{ "cells": [ { "cell_type": "code", "execution_count": 7, "source": [ "import json\r\n", "\r\n", "# create a new scene graph\r\n", "def new_scene(name):\r\n", " # create empty neutrino data\r\n", " data = {\r\n", " \"meta\": {\r\n", " \"name\": (\"name\", name),\r\n", " \"scale\": (\"float\", 1.0),\r\n", " \"asset_path\": (\"path\", \"./\"),\r\n", " },\r\n", " \"graph\": {\r\n", " \"scene\": {},\r\n", " \"assets\": {}\r\n", " },\r\n", " \"internal\": {\r\n", " \"max_object_key\": 0,\r\n", " \"max_cache_key\": 0\r\n", " }\r\n", " }\r\n", "\r\n", " # return that empty data\r\n", " return data\r\n", "\r\n", "# write the data to a JSON file\r\n", "def save_scene(data):\r\n", " # create working copy of the scene data\r\n", " clean_data = data.copy()\r\n", "\r\n", " # get rid of internal data (not to be exported)\r\n", " del clean_data[\"internal\"]\r\n", " \r\n", " filename = data[\"meta\"][\"name\"][1].replace(\" \", \"\") + \".json\"\r\n", " with open(filename, \"w\") as outfile:\r\n", " json.dump(clean_data, outfile, indent = 4)\r\n", "\r\n", "# get a new indexed object key and track it\r\n", "def object_key(data):\r\n", " # get the indexed key\r\n", " key = hex(data[\"internal\"][\"max_object_key\"] + 1)\r\n", "\r\n", " # index the max key\r\n", " data[\"internal\"][\"max_object_key\"] += 1\r\n", "\r\n", " return key\r\n", "\r\n", "# get a new indexed cache key and track it\r\n", "def cache_key(data):\r\n", " # get the indexed key\r\n", " key = hex(data[\"internal\"][\"max_cache_key\"] + 1)\r\n", "\r\n", " # index the max key\r\n", " data[\"internal\"][\"max_cache_key\"] += 1\r\n", "\r\n", " return key\r\n", "\r\n", "# add an asset to the graph\r\n", "def add_asset(data, name, path):\r\n", " asset_data = {\r\n", " \"name\": (\"name\", name),\r\n", " \"file\": (\"path\", path)\r\n", " }\r\n", " \r\n", " # add the asset to the graph\r\n", " data[\"graph\"][\"assets\"][object_key(data)] = (\"asset\", asset_data)\r\n", "\r\n", "# add an object to the scene\r\n", "def spawn_object(data, name, asset):\r\n", " object_data = {\r\n", " \"name\": (\"name\", name),\r\n", " \"asset\": \"\",\r\n", " \"trans\": (\"trans\", [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [1.0, 1.0, 1.0]])\r\n", " }\r\n", "\r\n", " # get an asset key by the provided name\r\n", " for key, value in data[\"graph\"][\"assets\"].items():\r\n", " if value[1][\"name\"][1] == asset:\r\n", " object_data[\"asset\"] = f\"*{key}\"\r\n", "\r\n", " # add the object to the scene\r\n", " data[\"graph\"][\"scene\"][object_key(data)] = (\"object\", object_data)" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 8, "source": [ "# cache the scene\r\n", "def cache_scene(data):\r\n", " # add the cache object to the scene data\r\n", " data[\"cache\"] = {}\r\n", "\r\n", " containers = [\r\n", " data[\"graph\"][\"scene\"],\r\n", " data[\"graph\"][\"assets\"]\r\n", " ]\r\n", "\r\n", " for objects in containers:\r\n", " # temp cache\r\n", " hash_cache = {}\r\n", "\r\n", " # hash all values\r\n", " for key, value in objects.items():\r\n", " for key, value in value[1].items():\r\n", " # ignore pointers (the only non-tuple object)\r\n", " if type(value) == tuple:\r\n", " # convert into string and hash that\r\n", " value_hash = hash(str(value))\r\n", "\r\n", " # track in temp cache\r\n", " if value_hash not in hash_cache:\r\n", " hash_cache[value_hash] = {\"value\": value, \"count\": 1}\r\n", " else:\r\n", " hash_cache[value_hash][\"count\"] += 1\r\n", "\r\n", " # throw out all non-repeated values\r\n", " bad_keys = []\r\n", " for key, value in hash_cache.items():\r\n", " if value[\"count\"] < 2:\r\n", " bad_keys.append(key)\r\n", " for key in bad_keys:\r\n", " del hash_cache[key]\r\n", "\r\n", " # create hash objects for each repeated value\r\n", " for key, value in hash_cache.items():\r\n", " cache_pointer = cache_key(data)\r\n", " data[\"cache\"][cache_pointer] = value[\"value\"]\r\n", " hash_cache[key][\"pointer\"] = cache_pointer\r\n", "\r\n", " # replace all instances of cached values in the graph with corresponding cache pointers\r\n", " for object_key, object_value in objects.items():\r\n", " for value_key, value_value in object_value[1].items():\r\n", " # ignore pointers (the only non-tuple object)\r\n", " if type(value_value) == tuple:\r\n", " # convert into string and hash that\r\n", " value_hash = hash(str(value_value))\r\n", "\r\n", " # if this value is cached, replace it with its cache pointer\r\n", " if value_hash in hash_cache:\r\n", " objects[object_key][1][value_key] = \"#\" + hash_cache[value_hash][\"pointer\"]" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 9, "source": [ "# just returns a random string\r\n", "import random\r\n", "import string\r\n", "def random_string(length):\r\n", " return ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(length))\r\n", "\r\n", "# create test scene\r\n", "test_scene = new_scene(\"Neutrino Test Scene\")\r\n", "\r\n", "# populate assets\r\n", "asset_names = []\r\n", "for i in range(3):\r\n", " name = random_string(8)\r\n", " add_asset(test_scene, name, \"Assets/TestAsset.obj\")\r\n", " asset_names.append(name)\r\n", "\r\n", "# populate objects in scene\r\n", "for i in range(5):\r\n", " spawn_object(test_scene, random_string(8), random.choice(asset_names))\r\n", "\r\n", "# cache the scene\r\n", "cache_scene(test_scene)\r\n", "\r\n", "save_scene(test_scene)" ], "outputs": [], "metadata": {} } ], "metadata": { "orig_nbformat": 4, "language_info": { "name": "python", "version": "3.7.8", "mimetype": "text/x-python", "codemirror_mode": { "name": "ipython", "version": 3 }, "pygments_lexer": "ipython3", "nbconvert_exporter": "python", "file_extension": ".py" }, "kernelspec": { "name": "python3", "display_name": "Python 3.7.8 64-bit" }, "interpreter": { "hash": "57baa5815c940fdaff4d14510622de9616cae602444507ba5d0b6727c008cbd6" } }, "nbformat": 4, "nbformat_minor": 2 }