Python demo: research

This commit is contained in:
Mrna 2025-09-18 19:19:24 +02:00
parent 36919b4bd1
commit e561cc340a
2 changed files with 6 additions and 4 deletions

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@ -4,11 +4,13 @@
- [ ] python - [ ] python
- [x] get jupyter lab running - [x] get jupyter lab running
- [ ] drawing utility - [x] drawing utility
- [ ] interface for pathfinding - [x] interface for pathfinding
- [ ] research methods - [ ] research methods
- [ ] implement methods - [ ] implement methods
- [ ] performance measurement: time/visited nodes
- [ ] finish text on the page - [ ] finish text on the page
- [ ] create a dedicated python script
- [ ] C++ - [ ] C++
- [ ] re-use 2D game engine - [ ] re-use 2D game engine
- [ ] add mouse-click movement (direct, no pathfinding, player always selected) - [ ] add mouse-click movement (direct, no pathfinding, player always selected)

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@ -24,7 +24,7 @@
{ {
"id": "16f8fedb-ac10-450c-b5c7-f820a985902d", "id": "16f8fedb-ac10-450c-b5c7-f820a985902d",
"cell_type": "markdown", "cell_type": "markdown",
"source": "# Pathfinding demo", "source": "# Pathfinding demo\n\n## Optimal path finding\n\nNon-exhaustive list of methods follows. \n\n$V$ is the set of all vertices; $|V|$ is the size of the set\n\n1. [Bellman-Ford algorithm](https://en.wikipedia.org/wiki/Bellman%E2%80%93Ford_algorithm)\n - exhaustive method\n - $O(|V|*|E|)$\n2. Dijkstra\n3. A*",
"metadata": { "metadata": {
"tags": [], "tags": [],
"slideshow": { "slideshow": {
@ -36,7 +36,7 @@
{ {
"id": "fbdf9d2c-d050-4744-b559-abc71e550725", "id": "fbdf9d2c-d050-4744-b559-abc71e550725",
"cell_type": "code", "cell_type": "code",
"source": "#\n# Imports\n#\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom typing import Protocol\nfrom dataclasses import dataclass", "source": "#\n# Imports\n#\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom typing import Protocol",
"metadata": { "metadata": {
"trusted": true, "trusted": true,
"tags": [], "tags": [],