qubed/tree_compresser/tests/reconstruct.py
2024-12-11 14:11:11 +00:00

44 lines
1.5 KiB
Python

from pathlib import Path
from tree_traverser import CompressedTree, RefcountedDict
class CompressedTreeFixed(CompressedTree):
@classmethod
def from_json(cls, data : dict):
c = cls({})
c.cache = {}
ca = data["cache"]
for k, v in ca.items():
g = {k2 : ca[str(v2)]["dict"][k2] if k2 in ca[str(v2)]["dict"] else v2 for k2, v2 in v["dict"].items()}
c.cache[int(k)] = RefcountedDict(g)
c.cache[int(k)].refcount = v["refcount"]
c.root_hash = data["root_hash"]
c.tree = c.cache[c.root_hash]
return c
def reconstruct(self, max_depth=None) -> dict[str, dict]:
"Reconstruct the tree as a normal nested dictionary"
def reconstruct_node(h : int, depth : int) -> dict[str, dict]:
if max_depth is not None and depth > max_depth:
return {}
return {k : reconstruct_node(v, depth=depth+1) for k, v in self.cache[h].items()}
return reconstruct_node(self.root_hash, depth = 0)
data_path = Path("data/compressed_tree_climate_dt.json")
# Print size of file
print(f"climate dt compressed tree: {data_path.stat().st_size // 1e6:.1f} MB")
print("Opening json file")
compressed_tree = CompressedTreeFixed.load(data_path)
output_data_path = Path("data/compressed_tree_climate_dt_ecmwf_style.json")
# Print size of file
compressed_tree.save(output_data_path)
print(f"climate dt compressed tree ecmwf style: {output_data_path.stat().st_size // 1e6:.1f} MB")