leonarski_f
b9f8c2b675
Foundation for a dataset (snapshot or, later, the main file) being a subset of the truly collected images: - JFJochReaderDataset gains source_image_number (image index -> original image number; empty = identity). - HDF5MetadataSource reads /entry/detector/number into that map and an inverse (original -> local) map; FillPerImage / ReadSpots translate the requested global image to this source's local index via ToLocalIndex (return nothing if the image is not covered), so partial snapshots are correct and never read out of bounds. - RegisterSnapshot now accepts a snapshot with fewer images than the dataset (only rejects more), so sub-range / strided reprocessing runs register. - The dataset-info plot draws each run at its original image numbers (x map from source_image_number), so a subset run lands at the right place on the shared axis. The live run's map is filled from msg.original_number. This makes the foundation ready for strided / filtered selections (e.g. reprocess only images with >N spots) without restricting to a min-max sub-range. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
79 lines
2.6 KiB
C++
79 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> 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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