brighteyes-mcs-dataprep 0.1.0

Calibration, output-building, and data preparation utilities for BrightEyes MCS HDF5 files.

BrightEyes-MCS-DataPrep

Calibration and data-preparation utilities for BrightEyes MCS HDF5 files.

brighteyes-mcs-dataprep contains the writer-side and processing helpers for BrightEyes MCS data. It calibrates FLIM histograms, estimates channel skew, creates schema-compatible /output groups, appends derived analysis products, and provides plotting and HDF5 inspection helpers.

Reader functionality is intentionally kept in BrightEyes-MCS-Reader and is imported from brighteyes_mcs_reader where needed.

Install

pip install brighteyes-mcs-dataprep

For local development:

pip install -e .
pytest

Usage

Calibrate a file

from brighteyes_mcs_dataprep import calibrate_h5_file

calibrated_path = calibrate_h5_file(
    "measurement.h5",
    "reference.h5",
    data_key=("data", "data_channels_extra"),
    reference_key=None,
    reference_type="ref",
    period_ns=12.5,
)

By default the calibrated copy is written next to the input file with a _calib.h5 suffix. Calibration results are stored under /calibration/results/<product>/, and the /output group is created unless create_output=False is passed.

Build standard outputs

from brighteyes_mcs_dataprep import build_h5_output

build_h5_output(
    "measurement_calib.h5",
    create_virtual_channels=True,
    create_sum_channels=True,
    create_sum_channels_with_skew_correction=True,
)

The output builder creates virtual per-channel datasets and summed SPAD/AUX products under /output. It reads current schema paths such as /raw/spad and /raw/aux by default. Legacy root-level datasets can be selected explicitly, for example spad_data_key="data" or aux_data_key="data_channels_extra".

Append analysis products

import numpy as np

from brighteyes_mcs_dataprep import H5OutputProduct, write_h5_output_run

written_path, run_id = write_h5_output_run(
    "measurement_calib.h5",
    "apr_001",
    [
        H5OutputProduct(
            "spad",
            np.ones((256, 256)),
            attrs={
                "data_role": "image",
                "axis_order": "y,x",
                "source_data_path": "/raw/spad",
                "units": "counts",
            },
        )
    ],
    tool_name="APR reassignment",
    algorithm_name="adaptive_pixel_reassignment",
    set_default=True,
)

Existing run IDs are versioned automatically, so a second write to apr_001 becomes apr_002 unless output_key_overwrite=True is passed.

Public API

Common imports are exposed directly from brighteyes_mcs_dataprep:

from brighteyes_mcs_dataprep import (
    H5DataCalibrator,
    H5OutputBuilder,
    H5OutputProduct,
    build_h5_output,
    calibrate_h5_file,
    estimate_channel_skew,
    show_h5_structure,
    write_h5_output_run,
)

Alignment and plotting helpers are also available through Alignment or as lazy top-level exports.

HDF5 Schema Notes

Current BrightEyes files store measured data under /raw, metadata under /raw/metadata, calibration artifacts under /calibration, and derived analysis runs under /output/<run_id>. The data-preparation helpers preserve this layout and add provenance attributes, source-file hashes, and default output pointers where appropriate.