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python/neutrino/__pycache__/decode.cpython-37.pyc
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python/neutrino/__pycache__/decode.cpython-37.pyc
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python/neutrino/__pycache__/encode.cpython-37.pyc
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python/neutrino/__pycache__/encode.cpython-37.pyc
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python/neutrino/decode.py
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python/neutrino/decode.py
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import json
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def uncache_scene(in_data):
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pure_data = {
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"meta": in_data["meta"],
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"graph": in_data["graph"]
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}
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raw_json = json.dumps(pure_data)
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# cache objects
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raw_cache = json.dumps(in_data["cache"])
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for key, value in in_data["cache"]["objects"].items():
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pointer = "#" + key
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raw_cache = raw_cache.replace(f'"{pointer}"', json.dumps(value))
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unpacked_object_cache = json.loads(raw_cache)
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# objects
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for key, value in unpacked_object_cache.items():
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print(json.dumps(value))
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pointer = "#" + key
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raw_json = raw_json.replace(f'"{pointer}"', json.dumps(value))
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# names
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for key, value in in_data["cache"]["names"].items():
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raw_json = raw_json.replace("@" + key, value)
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out_data = json.loads(raw_json)
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return out_data
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python/neutrino/encode.py
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python/neutrino/encode.py
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import json
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# create a new scene graph
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def new_scene(name, cache = True):
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# create empty neutrino data
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data = {
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"meta": {
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"name": ("name", name),
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"scale": ("float", 1.0),
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"asset_path": ("path", "./")
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},
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"graph": {
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"scene": {},
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"assets": {}
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},
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"cache": {
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"names": {},
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"objects": {}
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},
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"internal": {
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"cache": cache,
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"max_object_key": {"index": 0},
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"max_name_key": {"index": 0}
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}
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}
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# return that empty data
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return data
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# write the data to a JSON file
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def save_scene(data, readable = False):
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# cache the scene
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if data["internal"]["cache"]:
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cache_scene(data)
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# create working copy of the scene data
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clean_data = data.copy()
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# get rid of internal data (not to be exported)
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del clean_data["internal"]
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filename = data["meta"]["name"][1].replace(" ", "") + ".json"
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with open(filename, "w") as outfile:
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if readable:
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json.dump(clean_data, outfile, indent = 4)
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else:
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json.dump(clean_data, outfile)
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# get a new indexed object key and track it
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def new_key(index):
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# get the indexed key
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key = hex(index["index"] + 1)
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# index the max key
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index["index"] += 1
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return key
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# returns a cached name key from a string
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def name_key(data, name):
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if data["internal"]["cache"]:
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name_pointer = ""
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# retrieve the proper key if it exists
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for key, value in data["cache"]["names"].items():
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if value == name:
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name_pointer = key
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# if the name pointer is still empty, make a new key and add it to the cache
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if name_pointer == "":
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name_pointer = new_key(data["internal"]["max_name_key"])
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data["cache"]["names"][name_pointer] = name
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return "@" + name_pointer
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else:
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return name
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# add an asset to the graph
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def add_asset(data, name, path):
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asset_data = {
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name_key(data, "name"): (name_key(data, "name"), name),
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name_key(data, "file"): (name_key(data, "path"), path)
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}
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# add the asset to the graph
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data["graph"]["assets"][new_key(data["internal"]["max_object_key"])] = (name_key(data, "asset"), asset_data)
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# add an object to the scene
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def spawn_object(data, name, asset):
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object_data = {
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name_key(data, "name"): (name_key(data, "name"), name),
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name_key(data, "asset"): "",
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name_key(data, "transform"): (name_key(data, "transform"), {
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name_key(data, "position"): (name_key(data, "vec3"), [0.0, 0.0, 0.0]),
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name_key(data, "rotation"): (name_key(data, "vec3"), [0.0, 0.0, 0.0]),
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name_key(data, "scale"): (name_key(data, "vec3"), [1.0, 1.0, 1.0])
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})
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}
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# get an asset key by the provided name
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for key, value in data["graph"]["assets"].items():
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if value[1][name_key(data, "name")][1] == asset:
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object_data[name_key(data, "asset")] = f"*{key}"
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# add the object to the scene
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data["graph"]["scene"][new_key(data["internal"]["max_object_key"])] = (name_key(data, "object"), object_data)
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# recursively cache a single typeval tuple object
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def cache_typeval(cache, typeval):
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# ignore if not typeval
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if type(typeval) == tuple:
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for key, value in typeval[1].items():
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# refuse to cache pointers (that's just... that would just be a nightmare)
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if type(value) == str:
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is_pointer = ("*" in value)
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else:
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is_pointer = False
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if not is_pointer:
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# cache member objects if it's a dictionary object
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if type(value[1]) == dict:
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cache_typeval(cache, value)
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value_hash = hash(str(value))
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# track in cache
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if value_hash not in cache["objects"]:
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cache_pointer = new_key(cache["key_index"])
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cache["objects"][value_hash] = {"key": cache_pointer, "value": value, "count": 1}
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else:
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cache_pointer = cache["objects"][value_hash]["key"]
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cache["objects"][value_hash]["count"] += 1
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# replace real value with hash
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typeval[1][key] = "#" + cache_pointer
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# if there's only one instance of a certain value, convert it back to the original value and destroy the cached version
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def uncache_typeval(cache, typeval):
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for key, value in typeval[1].items():
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# refuse to cache pointers (that's just... that would just be a nightmare)
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if type(value) == str:
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is_pointer = ("*" in value)
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else:
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is_pointer = False
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if not is_pointer:
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# cache member objects if it's a dictionary object
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if type(value[1]) == dict:
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uncache_typeval(cache, value)
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value_hash = hash(str(value))
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# check if it occurs only once
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cache_key = value.replace("#", "")
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if cache[cache_key]["count"] <= 1:
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# replace the cache pointer in the scene data with its original value
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typeval[1][key] = cache[cache_key]["value"]
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# delete this object from the cache
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del cache[cache_key]
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# cache the scene
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def cache_scene(data):
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containers = [
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data["graph"]["scene"],
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data["graph"]["assets"]
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]
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# build a cache of value hashes and pointers
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hash_cache = {"key_index": {"index": 0}, "objects": {}}
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for objects in containers:
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for key, value in objects.items():
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cache_typeval(hash_cache, value)
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# create a cache hashed with pointer keys instead of value hashes
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key_cache = {}
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for key, value in hash_cache["objects"].items():
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key_cache[value["key"]] = {"value": value["value"], "count": value["count"]}
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# prune the cache to only redirect repeat values
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for objects in containers:
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for key, value in objects.items():
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uncache_typeval(key_cache, value)
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# create a serialized cache usable by neutrino
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serial_cache = {}
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for key, value in key_cache.items():
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serial_cache[key] = value["value"]
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# add that cache to the neutrino scene data
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data["cache"]["objects"] = serial_cache
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