VoxelServer/Laboratory/PerlinWorldGeneratorTest.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Perlin World Generator Test\n",
"---\n",
"this notebook tests the Perlin world generator"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append(\"../ServerCore\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"%pylab ipympl\n",
"\n",
"import matplotlib.image as mpimg\n",
"import scipy.ndimage as ndimage\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import numpy as np\n",
"\n",
"from WorldManager import WorldManager\n",
"from Chunk import Chunk"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* variables:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"n_chunks = 3\n",
"raw_noise_cell_size = 16\n",
"raw_noise_chunk_size = 4\n",
"world_seed = 42"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* create world manager"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"wm = WorldManager(raw_noise_cell_size=raw_noise_cell_size, raw_noise_chunk_size=raw_noise_chunk_size, world_seed=world_seed)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* create world's highmap"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"c = Chunk.CHUNK_SIDELENGTH\n",
"\n",
"height_map = np.zeros(shape=(n_chunks * c, n_chunks * c), dtype=float)\n",
"\n",
"for i in range(n_chunks):\n",
" for j in range(n_chunks):\n",
" height_map[i * c:(i+1)* c, j*c:(j+1)*c] = wm.getPerlinMap(i,j)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* plot height map"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "23dd04daba304f2d9668d861184e7153",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"FigureCanvasNbAgg()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots()\n",
"\n",
"ax.imshow(height_map, cmap='binary')\n",
"ax.set_title(\"stupid interpolated perlin noise map\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* create chunks and fill them with data"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"for x in range(n_chunks):\n",
" for y in range(2):\n",
" for z in range(n_chunks):\n",
" wm.createEmptyChunk(x,y,z)\n",
" wm.applyPerlinToChunk(x,y,z)\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* concatenate to one big array (just for plotting)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"world = np.zeros(shape=(n_chunks * c, 2*c, n_chunks*c), dtype=int)\n",
"\n",
"for x in range(n_chunks):\n",
" for y in range(2):\n",
" for z in range(n_chunks):\n",
" world[x*c:(x+1)*c, y*c:(y+1)*c, z*c:(z+1)*c] = wm.chunks[x][y][z].block_data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* and plot it"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"from mpl_toolkits.mplot3d import Axes3D\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"colors = np.zeros(shape=(n_chunks * c, 2*c, n_chunks*c,3))\n",
"for x,y,z in np.ndindex(world.shape):\n",
" i = y/(c)\n",
" colors[x,y,z,:] = [0,i,1-i]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3010f3d5167449b196314981a687108b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"FigureCanvasNbAgg()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"fig2 = plt.figure()\n",
"ax2 = fig2.gca(projection='3d')\n",
"\n",
"p = ax2.voxels(np.rollaxis(world,2), facecolors=np.rollaxis(colors,2))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}