leonarski_fandClaude Opus 5
a29c36600f
rugnux finds the beam stop and its holder in a projection of 60 images and marks them in the pixel mask as bit 9 (--detect-beam-stop[=N|off], on by default). Reflections behind the stop are attenuated but not flagged, so they integrate low with a plausible sigma and nothing downstream catches them: the signal-box gate requires 100% valid pixels and shadow pixels are valid, the background clip is high-side only, and the |zeta| cut applies only to the space-group search merge. The detection compares each pixel's background against the typical background at the same radius on two channels. An azimuthal one (the ring median) finds the holder arm, which is a minority of its ring; a radial one (the background just outside) finds the disk, which the ring median cannot see because inside a fully blocked ring the median is the shadow itself. Pixels are pooled over a 5x5 box and tested only where the background has actually been counted, so low-background data no longer masks the whole detector. Recorded reflections are carved back out - a beam stop cannot block a reflection that was measured. Bit 9 belongs to the run that found it, not to the dataset: it is cleared when a run starts, so a mask read back from a file that carries one starts clear. The user mask (bit 8) is left alone. Scaling and merging gain a low-resolution limit, default 50 A (--scaling-low-resolution <num>, 0 removes it), applied per observation before scaling so it also protects the per-frame scale fit and the space-group search. 50 A is the value XDS configurations use; rugnux_vs_xds.py now matches both of XDS's resolution limits instead of only the high one, so the lowest shell is the same shell in the two programs. The viewer draws the detected shadow in coral with a "Show beam stop" switch in the side panel, exposes the low-resolution limit in the settings dock, and offers detection in its processing jobs. Adding an image marker meant giving the reader a MIN_REAL_PXL_VALUE, because several places classify a pixel by range rather than by equality and would otherwise read the new marker as a very negative intensity. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
88 lines
3.1 KiB
C++
88 lines
3.1 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 <vector>
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#include <unordered_set>
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#include <map>
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#include <mutex>
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#include <optional>
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#include "../common/TopPixels.h"
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#include "JFJochReaderDataset.h"
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#include "../common/CrystalLattice.h"
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#include "../common/Histogram.h"
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// Markers stored in place of an intensity. They occupy the bottom of the int32 range and
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// INT32_MAX at the top, so anything in between is a real count. Add a marker at the BOTTOM and move
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// MIN_REAL_PXL_VALUE with it - several places classify a pixel by range rather than by equality,
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// and they all test against MIN_REAL_PXL_VALUE.
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constexpr static int32_t ERROR_PXL_VALUE = INT32_MIN;
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constexpr static int32_t GAP_PXL_VALUE = INT32_MIN + 1;
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constexpr static int32_t BEAM_STOP_PXL_VALUE = INT32_MIN + 2;
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constexpr static int32_t MIN_REAL_PXL_VALUE = INT32_MIN + 3;
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constexpr static int32_t SATURATED_PXL_VALUE = INT32_MAX;
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struct JFJochReaderRawImage {
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std::vector<uint8_t> image_buffer;
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CompressedImage image;
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};
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class JFJochReaderImage {
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std::shared_ptr<const JFJochReaderDataset> dataset;
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std::vector<int32_t> image; // Image in the reader must be 32-bit signed, uncompressed
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DataMessage message;
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std::unordered_set<int64_t> saturated_pixel;
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std::unordered_set<int64_t> error_pixel;
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std::vector<std::pair<int32_t, int32_t>> valid_pixel;
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// Fast stats without storing/sorting all valid pixels
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int32_t valid_min = 0;
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int32_t valid_max = 0;
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size_t valid_count = 0;
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bool has_valid = false;
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// For overlay: track top pixels with a tiny O(K) structure; export to vector for UI
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TopPixels top_pixels_acc{20};
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std::vector<std::pair<int32_t, int32_t>> top_pixels;
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// This histogram operates in square root of count from 0 to 10^20
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Histogram count_histogram{100000};
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constexpr static float auto_foreground_range = 99.0f;
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int32_t auto_foreground;
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void CalcAutoContrast();
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template <class T>
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void ProcessInputImage(const void* image, size_t npixel, int64_t sat_value, int64_t special_value);
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void ProcessInputImage(const CompressedImage& image);
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public:
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JFJochReaderImage(const DataMessage &msg, const std::shared_ptr<const JFJochReaderDataset> &dataset);
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JFJochReaderImage(const JFJochReaderImage &other);
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const DataMessage &ImageData() const;
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DataMessage &ImageData();
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const std::vector<int32_t> &Image() const;
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const std::unordered_set<int64_t> &SaturatedPixels() const;
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const std::unordered_set<int64_t> &ErrorPixels() const;
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const JFJochReaderDataset &Dataset() const;
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std::optional<std::pair<int32_t, int32_t>> ValidMinMax() const;
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const std::vector<std::pair<int32_t, int32_t>> &GetTopPixels() const;
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void AddImage(const JFJochReaderImage& other);
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std::vector<float> GetAzInt1D() const;
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std::vector<float> GetAzInt1D_BinToQ() const;
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std::shared_ptr<JFJochReaderDataset> CreateMutableDataset();
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int32_t GetAutoContrastValue() const;
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std::vector<float> GetHistogram() const;
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};
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