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Push mtzqmmrlmzzx #34

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coissac merged 25 commits from push-mtzqmmrlmzzx into main 2026-06-22 08:47:24 +00:00
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.gitea/workflows/ci.yml
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name: CI
on:
push:
branches: ['**']
pull_request:
jobs:
build:
runs-on: ubuntu-latest
defaults:
run:
working-directory: src
steps:
- uses: actions/checkout@v4
- name: Install Rust
run: |
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain stable
echo "$HOME/.cargo/bin" >> $GITHUB_PATH
- name: Cache cargo registry
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
src/target
key: ${{ runner.os }}-cargo-${{ hashFiles('src/Cargo.lock') }}
restore-keys: ${{ runner.os }}-cargo-
- name: Build
run: cargo build --release
- name: Test
run: cargo test --release
.gitea/workflows/release.yml
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name: Release
on:
push:
tags:
- 'v*'
jobs:
build-linux-static:
runs-on: ubuntu-latest
defaults:
run:
working-directory: src
steps:
- uses: actions/checkout@v4
- name: Install Rust + musl target
run: |
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain stable
echo "$HOME/.cargo/bin" >> $GITHUB_PATH
sudo apt-get update -qq && sudo apt-get install -y -qq musl-tools
$HOME/.cargo/bin/rustup target add x86_64-unknown-linux-musl
- name: Cache cargo registry
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
src/target
key: linux-musl-cargo-${{ hashFiles('src/Cargo.lock') }}
restore-keys: linux-musl-cargo-
- name: Build static binary
run: cargo build --release --target x86_64-unknown-linux-musl
- name: Prepare artifact
run: |
mkdir -p /tmp/dist
cp target/x86_64-unknown-linux-musl/release/obikmer /tmp/dist/obikmer-linux-x86_64
strip /tmp/dist/obikmer-linux-x86_64
- name: Upload release asset
uses: actions/upload-artifact@v4
with:
name: obikmer-linux-x86_64
path: /tmp/dist/obikmer-linux-x86_64
if-no-files-found: error
.gitignore
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@@ -9,3 +9,13 @@ data-stress
./**/*.json
*.bin
Betula_exilis--IGA-24-33
benchmark/genomes
benchmark/simulated_data
benchmark/specimen_index_presence
benchmark/specimen_index_count
benchmark/global_index_presence
benchmark/global_index_count
benchmark/stats
benchmark/reference_index
benchmark/specific_index_count
benchmark/specific_index_presence
.serena/.gitignore
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/cache
/project.local.yml
.serena/project.yml
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# the name by which the project can be referenced within Serena
project_name: "obikmer"
# list of languages for which language servers are started; choose from:
# al angular ansible bash clojure
# cpp cpp_ccls crystal csharp csharp_omnisharp
# dart elixir elm erlang fortran
# fsharp go groovy haskell haxe
# hlsl html java json julia
# kotlin lean4 lua luau markdown
# matlab msl nix ocaml pascal
# perl php php_phpactor powershell python
# python_jedi python_ty r rego ruby
# ruby_solargraph rust scala scss solidity
# svelte swift systemverilog terraform toml
# typescript typescript_vts vue yaml zig
# (This list may be outdated. For the current list, see values of Language enum here:
# https://github.com/oraios/serena/blob/main/src/solidlsp/ls_config.py
# For some languages, there are alternative language servers, e.g. csharp_omnisharp, ruby_solargraph.)
# Note:
# - For C, use cpp
# - For JavaScript, use typescript
# - For Angular projects, use angular (subsumes typescript+html; requires `npm install` in the project root)
# - For Svelte projects, use svelte (subsumes typescript/javascript for .svelte projects; requires npm)
# - For SCSS / Sass / plain CSS, use scss (some-sass-language-server handles all three)
# - For Free Pascal/Lazarus, use pascal
# Special requirements:
# Some languages require additional setup/installations.
# See here for details: https://oraios.github.io/serena/01-about/020_programming-languages.html#language-servers
# When using multiple languages, the first language server that supports a given file will be used for that file.
# The first language is the default language and the respective language server will be used as a fallback.
# Note that when using the JetBrains backend, language servers are not used and this list is correspondingly ignored.
languages:
- rust
# the encoding used by text files in the project
# For a list of possible encodings, see https://docs.python.org/3.11/library/codecs.html#standard-encodings
encoding: "utf-8"
# line ending convention to use when writing source files.
# Possible values: unset (use global setting), "lf", "crlf", or "native" (platform default)
# This does not affect Serena's own files (e.g. memories and configuration files), which always use native line endings.
line_ending:
# The language backend to use for this project.
# If not set, the global setting from serena_config.yml is used.
# Valid values: LSP, JetBrains
# Note: the backend is fixed at startup. If a project with a different backend
# is activated post-init, an error will be returned.
language_backend:
# whether to use project's .gitignore files to ignore files
ignore_all_files_in_gitignore: true
# advanced configuration option allowing to configure language server-specific options.
# Maps the language key to the options.
# Have a look at the docstring of the constructors of the LS implementations within solidlsp (e.g., for C# or PHP) to see which options are available.
# No documentation on options means no options are available.
ls_specific_settings: {}
# list of additional workspace folder paths for cross-package reference support (e.g. in monorepos).
# Paths can be absolute or relative to the project root.
# Each folder is registered as an LSP workspace folder, enabling language servers to discover
# symbols and references across package boundaries.
# Currently supported for: TypeScript.
# Example:
# additional_workspace_folders:
# - ../sibling-package
# - ../shared-lib
additional_workspace_folders: []
# list of additional paths to ignore in this project.
# Same syntax as gitignore, so you can use * and **.
# Note: global ignored_paths from serena_config.yml are also applied additively.
ignored_paths: []
# whether the project is in read-only mode
# If set to true, all editing tools will be disabled and attempts to use them will result in an error
# Added on 2025-04-18
read_only: false
# list of tool names to exclude.
# This extends the existing exclusions (e.g. from the global configuration)
# Find the list of tools here: https://oraios.github.io/serena/01-about/035_tools.html
excluded_tools: []
# list of tools to include that would otherwise be disabled (particularly optional tools that are disabled by default).
# This extends the existing inclusions (e.g. from the global configuration).
# Find the list of tools here: https://oraios.github.io/serena/01-about/035_tools.html
included_optional_tools: []
# fixed set of tools to use as the base tool set (if non-empty), replacing Serena's default set of tools.
# This cannot be combined with non-empty excluded_tools or included_optional_tools.
# Find the list of tools here: https://oraios.github.io/serena/01-about/035_tools.html
fixed_tools: []
# list of mode names that are to be activated by default, overriding the setting in the global configuration.
# The full set of modes to be activated is base_modes (from global config) + default_modes + added_modes.
# If the setting is undefined/empty, the default_modes from the global configuration (serena_config.yml) apply.
# Otherwise, this overrides the setting from the global configuration (serena_config.yml).
# Therefore, you can set this to [] if you do not want the default modes defined in the global config to apply
# for this project.
# This setting can, in turn, be overridden by CLI parameters (--mode).
# See https://oraios.github.io/serena/02-usage/050_configuration.html#modes
default_modes:
# list of mode names to be activated additionally for this project, e.g. ["query-projects"]
# The full set of modes to be activated is base_modes (from global config) + default_modes + added_modes.
# See https://oraios.github.io/serena/02-usage/050_configuration.html#modes
added_modes:
# initial prompt for the project. It will always be given to the LLM upon activating the project
# (contrary to the memories, which are loaded on demand).
initial_prompt: ""
# time budget (seconds) per tool call for the retrieval of additional symbol information
# such as docstrings or parameter information.
# This overrides the corresponding setting in the global configuration; see the documentation there.
# If null or missing, use the setting from the global configuration.
symbol_info_budget:
# list of regex patterns which, when matched, mark a memory entry as read‑only.
# Extends the list from the global configuration, merging the two lists.
read_only_memory_patterns: []
# list of regex patterns for memories to completely ignore.
# Matching memories will not appear in list_memories or activate_project output
# and cannot be accessed via read_memory or write_memory.
# To access ignored memory files, use the read_file tool on the raw file path.
# Extends the list from the global configuration, merging the two lists.
# Example: ["_archive/.*", "_episodes/.*"]
ignored_memory_patterns: []
CLAUDE.md
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@@ -73,3 +73,29 @@ Lors de l'ajout de nouveaux fichiers Markdown dans `docmd/`, mettre à jour la s
---
Je continue à poser mes questions et à guider la discussion.
---
## MCP Tools
**Règle absolue : avant tout travail de code, appeler `mcp__serena__initial_instructions` pour charger les instructions Serena.**
### Hiérarchie des outils pour ce projet Rust
**Navigation et édition de code → serena en priorité**
- Trouver un symbole, une déclaration, les implémentations d'un trait : `mcp__serena__find_symbol`, `mcp__serena__find_declaration`, `mcp__serena__find_implementations`
- Trouver les usages d'un symbole : `mcp__serena__find_referencing_symbols`
- Diagnostics LSP (erreurs de compilation) : `mcp__serena__get_diagnostics_for_file`
- Vue d'ensemble d'un fichier : `mcp__serena__get_symbols_overview`
- Modifier le corps d'une fonction/impl : `mcp__serena__replace_symbol_body`
- Ne pas utiliser `cclsp` quand serena couvre le besoin
**Analyse architecturale → jcodemunch**
- Hotspots, couplage, dead code, dépendances entre modules
- Utiliser avant de refactorer une zone critique
**Raisonnement complexe → sequential-thinking**
- Décisions d'architecture, choix d'algorithme, trade-offs non triviaux
**Documentation de crates → context7**
- Toujours consulter avant d'utiliser une API de bibliothèque externe
Makefile
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@@ -22,6 +22,7 @@ $(MKDOCS): $(VENV)/bin/activate
mkdocs mkdocs-material \
mkdocs-mermaid2-plugin \
mkdocs-bibtex
$(PIP) install --quiet --upgrade InSilicoSeq
# ── obikmer binary ───────────────────────────────────────────────────────────
@@ -62,3 +63,28 @@ clean-doc:
.PHONY: clean
clean: clean-doc
rm -rf $(VENV)
# ── release ───────────────────────────────────────────────────────────────────
CARGO_TOML := $(CARGO_DIR)/obikmer/Cargo.toml
.PHONY: bump-version
bump-version:
@current=$$(grep '^version = ' $(CARGO_TOML) | head -n 1 | sed 's/version = "\(.*\)"/\1/'); \
if [ -n "$(RELEASE)" ]; then \
new_version="$(RELEASE)"; \
else \
major=$$(echo $$current | cut -d. -f1); \
minor=$$(echo $$current | cut -d. -f2); \
patch=$$(echo $$current | cut -d. -f3); \
new_patch=$$((patch + 1)); \
new_version="$$major.$$minor.$$new_patch"; \
fi; \
echo "Version: $$current -> $$new_version"; \
sed -i.bak "s/^version = \"$$current\"/version = \"$$new_version\"/" $(CARGO_TOML) && \
rm $(CARGO_TOML).bak
.PHONY: release
release: bump-version
@jj auto-describe
@jj git push --change @
benchmark/Makefile
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# Requires GNU Make >= 4.3 (grouped targets &:) — use gmake on macOS
BINARY := ../src/target/release/obikmer
VENV_PY := ../.venv/bin/python3
GENOMES := $(wildcard genomes/*.fna.gz)
# SPECIMENS, SPECIES, and the full dependency graph are generated by
# make_deps.py from the genome FASTA headers — like .d files in C.
# Make rebuilds deps.mk whenever genomes/ changes and restarts.
-include deps.mk
REF_NPZS := $(SPECIMENS:%=reference_index/%.npz)
PRESENCE_DONE := $(SPECIMENS:%=specimen_index_presence/%/index.done)
PRESENCE_STATS := $(SPECIMENS:%=stats/indexing_presence/%.stats)
COUNT_DONE := $(SPECIMENS:%=specimen_index_count/%/index.done)
COUNT_STATS := $(SPECIMENS:%=stats/indexing_count/%.stats)
VERIFY_PRESENCE_STATS := $(SPECIMENS:%=stats/verify_presence/%.stats)
VERIFY_COUNT_STATS := $(SPECIMENS:%=stats/verify_count/%.stats)
SPECIFIC_PRESENCE_DONE := $(SPECIES:%=specific_index_presence/%/index.done)
SPECIFIC_PRESENCE_STATS := $(SPECIES:%=stats/specific_kmer_presence/%.stats)
SPECIFIC_COUNT_DONE := $(SPECIES:%=specific_index_count/%/index.done)
SPECIFIC_COUNT_STATS := $(SPECIES:%=stats/specific_kmer_count/%.stats)
SIMULATED_READS := $(foreach s,$(SPECIMENS),simulated_data/$(subst --,/,$s)/reads_R1.fastq.gz)
.NOTPARALLEL:
.PHONY: all simulate reference \
index_presence index_count \
aggregate_index_presence aggregate_index_count \
merge_presence merge_count \
verify_presence verify_count \
aggregate_verify_presence aggregate_verify_count \
verify_merge_presence verify_merge_count \
filter_presence filter_count \
aggregate_filter_presence aggregate_filter_count
verify_merge_presence: stats/verify_merge_presence/current.csv
verify_merge_count: stats/verify_merge_count/current.csv
all: aggregate_verify_presence aggregate_verify_count \
verify_merge_presence verify_merge_count \
aggregate_filter_presence aggregate_filter_count
# ── dependency file ───────────────────────────────────────────────────────────
deps.mk: $(GENOMES)
$(VENV_PY) make_deps.py $^ > $@
# ── simulation ────────────────────────────────────────────────────────────────
# Prerequisites (genome → reads) are in deps.mk; $< is the genome file.
$(SIMULATED_READS):
bash simulate_one.sh $< $(dir $@)
simulate: $(SIMULATED_READS)
# ── reference kmer sets ───────────────────────────────────────────────────────
# Prerequisites (reads → npz) are in deps.mk.
reference_index/%.npz:
bash build_reference.sh $*
reference: $(REF_NPZS)
# ── per-specimen indexing ─────────────────────────────────────────────────────
# Prerequisites (reads → index.done + .stats) are in deps.mk.
specimen_index_presence/%/index.done \
stats/indexing_presence/%.stats &: $(BINARY)
bash index_one_presence.sh $*
specimen_index_count/%/index.done \
stats/indexing_count/%.stats &: $(BINARY)
bash index_one_count.sh $*
index_presence: $(PRESENCE_DONE)
index_count: $(COUNT_DONE)
# ── indexing stats aggregation ────────────────────────────────────────────────
aggregate_index_presence: $(PRESENCE_STATS)
bash aggregate_stats.sh indexing_presence
aggregate_index_count: $(COUNT_STATS)
bash aggregate_stats.sh indexing_count
# ── global merge ──────────────────────────────────────────────────────────────
global_index_presence/index.done: $(PRESENCE_DONE) $(BINARY)
bash merge_presence.sh
global_index_count/index.done: $(COUNT_DONE) $(BINARY)
bash merge_count.sh
merge_presence: global_index_presence/index.done
merge_count: global_index_count/index.done
# ── per-specimen verification ─────────────────────────────────────────────────
# Prerequisites (index.done + npz → .stats) are in deps.mk.
stats/verify_presence/%.stats:
bash verify_one_presence.sh $*
stats/verify_count/%.stats:
bash verify_one_count.sh $*
verify_presence: $(VERIFY_PRESENCE_STATS)
verify_count: $(VERIFY_COUNT_STATS)
# ── verification stats aggregation ───────────────────────────────────────────
aggregate_verify_presence: $(VERIFY_PRESENCE_STATS)
bash aggregate_stats.sh verify_presence
aggregate_verify_count: $(VERIFY_COUNT_STATS)
bash aggregate_stats.sh verify_count
# ── species-specific indexes ──────────────────────────────────────────────────
# Prerequisites (global index → specific index) are in deps.mk.
specific_index_presence/%/index.done \
stats/specific_kmer_presence/%.stats &: $(BINARY)
bash filter_one_presence.sh $*
specific_index_count/%/index.done \
stats/specific_kmer_count/%.stats &: $(BINARY)
bash filter_one_count.sh $*
filter_presence: $(SPECIFIC_PRESENCE_DONE)
filter_count: $(SPECIFIC_COUNT_DONE)
aggregate_filter_presence: $(SPECIFIC_PRESENCE_STATS)
bash aggregate_stats.sh specific_kmer_presence
aggregate_filter_count: $(SPECIFIC_COUNT_STATS)
bash aggregate_stats.sh specific_kmer_count
# ── merged index verification ─────────────────────────────────────────────────
stats/verify_merge_presence/current.csv: $(REF_NPZS) global_index_presence/index.done
bash verify_merge_presence.sh
stats/verify_merge_count/current.csv: $(REF_NPZS) global_index_count/index.done
bash verify_merge_count.sh
benchmark/README.md
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# Benchmark pipeline
Requires **GNU Make ≥ 4.3** (grouped targets `&:`). On macOS use `gmake`.
```
gmake all # full pipeline
gmake simulate # simulation only
gmake reference # reference kmer sets only
```
## Pipeline overview
```mermaid
flowchart TD
GENOMES["genomes/*.fna.gz"]
BIN["obikmer binary"]
GENOMES --> simulate
simulate --> simdata[("simulated_data/")]
simdata --> reference
reference --> refnpz[("reference_index/*.npz")]
subgraph presence ["Presence track"]
simdata --> index_presence
BIN --> index_presence
index_presence --> pres_done[("specimen_index_presence/")]
index_presence --> pres_istats[("stats/indexing_presence/")]
pres_istats --> aggregate_index_presence
pres_done --> merge_presence
BIN --> merge_presence
merge_presence --> gpres[("global_index_presence/")]
refnpz --> verify_presence
pres_done --> verify_presence
verify_presence --> vpres_stats[("stats/verify_presence/")]
vpres_stats --> aggregate_verify_presence
gpres --> filter_presence
BIN --> filter_presence
filter_presence --> spec_pres[("specific_index_presence/")]
filter_presence --> spec_pres_stats[("stats/specific_kmer_presence/")]
spec_pres_stats --> aggregate_filter_presence
refnpz --> verify_merge_presence
gpres --> verify_merge_presence
verify_merge_presence --> vmp[("stats/verify_merge_presence/")]
end
subgraph count ["Count track"]
simdata --> index_count
BIN --> index_count
index_count --> count_done[("specimen_index_count/")]
index_count --> count_istats[("stats/indexing_count/")]
count_istats --> aggregate_index_count
count_done --> merge_count
BIN --> merge_count
merge_count --> gcount[("global_index_count/")]
refnpz --> verify_count
count_done --> verify_count
verify_count --> vcount_stats[("stats/verify_count/")]
vcount_stats --> aggregate_verify_count
gcount --> filter_count
BIN --> filter_count
filter_count --> spec_count[("specific_index_count/")]
filter_count --> spec_count_stats[("stats/specific_kmer_count/")]
spec_count_stats --> aggregate_filter_count
refnpz --> verify_merge_count
gcount --> verify_merge_count
verify_merge_count --> vmc[("stats/verify_merge_count/")]
end
aggregate_verify_presence --> all
aggregate_verify_count --> all
vmp --> all
vmc --> all
all -. "$(MAKE) re-eval" .-> aggregate_filter_presence
all -. "$(MAKE) re-eval" .-> aggregate_filter_count
```
## Steps
| Target | Script | Description |
|---|---|---|
| `simulate` | `simulate.sh` | Simulate sequencing reads from the reference genomes |
| `reference` | `build_reference.sh` | Build reference kmer sets (`.npz`) from simulation truth |
| `index_presence` | `index_one_presence.sh` | Index each specimen (presence mode) |
| `index_count` | `index_one_count.sh` | Index each specimen (count mode) |
| `aggregate_index_presence` | `aggregate_stats.sh` | Aggregate per-specimen indexing stats (presence) |
| `aggregate_index_count` | `aggregate_stats.sh` | Aggregate per-specimen indexing stats (count) |
| `merge_presence` | `merge_presence.sh` | Merge all specimen presence indexes into a global index |
| `merge_count` | `merge_count.sh` | Merge all specimen count indexes into a global index |
| `verify_presence` | `verify_one_presence.sh` | Verify each specimen presence index against reference |
| `verify_count` | `verify_one_count.sh` | Verify each specimen count index against reference |
| `aggregate_verify_presence` | `aggregate_stats.sh` | Aggregate per-specimen verification stats (presence) |
| `aggregate_verify_count` | `aggregate_stats.sh` | Aggregate per-specimen verification stats (count) |
| `filter_presence` | `filter_one_presence.sh` | Extract species-specific presence indexes from global index |
| `filter_count` | `filter_one_count.sh` | Extract species-specific count indexes from global index |
| `aggregate_filter_presence` | `aggregate_stats.sh` | Aggregate species-specific kmer stats (presence) |
| `aggregate_filter_count` | `aggregate_stats.sh` | Aggregate species-specific kmer stats (count) |
| `verify_merge_presence` | `verify_merge_presence.sh` | Verify global presence index against all reference sets |
| `verify_merge_count` | `verify_merge_count.sh` | Verify global count index against all reference sets |
## Directory layout
```
benchmark/
├── genomes/ # input reference genomes (.fna.gz)
├── simulated_data/ # generated by simulate
│ └── <species>/<specimen>/
├── reference_index/ # reference kmer sets (.npz)
├── specimen_index_presence/ # per-specimen presence indexes
├── specimen_index_count/ # per-specimen count indexes
├── global_index_presence/ # merged global presence index
├── global_index_count/ # merged global count index
├── specific_index_presence/ # species-specific presence indexes
├── specific_index_count/ # species-specific count indexes
└── stats/ # all benchmark statistics
├── indexing_presence/
├── indexing_count/
├── verify_presence/
├── verify_count/
├── specific_kmer_presence/
├── specific_kmer_count/
├── verify_merge_presence/
└── verify_merge_count/
```
benchmark/aggregate_stats.sh
Executable
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#!/usr/bin/env bash
# Usage: aggregate_stats.sh TYPE
# TYPE = indexing_presence | indexing_count | verify_presence | verify_count
#
# Reads all stats/TYPE/*.stats files (one CSV data row each, no header).
# Creates a new stats/TYPE/run_NNN.csv only if any .stats file is newer than
# the most recent run CSV (idempotent when nothing changed).
set -euo pipefail
TYPE="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
STATS_DIR="${SCRIPT_DIR}/stats/${TYPE}"
case "${TYPE}" in
indexing_presence|indexing_count)
HEADER="run,species,strain,scatter_wall_s,scatter_rss_b,dereplicate_wall_s,dereplicate_rss_b,count_kmer_wall_s,count_kmer_rss_b,index_wall_s,index_rss_b,total_wall_s,total_rss_b"
;;
verify_presence)
HEADER="run,species,strain,ref_kmers,idx_kmers,false_neg,false_pos,fn_pct,fp_pct"
;;
verify_count)
HEADER="run,species,strain,ref_kmers,idx_kmers,false_neg,false_pos,count_mismatch,fn_pct,fp_pct,cm_pct"
;;
specific_kmer_presence|specific_kmer_count)
HEADER="run,species,rebuild_wall_s,rebuild_rss_b,pack_wall_s,pack_rss_b,filter_total_wall_s,filter_total_rss_b,select_wall_s,select_rss_b,select_total_wall_s,select_total_rss_b"
;;
*)
echo "ERROR: unknown stats type '${TYPE}'" >&2
exit 1
;;
esac
# Find most recent existing run CSV (empty string if none).
latest_csv=$(find "${STATS_DIR}" -maxdepth 1 -name 'run_*.csv' 2>/dev/null | sort | tail -1)
# Check if any .stats file is newer than the latest run CSV.
if [[ -n "${latest_csv}" ]] && \
[[ -z "$(find "${STATS_DIR}" -maxdepth 1 -name '*.stats' -newer "${latest_csv}" 2>/dev/null)" ]]; then
echo "[${TYPE}] stats up to date (${latest_csv})"
exit 0
fi
run_n=$(printf '%03d' "$(find "${STATS_DIR}" -maxdepth 1 -name 'run_*.csv' 2>/dev/null | wc -l | tr -d ' ')")
CSV="${STATS_DIR}/run_${run_n}.csv"
echo "${HEADER}" >"${CSV}"
# Sort .stats files by name for reproducible row order.
while IFS= read -r stats_file; do
sed "s/^/${run_n},/" "${stats_file}"
done < <(find "${STATS_DIR}" -maxdepth 1 -name '*.stats' | sort) >>"${CSV}"
echo "[${TYPE}] run ${run_n} → ${CSV}"
benchmark/build_reference.py
Executable
+137
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#!/usr/bin/env python3
"""Build a reference kmer index from paired-end FASTQ reads.
Extracts canonical kmers — min(kmer, revcomp(kmer)) encoded as uint64 —
counts their abundances, and saves a sorted numpy pair (kmers, counts).
Output .npz arrays
kmers : uint64, sorted ascending — canonical kmer integers
counts : uint32, same order — raw read abundances
"""
import argparse
import gzip
import sys
from collections import defaultdict
import numpy as np
# ── encoding ────────────────────────────────────────────────────────────────
_ENCODE = {'A': 0, 'C': 1, 'G': 2, 'T': 3,
'a': 0, 'c': 1, 'g': 2, 't': 3}
# Lookup table: revcomp of one byte (4 bases, 8 bits).
# Precomputed once at import time.
_REVCOMP8 = [0] * 256
for _i in range(256):
_rc, _x = 0, _i
for _ in range(4):
_rc = (_rc << 2) | (3 - (_x & 3))
_x >>= 2
_REVCOMP8[_i] = _rc
del _i, _rc, _x
def revcomp_int(kmer: int, k: int) -> int:
"""Reverse-complement of a kmer encoded as an integer (2 bits/base).
Uses byte-level lookup (4 bases at a time) for speed.
"""
rc = 0
bits_left = 2 * k
while bits_left > 0:
chunk = min(8, bits_left)
rc_byte = _REVCOMP8[kmer & 0xFF] >> (8 - chunk)
rc = (rc << chunk) | rc_byte
kmer >>= chunk
bits_left -= chunk
return rc
# ── FASTQ parsing ────────────────────────────────────────────────────────────
def iter_sequences(path: str):
"""Yield raw sequences from a (gzipped) FASTQ file."""
opener = gzip.open if path.endswith('.gz') else open
with opener(path, 'rt') as fh:
while True:
if not fh.readline(): # '@' header
break
seq = fh.readline().rstrip('\n')
fh.readline() # '+'
fh.readline() # quality
yield seq
# ── kmer counting ────────────────────────────────────────────────────────────
def count_kmers(paths: list[str], k: int) -> dict[int, int]:
mask = (1 << (2 * k)) - 1
counts: dict[int, int] = defaultdict(int)
n_reads = 0
for path in paths:
for seq in iter_sequences(path):
n_reads += 1
kmer = 0
run = 0 # consecutive valid bases
for c in seq:
b = _ENCODE.get(c)
if b is None: # N or unexpected character → reset
kmer = 0
run = 0
continue
kmer = ((kmer << 2) | b) & mask
run += 1
if run >= k:
rc = revcomp_int(kmer, k)
counts[kmer if kmer <= rc else rc] += 1
if n_reads % 100_000 == 0:
print(f' {n_reads:,} reads processed, '
f'{len(counts):,} distinct kmers so far',
file=sys.stderr)
print(f' {n_reads:,} reads total, {len(counts):,} distinct kmers',
file=sys.stderr)
return counts
# ── main ─────────────────────────────────────────────────────────────────────
def main() -> None:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument('reads', nargs='+', metavar='FASTQ',
help='Input reads (FASTQ, gzip OK)')
ap.add_argument('-k', '--kmer-size', type=int, default=31,
metavar='K')
ap.add_argument('--min-abundance', type=int, default=1,
metavar='N', help='Drop kmers with count < N (default 1)')
ap.add_argument('-o', '--output', required=True,
metavar='FILE', help='Output .npz path')
args = ap.parse_args()
print(f'k={args.kmer_size} files={len(args.reads)}', file=sys.stderr)
counts = count_kmers(args.reads, args.kmer_size)
if args.min_abundance > 1:
before = len(counts)
counts = {k: v for k, v in counts.items() if v >= args.min_abundance}
print(f' min-abundance={args.min_abundance}: '
f'{before - len(counts):,} kmers dropped, '
f'{len(counts):,} retained',
file=sys.stderr)
print(f'Sorting and saving → {args.output}', file=sys.stderr)
kmers_arr = np.fromiter(sorted(counts), dtype=np.uint64, count=len(counts))
counts_arr = np.array([counts[int(k)] for k in kmers_arr], dtype=np.uint32)
np.savez_compressed(args.output, kmers=kmers_arr, counts=counts_arr)
print(f'Done {len(kmers_arr):,} kmers → {args.output}', file=sys.stderr)
if __name__ == '__main__':
main()
benchmark/build_reference.sh
Executable
+39
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@@ -0,0 +1,39 @@
#!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
SIMDATA_DIR="${SCRIPT_DIR}/simulated_data"
REF_DIR="${SCRIPT_DIR}/reference_index"
PYTHON="${SCRIPT_DIR}/../.venv/bin/python3"
BUILD_PY="${SCRIPT_DIR}/build_reference.py"
KMER_SIZE="${KMER_SIZE:-31}"
MIN_ABUNDANCE="${MIN_ABUNDANCE:-1}"
mkdir -p "${REF_DIR}"
for species_dir in "${SIMDATA_DIR}"/*/; do
[[ -d "${species_dir}" ]] || continue
species=$(basename "${species_dir}")
for strain_dir in "${species_dir}"*/; do
[[ -d "${strain_dir}" ]] || continue
strain=$(basename "${strain_dir}")
r1="${strain_dir}/reads_R1.fastq.gz"
r2="${strain_dir}/reads_R2.fastq.gz"
if [[ ! -f "${r1}" || ! -f "${r2}" ]]; then
echo "SKIP ${species}--${strain}: reads not found" >&2
continue
fi
out="${REF_DIR}/${species}--${strain}.npz"
echo "[${species}--${strain}] → ${out}"
"${PYTHON}" "${BUILD_PY}" \
--kmer-size "${KMER_SIZE}" \
--min-abundance "${MIN_ABUNDANCE}" \
--output "${out}" \
"${r1}" "${r2}"
done
done
benchmark/deps.mk
+199
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SPECIMENS := Escherichia_coli--K-12_MG1655 Escherichia_coli--EDL933 Salmonella_enterica--LT2 Escherichia_coli--CFT073 Bacillus_subtilis--168 Salmonella_enterica--P125109 Shouchella_clausii--KSM-K16 Escherichia_coli--K-12_W3110 Klebsiella_pneumoniae--MGH_78578 Opitutus_terrae--PB90-1 Saccharolobus_islandicus--M.16.4 Acidobacterium_capsulatum--ATCC_51196 Salmonella_enterica--AKU_12601 Proteus_mirabilis--HI4320 Salmonella_enterica--CT18 Klebsiella_pneumoniae--HS11286 Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1 Klebsiella_pneumoniae--ATCC_13883 Yersinia_ruckeri--YRB Candidozyma_auris--GCF_003013715.1_ASM301371v2
SPECIES := Escherichia_coli Salmonella_enterica Bacillus_subtilis Shouchella_clausii Klebsiella_pneumoniae Opitutus_terrae Saccharolobus_islandicus Acidobacterium_capsulatum Proteus_mirabilis Wolbachia_endosymbiont Yersinia_ruckeri Candidozyma_auris
# Escherichia_coli--K-12_MG1655
simulated_data/Escherichia_coli/K-12_MG1655/reads_R1.fastq.gz: genomes/GCF_000005845.2_ASM584v2_genomic.fna.gz
reference_index/Escherichia_coli--K-12_MG1655.npz: simulated_data/Escherichia_coli/K-12_MG1655/reads_R1.fastq.gz
specimen_index_presence/Escherichia_coli--K-12_MG1655/index.done stats/indexing_presence/Escherichia_coli--K-12_MG1655.stats: simulated_data/Escherichia_coli/K-12_MG1655/reads_R1.fastq.gz
specimen_index_count/Escherichia_coli--K-12_MG1655/index.done stats/indexing_count/Escherichia_coli--K-12_MG1655.stats: simulated_data/Escherichia_coli/K-12_MG1655/reads_R1.fastq.gz
stats/verify_presence/Escherichia_coli--K-12_MG1655.stats: reference_index/Escherichia_coli--K-12_MG1655.npz specimen_index_presence/Escherichia_coli--K-12_MG1655/index.done
stats/verify_count/Escherichia_coli--K-12_MG1655.stats: reference_index/Escherichia_coli--K-12_MG1655.npz specimen_index_count/Escherichia_coli--K-12_MG1655/index.done
# Escherichia_coli--EDL933
simulated_data/Escherichia_coli/EDL933/reads_R1.fastq.gz: genomes/GCF_000006665.1_ASM666v1_genomic.fna.gz
reference_index/Escherichia_coli--EDL933.npz: simulated_data/Escherichia_coli/EDL933/reads_R1.fastq.gz
specimen_index_presence/Escherichia_coli--EDL933/index.done stats/indexing_presence/Escherichia_coli--EDL933.stats: simulated_data/Escherichia_coli/EDL933/reads_R1.fastq.gz
specimen_index_count/Escherichia_coli--EDL933/index.done stats/indexing_count/Escherichia_coli--EDL933.stats: simulated_data/Escherichia_coli/EDL933/reads_R1.fastq.gz
stats/verify_presence/Escherichia_coli--EDL933.stats: reference_index/Escherichia_coli--EDL933.npz specimen_index_presence/Escherichia_coli--EDL933/index.done
stats/verify_count/Escherichia_coli--EDL933.stats: reference_index/Escherichia_coli--EDL933.npz specimen_index_count/Escherichia_coli--EDL933/index.done
# Salmonella_enterica--LT2
simulated_data/Salmonella_enterica/LT2/reads_R1.fastq.gz: genomes/GCF_000006945.2_ASM694v2_genomic.fna.gz
reference_index/Salmonella_enterica--LT2.npz: simulated_data/Salmonella_enterica/LT2/reads_R1.fastq.gz
specimen_index_presence/Salmonella_enterica--LT2/index.done stats/indexing_presence/Salmonella_enterica--LT2.stats: simulated_data/Salmonella_enterica/LT2/reads_R1.fastq.gz
specimen_index_count/Salmonella_enterica--LT2/index.done stats/indexing_count/Salmonella_enterica--LT2.stats: simulated_data/Salmonella_enterica/LT2/reads_R1.fastq.gz
stats/verify_presence/Salmonella_enterica--LT2.stats: reference_index/Salmonella_enterica--LT2.npz specimen_index_presence/Salmonella_enterica--LT2/index.done
stats/verify_count/Salmonella_enterica--LT2.stats: reference_index/Salmonella_enterica--LT2.npz specimen_index_count/Salmonella_enterica--LT2/index.done
# Escherichia_coli--CFT073
simulated_data/Escherichia_coli/CFT073/reads_R1.fastq.gz: genomes/GCF_000007445.1_ASM744v1_genomic.fna.gz
reference_index/Escherichia_coli--CFT073.npz: simulated_data/Escherichia_coli/CFT073/reads_R1.fastq.gz
specimen_index_presence/Escherichia_coli--CFT073/index.done stats/indexing_presence/Escherichia_coli--CFT073.stats: simulated_data/Escherichia_coli/CFT073/reads_R1.fastq.gz
specimen_index_count/Escherichia_coli--CFT073/index.done stats/indexing_count/Escherichia_coli--CFT073.stats: simulated_data/Escherichia_coli/CFT073/reads_R1.fastq.gz
stats/verify_presence/Escherichia_coli--CFT073.stats: reference_index/Escherichia_coli--CFT073.npz specimen_index_presence/Escherichia_coli--CFT073/index.done
stats/verify_count/Escherichia_coli--CFT073.stats: reference_index/Escherichia_coli--CFT073.npz specimen_index_count/Escherichia_coli--CFT073/index.done
# Bacillus_subtilis--168
simulated_data/Bacillus_subtilis/168/reads_R1.fastq.gz: genomes/GCF_000009045.1_ASM904v1_genomic.fna.gz
reference_index/Bacillus_subtilis--168.npz: simulated_data/Bacillus_subtilis/168/reads_R1.fastq.gz
specimen_index_presence/Bacillus_subtilis--168/index.done stats/indexing_presence/Bacillus_subtilis--168.stats: simulated_data/Bacillus_subtilis/168/reads_R1.fastq.gz
specimen_index_count/Bacillus_subtilis--168/index.done stats/indexing_count/Bacillus_subtilis--168.stats: simulated_data/Bacillus_subtilis/168/reads_R1.fastq.gz
stats/verify_presence/Bacillus_subtilis--168.stats: reference_index/Bacillus_subtilis--168.npz specimen_index_presence/Bacillus_subtilis--168/index.done
stats/verify_count/Bacillus_subtilis--168.stats: reference_index/Bacillus_subtilis--168.npz specimen_index_count/Bacillus_subtilis--168/index.done
# Salmonella_enterica--P125109
simulated_data/Salmonella_enterica/P125109/reads_R1.fastq.gz: genomes/GCF_000009505.1_ASM950v1_genomic.fna.gz
reference_index/Salmonella_enterica--P125109.npz: simulated_data/Salmonella_enterica/P125109/reads_R1.fastq.gz
specimen_index_presence/Salmonella_enterica--P125109/index.done stats/indexing_presence/Salmonella_enterica--P125109.stats: simulated_data/Salmonella_enterica/P125109/reads_R1.fastq.gz
specimen_index_count/Salmonella_enterica--P125109/index.done stats/indexing_count/Salmonella_enterica--P125109.stats: simulated_data/Salmonella_enterica/P125109/reads_R1.fastq.gz
stats/verify_presence/Salmonella_enterica--P125109.stats: reference_index/Salmonella_enterica--P125109.npz specimen_index_presence/Salmonella_enterica--P125109/index.done
stats/verify_count/Salmonella_enterica--P125109.stats: reference_index/Salmonella_enterica--P125109.npz specimen_index_count/Salmonella_enterica--P125109/index.done
# Shouchella_clausii--KSM-K16
simulated_data/Shouchella_clausii/KSM-K16/reads_R1.fastq.gz: genomes/GCF_000009825.1_ASM982v1_genomic.fna.gz
reference_index/Shouchella_clausii--KSM-K16.npz: simulated_data/Shouchella_clausii/KSM-K16/reads_R1.fastq.gz
specimen_index_presence/Shouchella_clausii--KSM-K16/index.done stats/indexing_presence/Shouchella_clausii--KSM-K16.stats: simulated_data/Shouchella_clausii/KSM-K16/reads_R1.fastq.gz
specimen_index_count/Shouchella_clausii--KSM-K16/index.done stats/indexing_count/Shouchella_clausii--KSM-K16.stats: simulated_data/Shouchella_clausii/KSM-K16/reads_R1.fastq.gz
stats/verify_presence/Shouchella_clausii--KSM-K16.stats: reference_index/Shouchella_clausii--KSM-K16.npz specimen_index_presence/Shouchella_clausii--KSM-K16/index.done
stats/verify_count/Shouchella_clausii--KSM-K16.stats: reference_index/Shouchella_clausii--KSM-K16.npz specimen_index_count/Shouchella_clausii--KSM-K16/index.done
# Escherichia_coli--K-12_W3110
simulated_data/Escherichia_coli/K-12_W3110/reads_R1.fastq.gz: genomes/GCF_000010245.2_ASM1024v1_genomic.fna.gz
reference_index/Escherichia_coli--K-12_W3110.npz: simulated_data/Escherichia_coli/K-12_W3110/reads_R1.fastq.gz
specimen_index_presence/Escherichia_coli--K-12_W3110/index.done stats/indexing_presence/Escherichia_coli--K-12_W3110.stats: simulated_data/Escherichia_coli/K-12_W3110/reads_R1.fastq.gz
specimen_index_count/Escherichia_coli--K-12_W3110/index.done stats/indexing_count/Escherichia_coli--K-12_W3110.stats: simulated_data/Escherichia_coli/K-12_W3110/reads_R1.fastq.gz
stats/verify_presence/Escherichia_coli--K-12_W3110.stats: reference_index/Escherichia_coli--K-12_W3110.npz specimen_index_presence/Escherichia_coli--K-12_W3110/index.done
stats/verify_count/Escherichia_coli--K-12_W3110.stats: reference_index/Escherichia_coli--K-12_W3110.npz specimen_index_count/Escherichia_coli--K-12_W3110/index.done
# Klebsiella_pneumoniae--MGH_78578
simulated_data/Klebsiella_pneumoniae/MGH_78578/reads_R1.fastq.gz: genomes/GCF_000016305.1_ASM1630v1_genomic.fna.gz
reference_index/Klebsiella_pneumoniae--MGH_78578.npz: simulated_data/Klebsiella_pneumoniae/MGH_78578/reads_R1.fastq.gz
specimen_index_presence/Klebsiella_pneumoniae--MGH_78578/index.done stats/indexing_presence/Klebsiella_pneumoniae--MGH_78578.stats: simulated_data/Klebsiella_pneumoniae/MGH_78578/reads_R1.fastq.gz
specimen_index_count/Klebsiella_pneumoniae--MGH_78578/index.done stats/indexing_count/Klebsiella_pneumoniae--MGH_78578.stats: simulated_data/Klebsiella_pneumoniae/MGH_78578/reads_R1.fastq.gz
stats/verify_presence/Klebsiella_pneumoniae--MGH_78578.stats: reference_index/Klebsiella_pneumoniae--MGH_78578.npz specimen_index_presence/Klebsiella_pneumoniae--MGH_78578/index.done
stats/verify_count/Klebsiella_pneumoniae--MGH_78578.stats: reference_index/Klebsiella_pneumoniae--MGH_78578.npz specimen_index_count/Klebsiella_pneumoniae--MGH_78578/index.done
# Opitutus_terrae--PB90-1
simulated_data/Opitutus_terrae/PB90-1/reads_R1.fastq.gz: genomes/GCF_000019965.1_ASM1996v1_genomic.fna.gz
reference_index/Opitutus_terrae--PB90-1.npz: simulated_data/Opitutus_terrae/PB90-1/reads_R1.fastq.gz
specimen_index_presence/Opitutus_terrae--PB90-1/index.done stats/indexing_presence/Opitutus_terrae--PB90-1.stats: simulated_data/Opitutus_terrae/PB90-1/reads_R1.fastq.gz
specimen_index_count/Opitutus_terrae--PB90-1/index.done stats/indexing_count/Opitutus_terrae--PB90-1.stats: simulated_data/Opitutus_terrae/PB90-1/reads_R1.fastq.gz
stats/verify_presence/Opitutus_terrae--PB90-1.stats: reference_index/Opitutus_terrae--PB90-1.npz specimen_index_presence/Opitutus_terrae--PB90-1/index.done
stats/verify_count/Opitutus_terrae--PB90-1.stats: reference_index/Opitutus_terrae--PB90-1.npz specimen_index_count/Opitutus_terrae--PB90-1/index.done
# Saccharolobus_islandicus--M.16.4
simulated_data/Saccharolobus_islandicus/M.16.4/reads_R1.fastq.gz: genomes/GCF_000022445.1_ASM2244v1_genomic.fna.gz
reference_index/Saccharolobus_islandicus--M.16.4.npz: simulated_data/Saccharolobus_islandicus/M.16.4/reads_R1.fastq.gz
specimen_index_presence/Saccharolobus_islandicus--M.16.4/index.done stats/indexing_presence/Saccharolobus_islandicus--M.16.4.stats: simulated_data/Saccharolobus_islandicus/M.16.4/reads_R1.fastq.gz
specimen_index_count/Saccharolobus_islandicus--M.16.4/index.done stats/indexing_count/Saccharolobus_islandicus--M.16.4.stats: simulated_data/Saccharolobus_islandicus/M.16.4/reads_R1.fastq.gz
stats/verify_presence/Saccharolobus_islandicus--M.16.4.stats: reference_index/Saccharolobus_islandicus--M.16.4.npz specimen_index_presence/Saccharolobus_islandicus--M.16.4/index.done
stats/verify_count/Saccharolobus_islandicus--M.16.4.stats: reference_index/Saccharolobus_islandicus--M.16.4.npz specimen_index_count/Saccharolobus_islandicus--M.16.4/index.done
# Acidobacterium_capsulatum--ATCC_51196
simulated_data/Acidobacterium_capsulatum/ATCC_51196/reads_R1.fastq.gz: genomes/GCF_000022565.1_ASM2256v1_genomic.fna.gz
reference_index/Acidobacterium_capsulatum--ATCC_51196.npz: simulated_data/Acidobacterium_capsulatum/ATCC_51196/reads_R1.fastq.gz
specimen_index_presence/Acidobacterium_capsulatum--ATCC_51196/index.done stats/indexing_presence/Acidobacterium_capsulatum--ATCC_51196.stats: simulated_data/Acidobacterium_capsulatum/ATCC_51196/reads_R1.fastq.gz
specimen_index_count/Acidobacterium_capsulatum--ATCC_51196/index.done stats/indexing_count/Acidobacterium_capsulatum--ATCC_51196.stats: simulated_data/Acidobacterium_capsulatum/ATCC_51196/reads_R1.fastq.gz
stats/verify_presence/Acidobacterium_capsulatum--ATCC_51196.stats: reference_index/Acidobacterium_capsulatum--ATCC_51196.npz specimen_index_presence/Acidobacterium_capsulatum--ATCC_51196/index.done
stats/verify_count/Acidobacterium_capsulatum--ATCC_51196.stats: reference_index/Acidobacterium_capsulatum--ATCC_51196.npz specimen_index_count/Acidobacterium_capsulatum--ATCC_51196/index.done
# Salmonella_enterica--AKU_12601
simulated_data/Salmonella_enterica/AKU_12601/reads_R1.fastq.gz: genomes/GCF_000026565.1_ASM2656v1_genomic.fna.gz
reference_index/Salmonella_enterica--AKU_12601.npz: simulated_data/Salmonella_enterica/AKU_12601/reads_R1.fastq.gz
specimen_index_presence/Salmonella_enterica--AKU_12601/index.done stats/indexing_presence/Salmonella_enterica--AKU_12601.stats: simulated_data/Salmonella_enterica/AKU_12601/reads_R1.fastq.gz
specimen_index_count/Salmonella_enterica--AKU_12601/index.done stats/indexing_count/Salmonella_enterica--AKU_12601.stats: simulated_data/Salmonella_enterica/AKU_12601/reads_R1.fastq.gz
stats/verify_presence/Salmonella_enterica--AKU_12601.stats: reference_index/Salmonella_enterica--AKU_12601.npz specimen_index_presence/Salmonella_enterica--AKU_12601/index.done
stats/verify_count/Salmonella_enterica--AKU_12601.stats: reference_index/Salmonella_enterica--AKU_12601.npz specimen_index_count/Salmonella_enterica--AKU_12601/index.done
# Proteus_mirabilis--HI4320
simulated_data/Proteus_mirabilis/HI4320/reads_R1.fastq.gz: genomes/GCF_000069965.1_ASM6996v1_genomic.fna.gz
reference_index/Proteus_mirabilis--HI4320.npz: simulated_data/Proteus_mirabilis/HI4320/reads_R1.fastq.gz
specimen_index_presence/Proteus_mirabilis--HI4320/index.done stats/indexing_presence/Proteus_mirabilis--HI4320.stats: simulated_data/Proteus_mirabilis/HI4320/reads_R1.fastq.gz
specimen_index_count/Proteus_mirabilis--HI4320/index.done stats/indexing_count/Proteus_mirabilis--HI4320.stats: simulated_data/Proteus_mirabilis/HI4320/reads_R1.fastq.gz
stats/verify_presence/Proteus_mirabilis--HI4320.stats: reference_index/Proteus_mirabilis--HI4320.npz specimen_index_presence/Proteus_mirabilis--HI4320/index.done
stats/verify_count/Proteus_mirabilis--HI4320.stats: reference_index/Proteus_mirabilis--HI4320.npz specimen_index_count/Proteus_mirabilis--HI4320/index.done
# Salmonella_enterica--CT18
simulated_data/Salmonella_enterica/CT18/reads_R1.fastq.gz: genomes/GCF_000195995.1_ASM19599v1_genomic.fna.gz
reference_index/Salmonella_enterica--CT18.npz: simulated_data/Salmonella_enterica/CT18/reads_R1.fastq.gz
specimen_index_presence/Salmonella_enterica--CT18/index.done stats/indexing_presence/Salmonella_enterica--CT18.stats: simulated_data/Salmonella_enterica/CT18/reads_R1.fastq.gz
specimen_index_count/Salmonella_enterica--CT18/index.done stats/indexing_count/Salmonella_enterica--CT18.stats: simulated_data/Salmonella_enterica/CT18/reads_R1.fastq.gz
stats/verify_presence/Salmonella_enterica--CT18.stats: reference_index/Salmonella_enterica--CT18.npz specimen_index_presence/Salmonella_enterica--CT18/index.done
stats/verify_count/Salmonella_enterica--CT18.stats: reference_index/Salmonella_enterica--CT18.npz specimen_index_count/Salmonella_enterica--CT18/index.done
# Klebsiella_pneumoniae--HS11286
simulated_data/Klebsiella_pneumoniae/HS11286/reads_R1.fastq.gz: genomes/GCF_000240185.1_ASM24018v2_genomic.fna.gz
reference_index/Klebsiella_pneumoniae--HS11286.npz: simulated_data/Klebsiella_pneumoniae/HS11286/reads_R1.fastq.gz
specimen_index_presence/Klebsiella_pneumoniae--HS11286/index.done stats/indexing_presence/Klebsiella_pneumoniae--HS11286.stats: simulated_data/Klebsiella_pneumoniae/HS11286/reads_R1.fastq.gz
specimen_index_count/Klebsiella_pneumoniae--HS11286/index.done stats/indexing_count/Klebsiella_pneumoniae--HS11286.stats: simulated_data/Klebsiella_pneumoniae/HS11286/reads_R1.fastq.gz
stats/verify_presence/Klebsiella_pneumoniae--HS11286.stats: reference_index/Klebsiella_pneumoniae--HS11286.npz specimen_index_presence/Klebsiella_pneumoniae--HS11286/index.done
stats/verify_count/Klebsiella_pneumoniae--HS11286.stats: reference_index/Klebsiella_pneumoniae--HS11286.npz specimen_index_count/Klebsiella_pneumoniae--HS11286/index.done
# Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1
simulated_data/Wolbachia_endosymbiont/GCF_000306885.1_ASM30688v1/reads_R1.fastq.gz: genomes/GCF_000306885.1_ASM30688v1_genomic.fna.gz
reference_index/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.npz: simulated_data/Wolbachia_endosymbiont/GCF_000306885.1_ASM30688v1/reads_R1.fastq.gz
specimen_index_presence/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1/index.done stats/indexing_presence/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.stats: simulated_data/Wolbachia_endosymbiont/GCF_000306885.1_ASM30688v1/reads_R1.fastq.gz
specimen_index_count/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1/index.done stats/indexing_count/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.stats: simulated_data/Wolbachia_endosymbiont/GCF_000306885.1_ASM30688v1/reads_R1.fastq.gz
stats/verify_presence/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.stats: reference_index/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.npz specimen_index_presence/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1/index.done
stats/verify_count/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.stats: reference_index/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1.npz specimen_index_count/Wolbachia_endosymbiont--GCF_000306885.1_ASM30688v1/index.done
# Klebsiella_pneumoniae--ATCC_13883
simulated_data/Klebsiella_pneumoniae/ATCC_13883/reads_R1.fastq.gz: genomes/GCF_000742135.1_ASM74213v1_genomic.fna.gz
reference_index/Klebsiella_pneumoniae--ATCC_13883.npz: simulated_data/Klebsiella_pneumoniae/ATCC_13883/reads_R1.fastq.gz
specimen_index_presence/Klebsiella_pneumoniae--ATCC_13883/index.done stats/indexing_presence/Klebsiella_pneumoniae--ATCC_13883.stats: simulated_data/Klebsiella_pneumoniae/ATCC_13883/reads_R1.fastq.gz
specimen_index_count/Klebsiella_pneumoniae--ATCC_13883/index.done stats/indexing_count/Klebsiella_pneumoniae--ATCC_13883.stats: simulated_data/Klebsiella_pneumoniae/ATCC_13883/reads_R1.fastq.gz
stats/verify_presence/Klebsiella_pneumoniae--ATCC_13883.stats: reference_index/Klebsiella_pneumoniae--ATCC_13883.npz specimen_index_presence/Klebsiella_pneumoniae--ATCC_13883/index.done
stats/verify_count/Klebsiella_pneumoniae--ATCC_13883.stats: reference_index/Klebsiella_pneumoniae--ATCC_13883.npz specimen_index_count/Klebsiella_pneumoniae--ATCC_13883/index.done
# Yersinia_ruckeri--YRB
simulated_data/Yersinia_ruckeri/YRB/reads_R1.fastq.gz: genomes/GCF_000834255.1_ASM83425v1_genomic.fna.gz
reference_index/Yersinia_ruckeri--YRB.npz: simulated_data/Yersinia_ruckeri/YRB/reads_R1.fastq.gz
specimen_index_presence/Yersinia_ruckeri--YRB/index.done stats/indexing_presence/Yersinia_ruckeri--YRB.stats: simulated_data/Yersinia_ruckeri/YRB/reads_R1.fastq.gz
specimen_index_count/Yersinia_ruckeri--YRB/index.done stats/indexing_count/Yersinia_ruckeri--YRB.stats: simulated_data/Yersinia_ruckeri/YRB/reads_R1.fastq.gz
stats/verify_presence/Yersinia_ruckeri--YRB.stats: reference_index/Yersinia_ruckeri--YRB.npz specimen_index_presence/Yersinia_ruckeri--YRB/index.done
stats/verify_count/Yersinia_ruckeri--YRB.stats: reference_index/Yersinia_ruckeri--YRB.npz specimen_index_count/Yersinia_ruckeri--YRB/index.done
# Candidozyma_auris--GCF_003013715.1_ASM301371v2
simulated_data/Candidozyma_auris/GCF_003013715.1_ASM301371v2/reads_R1.fastq.gz: genomes/GCF_003013715.1_ASM301371v2_genomic.fna.gz
reference_index/Candidozyma_auris--GCF_003013715.1_ASM301371v2.npz: simulated_data/Candidozyma_auris/GCF_003013715.1_ASM301371v2/reads_R1.fastq.gz
specimen_index_presence/Candidozyma_auris--GCF_003013715.1_ASM301371v2/index.done stats/indexing_presence/Candidozyma_auris--GCF_003013715.1_ASM301371v2.stats: simulated_data/Candidozyma_auris/GCF_003013715.1_ASM301371v2/reads_R1.fastq.gz
specimen_index_count/Candidozyma_auris--GCF_003013715.1_ASM301371v2/index.done stats/indexing_count/Candidozyma_auris--GCF_003013715.1_ASM301371v2.stats: simulated_data/Candidozyma_auris/GCF_003013715.1_ASM301371v2/reads_R1.fastq.gz
stats/verify_presence/Candidozyma_auris--GCF_003013715.1_ASM301371v2.stats: reference_index/Candidozyma_auris--GCF_003013715.1_ASM301371v2.npz specimen_index_presence/Candidozyma_auris--GCF_003013715.1_ASM301371v2/index.done
stats/verify_count/Candidozyma_auris--GCF_003013715.1_ASM301371v2.stats: reference_index/Candidozyma_auris--GCF_003013715.1_ASM301371v2.npz specimen_index_count/Candidozyma_auris--GCF_003013715.1_ASM301371v2/index.done
# Escherichia_coli
specific_index_presence/Escherichia_coli/index.done stats/specific_kmer_presence/Escherichia_coli.stats: global_index_presence/index.done
specific_index_count/Escherichia_coli/index.done stats/specific_kmer_count/Escherichia_coli.stats: global_index_count/index.done
# Salmonella_enterica
specific_index_presence/Salmonella_enterica/index.done stats/specific_kmer_presence/Salmonella_enterica.stats: global_index_presence/index.done
specific_index_count/Salmonella_enterica/index.done stats/specific_kmer_count/Salmonella_enterica.stats: global_index_count/index.done
# Bacillus_subtilis
specific_index_presence/Bacillus_subtilis/index.done stats/specific_kmer_presence/Bacillus_subtilis.stats: global_index_presence/index.done
specific_index_count/Bacillus_subtilis/index.done stats/specific_kmer_count/Bacillus_subtilis.stats: global_index_count/index.done
# Shouchella_clausii
specific_index_presence/Shouchella_clausii/index.done stats/specific_kmer_presence/Shouchella_clausii.stats: global_index_presence/index.done
specific_index_count/Shouchella_clausii/index.done stats/specific_kmer_count/Shouchella_clausii.stats: global_index_count/index.done
# Klebsiella_pneumoniae
specific_index_presence/Klebsiella_pneumoniae/index.done stats/specific_kmer_presence/Klebsiella_pneumoniae.stats: global_index_presence/index.done
specific_index_count/Klebsiella_pneumoniae/index.done stats/specific_kmer_count/Klebsiella_pneumoniae.stats: global_index_count/index.done
# Opitutus_terrae
specific_index_presence/Opitutus_terrae/index.done stats/specific_kmer_presence/Opitutus_terrae.stats: global_index_presence/index.done
specific_index_count/Opitutus_terrae/index.done stats/specific_kmer_count/Opitutus_terrae.stats: global_index_count/index.done
# Saccharolobus_islandicus
specific_index_presence/Saccharolobus_islandicus/index.done stats/specific_kmer_presence/Saccharolobus_islandicus.stats: global_index_presence/index.done
specific_index_count/Saccharolobus_islandicus/index.done stats/specific_kmer_count/Saccharolobus_islandicus.stats: global_index_count/index.done
# Acidobacterium_capsulatum
specific_index_presence/Acidobacterium_capsulatum/index.done stats/specific_kmer_presence/Acidobacterium_capsulatum.stats: global_index_presence/index.done
specific_index_count/Acidobacterium_capsulatum/index.done stats/specific_kmer_count/Acidobacterium_capsulatum.stats: global_index_count/index.done
# Proteus_mirabilis
specific_index_presence/Proteus_mirabilis/index.done stats/specific_kmer_presence/Proteus_mirabilis.stats: global_index_presence/index.done
specific_index_count/Proteus_mirabilis/index.done stats/specific_kmer_count/Proteus_mirabilis.stats: global_index_count/index.done
# Wolbachia_endosymbiont
specific_index_presence/Wolbachia_endosymbiont/index.done stats/specific_kmer_presence/Wolbachia_endosymbiont.stats: global_index_presence/index.done
specific_index_count/Wolbachia_endosymbiont/index.done stats/specific_kmer_count/Wolbachia_endosymbiont.stats: global_index_count/index.done
# Yersinia_ruckeri
specific_index_presence/Yersinia_ruckeri/index.done stats/specific_kmer_presence/Yersinia_ruckeri.stats: global_index_presence/index.done
specific_index_count/Yersinia_ruckeri/index.done stats/specific_kmer_count/Yersinia_ruckeri.stats: global_index_count/index.done
# Candidozyma_auris
specific_index_presence/Candidozyma_auris/index.done stats/specific_kmer_presence/Candidozyma_auris.stats: global_index_presence/index.done
specific_index_count/Candidozyma_auris/index.done stats/specific_kmer_count/Candidozyma_auris.stats: global_index_count/index.done
benchmark/downloads.sh
Executable
+48
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@@ -0,0 +1,48 @@
#!/usr/bin/env bash
set -euo pipefail
assemblies=(
GCF_000005845.2
GCF_000010245.2
GCF_000007445.1
GCF_000006665.1
GCF_000006945.2
GCF_000195995.1
GCF_000009505.1
GCF_000026565.1
GCF_000016305.1
GCF_000019965.1
GCF_000240185.1
GCF_000742135.1
GCF_000069965.1
GCF_000022565.1
GCF_000306885.1
GCF_003013715.1
GCF_000009045.1
GCF_000009825.1
GCF_000022445.1
GCF_000834255.1
)
mkdir -p genomes
for acc in "${assemblies[@]}"; do
echo "Downloading ${acc}"
datasets download genome accession "${acc}" \
--include genome \
--filename "${acc}.zip"
unzip -q "${acc}.zip" -d "${acc}"
find "${acc}" -name "*.fna" |
while read file; do
obiconvert -Z ${file} >genomes/$(basename ${file}).gz
done
rm -rf "${acc}" "${acc}.zip"
done
benchmark/filter_one_count.sh
Executable
+108
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#!/usr/bin/env bash
# Usage: filter_one_count.sh SPECIES
# Filters global_index_count to keep only kmers specific to SPECIES,
# then selects the SPECIES column in-place.
# Outputs:
# specific_index_count/SPECIES/index.done (written by obikmer select)
# stats/specific_kmer_count/SPECIES.stats (one CSV data row, no header)
set -euo pipefail
SPECIES="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
SOURCE="${SCRIPT_DIR}/global_index_count"
OUTPUT="${SCRIPT_DIR}/specific_index_count/${SPECIES}"
STATS_DIR="${SCRIPT_DIR}/stats/specific_kmer_count"
STATS_FILE="${STATS_DIR}/${SPECIES}.stats"
mkdir -p "${STATS_DIR}"
echo "[${SPECIES}] filter (count) → ${OUTPUT}"
LOG_FILTER=$(mktemp)
LOG_SELECT=$(mktemp)
trap 'rm -f "${LOG_FILTER}" "${LOG_SELECT}"' EXIT
"${BINARY}" filter \
--output "${OUTPUT}" \
--force \
--ingroup "species=${SPECIES}" \
--outgroup all \
--min-frac 0.5 \
--max-frac 1.0 \
--max-outgroup-count 0 \
"${SOURCE}" \
2>"${LOG_FILTER}"
cat "${LOG_FILTER}" >&2
"${BINARY}" select \
--in-place \
--group "${SPECIES}:species=${SPECIES}" \
--group-op "${SPECIES}:any" \
--select "${SPECIES}" \
"${OUTPUT}" \
2>"${LOG_SELECT}"
cat "${LOG_SELECT}" >&2
python3 - "${SPECIES}" "${LOG_FILTER}" "${LOG_SELECT}" <<'PYEOF' >"${STATS_FILE}"
import sys, re
species, log_filter, log_select = sys.argv[1], sys.argv[2], sys.argv[3]
def strip_ansi(s):
return re.sub(r'\x1b\[[\x30-\x3f]*[\x20-\x2f]*[\x40-\x7e]', '', s)
def parse_wall(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1000.0
if s.endswith('s'): return float(s[:-1])
return 0.0
def parse_rss(s):
m = re.match(r'([\d.]+)\s*(GB|MB|KB|B)', s.strip())
if not m: return 0
return int(float(m.group(1)) * {'GB': 1<<30, 'MB': 1<<20, 'KB': 1024, 'B': 1}[m.group(2)])
def is_sep(s):
return bool(s) and not re.search(r'[A-Za-z0-9]', s)
def parse_reporter(logfile):
stats = {}
state = 'scan'
with open(logfile, errors='replace') as fh:
for raw in fh:
line = strip_ansi(raw.rstrip('\n'))
s = line.strip()
if state == 'scan':
if re.search(r'\bstage\b.*\bwall\b', line):
state = 'in_header'
elif state == 'in_header':
if is_sep(s): state = 'rows'
elif state == 'rows':
if is_sep(s): state = 'total'
elif s:
parts = re.split(r' +', s)
if len(parts) >= 4:
stats[parts[0]] = (parse_wall(parts[1]), parse_rss(parts[3]))
elif state == 'total':
if s:
parts = re.split(r' +', s)
if len(parts) >= 3:
stats['TOTAL'] = (parse_wall(parts[1]),
parse_rss(parts[3]) if len(parts) > 3 else 0)
break
return stats
f = parse_reporter(log_filter)
s = parse_reporter(log_select)
row = [species]
for stage, d in [('rebuild', f), ('pack', f), ('filter_total', f), ('select', s), ('select_total', s)]:
key = 'TOTAL' if stage.endswith('_total') else stage
w, r = d.get(key, ('', ''))
row += [f'{w:.3f}' if isinstance(w, float) else '', str(r)]
print(','.join(row))
PYEOF
benchmark/filter_one_presence.sh
Executable
+108
View File
@@ -0,0 +1,108 @@
#!/usr/bin/env bash
# Usage: filter_one_presence.sh SPECIES
# Filters global_index_presence to keep only kmers specific to SPECIES,
# then selects the SPECIES column in-place.
# Outputs:
# specific_index_presence/SPECIES/index.done (written by obikmer select)
# stats/specific_kmer_presence/SPECIES.stats (one CSV data row, no header)
set -euo pipefail
SPECIES="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
SOURCE="${SCRIPT_DIR}/global_index_presence"
OUTPUT="${SCRIPT_DIR}/specific_index_presence/${SPECIES}"
STATS_DIR="${SCRIPT_DIR}/stats/specific_kmer_presence"
STATS_FILE="${STATS_DIR}/${SPECIES}.stats"
mkdir -p "${STATS_DIR}"
echo "[${SPECIES}] filter (presence) → ${OUTPUT}"
LOG_FILTER=$(mktemp)
LOG_SELECT=$(mktemp)
trap 'rm -f "${LOG_FILTER}" "${LOG_SELECT}"' EXIT
"${BINARY}" filter \
--output "${OUTPUT}" \
--force \
--ingroup "species=${SPECIES}" \
--outgroup all \
--min-frac 0.5 \
--max-frac 1.0 \
--max-outgroup-count 0 \
"${SOURCE}" \
2>"${LOG_FILTER}"
cat "${LOG_FILTER}" >&2
"${BINARY}" select \
--in-place \
--group "${SPECIES}:species=${SPECIES}" \
--group-op "${SPECIES}:any" \
--select "${SPECIES}" \
"${OUTPUT}" \
2>"${LOG_SELECT}"
cat "${LOG_SELECT}" >&2
python3 - "${SPECIES}" "${LOG_FILTER}" "${LOG_SELECT}" <<'PYEOF' >"${STATS_FILE}"
import sys, re
species, log_filter, log_select = sys.argv[1], sys.argv[2], sys.argv[3]
def strip_ansi(s):
return re.sub(r'\x1b\[[\x30-\x3f]*[\x20-\x2f]*[\x40-\x7e]', '', s)
def parse_wall(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1000.0
if s.endswith('s'): return float(s[:-1])
return 0.0
def parse_rss(s):
m = re.match(r'([\d.]+)\s*(GB|MB|KB|B)', s.strip())
if not m: return 0
return int(float(m.group(1)) * {'GB': 1<<30, 'MB': 1<<20, 'KB': 1024, 'B': 1}[m.group(2)])
def is_sep(s):
return bool(s) and not re.search(r'[A-Za-z0-9]', s)
def parse_reporter(logfile):
stats = {}
state = 'scan'
with open(logfile, errors='replace') as fh:
for raw in fh:
line = strip_ansi(raw.rstrip('\n'))
s = line.strip()
if state == 'scan':
if re.search(r'\bstage\b.*\bwall\b', line):
state = 'in_header'
elif state == 'in_header':
if is_sep(s): state = 'rows'
elif state == 'rows':
if is_sep(s): state = 'total'
elif s:
parts = re.split(r' +', s)
if len(parts) >= 4:
stats[parts[0]] = (parse_wall(parts[1]), parse_rss(parts[3]))
elif state == 'total':
if s:
parts = re.split(r' +', s)
if len(parts) >= 3:
stats['TOTAL'] = (parse_wall(parts[1]),
parse_rss(parts[3]) if len(parts) > 3 else 0)
break
return stats
f = parse_reporter(log_filter)
s = parse_reporter(log_select)
row = [species]
for stage, d in [('rebuild', f), ('pack', f), ('filter_total', f), ('select', s), ('select_total', s)]:
key = 'TOTAL' if stage.endswith('_total') else stage
w, r = d.get(key, ('', ''))
row += [f'{w:.3f}' if isinstance(w, float) else '', str(r)]
print(','.join(row))
PYEOF
benchmark/index_one_count.sh
Executable
+103
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@@ -0,0 +1,103 @@
#!/usr/bin/env bash
# Usage: index_one_count.sh SPECIMEN
# SPECIMEN = "species--strain" (Make pattern stem)
# Outputs:
# specimen_index_count/SPECIMEN/index.done (written by obikmer)
# stats/indexing_count/SPECIMEN.stats (one CSV data row, no header)
set -euo pipefail
SPECIMEN="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
species="${SPECIMEN%%--*}"
strain="${SPECIMEN#*--}"
READS_DIR="${SCRIPT_DIR}/simulated_data/${species}/${strain}"
INDEX_PATH="${SCRIPT_DIR}/specimen_index_count/${SPECIMEN}"
STATS_DIR="${SCRIPT_DIR}/stats/indexing_count"
STATS_FILE="${STATS_DIR}/${SPECIMEN}.stats"
mkdir -p "${STATS_DIR}"
r1="${READS_DIR}/reads_R1.fastq.gz"
r2="${READS_DIR}/reads_R2.fastq.gz"
if [[ ! -f "${r1}" || ! -f "${r2}" ]]; then
echo "ERROR: reads not found in ${READS_DIR}" >&2
exit 1
fi
echo "[${SPECIMEN}] indexing (count) → ${INDEX_PATH}"
STDERR_LOG=$(mktemp)
trap 'rm -f "${STDERR_LOG}"' EXIT
"${BINARY}" index \
--output "${INDEX_PATH}" \
--force \
--theta 0 \
--with-counts \
--label "${SPECIMEN}" \
--meta "species=${species}" \
"${r1}" "${r2}" \
2>"${STDERR_LOG}"
cat "${STDERR_LOG}" >&2
python3 - "${species}" "${strain}" "${STDERR_LOG}" <<'PYEOF' >"${STATS_FILE}"
import sys, re
species, strain, logfile = sys.argv[1], sys.argv[2], sys.argv[3]
def strip_ansi(s):
return re.sub(r'\x1b\[[\x30-\x3f]*[\x20-\x2f]*[\x40-\x7e]', '', s)
def parse_wall(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1000.0
if s.endswith('s'): return float(s[:-1])
return 0.0
def parse_rss(s):
m = re.match(r'([\d.]+)\s*(GB|MB|KB|B)', s.strip())
if not m: return 0
return int(float(m.group(1)) * {'GB': 1<<30, 'MB': 1<<20, 'KB': 1024, 'B': 1}[m.group(2)])
def is_sep(s):
return bool(s) and not re.search(r'[A-Za-z0-9]', s)
stats = {}
state = 'scan'
with open(logfile, errors='replace') as fh:
for raw in fh:
line = strip_ansi(raw.rstrip('\n'))
s = line.strip()
if state == 'scan':
if re.search(r'\bstage\b.*\bwall\b', line):
state = 'in_header'
elif state == 'in_header':
if is_sep(s): state = 'rows'
elif state == 'rows':
if is_sep(s): state = 'total'
elif s:
parts = re.split(r' +', s)
if len(parts) >= 4:
stats[parts[0]] = (parse_wall(parts[1]), parse_rss(parts[3]))
elif state == 'total':
if s:
parts = re.split(r' +', s)
if len(parts) >= 3:
stats[parts[0]] = (parse_wall(parts[1]),
parse_rss(parts[3]) if len(parts) > 3 else 0)
break
STAGE_ORDER = ['scatter', 'dereplicate', 'count_kmer', 'index']
row = [species, strain]
for stage in STAGE_ORDER:
w, r = stats.get(stage, ('', ''))
row += [f'{w:.3f}' if isinstance(w, float) else '', str(r)]
tw, tr = stats.get('TOTAL', ('', ''))
row += [f'{tw:.3f}' if isinstance(tw, float) else '', str(tr)]
print(','.join(row))
PYEOF
benchmark/index_one_presence.sh
Executable
+102
View File
@@ -0,0 +1,102 @@
#!/usr/bin/env bash
# Usage: index_one_presence.sh SPECIMEN
# SPECIMEN = "species--strain" (Make pattern stem)
# Outputs:
# specimen_index_presence/SPECIMEN/index.done (written by obikmer)
# stats/indexing_presence/SPECIMEN.stats (one CSV data row, no header)
set -euo pipefail
SPECIMEN="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
species="${SPECIMEN%%--*}"
strain="${SPECIMEN#*--}"
READS_DIR="${SCRIPT_DIR}/simulated_data/${species}/${strain}"
INDEX_PATH="${SCRIPT_DIR}/specimen_index_presence/${SPECIMEN}"
STATS_DIR="${SCRIPT_DIR}/stats/indexing_presence"
STATS_FILE="${STATS_DIR}/${SPECIMEN}.stats"
mkdir -p "${STATS_DIR}"
r1="${READS_DIR}/reads_R1.fastq.gz"
r2="${READS_DIR}/reads_R2.fastq.gz"
if [[ ! -f "${r1}" || ! -f "${r2}" ]]; then
echo "ERROR: reads not found in ${READS_DIR}" >&2
exit 1
fi
echo "[${SPECIMEN}] indexing (presence) → ${INDEX_PATH}"
STDERR_LOG=$(mktemp)
trap 'rm -f "${STDERR_LOG}"' EXIT
"${BINARY}" index \
--output "${INDEX_PATH}" \
--force \
--theta 0 \
--label "${SPECIMEN}" \
--meta "species=${species}" \
"${r1}" "${r2}" \
2>"${STDERR_LOG}"
cat "${STDERR_LOG}" >&2
python3 - "${species}" "${strain}" "${STDERR_LOG}" <<'PYEOF' >"${STATS_FILE}"
import sys, re
species, strain, logfile = sys.argv[1], sys.argv[2], sys.argv[3]
def strip_ansi(s):
return re.sub(r'\x1b\[[\x30-\x3f]*[\x20-\x2f]*[\x40-\x7e]', '', s)
def parse_wall(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1000.0
if s.endswith('s'): return float(s[:-1])
return 0.0
def parse_rss(s):
m = re.match(r'([\d.]+)\s*(GB|MB|KB|B)', s.strip())
if not m: return 0
return int(float(m.group(1)) * {'GB': 1<<30, 'MB': 1<<20, 'KB': 1024, 'B': 1}[m.group(2)])
def is_sep(s):
return bool(s) and not re.search(r'[A-Za-z0-9]', s)
stats = {}
state = 'scan'
with open(logfile, errors='replace') as fh:
for raw in fh:
line = strip_ansi(raw.rstrip('\n'))
s = line.strip()
if state == 'scan':
if re.search(r'\bstage\b.*\bwall\b', line):
state = 'in_header'
elif state == 'in_header':
if is_sep(s): state = 'rows'
elif state == 'rows':
if is_sep(s): state = 'total'
elif s:
parts = re.split(r' +', s)
if len(parts) >= 4:
stats[parts[0]] = (parse_wall(parts[1]), parse_rss(parts[3]))
elif state == 'total':
if s:
parts = re.split(r' +', s)
if len(parts) >= 3:
stats[parts[0]] = (parse_wall(parts[1]),
parse_rss(parts[3]) if len(parts) > 3 else 0)
break
STAGE_ORDER = ['scatter', 'dereplicate', 'count_kmer', 'index']
row = [species, strain]
for stage in STAGE_ORDER:
w, r = stats.get(stage, ('', ''))
row += [f'{w:.3f}' if isinstance(w, float) else '', str(r)]
tw, tr = stats.get('TOTAL', ('', ''))
row += [f'{tw:.3f}' if isinstance(tw, float) else '', str(tr)]
print(','.join(row))
PYEOF
benchmark/make_deps.py
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#!/usr/bin/env python3
"""Generate deps.mk — pure dependency declarations for the benchmark pipeline.
Like C .d files: only target: prerequisites lines, no recipes.
Recipes stay in the Makefile as generic rules.
"""
import gzip
import re
import sys
from pathlib import Path
STOP_WORDS = {'complete', 'chromosome', 'whole', 'sequence', 'genome',
'endosymbiont', 'of'}
STOP_PREFIXES = ('scaffold', 'contig', 'plasmid')
def is_stop(tok):
t = tok.lower()
return t in STOP_WORDS or any(t.startswith(p) for p in STOP_PREFIXES)
def sanitize(s):
return re.sub(r'[^A-Za-z0-9._-]', '_', s).strip('_')
def collect_tokens(text):
parts = []
for tok in text.split():
tok = tok.rstrip(',.')
if is_stop(tok):
break
parts.append(sanitize(tok))
return '_'.join(filter(None, parts))
def parse_organism(defn, gcf_id):
words = defn.split()
species = sanitize(words[0] + '_' + words[1])
m = re.search(r'\bstr\.\s+(\S+)(?:\s+substr\.\s+(\S+))?', defn)
if m:
strain = sanitize(m.group(1))
if m.group(2):
strain += '_' + sanitize(m.group(2))
return species, strain
m = re.search(r'\bstrain\b\s+(.*)', defn)
if m:
strain = collect_tokens(m.group(1))
if strain:
return species, strain
remainder = re.sub(r'^\S+ \S+\s*', '', defn)
remainder = re.sub(r'^subsp\.\s+\S+\s*', '', remainder)
remainder = re.sub(r'^serovar\s+\S+\s*', '', remainder)
strain = collect_tokens(remainder)
return species, strain if strain else gcf_id
def first_definition(path):
with gzip.open(path, 'rt') as fh:
for line in fh:
if line.startswith('>'):
m = re.search(r'"definition":"([^"]*)"', line)
return m.group(1) if m else line[1:].split()[0]
return Path(path).stem
def main():
entries = [] # (specimen, species, sim_dir, genome_path)
species_seen = []
for path in sorted(sys.argv[1:]):
gcf_id = Path(path).name.replace('_genomic.fna.gz', '')
defn = first_definition(path)
sp, st = parse_organism(defn, gcf_id)
specimen = f'{sp}--{st}'
sim_dir = f'simulated_data/{sp}/{st}'
entries.append((specimen, sp, sim_dir, path))
if sp not in species_seen:
species_seen.append(sp)
specimens = [e[0] for e in entries]
print('SPECIMENS :=', ' '.join(specimens))
print('SPECIES :=', ' '.join(species_seen))
for specimen, species, sim_dir, genome in entries:
reads = f'{sim_dir}/reads_R1.fastq.gz'
p_done = f'specimen_index_presence/{specimen}/index.done'
p_stats = f'stats/indexing_presence/{specimen}.stats'
c_done = f'specimen_index_count/{specimen}/index.done'
c_stats = f'stats/indexing_count/{specimen}.stats'
ref = f'reference_index/{specimen}.npz'
vp = f'stats/verify_presence/{specimen}.stats'
vc = f'stats/verify_count/{specimen}.stats'
print()
print(f'# {specimen}')
print(f'{reads}: {genome}')
print(f'{ref}: {reads}')
print(f'{p_done} {p_stats}: {reads}')
print(f'{c_done} {c_stats}: {reads}')
print(f'{vp}: {ref} {p_done}')
print(f'{vc}: {ref} {c_done}')
print()
for sp in species_seen:
sp_done = f'specific_index_presence/{sp}/index.done'
sp_stats = f'stats/specific_kmer_presence/{sp}.stats'
sc_done = f'specific_index_count/{sp}/index.done'
sc_stats = f'stats/specific_kmer_count/{sp}.stats'
print(f'# {sp}')
print(f'{sp_done} {sp_stats}: global_index_presence/index.done')
print(f'{sc_done} {sc_stats}: global_index_count/index.done')
if __name__ == '__main__':
main()
benchmark/merge_count.sh
Executable
+103
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#!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
IDX_DIR="${SCRIPT_DIR}/specimen_index_count"
OUTPUT="${SCRIPT_DIR}/global_index_count"
STATS_DIR="${SCRIPT_DIR}/stats/merge_count"
mkdir -p "${STATS_DIR}"
run_n=$(printf '%03d' "$(find "${STATS_DIR}" -maxdepth 1 -name 'run_*.csv' | wc -l | tr -d ' ')")
CSV="${STATS_DIR}/run_${run_n}.csv"
printf 'run,n_sources,bootstrap_wall_s,bootstrap_rss_b,spectrums_wall_s,spectrums_rss_b,merge_partitions_wall_s,merge_partitions_rss_b,pack_wall_s,pack_rss_b,total_wall_s,total_rss_b\n' >"${CSV}"
parse_reporter() {
local run="$1" n_sources="$2" logfile="$3"
python3 - "$run" "$n_sources" "$logfile" <<'PYEOF'
import sys, re
run, n_sources, logfile = sys.argv[1], sys.argv[2], sys.argv[3]
def strip_ansi(s):
return re.sub(r'\x1b\[[\x30-\x3f]*[\x20-\x2f]*[\x40-\x7e]', '', s)
def parse_wall(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1000.0
if s.endswith('s'): return float(s[:-1])
return 0.0
def parse_rss(s):
m = re.match(r'([\d.]+)\s*(GB|MB|KB|B)', s.strip())
if not m: return 0
return int(float(m.group(1)) * {'GB': 1<<30, 'MB': 1<<20, 'KB': 1024, 'B': 1}[m.group(2)])
def is_sep(s):
return bool(s) and not re.search(r'[A-Za-z0-9]', s)
stats = {}
state = 'scan'
with open(logfile, errors='replace') as fh:
for raw in fh:
line = strip_ansi(raw.rstrip('\n'))
s = line.strip()
if state == 'scan':
if re.search(r'\bstage\b.*\bwall\b', line):
state = 'in_header'
elif state == 'in_header':
if is_sep(s):
state = 'rows'
elif state == 'rows':
if is_sep(s):
state = 'total'
elif s:
parts = re.split(r' +', s)
if len(parts) >= 4:
stats[parts[0]] = (parse_wall(parts[1]), parse_rss(parts[3]))
elif state == 'total':
if s:
parts = re.split(r' +', s)
if len(parts) >= 3:
stats[parts[0]] = (parse_wall(parts[1]),
parse_rss(parts[3]) if len(parts) > 3 else 0)
break
STAGE_ORDER = ['bootstrap', 'spectrums', 'merge_partitions', 'pack']
row = [run, n_sources]
for stage in STAGE_ORDER:
w, r = stats.get(stage, ('', ''))
row += [f'{w:.3f}' if isinstance(w, float) else '', str(r)]
tw, tr = stats.get('TOTAL', ('', ''))
row += [f'{tw:.3f}' if isinstance(tw, float) else '', str(tr)]
print(','.join(row))
PYEOF
}
mapfile -t sources < <(find "${IDX_DIR}" -mindepth 1 -maxdepth 1 -type d | sort)
if [[ ${#sources[@]} -eq 0 ]]; then
echo "ERROR: no indexes found in ${IDX_DIR}" >&2
exit 1
fi
echo "Merging ${#sources[@]} count indexes → ${OUTPUT}"
printf ' %s\n' "${sources[@]}"
STDERR_LOG=$(mktemp)
trap 'rm -f "${STDERR_LOG}"' EXIT
"${BINARY}" merge \
--output "${OUTPUT}" \
--force \
"${sources[@]}" \
2>"${STDERR_LOG}"
cat "${STDERR_LOG}" >&2
parse_reporter "${run_n}" "${#sources[@]}" "${STDERR_LOG}" >>"${CSV}"
echo "Done. Run ${run_n} → ${CSV}"
benchmark/merge_presence.sh
Executable
+104
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#!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
IDX_DIR="${SCRIPT_DIR}/specimen_index_presence"
OUTPUT="${SCRIPT_DIR}/global_index_presence"
STATS_DIR="${SCRIPT_DIR}/stats/merge_presence"
mkdir -p "${STATS_DIR}"
run_n=$(printf '%03d' "$(find "${STATS_DIR}" -maxdepth 1 -name 'run_*.csv' | wc -l | tr -d ' ')")
CSV="${STATS_DIR}/run_${run_n}.csv"
printf 'run,n_sources,bootstrap_wall_s,bootstrap_rss_b,spectrums_wall_s,spectrums_rss_b,merge_partitions_wall_s,merge_partitions_rss_b,pack_wall_s,pack_rss_b,total_wall_s,total_rss_b\n' >"${CSV}"
parse_reporter() {
local run="$1" n_sources="$2" logfile="$3"
python3 - "$run" "$n_sources" "$logfile" <<'PYEOF'
import sys, re
run, n_sources, logfile = sys.argv[1], sys.argv[2], sys.argv[3]
def strip_ansi(s):
return re.sub(r'\x1b\[[\x30-\x3f]*[\x20-\x2f]*[\x40-\x7e]', '', s)
def parse_wall(s):
s = s.strip()
if s.endswith('ms'): return float(s[:-2]) / 1000.0
if s.endswith('s'): return float(s[:-1])
return 0.0
def parse_rss(s):
m = re.match(r'([\d.]+)\s*(GB|MB|KB|B)', s.strip())
if not m: return 0
return int(float(m.group(1)) * {'GB': 1<<30, 'MB': 1<<20, 'KB': 1024, 'B': 1}[m.group(2)])
def is_sep(s):
return bool(s) and not re.search(r'[A-Za-z0-9]', s)
stats = {}
state = 'scan'
with open(logfile, errors='replace') as fh:
for raw in fh:
line = strip_ansi(raw.rstrip('\n'))
s = line.strip()
if state == 'scan':
if re.search(r'\bstage\b.*\bwall\b', line):
state = 'in_header'
elif state == 'in_header':
if is_sep(s):
state = 'rows'
elif state == 'rows':
if is_sep(s):
state = 'total'
elif s:
parts = re.split(r' +', s)
if len(parts) >= 4:
stats[parts[0]] = (parse_wall(parts[1]), parse_rss(parts[3]))
elif state == 'total':
if s:
parts = re.split(r' +', s)
if len(parts) >= 3:
stats[parts[0]] = (parse_wall(parts[1]),
parse_rss(parts[3]) if len(parts) > 3 else 0)
break
STAGE_ORDER = ['bootstrap', 'spectrums', 'merge_partitions', 'pack']
row = [run, n_sources]
for stage in STAGE_ORDER:
w, r = stats.get(stage, ('', ''))
row += [f'{w:.3f}' if isinstance(w, float) else '', str(r)]
tw, tr = stats.get('TOTAL', ('', ''))
row += [f'{tw:.3f}' if isinstance(tw, float) else '', str(tr)]
print(','.join(row))
PYEOF
}
mapfile -t sources < <(find "${IDX_DIR}" -mindepth 1 -maxdepth 1 -type d | sort)
if [[ ${#sources[@]} -eq 0 ]]; then
echo "ERROR: no indexes found in ${IDX_DIR}" >&2
exit 1
fi
echo "Merging ${#sources[@]} presence indexes → ${OUTPUT}"
printf ' %s\n' "${sources[@]}"
STDERR_LOG=$(mktemp)
trap 'rm -f "${STDERR_LOG}"' EXIT
"${BINARY}" merge \
--output "${OUTPUT}" \
--force \
--force-presence \
"${sources[@]}" \
2>"${STDERR_LOG}"
cat "${STDERR_LOG}" >&2
parse_reporter "${run_n}" "${#sources[@]}" "${STDERR_LOG}" >>"${CSV}"
echo "Done. Run ${run_n} → ${CSV}"
benchmark/simulate.sh
Executable
+12
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#!/usr/bin/env bash
# Simulate all genomes. Delegates to simulate_one.sh per genome.
# Prefer running via `gmake simulate` which handles individual dependencies.
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
for genome_file in "${SCRIPT_DIR}"/genomes/*.fna.gz; do
out_dir=$("${SCRIPT_DIR}/../.venv/bin/python3" "${SCRIPT_DIR}/make_deps.py" \
--dir-for "${genome_file}")
bash "${SCRIPT_DIR}/simulate_one.sh" "${genome_file}" "${out_dir}"
done
benchmark/simulate_one.sh
+33
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#!/usr/bin/env bash
# Usage: simulate_one.sh genome.fna.gz output_dir
# Simulates paired-end HiSeq reads for a single genome.
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
ISS="${SCRIPT_DIR}/../.venv/bin/iss"
COVERAGE=15
READ_LENGTH=150
CPUS="${CPUS:-$(sysctl -n hw.logicalcpu 2>/dev/null || nproc 2>/dev/null || echo 2)}"
genome_file="$1"
out_dir="$2"
mkdir -p "${out_dir}"
tmp_fasta=$(mktemp "${TMPDIR:-/tmp}/obikmer_XXXXXX.fna")
trap 'rm -f "${tmp_fasta}"' EXIT
gzip -dc "${genome_file}" > "${tmp_fasta}"
genome_size=$(grep -v "^>" "${tmp_fasta}" | tr -d '[:space:]' | wc -c | tr -d ' ')
n_reads=$(python3 -c "import math; print(math.ceil(${COVERAGE} * ${genome_size} / (2 * ${READ_LENGTH})))")
echo "[${out_dir}] genome=${genome_size} bp → ${n_reads} read pairs (${COVERAGE}x HiSeq)"
"${ISS}" generate \
--genomes "${tmp_fasta}" \
--model HiSeq \
--n_reads "${n_reads}" \
--cpus "${CPUS}" \
--compress \
--output "${out_dir}/reads"
benchmark/verify_count.py
Executable
+181
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#!/usr/bin/env python3
"""Compare an obikmer count index against a reference kmer set (presence + counts).
Loads the reference .npz (sorted uint64 kmers + uint32 counts from build_reference.py),
streams `obikmer dump` from a --with-counts index, then reports:
- false negatives : kmers in reference absent from the index
- false positives : kmers in the index absent from the reference
- count mismatches: kmers present in both but with differing counts
Output to stdout: one CSV row
species,strain,ref_kmers,idx_kmers,false_neg,false_pos,count_mismatch,
fn_pct,fp_pct,cm_pct
"""
import argparse
import subprocess
import sys
import numpy as np
# ── encoding ──────────────────────────────────────────────────────────────────
_ENCODE = {'A': 0, 'C': 1, 'G': 2, 'T': 3,
'a': 0, 'c': 1, 'g': 2, 't': 3}
_DECODE = ['A', 'C', 'G', 'T']
def encode_kmer(s: str) -> int:
kmer = 0
for c in s:
kmer = (kmer << 2) | _ENCODE[c]
return kmer
def decode_kmer(val: int, k: int) -> str:
bases = []
for _ in range(k):
bases.append(_DECODE[val & 3])
val >>= 2
return ''.join(reversed(bases))
# ── dump parsing ──────────────────────────────────────────────────────────────
def load_index(obikmer_bin: str, index_dir: str) -> tuple[np.ndarray, np.ndarray]:
"""Stream `obikmer dump` and return (kmers_sorted_uint64, counts_uint32)."""
cmd = [obikmer_bin, 'dump', index_dir]
proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL,
text=True)
kmers, counts = [], []
header = True
for line in proc.stdout:
if header:
header = False
continue
parts = line.rstrip('\n').split(',')
kmers.append(encode_kmer(parts[0]))
counts.append(int(parts[1]))
proc.wait()
if proc.returncode != 0:
print(f'ERROR: obikmer dump exited {proc.returncode}', file=sys.stderr)
sys.exit(1)
order = np.argsort(np.array(kmers, dtype=np.uint64), kind='stable')
return (np.array(kmers, dtype=np.uint64)[order],
np.array(counts, dtype=np.uint32)[order])
# ── comparison ────────────────────────────────────────────────────────────────
def compare(ref_kmers: np.ndarray, ref_counts: np.ndarray,
idx_kmers: np.ndarray, idx_counts: np.ndarray,
) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
"""Return (false_neg, false_pos, cm_ref_kmers, cm_ref_counts, cm_idx_counts).
All arrays sorted; cm_* cover kmers present in both arrays but with
differing counts.
"""
false_neg = np.setdiff1d(ref_kmers, idx_kmers, assume_unique=True)
false_pos = np.setdiff1d(idx_kmers, ref_kmers, assume_unique=True)
# Count mismatches among shared kmers.
# Both arrays are sorted so we can use searchsorted.
pos_in_idx = np.searchsorted(idx_kmers, ref_kmers)
pos_in_idx = np.clip(pos_in_idx, 0, len(idx_kmers) - 1)
shared_mask = idx_kmers[pos_in_idx] == ref_kmers
shared_ref_counts = ref_counts[shared_mask]
shared_idx_counts = idx_counts[pos_in_idx[shared_mask]]
mismatch_mask = shared_ref_counts != shared_idx_counts
cm_kmers = ref_kmers[shared_mask][mismatch_mask]
cm_ref_counts = shared_ref_counts[mismatch_mask]
cm_idx_counts = shared_idx_counts[mismatch_mask]
return false_neg, false_pos, cm_kmers, cm_ref_counts, cm_idx_counts
# ── main ─────────────────────────────────────────────────────────────────────
def main() -> None:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument('reference', metavar='REF_NPZ', nargs='?',
help='Reference .npz file')
ap.add_argument('index', metavar='INDEX_DIR', nargs='?',
help='obikmer index directory (built with --with-counts)')
ap.add_argument('--obikmer', default='obikmer',
help='Path to obikmer binary')
ap.add_argument('--species', default='')
ap.add_argument('--strain', default='')
ap.add_argument('--header', action='store_true',
help='Print CSV header and exit')
ap.add_argument('--save-fp', metavar='FILE',
help='Save false-positive kmer strings to FILE')
ap.add_argument('--save-fn', metavar='FILE',
help='Save false-negative kmer strings to FILE')
ap.add_argument('--save-cm', metavar='FILE',
help='Save count-mismatch rows (kmer,ref_count,idx_count) to FILE')
args = ap.parse_args()
if args.header:
print('species,strain,ref_kmers,idx_kmers,'
'false_neg,false_pos,count_mismatch,'
'fn_pct,fp_pct,cm_pct')
return
# Detect k
cmd1 = [args.obikmer, 'dump', '--head', '1', args.index]
out1 = subprocess.check_output(cmd1, stderr=subprocess.DEVNULL, text=True)
k = len(out1.splitlines()[1].split(',')[0])
# Load reference
print(f'Loading reference: {args.reference}', file=sys.stderr)
npz = np.load(args.reference)
ref_kmers = npz['kmers'] # sorted uint64
ref_counts = npz['counts'] # uint32
# Load index
print(f'Streaming dump (k={k}): {args.index}', file=sys.stderr)
idx_kmers, idx_counts = load_index(args.obikmer, args.index)
print(f'k={k} ref={len(ref_kmers):,} idx={len(idx_kmers):,}', file=sys.stderr)
false_neg, false_pos, cm_kmers, cm_ref, cm_idx = compare(
ref_kmers, ref_counts, idx_kmers, idx_counts)
n_shared = len(ref_kmers) - len(false_neg)
fn_pct = 100.0 * len(false_neg) / len(ref_kmers) if len(ref_kmers) else 0.0
fp_pct = 100.0 * len(false_pos) / len(idx_kmers) if len(idx_kmers) else 0.0
cm_pct = 100.0 * len(cm_kmers) / n_shared if n_shared else 0.0
print(f'false negatives : {len(false_neg):,} ({fn_pct:.4f}%)', file=sys.stderr)
print(f'false positives : {len(false_pos):,} ({fp_pct:.4f}%)', file=sys.stderr)
print(f'count mismatches: {len(cm_kmers):,} ({cm_pct:.4f}% of shared)',
file=sys.stderr)
if args.save_fn and len(false_neg):
with open(args.save_fn, 'w') as fh:
for v in false_neg:
fh.write(decode_kmer(int(v), k) + '\n')
if args.save_fp and len(false_pos):
with open(args.save_fp, 'w') as fh:
for v in false_pos:
fh.write(decode_kmer(int(v), k) + '\n')
if args.save_cm and len(cm_kmers):
with open(args.save_cm, 'w') as fh:
fh.write('kmer,ref_count,idx_count\n')
for v, rc, ic in zip(cm_kmers, cm_ref, cm_idx):
fh.write(f'{decode_kmer(int(v), k)},{rc},{ic}\n')
print(f'{args.species},{args.strain},'
f'{len(ref_kmers)},{len(idx_kmers)},'
f'{len(false_neg)},{len(false_pos)},{len(cm_kmers)},'
f'{fn_pct:.4f},{fp_pct:.4f},{cm_pct:.4f}')
if __name__ == '__main__':
main()
benchmark/verify_merge_count.py
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#!/usr/bin/env python3
"""Verify the merged count index against all per-specimen reference sets.
Streams `obikmer dump` once on the merged index, accumulates per-specimen
kmer+count pairs from each column, then compares each against its reference .npz.
Output to stdout: one CSV row per specimen (same columns as verify_count.py)
species,strain,ref_kmers,idx_kmers,false_neg,false_pos,count_mismatch,
fn_pct,fp_pct,cm_pct
"""
import argparse
import subprocess
import sys
from pathlib import Path
import numpy as np
# ── encoding ──────────────────────────────────────────────────────────────────
_ENCODE = {'A': 0, 'C': 1, 'G': 2, 'T': 3,
'a': 0, 'c': 1, 'g': 2, 't': 3}
_DECODE = ['A', 'C', 'G', 'T']
def encode_kmer(s: str) -> int:
kmer = 0
for c in s:
kmer = (kmer << 2) | _ENCODE[c]
return kmer
def decode_kmer(val: int, k: int) -> str:
bases = []
for _ in range(k):
bases.append(_DECODE[val & 3])
val >>= 2
return ''.join(reversed(bases))
# ── single-pass dump ──────────────────────────────────────────────────────────
def stream_merged_dump(obikmer_bin: str, index_dir: str,
) -> tuple[list[str], dict[str, tuple[list[int], list[int]]]]:
"""Stream the merged dump once.
Returns:
specimen_names : column labels in dump order
per_specimen : mapping label → (kmer_ints, counts) for entries > 0
"""
cmd = [obikmer_bin, 'dump', index_dir]
proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL,
text=True)
header_line = proc.stdout.readline().rstrip('\n')
cols = header_line.split(',')
specimen_names = cols[1:]
per_specimen: dict[str, tuple[list[int], list[int]]] = {
name: ([], []) for name in specimen_names}
for line in proc.stdout:
parts = line.rstrip('\n').split(',')
kmer_int = encode_kmer(parts[0])
for i, name in enumerate(specimen_names):
count = int(parts[i + 1])
if count > 0:
per_specimen[name][0].append(kmer_int)
per_specimen[name][1].append(count)
proc.wait()
if proc.returncode != 0:
print(f'ERROR: obikmer dump exited {proc.returncode}', file=sys.stderr)
sys.exit(1)
return specimen_names, per_specimen
# ── per-specimen comparison ───────────────────────────────────────────────────
def compare_specimen(name: str,
kmer_list: list[int],
count_list: list[int],
ref_dir: Path,
k: int,
save_fn: Path | None,
save_fp: Path | None,
save_cm: Path | None,
) -> str:
ref_path = ref_dir / f'{name}.npz'
if not ref_path.exists():
print(f' SKIP {name}: no reference at {ref_path}', file=sys.stderr)
return ''
species = name.split('--')[0]
strain = name[len(species) + 2:]
npz = np.load(ref_path)
ref_kmers = npz['kmers'] # sorted uint64
ref_counts = npz['counts'] # uint32
order = np.argsort(np.array(kmer_list, dtype=np.uint64), kind='stable')
idx_kmers = np.array(kmer_list, dtype=np.uint64)[order]
idx_counts = np.array(count_list, dtype=np.uint32)[order]
false_neg = np.setdiff1d(ref_kmers, idx_kmers, assume_unique=True)
false_pos = np.setdiff1d(idx_kmers, ref_kmers, assume_unique=True)
# Count mismatches among shared kmers
pos_in_idx = np.searchsorted(idx_kmers, ref_kmers)
pos_in_idx = np.clip(pos_in_idx, 0, len(idx_kmers) - 1)
shared_mask = idx_kmers[pos_in_idx] == ref_kmers
mismatch_mask = ref_counts[shared_mask] != idx_counts[pos_in_idx[shared_mask]]
cm_kmers = ref_kmers[shared_mask][mismatch_mask]
cm_ref = ref_counts[shared_mask][mismatch_mask]
cm_idx = idx_counts[pos_in_idx[shared_mask]][mismatch_mask]
n_shared = int(shared_mask.sum())
fn_pct = 100.0 * len(false_neg) / len(ref_kmers) if len(ref_kmers) else 0.0
fp_pct = 100.0 * len(false_pos) / len(idx_kmers) if len(idx_kmers) else 0.0
cm_pct = 100.0 * len(cm_kmers) / n_shared if n_shared else 0.0
print(f' {name}: ref={len(ref_kmers):,} idx={len(idx_kmers):,} '
f'fn={len(false_neg):,} ({fn_pct:.4f}%) '
f'fp={len(false_pos):,} ({fp_pct:.4f}%) '
f'cm={len(cm_kmers):,} ({cm_pct:.4f}%)',
file=sys.stderr)
if save_fn and len(false_neg):
fn_file = save_fn / f'{name}_fn.txt'
fn_file.write_text('\n'.join(decode_kmer(int(v), k) for v in false_neg) + '\n')
if save_fp and len(false_pos):
fp_file = save_fp / f'{name}_fp.txt'
fp_file.write_text('\n'.join(decode_kmer(int(v), k) for v in false_pos) + '\n')
if save_cm and len(cm_kmers):
cm_file = save_cm / f'{name}_cm.csv'
lines = ['kmer,ref_count,idx_count']
for v, rc, ic in zip(cm_kmers, cm_ref, cm_idx):
lines.append(f'{decode_kmer(int(v), k)},{rc},{ic}')
cm_file.write_text('\n'.join(lines) + '\n')
return (f'{species},{strain},'
f'{len(ref_kmers)},{len(idx_kmers)},'
f'{len(false_neg)},{len(false_pos)},{len(cm_kmers)},'
f'{fn_pct:.4f},{fp_pct:.4f},{cm_pct:.4f}')
# ── main ─────────────────────────────────────────────────────────────────────
def main() -> None:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument('index', metavar='INDEX_DIR', nargs='?',
help='Merged count index directory')
ap.add_argument('ref_dir', metavar='REF_DIR', nargs='?',
help='Directory containing per-specimen .npz reference files')
ap.add_argument('--obikmer', default='obikmer')
ap.add_argument('--header', action='store_true',
help='Print CSV header and exit')
ap.add_argument('--save-fn', metavar='DIR',
help='Directory for false-negative kmer lists')
ap.add_argument('--save-fp', metavar='DIR',
help='Directory for false-positive kmer lists')
ap.add_argument('--save-cm', metavar='DIR',
help='Directory for count-mismatch CSV files')
args = ap.parse_args()
if args.header:
print('species,strain,ref_kmers,idx_kmers,'
'false_neg,false_pos,count_mismatch,'
'fn_pct,fp_pct,cm_pct')
return
ref_dir = Path(args.ref_dir)
save_fn = Path(args.save_fn) if args.save_fn else None
save_fp = Path(args.save_fp) if args.save_fp else None
save_cm = Path(args.save_cm) if args.save_cm else None
for d in (save_fn, save_fp, save_cm):
if d: d.mkdir(parents=True, exist_ok=True)
out1 = subprocess.check_output(
[args.obikmer, 'dump', '--head', '1', args.index],
stderr=subprocess.DEVNULL, text=True)
k = len(out1.splitlines()[1].split(',')[0])
print(f'k={k} streaming merged dump: {args.index}', file=sys.stderr)
specimen_names, per_specimen = stream_merged_dump(args.obikmer, args.index)
print(f'{len(specimen_names)} specimen columns loaded', file=sys.stderr)
for name in specimen_names:
kmers, counts = per_specimen[name]
row = compare_specimen(name, kmers, counts, ref_dir, k,
save_fn, save_fp, save_cm)
if row:
print(row)
if __name__ == '__main__':
main()
benchmark/verify_merge_count.sh
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#!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
INDEX="${SCRIPT_DIR}/global_index_count"
REF_DIR="${SCRIPT_DIR}/reference_index"
STATS_DIR="${SCRIPT_DIR}/stats/verify_merge_count"
PYTHON="${SCRIPT_DIR}/../.venv/bin/python3"
VERIFY_PY="${SCRIPT_DIR}/verify_merge_count.py"
mkdir -p "${STATS_DIR}"
CURRENT="${STATS_DIR}/current.csv"
"${PYTHON}" "${VERIFY_PY}" --header >"${CURRENT}"
"${PYTHON}" "${VERIFY_PY}" \
--obikmer "${BINARY}" \
"${INDEX}" "${REF_DIR}" \
>>"${CURRENT}"
run_n=$(printf '%03d' "$(find "${STATS_DIR}" -maxdepth 1 -name 'count_*.csv' | wc -l | tr -d ' ')")
ARCHIVE="${STATS_DIR}/count_${run_n}.csv"
cp "${CURRENT}" "${ARCHIVE}"
echo "Done. Results → ${ARCHIVE}"
benchmark/verify_merge_presence.py
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#!/usr/bin/env python3
"""Verify the merged presence index against all per-specimen reference sets.
Streams `obikmer dump` once on the merged index, accumulates per-specimen
kmer sets from each column, then compares each against its reference .npz.
Output to stdout: one CSV row per specimen (same columns as verify_presence.py)
species,strain,ref_kmers,idx_kmers,false_neg,false_pos,fn_pct,fp_pct
"""
import argparse
import subprocess
import sys
from pathlib import Path
import numpy as np
# ── encoding ──────────────────────────────────────────────────────────────────
_ENCODE = {'A': 0, 'C': 1, 'G': 2, 'T': 3,
'a': 0, 'c': 1, 'g': 2, 't': 3}
_DECODE = ['A', 'C', 'G', 'T']
def encode_kmer(s: str) -> int:
kmer = 0
for c in s:
kmer = (kmer << 2) | _ENCODE[c]
return kmer
def decode_kmer(val: int, k: int) -> str:
bases = []
for _ in range(k):
bases.append(_DECODE[val & 3])
val >>= 2
return ''.join(reversed(bases))
# ── single-pass dump ──────────────────────────────────────────────────────────
def stream_merged_dump(obikmer_bin: str, index_dir: str,
) -> tuple[list[str], dict[str, list[int]]]:
"""Stream the merged dump once.
Returns:
specimen_names : column labels in dump order (excluding 'kmer')
per_specimen : mapping label → list of kmer ints where presence > 0
"""
cmd = [obikmer_bin, 'dump', index_dir]
proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL,
text=True)
header_line = proc.stdout.readline().rstrip('\n')
cols = header_line.split(',')
specimen_names = cols[1:] # first col is 'kmer'
per_specimen: dict[str, list[int]] = {name: [] for name in specimen_names}
for line in proc.stdout:
parts = line.rstrip('\n').split(',')
kmer_int = encode_kmer(parts[0])
for i, name in enumerate(specimen_names):
if int(parts[i + 1]) > 0:
per_specimen[name].append(kmer_int)
proc.wait()
if proc.returncode != 0:
print(f'ERROR: obikmer dump exited {proc.returncode}', file=sys.stderr)
sys.exit(1)
return specimen_names, per_specimen
# ── per-specimen comparison ───────────────────────────────────────────────────
def compare_specimen(name: str,
kmer_list: list[int],
ref_dir: Path,
k: int,
save_fn: Path | None,
save_fp: Path | None,
) -> str:
"""Compare one specimen column against its reference .npz.
Returns a CSV row string.
"""
ref_path = ref_dir / f'{name}.npz'
if not ref_path.exists():
print(f' SKIP {name}: no reference at {ref_path}', file=sys.stderr)
return ''
species = name.split('--')[0]
strain = name[len(species) + 2:]
ref_kmers = np.load(ref_path)['kmers'] # sorted uint64
idx_kmers = np.array(sorted(kmer_list), dtype=np.uint64)
false_neg = np.setdiff1d(ref_kmers, idx_kmers, assume_unique=True)
false_pos = np.setdiff1d(idx_kmers, ref_kmers, assume_unique=True)
fn_pct = 100.0 * len(false_neg) / len(ref_kmers) if len(ref_kmers) else 0.0
fp_pct = 100.0 * len(false_pos) / len(idx_kmers) if len(idx_kmers) else 0.0
print(f' {name}: ref={len(ref_kmers):,} idx={len(idx_kmers):,} '
f'fn={len(false_neg):,} ({fn_pct:.4f}%) '
f'fp={len(false_pos):,} ({fp_pct:.4f}%)',
file=sys.stderr)
if save_fn and len(false_neg):
fn_file = save_fn / f'{name}_fn.txt'
fn_file.write_text('\n'.join(decode_kmer(int(v), k) for v in false_neg) + '\n')
if save_fp and len(false_pos):
fp_file = save_fp / f'{name}_fp.txt'
fp_file.write_text('\n'.join(decode_kmer(int(v), k) for v in false_pos) + '\n')
return (f'{species},{strain},'
f'{len(ref_kmers)},{len(idx_kmers)},'
f'{len(false_neg)},{len(false_pos)},'
f'{fn_pct:.4f},{fp_pct:.4f}')
# ── main ─────────────────────────────────────────────────────────────────────
def main() -> None:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument('index', metavar='INDEX_DIR', nargs='?',
help='Merged presence index directory')
ap.add_argument('ref_dir', metavar='REF_DIR', nargs='?',
help='Directory containing per-specimen .npz reference files')
ap.add_argument('--obikmer', default='obikmer')
ap.add_argument('--header', action='store_true',
help='Print CSV header and exit')
ap.add_argument('--save-fn', metavar='DIR',
help='Directory to save false-negative kmer lists')
ap.add_argument('--save-fp', metavar='DIR',
help='Directory to save false-positive kmer lists')
args = ap.parse_args()
if args.header:
print('species,strain,ref_kmers,idx_kmers,'
'false_neg,false_pos,fn_pct,fp_pct')
return
ref_dir = Path(args.ref_dir)
save_fn = Path(args.save_fn) if args.save_fn else None
save_fp = Path(args.save_fp) if args.save_fp else None
if save_fn: save_fn.mkdir(parents=True, exist_ok=True)
if save_fp: save_fp.mkdir(parents=True, exist_ok=True)
# Detect k
out1 = subprocess.check_output(
[args.obikmer, 'dump', '--head', '1', args.index],
stderr=subprocess.DEVNULL, text=True)
k = len(out1.splitlines()[1].split(',')[0])
print(f'k={k} streaming merged dump: {args.index}', file=sys.stderr)
specimen_names, per_specimen = stream_merged_dump(args.obikmer, args.index)
print(f'{len(specimen_names)} specimen columns loaded', file=sys.stderr)
for name in specimen_names:
row = compare_specimen(name, per_specimen[name], ref_dir, k, save_fn, save_fp)
if row:
print(row)
if __name__ == '__main__':
main()
benchmark/verify_merge_presence.sh
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#!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
INDEX="${SCRIPT_DIR}/global_index_presence"
REF_DIR="${SCRIPT_DIR}/reference_index"
STATS_DIR="${SCRIPT_DIR}/stats/verify_merge_presence"
PYTHON="${SCRIPT_DIR}/../.venv/bin/python3"
VERIFY_PY="${SCRIPT_DIR}/verify_merge_presence.py"
mkdir -p "${STATS_DIR}"
CURRENT="${STATS_DIR}/current.csv"
"${PYTHON}" "${VERIFY_PY}" --header >"${CURRENT}"
"${PYTHON}" "${VERIFY_PY}" \
--obikmer "${BINARY}" \
"${INDEX}" "${REF_DIR}" \
>>"${CURRENT}"
run_n=$(printf '%03d' "$(find "${STATS_DIR}" -maxdepth 1 -name 'presence_*.csv' | wc -l | tr -d ' ')")
ARCHIVE="${STATS_DIR}/presence_${run_n}.csv"
cp "${CURRENT}" "${ARCHIVE}"
echo "Done. Results → ${ARCHIVE}"
benchmark/verify_one_count.sh
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#!/usr/bin/env bash
# Usage: verify_one_count.sh SPECIMEN
# SPECIMEN = "species--strain" (Make pattern stem)
# Output: stats/verify_count/SPECIMEN.stats (one CSV data row, no header)
set -euo pipefail
SPECIMEN="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
PYTHON="${SCRIPT_DIR}/../.venv/bin/python3"
VERIFY_PY="${SCRIPT_DIR}/verify_count.py"
species="${SPECIMEN%%--*}"
strain="${SPECIMEN#*--}"
REF_NPZ="${SCRIPT_DIR}/reference_index/${SPECIMEN}.npz"
INDEX_DIR="${SCRIPT_DIR}/specimen_index_count/${SPECIMEN}"
STATS_DIR="${SCRIPT_DIR}/stats/verify_count"
STATS_FILE="${STATS_DIR}/${SPECIMEN}.stats"
mkdir -p "${STATS_DIR}"
echo "[${SPECIMEN}] verifying count"
"${PYTHON}" "${VERIFY_PY}" \
--obikmer "${BINARY}" \
--species "${species}" \
--strain "${strain}" \
"${REF_NPZ}" "${INDEX_DIR}" \
>"${STATS_FILE}"
benchmark/verify_one_presence.sh
Executable
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#!/usr/bin/env bash
# Usage: verify_one_presence.sh SPECIMEN
# SPECIMEN = "species--strain" (Make pattern stem)
# Output: stats/verify_presence/SPECIMEN.stats (one CSV data row, no header)
set -euo pipefail
SPECIMEN="$1"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
BINARY="${SCRIPT_DIR}/../src/target/release/obikmer"
PYTHON="${SCRIPT_DIR}/../.venv/bin/python3"
VERIFY_PY="${SCRIPT_DIR}/verify_presence.py"
species="${SPECIMEN%%--*}"
strain="${SPECIMEN#*--}"
REF_NPZ="${SCRIPT_DIR}/reference_index/${SPECIMEN}.npz"
INDEX_DIR="${SCRIPT_DIR}/specimen_index_presence/${SPECIMEN}"
STATS_DIR="${SCRIPT_DIR}/stats/verify_presence"
STATS_FILE="${STATS_DIR}/${SPECIMEN}.stats"
mkdir -p "${STATS_DIR}"
echo "[${SPECIMEN}] verifying presence"
"${PYTHON}" "${VERIFY_PY}" \
--obikmer "${BINARY}" \
--species "${species}" \
--strain "${strain}" \
"${REF_NPZ}" "${INDEX_DIR}" \
>"${STATS_FILE}"
benchmark/verify_presence.py
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#!/usr/bin/env python3
"""Compare an obikmer index against a reference kmer set (presence/absence).
Loads the reference .npz (sorted uint64 kmers built by build_reference.py),
streams the output of `obikmer dump`, encodes each kmer string to uint64,
then reports false negatives and false positives using numpy set operations.
Output to stdout: one CSV row
species, strain, ref_kmers, idx_kmers, false_neg, false_pos, fn_pct, fp_pct
"""
import argparse
import subprocess
import sys
import numpy as np
# ── encoding ──────────────────────────────────────────────────────────────────
_ENCODE = {'A': 0, 'C': 1, 'G': 2, 'T': 3,
'a': 0, 'c': 1, 'g': 2, 't': 3}
_DECODE = ['A', 'C', 'G', 'T']
def encode_kmer(s: str) -> int:
kmer = 0
for c in s:
kmer = (kmer << 2) | _ENCODE[c]
return kmer
def decode_kmer(val: int, k: int) -> str:
bases = []
for _ in range(k):
bases.append(_DECODE[val & 3])
val >>= 2
return ''.join(reversed(bases))
# ── dump parsing ──────────────────────────────────────────────────────────────
def load_index_kmers(obikmer_bin: str, index_dir: str) -> np.ndarray:
"""Stream `obikmer dump` and return a sorted uint64 array of kmer integers."""
cmd = [obikmer_bin, 'dump', index_dir]
proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL,
text=True)
kmers = []
header = True
for line in proc.stdout:
if header:
header = False
continue
kmer_str = line.split(',', 1)[0]
kmers.append(encode_kmer(kmer_str))
proc.wait()
if proc.returncode != 0:
print(f'ERROR: obikmer dump exited {proc.returncode}', file=sys.stderr)
sys.exit(1)
arr = np.array(kmers, dtype=np.uint64)
arr.sort()
return arr
# ── comparison ────────────────────────────────────────────────────────────────
def compare(ref: np.ndarray, idx: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
"""Return (false_negatives, false_positives) as uint64 arrays."""
false_neg = np.setdiff1d(ref, idx, assume_unique=True)
false_pos = np.setdiff1d(idx, ref, assume_unique=True)
return false_neg, false_pos
# ── main ─────────────────────────────────────────────────────────────────────
def main() -> None:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument('reference', metavar='REF_NPZ', nargs='?', help='Reference .npz file')
ap.add_argument('index', metavar='INDEX_DIR', nargs='?', help='obikmer index directory')
ap.add_argument('--obikmer', default='obikmer', help='Path to obikmer binary')
ap.add_argument('--species', default='', help='Species label for CSV row')
ap.add_argument('--strain', default='', help='Strain label for CSV row')
ap.add_argument('--header', action='store_true', help='Print CSV header and exit')
ap.add_argument('--save-fp', metavar='FILE',
help='Save false-positive kmer strings to FILE')
ap.add_argument('--save-fn', metavar='FILE',
help='Save false-negative kmer strings to FILE')
args = ap.parse_args()
if args.header:
print('species,strain,ref_kmers,idx_kmers,'
'false_neg,false_pos,fn_pct,fp_pct')
return
# Detect k from the index (one cheap call before the full dump).
cmd1 = [args.obikmer, 'dump', '--head', '1', args.index]
out1 = subprocess.check_output(cmd1, stderr=subprocess.DEVNULL, text=True)
k = len(out1.splitlines()[1].split(',')[0])
# Load reference
print(f'Loading reference: {args.reference}', file=sys.stderr)
npz = np.load(args.reference)
ref_kmers = npz['kmers'] # already sorted uint64
# Load index
print(f'Streaming dump (k={k}): {args.index}', file=sys.stderr)
idx_kmers = load_index_kmers(args.obikmer, args.index)
print(f'k={k} ref={len(ref_kmers):,} idx={len(idx_kmers):,}', file=sys.stderr)
false_neg, false_pos = compare(ref_kmers, idx_kmers)
fn_pct = 100.0 * len(false_neg) / len(ref_kmers) if len(ref_kmers) else 0.0
fp_pct = 100.0 * len(false_pos) / len(idx_kmers) if len(idx_kmers) else 0.0
print(f'false negatives: {len(false_neg):,} ({fn_pct:.4f}%)', file=sys.stderr)
print(f'false positives: {len(false_pos):,} ({fp_pct:.4f}%)', file=sys.stderr)
if args.save_fn and len(false_neg):
with open(args.save_fn, 'w') as fh:
for v in false_neg:
fh.write(decode_kmer(int(v), k) + '\n')
print(f'False negatives saved → {args.save_fn}', file=sys.stderr)
if args.save_fp and len(false_pos):
with open(args.save_fp, 'w') as fh:
for v in false_pos:
fh.write(decode_kmer(int(v), k) + '\n')
print(f'False positives saved → {args.save_fp}', file=sys.stderr)
print(f'{args.species},{args.strain},'
f'{len(ref_kmers)},{len(idx_kmers)},'
f'{len(false_neg)},{len(false_pos)},'
f'{fn_pct:.4f},{fp_pct:.4f}')
if __name__ == '__main__':
main()
docmd/architecture/rebuild_filter.md
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# Rebuild / filter — column-first design
## Problem with the current two-pass design
`rebuild_partition` currently makes **two full passes** over source data:
**Pass 1** — read unitigs → MPHF lookup (source) → read row (108 values) → apply filter → push kmer into `GraphDeBruijn`, **discard row**.
**Pass 2** — read unitigs again → MPHF lookup again → read row again → for each passing kmer, look up slot in new MPHF → fill column builders.
Both passes do random access into the source matrix: for each kmer, the MPHF returns a slot, then we read 108 values scattered across 108 column positions. This is cache-hostile even with a packed matrix (`.pbmx`), because the matrix is column-major: consecutive row reads jump across the file.
## Memory budget
The `keep` bitvector costs **1 bit per slot**. With 256 partitions and realistic kmer counts, each partition holds at most a few tens of millions of slots → a few MB per bitvector. Even in the absolute worst case (800 M slots), it stays under 100 MB. This is negligible.
The `slot_map` option (Option B, 8–16 bytes per slot) is heavier but still bounded: at 15 M slots and 8 bytes, that is 120 MB per partition, acceptable for a single worker.
## Key observation
**The filter operates on column values, not on kmers.** A filter like `--max-outgroup-count 0` only needs to know, for each slot, whether any outgroup column is non-zero. It does not need to know which kmer occupies that slot.
This means filtering can be done as a **sequential column scan** that produces a `keep: BitVec[n_slots]` — no MPHF lookups, no kmer knowledge, perfectly cache-friendly.
## Proposed single-scan design
### Step 1 — column scan → `keep` bitvector
```
for each column c in source matrix:
read column c sequentially (one mmap range)
update keep[slot] according to filter contribution of column c
```
For `GroupQuorumFilter` with ingroup/outgroup:
- ingroup columns: count presence per slot → `ingroup_count[slot]`
- outgroup columns: `keep[slot] &= (value[slot] == 0)` (early-exit possible)
Result: `keep: BitVec` of size `n_slots`, computed with purely sequential IO.
### Step 2 — unitig scan → kept kmers + new MPHF
```
for each kmer in unitig files:
old_slot = old_MPHF(kmer)
if keep[old_slot]:
push kmer into new GraphDeBruijn
record (old_slot, kmer) ← or just old_slot in order
```
Build new MPHF from `GraphDeBruijn` via `materialize_layer`.
### Step 3 — fill new matrix
Two sub-options:
**Option A — from recorded (old_slot, kmer) pairs:**
```
for each (old_slot, kmer) in recorded list:
new_slot = new_MPHF(kmer)
for each column c:
new_matrix[new_slot, c] = old_matrix[old_slot, c]
```
Memory cost: `n_kept × (8 + 8)` bytes for `(old_slot: usize, kmer: CanonicalKmer)`.
For species-specific filters, `n_kept` is small. For unfiltered rebuild, `n_kept = n_slots`.
**Option B — column-by-column copy using old→new slot mapping:**
Precompute `slot_map: Vec<Option<usize>>` of size `n_slots`:
- For each kmer in unitig file: `slot_map[old_MPHF(kmer)] = Some(new_MPHF(kmer))`
Then for each source column:
```
read source column sequentially
for each slot where slot_map[slot] = Some(new_slot):
write value to new column at new_slot
```
Memory cost: `n_slots × sizeof(usize)` for the slot map (one usize per source slot).
IO pattern: sequential read of each source column → random write into new column builders.
Option B avoids storing kmer values and works uniformly regardless of filter selectivity.
## Comparison
| | Current | Proposed |
|---|---|---|
| Disk reads | 2× unitigs + 2× random matrix | 1× columns (sequential) + 1× unitigs |
| MPHF lookups (source) | 2× N_kmers | 1× N_kept (step 2) or 0 (option B, col scan only) |
| Cache behavior | poor (random row access) | good (sequential column scan) |
| Extra memory | none | slot_map (option B) or (old_slot, kmer) list (option A) |
## Files to modify
- `src/obikpartitionner/src/rebuild_layer.rs` — `rebuild_partition` and `iter_src_layers`
- Possibly `src/obicompactvec/` — add column iterator API if not already present
- `src/obilayeredmap/` — check if per-column sequential access is exposed on `SrcLayerData`
## Open questions
- Does `SrcLayerData` expose per-column sequential iteration, or only `lookup(kmer, n_genomes)` random access?
- For option B: are new column builders writable in random-slot order (i.e. `set_val(slot, value)` without sequential constraint)?
- For `GroupQuorumFilter` specifically: can the filter be decomposed into independent per-column contributions, or does it need the full row?
docmd/implementation/filtering.md
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### Path matching (`~` and `!~`)
Metadata values can represent hierarchical taxonomic paths such as
Metadata values can represent hierarchical concept paths such as
`/Eukaryota/Viridiplantae/Streptophyta/Betulaceae/Betula/nana`.
- **Absolute pattern** (starts with `/`): the value must start with the pattern
at a segment boundary.
`taxon~/Betulaceae/Betula` matches `/Betulaceae/Betula/nana` and
`/Betulaceae/Betula` but not `/Betulaceae/Betuloides/…`.
- **Bare segment** (no leading `/`): the value must contain the pattern as an
exact path component anywhere.
`taxon~Betula` matches any path that has `Betula` as one of its segments.
Stored taxonomy values always start with `/` (the root of the path).
Query patterns do **not** need to start with `/` — a leading `/` is an optional
start anchor, not a requirement.
| Pattern form | Semantics |
|---|---|
| `A/B` | contiguous sub-path A then B, anywhere in the value |
| `/A/B` | value starts with A then B |
| `A/B$` | value ends with A then B |
| `/A/B$` | value is exactly A then B |
| `A@x/B` | A with class `x` followed by B with any class |
- `taxon~/Betulaceae/Betula` matches any path that starts with `Betulaceae` then `Betula`.
- `taxon~Betula` matches any path containing `Betula` as a segment, anywhere.
### Missing metadata key → NA
docmd/implementation/obicompactvec.md
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# obicompactvec — Complete Reference
## Module structure
```
src/obicompactvec/src/
lib.rs public re-exports
views.rs BitSliceView<'a>, IntSliceView<'a> — zero-copy read views
traits.rs ColumnWeights, CountPartials, BitPartials (matrix aggregation)
bitvec.rs PersistentBitVec, PersistentBitVecBuilder, BitIter
reader.rs PersistentCompactIntVec (read-only)
builder.rs PersistentCompactIntVecBuilder (read-write)
tempintvec.rs TempCompactIntVec, TempCompactIntVecBuilder (temp-file-backed)
tempbitvec.rs TempBitVec, TempBitVecBuilder (temp-file-backed)
bitmatrix.rs PersistentBitMatrix, PersistentBitMatrixBuilder
intmatrix.rs PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder
colgroup.rs ColGroup, MatrixGroupOps trait
format.rs file format constants, encode/decode helpers
layer_meta.rs LayerMeta (column metadata)
meta.rs matrix metadata
```
```mermaid
graph TD
views --> bitvec
views --> builder
views --> tempbitvec
views --> tempintvec
views --> bitmatrix
views --> intmatrix
format --> reader
format --> builder
reader --> intmatrix
reader --> tempintvec
builder --> intmatrix
builder --> tempintvec
bitvec --> tempbitvec
bitvec --> bitmatrix
tempintvec --> intmatrix
tempintvec --> bitmatrix
tempbitvec --> intmatrix
tempbitvec --> bitmatrix
colgroup --> intmatrix
colgroup --> bitmatrix
layer_meta --> bitmatrix
layer_meta --> intmatrix
meta --> bitmatrix
meta --> intmatrix
```
---
## Compact int encoding
All integer vectors use the same two-tier encoding regardless of storage backend.
**Primary array** — one `u8` per slot:
- Values **0–254** are stored directly. No overhead.
- Value **255 is a sentinel**: the slot's actual value is ≥ 255 and lives in the overflow store.
**Overflow store** — maps slot index to a `u32` value ≥ 255:
- In `PersistentCompactIntVecBuilder`: a `HashMap<usize, u32>` in RAM.
- In `PersistentCompactIntVec` (reader): a sorted `[(slot: u64, value: u32)]` array in the mmap, with a sparse L1-resident index for binary search.
```mermaid
flowchart LR
slot --> P["primary[slot]: u8"]
P -->|"< 255"| V["value = byte (0–254)"]
P -->|"= 255 sentinel"| OV["overflow store"]
OV -->|"Builder"| HM["HashMap&lt;usize, u32&gt;\nin RAM"]
OV -->|"PersistentCompactIntVec"| SA["sorted [(slot,value)] in mmap\n+ sparse L1 index"]
```
**Key property — sentinel 255 = +∞ on `u8`:**
- `min(a, 255) = a` for all `a ≤ 254` → correct when only one side is overflow
- `max(a, 255) = 255` → correct sentinel when either side is overflow
- Only the **both-overflow** case requires reading actual values from the overflow store.
In practice, k (overflow count) ≪ n (total slots). Observed genomic data: ~0.07% of kmer slots are in overflow.
---
## View types
The previous trait hierarchy (`BitSlice`, `BitSliceMut`, `IntSlice`, `IntSliceMut`) has been replaced by two concrete zero-copy view structs with inherent methods. Views are **`Copy`** — passing them is free. All read operations live on these two types.
### `BitSliceView<'a>`
```rust
#[derive(Clone, Copy)]
pub struct BitSliceView<'a> { pub(crate) words: &'a [u64], pub(crate) n: usize }
```
Bit `i` is at `words[i >> 6]` bit `i & 63` (LSB-first). Padding bits in the last word are zero.
| Method | Cost |
|---|---|
| `len()`, `is_empty()` | O(1) |
| `get(slot)` | O(1) |
| `count_ones()` | POPCNT per word, O(n/64) |
| `count_zeros()` | `n − count_ones()`, O(n/64) |
| `iter() -> BitSliceIter<'a>` | O(1) setup, O(n) iteration |
| `partial_jaccard_dist(other: BitSliceView)` | `(a&b).popcount`, `(a\|b).popcount` per word, O(n/64) |
| `jaccard_dist(other: BitSliceView)` | from partial, O(n/64) |
| `hamming_dist(other: BitSliceView)` | `(a^b).popcount` per word, O(n/64) |
`BitSliceIter<'a>`: word-level scan; one word per 64 iterations.
### `IntSliceView<'a>`
```rust
#[derive(Clone, Copy)]
pub struct IntSliceView<'a> {
pub(crate) primary: &'a [u8],
pub(crate) overflow_raw: &'a [u8], // sorted [(slot:u64, value:u32)] entries
pub(crate) n_overflow: usize,
pub(crate) n: usize,
}
```
`overflow_raw` contains `n_overflow` entries of `OVERFLOW_ENTRY_SIZE` bytes each, sorted by slot. The sort invariant is established at `close()`/`freeze()` time.
| Method | Cost |
|---|---|
| `len()`, `is_empty()` | O(1) |
| `primary_bytes()` | O(1) |
| `overflow_entries() -> impl Iterator<(usize,u32)>` | O(n_overflow) iteration |
| `get(slot)` | O(1) primary; binary search O(log k) for overflow slots |
| `iter() -> IntSliceViewIter<'a>` | merge scan, O(n + k) |
| `sum()` | byte scan + overflow, O(n + k) |
| `count_nonzero()` | byte scan, O(n) |
| Distance methods (`bray_dist`, `euclidean_dist`, `jaccard_dist`, …) | O(n + k) |
`IntSliceViewIter<'a>`: merge scan using `overflow_pos` index. Requires sorted overflow — guaranteed by the construction lifecycle.
**Builder `view()` vs reader `view()`:** `PersistentCompactIntVecBuilder` stores overflow as an unsorted `HashMap`, not raw bytes. Its `view()` returns an `IntSliceView` with `overflow_raw = &[]` and `n_overflow = 0`. This is intentional — the view is primarily useful after `freeze()`. During building, callers that need overflow use `overflow_entries()` directly.
---
## Concrete types
```mermaid
classDiagram
class BitSliceView {
+words: &[u64]
+n: usize
+get(slot) bool
+count_ones() u64
+iter() BitSliceIter
+jaccard_dist/hamming_dist(other: BitSliceView)
}
class IntSliceView {
+primary: &[u8]
+overflow_raw: &[u8]
+n_overflow: usize
+n: usize
+get(slot) u32
+iter() IntSliceViewIter
+overflow_entries() Iterator
+bray_dist/euclidean_dist/…(other: IntSliceView)
}
class PersistentBitVec {
-mmap: Mmap
-n: usize
+view() BitSliceView
+get(slot) bool
+count_ones/zeros() u64
+iter() BitIter
+partial_jaccard_dist(&Self) (u64,u64)
+jaccard_dist/hamming_dist(&Self) …
}
class PersistentBitVecBuilder {
-mmap: MmapMut
-n: usize
+view() BitSliceView
+set(slot, bool)
+or/and/xor/not(BitSliceView)
+copy_from(BitSliceView)
+close() / finish() → PersistentBitVec
}
class PersistentCompactIntVec {
-mmap: Mmap
-n: usize
-n_overflow: usize
-step: usize
-index: Vec~(usize,usize)~
+view() IntSliceView
+get(slot) u32
+iter() Iter
+sum/count_nonzero() u64
+bray_dist/euclidean_dist/… (&Self)
}
class PersistentCompactIntVecBuilder {
-mmap: MmapMut
-n: usize
-overflow: HashMap~usize,u32~
+view() IntSliceView
+set(slot, u32) / get(slot) u32
+inc / inc_present / inc_present_fast
+inc_predicate / inc_predicate_fast
+add/min/max/diff/mask_with(…View)
+primary_bytes/primary_bytes_mut()
+close() / finish() → PersistentCompactIntVec
}
PersistentBitVec --> BitSliceView : view()
PersistentBitVecBuilder --> BitSliceView : view()
PersistentCompactIntVec --> IntSliceView : view()
PersistentCompactIntVecBuilder --> IntSliceView : view() (primary only)
PersistentBitVecBuilder --> PersistentBitVec : close() then open()
PersistentCompactIntVecBuilder --> PersistentCompactIntVec : close() then open()
```
### `PersistentBitVec` / `PersistentBitVecBuilder`
`PersistentBitVec` is the read-only type. `view()` returns a `BitSliceView<'_>` over the mmap word array. Direct inherent methods delegate to the view: `count_ones()`, `count_zeros()`, `partial_jaccard_dist(&Self)`, `jaccard_dist(&Self)`, `hamming_dist(&Self)`.
`BitIter<'a>` — exported iterator for `PersistentBitVec::iter()`:
```rust
pub struct BitIter<'a> { pub(crate) words: &'a [u64], pub(crate) slot: usize, pub(crate) n: usize }
```
`PersistentBitVecBuilder` is the read-write type. Mutation operations accept `BitSliceView<'_>`:
| Method | Cost |
|---|---|
| `set(slot, bool)` | O(1) |
| `view() -> BitSliceView<'_>` | O(1) |
| `or/and/xor(BitSliceView)` | word-level, O(n/64), SIMD-friendly |
| `not()` | `w ^= u64::MAX` per word, re-masks last word | O(n/64) |
| `copy_from(BitSliceView)` | `copy_from_slice` | O(n/64) |
### `PersistentCompactIntVec` / `PersistentCompactIntVecBuilder`
`PersistentCompactIntVec` is the read-only type. `view()` returns an `IntSliceView<'_>` over the mmap primary and overflow arrays. Inherent `iter()` is a merge scan (`Iter` struct). Inherent `sum()` and `count_nonzero()` use fast byte-scan helpers.
`PersistentCompactIntVecBuilder` is the read-write type. Mutation methods on the builder fall into two categories:
**Point mutations:**
| Method | Note |
|---|---|
| `set(slot, u32)` | writes primary[slot] or 255+overflow |
| `get(slot) -> u32` | reads primary byte or HashMap |
| `inc(slot)` | `get` + `set`, O(1) |
**Bulk computation methods** — accept view arguments:
| Method | Semantics | Overflow |
|---|---|---|
| `inc_present(BitSliceView)` | `+= 1` at each 1-bit | via `inc`, safe for any group size |
| `inc_present_fast(BitSliceView)` | same, raw u8 `+= 1` | `debug_assert` no 255 reached |
| `inc_predicate(IntSliceView, pred)` | `+= 1` where `pred(col[s])` | two-pass, safe |
| `inc_predicate_fast(IntSliceView, pred)` | same, raw u8 | `debug_assert` no 255 reached |
| `add(IntSliceView)` | `self[s] += other[s]` | primary fast path + overflow fallback |
| `min(IntSliceView)` | byte min + both-overflow fixup | see algorithm below |
| `max(IntSliceView)` | pre-pass + byte max | see algorithm below |
| `diff(IntSliceView)` | saturating sub | self<255 hot path |
| `mask_with(BitSliceView)` | zeros slots where mask bit = 0 | O(n_zeros) |
**`inc_present_fast` / `inc_predicate_fast` invariant:** caller guarantees no counter reaches 255 during the operation (group size < 255 for `inc_present_fast`, or chunk size < 255 for `inc_predicate_fast`). Violation is caught by `debug_assert` in dev builds.
**`min` algorithm:**
Exploits 255 = +∞: byte-level min is correct unless both sides are overflow.
```
snapshot self_ov: Vec<(slot,val)>
snapshot other_ov: HashMap<slot,val>
clear_overflow()
Pass 1 — byte min, SIMD-vectorizable, O(n)
Pass 2 — both-overflow fixup, O(k_self):
for (slot, self_val) in self_ov:
if slot ∈ other_ov: set(slot, min(self_val, other_ov[slot]))
```
**`max` algorithm:**
Cannot do byte max first — `max(255, b<255)=255` overwrites self's original overflow value. Pre-pass reads self's value at other's overflow slots before the byte pass.
```
Pre-pass O(k_other): for (slot, other_val) in other.overflow_entries():
set(slot, max(self.get(slot), other_val))
Pass 1 — byte max, SIMD-vectorizable, O(n)
```
---
## Matrix types
Four matrix types, two encodings × two formats:
| | Columnar format | Packed format |
|---|---|---|
| **Bit** | `PersistentBitMatrix` (Columnar variant) | `PersistentBitMatrix` (Packed variant) |
| **Int** | `PersistentCompactIntMatrix` (Columnar variant) | `PersistentCompactIntMatrix` (Packed variant) |
Both matrix types are enums (`Columnar` / `Packed` / `Implicit` for bit) behind a transparent API. `col_view(c)` returns the appropriate view directly:
```rust
// PersistentBitMatrix
pub fn col_view(&self, c: usize) -> BitSliceView<'_>
// PersistentCompactIntMatrix
pub fn col_view(&self, c: usize) -> IntSliceView<'_>
```
No wrapper enums (`BitColView`, `IntColView`): the caller receives a `Copy` view struct immediately usable with any view method or bulk builder method.
`pack_compact_int_matrix` and `pack_bit_matrix` convert columnar → packed format.
---
## Aggregation traits (matrix level)
### ColumnWeights
```rust
trait ColumnWeights: Send + Sync {
fn col_weights(&self) -> Array1<u64>; // sum per column
fn partial_kmer_counts(&self) -> Array1<u64>; // default = col_weights()
}
```
`partial_kmer_counts` is overridden for count matrices to return `count_nonzero` per column (distinct kmers) rather than total count.
### CountPartials
Abstract required methods: `partial_bray`, `partial_euclidean`, `partial_threshold_jaccard`, `partial_relfreq_bray`, `partial_relfreq_euclidean`, `partial_hellinger`.
**Additivity rule:** self-contained partials (`partial_bray`, `partial_euclidean`, `partial_threshold_jaccard`) can be element-wise summed across all `(partition, layer)` pairs. Normalised partials (`partial_relfreq_*`, `partial_hellinger`) require the **global** `col_weights` (accumulated across all layers and all partitions) as parameter.
**`partial_threshold_jaccard` returns `(inter, union)`** because `union[i,j]` depends on both columns simultaneously.
Provided finalisations:
| Finalisation | Formula |
|---|---|
| `bray_dist_matrix()` | `1 − 2·partial_bray[i,j] / (w[i] + w[j])` |
| `euclidean_dist_matrix()` | `√partial_euclidean[i,j]` |
| `threshold_jaccard_dist_matrix(t)` | `1 − inter[i,j] / union[i,j]` |
| `relfreq_bray_dist_matrix()` | `1 − partial_relfreq_bray[i,j]` |
| `relfreq_euclidean_dist_matrix()` | `√partial_relfreq_euclidean[i,j]` |
| `hellinger_dist_matrix()` | `√partial_hellinger[i,j] / √2` |
| `hellinger_euclidean_dist_matrix()` | `√partial_hellinger[i,j]` |
### BitPartials
Required: `partial_jaccard() -> (Array2<u64>, Array2<u64>)`, `partial_hamming() -> Array2<u64>`. Both additive across layers and partitions.
---
## Temp-file-backed types
**All inter-function results use temp-file-backed types** so the OS can page them out under memory pressure. This matters in practice: processing dozens of layers × hundreds of partitions in parallel would otherwise accumulate gigabytes of live anonymous memory.
### Lifecycle
```
TempCompactIntVecBuilder::new(n) → writable mmap in TempDir
↓ (inc_present_fast / inc_predicate_fast / add / mask_with / …)
.freeze() → TempCompactIntVec (read-only mmap + TempDir)
↓ (optional)
.make_persistent(path) → PersistentCompactIntVec (permanent file)
```
Same pattern for `TempBitVecBuilder` → `TempBitVec` → `PersistentBitVec`.
**Drop order**: `TempCompactIntVec { vec: PersistentCompactIntVec, _temp: TempDir }` — Rust drops fields in declaration order. `vec` (mmap) released before `_temp` (directory deleted). No explicit `drop()` needed.
### TempCompactIntVec / TempCompactIntVecBuilder
```rust
pub struct TempCompactIntVec {
vec: PersistentCompactIntVec,
_temp: TempDir, // dropped after vec
}
pub(crate) struct TempCompactIntVecBuilder {
builder: PersistentCompactIntVecBuilder,
temp: TempDir,
}
```
`TempCompactIntVec`: read access via `get(slot)`, `sum()`, `iter()`, `view() -> IntSliceView<'_>`.
`TempCompactIntVecBuilder`: full delegation to inner `PersistentCompactIntVecBuilder` — all bulk computation methods (`inc_present_fast`, `inc_predicate_fast`, `add`, `min`, `max`, `diff`, `mask_with`) are exposed as `pub(crate)`.
### TempBitVec / TempBitVecBuilder
```rust
pub struct TempBitVec {
vec: PersistentBitVec,
_temp: TempDir,
}
pub(crate) struct TempBitVecBuilder {
builder: PersistentBitVecBuilder,
temp: TempDir,
}
```
`TempBitVec`: read access via `get(slot)`, `count_ones()`, `view() -> BitSliceView<'_>`, `iter()`.
`TempBitVecBuilder`: exposes `set(slot, bool)`, `or(BitSliceView)`, and:
```rust
pub(crate) fn or_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool)
```
`or_where` — two passes, no intermediate allocation:
```
Pass 1 — primary bytes, O(n):
for slot in 0..n:
b = col.primary_bytes()[slot]
if b < 255 AND pred(b as u32): self.set(slot, true)
Pass 2 — overflow, O(k):
for (slot, val) in col.overflow_entries():
if pred(val): self.set(slot, true)
```
---
## Filter / Select API
### ColGroup
```rust
pub struct ColGroup { pub name: String, pub indices: Vec<usize> }
```
Defined **once at the index level** from column metadata. Valid in all matrices of all layers and partitions — column structure is identical across the entire hierarchy; only rows (kmer slots) are partitioned.
### Composition axis
- **Across partitions**: kmer space is partitioned → partial results **concatenated** (disjoint kmer ranges).
- **Across layers**: same kmer space, different counts → partial results **aggregated** (add, OR, etc.).
### MatrixGroupOps
Five required primitives + two default methods derived from them. All return temp-file-backed types.
```rust
pub trait MatrixGroupOps {
// required
fn partial_group_presence_count(&self, g: &ColGroup, threshold: u32)
-> io::Result<TempCompactIntVec>;
fn partial_group_sum(&self, g: &ColGroup)
-> io::Result<TempCompactIntVec>;
fn partial_group_any(&self, g: &ColGroup, threshold: u32)
-> io::Result<TempBitVec>;
fn partial_group_min(&self, g: &ColGroup)
-> io::Result<TempCompactIntVec>;
fn partial_group_max(&self, g: &ColGroup)
-> io::Result<TempCompactIntVec>;
// defaults derived from partial_group_presence_count
fn partial_group_all(&self, g: &ColGroup, threshold: u32)
-> io::Result<TempBitVec>; // slot=1 iff count == g.indices.len()
fn partial_group_none(&self, g: &ColGroup, threshold: u32)
-> io::Result<TempBitVec>; // slot=1 iff count == 0
}
```
Implemented for both `PersistentCompactIntMatrix` and `PersistentBitMatrix`.
For **bit matrices**: values are 0/1, so `partial_group_sum` = `partial_group_presence_count(g, 1)`; `partial_group_min` is AND (set first column then mask-with remaining); `partial_group_max` is OR via `partial_group_any` + `inc_present`.
**`partial_group_presence_count` — chunking for large groups:**
When `g.indices.len() < 255`: per-slot counts stay within `u8` range. Use `inc_present_fast` (bit) or `inc_predicate_fast(col_view(c), |v| v >= threshold)` (int) — raw u8 increment, no overflow entry written.
When `g.indices.len() ≥ 255`: process in chunks of 254 columns, accumulate via `.add(chunk_frozen.view())`.
**`partial_group_min` (int matrix)**: copy first column via `.add(col_view(first))` (start from 0 ⇒ copy), then `.min(col_view(c))` for remaining.
**`partial_group_max` (int matrix)**: `.max(col_view(c))` for all columns (start from 0 ⇒ first column acts as copy).
**`partial_group_any`** uses `or_where` on `TempBitVecBuilder` (two-pass: primary bytes then overflow entries).
**`partial_group_all` / `partial_group_none`** (default): call `partial_group_presence_count`, then iterate slots to produce the bit result. O(n) extra pass, not chunked.
### add_col_from — matrix builder integration
Both matrix builders accept temp-file results directly:
```rust
// PersistentBitMatrixBuilder
fn add_col_from(&mut self, src: &TempBitVec) -> io::Result<()>
fn add_col_from_int(&mut self, src: &TempCompactIntVec) -> io::Result<()> // nonzero → 1
// PersistentCompactIntMatrixBuilder
fn add_col_from(&mut self, src: &TempCompactIntVec) -> io::Result<()>
fn add_col_from_bit(&mut self, src: &TempBitVec) -> io::Result<()> // bit → 0/1 u32
```
`add_col_from` copies the temp file to the matrix directory and increments `n_cols`; `close()` writes `meta.json` with the final column count. No separate `write_meta` step needed.
### mask_with
Direct method on `PersistentCompactIntVecBuilder` (and delegation via `TempCompactIntVecBuilder`). Zeros every slot where the corresponding mask bit is 0. Iterates only zero bits — O(n_zeros), O(1) when mask is all-ones.
```
for (w_idx, word) in mask.words():
if word == u64::MAX: continue // skip all-ones words
zeros = !word
while zeros != 0:
bit = trailing_zeros(zeros)
s = w_idx * 64 + bit
if primary[s] != 0: set(s, 0) // clears overflow entry too
zeros &= zeros − 1
```
Terminal operation for Filter (retain only selected kmer slots in a count vector) and Select (positional selection without MPHF).
docmd/implementation/obitaxonomy.md
+143
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@@ -0,0 +1,143 @@
# `obitaxonomy` — taxonomy concept paths
`obitaxonomy` is a dependency-free crate that defines a typed representation
of hierarchical concept paths (taxonomic or otherwise) stored in genome metadata.
---
## Concept path syntax
A concept path is stored as a metadata value with the prefix `taxonomy:/`:
```
taxonomy:/enterobacteriaceae@family/Escherichia@genus/Escherichia coli@species
```
Structure:
- The `taxonomy:/` prefix is the type discriminator. Any metadata value starting
with it is parsed as a `TaxPath`; all others remain plain strings.
- The remainder is one or more `/`-separated segments.
- Each segment is `name` or `name@rank`, where `rank` is a label for the
taxonomic level (e.g. `family`, `genus`, `species`).
- Rank annotations are **optional per segment** and can be mixed freely.
- Spaces are allowed in both names and ranks.
### Reserved character
`@` is reserved throughout the taxonomy system and may **not** appear in:
| Context | Constraint |
|---------|------------|
| Segment name | forbidden |
| Rank/class label | forbidden |
| Metadata key names | forbidden (used as `key@rank` in predicate syntax) |
`@` is freely allowed in plain-text metadata values (non-taxonomy).
### Parse errors
| Condition | Error |
|-----------|-------|
| Value does not start with `taxonomy:/` | `MissingPrefix` |
| No segments after the prefix | `EmptyPath` |
| Segment with empty name (consecutive `/`) | `EmptySegmentName` |
| Segment with trailing `@` and no rank (`name@`) | `EmptyRankName` |
| Segment with more than one `@` | `AmbiguousRank` |
---
## Public API
### `TaxSegment`
A single node: a name and an optional rank.
```rust
seg.name() // &str
seg.rank() // Option<&str>
seg.to_string() // "name" or "name@rank"
TaxSegment::parse(s) // Result<TaxSegment, TaxError>
```
### `TaxPath`
```rust
TaxPath::parse(s) // Result<TaxPath, TaxError>
path.segments() // &[TaxSegment]
path.depth() // usize — number of segments
path.is_ancestor_of(&other) // bool — prefix match by name, ranks ignored
path.name_at_rank("genus") // Option<&str>
path.to_string() // reconstructs "taxonomy:/…"
```
`is_ancestor_of` compares segment **names** only — rank annotations are
informational and do not affect the ancestry relation.
```rust
let a: TaxPath = "taxonomy:/Enterobacteriaceae@family/Escherichia@genus".parse()?;
let b: TaxPath = "taxonomy:/Enterobacteriaceae@family/Escherichia@genus/Escherichia coli@species".parse()?;
assert!(a.is_ancestor_of(&b)); // true
assert!(b.is_ancestor_of(&a)); // false
assert!(a.is_ancestor_of(&a)); // true (equal ⇒ ancestor)
assert_eq!(b.name_at_rank("species"), Some("Escherichia coli"));
assert_eq!(b.name_at_rank("genus"), Some("Escherichia"));
assert_eq!(b.name_at_rank("order"), None);
```
---
## Integration with `GenomeInfo`
At index load time, every metadata value is inspected once:
- Starts with `taxonomy:/` → parsed into `TaxPath`, stored in `genome.taxonomy`.
- Otherwise → kept as-is in `genome.meta`.
```rust
struct GenomeInfo {
label: String,
meta: HashMap<String, String>, // plain text metadata
taxonomy: HashMap<String, TaxPath>, // parsed taxonomy metadata
}
```
The raw string is not duplicated. `TaxPath::to_string()` reconstructs the
original value losslessly for serialisation.
---
## Predicate operators (in `filter` / `select`)
Path predicates use the `~` / `!~` operators. The **stored value** always starts
with `/` (rooted path); the **query pattern** does not need to.
### Path pattern syntax
| Pattern | Semantics |
|---------|-----------|
| `A/B` | contiguous sub-path A then B, anywhere in the value |
| `/A/B` | value starts with A then B (start-anchored) |
| `A/B$` | value ends with A then B (end-anchored) |
| `/A/B$` | value is exactly A then B (fully anchored) |
| `A@x/B` | A with class `x` followed by B with any class |
| `A@x/B@y` | A with class `x` followed by B with class `y` |
A segment pattern without `@` matches the segment name regardless of its stored class.
### Rank-aware queries
```
key@rank=value
```
| Predicate form | Semantics |
|----------------|-----------|
| `key@rank=value` | genome's `key` has `value` at rank `rank` |
| `key@rank!=value` | does not |
| `key@rank=v1\|v2` | value at `rank` is `v1` or `v2` |
`~` combined with `@rank` on the key (e.g. `key@genus~pattern`) is not defined
and is rejected at parse time.
docmd/installation.md
+2 -2
View File
@@ -60,13 +60,13 @@ HPC home directories are typically on a network filesystem (Lustre, NFS) optimis
**Always redirect the build directory to a local scratch disk:**
```bash
CARGO_TARGET_DIR=/scratch/local/$USER/cargo-target cargo build --release
CARGO_TARGET_DIR=/scratch/$USER/cargo-target cargo build --release
```
Adapt the path to the local scratch available on your cluster (`/var/tmp`, `/tmp`, `/scratch/local`, etc.). Once built, copy the binary to a permanent location:
```bash
cp /scratch/local/$USER/cargo-target/release/obikmer ~/bin/
cp /scratch/$USER/cargo-target/release/obikmer ~/bin/
```
## NUMA support
mkdocs.yml
+1
View File
@@ -53,6 +53,7 @@ nav:
- Merge parallelism & memory: implementation/merge_parallelism.md
- Kmer filtering: implementation/filtering.md
- Select command: implementation/select.md
- obitaxonomy crate: implementation/obitaxonomy.md
- Architecture:
- Sequences: architecture/sequences/invariant.md
- Kmer index: architecture/index_architecture.md
obicompactvector_reflexion.md
+44
View File
@@ -0,0 +1,44 @@
# La crate obicompactvector
Le code actuelle est ce qu'il est. Ce n'est pad la vrérité absolue, c'est un premier effort d'implémentation rien de plus. Ci-dessous je vais décrire les objectif et la structure qui devrait être. LA VERITE A ATTEINDRE.
La crate fournie des représentations les plus compact possible en mémoire de matrice de comptage ou de présence de k-mer dans des génomes. Chaque colonne représente un génome chaque ligne un kmer. une matrice est une collection de vecteur ou chacun des vecteur est un colonne de la matrice.
Les matrices comme les colonnes ont vocation à être persistante. Les données sont stockées dans des fichiers binaires. Les données sont mappées en mémoire via `mmap`
Les structure sont par essence immutables. Il existe des représentations mutables des colonnes qui permettent leur construction. À la fin de leur construction, les colonnes sont fermée ce qui les rends immutable.
Les matrices peuvent êtres représenté de deux façons:
- via un répertoire contenant une collection de fichier colonnes
- via un fichier matrix qui est la concatenation de plusieurs fichiers colonnes.
## Les matrices de comptage
Ce sont des matrice d'entiers positif la plus part du temps de petites valeurs (inferieurs à 255). On assume que toutes les valeurs sont représentables sur un `u32`
## Les matrices de presence
Ce sont des matrices de boolean représenté comme des champs de bits
Il existe une forme implicite des vecteur de présence, qui n'est représenté par aucun fichier pour lequel toutes les valeurs sont vraies
## représentation légère des colonnes
Les colonnes qu'elles soient de unitiaire (fichier colonne) ou partie d'un fichier composite matrice peuvent être représenté par un objet léger donnant acces à ces valeurs ainsi qu'à la longeur du vecteurs. Toutes les méthodes de calcules doivent uniquement travailler à partir de ces représentations légère unifiées des colonnes.
### Représentation légère d'un vecteur de présence
Le vecteur est représenté par
- un champs de bits encodé comme un [u64]
- un usize encodant la longeur du champs de bits
### Représentation légère d'un vecteur de présence
Le vecteur est représenté par
- un vecteur [u8] encodant directement les valeur faibe du vecteur [0,255[
La valeur 255 est une valeur sentinelle indiquant que la valeure vraie est >=255
et se trouvent dans une structure d'overflow
- un iterateur de (usize,u32) listant les valeurs d'overflow coorespondant aux valeurs
sentinels (255) du [u8]
- un usize encodant la longeur du champs de bits
src/Cargo.lock
Generated
+6 -1
View File
@@ -1704,7 +1704,7 @@ dependencies = [
[[package]]
name = "obikmer"
version = "0.1.0"
version = "0.1.3"
dependencies = [
"clap",
"csv",
@@ -1722,6 +1722,7 @@ dependencies = [
"obiskbuilder",
"obiskio",
"obisys",
"obitaxonomy",
"pprof",
"rayon",
"serde_json",
@@ -1853,6 +1854,10 @@ dependencies = [
"tracing",
]
[[package]]
name = "obitaxonomy"
version = "0.1.0"
[[package]]
name = "object"
version = "0.37.3"
src/Cargo.toml
+1 -1
View File
@@ -1,5 +1,5 @@
[workspace]
resolver = "3"
members = ["obikseq", "obiread", "obiskbuilder", "obifastwrite", "obikmer","obikrope","obipipeline", "obikpartitionner","obiskio","obidebruinj","obilayeredmap", "obicompactvec", "obisys", "obikindex"]
members = ["obikseq", "obiread", "obiskbuilder", "obifastwrite", "obikmer","obikrope","obipipeline", "obikpartitionner","obiskio","obidebruinj","obilayeredmap", "obicompactvec", "obisys", "obikindex", "obitaxonomy"]
[profile.release]
debug = 1
src/obicompactvec/Cargo.toml
+1 -1
View File
@@ -7,6 +7,6 @@ edition = "2024"
memmap2 = "0.9"
ndarray = "0.16"
rayon = "1"
tempfile = "3"
[dev-dependencies]
tempfile = "3"
src/obicompactvec/src/bitmatrix.rs
+154 -85
View File
@@ -7,8 +7,12 @@ use ndarray::{Array1, Array2};
use rayon::prelude::*;
use crate::bitvec::{PersistentBitVec, PersistentBitVecBuilder};
use crate::colgroup::{ColGroup, MatrixGroupOps};
use crate::layer_meta::LayerMeta;
use crate::meta::MatrixMeta;
use crate::tempbitvec::{TempBitVec, TempBitVecBuilder};
use crate::tempintvec::{TempCompactIntVec, TempCompactIntVecBuilder};
use crate::views::BitSliceView;
fn col_path(dir: &Path, col: usize) -> PathBuf {
dir.join(format!("col_{col:06}.pbiv"))
@@ -54,34 +58,11 @@ impl ColumnarBitMatrix {
}
pub(crate) fn partial_jaccard_dist_matrix(&self) -> (Array2<u64>, Array2<u64>) {
let n = self.n_cols();
let results: Vec<(usize, usize, u64, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| {
let (inter, union) = self.col(i).partial_jaccard_dist(self.col(j));
(i, j, inter, union)
})
.collect();
let mut inter_m = Array2::zeros((n, n));
let mut union_m = Array2::zeros((n, n));
for (i, j, inter, union) in results {
inter_m[[i, j]] = inter; inter_m[[j, i]] = inter;
union_m[[i, j]] = union; union_m[[j, i]] = union;
}
(inter_m, union_m)
pairwise2_matrix(self.n_cols(), |i, j| self.col(i).partial_jaccard_dist(self.col(j)))
}
pub(crate) fn partial_hamming_dist_matrix(&self) -> Array2<u64> {
self.pairwise_u64(|i, j| self.col(i).hamming_dist(self.col(j)))
}
fn pairwise_u64(&self, f: impl Fn(usize, usize) -> u64 + Sync) -> Array2<u64> {
let n = self.n_cols();
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| (i, j, f(i, j)))
.collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
pairwise_matrix(self.n_cols(), |i, j| self.col(i).hamming_dist(self.col(j)))
}
pub(crate) fn append_column(dir: &Path, value_of: impl Fn(usize) -> bool) -> io::Result<()> {
@@ -147,84 +128,46 @@ impl PackedBitMatrix {
}).collect()
}
#[inline]
fn col_bytes(&self, c: usize) -> &[u8] {
let start = self.data_offsets[c];
let len = (self.n_rows + 7) / 8;
&self.mmap[start..start + len]
&self.mmap[start..start + self.n_rows.div_ceil(8)]
}
fn count_ones_col(&self, c: usize) -> u64 {
let bytes = self.col_bytes(c);
let full = self.n_rows / 8;
let rem = self.n_rows % 8;
let mut n: u64 = bytes[..full].iter().map(|b| b.count_ones() as u64).sum();
if rem > 0 { n += (bytes[full] & ((1u8 << rem) - 1)).count_ones() as u64; }
n
fn col_words(&self, c: usize) -> &[u64] {
let nw = self.n_rows.div_ceil(64);
// SAFETY: data_offsets[c] is always 8-byte aligned.
// PBMX header = 24 + n_cols×8 (multiple of 8); each PBIV blob =
// 16 + nwords×8 (multiple of 8); mmap base is page-aligned.
let ptr = self.mmap[self.data_offsets[c]..].as_ptr() as *const u64;
unsafe { std::slice::from_raw_parts(ptr, nw) }
}
fn pair_op(&self, i: usize, j: usize, and_or: bool) -> u64 {
let ai = self.col_bytes(i);
let aj = self.col_bytes(j);
let full = self.n_rows / 8;
let rem = self.n_rows % 8;
let mut n: u64 = ai[..full].iter().zip(aj[..full].iter())
.map(|(a, b)| if and_or { a & b } else { a ^ b }.count_ones() as u64)
.sum();
if rem > 0 {
let mask = (1u8 << rem) - 1;
let last = if and_or { ai[full] & aj[full] } else { ai[full] ^ aj[full] };
n += (last & mask).count_ones() as u64;
}
n
pub(crate) fn col_slice(&self, c: usize) -> BitSliceView<'_> {
BitSliceView::new(self.col_words(c), self.n_rows)
}
fn partial_jaccard_col(&self, i: usize, j: usize) -> (u64, u64) {
let ai = self.col_bytes(i);
let aj = self.col_bytes(j);
let full = self.n_rows / 8;
let rem = self.n_rows % 8;
let (mut inter, mut union) = ai[..full].iter().zip(aj[..full].iter())
.fold((0u64, 0u64), |(inter, union), (a, b)| {
(inter + (a & b).count_ones() as u64,
union + (a | b).count_ones() as u64)
});
if rem > 0 {
let mask = (1u8 << rem) - 1;
inter += ((ai[full] & aj[full]) & mask).count_ones() as u64;
union += ((ai[full] | aj[full]) & mask).count_ones() as u64;
}
(inter, union)
pub(crate) fn col_persist(&self, c: usize, path: &Path) -> io::Result<PersistentBitVecBuilder> {
PersistentBitVecBuilder::from_raw_bytes(self.col_bytes(c), self.n_rows, path)
}
pub(crate) fn count_ones(&self) -> Array1<u64> {
Array1::from_vec(
(0..self.n_cols).into_par_iter().map(|c| self.count_ones_col(c)).collect()
(0..self.n_cols).into_par_iter()
.map(|c| self.col_slice(c).count_ones())
.collect()
)
}
pub(crate) fn partial_jaccard_dist_matrix(&self) -> (Array2<u64>, Array2<u64>) {
let n = self.n_cols;
let results: Vec<(usize, usize, u64, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| { let (inter, union) = self.partial_jaccard_col(i, j); (i, j, inter, union) })
.collect();
let mut inter_m = Array2::zeros((n, n));
let mut union_m = Array2::zeros((n, n));
for (i, j, inter, union) in results {
inter_m[[i, j]] = inter; inter_m[[j, i]] = inter;
union_m[[i, j]] = union; union_m[[j, i]] = union;
}
(inter_m, union_m)
pairwise2_matrix(self.n_cols, |i, j| {
self.col_slice(i).partial_jaccard_dist(self.col_slice(j))
})
}
pub(crate) fn partial_hamming_dist_matrix(&self) -> Array2<u64> {
let n = self.n_cols;
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| (i, j, self.pair_op(i, j, false)))
.collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
pairwise_matrix(self.n_cols, |i, j| {
self.col_slice(i).hamming_dist(self.col_slice(j))
})
}
}
@@ -343,6 +286,24 @@ impl PersistentBitMatrix {
}
}
pub fn col_view(&self, c: usize) -> BitSliceView<'_> {
match self {
Self::Columnar(m) => m.col(c).view(),
Self::Packed(m) => m.col_slice(c),
Self::Implicit { .. } => panic!("col_view() not available on Implicit PersistentBitMatrix"),
}
}
pub fn col_persist(&self, c: usize, path: &Path) -> io::Result<PersistentBitVecBuilder> {
match self {
Self::Columnar(m) => PersistentBitVecBuilder::build_from(m.col(c), path),
Self::Packed(m) => m.col_persist(c, path),
Self::Implicit { n_rows, .. } => {
PersistentBitVecBuilder::new_ones(*n_rows, path)
}
}
}
pub fn row(&self, slot: usize) -> Box<[bool]> {
match self {
Self::Columnar(m) => m.row(slot),
@@ -439,12 +400,93 @@ impl PersistentBitMatrixBuilder {
PersistentBitVecBuilder::new(self.n, &path)
}
pub fn add_col_ones(&mut self) -> io::Result<PersistentBitVecBuilder> {
let path = col_path(&self.dir, self.n_cols);
self.n_cols += 1;
PersistentBitVecBuilder::new_ones(self.n, &path)
}
pub fn add_col_from(&mut self, src: &TempBitVec) -> io::Result<()> {
src.make_persistent(&col_path(&self.dir, self.n_cols))?;
self.n_cols += 1;
Ok(())
}
pub fn add_col_from_int(&mut self, src: &TempCompactIntVec) -> io::Result<()> {
let path = col_path(&self.dir, self.n_cols);
self.n_cols += 1;
let mut b = PersistentBitVecBuilder::new(self.n, &path)?;
b.or_where(src.view(), |v| v > 0);
b.close()
}
pub fn close(self) -> io::Result<()> {
MatrixMeta { n: self.n, n_cols: self.n_cols }.save(&self.dir)
}
}
// ── Helpers ───────────────────────────────────────────────────────────────────
// ── MatrixGroupOps ────────────────────────────────────────────────────────────
impl MatrixGroupOps for PersistentBitMatrix {
fn partial_group_presence_count(&self, g: &ColGroup, _threshold: u32) -> io::Result<TempCompactIntVec> {
// Bit matrices store 0/1 — threshold is structurally always 1.
let n = self.n();
if g.indices.len() < 255 {
let mut builder = TempCompactIntVecBuilder::new(n)?;
for &c in &g.indices {
builder.inc_present_fast(self.col_view(c));
}
builder.freeze()
} else {
let mut result = TempCompactIntVecBuilder::new(n)?;
for chunk in g.indices.chunks(254) {
let mut chunk_b = TempCompactIntVecBuilder::new(n)?;
for &c in chunk {
chunk_b.inc_present_fast(self.col_view(c));
}
let frozen = chunk_b.freeze()?;
result.add(frozen.view());
}
result.freeze()
}
}
fn partial_group_sum(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {
// For bit matrices, sum = count of 1-bits — identical to presence_count.
self.partial_group_presence_count(g, 1)
}
fn partial_group_any(&self, g: &ColGroup, _threshold: u32) -> io::Result<TempBitVec> {
let n = self.n();
let mut result = TempBitVecBuilder::new(n)?;
for &c in &g.indices {
result.or(self.col_view(c));
}
result.freeze()
}
fn partial_group_min(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {
// min of 0/1 values = AND: 1 only if ALL columns are 1
let n = self.n();
let mut result = TempCompactIntVecBuilder::new(n)?;
if let Some((&first, rest)) = g.indices.split_first() {
result.inc_present_fast(self.col_view(first));
for &c in rest { result.mask_with(self.col_view(c)); }
}
result.freeze()
}
fn partial_group_max(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {
// max of 0/1 values = OR: 1 if any column is 1
let any = self.partial_group_any(g, 1)?;
let n = any.len();
let mut result = TempCompactIntVecBuilder::new(n)?;
result.inc_present(any.view());
result.freeze()
}
}
// ── Shared matrix helpers (also used by intmatrix.rs) ─────────────────────────
fn upper_pairs(n: usize) -> Vec<(usize, usize)> {
(0..n).flat_map(|i| (i + 1..n).map(move |j| (i, j))).collect()
@@ -456,3 +498,30 @@ where T: Clone + Default {
for (i, j, vij, vji) in vals { m[[i, j]] = vij; m[[j, i]] = vji; }
m
}
/// Compute a symmetric `n×n` matrix in parallel by evaluating `f(i,j)` for
/// all upper-triangle pairs. `T: Copy` avoids the `.clone()` needed for the
/// lower-triangle mirror.
pub(crate) fn pairwise_matrix<T>(n: usize, f: impl Fn(usize, usize) -> T + Sync) -> Array2<T>
where T: Copy + Default + Send {
let results: Vec<(usize, usize, T)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
/// Same as `pairwise_matrix` but `f` returns two values that fill two
/// symmetric matrices simultaneously (e.g. intersection + union for Jaccard).
pub(crate) fn pairwise2_matrix<T>(n: usize, f: impl Fn(usize, usize) -> (T, T) + Sync) -> (Array2<T>, Array2<T>)
where T: Copy + Default + Send {
let results: Vec<(usize, usize, T, T)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| { let (a, b) = f(i, j); (i, j, a, b) })
.collect();
let mut m0 = Array2::from_elem((n, n), T::default());
let mut m1 = Array2::from_elem((n, n), T::default());
for (i, j, a, b) in results {
m0[[i, j]] = a; m0[[j, i]] = a;
m1[[i, j]] = b; m1[[j, i]] = b;
}
(m0, m1)
}
src/obicompactvec/src/bitvec.rs
+197 -155
View File
@@ -5,25 +5,21 @@ use std::path::{Path, PathBuf};
use memmap2::{Mmap, MmapMut};
use crate::reader::PersistentCompactIntVec;
use crate::views::{BitSliceIter, BitSliceView, IntSliceView};
const MAGIC: [u8; 4] = *b"PBIV";
// Header: magic(4) + _pad(4) + n(8) = 16 bytes.
// Data starts at offset 16, which is divisible by 8 → u64-aligned
// (mmap base is page-aligned, 16 % 8 == 0).
// Data starts at offset 16, u64-aligned (mmap base is page-aligned, 16 % 8 == 0).
const HEADER_SIZE: usize = 16;
#[inline]
fn n_words(n: usize) -> usize {
n.div_ceil(64)
}
pub(crate) fn n_words(n: usize) -> usize { n.div_ceil(64) }
#[inline]
fn n_bytes_for_words(n: usize) -> usize {
n_words(n) * 8
}
fn n_bytes_for_words(n: usize) -> usize { n_words(n) * 8 }
// ── Reader ────────────────────────────────────────────────────────────────────
// ── PersistentBitVec ──────────────────────────────────────────────────────────
pub struct PersistentBitVec {
mmap: Mmap,
@@ -35,110 +31,64 @@ impl PersistentBitVec {
pub fn open(path: &Path) -> io::Result<Self> {
let mmap = unsafe { Mmap::map(&File::open(path)?)? };
if mmap.len() < HEADER_SIZE {
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"PBIV file too short",
));
return Err(io::Error::new(io::ErrorKind::InvalidData, "PBIV file too short"));
}
if &mmap[0..4] != &MAGIC {
return Err(io::Error::new(io::ErrorKind::InvalidData, "bad PBIV magic"));
}
let n = u64::from_le_bytes(mmap[8..16].try_into().unwrap()) as usize;
Ok(Self {
mmap,
n,
path: path.to_path_buf(),
})
Ok(Self { mmap, n, path: path.to_path_buf() })
}
pub fn path(&self) -> &Path {
&self.path
}
pub fn len(&self) -> usize {
self.n
}
pub fn is_empty(&self) -> bool {
self.n == 0
}
pub fn path(&self) -> &Path { &self.path }
pub fn len(&self) -> usize { self.n }
pub fn is_empty(&self) -> bool { self.n == 0 }
pub fn get(&self, slot: usize) -> bool {
(self.mmap[HEADER_SIZE + (slot >> 3)] >> (slot & 7)) & 1 != 0
}
// Used by iter() and get(): exact byte window, no padding.
fn data_bytes(&self) -> &[u8] {
&self.mmap[HEADER_SIZE..HEADER_SIZE + self.n.div_ceil(8)]
}
// Bulk word view. SAFETY: mmap is page-aligned, HEADER_SIZE=16 is divisible by 8,
// so &mmap[HEADER_SIZE] is u64-aligned. Slice length is n_words * 8 bytes.
// SAFETY: mmap is page-aligned, HEADER_SIZE=16 divisible by 8 → u64-aligned.
fn data_words(&self) -> &[u64] {
let nw = n_words(self.n);
let ptr = self.mmap[HEADER_SIZE..].as_ptr() as *const u64;
unsafe { std::slice::from_raw_parts(ptr, nw) }
}
pub fn count_ones(&self) -> u64 {
// Padding bits in the last word are 0, so no masking needed.
self.data_words()
.iter()
.map(|w| w.count_ones() as u64)
.sum()
pub fn view(&self) -> BitSliceView<'_> {
BitSliceView::new(self.data_words(), self.n)
}
pub fn count_zeros(&self) -> u64 {
self.n as u64 - self.count_ones()
}
pub fn words(&self) -> &[u64] { self.data_words() }
pub fn jaccard_dist(&self, other: &PersistentBitVec) -> f64 {
let (inter, union) = self.partial_jaccard_dist(other);
if union == 0 {
return 0.0;
}
1.0 - inter as f64 / union as f64
}
pub fn count_ones(&self) -> u64 { self.view().count_ones() }
pub fn count_zeros(&self) -> u64 { self.view().count_zeros() }
pub fn partial_jaccard_dist(&self, other: &PersistentBitVec) -> (u64, u64) {
assert_eq!(self.n, other.n, "length mismatch");
self.data_words()
.iter()
.zip(other.data_words())
.fold((0u64, 0u64), |(i, u), (&a, &b)| {
(
i + (a & b).count_ones() as u64,
u + (a | b).count_ones() as u64,
)
})
self.view().partial_jaccard_dist(other.view())
}
pub fn jaccard_dist(&self, other: &PersistentBitVec) -> f64 {
self.view().jaccard_dist(other.view())
}
pub fn hamming_dist(&self, other: &PersistentBitVec) -> u64 {
assert_eq!(self.n, other.n, "length mismatch");
self.data_words()
.iter()
.zip(other.data_words())
.map(|(&a, &b)| (a ^ b).count_ones() as u64)
.sum()
self.view().hamming_dist(other.view())
}
pub fn iter(&self) -> BitIter<'_> {
BitIter {
bytes: self.data_bytes(),
slot: 0,
n: self.n,
}
BitIter { words: self.data_words(), slot: 0, n: self.n }
}
}
impl<'a> IntoIterator for &'a PersistentBitVec {
type Item = bool;
type IntoIter = BitIter<'a>;
fn into_iter(self) -> BitIter<'a> {
self.iter()
}
fn into_iter(self) -> BitIter<'a> { self.iter() }
}
// ── BitIter ───────────────────────────────────────────────────────────────────
pub struct BitIter<'a> {
bytes: &'a [u8],
words: &'a [u64],
slot: usize,
n: usize,
}
@@ -147,45 +97,79 @@ impl ExactSizeIterator for BitIter<'_> {}
impl Iterator for BitIter<'_> {
type Item = bool;
fn next(&mut self) -> Option<bool> {
if self.slot >= self.n {
return None;
}
let v = (self.bytes[self.slot >> 3] >> (self.slot & 7)) & 1 != 0;
if self.slot >= self.n { return None; }
let v = (self.words[self.slot >> 6] >> (self.slot & 63)) & 1 != 0;
self.slot += 1;
Some(v)
}
fn size_hint(&self) -> (usize, Option<usize>) {
let rem = self.n - self.slot;
(rem, Some(rem))
}
}
// ── Builder ───────────────────────────────────────────────────────────────────
// ── PersistentBitVecBuilder ───────────────────────────────────────────────────
pub struct PersistentBitVecBuilder {
mmap: MmapMut,
n: usize,
path: PathBuf,
}
impl PersistentBitVecBuilder {
pub fn new(n: usize, path: &Path) -> io::Result<Self> {
let file_size = HEADER_SIZE + n_bytes_for_words(n);
let mut file = OpenOptions::new()
.read(true)
.write(true)
.create(true)
.truncate(true)
.read(true).write(true).create(true).truncate(true)
.open(path)?;
file.write_all(&MAGIC)?;
file.write_all(&[0u8; 4])?; // padding
file.write_all(&[0u8; 4])?;
file.write_all(&(n as u64).to_le_bytes())?;
file.seek(SeekFrom::Start(0))?;
file.set_len(file_size as u64)?;
let mmap = unsafe { MmapMut::map_mut(&file)? };
Ok(Self { mmap, n })
Ok(Self { mmap, n, path: path.to_path_buf() })
}
pub fn from_raw_bytes(bytes: &[u8], n: usize, path: &Path) -> io::Result<Self> {
let file_size = HEADER_SIZE + n_bytes_for_words(n);
let file = OpenOptions::new()
.read(true).write(true).create(true).truncate(true)
.open(path)?;
file.set_len(file_size as u64)?;
let mut mmap = unsafe { MmapMut::map_mut(&file)? };
mmap[0..4].copy_from_slice(&MAGIC);
mmap[8..16].copy_from_slice(&(n as u64).to_le_bytes());
mmap[HEADER_SIZE..HEADER_SIZE + bytes.len()].copy_from_slice(bytes);
Ok(Self { mmap, n, path: path.to_path_buf() })
}
/// Create an all-ones bit vector of length `n` at `path`.
///
/// More efficient than `new(n, path)` + `not()`: the data is written as
/// 0xFF bytes in a single sequential pass, with no intermediate all-zeros state.
pub fn new_ones(n: usize, path: &Path) -> io::Result<Self> {
let nw = n_words(n);
let file_size = HEADER_SIZE + nw * 8;
let mut file = OpenOptions::new()
.read(true).write(true).create(true).truncate(true)
.open(path)?;
file.write_all(&MAGIC)?;
file.write_all(&[0u8; 4])?;
file.write_all(&(n as u64).to_le_bytes())?;
file.write_all(&vec![0xFFu8; nw * 8])?;
file.seek(SeekFrom::Start(0))?;
file.set_len(file_size as u64)?;
let mut mmap = unsafe { MmapMut::map_mut(&file)? };
// Clear padding bits in the last word so trailing bits are always 0.
let rem = n % 64;
if rem != 0 {
let ptr = mmap[HEADER_SIZE..].as_mut_ptr() as *mut u64;
let words = unsafe { std::slice::from_raw_parts_mut(ptr, nw) };
words[nw - 1] &= (1u64 << rem) - 1;
}
Ok(Self { mmap, n, path: path.to_path_buf() })
}
pub fn build_from(source: &PersistentBitVec, path: &Path) -> io::Result<Self> {
@@ -193,28 +177,53 @@ impl PersistentBitVecBuilder {
let file = OpenOptions::new().read(true).write(true).open(path)?;
let mmap = unsafe { MmapMut::map_mut(&file)? };
let n = source.len();
Ok(Self { mmap, n })
Ok(Self { mmap, n, path: path.to_path_buf() })
}
pub fn len(&self) -> usize {
self.n
pub fn build_from_counts(source: &PersistentCompactIntVec, threshold: u32, path: &Path) -> io::Result<Self> {
let n = source.len();
let file_size = HEADER_SIZE + n_bytes_for_words(n);
let mut file = OpenOptions::new()
.read(true).write(true).create(true).truncate(true)
.open(path)?;
file.write_all(&MAGIC)?;
file.write_all(&[0u8; 4])?;
file.write_all(&(n as u64).to_le_bytes())?;
file.seek(SeekFrom::Start(0))?;
file.set_len(file_size as u64)?;
let mut mmap = unsafe { MmapMut::map_mut(&file)? };
{
let nw = n_words(n);
let ptr = mmap[HEADER_SIZE..].as_mut_ptr() as *mut u64;
let words = unsafe { std::slice::from_raw_parts_mut(ptr, nw) };
for (slot, count) in source.iter().enumerate() {
if count >= threshold { words[slot >> 6] |= 1u64 << (slot & 63); }
}
pub fn is_empty(&self) -> bool {
self.n == 0
}
Ok(Self { mmap, n, path: path.to_path_buf() })
}
pub fn build_from_presence(source: &PersistentCompactIntVec, path: &Path) -> io::Result<Self> {
Self::build_from_counts(source, 1, path)
}
pub fn len(&self) -> usize { self.n }
pub fn is_empty(&self) -> bool { self.n == 0 }
pub fn get(&self, slot: usize) -> bool {
(self.mmap[HEADER_SIZE + (slot >> 3)] >> (slot & 7)) & 1 != 0
}
pub fn set(&mut self, slot: usize, value: bool) {
let byte = HEADER_SIZE + (slot >> 3);
let bit = 1u8 << (slot & 7);
if value {
self.mmap[byte] |= bit;
} else {
self.mmap[byte] &= !bit;
let bit = 1u64 << (slot & 63);
if value { self.data_words_mut()[slot >> 6] |= bit; }
else { self.data_words_mut()[slot >> 6] &= !bit; }
}
fn data_words(&self) -> &[u64] {
let nw = n_words(self.n);
let ptr = self.mmap[HEADER_SIZE..].as_ptr() as *const u64;
unsafe { std::slice::from_raw_parts(ptr, nw) }
}
// SAFETY: same alignment argument as PersistentBitVec::data_words.
@@ -224,83 +233,116 @@ impl PersistentBitVecBuilder {
unsafe { std::slice::from_raw_parts_mut(ptr, nw) }
}
pub fn and(&mut self, other: &PersistentBitVec) {
assert_eq!(self.n, other.n, "length mismatch");
for (sw, &ow) in self.data_words_mut().iter_mut().zip(other.data_words()) {
*sw &= ow;
}
pub fn view(&self) -> BitSliceView<'_> {
BitSliceView::new(self.data_words(), self.n)
}
pub fn or(&mut self, other: &PersistentBitVec) {
assert_eq!(self.n, other.n, "length mismatch");
for (sw, &ow) in self.data_words_mut().iter_mut().zip(other.data_words()) {
*sw |= ow;
}
pub fn words(&self) -> &[u64] { self.data_words() }
pub fn copy_from(&mut self, src: BitSliceView<'_>) {
assert_eq!(self.n, src.len(), "BitSliceView length mismatch");
self.data_words_mut().copy_from_slice(src.words());
}
pub fn xor(&mut self, other: &PersistentBitVec) {
assert_eq!(self.n, other.n, "length mismatch");
for (sw, &ow) in self.data_words_mut().iter_mut().zip(other.data_words()) {
*sw ^= ow;
pub fn and(&mut self, other: BitSliceView<'_>) {
assert_eq!(self.n, other.len(), "BitSliceView length mismatch");
for (w, &o) in self.data_words_mut().iter_mut().zip(other.words()) { *w &= o; }
}
pub fn or(&mut self, other: BitSliceView<'_>) {
assert_eq!(self.n, other.len(), "BitSliceView length mismatch");
for (w, &o) in self.data_words_mut().iter_mut().zip(other.words()) { *w |= o; }
}
pub fn xor(&mut self, other: BitSliceView<'_>) {
assert_eq!(self.n, other.len(), "BitSliceView length mismatch");
for (w, &o) in self.data_words_mut().iter_mut().zip(other.words()) { *w ^= o; }
}
pub fn not(&mut self) {
let rem = self.n % 64;
let words = self.data_words_mut();
for w in words.iter_mut() {
*w ^= u64::MAX;
}
// Zero padding bits in the last word so count_ones / jaccard remain correct.
for w in words.iter_mut() { *w ^= u64::MAX; }
if rem != 0 {
if let Some(last) = words.last_mut() {
*last &= (1u64 << rem) - 1;
}
if let Some(last) = words.last_mut() { *last &= (1u64 << rem) - 1; }
}
}
/// Convert a count vector to a bit vector: bit set iff count >= threshold.
/// Fills u64 words directly from the count iterator — O(n), no bit-level set() overhead.
pub fn build_from_counts(
source: &PersistentCompactIntVec,
threshold: u32,
path: &Path,
) -> io::Result<Self> {
let n = source.len();
let file_size = HEADER_SIZE + n_bytes_for_words(n);
let mut file = OpenOptions::new()
.read(true)
.write(true)
.create(true)
.truncate(true)
.open(path)?;
file.write_all(&MAGIC)?;
file.write_all(&[0u8; 4])?;
file.write_all(&(n as u64).to_le_bytes())?;
file.seek(SeekFrom::Start(0))?;
file.set_len(file_size as u64)?;
let mut mmap = unsafe { MmapMut::map_mut(&file)? };
{
/// OR in bits at slots where `pred(col[slot])` is true.
pub fn or_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
assert_eq!(self.n, col.len(), "IntSliceView length mismatch");
let n = self.n;
let primary = col.primary_bytes();
let words = self.data_words_mut();
let nw = n_words(n);
let ptr = mmap[HEADER_SIZE..].as_mut_ptr() as *mut u64;
let words = unsafe { std::slice::from_raw_parts_mut(ptr, nw) };
for (slot, count) in source.iter().enumerate() {
if count >= threshold {
words[slot >> 6] |= 1u64 << (slot & 63);
for wi in 0..nw {
let base = wi * 64;
let limit = (base + 64).min(n);
let mut mask = 0u64;
for bit in 0..(limit - base) {
let b = primary[base + bit];
if b < 255 && pred(b as u32) { mask |= 1u64 << bit; }
}
words[wi] |= mask;
}
for (slot, val) in col.overflow_entries() {
if pred(val) { words[slot >> 6] |= 1u64 << (slot & 63); }
}
}
Ok(Self { mmap, n })
/// Clear bits at slots where `pred(col[slot])` is false.
pub fn and_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
assert_eq!(self.n, col.len(), "IntSliceView length mismatch");
let n = self.n;
let primary = col.primary_bytes();
let words = self.data_words_mut();
let nw = n_words(n);
for wi in 0..nw {
let base = wi * 64;
let limit = (base + 64).min(n);
let mut mask = 0u64;
for bit in 0..(limit - base) {
let b = primary[base + bit];
if b < 255 && !pred(b as u32) { mask |= 1u64 << bit; }
}
words[wi] &= !mask;
}
for (slot, val) in col.overflow_entries() {
if !pred(val) { words[slot >> 6] &= !(1u64 << (slot & 63)); }
}
}
/// Convert a count vector to a presence/absence bit vector (threshold = 1).
pub fn build_from_presence(source: &PersistentCompactIntVec, path: &Path) -> io::Result<Self> {
Self::build_from_counts(source, 1, path)
/// Toggle bits at slots where `pred(col[slot])` is true.
pub fn xor_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
assert_eq!(self.n, col.len(), "IntSliceView length mismatch");
let n = self.n;
let primary = col.primary_bytes();
let words = self.data_words_mut();
let nw = n_words(n);
for wi in 0..nw {
let base = wi * 64;
let limit = (base + 64).min(n);
let mut mask = 0u64;
for bit in 0..(limit - base) {
let b = primary[base + bit];
if b < 255 && pred(b as u32) { mask |= 1u64 << bit; }
}
words[wi] ^= mask;
}
for (slot, val) in col.overflow_entries() {
if pred(val) { words[slot >> 6] ^= 1u64 << (slot & 63); }
}
}
pub fn close(self) -> io::Result<()> {
self.mmap.flush()
pub fn iter(&self) -> BitSliceIter<'_> {
self.view().iter()
}
pub fn close(self) -> io::Result<()> { self.mmap.flush() }
pub fn finish(self) -> io::Result<PersistentBitVec> {
let path = self.path.clone();
self.close()?;
PersistentBitVec::open(&path)
}
}
src/obicompactvec/src/builder.rs
+190 -64
View File
@@ -5,8 +5,9 @@ use std::path::{Path, PathBuf};
use memmap2::MmapMut;
use crate::format::{HEADER_SIZE, OVERFLOW_ENTRY_SIZE, finalize_pciv};
use crate::format::{byte_count_nonzero, byte_sum, HEADER_SIZE, finalize_pciv, parse_overflow_entry};
use crate::reader::PersistentCompactIntVec;
use crate::views::{BitSliceView, IntSliceView};
pub struct PersistentCompactIntVecBuilder {
path: PathBuf,
@@ -16,59 +17,44 @@ pub struct PersistentCompactIntVecBuilder {
}
impl PersistentCompactIntVecBuilder {
/// Create a new, zero-filled PCIV at `path`. Primary is mmapped immediately.
pub fn new(n: usize, path: &Path) -> io::Result<Self> {
let file = OpenOptions::new()
.read(true)
.write(true)
.create(true)
.truncate(true)
.read(true).write(true).create(true).truncate(true)
.open(path)?;
file.set_len((HEADER_SIZE + n) as u64)?;
let mmap = unsafe { MmapMut::map_mut(&file)? };
Ok(Self {
path: path.to_path_buf(),
mmap,
n,
overflow: HashMap::new(),
})
Ok(Self { path: path.to_path_buf(), mmap, n, overflow: HashMap::new() })
}
pub fn from_raw_primary(primary: &[u8], overflow: HashMap<usize, u32>, path: &Path) -> io::Result<Self> {
let n = primary.len();
let file = OpenOptions::new()
.read(true).write(true).create(true).truncate(true)
.open(path)?;
file.set_len((HEADER_SIZE + n) as u64)?;
let mut mmap = unsafe { MmapMut::map_mut(&file)? };
mmap[HEADER_SIZE..HEADER_SIZE + n].copy_from_slice(primary);
Ok(Self { path: path.to_path_buf(), mmap, n, overflow })
}
/// Copy `source`'s file to `path`, mmap the primary section, load overflow into RAM.
/// Avoids iterating all n slots: the file copy is OS-level, overflow loading is O(n_overflow).
pub fn build_from(source: &PersistentCompactIntVec, path: &Path) -> io::Result<Self> {
fs::copy(source.path(), path)?;
let file = OpenOptions::new().read(true).write(true).open(path)?;
let mmap = unsafe { MmapMut::map_mut(&file)? };
let n = source.len();
let n_overflow = u64::from_le_bytes(mmap[16..24].try_into().unwrap()) as usize;
let data_offset = HEADER_SIZE + n;
let mut overflow = HashMap::with_capacity(n_overflow);
for i in 0..n_overflow {
let off = data_offset + i * OVERFLOW_ENTRY_SIZE;
let slot = u64::from_le_bytes(mmap[off..off + 8].try_into().unwrap()) as usize;
let value = u32::from_le_bytes(mmap[off + 8..off + 12].try_into().unwrap());
let (slot, value) = parse_overflow_entry(&mmap, data_offset, i);
overflow.insert(slot, value);
}
Ok(Self {
path: path.to_path_buf(),
mmap,
n,
overflow,
})
Ok(Self { path: path.to_path_buf(), mmap, n, overflow })
}
/// Get the value at the given slot, handling overflow if necessary.
pub fn get(&self, slot: usize) -> u32 {
match self.mmap[HEADER_SIZE + slot] {
255 => *self
.overflow
.get(&slot)
.expect("sentinel without overflow entry"),
255 => *self.overflow.get(&slot).expect("sentinel without overflow entry"),
v => v as u32,
}
}
@@ -83,61 +69,201 @@ impl PersistentCompactIntVecBuilder {
}
}
pub fn len(&self) -> usize {
self.n
pub fn len(&self) -> usize { self.n }
pub fn is_empty(&self) -> bool { self.n == 0 }
pub fn primary_bytes(&self) -> &[u8] { &self.mmap[HEADER_SIZE..HEADER_SIZE + self.n] }
pub fn primary_bytes_mut(&mut self) -> &mut [u8] { &mut self.mmap[HEADER_SIZE..HEADER_SIZE + self.n] }
pub fn clear_overflow(&mut self) { self.overflow.clear(); }
pub fn sum(&self) -> u64 {
byte_sum(&self.mmap[HEADER_SIZE..HEADER_SIZE + self.n], self.overflow.values().copied())
}
pub fn count_nonzero(&self) -> u64 {
byte_count_nonzero(&self.mmap[HEADER_SIZE..HEADER_SIZE + self.n])
}
pub fn is_empty(&self) -> bool {
self.n == 0
pub fn view(&self) -> IntSliceView<'_> {
// Builder overflow is a HashMap, not sorted raw bytes — convert on the fly
// by collecting into a sorted vec and storing in a thread-local buffer.
// For read-back during building, just call get(slot) directly.
// view() is primarily useful AFTER freeze (on PersistentCompactIntVec).
// Here we expose it via a zero-alloc path: primary only, no overflow raw.
// Callers that need overflow_entries during building use overflow_entries().
let primary = &self.mmap[HEADER_SIZE..HEADER_SIZE + self.n];
IntSliceView::new(primary, &[], 0, self.n)
}
pub fn min(&mut self, other: &PersistentCompactIntVec) {
assert_eq!(self.n, other.len(), "length mismatch");
for (slot, other_val) in other.iter().enumerate() {
if other_val < self.get(slot) {
self.set(slot, other_val);
pub fn overflow_entries(&self) -> impl Iterator<Item = (usize, u32)> + '_ {
self.overflow.iter().map(|(&k, &v)| (k, v))
}
pub fn inc(&mut self, slot: usize) {
let v = self.get(slot);
self.set(slot, v.saturating_add(1));
}
// ── Computation methods ───────────────────────────────────────────────────
/// Increment one counter per 1-bit of `col`. Safe for any group size.
pub fn inc_present(&mut self, col: BitSliceView<'_>) {
let n = self.n;
for (wi, &word) in col.words().iter().enumerate() {
if word == 0 { continue; }
let mut w = word;
while w != 0 {
let bit = w.trailing_zeros() as usize;
let slot = wi * 64 + bit;
if slot < n { self.inc(slot); }
w &= w - 1;
}
}
}
pub fn max(&mut self, other: &PersistentCompactIntVec) {
assert_eq!(self.n, other.len(), "length mismatch");
for (slot, other_val) in other.iter().enumerate() {
if other_val > self.get(slot) {
self.set(slot, other_val);
/// Increment one counter per 1-bit of `col`, using raw u8 arithmetic.
/// Caller guarantees no counter will reach 255 (group size < 255).
pub fn inc_present_fast(&mut self, col: BitSliceView<'_>) {
{
let primary = self.primary_bytes_mut();
let n = primary.len();
for (wi, &word) in col.words().iter().enumerate() {
if word == 0 { continue; }
let mut w = word;
while w != 0 {
let bit = w.trailing_zeros() as usize;
let s = wi * 64 + bit;
if s < n { primary[s] += 1; }
w &= w - 1;
}
}
}
debug_assert!(
!self.primary_bytes().contains(&255),
"sentinel 255 reached in inc_present_fast — group size must be < 255"
);
}
/// Two-pass: primary bytes then overflow. Increments `self[slot]` for each
/// slot where `pred(col[slot])` is true. Safe for any group size.
pub fn inc_predicate(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
let n = col.len();
for slot in 0..n {
let b = col.primary_bytes()[slot];
if b < 255 && pred(b as u32) {
self.inc(slot);
}
}
for (slot, val) in col.overflow_entries() {
if pred(val) { self.inc(slot); }
}
}
/// Fast two-pass: raw u8 arithmetic. Caller guarantees no counter reaches 255.
pub fn inc_predicate_fast(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
let n = col.len();
{
let primary = self.primary_bytes_mut();
for slot in 0..n {
let b = col.primary_bytes()[slot];
if b < 255 && pred(b as u32) {
primary[slot] += 1;
}
}
}
for (slot, val) in col.overflow_entries() {
if pred(val) { self.primary_bytes_mut()[slot] += 1; }
}
debug_assert!(
!self.primary_bytes().contains(&255),
"sentinel 255 reached in inc_predicate_fast — group size must be < 255"
);
}
pub fn add(&mut self, other: IntSliceView<'_>) {
let n = self.n;
for s in 0..n {
let sb = self.primary_bytes()[s];
let ob = other.primary_bytes()[s];
if sb < 255 && ob < 255 {
let sum = sb as u32 + ob as u32;
if sum < 255 { self.primary_bytes_mut()[s] = sum as u8; }
else { self.set(s, sum); }
} else {
let sv = self.get(s);
let ov = other.get(s);
self.set(s, sv + ov);
}
}
}
pub fn add(&mut self, other: &PersistentCompactIntVec) {
assert_eq!(self.n, other.len(), "length mismatch");
for (slot, other_val) in other.iter().enumerate() {
let cur = self.get(slot);
self.set(slot, cur.checked_add(other_val).expect("u32 overflow in add"));
pub fn min(&mut self, other: IntSliceView<'_>) {
let self_ov: Vec<(usize, u32)> = self.overflow_entries().collect();
let other_ov: HashMap<usize, u32> = other.overflow_entries().collect();
self.clear_overflow();
for (a, &b) in self.primary_bytes_mut().iter_mut().zip(other.primary_bytes()) {
if b < *a { *a = b; }
}
for (slot, self_val) in self_ov {
if let Some(&other_val) = other_ov.get(&slot) {
self.set(slot, self_val.min(other_val));
}
}
}
pub fn diff(&mut self, other: &PersistentCompactIntVec) {
assert_eq!(self.n, other.len(), "length mismatch");
for (slot, other_val) in other.iter().enumerate() {
self.set(slot, self.get(slot).saturating_sub(other_val));
pub fn max(&mut self, other: IntSliceView<'_>) {
for (slot, other_val) in other.overflow_entries() {
let sv = self.get(slot);
self.set(slot, sv.max(other_val));
}
for (a, &b) in self.primary_bytes_mut().iter_mut().zip(other.primary_bytes()) {
if b > *a { *a = b; }
}
}
pub fn diff(&mut self, other: IntSliceView<'_>) {
let n = self.n;
for s in 0..n {
let sb = self.primary_bytes()[s];
let ob = other.primary_bytes()[s];
if sb < 255 {
self.primary_bytes_mut()[s] = if ob < 255 { sb.saturating_sub(ob) } else { 0 };
} else {
let sv = self.get(s);
let ov = if ob < 255 { ob as u32 } else { other.get(s) };
self.set(s, sv.saturating_sub(ov));
}
}
}
pub fn mask_with(&mut self, mask: BitSliceView<'_>) {
let n = self.n;
for (wi, &word) in mask.words().iter().enumerate() {
if word == u64::MAX { continue; }
let mut zeros = !word;
while zeros != 0 {
let bit = zeros.trailing_zeros() as usize;
let s = wi * 64 + bit;
if s < n {
let b = self.primary_bytes()[s];
if b != 0 { self.set(s, 0); }
}
zeros &= zeros - 1;
}
}
}
/// Flush the primary mmap, then write sorted overflow data + index and fix the header.
pub fn close(self) -> io::Result<()> {
self.mmap.flush()?;
let Self {
path,
mmap,
n,
overflow,
} = self;
let Self { path, mmap, n, overflow } = self;
drop(mmap);
let mut entries: Vec<(usize, u32)> = overflow.into_iter().collect();
entries.sort_unstable_by_key(|&(slot, _)| slot);
finalize_pciv(&path, n, &entries)
}
pub fn finish(self) -> io::Result<PersistentCompactIntVec> {
let path = self.path.clone();
self.close()?;
PersistentCompactIntVec::open(&path)
}
}
src/obicompactvec/src/colgroup.rs
+137
View File
@@ -0,0 +1,137 @@
use std::io;
use crate::tempbitvec::{TempBitVec, TempBitVecBuilder};
use crate::tempintvec::TempCompactIntVec;
// ── ColGroup ──────────────────────────────────────────────────────────────────
/// A named subset of columns, identified by their indices within the matrix.
///
/// Defined once at the index level; the same indices are valid across all
/// partitions and layers because the column structure (samples / genomes) is
/// identical everywhere — only the row space (kmer slots) is partitioned.
pub struct ColGroup {
pub name: String,
pub indices: Vec<usize>,
}
impl ColGroup {
pub fn new(name: impl Into<String>, indices: Vec<usize>) -> Self {
Self { name: name.into(), indices }
}
}
// ── MatrixGroupOps ────────────────────────────────────────────────────────────
/// Per-matrix group aggregations.
///
/// `partial_group_presence_count`, `partial_group_sum`, `partial_group_any`,
/// `partial_group_min`, `partial_group_max` are the primitives; each impl must
/// provide all five.
///
/// `partial_group_all` and `partial_group_none` have default implementations
/// derived from `partial_group_presence_count` and should rarely need overriding.
pub trait MatrixGroupOps {
/// Per-slot count of group columns whose value ≥ `threshold`.
fn partial_group_presence_count(&self, g: &ColGroup, threshold: u32) -> io::Result<TempCompactIntVec>;
/// Per-slot sum of values across all group columns.
fn partial_group_sum(&self, g: &ColGroup) -> io::Result<TempCompactIntVec>;
/// Per-slot OR: 1 if any group column has value ≥ `threshold`.
fn partial_group_any(&self, g: &ColGroup, threshold: u32) -> io::Result<TempBitVec>;
/// Per-slot min value across all group columns (0 if group is empty).
fn partial_group_min(&self, g: &ColGroup) -> io::Result<TempCompactIntVec>;
/// Per-slot max value across all group columns (0 if group is empty).
fn partial_group_max(&self, g: &ColGroup) -> io::Result<TempCompactIntVec>;
/// Per-slot AND: 1 if ALL group columns have value ≥ `threshold`.
fn partial_group_all(&self, g: &ColGroup, threshold: u32) -> io::Result<TempBitVec> {
let counts = self.partial_group_presence_count(g, threshold)?;
let n = counts.len();
let n_required = g.indices.len() as u32;
let mut b = TempBitVecBuilder::new(n)?;
b.or_where(counts.view(), |v| v >= n_required);
b.freeze()
}
/// Per-slot NOR: 1 if NO group column has value ≥ `threshold`.
fn partial_group_none(&self, g: &ColGroup, threshold: u32) -> io::Result<TempBitVec> {
let counts = self.partial_group_presence_count(g, threshold)?;
let n = counts.len();
let mut b = TempBitVecBuilder::new(n)?;
b.or_where(counts.view(), |v| v == 0);
b.freeze()
}
}
// ── FilterMask — expression tree for column-based slot filters ────────────────
/// A composable filter expression that can be evaluated against a matrix
/// using only column operations (no MPHF lookup per kmer).
///
/// `threshold` semantics follow [`MatrixGroupOps::partial_group_presence_count`]:
/// a slot contributes to the count when its value is **≥ threshold**.
/// To match the row-level filter (`value > t`), callers should pass `t + 1`.
#[derive(Debug, Clone)]
pub enum FilterMask {
/// Slot passes if count of columns in `indices` with value ≥ `threshold` is ≥ `min_count`.
PresenceGeq { indices: Vec<usize>, threshold: u32, min_count: usize },
/// Slot passes if count of columns in `indices` with value ≥ `threshold` is ≤ `max_count`.
PresenceLeq { indices: Vec<usize>, threshold: u32, max_count: usize },
/// Slot passes if sum of values across `indices` columns is ≥ `min_sum`.
SumGeq { indices: Vec<usize>, min_sum: u32 },
/// Slot passes if sum of values across `indices` columns is ≤ `max_sum`.
SumLeq { indices: Vec<usize>, max_sum: u32 },
/// Slot passes if it passes all sub-expressions. Empty `And` is always true.
And(Vec<FilterMask>),
}
/// Evaluate a [`FilterMask`] against `mat`, returning a per-slot `TempBitVec`
/// where bit=1 means the slot passes the filter.
pub fn eval_filter_mask(expr: &FilterMask, mat: &dyn MatrixGroupOps, n: usize) -> io::Result<TempBitVec> {
match expr {
FilterMask::PresenceGeq { indices, threshold, min_count } => {
let g = ColGroup::new("", indices.clone());
let counts = mat.partial_group_presence_count(&g, *threshold)?;
let mut b = TempBitVecBuilder::new(n)?;
let mc = *min_count as u32;
b.or_where(counts.view(), |v| v >= mc);
b.freeze()
}
FilterMask::PresenceLeq { indices, threshold, max_count } => {
let g = ColGroup::new("", indices.clone());
let counts = mat.partial_group_presence_count(&g, *threshold)?;
let mut b = TempBitVecBuilder::new(n)?;
let mc = *max_count as u32;
b.or_where(counts.view(), |v| v <= mc);
b.freeze()
}
FilterMask::SumGeq { indices, min_sum } => {
let g = ColGroup::new("", indices.clone());
let sums = mat.partial_group_sum(&g)?;
let mut b = TempBitVecBuilder::new(n)?;
let ms = *min_sum;
b.or_where(sums.view(), |v| v >= ms);
b.freeze()
}
FilterMask::SumLeq { indices, max_sum } => {
let g = ColGroup::new("", indices.clone());
let sums = mat.partial_group_sum(&g)?;
let mut b = TempBitVecBuilder::new(n)?;
let ms = *max_sum;
b.or_where(sums.view(), |v| v <= ms);
b.freeze()
}
FilterMask::And(parts) => {
let mut b = TempBitVecBuilder::new_ones(n)?;
for part in parts {
let m = eval_filter_mask(part, mat, n)?;
b.and(m.view());
}
b.freeze()
}
}
}
src/obicompactvec/src/format.rs
+38
View File
@@ -13,6 +13,44 @@ pub const OVERFLOW_ENTRY_SIZE: usize = 12;
// Index entry: slot(u64) + pos(u64) = 16 bytes.
pub const INDEX_ENTRY_SIZE: usize = 16;
/// Sum all values in a compact-int primary byte slice, correcting for overflow sentinels.
///
/// `primary` is the raw `&[u8]` where 255 is a sentinel for large values.
/// `overflow` yields the true values (≥ 255) for each sentinel, in any order.
#[inline]
pub(crate) fn byte_sum(primary: &[u8], overflow: impl Iterator<Item = u32>) -> u64 {
let raw: u64 = primary.iter().map(|&b| b as u64).sum();
let (n, ov) = overflow.fold((0u64, 0u64), |(n, s), v| (n + 1, s + v as u64));
raw - 255 * n + ov
}
/// Count non-zero values in a compact-int primary byte slice.
///
/// Overflow sentinels (255) are always non-zero by construction, so a single
/// `b != 0` test is sufficient — no overflow map lookup needed.
#[inline]
pub(crate) fn byte_count_nonzero(primary: &[u8]) -> u64 {
primary.iter().filter(|&&b| b != 0).count() as u64
}
/// Parse a single overflow entry `(slot, value)` from a byte slice.
#[inline]
pub fn parse_overflow_entry(data: &[u8], base: usize, i: usize) -> (usize, u32) {
let off = base + i * OVERFLOW_ENTRY_SIZE;
let slot = u64::from_le_bytes(data[off..off+8].try_into().unwrap()) as usize;
let value = u32::from_le_bytes(data[off+8..off+12].try_into().unwrap());
(slot, value)
}
/// Parse a single sparse-index entry `(slot, pos)` from a byte slice.
#[inline]
pub fn parse_index_entry(data: &[u8], base: usize, i: usize) -> (usize, usize) {
let off = base + i * INDEX_ENTRY_SIZE;
let slot = u64::from_le_bytes(data[off..off+8].try_into().unwrap()) as usize;
let pos = u64::from_le_bytes(data[off+8..off+16].try_into().unwrap()) as usize;
(slot, pos)
}
// Sparse index target: ≤ 32 KB in L1 cache (16 B per entry → 2048 entries).
pub const L1_INDEX_ENTRIES: usize = 2048;
src/obicompactvec/src/intmatrix.rs
+136 -212
View File
@@ -1,4 +1,3 @@
use std::cmp::Ordering;
use std::fs::{self, File};
use std::io::{self, BufWriter, Write as _};
use std::path::{Path, PathBuf};
@@ -7,10 +6,15 @@ use memmap2::Mmap;
use ndarray::{Array1, Array2};
use rayon::prelude::*;
use crate::bitmatrix::{pairwise_matrix, pairwise2_matrix};
use crate::builder::PersistentCompactIntVecBuilder;
use crate::format::{HEADER_SIZE, INDEX_ENTRY_SIZE, OVERFLOW_ENTRY_SIZE};
use crate::colgroup::{ColGroup, MatrixGroupOps};
use crate::format::{HEADER_SIZE, OVERFLOW_ENTRY_SIZE};
use crate::meta::MatrixMeta;
use crate::reader::PersistentCompactIntVec;
use crate::tempbitvec::{TempBitVec, TempBitVecBuilder};
use crate::tempintvec::{TempCompactIntVec, TempCompactIntVecBuilder};
use crate::views::IntSliceView;
fn col_path(dir: &Path, col: usize) -> PathBuf {
dir.join(format!("col_{col:06}.pciv"))
@@ -41,9 +45,7 @@ impl ColumnarCompactIntMatrix {
}
pub(crate) fn fill_row(&self, slot: usize, buf: &mut [u32]) {
for (c, col) in self.cols.iter().enumerate() {
buf[c] = col.get(slot);
}
for (c, col) in self.cols.iter().enumerate() { buf[c] = col.get(slot); }
}
pub(crate) fn sum(&self) -> Array1<u64> {
@@ -63,49 +65,26 @@ impl ColumnarCompactIntMatrix {
}
pub(crate) fn partial_bray_dist_matrix(&self) -> Array2<u64> {
self.pairwise_u64(|i, j| self.col(i).partial_bray_dist(self.col(j)))
pairwise_matrix(self.n_cols(), |i, j| self.col(i).partial_bray_dist(self.col(j)))
}
pub(crate) fn partial_euclidean_dist_matrix(&self) -> Array2<f64> {
self.pairwise(|i, j| self.col(i).partial_euclidean_dist(self.col(j)))
pairwise_matrix(self.n_cols(), |i, j| self.col(i).partial_euclidean_dist(self.col(j)))
}
pub(crate) fn partial_threshold_jaccard_dist_matrix(
&self, threshold: u32,
) -> (Array2<u64>, Array2<u64>) {
let n = self.n_cols();
let pairs = upper_pairs(n);
let results: Vec<(usize, usize, u64, u64)> = pairs
.into_par_iter()
.map(|(i, j)| {
let (inter, union) =
self.col(i).partial_threshold_jaccard_dist(self.col(j), threshold);
(i, j, inter, union)
})
.collect();
let mut inter_m = Array2::zeros((n, n));
let mut union_m = Array2::zeros((n, n));
for (i, j, inter, union) in results {
inter_m[[i, j]] = inter; inter_m[[j, i]] = inter;
union_m[[i, j]] = union; union_m[[j, i]] = union;
pub(crate) fn partial_threshold_jaccard_dist_matrix(&self, threshold: u32) -> (Array2<u64>, Array2<u64>) {
pairwise2_matrix(self.n_cols(), |i, j| self.col(i).partial_threshold_jaccard_dist(self.col(j), threshold))
}
(inter_m, union_m)
}
pub(crate) fn partial_relfreq_bray_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| {
pairwise_matrix(self.n_cols(), |i, j| {
self.col(i).partial_relfreq_bray_dist(self.col(j), col_sums[i] as f64, col_sums[j] as f64)
})
}
pub(crate) fn partial_relfreq_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| {
pairwise_matrix(self.n_cols(), |i, j| {
self.col(i).partial_relfreq_euclidean_dist(self.col(j), col_sums[i] as f64, col_sums[j] as f64)
})
}
pub(crate) fn partial_hellinger_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| {
pairwise_matrix(self.n_cols(), |i, j| {
self.col(i).partial_hellinger_euclidean_dist(self.col(j), col_sums[i] as f64, col_sums[j] as f64)
})
}
@@ -118,20 +97,6 @@ impl ColumnarCompactIntMatrix {
meta.n_cols += 1;
meta.save(dir)
}
fn pairwise(&self, f: impl Fn(usize, usize) -> f64 + Sync) -> Array2<f64> {
let n = self.n_cols();
let results: Vec<(usize, usize, f64)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
fn pairwise_u64(&self, f: impl Fn(usize, usize) -> u64 + Sync) -> Array2<u64> {
let n = self.n_cols();
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
}
}
// ── PackedCompactIntMatrix ────────────────────────────────────────────────────
@@ -139,13 +104,10 @@ impl ColumnarCompactIntMatrix {
const PCMX_MAGIC: [u8; 4] = *b"PCMX";
const PCMX_HEADER: usize = 24; // magic(4) + pad(4) + n_rows(8) + n_cols(8)
/// Per-column metadata pre-parsed from the embedded PCIV header.
struct ColInfo {
primary_start: usize, // absolute mmap offset to primary array
data_offset: usize, // absolute mmap offset to overflow array
primary_start: usize,
data_offset: usize,
n_overflow: usize,
step: usize,
index: Vec<(usize, usize)>,
}
pub struct PackedCompactIntMatrix {
@@ -171,61 +133,31 @@ impl PackedCompactIntMatrix {
for c in 0..n_cols {
let off_pos = PCMX_HEADER + c * 8;
let col_base = u64::from_le_bytes(mmap[off_pos..off_pos+8].try_into().unwrap()) as usize;
// Parse embedded PCIV header at col_base
let n_ov = u64::from_le_bytes(mmap[col_base+16..col_base+24].try_into().unwrap()) as usize;
let n_idx = u64::from_le_bytes(mmap[col_base+24..col_base+32].try_into().unwrap()) as usize;
let step = u64::from_le_bytes(mmap[col_base+32..col_base+40].try_into().unwrap()) as usize;
let n_pciv = u64::from_le_bytes(mmap[col_base+8..col_base+16].try_into().unwrap()) as usize;
let primary_start = col_base + HEADER_SIZE;
let data_offset = primary_start + n_pciv;
let index_offset = data_offset + n_ov * OVERFLOW_ENTRY_SIZE;
let mut index = Vec::with_capacity(n_idx);
for i in 0..n_idx {
let ioff = index_offset + i * INDEX_ENTRY_SIZE;
let slot = u64::from_le_bytes(mmap[ioff..ioff+8].try_into().unwrap()) as usize;
let pos = u64::from_le_bytes(mmap[ioff+8..ioff+16].try_into().unwrap()) as usize;
index.push((slot, pos));
columns.push(ColInfo { primary_start, data_offset, n_overflow: n_ov });
}
columns.push(ColInfo { primary_start, data_offset, n_overflow: n_ov, step, index });
}
Ok(Self { mmap, n_rows, n_cols, columns })
}
#[inline]
pub(crate) fn get(&self, col: usize, slot: usize) -> u32 {
let ci = &self.columns[col];
let v = self.mmap[ci.primary_start + slot];
if v < 255 { return v as u32; }
self.overflow_get(ci, slot)
pub(crate) fn col_view(&self, c: usize) -> IntSliceView<'_> {
let ci = &self.columns[c];
let primary = &self.mmap[ci.primary_start..ci.primary_start + self.n_rows];
let overflow_raw = &self.mmap[ci.data_offset..ci.data_offset + ci.n_overflow * OVERFLOW_ENTRY_SIZE];
IntSliceView::new(primary, overflow_raw, ci.n_overflow, self.n_rows)
}
fn overflow_get(&self, ci: &ColInfo, slot: usize) -> u32 {
let (pos_start, pos_end) = if ci.step == 0 {
(0, ci.n_overflow)
} else {
let i = ci.index.partition_point(|&(s, _)| s <= slot).saturating_sub(1);
let start = ci.index[i].1;
let end = if i + 1 < ci.index.len() { ci.index[i+1].1 } else { ci.n_overflow };
(start, end)
};
let mut lo = pos_start;
let mut hi = pos_end;
while lo < hi {
let mid = lo + (hi - lo) / 2;
let off = ci.data_offset + mid * OVERFLOW_ENTRY_SIZE;
let stored = u64::from_le_bytes(self.mmap[off..off+8].try_into().unwrap()) as usize;
match stored.cmp(&slot) {
Ordering::Equal => return u32::from_le_bytes(self.mmap[off+8..off+12].try_into().unwrap()),
Ordering::Less => lo = mid + 1,
Ordering::Greater => hi = mid,
}
}
panic!("slot {slot} marked overflow but not found")
pub(crate) fn col_persist(&self, c: usize, path: &Path) -> io::Result<PersistentCompactIntVecBuilder> {
let view = self.col_view(c);
let overflow: std::collections::HashMap<usize, u32> = view.overflow_entries().collect();
PersistentCompactIntVecBuilder::from_raw_primary(view.primary_bytes(), overflow, path)
}
#[inline]
pub(crate) fn get(&self, col: usize, slot: usize) -> u32 { self.col_view(col).get(slot) }
pub(crate) fn fill_row(&self, slot: usize, buf: &mut [u32]) {
for c in 0..self.n_cols { buf[c] = self.get(c, slot); }
}
@@ -236,152 +168,85 @@ impl PackedCompactIntMatrix {
pub(crate) fn sum(&self) -> Array1<u64> {
Array1::from_vec(
(0..self.n_cols).into_par_iter()
.map(|c| (0..self.n_rows).map(|s| self.get(c, s) as u64).sum())
.collect()
(0..self.n_cols).into_par_iter().map(|c| self.col_view(c).sum()).collect()
)
}
pub(crate) fn count_nonzero(&self) -> Array1<u64> {
Array1::from_vec(
(0..self.n_cols).into_par_iter()
.map(|c| (0..self.n_rows).filter(|&s| self.get(c, s) > 0).count() as u64)
.collect()
(0..self.n_cols).into_par_iter().map(|c| self.col_view(c).count_nonzero()).collect()
)
}
// ── Pair primitives ───────────────────────────────────────────────────────
fn pair_partial_bray(&self, i: usize, j: usize) -> u64 {
(0..self.n_rows).map(|s| self.get(i, s).min(self.get(j, s)) as u64).sum()
self.col_view(i).iter().zip(self.col_view(j).iter()).map(|(a, b)| a.min(b) as u64).sum()
}
fn pair_partial_euclidean(&self, i: usize, j: usize) -> f64 {
(0..self.n_rows).map(|s| {
let d = self.get(i, s) as f64 - self.get(j, s) as f64;
d * d
}).sum()
self.col_view(i).iter().zip(self.col_view(j).iter())
.map(|(a, b)| { let d = a as f64 - b as f64; d * d }).sum()
}
fn pair_partial_threshold_jaccard(&self, i: usize, j: usize, t: u32) -> (u64, u64) {
let (mut inter, mut union) = (0u64, 0u64);
for s in 0..self.n_rows {
let a = self.get(i, s) >= t;
let b = self.get(j, s) >= t;
if a && b { inter += 1; }
if a || b { union += 1; }
self.col_view(i).iter().zip(self.col_view(j).iter())
.fold((0u64, 0u64), |(inter, uni), (a, b)| {
let ap = a >= t; let bp = b >= t;
(inter + (ap & bp) as u64, uni + (ap | bp) as u64)
})
}
(inter, union)
}
fn pair_partial_relfreq_bray(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
if si == 0.0 || sj == 0.0 { return 0.0; }
(0..self.n_rows).map(|s| {
(self.get(i, s) as f64 / si).min(self.get(j, s) as f64 / sj)
}).sum()
self.col_view(i).iter().zip(self.col_view(j).iter())
.map(|(a, b)| (a as f64 / si).min(b as f64 / sj)).sum()
}
fn pair_partial_relfreq_euclidean(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
if si == 0.0 || sj == 0.0 { return 0.0; }
(0..self.n_rows).map(|s| {
let d = self.get(i, s) as f64 / si - self.get(j, s) as f64 / sj;
d * d
}).sum()
self.col_view(i).iter().zip(self.col_view(j).iter())
.map(|(a, b)| { let d = a as f64 / si - b as f64 / sj; d * d }).sum()
}
fn pair_partial_hellinger(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
if si == 0.0 || sj == 0.0 { return 0.0; }
(0..self.n_rows).map(|s| {
let d = (self.get(i, s) as f64 / si).sqrt() - (self.get(j, s) as f64 / sj).sqrt();
d * d
}).sum()
}
// ── Matrix methods ────────────────────────────────────────────────────────
fn pairwise<T>(&self, f: impl Fn(usize, usize) -> T + Sync) -> Array2<T>
where T: Clone + Default + Send {
let n = self.n_cols;
let results: Vec<(usize, usize, T)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| { let w = v.clone(); (i, j, v, w) }))
}
fn pairwise_u64(&self, f: impl Fn(usize, usize) -> u64 + Sync) -> Array2<u64> {
let n = self.n_cols;
let results: Vec<(usize, usize, u64)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)))
self.col_view(i).iter().zip(self.col_view(j).iter())
.map(|(a, b)| { let d = (a as f64 / si).sqrt() - (b as f64 / sj).sqrt(); d * d }).sum()
}
pub(crate) fn partial_bray_dist_matrix(&self) -> Array2<u64> {
self.pairwise_u64(|i, j| self.pair_partial_bray(i, j))
pairwise_matrix(self.n_cols, |i, j| self.pair_partial_bray(i, j))
}
pub(crate) fn partial_euclidean_dist_matrix(&self) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_euclidean(i, j))
pairwise_matrix(self.n_cols, |i, j| self.pair_partial_euclidean(i, j))
}
pub(crate) fn partial_threshold_jaccard_dist_matrix(&self, t: u32) -> (Array2<u64>, Array2<u64>) {
let n = self.n_cols;
let results: Vec<(usize, usize, u64, u64)> = upper_pairs(n)
.into_par_iter()
.map(|(i, j)| { let (inter, union) = self.pair_partial_threshold_jaccard(i, j, t); (i, j, inter, union) })
.collect();
let mut inter_m = Array2::zeros((n, n));
let mut union_m = Array2::zeros((n, n));
for (i, j, inter, union) in results {
inter_m[[i, j]] = inter; inter_m[[j, i]] = inter;
union_m[[i, j]] = union; union_m[[j, i]] = union;
pairwise2_matrix(self.n_cols, |i, j| self.pair_partial_threshold_jaccard(i, j, t))
}
(inter_m, union_m)
}
pub(crate) fn partial_relfreq_bray_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_relfreq_bray(i, j, col_sums[i] as f64, col_sums[j] as f64))
pairwise_matrix(self.n_cols, |i, j| self.pair_partial_relfreq_bray(i, j, col_sums[i] as f64, col_sums[j] as f64))
}
pub(crate) fn partial_relfreq_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_relfreq_euclidean(i, j, col_sums[i] as f64, col_sums[j] as f64))
pairwise_matrix(self.n_cols, |i, j| self.pair_partial_relfreq_euclidean(i, j, col_sums[i] as f64, col_sums[j] as f64))
}
pub(crate) fn partial_hellinger_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
self.pairwise(|i, j| self.pair_partial_hellinger(i, j, col_sums[i] as f64, col_sums[j] as f64))
pairwise_matrix(self.n_cols, |i, j| self.pair_partial_hellinger(i, j, col_sums[i] as f64, col_sums[j] as f64))
}
}
/// Build `counts/matrix.pcmx` from existing `col_*.pciv` files.
pub fn pack_compact_int_matrix(dir: &Path) -> io::Result<()> {
let packed_path = dir.join("matrix.pcmx");
if packed_path.exists() {
// Matrix complete; remove any leftover column files from a killed cleanup.
if let Ok(meta) = MatrixMeta::load(dir) {
for c in 0..meta.n_cols { let _ = fs::remove_file(col_path(dir, c)); }
let _ = fs::remove_file(dir.join("meta.json"));
}
return Ok(());
}
let meta = MatrixMeta::load(dir)?;
let n_cols = meta.n_cols;
// Compute offsets from file sizes — no column data loaded into RAM.
let col_sizes: Vec<u64> = (0..n_cols)
.map(|c| fs::metadata(col_path(dir, c)).map(|m| m.len()))
.collect::<io::Result<_>>()?;
let header_size = (PCMX_HEADER + n_cols * 8) as u64;
let mut col_offset = header_size;
let mut offsets = Vec::with_capacity(n_cols);
for &size in &col_sizes {
offsets.push(col_offset);
col_offset += size;
}
// Write to a temp file; rename atomically so a killed process never leaves
// a truncated matrix.pcmx that would be mistaken for a complete file.
for &size in &col_sizes { offsets.push(col_offset); col_offset += size; }
let tmp_path = dir.join("matrix.pcmx.tmp");
let mut out = BufWriter::new(File::create(&tmp_path)?);
out.write_all(&PCMX_MAGIC)?;
@@ -389,13 +254,10 @@ pub fn pack_compact_int_matrix(dir: &Path) -> io::Result<()> {
out.write_all(&(meta.n as u64).to_le_bytes())?;
out.write_all(&(n_cols as u64).to_le_bytes())?;
for &off in &offsets { out.write_all(&off.to_le_bytes())?; }
for c in 0..n_cols {
io::copy(&mut File::open(col_path(dir, c))?, &mut out)?;
}
for c in 0..n_cols { io::copy(&mut File::open(col_path(dir, c))?, &mut out)?; }
out.flush()?;
drop(out);
fs::rename(&tmp_path, &packed_path)?;
for c in 0..n_cols { fs::remove_file(col_path(dir, c))?; }
fs::remove_file(dir.join("meta.json"))?;
Ok(())
@@ -409,18 +271,14 @@ pub enum PersistentCompactIntMatrix {
}
impl PersistentCompactIntMatrix {
/// Open from `layer_dir`, auto-detecting Packed or Columnar.
pub fn open(layer_dir: &Path) -> io::Result<Self> {
let counts_dir = layer_dir.join("counts");
if counts_dir.join("matrix.pcmx").exists() {
return Ok(Self::Packed(PackedCompactIntMatrix::open(&counts_dir.join("matrix.pcmx"))?));
}
if MatrixMeta::load(&counts_dir).is_ok() {
return Ok(Self::Columnar(ColumnarCompactIntMatrix::open(&counts_dir)?));
}
Err(io::Error::new(
io::ErrorKind::NotFound,
format!("no count matrix found in {} — run 'obikmer upgrade'", layer_dir.display()),
@@ -430,7 +288,6 @@ impl PersistentCompactIntMatrix {
pub fn n(&self) -> usize {
match self { Self::Columnar(m) => m.n(), Self::Packed(m) => m.n_rows }
}
pub fn n_cols(&self) -> usize {
match self { Self::Columnar(m) => m.n_cols(), Self::Packed(m) => m.n_cols }
}
@@ -442,22 +299,32 @@ impl PersistentCompactIntMatrix {
}
}
pub fn col_view(&self, c: usize) -> IntSliceView<'_> {
match self {
Self::Columnar(m) => m.col(c).view(),
Self::Packed(m) => m.col_view(c),
}
}
pub fn col_persist(&self, c: usize, path: &Path) -> io::Result<PersistentCompactIntVecBuilder> {
match self {
Self::Columnar(m) => PersistentCompactIntVecBuilder::build_from(m.col(c), path),
Self::Packed(m) => m.col_persist(c, path),
}
}
pub fn row(&self, slot: usize) -> Box<[u32]> {
match self { Self::Columnar(m) => m.row(slot), Self::Packed(m) => m.row(slot) }
}
pub fn fill_row(&self, slot: usize, buf: &mut [u32]) {
match self { Self::Columnar(m) => m.fill_row(slot, buf), Self::Packed(m) => m.fill_row(slot, buf) }
}
pub fn sum(&self) -> Array1<u64> {
match self { Self::Columnar(m) => m.sum(), Self::Packed(m) => m.sum() }
}
pub fn count_nonzero(&self) -> Array1<u64> {
match self { Self::Columnar(m) => m.count_nonzero(), Self::Packed(m) => m.count_nonzero() }
}
pub fn partial_bray_dist_matrix(&self) -> Array2<u64> {
match self { Self::Columnar(m) => m.partial_bray_dist_matrix(), Self::Packed(m) => m.partial_bray_dist_matrix() }
}
@@ -476,7 +343,6 @@ impl PersistentCompactIntMatrix {
pub fn partial_hellinger_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
match self { Self::Columnar(m) => m.partial_hellinger_euclidean_dist_matrix(col_sums), Self::Packed(m) => m.partial_hellinger_euclidean_dist_matrix(col_sums) }
}
pub fn append_column(dir: &Path, value_of: impl Fn(usize) -> u32) -> io::Result<()> {
ColumnarCompactIntMatrix::append_column(dir, value_of)
}
@@ -513,30 +379,88 @@ impl PersistentCompactIntMatrixBuilder {
fs::create_dir_all(dir)?;
Ok(Self { dir: dir.to_path_buf(), n, n_cols: 0 })
}
pub fn n(&self) -> usize { self.n }
pub fn n_cols(&self) -> usize { self.n_cols }
pub fn add_col(&mut self) -> io::Result<PersistentCompactIntVecBuilder> {
let path = col_path(&self.dir, self.n_cols);
self.n_cols += 1;
PersistentCompactIntVecBuilder::new(self.n, &path)
}
pub fn add_col_from(&mut self, src: &TempCompactIntVec) -> io::Result<()> {
src.make_persistent(&col_path(&self.dir, self.n_cols))?;
self.n_cols += 1;
Ok(())
}
pub fn add_col_from_bit(&mut self, src: &TempBitVec) -> io::Result<()> {
let path = col_path(&self.dir, self.n_cols);
self.n_cols += 1;
let mut b = PersistentCompactIntVecBuilder::new(self.n, &path)?;
b.inc_present(src.view());
b.close()
}
pub fn close(self) -> io::Result<()> {
MatrixMeta { n: self.n, n_cols: self.n_cols }.save(&self.dir)
}
}
// ── Helpers ───────────────────────────────────────────────────────────────────
// ── MatrixGroupOps ────────────────────────────────────────────────────────────
fn upper_pairs(n: usize) -> Vec<(usize, usize)> {
(0..n).flat_map(|i| (i + 1..n).map(move |j| (i, j))).collect()
}
impl MatrixGroupOps for PersistentCompactIntMatrix {
fn partial_group_presence_count(&self, g: &ColGroup, threshold: u32) -> io::Result<TempCompactIntVec> {
let n = self.n();
if g.indices.len() < 255 {
let mut builder = TempCompactIntVecBuilder::new(n)?;
for &c in &g.indices {
builder.inc_predicate_fast(self.col_view(c), |v| v >= threshold);
}
builder.freeze()
} else {
let mut result = TempCompactIntVecBuilder::new(n)?;
for chunk in g.indices.chunks(254) {
let mut chunk_b = TempCompactIntVecBuilder::new(n)?;
for &c in chunk {
chunk_b.inc_predicate_fast(self.col_view(c), |v| v >= threshold);
}
let frozen = chunk_b.freeze()?;
result.add(frozen.view());
}
result.freeze()
}
}
fn fill_symmetric<T>(n: usize, vals: impl Iterator<Item = (usize, usize, T, T)>) -> Array2<T>
where T: Clone + Default {
let mut m = Array2::from_elem((n, n), T::default());
for (i, j, vij, vji) in vals { m[[i, j]] = vij; m[[j, i]] = vji; }
m
fn partial_group_sum(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {
let n = self.n();
let mut result = TempCompactIntVecBuilder::new(n)?;
for &c in &g.indices { result.add(self.col_view(c)); }
result.freeze()
}
fn partial_group_any(&self, g: &ColGroup, threshold: u32) -> io::Result<TempBitVec> {
let n = self.n();
let mut result = TempBitVecBuilder::new(n)?;
for &c in &g.indices {
result.or_where(self.col_view(c), |v| v >= threshold);
}
result.freeze()
}
fn partial_group_min(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {
let n = self.n();
let mut result = TempCompactIntVecBuilder::new(n)?;
if let Some((&first, rest)) = g.indices.split_first() {
result.add(self.col_view(first));
for &c in rest { result.min(self.col_view(c)); }
}
result.freeze()
}
fn partial_group_max(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {
let n = self.n();
let mut result = TempCompactIntVecBuilder::new(n)?;
for &c in &g.indices { result.max(self.col_view(c)); }
result.freeze()
}
}
src/obicompactvec/src/layer_meta.rs
+1 -6
View File
@@ -23,11 +23,6 @@ impl LayerMeta {
}
fn parse(s: &str) -> Option<Self> {
let key = "\"n\":";
let pos = s.find(key)? + key.len();
let rest = s[pos..].trim_start();
let end = rest.find(|c: char| !c.is_ascii_digit()).unwrap_or(rest.len());
let n = rest[..end].parse().ok()?;
Some(Self { n })
Some(Self { n: crate::meta::field(s, "n")? })
}
}
src/obicompactvec/src/lib.rs
+9 -1
View File
@@ -1,20 +1,28 @@
mod bitvec;
mod bitmatrix;
mod builder;
mod colgroup;
mod format;
mod intmatrix;
mod layer_meta;
mod meta;
mod reader;
mod tempbitvec;
mod tempintvec;
mod views;
pub mod traits;
pub use bitvec::{BitIter, PersistentBitVec, PersistentBitVecBuilder};
pub use bitmatrix::{PersistentBitMatrix, PersistentBitMatrixBuilder, pack_bit_matrix};
pub use builder::PersistentCompactIntVecBuilder;
pub use colgroup::{ColGroup, FilterMask, MatrixGroupOps, eval_filter_mask};
pub use intmatrix::{PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder, pack_compact_int_matrix};
pub use layer_meta::LayerMeta;
pub use reader::PersistentCompactIntVec;
pub use reader::{PersistentCompactIntVec, Iter as CompactIntVecIter};
pub use tempbitvec::{TempBitVec, TempBitVecBuilder};
pub use tempintvec::{TempCompactIntVec, TempCompactIntVecBuilder};
pub use traits::{BitPartials, ColumnWeights, CountPartials};
pub use views::{BitSliceView, BitSliceIter, IntSliceView, IntSliceViewIter};
#[cfg(test)]
#[path = "tests/mod.rs"]
src/obicompactvec/src/meta.rs
+1 -1
View File
@@ -23,7 +23,7 @@ fn parse(s: &str) -> Option<MatrixMeta> {
Some(MatrixMeta { n: field(s, "n")?, n_cols: field(s, "n_cols")? })
}
fn field(s: &str, name: &str) -> Option<usize> {
pub(crate) fn field(s: &str, name: &str) -> Option<usize> {
let key = format!("\"{}\":", name);
let pos = s.find(&key)? + key.len();
let rest = s[pos..].trim_start();
src/obicompactvec/src/reader.rs
+61 -202
View File
@@ -4,7 +4,8 @@ use std::path::{Path, PathBuf};
use memmap2::Mmap;
use crate::format::{HEADER_SIZE, INDEX_ENTRY_SIZE, MAGIC, OVERFLOW_ENTRY_SIZE};
use crate::format::{byte_count_nonzero, byte_sum, HEADER_SIZE, MAGIC, OVERFLOW_ENTRY_SIZE, parse_index_entry};
use crate::views::IntSliceView;
pub struct PersistentCompactIntVec {
mmap: Mmap,
@@ -18,15 +19,11 @@ pub struct PersistentCompactIntVec {
}
impl PersistentCompactIntVec {
/// Opens a persistent compact int vector from the given path.
pub fn open(path: &Path) -> io::Result<Self> {
let mmap = unsafe { Mmap::map(&File::open(path)?)? };
if mmap.len() < HEADER_SIZE {
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"PCIV file too short",
));
return Err(io::Error::new(io::ErrorKind::InvalidData, "PCIV file too short"));
}
if &mmap[0..4] != &MAGIC {
return Err(io::Error::new(io::ErrorKind::InvalidData, "bad PCIV magic"));
@@ -43,40 +40,16 @@ impl PersistentCompactIntVec {
let mut index = Vec::with_capacity(n_index);
for i in 0..n_index {
let off = index_offset + i * INDEX_ENTRY_SIZE;
let slot = u64::from_le_bytes(mmap[off..off + 8].try_into().unwrap()) as usize;
let pos = u64::from_le_bytes(mmap[off + 8..off + 16].try_into().unwrap()) as usize;
index.push((slot, pos));
index.push(parse_index_entry(&mmap, index_offset, i));
}
Ok(Self {
mmap,
n,
n_overflow,
step,
index,
primary_offset,
data_offset,
path: path.to_path_buf(),
})
Ok(Self { mmap, n, n_overflow, step, index, primary_offset, data_offset, path: path.to_path_buf() })
}
/// Returns the path of the compact int vector file.
pub fn path(&self) -> &Path {
&self.path
}
pub fn path(&self) -> &Path { &self.path }
pub fn len(&self) -> usize { self.n }
pub fn is_empty(&self) -> bool { self.n == 0 }
/// Returns the length of the compact int vector.
pub fn len(&self) -> usize {
self.n
}
/// Returns whether the compact int vector is empty.
pub fn is_empty(&self) -> bool {
self.n == 0
}
/// Returns the value at the given slot.
pub fn get(&self, slot: usize) -> u32 {
match self.mmap[self.primary_offset + slot] {
255 => self.overflow_get(slot),
@@ -84,27 +57,15 @@ impl PersistentCompactIntVec {
}
}
/// Returns the value at the given slot from the overflow region.
fn overflow_get(&self, slot: usize) -> u32 {
let pos_start;
let pos_end;
if self.step == 0 {
pos_start = 0;
pos_end = self.n_overflow;
let (pos_start, pos_end) = if self.step == 0 {
(0, self.n_overflow)
} else {
let i = self
.index
.partition_point(|&(s, _)| s <= slot)
.saturating_sub(1);
pos_start = self.index[i].1;
pos_end = if i + 1 < self.index.len() {
self.index[i + 1].1
} else {
self.n_overflow
let i = self.index.partition_point(|&(s, _)| s <= slot).saturating_sub(1);
let start = self.index[i].1;
let end = if i + 1 < self.index.len() { self.index[i + 1].1 } else { self.n_overflow };
(start, end)
};
}
let mut lo = pos_start;
let mut hi = pos_end;
while lo < hi {
@@ -119,144 +80,91 @@ impl PersistentCompactIntVec {
}
#[inline]
/// Returns the slot at the given index in the overflow region.
fn data_slot(&self, i: usize) -> usize {
let off = self.data_offset + i * OVERFLOW_ENTRY_SIZE;
u64::from_le_bytes(self.mmap[off..off + 8].try_into().unwrap()) as usize
}
#[inline]
/// Returns the value at the given index in the overflow region.
fn data_value(&self, i: usize) -> u32 {
let off = self.data_offset + i * OVERFLOW_ENTRY_SIZE + 8;
u32::from_le_bytes(self.mmap[off..off + 4].try_into().unwrap())
}
#[inline]
pub fn sum(&self) -> u64 {
self.iter().map(|v| v as u64).sum()
let primary = &self.mmap[self.primary_offset..self.primary_offset + self.n];
byte_sum(primary, (0..self.n_overflow).map(|i| self.data_value(i)))
}
#[inline]
pub fn count_nonzero(&self) -> u64 {
self.iter().filter(|&v| v > 0).count() as u64
let primary = &self.mmap[self.primary_offset..self.primary_offset + self.n];
byte_count_nonzero(primary)
}
#[inline]
/// Returns the Bray-Curtis distance between two compact int vectors.
/// Lightweight zero-copy view — primary and overflow point into the mmap.
pub fn view(&self) -> IntSliceView<'_> {
let primary = &self.mmap[self.primary_offset..self.primary_offset + self.n];
let overflow_raw = &self.mmap[self.data_offset..self.data_offset + self.n_overflow * OVERFLOW_ENTRY_SIZE];
IntSliceView::new(primary, overflow_raw, self.n_overflow, self.n)
}
pub fn iter(&self) -> Iter<'_> {
Iter { pciv: self, slot: 0, overflow_pos: 0 }
}
// ── Distance methods ──────────────────────────────────────────────────────
pub fn bray_dist(&self, other: &PersistentCompactIntVec) -> f64 {
let sum_min = self.partial_bray_dist(other);
let denom = self.sum() + other.sum();
if denom == 0 {
return 0.0;
}
1.0 - 2.0 * sum_min as f64 / denom as f64
if denom == 0 { 0.0 } else { 1.0 - 2.0 * sum_min as f64 / denom as f64 }
}
/// Returns `Σ_slot min(self[slot], other[slot])` — the additive numerator of Bray-Curtis.
/// The denominator `sum_a + sum_b` is obtained from `self.sum() + other.sum()`.
pub fn partial_bray_dist(&self, other: &PersistentCompactIntVec) -> u64 {
assert_eq!(self.n, other.len(), "length mismatch");
self.iter()
.zip(other.iter())
.map(|(a, b)| a.min(b) as u64)
.sum()
self.iter().zip(other.iter()).map(|(a, b)| a.min(b) as u64).sum()
}
/// Returns the relative frequency Bray-Curtis distance between two compact int vectors.
///
/// This is a variant of [`bray_dist`] that uses relative frequencies instead of raw counts.
pub fn relfreq_bray_dist(&self, other: &PersistentCompactIntVec) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
let sum_a = self.sum() as f64;
let sum_b = other.sum() as f64;
if sum_a == 0.0 && sum_b == 0.0 {
return 0.0;
}
let sum_min = self.partial_relfreq_bray_dist(other, sum_a, sum_b);
1.0 - sum_min
let sa = self.sum() as f64;
let sb = other.sum() as f64;
if sa == 0.0 && sb == 0.0 { return 0.0; }
1.0 - self.partial_relfreq_bray_dist(other, sa, sb)
}
/// Returns the partial relative frequency Bray-Curtis distance between two compact int vectors.
///
/// This is used internally by [`relfreq_bray_dist`] and to easily compute the relative frequency
/// Bray-Curtis distance over a set of vector pairs.
///
/// Arguments:
/// - `other`: the other compact int vector to compare with
/// - `sum_a`: the sum of the first vector's counts
/// - `sum_b`: the sum of the second vector's counts
///
/// Returns the sum of the minimum relative frequencies at each index.
pub fn partial_relfreq_bray_dist(
&self,
other: &PersistentCompactIntVec,
sum_a: f64,
sum_b: f64,
) -> f64 {
pub fn partial_relfreq_bray_dist(&self, other: &PersistentCompactIntVec, sum_a: f64, sum_b: f64) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
let sum_min: f64 = self
.iter()
.zip(other.iter())
self.iter().zip(other.iter())
.map(|(a, b)| {
let pa = if sum_a > 0.0 { a as f64 / sum_a } else { 0.0 };
let pb = if sum_b > 0.0 { b as f64 / sum_b } else { 0.0 };
pa.min(pb)
})
.sum();
sum_min
.sum()
}
/// Returns the euclidean distance between two compact int vectors.
pub fn euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
self.partial_euclidean_dist(other).sqrt()
}
/// Returns the partial euclidean distance between two compact int vectors.
///
/// This is used internally by [`euclidean_dist`] and to easily compute the euclidean distance
/// over a set of vector pairs.
///
/// The result is the sum of the squared differences between corresponding elements of the two
/// vectors.
pub fn partial_euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
self.iter()
.zip(other.iter())
.map(|(a, b)| {
let d = a as f64 - b as f64;
d * d
})
self.iter().zip(other.iter())
.map(|(a, b)| { let d = a as f64 - b as f64; d * d })
.sum()
}
/// Returns the relative frequency euclidean distance between two compact int vectors.
///
/// This is a variant of [`euclidean_dist`] that uses relative frequencies instead of raw counts.
pub fn relfreq_euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
let sum_a = self.sum() as f64;
let sum_b = other.sum() as f64;
if sum_a == 0.0 && sum_b == 0.0 {
return 0.0;
}
self.partial_relfreq_euclidean_dist(other, sum_a, sum_b)
.sqrt()
let sa = self.sum() as f64;
let sb = other.sum() as f64;
if sa == 0.0 && sb == 0.0 { return 0.0; }
self.partial_relfreq_euclidean_dist(other, sa, sb).sqrt()
}
/// Returns the partial relative frequency euclidean distance between two compact int vectors.
///
/// This is used internally by [`relfreq_euclidean_dist`] and to easily compute the relative frequency
/// euclidean distance over a set of vector pairs.
pub fn partial_relfreq_euclidean_dist(
&self,
other: &PersistentCompactIntVec,
sum_a: f64,
sum_b: f64,
) -> f64 {
pub fn partial_relfreq_euclidean_dist(&self, other: &PersistentCompactIntVec, sum_a: f64, sum_b: f64) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
self.iter()
.zip(other.iter())
self.iter().zip(other.iter())
.map(|(a, b)| {
let pa = if sum_a > 0.0 { a as f64 / sum_a } else { 0.0 };
let pb = if sum_b > 0.0 { b as f64 / sum_b } else { 0.0 };
@@ -266,46 +174,19 @@ impl PersistentCompactIntVec {
.sum()
}
/// Returns the Euclidean distance between two compact int vectors using the Hellinger transform.
///
/// The Hellinger transform is applied to the raw counts of each vector, and the result is
/// the Euclidean distance between the transformed vectors. The Hellinger transform is defined
/// as the square root of the relative frequencies.
pub fn hellinger_euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
let sum_a = self.sum() as f64;
let sum_b = other.sum() as f64;
if sum_a == 0.0 && sum_b == 0.0 {
return 0.0;
}
self.partial_hellinger_euclidean_dist(other, sum_a, sum_b)
.sqrt()
let sa = self.sum() as f64;
let sb = other.sum() as f64;
if sa == 0.0 && sb == 0.0 { return 0.0; }
self.partial_hellinger_euclidean_dist(other, sa, sb).sqrt()
}
/// Returns the partial Hellinger Euclidean distance between two compact int vectors.
///
/// This is used internally by [`hellinger_euclidean_dist`] and to easily compute the Hellinger
/// Euclidean distance over a set of vector pairs.
pub fn partial_hellinger_euclidean_dist(
&self,
other: &PersistentCompactIntVec,
sum_a: f64,
sum_b: f64,
) -> f64 {
pub fn partial_hellinger_euclidean_dist(&self, other: &PersistentCompactIntVec, sum_a: f64, sum_b: f64) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
self.iter()
.zip(other.iter())
self.iter().zip(other.iter())
.map(|(a, b)| {
let pa = if sum_a > 0.0 {
(a as f64 / sum_a).sqrt()
} else {
0.0
};
let pb = if sum_b > 0.0 {
(b as f64 / sum_b).sqrt()
} else {
0.0
};
let pa = if sum_a > 0.0 { (a as f64 / sum_a).sqrt() } else { 0.0 };
let pb = if sum_b > 0.0 { (b as f64 / sum_b).sqrt() } else { 0.0 };
let d = pa - pb;
d * d
})
@@ -317,22 +198,13 @@ impl PersistentCompactIntVec {
}
pub fn threshold_jaccard_dist(&self, other: &PersistentCompactIntVec, threshold: u32) -> f64 {
assert_eq!(self.n, other.len(), "length mismatch");
let (intersection, union) = self.partial_threshold_jaccard_dist(other, threshold);
if union == 0 {
return 0.0;
}
1.0 - intersection as f64 / union as f64
if union == 0 { 0.0 } else { 1.0 - intersection as f64 / union as f64 }
}
pub fn partial_threshold_jaccard_dist(
&self,
other: &PersistentCompactIntVec,
threshold: u32,
) -> (u64, u64) {
pub fn partial_threshold_jaccard_dist(&self, other: &PersistentCompactIntVec, threshold: u32) -> (u64, u64) {
assert_eq!(self.n, other.len(), "length mismatch");
self.iter()
.zip(other.iter())
self.iter().zip(other.iter())
.fold((0u64, 0u64), |(inter, uni), (a, b)| {
let ap = a >= threshold;
let bp = b >= threshold;
@@ -343,23 +215,12 @@ impl PersistentCompactIntVec {
pub fn jaccard_dist(&self, other: &PersistentCompactIntVec) -> f64 {
self.threshold_jaccard_dist(other, 1)
}
pub fn iter(&self) -> Iter<'_> {
Iter {
pciv: self,
slot: 0,
overflow_pos: 0,
}
}
}
impl<'a> IntoIterator for &'a PersistentCompactIntVec {
type Item = u32;
type IntoIter = Iter<'a>;
fn into_iter(self) -> Iter<'a> {
self.iter()
}
fn into_iter(self) -> Iter<'a> { self.iter() }
}
pub struct Iter<'a> {
@@ -374,9 +235,7 @@ impl Iterator for Iter<'_> {
type Item = u32;
fn next(&mut self) -> Option<u32> {
if self.slot >= self.pciv.n {
return None;
}
if self.slot >= self.pciv.n { return None; }
let v = self.pciv.mmap[self.pciv.primary_offset + self.slot];
self.slot += 1;
if v < 255 {
src/obicompactvec/src/tempbitvec.rs
+111
View File
@@ -0,0 +1,111 @@
use std::io;
use std::path::Path;
use tempfile::TempDir;
use crate::bitvec::{PersistentBitVec, PersistentBitVecBuilder};
use crate::views::{BitSliceIter, BitSliceView, IntSliceView};
// ── TempBitVec — frozen read-only, auto-deleted on drop ──────────────────────
pub struct TempBitVec {
vec: PersistentBitVec,
// Dropped after `vec` (field order), so the mmap is released before the
// temp directory is deleted.
_temp: TempDir,
}
impl TempBitVec {
pub fn make_persistent(&self, path: &Path) -> io::Result<PersistentBitVec> {
std::fs::copy(self.vec.path(), path)?;
PersistentBitVec::open(path)
}
pub fn len(&self) -> usize {
self.vec.len()
}
pub fn is_empty(&self) -> bool {
self.vec.is_empty()
}
pub fn get(&self, slot: usize) -> bool {
self.vec.get(slot)
}
pub fn count_ones(&self) -> u64 {
self.vec.count_ones()
}
pub fn view(&self) -> BitSliceView<'_> {
self.vec.view()
}
pub fn iter(&self) -> BitSliceIter<'_> {
self.view().iter()
}
}
// ── TempBitVecBuilder — mutable, becomes TempBitVec on freeze ────────────────
pub struct TempBitVecBuilder {
builder: PersistentBitVecBuilder,
temp: TempDir,
}
impl TempBitVecBuilder {
pub fn new(n: usize) -> io::Result<Self> {
let temp = TempDir::new()?;
let path = temp.path().join("data.pbiv");
let builder = PersistentBitVecBuilder::new(n, &path)?;
Ok(Self { builder, temp })
}
pub fn new_ones(n: usize) -> io::Result<Self> {
let temp = TempDir::new()?;
let path = temp.path().join("data.pbiv");
let builder = PersistentBitVecBuilder::new_ones(n, &path)?;
Ok(Self { builder, temp })
}
pub fn freeze(self) -> io::Result<TempBitVec> {
let Self { builder, temp } = self;
let vec = builder.finish()?;
Ok(TempBitVec { vec, _temp: temp })
}
pub fn set(&mut self, slot: usize, value: bool) {
self.builder.set(slot, value);
}
pub fn view(&self) -> BitSliceView<'_> {
self.builder.view()
}
pub fn or(&mut self, other: BitSliceView<'_>) {
self.builder.or(other);
}
pub fn and(&mut self, other: BitSliceView<'_>) {
self.builder.and(other);
}
pub fn xor(&mut self, other: BitSliceView<'_>) {
self.builder.xor(other);
}
pub fn not(&mut self) {
self.builder.not();
}
pub fn copy_from(&mut self, src: BitSliceView<'_>) {
self.builder.copy_from(src);
}
pub fn or_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
self.builder.or_where(col, pred);
}
pub fn and_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
self.builder.and_where(col, pred);
}
pub fn xor_where(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
self.builder.xor_where(col, pred);
}
}
src/obicompactvec/src/tempintvec.rs
+89
View File
@@ -0,0 +1,89 @@
use std::io;
use std::path::Path;
use tempfile::TempDir;
use crate::builder::PersistentCompactIntVecBuilder;
use crate::reader::PersistentCompactIntVec;
use crate::views::{BitSliceView, IntSliceView};
// ── TempCompactIntVec — frozen read-only, auto-deleted on drop ────────────────
pub struct TempCompactIntVec {
vec: PersistentCompactIntVec,
// Dropped after `vec` (field order), so the mmap is released before the
// temp directory is deleted.
_temp: TempDir,
}
impl TempCompactIntVec {
pub fn make_persistent(&self, path: &Path) -> io::Result<PersistentCompactIntVec> {
std::fs::copy(self.vec.path(), path)?;
PersistentCompactIntVec::open(path)
}
pub fn len(&self) -> usize { self.vec.len() }
pub fn is_empty(&self) -> bool { self.vec.is_empty() }
pub fn get(&self, slot: usize) -> u32 { self.vec.get(slot) }
pub fn sum(&self) -> u64 { self.vec.sum() }
pub fn view(&self) -> IntSliceView<'_> { self.vec.view() }
pub fn iter(&self) -> crate::reader::Iter<'_> { self.vec.iter() }
}
// ── TempCompactIntVecBuilder — mutable, becomes TempCompactIntVec on freeze ──
pub struct TempCompactIntVecBuilder {
builder: PersistentCompactIntVecBuilder,
temp: TempDir,
}
impl TempCompactIntVecBuilder {
pub fn new(n: usize) -> io::Result<Self> {
let temp = TempDir::new()?;
let path = temp.path().join("data.pciv");
let builder = PersistentCompactIntVecBuilder::new(n, &path)?;
Ok(Self { builder, temp })
}
pub fn freeze(self) -> io::Result<TempCompactIntVec> {
let Self { builder, temp } = self;
let vec = builder.finish()?;
Ok(TempCompactIntVec { vec, _temp: temp })
}
pub fn n(&self) -> usize { self.builder.len() }
pub fn set(&mut self, slot: usize, value: u32) { self.builder.set(slot, value); }
pub fn get(&self, slot: usize) -> u32 { self.builder.get(slot) }
pub fn primary_bytes(&self) -> &[u8] { self.builder.primary_bytes() }
pub fn primary_bytes_mut(&mut self) -> &mut [u8] { self.builder.primary_bytes_mut() }
pub fn inc_present(&mut self, col: BitSliceView<'_>) {
self.builder.inc_present(col);
}
pub fn inc_present_fast(&mut self, col: BitSliceView<'_>) {
self.builder.inc_present_fast(col);
}
pub fn inc_predicate(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
self.builder.inc_predicate(col, pred);
}
pub fn inc_predicate_fast(&mut self, col: IntSliceView<'_>, pred: impl Fn(u32) -> bool) {
self.builder.inc_predicate_fast(col, pred);
}
pub fn add(&mut self, other: IntSliceView<'_>) {
self.builder.add(other);
}
pub fn mask_with(&mut self, mask: BitSliceView<'_>) {
self.builder.mask_with(mask);
}
pub fn min(&mut self, other: IntSliceView<'_>) { self.builder.min(other); }
pub fn max(&mut self, other: IntSliceView<'_>) { self.builder.max(other); }
pub fn diff(&mut self, other: IntSliceView<'_>) { self.builder.diff(other); }
}
src/obicompactvec/src/tests/bitmatrix.rs
+55 -1
View File
@@ -1,6 +1,6 @@
use tempfile::tempdir;
use crate::{PersistentBitMatrix, PersistentBitMatrixBuilder};
use crate::{pack_bit_matrix, PersistentBitMatrix, PersistentBitMatrixBuilder};
use crate::traits::BitPartials;
fn make_matrix(cols: &[&[bool]]) -> (tempfile::TempDir, PersistentBitMatrix) {
@@ -203,3 +203,57 @@ fn partial_hamming_matches_hamming() {
let full = m.hamming_dist_matrix();
assert_eq!(partial, full);
}
// ── col_view on Packed ────────────────────────────────────────────────────────
#[test]
fn col_view_packed_values() {
let (dir, _) = make_matrix(&[
&[true, false, true, true],
&[false, true, false, true],
]);
pack_bit_matrix(&dir.path().join("presence")).unwrap();
let m = PersistentBitMatrix::open(dir.path()).unwrap();
// col 0: [T, F, T, T]
let v0 = m.col_view(0);
assert_eq!(v0.len(), 4);
assert_eq!(v0.get(0), true);
assert_eq!(v0.get(1), false);
assert_eq!(v0.get(2), true);
assert_eq!(v0.get(3), true);
assert_eq!(v0.count_ones(), 3);
// col 1: [F, T, F, T]
let v1 = m.col_view(1);
assert_eq!(v1.get(0), false);
assert_eq!(v1.get(1), true);
assert_eq!(v1.get(2), false);
assert_eq!(v1.get(3), true);
assert_eq!(v1.count_ones(), 2);
}
#[test]
fn col_view_packed_matches_columnar() {
let data: &[&[bool]] = &[
&[true, false, true, false, true, true, false, true],
&[false, false, true, true, false, true, true, false],
&[true, true, true, false, false, false, true, true],
];
let (dir_col, m_col) = make_matrix(data);
let (dir_pack, _) = make_matrix(data);
pack_bit_matrix(&dir_pack.path().join("presence")).unwrap();
let m_pack = PersistentBitMatrix::open(dir_pack.path()).unwrap();
for c in 0..data.len() {
let col_ref = m_col.col(c);
let col_view = m_pack.col_view(c);
assert_eq!(col_view.len(), col_ref.len(), "col={c} len");
for s in 0..col_ref.len() {
assert_eq!(col_view.get(s), col_ref.get(s), "col={c} slot={s}");
}
assert_eq!(col_view.count_ones(), col_ref.count_ones(), "col={c} count_ones");
assert_eq!(col_view.words(), col_ref.words(), "col={c} words");
}
drop(dir_col);
}
src/obicompactvec/src/tests/bitvec.rs
+3 -3
View File
@@ -77,7 +77,7 @@ fn op_and() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pbiv");
let mut b = PersistentBitVecBuilder::build_from(&ra, &path).unwrap();
b.and(&rb);
b.and(rb.view());
b.close().unwrap();
let r = PersistentBitVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![true, false, false, false]);
@@ -90,7 +90,7 @@ fn op_or() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pbiv");
let mut b = PersistentBitVecBuilder::build_from(&ra, &path).unwrap();
b.or(&rb);
b.or(rb.view());
b.close().unwrap();
let r = PersistentBitVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![true, true, true, false]);
@@ -103,7 +103,7 @@ fn op_xor() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pbiv");
let mut b = PersistentBitVecBuilder::build_from(&ra, &path).unwrap();
b.xor(&rb);
b.xor(rb.view());
b.close().unwrap();
let r = PersistentBitVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![false, true, true, false]);
src/obicompactvec/src/tests/colgroup.rs
+223
View File
@@ -0,0 +1,223 @@
use tempfile::tempdir;
use crate::{
ColGroup, MatrixGroupOps,
PersistentBitMatrix, PersistentBitMatrixBuilder,
PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder,
};
use crate::{PersistentBitVecBuilder, PersistentCompactIntVec, PersistentCompactIntVecBuilder};
// ── helpers ───────────────────────────────────────────────────────────────────
fn make_int_matrix(cols: &[&[u32]]) -> (tempfile::TempDir, PersistentCompactIntMatrix) {
let n = cols.first().map_or(0, |c| c.len());
let dir = tempdir().unwrap();
let mut b = PersistentCompactIntMatrixBuilder::new(n, &dir.path().join("counts")).unwrap();
for &col in cols {
let mut cb = b.add_col().unwrap();
for (slot, &v) in col.iter().enumerate() { cb.set(slot, v); }
cb.close().unwrap();
}
b.close().unwrap();
let m = PersistentCompactIntMatrix::open(dir.path()).unwrap();
(dir, m)
}
fn make_bit_matrix(cols: &[&[bool]]) -> (tempfile::TempDir, PersistentBitMatrix) {
let n = cols.first().map_or(0, |c| c.len());
let dir = tempdir().unwrap();
let presence = dir.path().join("presence");
let mut b = PersistentBitMatrixBuilder::new(n, &presence).unwrap();
for &col in cols {
let mut cb = b.add_col().unwrap();
for (slot, &v) in col.iter().enumerate() { cb.set(slot, v); }
cb.close().unwrap();
}
b.close().unwrap();
let m = PersistentBitMatrix::open(dir.path()).unwrap();
(dir, m)
}
// ── IntMatrix: partial_group_sum ──────────────────────────────────────────────
#[test]
fn int_partial_group_sum_basic() {
// col0=[1,2,3], col1=[10,20,30], col2=[100,0,5]
// group {0,2}: sum = [101, 2, 8]
let (_d, m) = make_int_matrix(&[&[1, 2, 3], &[10, 20, 30], &[100, 0, 5]]);
let g = ColGroup::new("g", vec![0, 2]);
let result = m.partial_group_sum(&g).unwrap();
assert_eq!(result.get(0), 101);
assert_eq!(result.get(1), 2);
assert_eq!(result.get(2), 8);
}
#[test]
fn int_partial_group_sum_with_overflow() {
// col0=[300,0], col1=[200,400]: group {0,1}: sum=[500, 400]
let (_d, m) = make_int_matrix(&[&[300, 0], &[200, 400]]);
let g = ColGroup::new("g", vec![0, 1]);
let result = m.partial_group_sum(&g).unwrap();
assert_eq!(result.get(0), 500);
assert_eq!(result.get(1), 400);
assert_eq!(result.sum(), 900);
}
// ── IntMatrix: partial_group_presence_count ───────────────────────────────────
#[test]
fn int_partial_group_presence_count() {
// col0=[5,1,0,3], col1=[2,0,4,3], col2=[0,3,1,0]
// threshold=2: col0: [T,F,F,T], col1: [T,F,T,T], col2: [F,T,F,F]
// group {0,1,2}: counts = [2, 1, 1, 2]
let (_d, m) = make_int_matrix(&[&[5, 1, 0, 3], &[2, 0, 4, 3], &[0, 3, 1, 0]]);
let g = ColGroup::new("g", vec![0, 1, 2]);
let result = m.partial_group_presence_count(&g, 2).unwrap();
assert_eq!(result.get(0), 2);
assert_eq!(result.get(1), 1);
assert_eq!(result.get(2), 1);
assert_eq!(result.get(3), 2);
}
#[test]
fn int_partial_group_presence_count_with_overflow() {
// col0=[300,0,10], col1=[0,400,10], col2=[1,1,10]
// threshold=5: col0: [T,F,T], col1: [F,T,T], col2: [F,F,T]
// group {0,1,2}: counts = [1, 1, 3]
let (_d, m) = make_int_matrix(&[&[300, 0, 10], &[0, 400, 10], &[1, 1, 10]]);
let g = ColGroup::new("g", vec![0, 1, 2]);
let result = m.partial_group_presence_count(&g, 5).unwrap();
assert_eq!(result.get(0), 1);
assert_eq!(result.get(1), 1);
assert_eq!(result.get(2), 3);
}
// ── IntMatrix: partial_group_any ──────────────────────────────────────────────
#[test]
fn int_partial_group_any() {
// col0=[0,3,0,1], col1=[2,0,0,0], col2=[0,0,5,0]
// threshold=2: col0: [F,T,F,F], col1: [T,F,F,F], col2: [F,F,T,F]
// group {0,1,2}: any = [T, T, T, F]
let (_d, m) = make_int_matrix(&[&[0, 3, 0, 1], &[2, 0, 0, 0], &[0, 0, 5, 0]]);
let g = ColGroup::new("g", vec![0, 1, 2]);
let result = m.partial_group_any(&g, 2).unwrap();
assert_eq!(result.get(0), true);
assert_eq!(result.get(1), true);
assert_eq!(result.get(2), true);
assert_eq!(result.get(3), false);
}
// ── IntMatrix: mask_with ──────────────────────────────────────────────────────
#[test]
fn mask_with_zeros_selected_slots() {
// count vec [10, 20, 30, 40], mask [T, F, T, F] → [10, 0, 30, 0]
let dir = tempdir().unwrap();
let mut v = PersistentCompactIntVecBuilder::new(4, &dir.path().join("v.pciv")).unwrap();
v.set(0, 10); v.set(1, 20); v.set(2, 30); v.set(3, 40);
let mut mask = PersistentBitVecBuilder::new(4, &dir.path().join("m.pbiv")).unwrap();
mask.set(0, true); mask.set(2, true);
v.mask_with(mask.view());
v.close().unwrap();
let r = PersistentCompactIntVec::open(&dir.path().join("v.pciv")).unwrap();
assert_eq!(r.get(0), 10);
assert_eq!(r.get(1), 0);
assert_eq!(r.get(2), 30);
assert_eq!(r.get(3), 0);
}
#[test]
fn mask_with_overflow_slot_zeroed() {
// overflow slot (value 500) masked out → removed from overflow, primary=0
let dir = tempdir().unwrap();
let mut v = PersistentCompactIntVecBuilder::new(3, &dir.path().join("v.pciv")).unwrap();
v.set(0, 10); v.set(1, 500); v.set(2, 5);
let mut mask = PersistentBitVecBuilder::new(3, &dir.path().join("m.pbiv")).unwrap();
mask.set(0, true); mask.set(2, true); // slot 1 masked out
v.mask_with(mask.view());
v.close().unwrap();
let r = PersistentCompactIntVec::open(&dir.path().join("v.pciv")).unwrap();
assert_eq!(r.get(0), 10);
assert_eq!(r.get(1), 0);
assert_eq!(r.get(2), 5);
let ov: Vec<_> = r.view().overflow_entries().collect();
assert!(ov.is_empty(), "overflow entry for masked-out slot should be gone");
}
#[test]
fn mask_with_all_ones_is_noop() {
let dir = tempdir().unwrap();
let mut v = PersistentCompactIntVecBuilder::new(4, &dir.path().join("v.pciv")).unwrap();
v.set(0, 300); v.set(1, 1); v.set(2, 0); v.set(3, 42);
let mask = PersistentBitVecBuilder::new_ones(4, &dir.path().join("m.pbiv")).unwrap();
v.mask_with(mask.view());
v.close().unwrap();
let r = PersistentCompactIntVec::open(&dir.path().join("v.pciv")).unwrap();
assert_eq!(r.get(0), 300);
assert_eq!(r.get(1), 1);
assert_eq!(r.get(2), 0);
assert_eq!(r.get(3), 42);
}
// ── BitMatrix: partial_group_presence_count ───────────────────────────────────
#[test]
fn bit_partial_group_presence_count() {
// col0=[T,F,T,F], col1=[T,T,F,F], col2=[F,T,T,F]
// group {0,1,2}: counts = [2, 2, 2, 0]
let (_d, m) = make_bit_matrix(&[
&[true, false, true, false],
&[true, true, false, false],
&[false,true, true, false],
]);
let g = ColGroup::new("g", vec![0, 1, 2]);
let result = m.partial_group_presence_count(&g, 1).unwrap();
assert_eq!(result.get(0), 2);
assert_eq!(result.get(1), 2);
assert_eq!(result.get(2), 2);
assert_eq!(result.get(3), 0);
}
// ── BitMatrix: partial_group_any ──────────────────────────────────────────────
#[test]
fn bit_partial_group_any() {
// col0=[T,F,F], col1=[F,F,T], group {0,1}: any = [T, F, T]
let (_d, m) = make_bit_matrix(&[
&[true, false, false],
&[false, false, true],
]);
let g = ColGroup::new("g", vec![0, 1]);
let result = m.partial_group_any(&g, 1).unwrap();
assert_eq!(result.get(0), true);
assert_eq!(result.get(1), false);
assert_eq!(result.get(2), true);
}
// ── Composition: partial results are additive ─────────────────────────────────
#[test]
fn int_presence_count_additive_across_split() {
// Simulate two partitions (different kmer ranges) whose counts should add.
// Global data for col0: [5,1,0,3,2], col1: [2,0,4,3,1] — threshold=2
// Split: partition A = slots 0..2, partition B = slots 2..5
let data_a: &[&[u32]] = &[&[5, 1], &[2, 0]];
let data_b: &[&[u32]] = &[&[0, 3, 2], &[4, 3, 1]];
let (_da, ma) = make_int_matrix(data_a);
let (_db, mb) = make_int_matrix(data_b);
let g = ColGroup::new("g", vec![0, 1]);
let pa = ma.partial_group_presence_count(&g, 2).unwrap();
let pb = mb.partial_group_presence_count(&g, 2).unwrap();
// Concatenate by adding (disjoint kmer ranges — here we just verify
// individual results match the expected per-partition counts).
// partition A: col0=[5≥2,1<2]=[T,F], col1=[2≥2,0<2]=[T,F] → [2, 0]
assert_eq!(pa.get(0), 2);
assert_eq!(pa.get(1), 0);
// partition B: col0=[0<2,3≥2,2≥2]=[F,T,T], col1=[4≥2,3≥2,1<2]=[T,T,F] → [1, 2, 1]
assert_eq!(pb.get(0), 1);
assert_eq!(pb.get(1), 2);
assert_eq!(pb.get(2), 1);
}
src/obicompactvec/src/tests/intmatrix.rs
+56 -1
View File
@@ -1,6 +1,6 @@
use tempfile::tempdir;
use crate::{PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder};
use crate::{pack_compact_int_matrix, PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder};
use crate::traits::CountPartials;
fn make_matrix(cols: &[&[u32]]) -> (tempfile::TempDir, PersistentCompactIntMatrix) {
@@ -243,6 +243,61 @@ fn partial_hellinger_matches_full() {
}
}
#[test]
fn col_view_packed_values() {
// Build Columnar with overflow values (≥ 255), pack, reopen as Packed, exercise col_view().
let (dir, _col) = make_matrix(&[&[10, 300, 500], &[200, 50, 1000]]);
pack_compact_int_matrix(&dir.path().join("counts")).unwrap();
let m = PersistentCompactIntMatrix::open(dir.path()).unwrap();
// col 0: [10, 300, 500] — two overflow slots
let v0 = m.col_view(0);
assert_eq!(v0.get(0), 10);
assert_eq!(v0.get(1), 300);
assert_eq!(v0.get(2), 500);
assert_eq!(v0.sum(), 810);
assert_eq!(v0.count_nonzero(), 3);
let mut ov0: Vec<(usize, u32)> = v0.overflow_entries().collect();
ov0.sort_unstable_by_key(|&(s, _)| s);
assert_eq!(ov0, vec![(1, 300), (2, 500)]);
// col 1: [200, 50, 1000] — one overflow slot
let v1 = m.col_view(1);
assert_eq!(v1.get(0), 200);
assert_eq!(v1.get(1), 50);
assert_eq!(v1.get(2), 1000);
let mut ov1: Vec<(usize, u32)> = v1.overflow_entries().collect();
ov1.sort_unstable_by_key(|&(s, _)| s);
assert_eq!(ov1, vec![(2, 1000)]);
}
#[test]
fn col_view_packed_matches_columnar() {
// Same data, compare col_view() on Packed against col() on Columnar slot-by-slot.
let data: &[&[u32]] = &[&[0, 255, 1, 300, 128], &[500, 3, 0, 700, 42]];
let (dir_col, m_col) = make_matrix(data);
// Re-build in a separate dir so we can pack without touching m_col's files.
let (dir_pack, _) = make_matrix(data);
pack_compact_int_matrix(&dir_pack.path().join("counts")).unwrap();
let m_pack = PersistentCompactIntMatrix::open(dir_pack.path()).unwrap();
for c in 0..data.len() {
let col_ref = m_col.col(c);
let col_view = m_pack.col_view(c);
assert_eq!(col_view.len(), col_ref.len());
for s in 0..col_ref.len() {
assert_eq!(col_view.get(s), col_ref.get(s), "col={c} slot={s}");
}
assert_eq!(col_view.sum(), col_ref.sum(), "col={c} sum");
let mut ov_view: Vec<(usize, u32)> = col_view.overflow_entries().collect();
let mut ov_ref: Vec<(usize, u32)> = col_ref.view().overflow_entries().collect();
ov_view.sort_unstable_by_key(|&(s, _)| s);
ov_ref.sort_unstable_by_key(|&(s, _)| s);
assert_eq!(ov_view, ov_ref, "col={c} overflow_entries");
}
drop(dir_col);
}
#[test]
fn partial_relfreq_bray_additive_across_split() {
// Split rows [1,2,3,4,5] between two matrices; partial sums should add up.
src/obicompactvec/src/tests/mod.rs
+5 -4
View File
@@ -1,5 +1,6 @@
mod bitmatrix;
mod bitvec;
mod colgroup;
mod intmatrix;
use tempfile::tempdir;
@@ -169,7 +170,7 @@ fn combine_min() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pciv");
let mut b = PersistentCompactIntVecBuilder::build_from(&ra, &path).unwrap();
b.min(&rb);
b.min(rb.view());
b.close().unwrap();
let r = PersistentCompactIntVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![10, 100, 0, 800]);
@@ -182,7 +183,7 @@ fn combine_max() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pciv");
let mut b = PersistentCompactIntVecBuilder::build_from(&ra, &path).unwrap();
b.max(&rb);
b.max(rb.view());
b.close().unwrap();
let r = PersistentCompactIntVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![20, 300, 500, 1000]);
@@ -195,7 +196,7 @@ fn combine_add() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pciv");
let mut b = PersistentCompactIntVecBuilder::build_from(&ra, &path).unwrap();
b.add(&rb);
b.add(rb.view());
b.close().unwrap();
let r = PersistentCompactIntVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![30, 300, 5, 101]);
@@ -220,7 +221,7 @@ fn combine_diff() {
let dir = tempdir().unwrap();
let path = dir.path().join("out.pciv");
let mut b = PersistentCompactIntVecBuilder::build_from(&ra, &path).unwrap();
b.diff(&rb);
b.diff(rb.view());
b.close().unwrap();
let r = PersistentCompactIntVec::open(&path).unwrap();
assert_eq!(r.iter().collect::<Vec<_>>(), vec![10, 700, 0, 0]);
src/obicompactvec/src/traits.rs
+1 -1
View File
@@ -1,6 +1,6 @@
use ndarray::{Array1, Array2};
/// Column-level weight statistic — total count or presence count per column.
// ── Column-level weight statistic — total count or presence count per column.
/// Additive across layers and partitions; used as denominator in normalised distances.
///
/// `partial_kmer_counts` returns the number of **distinct k-mers** present per
src/obicompactvec/src/views.rs
+278
View File
@@ -0,0 +1,278 @@
use crate::format::{byte_count_nonzero, byte_sum, parse_overflow_entry};
// ── BitSliceView ──────────────────────────────────────────────────────────────
/// Lightweight, copy-able read-only view over a u64 word array.
/// Bit `i` is in `words[i >> 6]` at position `i & 63`. Padding bits are zero.
#[derive(Clone, Copy)]
pub struct BitSliceView<'a> {
pub(crate) words: &'a [u64],
pub(crate) n: usize,
}
impl<'a> BitSliceView<'a> {
#[inline]
pub fn new(words: &'a [u64], n: usize) -> Self { Self { words, n } }
pub fn len(&self) -> usize { self.n }
pub fn is_empty(&self) -> bool { self.n == 0 }
pub fn words(&self) -> &'a [u64] { self.words }
#[inline]
pub fn get(&self, slot: usize) -> bool {
(self.words[slot >> 6] >> (slot & 63)) & 1 != 0
}
pub fn count_ones(&self) -> u64 {
self.words.iter().map(|w| w.count_ones() as u64).sum()
}
pub fn count_zeros(&self) -> u64 { self.n as u64 - self.count_ones() }
pub fn iter(&self) -> BitSliceIter<'a> {
BitSliceIter { words: self.words, slot: 0, n: self.n }
}
pub fn partial_jaccard_dist(self, other: BitSliceView<'_>) -> (u64, u64) {
assert_eq!(self.n, other.n, "BitSliceView length mismatch");
self.words.iter().zip(other.words)
.fold((0u64, 0u64), |(i, u), (&a, &b)| {
(i + (a & b).count_ones() as u64, u + (a | b).count_ones() as u64)
})
}
pub fn jaccard_dist(self, other: BitSliceView<'_>) -> f64 {
let (inter, union) = self.partial_jaccard_dist(other);
if union == 0 { 0.0 } else { 1.0 - inter as f64 / union as f64 }
}
pub fn hamming_dist(self, other: BitSliceView<'_>) -> u64 {
assert_eq!(self.n, other.n, "BitSliceView length mismatch");
self.words.iter().zip(other.words)
.map(|(&a, &b)| (a ^ b).count_ones() as u64)
.sum()
}
}
// ── BitSliceIter ──────────────────────────────────────────────────────────────
pub struct BitSliceIter<'a> {
words: &'a [u64],
slot: usize,
n: usize,
}
impl Iterator for BitSliceIter<'_> {
type Item = bool;
fn next(&mut self) -> Option<bool> {
if self.slot >= self.n { return None; }
let v = (self.words[self.slot >> 6] >> (self.slot & 63)) & 1 != 0;
self.slot += 1;
Some(v)
}
fn size_hint(&self) -> (usize, Option<usize>) {
let rem = self.n - self.slot;
(rem, Some(rem))
}
}
impl ExactSizeIterator for BitSliceIter<'_> {}
// ── IntSliceView ──────────────────────────────────────────────────────────────
/// Lightweight, copy-able read-only view over a compact-int primary array plus
/// its sorted raw overflow bytes. Zero-copy: all data lives in the caller's mmap.
#[derive(Clone, Copy)]
pub struct IntSliceView<'a> {
pub(crate) primary: &'a [u8],
pub(crate) overflow_raw: &'a [u8], // n_overflow × OVERFLOW_ENTRY_SIZE bytes, sorted by slot
pub(crate) n_overflow: usize,
pub(crate) n: usize,
}
impl<'a> IntSliceView<'a> {
#[inline]
pub fn new(primary: &'a [u8], overflow_raw: &'a [u8], n_overflow: usize, n: usize) -> Self {
Self { primary, overflow_raw, n_overflow, n }
}
pub fn len(&self) -> usize { self.n }
pub fn is_empty(&self) -> bool { self.n == 0 }
pub fn primary_bytes(&self) -> &'a [u8] { self.primary }
pub fn n_overflow(&self) -> usize { self.n_overflow }
pub fn overflow_entries(&self) -> impl Iterator<Item = (usize, u32)> + 'a {
let raw = self.overflow_raw;
let n_ov = self.n_overflow;
(0..n_ov).map(move |i| parse_overflow_entry(raw, 0, i))
}
/// O(log n_overflow) via binary search (overflow is always sorted by slot).
pub fn get(&self, slot: usize) -> u32 {
let b = self.primary[slot];
if b < 255 { return b as u32; }
let mut lo = 0usize;
let mut hi = self.n_overflow;
while lo < hi {
let mid = lo + (hi - lo) / 2;
let (s, v) = parse_overflow_entry(self.overflow_raw, 0, mid);
match s.cmp(&slot) {
std::cmp::Ordering::Equal => return v,
std::cmp::Ordering::Less => lo = mid + 1,
std::cmp::Ordering::Greater => hi = mid,
}
}
panic!("slot {slot} marked overflow but not found")
}
/// Sequential merge scan: yields all n values in slot order.
pub fn iter(&self) -> IntSliceViewIter<'a> {
IntSliceViewIter {
primary: self.primary,
overflow_raw: self.overflow_raw,
slot: 0,
overflow_pos: 0,
n: self.n,
}
}
pub fn sum(&self) -> u64 {
byte_sum(self.primary, self.overflow_entries().map(|(_, v)| v))
}
pub fn count_nonzero(&self) -> u64 {
byte_count_nonzero(self.primary)
}
// ── Distance methods ──────────────────────────────────────────────────────
pub fn partial_bray_dist(self, other: IntSliceView<'_>) -> u64 {
assert_eq!(self.n, other.n, "length mismatch");
self.iter().zip(other.iter()).map(|(a, b)| a.min(b) as u64).sum()
}
pub fn bray_dist(self, other: IntSliceView<'_>) -> f64 {
let sum_min = self.partial_bray_dist(other);
let denom = self.sum() + other.sum();
if denom == 0 { 0.0 } else { 1.0 - 2.0 * sum_min as f64 / denom as f64 }
}
pub fn partial_relfreq_bray_dist(self, other: IntSliceView<'_>, sa: f64, sb: f64) -> f64 {
assert_eq!(self.n, other.n, "length mismatch");
self.iter().zip(other.iter())
.map(|(a, b)| {
let pa = if sa > 0.0 { a as f64 / sa } else { 0.0 };
let pb = if sb > 0.0 { b as f64 / sb } else { 0.0 };
pa.min(pb)
})
.sum()
}
pub fn relfreq_bray_dist(self, other: IntSliceView<'_>) -> f64 {
let sa = self.sum() as f64;
let sb = other.sum() as f64;
if sa == 0.0 && sb == 0.0 { return 0.0; }
1.0 - self.partial_relfreq_bray_dist(other, sa, sb)
}
pub fn partial_euclidean_dist(self, other: IntSliceView<'_>) -> f64 {
assert_eq!(self.n, other.n, "length mismatch");
self.iter().zip(other.iter())
.map(|(a, b)| { let d = a as f64 - b as f64; d * d })
.sum()
}
pub fn euclidean_dist(self, other: IntSliceView<'_>) -> f64 {
self.partial_euclidean_dist(other).sqrt()
}
pub fn partial_relfreq_euclidean_dist(self, other: IntSliceView<'_>, sa: f64, sb: f64) -> f64 {
assert_eq!(self.n, other.n, "length mismatch");
self.iter().zip(other.iter())
.map(|(a, b)| {
let pa = if sa > 0.0 { a as f64 / sa } else { 0.0 };
let pb = if sb > 0.0 { b as f64 / sb } else { 0.0 };
let d = pa - pb;
d * d
})
.sum()
}
pub fn relfreq_euclidean_dist(self, other: IntSliceView<'_>) -> f64 {
let sa = self.sum() as f64;
let sb = other.sum() as f64;
if sa == 0.0 && sb == 0.0 { return 0.0; }
self.partial_relfreq_euclidean_dist(other, sa, sb).sqrt()
}
pub fn partial_hellinger_euclidean_dist(self, other: IntSliceView<'_>, sa: f64, sb: f64) -> f64 {
assert_eq!(self.n, other.n, "length mismatch");
self.iter().zip(other.iter())
.map(|(a, b)| {
let pa = if sa > 0.0 { (a as f64 / sa).sqrt() } else { 0.0 };
let pb = if sb > 0.0 { (b as f64 / sb).sqrt() } else { 0.0 };
let d = pa - pb;
d * d
})
.sum()
}
pub fn hellinger_euclidean_dist(self, other: IntSliceView<'_>) -> f64 {
let sa = self.sum() as f64;
let sb = other.sum() as f64;
if sa == 0.0 && sb == 0.0 { return 0.0; }
self.partial_hellinger_euclidean_dist(other, sa, sb).sqrt()
}
pub fn hellinger_dist(self, other: IntSliceView<'_>) -> f64 {
self.hellinger_euclidean_dist(other) / std::f64::consts::SQRT_2
}
pub fn partial_threshold_jaccard_dist(self, other: IntSliceView<'_>, threshold: u32) -> (u64, u64) {
assert_eq!(self.n, other.n, "length mismatch");
self.iter().zip(other.iter())
.fold((0u64, 0u64), |(inter, uni), (a, b)| {
let ap = a >= threshold;
let bp = b >= threshold;
(inter + (ap & bp) as u64, uni + (ap | bp) as u64)
})
}
pub fn threshold_jaccard_dist(self, other: IntSliceView<'_>, threshold: u32) -> f64 {
let (inter, union) = self.partial_threshold_jaccard_dist(other, threshold);
if union == 0 { 0.0 } else { 1.0 - inter as f64 / union as f64 }
}
pub fn jaccard_dist(self, other: IntSliceView<'_>) -> f64 {
self.threshold_jaccard_dist(other, 1)
}
}
// ── IntSliceViewIter ──────────────────────────────────────────────────────────
pub struct IntSliceViewIter<'a> {
primary: &'a [u8],
overflow_raw: &'a [u8],
slot: usize,
overflow_pos: usize,
n: usize,
}
impl Iterator for IntSliceViewIter<'_> {
type Item = u32;
fn next(&mut self) -> Option<u32> {
if self.slot >= self.n { return None; }
let v = self.primary[self.slot];
self.slot += 1;
if v < 255 {
Some(v as u32)
} else {
let (_, val) = parse_overflow_entry(self.overflow_raw, 0, self.overflow_pos);
self.overflow_pos += 1;
Some(val)
}
}
fn size_hint(&self) -> (usize, Option<usize>) {
let rem = self.n - self.slot;
(rem, Some(rem))
}
}
impl ExactSizeIterator for IntSliceViewIter<'_> {}
src/obidebruinj/src/debruijn.rs
+1
View File
@@ -3,6 +3,7 @@ use crossbeam_channel;
use hashbrown::HashMap;
use obikseq::k;
use obikseq::{CanonicalKmer, Sequence, Unitig};
#[cfg(not(any(test, feature = "test-utils")))]
use rayon::iter::{IntoParallelRefIterator, ParallelIterator};
use std::cell::RefCell;
use std::fmt;
src/obikindex/src/index.rs
+5 -2
View File
@@ -204,6 +204,7 @@ impl KmerIndex {
let n = self.n_partitions();
let order: Vec<usize> = (0..n).collect();
let pb = progress_bar("pack", n as u64, "partitions");
crate::numa::PartitionRunner::new().run(
&order,
|i| -> OKIResult<()> {
@@ -220,8 +221,10 @@ impl KmerIndex {
}
Ok(())
},
|_, _, _| {},
)
|_, _, _| { pb.inc(1); },
)?;
pb.finish_and_clear();
Ok(())
}
/// Write a `layer_meta.json` in any layer directory that is missing one.
src/obikindex/src/merge.rs
+3 -1
View File
@@ -11,7 +11,7 @@ use obilayeredmap::IndexMode;
use crate::error::{OKIError, OKIResult};
use crate::index::KmerIndex;
use crate::meta::{GenomeInfo, IndexMeta};
use crate::state::IndexState;
use crate::state::{IndexState, SENTINEL_INDEXED};
pub use obikpartitionner::MergeMode;
@@ -263,6 +263,8 @@ impl KmerIndex {
rep.push(t.stop());
}
fs::File::create(output.join(SENTINEL_INDEXED)).map_err(OKIError::Io)?;
KmerIndex::open(output)
}
}
src/obikindex/src/rebuild.rs
+2
View File
@@ -98,7 +98,9 @@ impl KmerIndex {
fs::File::create(output.join(SENTINEL_INDEXED))?;
let idx = KmerIndex::open(output)?;
let t_pack = Stage::start("pack");
idx.pack_matrices()?;
rep.push(t_pack.stop());
Ok(idx)
}
}
src/obikindex/src/select.rs
+9 -7
View File
@@ -3,7 +3,7 @@ use std::io;
use std::path::Path;
use obikpartitionner::{KmerPartition, OutputCol, PARTITIONS_SUBDIR};
use obisys::{Stage, progress_bar};
use obisys::{Reporter, Stage, progress_bar};
use tracing::info;
use crate::error::{OKIError, OKIResult};
@@ -25,6 +25,7 @@ impl KmerIndex {
threshold: u32,
output_presence: bool,
force: bool,
rep: &mut Reporter,
) -> OKIResult<Self> {
let output = output.as_ref();
@@ -80,13 +81,14 @@ impl KmerIndex {
).map_err(OKIError::Partition)?;
pb.finish_and_clear();
let _ = t.stop();
rep.push(t.stop());
fs::File::create(output.join(SENTINEL_INDEXED))?;
let idx = KmerIndex::open(output)?;
let t_pack = Stage::start("pack");
idx.pack_matrices()?;
rep.push(t_pack.stop());
Ok(idx)
}
@@ -98,6 +100,7 @@ impl KmerIndex {
specs: &[OutputCol],
threshold: u32,
output_presence: bool,
rep: &mut Reporter,
) -> OKIResult<()> {
if self.state() != IndexState::Indexed {
return Err(OKIError::NotIndexed(self.root_path.clone()));
@@ -106,7 +109,6 @@ impl KmerIndex {
let n_src_genomes = self.meta.genomes.len();
let n_partitions = self.partition.n_partitions();
// Open a second handle to the same path so we can borrow src and dst simultaneously.
let src_partition = KmerPartition::open_with_config(
&self.root_path,
self.meta.config.kmer_size,
@@ -132,17 +134,17 @@ impl KmerIndex {
).map_err(OKIError::Partition)?;
pb.finish_and_clear();
rep.push(t.stop());
let _ = t.stop();
// Update index.meta with new genome list and with_counts flag.
self.meta.config.with_counts = !output_presence;
self.meta.genomes = specs.iter()
.map(|s| GenomeInfo::new(s.label.clone()))
.collect();
self.meta.write(&self.root_path)?;
let t_pack = Stage::start("pack");
self.pack_matrices()?;
rep.push(t_pack.stop());
Ok(())
}
}
src/obikmer/Cargo.toml
+2 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "obikmer"
version = "0.1.0"
version = "0.1.3"
edition = "2024"
[[bin]]
@@ -19,6 +19,7 @@ obikpartitionner = { path = "../obikpartitionner" }
obisys = { path = "../obisys" }
obiskio = { path = "../obiskio" }
obikindex = { path = "../obikindex" }
obitaxonomy = { path = "../obitaxonomy" }
obilayeredmap = { path = "../obilayeredmap" }
clap = { version = "4", features = ["derive"] }
serde_json = "1"
src/obikmer/src/cmd/predicate.rs
+8 -11
View File
@@ -3,6 +3,7 @@ use std::collections::HashMap;
use clap::Args;
use obikindex::GenomeInfo;
use obikpartitionner::{GroupQuorumFilter, KmerFilter};
use obitaxonomy::{TaxPath, TaxPattern};
// ── Operator ──────────────────────────────────────────────────────────────────
@@ -49,7 +50,6 @@ impl MetaPred {
if values.iter().any(|v| v.is_empty()) {
return Err(format!("empty value in predicate: {s}"));
}
Ok(Self { key, op, values })
}
@@ -70,18 +70,15 @@ impl MetaPred {
// ── Path matching ─────────────────────────────────────────────────────────────
/// True if `value` is equal to `pattern` or is a descendant of it in a `/`-separated hierarchy.
/// True if the stored taxonomy `value` matches `pattern`.
///
/// - Absolute pattern (`/a/b`): `value` must start with `/a/b` at a segment boundary.
/// - Bare segment (`b`): `value` must contain `b` as an exact segment anywhere.
/// `value` must be a valid `TaxPath` (starts with `taxonomy:/`).
/// `pattern` is a `TaxPattern` query (see `obitaxonomy::TaxPattern` for syntax).
/// Returns `false` if either fails to parse.
fn path_matches(value: &str, pattern: &str) -> bool {
if pattern.starts_with('/') {
value == pattern
|| (value.starts_with(pattern)
&& value[pattern.len()..].starts_with('/'))
} else {
value.split('/').any(|seg| seg == pattern)
}
let Ok(path) = TaxPath::parse(value) else { return false };
let Ok(pat) = TaxPattern::parse(pattern) else { return false };
pat.matches(&path)
}
// ── Three-value group evaluation ──────────────────────────────────────────────
src/obikmer/src/cmd/select.rs
+7 -2
View File
@@ -4,6 +4,7 @@ use std::path::PathBuf;
use clap::{Args, ValueEnum};
use obikindex::{GenomeInfo, KmerIndex};
use obikpartitionner::{AggOp, OutputCol};
use obisys::Reporter;
use tracing::info;
use super::predicate::matching_genome_indices;
@@ -229,20 +230,24 @@ pub fn run(args: SelectArgs) {
if output_presence { "presence" } else { "count" },
);
let mut rep = Reporter::new();
if args.in_place {
src.select_in_place(&specs, args.presence_threshold, output_presence)
src.select_in_place(&specs, args.presence_threshold, output_presence, &mut rep)
.unwrap_or_else(|e| {
eprintln!("select error: {e}");
std::process::exit(1);
});
rep.print();
info!("selected in-place → {}", args.source.display());
} else {
let output = args.output.unwrap();
KmerIndex::select(&output, &src, &specs, args.presence_threshold, output_presence, args.force)
KmerIndex::select(&output, &src, &specs, args.presence_threshold, output_presence, args.force, &mut rep)
.unwrap_or_else(|e| {
eprintln!("select error: {e}");
std::process::exit(1);
});
rep.print();
info!("selected index → {}", output.display());
}
}
src/obikmer/src/main.rs
+1 -1
View File
@@ -6,7 +6,7 @@ use clap::{Parser, Subcommand};
use tracing_subscriber::{EnvFilter, fmt};
#[derive(Parser)]
#[command(name = "obikmer", about = "DNA k-mer tools")]
#[command(name = "obikmer", about = "DNA k-mer tools", version)]
struct Cli {
#[command(subcommand)]
command: Commands,
src/obikpartitionner/src/filter.rs
+120
View File
@@ -1,9 +1,24 @@
use obicompactvec::FilterMask;
/// Trait for kmer row filters.
///
/// `row` contains raw per-genome counts (or 0/1 for presence/absence data).
/// `n_genomes` equals `row.len()`.
pub trait KmerFilter: Send + Sync {
fn passes(&self, row: &[u32], n_genomes: usize) -> bool;
/// Express this filter as a [`FilterMask`] column-operation expression.
///
/// Returns `Some(expr)` if the filter can be evaluated solely from matrix
/// column aggregates (no per-kmer row scan needed). Returns `None` if the
/// filter requires row-level inspection.
///
/// `threshold` semantics in the returned mask use `>= threshold`, matching
/// [`obicompactvec::MatrixGroupOps`]. Implementations must add 1 to any
/// row-level threshold that uses strict `>` comparison.
fn column_mask_expr(&self, _n_genomes: usize) -> Option<FilterMask> {
None
}
}
/// True when `row` passes every filter in `filters`.
@@ -29,6 +44,16 @@ impl KmerFilter for MinGenomeFraction {
let p = present_count(row, self.threshold);
p as f64 / n_genomes as f64 >= self.frac
}
fn column_mask_expr(&self, n_genomes: usize) -> Option<FilterMask> {
let t = self.threshold.checked_add(1)?;
let min_count = (self.frac * n_genomes as f64).ceil() as usize;
Some(FilterMask::PresenceGeq {
indices: (0..n_genomes).collect(),
threshold: t,
min_count,
})
}
}
/// At most `frac` fraction of genomes contain this kmer (count > `threshold`).
@@ -42,6 +67,16 @@ impl KmerFilter for MaxGenomeFraction {
let p = present_count(row, self.threshold);
p as f64 / n_genomes as f64 <= self.frac
}
fn column_mask_expr(&self, n_genomes: usize) -> Option<FilterMask> {
let t = self.threshold.checked_add(1)?;
let max_count = (self.frac * n_genomes as f64).floor() as usize;
Some(FilterMask::PresenceLeq {
indices: (0..n_genomes).collect(),
threshold: t,
max_count,
})
}
}
/// At least `count` genomes contain this kmer (count > `threshold`).
@@ -54,6 +89,15 @@ impl KmerFilter for MinGenomeCount {
fn passes(&self, row: &[u32], _n_genomes: usize) -> bool {
present_count(row, self.threshold) >= self.count
}
fn column_mask_expr(&self, n_genomes: usize) -> Option<FilterMask> {
let t = self.threshold.checked_add(1)?;
Some(FilterMask::PresenceGeq {
indices: (0..n_genomes).collect(),
threshold: t,
min_count: self.count,
})
}
}
/// At most `count` genomes contain this kmer (count > `threshold`).
@@ -66,6 +110,15 @@ impl KmerFilter for MaxGenomeCount {
fn passes(&self, row: &[u32], _n_genomes: usize) -> bool {
present_count(row, self.threshold) <= self.count
}
fn column_mask_expr(&self, n_genomes: usize) -> Option<FilterMask> {
let t = self.threshold.checked_add(1)?;
Some(FilterMask::PresenceLeq {
indices: (0..n_genomes).collect(),
threshold: t,
max_count: self.count,
})
}
}
// ── Total-count filters (count indexes only) ───────────────────────────────────
@@ -79,6 +132,13 @@ impl KmerFilter for MinTotalCount {
fn passes(&self, row: &[u32], _n_genomes: usize) -> bool {
row.iter().sum::<u32>() >= self.total
}
fn column_mask_expr(&self, n_genomes: usize) -> Option<FilterMask> {
Some(FilterMask::SumGeq {
indices: (0..n_genomes).collect(),
min_sum: self.total,
})
}
}
/// Sum of counts across all genomes <= `total`.
@@ -90,6 +150,13 @@ impl KmerFilter for MaxTotalCount {
fn passes(&self, row: &[u32], _n_genomes: usize) -> bool {
row.iter().sum::<u32>() <= self.total
}
fn column_mask_expr(&self, n_genomes: usize) -> Option<FilterMask> {
Some(FilterMask::SumLeq {
indices: (0..n_genomes).collect(),
max_sum: self.total,
})
}
}
// ── Group-based quorum filter ─────────────────────────────────────────────────
@@ -113,6 +180,37 @@ pub struct GroupQuorumFilter {
pub max_outgroup_frac: f64,
}
impl GroupQuorumFilter {
// Build PresenceGeq/PresenceLeq constraints for one group (ingroup or outgroup).
fn group_mask_parts(
indices: &[usize],
threshold: u32,
min_count: usize,
max_count: usize,
min_frac: f64,
max_frac: f64,
parts: &mut Vec<FilterMask>,
) {
let n = indices.len();
let geq = min_count.max((min_frac * n as f64).ceil() as usize);
if geq > 0 {
parts.push(FilterMask::PresenceGeq {
indices: indices.to_vec(),
threshold,
min_count: geq,
});
}
let leq = max_count.min((max_frac * n as f64).floor() as usize);
if leq < n {
parts.push(FilterMask::PresenceLeq {
indices: indices.to_vec(),
threshold,
max_count: leq,
});
}
}
}
impl KmerFilter for GroupQuorumFilter {
fn passes(&self, row: &[u32], _n_genomes: usize) -> bool {
if !self.ingroup_idx.is_empty() {
@@ -139,4 +237,26 @@ impl KmerFilter for GroupQuorumFilter {
}
true
}
fn column_mask_expr(&self, _n_genomes: usize) -> Option<FilterMask> {
let t = self.threshold.checked_add(1)?;
let mut parts: Vec<FilterMask> = Vec::new();
if !self.ingroup_idx.is_empty() {
Self::group_mask_parts(
&self.ingroup_idx, t,
self.min_count, self.max_count,
self.min_frac, self.max_frac,
&mut parts,
);
}
if !self.outgroup_idx.is_empty() {
Self::group_mask_parts(
&self.outgroup_idx, t,
self.min_outgroup_count, self.max_outgroup_count,
self.min_outgroup_frac, self.max_outgroup_frac,
&mut parts,
);
}
Some(FilterMask::And(parts))
}
}
src/obikpartitionner/src/merge_layer.rs
+36
View File
@@ -10,6 +10,7 @@ use obipipeline::{
};
use obicompactvec::{
MatrixGroupOps,
PersistentBitMatrix, PersistentBitMatrixBuilder, PersistentBitVecBuilder,
PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder, PersistentCompactIntVecBuilder,
};
@@ -78,6 +79,41 @@ impl SrcLayerData {
}
buf
}
pub(crate) fn n_slots(&self) -> usize {
match self {
SrcLayerData::Presence(_, mat) => mat.n(),
SrcLayerData::Count(_, mat) => mat.n(),
}
}
/// MPHF lookup: returns the slot index for `kmer` (kmer must be in the domain).
#[inline]
pub(crate) fn slot(&self, kmer: CanonicalKmer) -> usize {
match self {
SrcLayerData::Presence(mphf, _) => mphf.index(kmer),
SrcLayerData::Count(mphf, _) => mphf.index(kmer),
}
}
/// Row lookup by slot index, bypassing the MPHF.
#[inline]
pub(crate) fn fill_row_by_slot(&self, slot: usize, n_genomes: usize) -> Vec<u32> {
let mut buf = vec![0u32; n_genomes];
match self {
SrcLayerData::Presence(_, mat) => mat.fill_row(slot, &mut buf),
SrcLayerData::Count(_, mat) => mat.fill_row(slot, &mut buf),
}
buf
}
/// Call `f` with a reference to the underlying matrix as `&dyn MatrixGroupOps`.
pub(crate) fn with_matrix<R>(&self, f: impl FnOnce(&dyn MatrixGroupOps) -> R) -> R {
match self {
SrcLayerData::Presence(_, mat) => f(mat),
SrcLayerData::Count(_, mat) => f(mat),
}
}
}
// ── helpers ───────────────────────────────────────────────────────────────────
src/obikpartitionner/src/rebuild_layer.rs
+142 -50
View File
@@ -1,8 +1,9 @@
use std::path::Path;
use obicompactvec::{
PersistentBitMatrixBuilder, PersistentBitVecBuilder, PersistentCompactIntMatrixBuilder,
PersistentCompactIntVecBuilder,
FilterMask, eval_filter_mask,
PersistentBitMatrixBuilder, PersistentBitVecBuilder,
PersistentCompactIntMatrixBuilder, PersistentCompactIntVecBuilder,
};
use obidebruinj::GraphDeBruijn;
use obikseq::CanonicalKmer;
@@ -10,18 +11,135 @@ use obilayeredmap::meta::PartitionMeta;
use obilayeredmap::{IndexMode, MphfLayer};
use obiskio::{SKError, SKResult, UnitigFileReader};
use crate::common::{ColBuilder, col_path_bit, col_path_int, load_meta, olm_to_sk, write_matrix_meta};
use crate::filter::{KmerFilter, passes_all};
use crate::common::{load_meta, olm_to_sk};
use crate::filter::KmerFilter;
use crate::graph_pipeline::materialize_layer;
use crate::merge_layer::{MergeMode, SrcLayerData};
use crate::partition::KmerPartition;
const INDEX_SUBDIR: &str = "index";
/// Iterate all kmers in `src_index_dir` that pass `filters`, yielding `(kmer, row)`.
// ── Builders — pair matrix builder + column builders for one mode ─────────────
enum Builders {
Presence(PersistentBitMatrixBuilder, Vec<PersistentBitVecBuilder>),
Count(PersistentCompactIntMatrixBuilder, Vec<PersistentCompactIntVecBuilder>),
}
impl Builders {
fn new(mode: MergeMode, n: usize, dir: &Path, n_genomes: usize) -> SKResult<Self> {
match mode {
MergeMode::Presence => {
let mut mat = PersistentBitMatrixBuilder::new(n, dir).map_err(SKError::Io)?;
let mut cols = Vec::with_capacity(n_genomes);
for _ in 0..n_genomes { cols.push(mat.add_col().map_err(SKError::Io)?); }
Ok(Builders::Presence(mat, cols))
}
MergeMode::Count => {
let mut mat = PersistentCompactIntMatrixBuilder::new(n, dir).map_err(SKError::Io)?;
let mut cols = Vec::with_capacity(n_genomes);
for _ in 0..n_genomes { cols.push(mat.add_col().map_err(SKError::Io)?); }
Ok(Builders::Count(mat, cols))
}
}
}
fn set_val(&mut self, col: usize, slot: usize, value: u32) {
match self {
Builders::Presence(_, cols) => cols[col].set(slot, value > 0),
Builders::Count(_, cols) => cols[col].set(slot, value),
}
}
fn close(self) -> SKResult<()> {
match self {
Builders::Presence(mat, cols) => {
for b in cols { b.close().map_err(SKError::Io)?; }
mat.close().map_err(SKError::Io)
}
Builders::Count(mat, cols) => {
for b in cols { b.close().map_err(SKError::Io)?; }
mat.close().map_err(SKError::Io)
}
}
}
}
// ── try_compute_combined_mask ─────────────────────────────────────────────────
/// Build a per-slot `TempBitVec` mask from `filters` using column operations
/// on the source matrix — no per-kmer MPHF lookup or row read needed.
///
/// Uses [`SrcLayerData`] semantics: counts take priority over presence when
/// `mode = Count`; presence (or implicit all-ones) is used for `Presence`.
/// Returns `Some(mask)` when every filter in `filters` can express itself as
/// a [`FilterMask`] expression. Returns `None` when any filter requires
/// row-level inspection (fall back to `passes_all`).
fn try_compute_combined_mask(
filters: &[Box<dyn KmerFilter>],
src_data: &SrcLayerData,
n_genomes: usize,
) -> SKResult<Option<obicompactvec::TempBitVec>> {
if filters.is_empty() {
return Ok(None);
}
let mut exprs: Vec<FilterMask> = Vec::with_capacity(filters.len());
for f in filters {
match f.column_mask_expr(n_genomes) {
Some(expr) => exprs.push(expr),
None => return Ok(None),
}
}
let combined = FilterMask::And(exprs);
let n = src_data.n_slots();
let mask = src_data
.with_matrix(|mat| eval_filter_mask(&combined, mat, n))
.map_err(SKError::Io)?;
Ok(Some(mask))
}
// ── iter_src_kmers_masked (pass 1) ────────────────────────────────────────────
/// Iterate all passing kmers in `src_index_dir`, yielding only the kmer value.
///
/// When all filters can be expressed as column operations, a per-slot mask is
/// computed once per layer and used for O(1) slot-check per kmer instead of a
/// full row read. Falls back to row-level `passes_all` otherwise.
fn iter_src_kmers_masked(
src_index_dir: &Path,
mode: MergeMode,
n_genomes: usize,
filters: &[Box<dyn KmerFilter>],
mut cb: impl FnMut(CanonicalKmer),
) -> SKResult<()> {
let src_meta = load_meta(src_index_dir, "rebuild")?;
for l in 0..src_meta.n_layers {
let src_layer_dir = src_index_dir.join(format!("layer_{l}"));
let unitigs_path = src_layer_dir.join("unitigs.bin");
if !unitigs_path.exists() { continue; }
let src_data = SrcLayerData::open(&src_layer_dir, mode)?;
let mask = try_compute_combined_mask(filters, &src_data, n_genomes)?;
let reader = UnitigFileReader::open_sequential(&unitigs_path)?;
for (kmer, _, _) in reader.iter_indexed_canonical_kmers() {
let slot = src_data.slot(kmer);
let passes = match &mask {
Some(m) => m.get(slot),
None => {
let row = src_data.fill_row_by_slot(slot, n_genomes);
filters.iter().all(|f| f.passes(&row, n_genomes))
}
};
if passes { cb(kmer); }
}
}
Ok(())
}
// ── iter_src_layers (pass 2) ──────────────────────────────────────────────────
/// Iterate all passing kmers in `src_index_dir`, yielding `(kmer, row)`.
///
/// When the slot mask is available, skips the row read for filtered-out slots.
fn iter_src_layers(
src_index_dir: &Path,
mode: MergeMode,
@@ -33,17 +151,23 @@ fn iter_src_layers(
for l in 0..src_meta.n_layers {
let src_layer_dir = src_index_dir.join(format!("layer_{l}"));
let unitigs_path = src_layer_dir.join("unitigs.bin");
if !unitigs_path.exists() {
continue;
}
if !unitigs_path.exists() { continue; }
let reader = UnitigFileReader::open_sequential(&unitigs_path)?;
let src_data = SrcLayerData::open(&src_layer_dir, mode)?;
let mask = try_compute_combined_mask(filters, &src_data, n_genomes)?;
let reader = UnitigFileReader::open_sequential(&unitigs_path)?;
for (kmer, _, _) in reader.iter_indexed_canonical_kmers() {
let row = src_data.lookup(kmer, n_genomes);
if passes_all(filters, &row, n_genomes) {
let slot = src_data.slot(kmer);
if let Some(ref m) = mask {
if !m.get(slot) { continue; }
let row = src_data.fill_row_by_slot(slot, n_genomes);
cb(kmer, row.into_boxed_slice());
} else {
let row = src_data.fill_row_by_slot(slot, n_genomes);
if filters.iter().all(|f| f.passes(&row, n_genomes)) {
cb(kmer, row.into_boxed_slice());
}
}
}
}
@@ -81,7 +205,7 @@ impl KmerPartition {
// ── Pass 1: collect filtered kmers into de Bruijn graph ───────────────
let mut g = GraphDeBruijn::new();
iter_src_layers(&src_index_dir, mode, n_genomes, filters, |kmer, _row| {
iter_src_kmers_masked(&src_index_dir, mode, n_genomes, filters, |kmer| {
g.push(kmer);
})?;
@@ -103,51 +227,19 @@ impl KmerPartition {
MergeMode::Count => dst_layer_dir.join("counts"),
};
std::fs::create_dir_all(&data_dir)?;
let mut builders: Vec<ColBuilder> = match mode {
MergeMode::Presence => {
PersistentBitMatrixBuilder::new(n_new, &data_dir)
.map_err(SKError::Io)?
.close()
.map_err(SKError::Io)?;
(0..n_genomes)
.map(|g| -> SKResult<ColBuilder> {
let b = PersistentBitVecBuilder::new(n_new, &col_path_bit(&data_dir, g))?;
Ok(ColBuilder::Bit(b))
})
.collect::<SKResult<_>>()?
}
MergeMode::Count => {
PersistentCompactIntMatrixBuilder::new(n_new, &data_dir)
.map_err(SKError::Io)?
.close()
.map_err(SKError::Io)?;
(0..n_genomes)
.map(|g| -> SKResult<ColBuilder> {
let b = PersistentCompactIntVecBuilder::new(
n_new,
&col_path_int(&data_dir, g),
)?;
Ok(ColBuilder::Int(b))
})
.collect::<SKResult<_>>()?
}
};
let mut builders = Builders::new(mode, n_new, &data_dir, n_genomes)?;
// ── Pass 2: fill builders ─────────────────────────────────────────────
iter_src_layers(&src_index_dir, mode, n_genomes, filters, |kmer, row| {
if let Some(slot) = dst_mphf.find(kmer) {
for (col, &value) in row.iter().enumerate() {
builders[col].set_val(slot, value);
builders.set_val(col, slot, value);
}
}
})?;
// ── Close builders, write metadata ────────────────────────────────────
for b in builders {
b.close()?;
}
write_matrix_meta(&data_dir, n_new, n_genomes).map_err(SKError::Io)?;
// ── Close builders and write metadata ─────────────────────────────────
builders.close()?;
PartitionMeta {
n_layers: 1,
src/obikpartitionner/src/select_layer.rs
+64 -106
View File
@@ -3,8 +3,9 @@ use std::io;
use std::path::{Path, PathBuf};
use obicompactvec::{
PersistentBitMatrix, PersistentBitMatrixBuilder, PersistentBitVecBuilder,
PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder, PersistentCompactIntVecBuilder,
ColGroup, MatrixGroupOps,
PersistentBitMatrix, PersistentBitMatrixBuilder,
PersistentCompactIntMatrix, PersistentCompactIntMatrixBuilder,
};
use obilayeredmap::meta::PartitionMeta;
use obilayeredmap::OLMError;
@@ -40,52 +41,6 @@ pub struct OutputCol {
pub op: AggOp,
}
// ── Aggregation ───────────────────────────────────────────────────────────────
#[inline]
fn aggregate(op: AggOp, indices: &[usize], src_row: &[u32], threshold: u32) -> u32 {
match op {
AggOp::Any => {
if indices.iter().any(|&i| src_row[i] > threshold) { 1 } else { 0 }
}
AggOp::All => {
if indices.is_empty() { return 0; }
if indices.iter().all(|&i| src_row[i] > threshold) { 1 } else { 0 }
}
AggOp::None => {
if indices.iter().all(|&i| src_row[i] <= threshold) { 1 } else { 0 }
}
AggOp::Sum => {
indices.iter().map(|&i| src_row[i]).fold(0u32, |a, b| a.saturating_add(b))
}
AggOp::Min => indices.iter().map(|&i| src_row[i]).min().unwrap_or(0),
AggOp::Max => indices.iter().map(|&i| src_row[i]).max().unwrap_or(0),
}
}
// ── ColBuilder ────────────────────────────────────────────────────────────────
enum ColBuilder {
Bit(PersistentBitVecBuilder),
Int(PersistentCompactIntVecBuilder),
}
impl ColBuilder {
fn set_val(&mut self, slot: usize, value: u32) {
match self {
ColBuilder::Bit(b) => b.set(slot, value > 0),
ColBuilder::Int(b) => b.set(slot, value),
}
}
fn close(self) -> SKResult<()> {
match self {
ColBuilder::Bit(b) => b.close().map_err(SKError::Io),
ColBuilder::Int(b) => b.close().map_err(SKError::Io),
}
}
}
// ── Helpers ───────────────────────────────────────────────────────────────────
fn olm_to_sk(e: OLMError) -> SKError {
@@ -95,21 +50,6 @@ fn olm_to_sk(e: OLMError) -> SKError {
}
}
fn col_path_bit(dir: &Path, col: usize) -> PathBuf {
dir.join(format!("col_{col:06}.pbiv"))
}
fn col_path_int(dir: &Path, col: usize) -> PathBuf {
dir.join(format!("col_{col:06}.pciv"))
}
fn write_matrix_meta(dir: &Path, n: usize, n_cols: usize) -> io::Result<()> {
fs::write(
dir.join("meta.json"),
format!("{{\"n\":{n},\"n_cols\":{n_cols}}}\n"),
)
}
/// Copy all plain files (not subdirectories) from `src_dir` to `dst_dir`.
fn copy_layer_files(src_dir: &Path, dst_dir: &Path) -> io::Result<()> {
for entry in fs::read_dir(src_dir)? {
@@ -125,30 +65,64 @@ fn copy_layer_files(src_dir: &Path, dst_dir: &Path) -> io::Result<()> {
// ── fill_builders ─────────────────────────────────────────────────────────────
fn fill_builders(
builders: &mut [ColBuilder],
specs: &[OutputCol],
n: usize,
n_src: usize,
src_layer_dir: &Path,
src_is_count: bool,
threshold: u32,
output_presence: bool,
mut dst_bit: Option<&mut PersistentBitMatrixBuilder>,
mut dst_int: Option<&mut PersistentCompactIntMatrixBuilder>,
) -> SKResult<()> {
let mut src_buf = vec![0u32; n_src];
if src_is_count {
let mat = PersistentCompactIntMatrix::open(src_layer_dir).map_err(SKError::Io)?;
for slot in 0..n {
mat.fill_row(slot, &mut src_buf);
for (col, spec) in specs.iter().enumerate() {
builders[col].set_val(slot, aggregate(spec.op, &spec.indices, &src_buf, threshold));
for spec in specs {
let g = ColGroup::new(&spec.label, spec.indices.clone());
if output_presence {
let b = dst_bit.as_deref_mut().unwrap();
match spec.op {
AggOp::Any => b.add_col_from (&mat.partial_group_any (&g, threshold).map_err(SKError::Io)?),
AggOp::All => b.add_col_from (&mat.partial_group_all (&g, threshold).map_err(SKError::Io)?),
AggOp::None => b.add_col_from (&mat.partial_group_none(&g, threshold).map_err(SKError::Io)?),
AggOp::Sum => b.add_col_from_int(&mat.partial_group_sum (&g).map_err(SKError::Io)?),
AggOp::Min => b.add_col_from_int(&mat.partial_group_min (&g).map_err(SKError::Io)?),
AggOp::Max => b.add_col_from_int(&mat.partial_group_max (&g).map_err(SKError::Io)?),
}.map_err(SKError::Io)?;
} else {
let b = dst_int.as_deref_mut().unwrap();
match spec.op {
AggOp::Sum => b.add_col_from (&mat.partial_group_sum (&g).map_err(SKError::Io)?),
AggOp::Min => b.add_col_from (&mat.partial_group_min (&g).map_err(SKError::Io)?),
AggOp::Max => b.add_col_from (&mat.partial_group_max (&g).map_err(SKError::Io)?),
AggOp::Any => b.add_col_from_bit(&mat.partial_group_any (&g, threshold).map_err(SKError::Io)?),
AggOp::All => b.add_col_from_bit(&mat.partial_group_all (&g, threshold).map_err(SKError::Io)?),
AggOp::None => b.add_col_from_bit(&mat.partial_group_none(&g, threshold).map_err(SKError::Io)?),
}.map_err(SKError::Io)?;
}
}
} else {
let mat = PersistentBitMatrix::open(src_layer_dir).map_err(SKError::Io)?;
for slot in 0..n {
mat.fill_row(slot, &mut src_buf);
for (col, spec) in specs.iter().enumerate() {
builders[col].set_val(slot, aggregate(spec.op, &spec.indices, &src_buf, threshold));
for spec in specs {
let g = ColGroup::new(&spec.label, spec.indices.clone());
if output_presence {
let b = dst_bit.as_deref_mut().unwrap();
match spec.op {
AggOp::Any => b.add_col_from (&mat.partial_group_any (&g, 1).map_err(SKError::Io)?),
AggOp::All => b.add_col_from (&mat.partial_group_all (&g, 1).map_err(SKError::Io)?),
AggOp::None => b.add_col_from (&mat.partial_group_none(&g, 1).map_err(SKError::Io)?),
AggOp::Sum => b.add_col_from_int(&mat.partial_group_sum (&g).map_err(SKError::Io)?),
AggOp::Min => b.add_col_from_int(&mat.partial_group_min (&g).map_err(SKError::Io)?),
AggOp::Max => b.add_col_from_int(&mat.partial_group_max (&g).map_err(SKError::Io)?),
}.map_err(SKError::Io)?;
} else {
let b = dst_int.as_deref_mut().unwrap();
match spec.op {
AggOp::Sum => b.add_col_from (&mat.partial_group_sum (&g).map_err(SKError::Io)?),
AggOp::Min => b.add_col_from (&mat.partial_group_min (&g).map_err(SKError::Io)?),
AggOp::Max => b.add_col_from (&mat.partial_group_max (&g).map_err(SKError::Io)?),
AggOp::Any => b.add_col_from_bit(&mat.partial_group_any (&g, 1).map_err(SKError::Io)?),
AggOp::All => b.add_col_from_bit(&mat.partial_group_all (&g, 1).map_err(SKError::Io)?),
AggOp::None => b.add_col_from_bit(&mat.partial_group_none(&g, 1).map_err(SKError::Io)?),
}.map_err(SKError::Io)?;
}
}
}
@@ -168,7 +142,7 @@ impl KmerPartition {
src: &KmerPartition,
i: usize,
specs: &[OutputCol],
n_src_genomes: usize,
_n_src_genomes: usize,
threshold: u32,
output_presence: bool,
in_place: bool,
@@ -188,7 +162,6 @@ impl KmerPartition {
fs::create_dir_all(&dst_index_dir)?;
}
let n_out = specs.len();
let data_subdir = if output_presence { "presence" } else { "counts" };
for l in 0..src_meta.n_layers {
@@ -201,7 +174,7 @@ impl KmerPartition {
let presence_dir = src_layer_dir.join("presence");
let src_is_count = counts_dir.exists() && !presence_dir.exists();
// Determine number of slots from the source matrix.
// Determine number of slots and detect implicit layers.
let n = if counts_dir.exists() {
PersistentCompactIntMatrix::open(&src_layer_dir).map_err(SKError::Io)?.n()
} else if presence_dir.exists() {
@@ -216,7 +189,7 @@ impl KmerPartition {
};
// Choose the output data directory (temp name for in-place).
let (dst_data_dir, final_data_dir) = if in_place {
let (dst_data_dir, final_data_dir): (PathBuf, PathBuf) = if in_place {
let tmp = dst_layer_dir.join(format!("{data_subdir}_new"));
let perm = dst_layer_dir.join(data_subdir);
(tmp, perm)
@@ -231,37 +204,22 @@ impl KmerPartition {
}
fs::create_dir_all(&dst_data_dir)?;
// Initialise packed-format skeleton.
if output_presence {
PersistentBitMatrixBuilder::new(n, &dst_data_dir)
.map_err(SKError::Io)?.close().map_err(SKError::Io)?;
let (mut dst_bit, mut dst_int) = if output_presence {
(Some(PersistentBitMatrixBuilder::new(n, &dst_data_dir).map_err(SKError::Io)?), None)
} else {
PersistentCompactIntMatrixBuilder::new(n, &dst_data_dir)
.map_err(SKError::Io)?.close().map_err(SKError::Io)?;
}
// Create column builders.
let mut builders: Vec<ColBuilder> = (0..n_out)
.map(|col| -> SKResult<ColBuilder> {
if output_presence {
Ok(ColBuilder::Bit(PersistentBitVecBuilder::new(
n, &col_path_bit(&dst_data_dir, col),
)?))
} else {
Ok(ColBuilder::Int(PersistentCompactIntVecBuilder::new(
n, &col_path_int(&dst_data_dir, col),
)?))
}
})
.collect::<SKResult<_>>()?;
(None, Some(PersistentCompactIntMatrixBuilder::new(n, &dst_data_dir).map_err(SKError::Io)?))
};
fill_builders(
&mut builders, specs, n, n_src_genomes,
&src_layer_dir, src_is_count, threshold,
specs, &src_layer_dir, src_is_count, threshold, output_presence,
dst_bit.as_mut(), dst_int.as_mut(),
)?;
for b in builders { b.close()?; }
write_matrix_meta(&dst_data_dir, n, n_out).map_err(SKError::Io)?;
if output_presence {
dst_bit.unwrap().close().map_err(SKError::Io)?;
} else {
dst_int.unwrap().close().map_err(SKError::Io)?;
}
// In-place: swap old data dir for new.
if in_place {
src/obilayeredmap/src/layer.rs
+1 -5
View File
@@ -106,11 +106,7 @@ impl Layer<()> {
let presence_dir = layer_dir.join(PRESENCE_DIR);
fs::create_dir_all(&presence_dir).map_err(OLMError::Io)?;
let mut mb = PersistentBitMatrixBuilder::new(n_kmers, &presence_dir).map_err(OLMError::Io)?;
let mut col = mb.add_col().map_err(OLMError::Io)?;
for slot in 0..n_kmers {
col.set(slot, true);
}
col.close().map_err(OLMError::Io)?;
mb.add_col_ones().map_err(OLMError::Io)?.close().map_err(OLMError::Io)?;
mb.close().map_err(OLMError::Io)
}
}
src/obitaxonomy/Cargo.toml
+6
View File
@@ -0,0 +1,6 @@
[package]
name = "obitaxonomy"
version = "0.1.0"
edition = "2024"
[dependencies]
src/obitaxonomy/src/error.rs
+38
View File
@@ -0,0 +1,38 @@
use std::fmt;
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum TaxError {
/// Stored value does not start with the `taxonomy:/` prefix.
MissingPrefix,
/// Stored path contains no segments after the prefix.
EmptyPath,
/// Query pattern contains no segments (after stripping anchors).
EmptyPattern,
/// A segment has an empty name (e.g. consecutive `/`).
EmptySegmentName,
/// A segment has a trailing `@` with no rank name.
EmptyRankName { segment: String },
/// A segment contains more than one `@`.
AmbiguousRank { segment: String },
}
impl fmt::Display for TaxError {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match self {
TaxError::MissingPrefix =>
write!(f, "taxonomy path must start with \"taxonomy:/\""),
TaxError::EmptyPath =>
write!(f, "taxonomy path has no segments"),
TaxError::EmptyPattern =>
write!(f, "taxonomy query pattern has no segments"),
TaxError::EmptySegmentName =>
write!(f, "segment has an empty name"),
TaxError::EmptyRankName { segment } =>
write!(f, "segment has '@' with no rank name: {segment:?}"),
TaxError::AmbiguousRank { segment } =>
write!(f, "segment contains more than one '@': {segment:?}"),
}
}
}
impl std::error::Error for TaxError {}
src/obitaxonomy/src/lib.rs
+11
View File
@@ -0,0 +1,11 @@
mod error;
mod segment;
mod segment_pattern;
mod path;
mod pattern;
pub use error::TaxError;
pub use segment::TaxSegment;
pub use segment_pattern::SegmentPattern;
pub use path::{TaxPath, PREFIX};
pub use pattern::TaxPattern;
src/obitaxonomy/src/path.rs
+82
View File
@@ -0,0 +1,82 @@
use std::fmt;
use std::str::FromStr;
use crate::error::TaxError;
use crate::segment::TaxSegment;
/// The prefix that marks a metadata value as a taxonomy path.
pub const PREFIX: &str = "taxonomy:/";
/// A rooted, `/`-separated taxonomy path with optional per-segment rank annotations.
///
/// Stored form: `taxonomy:/seg1@rank1/seg2/seg3@rank3`
/// The leading `taxonomy:/` is the discriminator; the remainder is one or more
/// `/`-separated segments, each of the form `name` or `name@rank`.
///
/// `@` is reserved and may not appear in segment names or rank names.
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct TaxPath {
segments: Vec<TaxSegment>,
}
impl TaxPath {
pub fn parse(s: &str) -> Result<Self, TaxError> {
let tail = s.strip_prefix(PREFIX).ok_or(TaxError::MissingPrefix)?;
if tail.is_empty() {
return Err(TaxError::EmptyPath);
}
let segments = tail.split('/')
.map(TaxSegment::parse)
.collect::<Result<Vec<_>, _>>()?;
Ok(Self { segments })
}
/// True if `self` is an ancestor of — or equal to — `other`.
///
/// Comparison is by segment name only; rank annotations are ignored.
/// `self` must be a prefix of `other` at segment granularity.
pub fn is_ancestor_of(&self, other: &TaxPath) -> bool {
self.segments.len() <= other.segments.len()
&& self.segments.iter().zip(other.segments.iter())
.all(|(a, b)| a.name() == b.name())
}
/// Returns the name of the first segment whose rank equals `rank`, if any.
pub fn name_at_rank(&self, rank: &str) -> Option<&str> {
self.segments.iter()
.find(|s| s.rank() == Some(rank))
.map(|s| s.name())
}
/// True if any segment has the given rank.
pub fn has_rank(&self, rank: &str) -> bool {
self.segments.iter().any(|s| s.rank() == Some(rank))
}
/// True if the path contains a segment with both the given rank and name.
pub fn matches_rank(&self, rank: &str, name: &str) -> bool {
self.segments.iter().any(|s| s.rank() == Some(rank) && s.name() == name)
}
pub fn segments(&self) -> &[TaxSegment] { &self.segments }
pub fn depth(&self) -> usize { self.segments.len() }
pub fn is_empty(&self) -> bool { self.segments.is_empty() }
}
impl fmt::Display for TaxPath {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "{}", PREFIX)?;
let mut first = true;
for seg in &self.segments {
if !first { write!(f, "/")?; }
write!(f, "{seg}")?;
first = false;
}
Ok(())
}
}
impl FromStr for TaxPath {
type Err = TaxError;
fn from_str(s: &str) -> Result<Self, Self::Err> { Self::parse(s) }
}
src/obitaxonomy/src/pattern.rs
+72
View File
@@ -0,0 +1,72 @@
use crate::error::TaxError;
use crate::path::TaxPath;
use crate::segment::TaxSegment;
use crate::segment_pattern::SegmentPattern;
/// A query pattern for matching against stored `TaxPath` values.
///
/// Syntax:
///
/// | Form | Semantics |
/// |----------|-----------|
/// | `A/B` | A then B as a contiguous sub-path, anywhere in the value |
/// | `/A/B` | value starts with A then B (start-anchored) |
/// | `A/B$` | value ends with A then B (end-anchored) |
/// | `/A/B$` | value is exactly A then B (fully anchored) |
/// | `A@x/B` | A with rank `x`, followed by B with any rank |
///
/// A segment pattern without `@` matches any segment with that name regardless
/// of its stored rank.
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct TaxPattern {
start_anchored: bool,
end_anchored: bool,
segments: Vec<SegmentPattern>,
}
impl TaxPattern {
pub fn parse(s: &str) -> Result<Self, TaxError> {
let s = s.trim();
let start_anchored = s.starts_with('/');
let s = if start_anchored { &s[1..] } else { s };
let end_anchored = s.ends_with('$');
let s = if end_anchored { &s[..s.len() - 1] } else { s };
if s.is_empty() {
return Err(TaxError::EmptyPattern);
}
let segments = s.split('/')
.map(SegmentPattern::parse)
.collect::<Result<Vec<_>, _>>()?;
Ok(Self { start_anchored, end_anchored, segments })
}
/// True if this pattern matches `path` according to the anchor flags.
///
/// The pattern must match a contiguous run of segments in the path.
/// Start/end anchors restrict where that run may begin or end.
pub fn matches(&self, path: &TaxPath) -> bool {
let n = self.segments.len();
let m = path.depth();
if n > m { return false; }
let segs = path.segments();
match (self.start_anchored, self.end_anchored) {
(true, true) => n == m && self.window_matches(segs, 0),
(true, false) => self.window_matches(segs, 0),
(false, true) => self.window_matches(segs, m - n),
(false, false) => (0..=(m - n)).any(|i| self.window_matches(segs, i)),
}
}
fn window_matches(&self, segs: &[TaxSegment], start: usize) -> bool {
self.segments.iter()
.zip(segs[start..start + self.segments.len()].iter())
.all(|(pat, seg)| pat.matches(seg))
}
}
src/obitaxonomy/src/segment.rs
+49
View File
@@ -0,0 +1,49 @@
use std::fmt;
use crate::error::TaxError;
/// A single node in a taxonomy path: a name and an optional rank.
///
/// Neither `name` nor `rank` may contain `@` (reserved separator).
/// Serialised form: `name` or `name@rank`.
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct TaxSegment {
name: String,
rank: Option<String>,
}
impl TaxSegment {
pub fn parse(raw: &str) -> Result<Self, TaxError> {
let parts: Vec<&str> = raw.splitn(3, '@').collect();
let (name_raw, rank_raw) = match parts.as_slice() {
[name] => (*name, None),
[name, rank] => (*name, Some(*rank)),
_ => return Err(TaxError::AmbiguousRank { segment: raw.to_string() }),
};
if name_raw.is_empty() {
return Err(TaxError::EmptySegmentName);
}
let rank = match rank_raw {
None => None,
Some("") => return Err(TaxError::EmptyRankName { segment: raw.to_string() }),
Some(r) => Some(r.to_string()),
};
Ok(Self { name: name_raw.to_string(), rank })
}
pub fn name(&self) -> &str { &self.name }
pub fn rank(&self) -> Option<&str> { self.rank.as_deref() }
}
impl fmt::Display for TaxSegment {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &self.rank {
None => write!(f, "{}", self.name),
Some(r) => write!(f, "{}@{}", self.name, r),
}
}
}
src/obitaxonomy/src/segment_pattern.rs
+41
View File
@@ -0,0 +1,41 @@
use crate::error::TaxError;
use crate::segment::TaxSegment;
/// A single segment in a query pattern: a required name and an optional rank filter.
///
/// If `rank` is `None`, the pattern matches any segment with the given name,
/// regardless of its stored rank. If `rank` is `Some(r)`, both name and rank
/// must match exactly.
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct SegmentPattern {
name: String,
rank: Option<String>,
}
impl SegmentPattern {
pub fn parse(raw: &str) -> Result<Self, TaxError> {
let parts: Vec<&str> = raw.splitn(3, '@').collect();
let (name_raw, rank_raw) = match parts.as_slice() {
[name] => (*name, None),
[name, rank] => (*name, Some(*rank)),
_ => return Err(TaxError::AmbiguousRank { segment: raw.to_string() }),
};
if name_raw.is_empty() {
return Err(TaxError::EmptySegmentName);
}
let rank = match rank_raw {
None => None,
Some("") => return Err(TaxError::EmptyRankName { segment: raw.to_string() }),
Some(r) => Some(r.to_string()),
};
Ok(Self { name: name_raw.to_string(), rank })
}
/// True if this pattern matches `seg`.
/// Name must match exactly. If a rank is specified in the pattern, the
/// segment's rank must match; otherwise any rank (or no rank) is accepted.
pub fn matches(&self, seg: &TaxSegment) -> bool {
self.name == seg.name()
&& self.rank.as_deref().map_or(true, |r| seg.rank() == Some(r))
}
}
test.sk.fasta
-28
View File
@@ -1,28 +0,0 @@
>F1FE4776BF3E1F06 {"seq_length":51,"kmer_size":31,"minimizer_size":11,"partition":229,"minimizer":"AAAAAAAATTA"}
GAGTATACTCATGTGAGGGTAAAAAAAATTAAGTCCCATATTGAAACATTA
>C14BF81526DD6CB7 {"seq_length":31,"kmer_size":31,"minimizer_size":11,"partition":84,"minimizer":"AAAAAAATTAA"}
AAAAAAATTAAGTCCCATATTGAAACATTAT
>9156D79605E4AC23 {"seq_length":31,"kmer_size":31,"minimizer_size":11,"partition":87,"minimizer":"AAAAAATTAAG"}
AAAAAATTAAGTCCCATATTGAAACATTATC
>74666D1D78812D1E {"seq_length":31,"kmer_size":31,"minimizer_size":11,"partition":118,"minimizer":"AAAAATTAAGT"}
AAAAATTAAGTCCCATATTGAAACATTATCA
>45EEFC3520FBDA9A {"seq_length":31,"kmer_size":31,"minimizer_size":11,"partition":32,"minimizer":"AAAATTAAGTC"}
AAAATTAAGTCCCATATTGAAACATTATCAC
>5F44864B90170AF4 {"seq_length":49,"kmer_size":31,"minimizer_size":11,"partition":137,"minimizer":"AAACATTATCA"}
AAATTAAGTCCCATATTGAAACATTATCACAAATGTGAGTTGTTAATAT
>8D10A11C86F8EF26 {"seq_length":42,"kmer_size":31,"minimizer_size":11,"partition":26,"minimizer":"AAATGTGAGTT"}
AACATTATCACAAATGTGAGTTGTTAATATTACATAATTGGG
>C18F1086D0AF6E34 {"seq_length":32,"kmer_size":31,"minimizer_size":11,"partition":9,"minimizer":"TGTGAGTTGTT"}
AATGTGAGTTGTTAATATTACATAATTGGGTT
>933477394DAF03BB {"seq_length":31,"kmer_size":31,"minimizer_size":11,"partition":48,"minimizer":"TAATTGGGTTT"}
TGTGAGTTGTTAATATTACATAATTGGGTTT
>3CEE7E5227956042 {"seq_length":36,"kmer_size":31,"minimizer_size":11,"partition":252,"minimizer":"AATTGGGTTTT"}
GTGAGTTGTTAATATTACATAATTGGGTTTTATGCT
>1BAF5B8767D63D0B {"seq_length":33,"kmer_size":31,"minimizer_size":11,"partition":201,"minimizer":"AAAGGCTCCCT"}
TGAAAGGCTCCCTAGCGTGTTAATTAATCTCCC
>8368A897DB263C6F {"seq_length":38,"kmer_size":31,"minimizer_size":11,"partition":22,"minimizer":"CCTAGCGTGTT"}
AAGGCTCCCTAGCGTGTTAATTAATCTCCCTGACAAGT
>247DC82E11CF8055 {"seq_length":35,"kmer_size":31,"minimizer_size":11,"partition":128,"minimizer":"AATCTCCCTGA"}
CTAGCGTGTTAATTAATCTCCCTGACAAGTAGTGT
>11C93BBC8A5F6327 {"seq_length":35,"kmer_size":31,"minimizer_size":11,"partition":62,"minimizer":"CAAGTAGTGTT"}
GTGTTAATTAATCTCCCTGACAAGTAGTGTTAGTG