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from __future__ import annotations
import dataclasses
from typing import Any
from uhi.io import remove_writer_info
from uhi.io._common import _convert_input
def test_remove_writer_info() -> None:
d = {"uhi_schema": 1, "writer_info": {"a": {"foo": "bar"}, "b": {"FOO": "BAR"}}}
assert remove_writer_info(d, library=None) == {"uhi_schema": 1}
assert remove_writer_info(d, library="a") == {
"uhi_schema": 1,
"writer_info": {"b": {"FOO": "BAR"}},
}
assert remove_writer_info(d, library="b") == {
"uhi_schema": 1,
"writer_info": {"a": {"foo": "bar"}},
}
assert remove_writer_info(d, library="c") == d
@dataclasses.dataclass
class _Simple:
value: dict[str, Any]
def _to_uhi_(self) -> dict[str, Any]:
return self.value
def test_remove_empty_metadata() -> None:
d = {
"uhi_schema": 1,
"writer_info": {"boost-histogram": {"version": "1.6.1"}},
"axes": [
{
"type": "regular",
"lower": 0.0,
"upper": 1.0,
"bins": 4,
"underflow": True,
"overflow": True,
"circular": False,
"metadata": {},
}
],
"storage": {
"type": "weighted_mean",
"sum_of_weights": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
"sum_of_weights_squared": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
"values": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
"variances": [float("nan")] * 6,
},
"metadata": {},
}
h = _Simple(d)
ir = _convert_input(h)
assert "metadata" not in ir
assert "metadata" not in ir["axes"][0]
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