Source code for blissoda.tomo.nxtomo.holotomo

from __future__ import annotations

from pathlib import Path
from typing import Any


def _scan_category(entry: Any) -> str:
    return str(entry.get("technique", {}).get("scan_category", ""))



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def matches(processor: Any, entry: Any) -> bool:
    return _scan_category(entry) == "tomo:fulltomo+tomo:holostep"



def _position_label(entry: Any) -> str:
    position = int(entry.get("technique", {}).get("num_position", 0))
    return f"{position:04d}"



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def expanded_subscan_plan(processor: Any, entry: Any) -> list[tuple[str | None, int]]:
    return processor._subscan_plan(entry)




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def synthetic_translation(processor: Any, entry: Any, alias_name: str):
    return processor._position_array(entry, alias_name)




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def segment_specs(processor: Any, entry: Any, records: list[dict[str, Any]]):
    return [{"label": _position_label(entry), "pieces": records}]




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def dataset_stem(processor: Any, bliss_path: str, label: str | None) -> str:
    return processor._default_dataset_stem(bliss_path, label)




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def output_stem(processor: Any, bliss_path: str, label: str | None) -> str:
    return processor._default_output_stem(bliss_path, label)




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def dataset_processed_dir(processor: Any, bliss_path: str) -> Path:
    return processor._default_dataset_processed_dir(bliss_path)




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def build_output_path(processor: Any, bliss_path: str, label: str | None) -> str:
    dataset_dir = processor._default_dataset_processed_dir(bliss_path)
    projections_dir = dataset_dir / "projections"
    stem = processor._default_output_stem(bliss_path, label)
    return str(projections_dir / f"{stem}.nx")




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def workflows_dir(processor: Any, dataset_filename: str, label: str | None) -> Path:
    return (
        processor._default_dataset_processed_dir(dataset_filename)
        / "workflows"
        / "gallery"
    )