation grammar 42 | for Vortex. 43 | 44 | The strudel PEG grammar written in pegjs by Felix Roos was a valuable starting 45 | point, and many ideas were taken from there. 46 | https://github.com/tidalcycles/strudel/blob/main/packages/mini/krill.pegjs 47 | 48 | Reach out on the TidalCycles discord or club.tidalcycles.org if you have any 49 | bugs, optimizations, or questions. 50 | 51 | -Tyler 52 | 53 | """ 54 | 55 | from parsimonious import Grammar 56 | 57 | grammar = Grammar( 58 | r""" 59 | root = ws? sequence ws? 60 | 61 | ## 62 | # Sequences 63 | # 64 | # A Sequence is a white-space separated collection of 2 or more elements 65 | # like "bd bd" or "[bd bd] [bd bd]". Underscores (continuation symbol) can 66 | # be part of a sequence but cannot be the first element. 67 | sequence = group (ws !'|' '.' ws group)* (ws? '|' ws? sequence)* 68 | group = element (ws !'.' element)* 69 | 70 | # An Element is an item of a Sequence, it can be a simple Term, or another 71 | # subsequence: Polymeters (braces), Polyrhythms (square brackets) or one-cycle 72 | # polymeter (angle brackets) 73 | element = element_value euclid_modifier? modifiers (ws '_')* 74 | element_value = term / polyrhythm_subseq / polymeter_subseq / polymeter1_subseq 75 | 76 | ## 77 | # Subsequences 78 | # 79 | polyrhythm_subseq = '[' ws? subseq_body ws? ']' 80 | polymeter_subseq = '{' ws? subseq_body ws? '}' polymeter_steps? 81 | polymeter1_subseq = '<' ws? subseq_body ws? '>' 82 | polymeter_steps = '%' number 83 | subseq_body = sequence (ws? ',' ws? sequence)* 84 | 85 | ## 86 | # Terms 87 | # 88 | term = number / word_with_index / rest 89 | word_with_index = word index? 90 | index = ':' number 91 | 92 | ## 93 | # Euclid modifier 94 | # 95 | euclid_modifier = '(' ws? sequence ws? ',' ws? sequence euclid_rotation_param? ws? ')' 96 | euclid_rotation_param = ws? ',' ws? sequence 97 | 98 | ## 99 | # Term modifiers 100 | # 101 | modifiers = modifier* 102 | modifier = fast / slow / repeat / degrade / weight 103 | fast = '*' element 104 | slow = '/' element 105 | repeat = (repeatn / repeat1)+ 106 | repeatn = '!' !'!' pos_integer 107 | repeat1 = '!' 108 | degrade = degrader / degraden / degrade1 109 | degrader = '?' !'?' pos_real 110 | degraden = '?' !'?' !pos_real pos_integer 111 | degrade1 = '?' 112 | weight = '@' number 113 | 114 | ## 115 | # Primitives 116 | # 117 | # A primitive is a simple token like a word (string) or a number (real or 118 | # integer). 119 | word = ~"[-\w]+" 120 | number = real / integer 121 | real = integer '.' pos_integer? 122 | pos_real = pos_integer '.' pos_integer? 123 | integer = minus? pos_integer 124 | pos_integer = !minus ~"[0-9]+" 125 | rest = '~' 126 | 127 | ## Misc 128 | minus = '-' 129 | ws = ~"\s+" 130 | """ 131 | ) 132 | -------------------------------------------------------------------------------- /vortex/mini/interpreter.py: -------------------------------------------------------------------------------- 1 | from fractions import Fraction 2 | 3 | from parsimonious import NodeVisitor 4 | from parsimonious.nodes import Node 5 | 6 | from vortex.control import n, s 7 | from vortex.pattern import pure # polymeter, 8 | from vortex.pattern import ( 9 | choose_cycles, 10 | id, 11 | polyrhythm, 12 | sequence, 13 | silence, 14 | stack, 15 | timecat, 16 | ) 17 | from vortex.utils import flatten 18 | 19 | 20 | class MiniVisitor(NodeVisitor): 21 | def visit_root(self, _node, children): 22 | _, sequence, _ = children 23 | return sequence 24 | 25 | def visit_sequence(self, _node, children): 26 | group, other_groups, other_seqs = children 27 | if isinstance(other_groups, Node): 28 | other_groups = [] 29 | if isinstance(other_seqs, Node): 30 | other_seqs = [] 31 | other_groups = [e[4] for e in other_groups] 32 | other_seqs = [e[3] for e in other_seqs] 33 | if other_groups: 34 | # Workaround: Re-build AST nodes as if it were a polyrhythm ("a b . 35 | # c" == "[a b] [c]") 36 | group = dict( 37 | type="sequence", 38 | elements=[ 39 | dict( 40 | type="element", 41 | value=dict(type="polyrhythm", seqs=[group]), 42 | modifiers=[], 43 | ), 44 | *[ 45 | dict( 46 | type="element", 47 | value=dict(type="polyrhythm", seqs=[g]), 48 | modifiers=[], 49 | ) 50 | for g in other_groups 51 | ], 52 | ], 53 | ) 54 | if other_seqs: 55 | return dict(type="random_sequence", elements=[group, *other_seqs]) 56 | return group 57 | 58 | def visit_group(self, _node, children): 59 | element, other_elements = children 60 | if isinstance(other_elements, Node): 61 | other_elements = [] 62 | other_elements = [e[2] for e in other_elements] 63 | return dict(type="sequence", elements=[element] + other_elements) 64 | 65 | def visit_element(self, _node, children): 66 | value, euclid_modifier, modifiers, elongate = children 67 | weight = 1 if isinstance(elongate, Node) else len(elongate) + 1 68 | element = dict( 69 | type="element", 70 | value=value, 71 | ) 72 | if not isinstance(euclid_modifier, Node): 73 | element["euclid_modifier"] = euclid_modifier[0] 74 | weight_mod = next( 75 | (m for m in modifiers if m["op"] == "weight"), 76 | dict(type="modifier", op="weight", value=weight), 77 | ) 78 | modifiers = [m for m in modifiers if m["op"] != "weight"] 79 | if weight_mod["value"] != 1: 80 | modifiers.append(weight_mod) 81 | element["modifiers"] = modifiers 82 | return element 83 | 84 | def visit_element_value(self, _node, children): 85 | return children[0] 86 | 87 | def visit_polyrhythm_subseq(self, _node, children): 88 | seqs = children[2] 89 | return dict(type="polyrhythm", seqs=seqs) 90 | 91 | def visit_polymeter_subseq(self, _node, children): 92 | seqs = children[2] 93 | steps = children[5] 94 | if isinstance(steps, Node): 95 | steps = 1 96 | else: 97 | steps = steps[0] 98 | return dict(type="polymeter", seqs=seqs, steps=steps) 99 | 100 | def visit_polymeter_steps(self, _node, children): 101 | _, number = children 102 | return number 103 | 104 | def visit_polymeter1_subseq(self, _node, children): 105 | seqs = children[2] 106 | return dict(type="polymeter", seqs=seqs, steps=1) 107 | 108 | def visit_subseq_body(self, _node, children): 109 | # sequence (ws? ',' ws? sequence)* 110 | seq, other_seqs = children 111 | if isinstance(other_seqs, Node): 112 | other_seqs = [] 113 | other_seqs = [s[3] for s in other_seqs] 114 | return [seq] + other_seqs 115 | 116 | ## 117 | # Terms 118 | # 119 | 120 | def visit_term(self, _node, children): 121 | # Workaround to return an AST element "number" for numbers 122 | if not isinstance(children[0], dict): 123 | return dict(type="number", value=children[0]) 124 | return children[0] 125 | 126 | def visit_rest(self, _node, _children): 127 | return dict(type="rest") 128 | 129 | def visit_word_with_index(self, _node, children): 130 | word, index = children 131 | index = 0 if isinstance(index, Node) else index[0] 132 | return dict(type="word", value=word, index=index) 133 | 134 | def visit_index(self, _node, children): 135 | _, number = children 136 | return number 137 | 138 | ## 139 | # Modifiers 140 | # 141 | 142 | def visit_euclid_modifier(self, _node, children): 143 | _, _, k, _, _, _, n, rotation, _, _ = children 144 | mod = dict(type="euclid_modifier", k=k, n=n) 145 | if not isinstance(rotation, Node): 146 | mod["rotation"] = rotation[0] 147 | return mod 148 | 149 | def visit_euclid_rotation_param(self, _node, children): 150 | _, _, _, rotation = children 151 | return rotation 152 | 153 | def visit_modifiers(self, _node, children): 154 | mods = [m for m in children if m["op"] not in ("degrade", "weight")] 155 | 156 | # The degrade modifier (?) does not take into account application order, 157 | # so we merge them into a single modifier. 158 | # There are two kinds of degrade modifiers, depending on its argument: 159 | # 1) "count" (degrade1/degraden) and 2) "value" (degrader). If there is 160 | # at least one "value" argument, the last occurrence takes precedences 161 | # and overwrites other degrade modifiers. Otherwise, we merge all other 162 | # "count" arguments into a single "count" modifier to simplify 163 | # representation. 164 | degrade_mods = [m for m in children if m["op"] == "degrade"] 165 | if degrade_mods: 166 | value_deg_mod = next( 167 | reversed([a for a in degrade_mods if a["value"]["op"] == "value"]), None 168 | ) 169 | count_deg_mods = [a for a in degrade_mods if a["value"]["op"] == "count"] 170 | if value_deg_mod: 171 | mods.append(value_deg_mod) 172 | elif count_deg_mods: 173 | count_deg_mod = count_deg_mods[0].copy() 174 | deg_count = sum([m["value"]["value"] for m in count_deg_mods]) 175 | count_deg_mod["value"]["value"] = deg_count 176 | mods.append(count_deg_mod) 177 | 178 | # The weight modifier (@) can be duplicated, but only the last one is 179 | # used, all others are ignored. 180 | weight_mods = [m for m in children if m["op"] == "weight"] 181 | if weight_mods: 182 | mods.append(weight_mods[-1]) 183 | 184 | return mods 185 | 186 | def visit_modifier(self, _node, children): 187 | return children[0] 188 | 189 | def visit_fast(self, _node, children): 190 | _, number = children 191 | return dict(type="modifier", op="fast", value=number) 192 | 193 | def visit_slow(self, _node, children): 194 | _, number = children 195 | return dict(type="modifier", op="slow", value=number) 196 | 197 | def visit_repeat(self, _node, children): 198 | count = sum(flatten(children)) 199 | return dict(type="modifier", op="repeat", count=count) 200 | 201 | def visit_repeatn(self, _node, children): 202 | _, _, count = children 203 | return count 204 | 205 | def visit_repeat1(self, _node, children): 206 | return 1 207 | 208 | def visit_degrade(self, _node, children): 209 | return dict(type="modifier", op="degrade", value=children[0]) 210 | 211 | def visit_degrader(self, _node, children): 212 | _, _, value = children 213 | return dict(type="degrade_arg", op="value", value=value) 214 | 215 | def visit_degraden(self, _node, children): 216 | _, _, _, count = children 217 | return dict(type="degrade_arg", op="count", value=count) 218 | 219 | def visit_degrade1(self, _node, children): 220 | return dict(type="degrade_arg", op="count", value=1) 221 | 222 | def visit_weight(self, _node, children): 223 | _, number = children 224 | return dict(type="modifier", op="weight", value=number) 225 | 226 | ## 227 | # Primitives 228 | # 229 | 230 | def visit_word(self, node, _children): 231 | return node.text 232 | 233 | def visit_number(self, node, children): 234 | return children[0] 235 | 236 | def visit_real(self, node, _children): 237 | return float(node.text) 238 | 239 | def visit_integer(self, node, _children): 240 | return int(node.text) 241 | 242 | def visit_pos_integer(self, node, _children): 243 | return int(node.text) 244 | 245 | def visit_pos_real(self, node, _children): 246 | return float(node.text) 247 | 248 | ## 249 | # Others 250 | # 251 | 252 | def visit_ws(self, _node, _children): 253 | return 254 | 255 | def generic_visit(self, node, children): 256 | return children or node 257 | 258 | 259 | class MiniInterpreter: 260 | def eval(self, node): 261 | node_type = node["type"] 262 | eval_method = getattr(self, f"eval_{node_type}") 263 | return eval_method(node) 264 | 265 | def eval_sequence(self, node): 266 | return self._eval_sequence_elements(node["elements"]) 267 | 268 | def _eval_sequence_elements(self, elements): 269 | elements = [self.eval(n) for n in elements] 270 | tc_args = [] 271 | # Because each element might have been replicated/repeated, each element 272 | # is actually a list of tuples (weight, pattern, degrade_ratio). 273 | for es in elements: 274 | # We extract the weight and degrade_ratio from the first element (it 275 | # does not matter from which element, all have the same state 276 | # values). 277 | weight = es[0][0] if es else 1 278 | deg_ratio = es[0][2] if es else 0 279 | # Use the length of the replicated element as weight times the 280 | # `weight` modifier (if present). Build a sequence out of the 281 | # replicated elements and degrade by the accumulated degrade ratio. 282 | tc_args.append( 283 | (len(es) * weight, sequence(*[e[1] for e in es]).degrade_by(deg_ratio)) 284 | ) 285 | # Finally use timecat to create a pattern out of this sequence 286 | return timecat(*tc_args) 287 | 288 | def eval_random_sequence(self, node): 289 | seqs = [self.eval(e) for e in node["elements"]] 290 | return choose_cycles(*seqs) 291 | 292 | def eval_polyrhythm(self, node): 293 | return polyrhythm(*[self.eval(seq) for seq in node["seqs"]]) 294 | 295 | def eval_polymeter(self, node): 296 | # FIXME: Is there a better way to do this? It'd be nice to use 297 | # `polymeter()`, but the sequences are already "sequence" patterns, not 298 | # a list of events. We might need to restructure grammar... 299 | 300 | # return polymeter(*[self.eval(seq) for seq in node["seqs"]], steps=node["steps"]) 301 | fast_params = [ 302 | Fraction(node["steps"], len(seq["elements"])) for seq in node["seqs"] 303 | ] 304 | return stack( 305 | *[ 306 | self.eval(seq).fast(fparam) 307 | for seq, fparam in zip(node["seqs"], fast_params) 308 | ] 309 | ) 310 | 311 | def eval_element(self, node): 312 | # Here we collect all modifier functions of an element and reduce them 313 | modifiers = [self.eval(m) for m in node["modifiers"]] 314 | pat = self.eval(node["value"]) 315 | # Apply an euclid modifier if present 316 | if "euclid_modifier" in node: 317 | k, n, rotation = self.eval(node["euclid_modifier"]) 318 | pat = pat.euclid(k, n, rotation) 319 | # The initial value is the tuple of 3 elements (see visit_modifier): a 320 | # default weight of 1, a "pure" pattern of the elements value and 321 | # degrade ratio of 0 (no degradation). It is a list of tuples, because 322 | # modifiers return a list of tuples (there might be repeat modifiers 323 | # that return multiple patterns). 324 | values = [(1, pat, 0)] 325 | for modifier in modifiers: 326 | # We eventually flatten list of lists into a single list 327 | values = flatten([modifier(v) for v in values]) 328 | return values 329 | 330 | def eval_euclid_modifier(self, node): 331 | k = self.eval(node["k"]) 332 | n = self.eval(node["n"]) 333 | rotation = self.eval(node["rotation"]) if "rotation" in node else pure(0) 334 | return k, n, rotation 335 | 336 | def eval_modifier(self, node): 337 | # This is a bit ugly, but we maintain the "state" of modifiers by returning 338 | # a tuple of 3 elements: (weight, pattern, degrade_ratio), where: 339 | # 340 | # * `weight` is the current weight value for timecat 341 | # * `pattern` is the modified pattern 342 | # * `degrade_ratio` is the accumulated degrade ratio. 343 | # 344 | # The return value of the modifier functions is a list of Patterns, 345 | # because the repeat modifier might return multiple patterns of the 346 | # element, so we generalize it into a list for all modifiers. 347 | if node["op"] == "degrade": 348 | # Use the formula `n / (n + 1)` to increase the degrade ratio 349 | # "linearly". We expect there is a single degrade modifier 350 | # (guaranteed by the AST), so we can use the `count` as the final 351 | # count of degrade occurrences. 352 | arg = node["value"] 353 | if arg["op"] == "count": 354 | return lambda w_p: [ 355 | (w_p[0], w_p[1], Fraction(arg["value"], arg["value"] + 1)) 356 | ] 357 | elif arg["op"] == "value": 358 | return lambda w_p: [(w_p[0], w_p[1], arg["value"])] 359 | elif node["op"] == "repeat": 360 | return lambda w_p: [w_p] * (node["count"] + 1) 361 | elif node["op"] == "fast": 362 | param = self._eval_sequence_elements([node["value"]]) 363 | return lambda w_p: [(w_p[0], w_p[1].fast(param), w_p[2])] 364 | elif node["op"] == "slow": 365 | param = self._eval_sequence_elements([node["value"]]) 366 | return lambda w_p: [(w_p[0], w_p[1].slow(param), w_p[2])] 367 | elif node["op"] == "weight": 368 | # Overwrite current weight state value with the new weight from this 369 | # modifier. The AST will only contain a single "weight" modifier, 370 | # so there is no issue with replacing it. 371 | return lambda w_p: [(node["value"], w_p[1], w_p[2])] 372 | return id 373 | 374 | def eval_number(self, node): 375 | return pure(node["value"]) 376 | 377 | def eval_word(self, node): 378 | if node["index"]: 379 | return s(node["value"]) << n(node["index"]) 380 | else: 381 | return pure(node["value"]) 382 | 383 | def eval_rest(self, node): 384 | return silence() 385 | -------------------------------------------------------------------------------- /vortex/repl.py: -------------------------------------------------------------------------------- 1 | from IPython.terminal.embed import InteractiveShellEmbed 2 | 3 | from vortex import * 4 | from vortex import __version__ 5 | 6 | 7 | def start_repl(*kwargs): 8 | """Start the interactive shell inside a Vortex environment""" 9 | with vortex_dsl() as module: 10 | ipshell = InteractiveShellEmbed(banner1=f"Vortex REPL, version {__version__}") 11 | ipshell(module=module) 12 | -------------------------------------------------------------------------------- /vortex/res/fonts/FiraCode-Bold.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/FiraCode-Bold.ttf -------------------------------------------------------------------------------- /vortex/res/fonts/FiraCode-Light.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/FiraCode-Light.ttf -------------------------------------------------------------------------------- /vortex/res/fonts/FiraCode-Medium.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/FiraCode-Medium.ttf -------------------------------------------------------------------------------- /vortex/res/fonts/FiraCode-Regular.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/FiraCode-Regular.ttf -------------------------------------------------------------------------------- /vortex/res/fonts/FiraCode-Retina.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/FiraCode-Retina.ttf -------------------------------------------------------------------------------- /vortex/res/fonts/FiraCode-SemiBold.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/FiraCode-SemiBold.ttf -------------------------------------------------------------------------------- /vortex/res/fonts/iosevka-term-regular.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tidalcycles/vortex/762200a75044eabf036ca3469810033931083fc6/vortex/res/fonts/iosevka-term-regular.ttf -------------------------------------------------------------------------------- /vortex/stream.py: -------------------------------------------------------------------------------- 1 | from __future__ import annotations 2 | 3 | import logging 4 | import math 5 | import threading 6 | import time 7 | from abc import ABC 8 | from fractions import Fraction 9 | from typing import Any, Dict 10 | 11 | import liblo 12 | import link 13 | 14 | from vortex import * 15 | 16 | _logger = logging.getLogger(__name__) 17 | 18 | 19 | class LinkClock: 20 | """ 21 | This class handles synchronization between different devices using the Link 22 | protocol. 23 | 24 | You can subscribe other objects (i.e. Streams), which will be notified on 25 | each clock tick. It expects that subscribers define a `notify_tick` method. 26 | 27 | Parameters 28 | ---------- 29 | bpm: float 30 | beats per minute (default: 120) 31 | 32 | """ 33 | 34 | def __init__(self, bpm=120): 35 | self.bpm = bpm 36 | 37 | self._subscribers = [] 38 | self._link = link.Link(bpm) 39 | self._is_running = False 40 | self._mutex = threading.Lock() 41 | 42 | def subscribe(self, subscriber): 43 | """Subscribe an object to tick notifications""" 44 | with self._mutex: 45 | self._subscribers.append(subscriber) 46 | 47 | def unsubscribe(self, subscriber): 48 | """Unsubscribe from tick notifications""" 49 | with self._mutex: 50 | self._subscribers.remove(subscriber) 51 | 52 | def start(self): 53 | """Start the clock""" 54 | with self._mutex: 55 | if self._is_running: 56 | return 57 | self._is_running = True 58 | self._create_notify_thread() 59 | 60 | def stop(self): 61 | """Stop the clock""" 62 | with self._mutex: 63 | self._is_running = False 64 | # Wait until thread has stopped 65 | # Will block until (at least) the next start of frame 66 | self._notify_thread.join() 67 | 68 | @property 69 | def is_playing(self): 70 | """Returns whether clock is currently running""" 71 | return self._is_running 72 | 73 | def _create_notify_thread(self): 74 | self._notify_thread = threading.Thread(target=self._notify_thread_target) 75 | self._notify_thread.start() 76 | 77 | def _notify_thread_target(self): 78 | _logger.info("Link enabled") 79 | self._link.enabled = True 80 | self._link.startStopSyncEnabled = True 81 | 82 | start = self._link.clock().micros() 83 | mill = 1000000 84 | start_beat = self._link.captureSessionState().beatAtTime(start, 4) 85 | _logger.info("Start beat: %f", start_beat) 86 | 87 | ticks = 0 88 | 89 | # FIXME rate, bpc and latency should be constructor parameters 90 | rate = 1 / 20 91 | frame = rate * mill 92 | bpc = 4 93 | 94 | while self._is_running: 95 | ticks = ticks + 1 96 | 97 | logical_now = math.floor(start + (ticks * frame)) 98 | logical_next = math.floor(start + ((ticks + 1) * frame)) 99 | 100 | now = self._link.clock().micros() 101 | 102 | # wait until start of next frame 103 | wait = (logical_now - now) / mill 104 | if wait > 0: 105 | time.sleep(wait) 106 | 107 | if not self._is_running: 108 | break 109 | 110 | s = self._link.captureSessionState() 111 | cps = (s.tempo() / bpc) / 60 112 | cycle_from = s.beatAtTime(logical_now, 0) / bpc 113 | cycle_to = s.beatAtTime(logical_next, 0) / bpc 114 | 115 | try: 116 | for sub in self._subscribers: 117 | sub.notify_tick((cycle_from, cycle_to), s, cps, bpc, mill, now) 118 | except: 119 | pass 120 | 121 | # sys.stdout.write( 122 | # "cps %.2f | playing %s | cycle %.2f\r" 123 | # % (cps, s.isPlaying(), cycle_from) 124 | # ) 125 | 126 | # sys.stdout.flush() 127 | 128 | self._link.enabled = False 129 | _logger.info("Link disabled") 130 | return 131 | 132 | 133 | class BaseStream(ABC): 134 | """ 135 | A class for playing control pattern events 136 | 137 | It should be subscribed to a LinkClock instance. 138 | 139 | Parameters 140 | ---------- 141 | name: Optional[str] 142 | Name of the stream instance 143 | 144 | """ 145 | 146 | def __init__(self, name: str = None): 147 | self.name = name 148 | self.pattern = None 149 | 150 | def notify_tick(self, cycle, s, cps, bpc, mill, now): 151 | """Called by a Clock every time it ticks, when subscribed to it""" 152 | if not self.pattern: 153 | return 154 | 155 | cycle_from, cycle_to = cycle 156 | es = self.pattern.onsets_only().query(TimeSpan(cycle_from, cycle_to)) 157 | if len(es): 158 | _logger.debug("%s", [e.value for e in es]) 159 | 160 | for e in es: 161 | cycle_on = e.whole.begin 162 | cycle_off = e.whole.end 163 | 164 | link_on = s.timeAtBeat(cycle_on * bpc, 0) 165 | link_off = s.timeAtBeat(cycle_off * bpc, 0) 166 | delta_secs = (link_off - link_on) / mill 167 | 168 | # Maybe better to only calc this once?? 169 | # + it would be better to send link time to supercollider.. 170 | link_secs = now / mill 171 | liblo_diff = liblo.time() - link_secs 172 | nudge = e.value.get("nudge", 0) 173 | ts = (link_on / mill) + liblo_diff + self.latency + nudge 174 | 175 | # print("liblo time %f link_time %f link_on %f cycle_on %f liblo_diff %f ts %f" % (liblo.time(), link_secs, link_on, cycle_on, liblo_diff, ts)) 176 | self.notify_event( 177 | e.value, 178 | timestamp=ts, 179 | cps=float(cps), 180 | cycle=float(cycle_on), 181 | delta=float(delta_secs), 182 | ) 183 | 184 | def notify_event( 185 | self, 186 | event: Dict[str, Any], 187 | timestamp: float, 188 | cps: float, 189 | cycle: float, 190 | delta: float, 191 | ): 192 | """Called by `notify_tick` with the event and timestamp that should be played""" 193 | raise NotImplementedError 194 | 195 | def __repr__(self): 196 | pattern_repr = " \n" + repr(self.pattern) if self.pattern else "" 197 | return f"<{self.__class__.__name__} {repr(self.name)}{pattern_repr}>" 198 | 199 | 200 | class SuperDirtStream(BaseStream): 201 | """ 202 | This Stream class sends control pattern messages to SuperDirt via OSC 203 | 204 | Parameters 205 | ---------- 206 | port: int 207 | The port where SuperDirt is listening 208 | latency: float 209 | SuperDirt latency 210 | 211 | """ 212 | 213 | def __init__(self, port=57120, latency=0.2, *args, **kwargs): 214 | super().__init__(*args, **kwargs) 215 | 216 | self.latency = latency 217 | 218 | self._port = port 219 | self._address = liblo.Address(port) 220 | 221 | @property 222 | def port(self): 223 | """SuperDirt listening port""" 224 | return self._port 225 | 226 | def notify_event( 227 | self, 228 | event: Dict[str, Any], 229 | timestamp: float, 230 | cps: float, 231 | cycle: float, 232 | delta: float, 233 | ): 234 | msg = [] 235 | for key, val in event.items(): 236 | if isinstance(val, Fraction): 237 | val = float(val) 238 | msg.append(key) 239 | msg.append(val) 240 | msg.extend(["cps", cps, "cycle", cycle, "delta", delta]) 241 | _logger.info("%s", msg) 242 | 243 | # liblo.send(superdirt, "/dirt/play", *msg) 244 | bundle = liblo.Bundle(timestamp, liblo.Message("/dirt/play", *msg)) 245 | liblo.send(self._address, bundle) 246 | 247 | def setup_logging(loglevel): 248 | """Setup basic logging 249 | 250 | Args: 251 | loglevel (int): minimum loglevel for emitting messages 252 | """ 253 | logformat = "[%(asctime)s] %(levelname)s:%(name)s:%(message)s" 254 | logging.basicConfig( 255 | level=loglevel, stream=sys.stdout, format=logformat, datefmt="%Y-%m-%d %H:%M:%S" 256 | ) 257 | 258 | if __name__ == "__main__": 259 | setup_logging(logging.DEBUG) 260 | clock = LinkClock(120) 261 | clock.start() 262 | 263 | stream = SuperDirtStream() 264 | clock.subscribe(stream) 265 | 266 | logging.info(">> Wait a sec") 267 | time.sleep(1) 268 | 269 | logging.info(">> Set pattern and let it play for 2 seconds") 270 | stream.pattern = s(stack("gabba*4", "cp*3")).speed("2 3") >> room(0.5).size(0.8) 271 | time.sleep(2) 272 | 273 | logging.info(">> Stop the clock momentarily") 274 | clock.stop() 275 | 276 | logging.info(">> Now, wait 3 secs") 277 | time.sleep(3) 278 | 279 | logging.info(">> Start again...") 280 | clock.start() 281 | 282 | time.sleep(2) 283 | 284 | logging.info(">> Stop the clock") 285 | clock.stop() 286 | logging.info(">> Done") 287 | -------------------------------------------------------------------------------- /vortex/utils.py: -------------------------------------------------------------------------------- 1 | import operator 2 | from fractions import Fraction 3 | from functools import partial, reduce, wraps 4 | 5 | 6 | def flatten(lst) -> list: 7 | """Flattens a list of lists""" 8 | return [item for sublist in lst for item in sublist] 9 | 10 | 11 | def remove_nones(lst) -> list: 12 | """Removes 'None' values from given list""" 13 | return filter(lambda x: x != None, lst) 14 | 15 | 16 | def id(x): 17 | """Identity function""" 18 | return x 19 | 20 | 21 | def merge_dicts(a, b, op=operator.add): 22 | return dict(a.items() + b.items() + [(k, op(a[k], b[k])) for k in set(b) & set(a)]) 23 | 24 | 25 | def rotate_left(lst, n): 26 | """Rotate an array `n` elements to the left""" 27 | return lst[n:] + lst[:n] 28 | 29 | 30 | def partial_function(f): 31 | """Decorator for functions to support partial application. When not given enough 32 | arguments, a decoracted function will return a new function for the remaining 33 | arguments""" 34 | 35 | def wrapper(*args): 36 | try: 37 | return f(*args) 38 | except (TypeError) as e: 39 | return partial(f, *args) 40 | 41 | return wrapper 42 | 43 | 44 | def show_fraction(frac): 45 | if frac == None: 46 | return "None" 47 | 48 | if frac.denominator == 1: 49 | return str(frac.numerator) 50 | 51 | lookup = { 52 | Fraction(1, 2): "½", 53 | Fraction(1, 3): "⅓", 54 | Fraction(2, 3): "⅔", 55 | Fraction(1, 4): "¼", 56 | Fraction(3, 4): "¾", 57 | Fraction(1, 5): "⅕", 58 | Fraction(2, 5): "⅖", 59 | Fraction(3, 5): "⅗", 60 | Fraction(4, 5): "⅘", 61 | Fraction(1, 6): "⅙", 62 | Fraction(5, 6): "⅚", 63 | Fraction(1, 7): "⅐", 64 | Fraction(1, 8): "⅛", 65 | Fraction(3, 8): "⅜", 66 | Fraction(5, 8): "⅝", 67 | Fraction(7, 8): "⅞", 68 | Fraction(1, 9): "⅑", 69 | Fraction(1, 10): "⅒", 70 | } 71 | if frac in lookup: 72 | result = lookup[frac] 73 | else: 74 | result = "(%d/%d)" % (frac.numerator, frac.denominator) 75 | return result 76 | 77 | 78 | def curry(f): 79 | @wraps(f) 80 | def _(arg): 81 | try: 82 | return f(arg) 83 | except TypeError: 84 | return curry(wraps(f)(partial(f, arg))) 85 | 86 | return _ 87 | 88 | 89 | def uncurry(f): 90 | @wraps(f) 91 | def _(*args): 92 | return reduce(lambda x, y: x(y), args, f) 93 | 94 | return _ 95 | -------------------------------------------------------------------------------- /vortex/vortex.py: -------------------------------------------------------------------------------- 1 | """ 2 | Experiment: porting Tidalcycles to Python 3.x. 3 | """ 4 | 5 | from __future__ import annotations 6 | 7 | import logging 8 | 9 | from vortex.pattern import * 10 | 11 | 12 | def pattern_pretty_printing(pattern: Pattern, query_span: TimeSpan) -> None: 13 | """Better formatting for logging.debuging Tidal Patterns""" 14 | for event in pattern.query(query_span): 15 | 16 | logging.debug(event) 17 | 18 | 19 | if __name__ == "__main__": 20 | # Simple patterns 21 | a = pure("hello") 22 | b = pure("world") 23 | c = fastcat(a, b) 24 | d = stack(a, b) 25 | 26 | # printing the pattern 27 | logging.debug("\n== TEST PATTERN ==\n") 28 | logging.debug('Like: "hello world" (over two cycles)') 29 | pattern_pretty_printing(pattern=c, query_span=TimeSpan(0, 2)) 30 | 31 | # printing the pattern with fast 32 | logging.debug("\n== SAME BUT FASTER==\n") 33 | logging.debug('Like: fast 4 "hello world"') 34 | pattern_pretty_printing(pattern=c._fast(2), query_span=TimeSpan(0, 1)) 35 | 36 | # printing the pattern with patterned fast 37 | logging.debug("\n== PATTERNS OF FAST OF PATTERNS==\n") 38 | logging.debug('Like: fast "2 4" "hello world"') 39 | pattern_pretty_printing(pattern=c.fast(fastcat(2, 4)), query_span=TimeSpan(0, 1)) 40 | 41 | # printing the pattern with stack 42 | logging.debug("\n== STACK ==\n") 43 | pattern_pretty_printing(pattern=d, query_span=TimeSpan(0, 1)) 44 | 45 | # printing the pattern with late 46 | logging.debug("\n== LATE ==\n") 47 | pattern_pretty_printing(pattern=c.late(0.5), query_span=TimeSpan(0, 1)) 48 | 49 | # Apply pattern of values to a pattern of functions 50 | logging.debug("\n== APPLICATIVE ==\n") 51 | x = fastcat(pure(lambda x: x + 1), pure(lambda x: x + 4)) 52 | y = fastcat(3, 4, 5) 53 | z = x.app(y) 54 | pattern_pretty_printing(pattern=z, query_span=TimeSpan(0, 1)) 55 | 56 | # Add number patterns together 57 | logging.debug("\n== ADDITION ==\n") 58 | numbers = fastcat(*[pure(v) for v in [2, 3, 4, 5]]) 59 | more_numbers = fastcat(pure(10), pure(100)) 60 | pattern_pretty_printing(pattern=numbers + more_numbers, query_span=TimeSpan(0, 1)) 61 | 62 | logging.debug("\n== EMBEDDED SEQUENCES ==\n") 63 | # sequence([0,1,[2, [3, 4]]]) is the same as "[0 1 [2 [3 4]]]" in mininotation 64 | pattern_pretty_printing( 65 | pattern=sequence(0, 1, [2, [3, 4]]), query_span=TimeSpan(0, 1) 66 | ) 67 | 68 | logging.debug("\n== Polyrhythm ==\n") 69 | pattern_pretty_printing( 70 | pattern=polyrhythm([0, 1, 2, 3], [20, 30]), query_span=TimeSpan(0, 1) 71 | ) 72 | 73 | logging.debug("\n== Polyrhythm with fewer steps ==\n") 74 | pattern_pretty_printing( 75 | pattern=polyrhythm([0, 1, 2, 3], [20, 30], steps=2), query_span=TimeSpan(0, 1) 76 | ) 77 | 78 | logging.debug("\n== Polymeter ==\n") 79 | pattern_pretty_printing( 80 | pattern=polymeter([0, 1, 2], [20, 30]), query_span=TimeSpan(0, 1) 81 | ) 82 | 83 | logging.debug("\n== Polymeter with embedded polyrhythm ==\n") 84 | pattern_pretty_printing( 85 | pattern=pm(pr([100, 200, 300, 400], [0, 1]), [20, 30]), 86 | query_span=TimeSpan(0, 1), 87 | ) 88 | 89 | logging.debug("\n== Every with partially applied 'fast' ==\n") 90 | pattern_pretty_printing(pattern=c.every(3, fast(2)), query_span=TimeSpan(0, 1)) 91 | --------------------------------------------------------------------------------