Logic change (deterministic), kept on evidence. Every Refit searched the whole k_sol/b_sol box - an 88-point coarse pass of plain least squares, then the robust fine pass around its winner. ModelScaleBox (and ModelScaleGPUPool::Fit / ModelScaleGPU::FitSolvent) take an optional start; with one, the coarse pass is skipped and the fine pass is laid around it. Refinement passes the grid winner of the context's previous Refit (before MoveOverallB moves the overall B into b_sol); it travels with a trial's fit, and a trial's first Refit without one (Context::ForgetStarts, which also clears the likelihood's D start) searches the whole box, so a trial still depends on nothing its slot ran before (side by side = one at a time, md5). Evidence (GPU, -N 8): full refinement of the 14 parity sets from their placed models - 12 refined CIFs identical (md5), 9ig7 and 6iu9 differ, final R-work/R-free equal to 4 digits but 6iu9 R-work 0.2911 -> 0.2910; of the 5 timing cases 4 identical, 7d98 (cif start) R-free 0.3096 -> 0.3095; 5f6m MD starts 01-04 median R-free 0.1692 -> 0.1692; 6o2h on the CPU engine identical (md5). The score-only parity table is not touched (one Refit, no start). refit.scale (TIMING sum): 5f6m 1.52 -> 1.10 s. Wall: 5reo 1.68 -> 1.53, 5f6m 2.43 -> 2.24, 9yl4 7.19 -> 7.02, 7d98 3.70 -> 3.65, 5f6m MD start 4.57 -> 4.22 s. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit ff285fb525ecf4b480698d4aafe212a34301a8fe)
95 lines
5.0 KiB
C++
95 lines
5.0 KiB
C++
// SPDX-FileCopyrightText: 2026 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 <condition_variable>
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#include <cstddef>
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#include <memory>
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#include <mutex>
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#include <vector>
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#include "gemmi/model.hpp"
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#include "gemmi/scaling.hpp"
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// Fit the overall scale, the anisotropic B and the flat bulk solvent of a model to observed
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// amplitudes, writing the answer into `scaling` (k_overall, b_star, k_sol, b_sol) so that
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// gemmi's own scale_data() can then apply it.
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//
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// The caller decides which reflections are fitted: FitModelScale reads scaling.points, which
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// prepare_points() filled. Pass the WORKING set to keep the free reflections out of the scale
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// model - that is a property of the call site, not of this function.
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//
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// Replaces gemmi's fit_isotropic_b_approximately() + fit_parameters(), which is an unbounded
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// Levenberg-Marquardt: nothing there stops k_sol and b_sol reaching values a flat solvent model
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// is meaningless at (b_sol of 1707 A^2 was measured on this corpus). Here k_sol and b_sol come
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// from a grid search over the physical ranges, so an unphysical answer cannot be represented.
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// The box the solvent parameters are searched in. The defaults are the physically reasonable
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// range reported by Fokine & Urzhumtsev and adopted as phenix's default grid: k_sol in (0.1, 0.8)
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// and b_sol in (10, 80) A^2, of which phenix searches b_sol 10-80 in steps of 5. A model with high
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// atomic B gets a higher b_sol ceiling (SolventBMax).
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struct ModelScaleBox {
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double k_lo = 0.10, k_hi = 0.60;
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double b_lo = 10.0, b_hi = 80.0;
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// The overall scale and anisotropic B of the points of the fine pass by robust least squares
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// (ModelScaling.cpp, RobustReweight) rather than plain least squares on |F|: what refinement scores a model with.
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bool robust = false;
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// Where a fit of the model as it was a moment ago found the solvent: the fine pass around (k_start, b_start)
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// without the coarse pass. Negative: the coarse pass finds where to look.
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double k_start = -1, b_start = -1;
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};
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// The b_sol ceiling for `model`: 80 A^2, or twice the model's mean atomic B where that is higher.
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// b_sol is how far the solvent's edge is smeared, and the edge can be no sharper than the atoms it
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// lies against: a model at B of 300 A^2 beside a solvent held at 80 gets a solvent term that reaches
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// far too deep in resolution, which only a too-small k_sol can then offset. Fokine & Urzhumtsev's
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// 10-80 A^2 is for models at the B of ordinary entries (their mean b_sol 46 A^2), where the ceiling
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// stays at 80.
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double SolventBMax(const gemmi::Model &model);
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struct ModelScaleReport {
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int n_points = 0; // reflections the fit actually used
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int n_grid = 0; // grid points evaluated
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double r_work_fit = 1.0; // R on the fitted reflections, at the chosen solution
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};
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// nthreads: the grid points are fitted in parallel on up to this many threads; the answer does not
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// depend on it.
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ModelScaleReport FitModelScale(gemmi::Scaling<float> &scaling, ModelScaleBox box = {}, size_t nthreads = 1);
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#ifdef JFJOCH_USE_CUDA
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// FitModelScale on a GPU (ModelScaleGPU::FitSolvent): the same grid over the same box, the same fits and
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// the same winner, with the sums over the reflections taken in double on the device where the host takes
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// them in long double - so the answer is FitModelScale's to rounding, not to the bit. A few engines,
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// reserved once, each a stream and room for one fit at a time; a fit takes a free one and waits for one
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// where all are taken. Every kernel is deterministic, so which engine a fit gets changes no number.
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class ModelScaleGPUPool {
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public:
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// What `engines` engines for fits of up to `max_points` reflections take on the card.
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static size_t DeviceBytes(size_t max_points, size_t engines, bool robust = false);
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// On `device`. Throws JFJochException on a CUDA failure.
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ModelScaleGPUPool(int device, size_t max_points, size_t engines);
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~ModelScaleGPUPool();
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// FitModelScale(scaling, {.b_hi = b_hi, .robust = robust}, nthreads). Where FitModelScale would walk the
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// grid point to point (five or fewer reflections for the isotropic start), it is FitModelScale on the host.
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// Safe to call from several threads. Throws JFJochException on a CUDA failure. The robust fit's reweighting
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// runs on the device; it is FitModelScale's robust fit to rounding (float residuals and weights, the
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// anisotropic factor of the steps in float), deterministic run to run.
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// k_start, b_start: ModelScaleBox's.
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ModelScaleReport Fit(gemmi::Scaling<float> &scaling, double b_hi, size_t nthreads, bool robust = false,
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double k_start = -1, double b_start = -1);
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// What the pool holds on the card.
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size_t Bytes() const { return DeviceBytes(max_points_, engines_.size()); }
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private:
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struct Engine;
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int device_;
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size_t max_points_;
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std::vector<std::unique_ptr<Engine>> engines_;
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std::vector<Engine *> idle_;
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std::mutex m_;
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std::condition_variable cv_;
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};
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#endif
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