Image Metrics
Live information-content metrics computed from an EPICS NTNDArray image PV: entropy, normalized entropy, zlib compressibility, Laplacian variance, spectral entropy/centroid/flatness, high-frequency energy, gradient magnitude, optional mutual information against a captured reference, and a combined 0–1 interest score.
Launch with metrics, enter the detector PV (e.g.
32idbSP1:Pva1:Image), and press Start.
Usage
Capture Reference records a frame; mutual information is then plotted against it.
Tomography mode switches the x-axis from time to angle and uses start/end angles + spacing to estimate total projections.
Frames above the Interest Threshold are marked; the best frame is highlighted. Save Data… exports CSV or NPZ.
Adding a new metric
Add the metric function in src/pystream/plugins/metrics.py, following the existing helpers (input is a float grayscale image in
[0, 1]).Call it from
compute_all_metrics()and add its key to the returned dict.Add a plot trace for it in the dialog setup so it appears in the UI.