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This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use. * rugnux: Add `--model model.pdb` - score the merged data against an atomic model and compute initial maps. It reports R-work/R-free (scaling the model to the observed amplitudes with an overall scale, an anisotropic B and a flat bulk solvent - the standard few-parameter model, so a batch of maps stays directly comparable) and writes 2Fo-Fc / Fo-Fc electron-density maps (CCP4) plus a map-coefficient MTZ. The structure itself is not refined; the model is only re-fractionalised into the data cell. * rugnux: The merged reflection output now carries French-Wilson amplitudes (|F| and its sigma) next to the intensities - MTZ `F`/`SIGF`, mmCIF `_refln.F_meas_au`, and the text HKL - computed with the correct centric/acentric Wilson prior and epsilon multiplicity, so a downstream program (e.g. phenix.refine) can refine against amplitudes. The intensity columns are unchanged. * rugnux: R-free test-set flags are now assigned deterministically and consistently across symmetry - a Bijvoet pair I(+)/I(-) is never split between the work and free sets, and the assignment is a reproducible per-hkl hash that depends only on the reflection index, so every dataset of one crystal form gets the same ~5% free set (what a multi-dataset campaign such as PanDDA needs). On small data the fraction is floored so the test set stays large enough for a stable R-free (~500 reflections, capped at 10%); it stays flat at 5% on ordinary data. When a reference MTZ carries a `FreeR_flag` column its test set is imported instead, letting a whole campaign inherit one shared free set. * rugnux: A reference MTZ (`--reference-mtz`) can now fix the space group and cell for rotation data too (previously rejected), without being used to scale - the rotation merge stays self-consistent. When the crystal has an indexing (merohedral) ambiguity - a lattice symmetry higher than its Laue symmetry, e.g. P3/P4/P6/C2 - the reference also resolves it: each candidate reindexing (identity plus the twin-law cosets of the metric symmetry) is scored by its intensity correlation against the reference and the data are re-merged in the best-correlating one. This is a metric-preserving relabelling of hkl (the cell is unchanged) and a no-op for a holohedral crystal such as lysozyme. * rugnux: `--model` validation now aligns the data to the model before scoring - the observed reflections are reindexed into the model's enantiomorph when the two differ only by hand (indistinguishable from merged intensities). A merohedral indexing ambiguity is resolved against the reference MTZ when one is given (so a whole campaign shares one indexing convention); only with a model and no reference does validation fall back to fitting each candidate reindexing and keeping the lowest R-free. * rugnux: De-novo symmetry - recover a genuine high-symmetry group whose data are imperfectly scaled. Such a merge's within-orbit chi² lands just past the self-consistency bound (each real symmetry step adds a little systematic scatter), right where a merohedral twin also lands, so the chi² ratio alone cannot separate them. The candidate is now rescued when the extra intensity-proportional systematic error it invokes stays small relative to the confirmed subgroup - a genuine symmetry step gains multiplicity without inflating the merge error model's b, whereas a twin forces non-equivalent reflections together and b balloons. Fixes cubic insulin (I23 instead of I222) with no change to any other crystal in the test battery, including the twins that must stay in their lower symmetry. * Docs: Document the French-Wilson amplitude estimation, R-free flagging, reference-based space-group/ambiguity resolution, and model-based validation/maps in CPU_DATA_ANALYSIS.md. * Frontend: The status-bar pill now shows a progress bar during detector calibration (previously only during measurement), and the calibration state and its button are labelled "Calibration"/"CALIBRATE" (the internal `Pedestal` state name is unchanged for back-compatibility).Reviewed-on: #69 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
138 lines
4.6 KiB
C++
138 lines
4.6 KiB
C++
// Copyright 2019 Global Phasing Ltd.
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//
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// Span - span of array or std::vector.
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// MutableVectorSpan - span of std::vector with insert() and erase()
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#ifndef GEMMI_SPAN_HPP_
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#define GEMMI_SPAN_HPP_
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#include <algorithm> // for find_if, find_if_not
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#include <vector>
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#include <stdexcept> // for out_of_range
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#include <type_traits> // for remove_cv, conditional, is_const
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namespace gemmi {
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template<typename Item> struct MutableVectorSpan;
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// Minimalistic Span, somewhat similar to C++20 std::span.
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template<typename Item> struct Span {
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using iterator = Item*;
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using const_iterator = Item const*;
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using element_type = Item;
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using value_type = typename std::remove_cv<Item>::type;
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friend Span<const value_type>;
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friend MutableVectorSpan<value_type>;
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Span() = default;
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Span(iterator begin, std::size_t n) : begin_(begin), size_(n) {}
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#if !defined(_MSC_VER) || _MSC_VER-0 >= 1926
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// constructor only for const Item, to allow non-const -> const conversion
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template<typename T=Item>
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Span(const Span<value_type>& o,
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typename std::enable_if<std::is_const<T>::value>::type* = 0)
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#else
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// older MSVC don't like the version above
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Span(const Span<value_type>& o)
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#endif
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: begin_(o.begin_), size_(o.size_) {}
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void set_begin(iterator begin) { begin_ = begin; }
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void set_size(std::size_t n) { size_ = n; }
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const_iterator begin() const { return begin_; }
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const_iterator end() const { return begin_ + size_; }
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iterator begin() { return begin_; }
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iterator end() { return begin_ + size_; }
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Item& front() { return *begin_; }
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const Item& front() const { return *begin_; }
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Item& back() { return *(begin_ + size_ - 1); }
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const Item& back() const { return *(begin_ + size_ - 1); }
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const Item& operator[](std::size_t i) const { return *(begin_ + i); }
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Item& operator[](std::size_t i) { return *(begin_ + i); }
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Item& at(std::size_t i) {
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if (i >= size())
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throw std::out_of_range("item index ouf of range: #" + std::to_string(i));
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return *(begin_ + i);
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}
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const Item& at(std::size_t i) const {
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return const_cast<Span*>(this)->at(i);
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}
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std::size_t size() const { return size_; }
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bool empty() const { return size_ == 0; }
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explicit operator bool() const { return size_ != 0; }
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template<typename Iter> Span<Item> sub(Iter first, Iter last) {
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return Span<Item>(&*first, last - first);
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}
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template<typename F, typename V=Item> Span<V> subspan(F&& func) {
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iterator group_begin = std::find_if(this->begin(), this->end(), func);
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iterator group_end = std::find_if_not(group_begin, this->end(), func);
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return Span<V>(&*group_begin, group_end - group_begin);
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}
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template<typename F> Span<const value_type> subspan(F&& func) const {
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using V = const value_type;
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return const_cast<Span*>(this)->subspan<F, V>(std::forward<F>(func));
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}
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// we use children() to iterate over Model, Chain, etc
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Span& children() { return *this; }
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const Span& children() const { return *this; }
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private:
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iterator begin_ = nullptr;
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std::size_t size_ = 0;
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};
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// Span of std::vector, implements insert() and erase().
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template<typename Item> struct MutableVectorSpan : Span<Item> {
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using vector_type = std::vector<typename Span<Item>::value_type>;
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using iterator = typename Span<Item>::iterator;
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//friend Span<const value_type>;
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MutableVectorSpan() = default;
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MutableVectorSpan(Span<Item>&& p, vector_type* v)
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: Span<Item>(p), vector_(v) {}
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MutableVectorSpan(vector_type& v, iterator begin, std::size_t n)
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: Span<Item>(begin, n), vector_(&v) {}
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template<typename Iter> MutableVectorSpan<Item> sub(Iter first, Iter last) {
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return {Span<Item>::sub(first, last), vector_};
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}
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template<typename F> MutableVectorSpan<Item> subspan(F&& func) {
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return {Span<Item>::subspan(std::forward<F>(func)), vector_};
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}
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template<typename F> MutableVectorSpan<const Item> subspan(F&& func) const {
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return {Span<const Item>::subspan(std::forward<F>(func)), vector_};
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}
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iterator insert(iterator pos, Item&& item) {
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auto offset = this->begin_ - this->vector_->data();
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auto iter = vector_->begin() + (pos - this->vector_->data());
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auto ret = vector_->insert(iter, std::move(item));
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this->begin_ = vector_->data() + offset;
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++this->size_;
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return &*ret;
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}
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void erase(iterator pos) {
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vector_->erase(vector_->begin() + (pos - vector_->data()));
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--this->size_;
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}
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bool is_beginning() const { return this->begin() == vector_->data(); }
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bool is_ending() const { return this->end() == vector_->data() + vector_->size(); }
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private:
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vector_type* vector_ = nullptr; // for insert() and erase()
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};
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} // namespace gemmi
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#endif
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