leonarski_fandClaude Fable 5
f422988cd2
A single per-image ice_ring_score - the strongest hexagonal-ice ring band/shoulder intensity ratio from the azimuthal profile (1 = no ice) - computed in the CPU and FPGA analysis paths and the offline azint worker, then plumbed through every layer: DataMessage/EndMessage, CBOR (frame_serialize), HDF5 (/entry/MX/iceRingScore), ScanResult, receiver plots (PlotType::IceRingScore), the OpenAPI spec (plot_type + scan_result schema, with regenerated broker/gen and frontend client) and OpenAPIConvert, the reader + Qt viewer, and the React frontend plot. Documented in docs/CBOR.md, docs/HDF5.md and docs/CPU_DATA_ANALYSIS.md, with the general "add a per-image quantity" recipe added to CLAUDE.md. Verified in HDF5: lysoC (weak ice) mean 1.23, EP_cs_01-17 (heavy ice) mean 1.67 / max 2.23. This is a monitoring quantity - it does not gate scaling (which already excludes all ice rings) or merging (handled by the CC1/2 ring mask). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
80 lines
2.6 KiB
C++
80 lines
2.6 KiB
C++
// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#pragma once
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#include <string>
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#include <optional>
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#include <vector>
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#include <map>
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#include "../common/DiffractionGeometry.h"
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#include "../common/DiffractionExperiment.h"
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#include "../common/PixelMask.h"
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#include "../common/AzimuthalIntegrationMapping.h"
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struct JFJochReaderDataset {
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std::string arm_date;
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DiffractionExperiment experiment;
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PixelMask pixel_mask;
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std::optional<int64_t> error_value;
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std::string jfjoch_release;
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std::vector<float> az_int_bin_to_q;
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std::vector<float> az_int_bin_to_phi;
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size_t azimuthal_bins = 0;
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size_t q_bins = 0;
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std::vector<float> spot_count;
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std::vector<float> spot_count_indexed;
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std::vector<float> spot_count_low_res;
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std::vector<float> spot_count_ice_rings;
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std::vector<float> indexing_result;
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std::vector<float> indexing_lattice_count;
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std::vector<float> bkg_estimate;
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std::vector<float> ice_ring_score;
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std::vector<float> resolution_estimate;
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std::vector<float> efficiency;
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std::vector<float> profile_radius;
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std::vector<float> mosaicity_deg;
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std::vector<float> b_factor;
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std::vector<float> integrated_reflections;
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std::vector<float> image_scale_factor;
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std::vector<float> image_scale_cc;
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std::vector<float> image_scale_b;
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std::vector<int64_t> max_value;
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// Maps this dataset's image index -> the original/collected image number it came from.
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// Empty means identity (image i == original image i). Lets a dataset be a subset (or strided
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// selection) of the truly collected images: reprocessing snapshots over a sub-range, and (in
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// future) a main dataset that was filtered on-the-fly during collection.
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std::vector<int> source_image_number;
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std::vector<std::string> roi;
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std::vector<std::vector<int64_t>> roi_sum;
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std::vector<std::vector<int64_t>> roi_sum_sq;
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std::vector<std::vector<int64_t>> roi_max;
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std::vector<std::vector<int64_t>> roi_npixel;
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std::vector<std::vector<float>> roi_x;
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std::vector<std::vector<float>> roi_y;
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// ROI definitions stored in the master file. The logical definitions populate
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// experiment.ROI() (they re-derive with the current geometry); roi_map is the
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// per-pixel bitmask as written (constant footprint), with roi_bit_index mapping
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// each ROI name to its bit.
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std::vector<uint16_t> roi_map;
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std::map<std::string, uint16_t> roi_bit_index;
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std::vector<std::string> calibration_data;
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JFJochReaderDataset() = default;
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JFJochReaderDataset(const JFJochReaderDataset &other) = default;
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};
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