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nwgrad

Differentiable sequence alignment. nwgrad runs Needleman–Wunsch (global) and Smith–Waterman (local) alignment and returns not just the score but its gradient with respect to the substitution matrix and the gap penalties — so alignment parameters can be learned by gradient descent, inside any ML pipeline.

score, grad = nwgrad.SeqPair("PLEASANTLY", "MEANLY", params).score_and_grad()
params = params + 0.01 * grad   # every matrix cell and all four gap costs move together

Why nwgrad

  • Gradients, not just scores. The hard gradient counts substitution pairs and gap positions along the optimal path (a subgradient of the Viterbi score). The soft gradient is the exact gradient of the log-partition function over all alignments, computed by forward–backward in log space. Matrix and gap fields share one sign convention, so a single update rule moves them all.
  • Fast. Striped SIMD kernels for SSE2, AVX2, AVX-512 and NEON ship in one binary and are chosen at runtime. Every one is bit-exact with the scalar reference: the instruction set is a speed knob, never a correctness one. Batches run on all cores; measured at 6.4 billion DP cells per second on a 16-thread laptop CPU (Intel i7-11850H, AVX-512, float32).
  • Linear memory for long sequences. Affine global alignment defaults to Hirschberg (Myers–Miller) traceback, which keeps O(m+n) state instead of O(m×n) tables: titin (35,991 residues) aligned against itself needs about 0.9 MB of DP memory per thread rather than 3.9 GB.
  • Built for training loops. Sequences are validated and encoded once and reused across steps. After a parameter update, banded re-alignment around the previous path costs O(length × bandwidth) instead of a full O(m × n) DP.
  • Any alphabet. Protein, DNA, RNA or your own symbol set; asymmetric matrices and asymmetric gap costs; BLOSUM, PAM, VTML and NUC44 included.
  • Python and C++. nanobind bindings with zero-copy numpy interop over a header-only C++20 core.

Installation

pip install nwgrad

Prebuilt wheels cover CPython 3.10–3.14 on Linux x86_64 / aarch64 and macOS arm64. Anywhere else pip builds from source, which needs a C++20 compiler with libstdc++'s <experimental/simd>: GCC 11+, or Clang 13+ built against libstdc++. Apple's system clang (libc++) and MSVC lack that header — on macOS use Homebrew gcc; Windows is not supported.

Quick start

import nwgrad
from nwgrad.matrices import BLOSUM62        # ready-made SubstMatrix, alphabet included

params = nwgrad.AlignParams(BLOSUM62,
                            gap_open_a=11.0, gap_extend_a=1.0,
                            gap_open_b=11.0, gap_extend_b=1.0)

sp = nwgrad.SeqPair("PLEASANTLY", "MEANLY", params,
                    gap_model="affine",     # or "linear"
                    mode="global",          # or "local"
                    grad_mode="hard")       # or "soft", or "none"

score, grad = sp.score_and_grad()
print(score)
print(sp.formatted())                       # the alignment, ready to read
g = grad.to_dict()                          # numpy matrix + the four gap fields
print(g["matrix"].shape, g["gap_open_a"], g["gap_extend_b"])

A gradient is itself an AlignParams, so params + lr * grad is a complete update step. Gap penalties are costs: a gap of length k costs gap_extend * k (linear) or gap_open + gap_extend * k (affine), matching BioPython; _a applies to gaps in sequence A, _b to gaps in sequence B.

Learning a substitution matrix

Any differentiable objective over alignment scores works. Here, a contrastive one: make a set of pairs you believe are homologous score higher than a set of decoys.

pos = nwgrad.SeqPairBatch()                 # all cores by default
neg = nwgrad.SeqPairBatch()
pos.add_many(homologs_a, homologs_b, params, grad_mode="soft")
neg.add_many(decoys_a, decoys_b, params, grad_mode="soft")

for step in range(100):
    margin = pos.score_and_grad() - neg.score_and_grad()     # sums of log Z
    grad = pos.compute_grad() - neg.compute_grad()            # d margin / d params
    params = params + 1e-3 * grad
    pos.set_params(params)
    neg.set_params(params)

add_many() builds the pairs in parallel C++ with no per-pair Python objects, so batches of millions of pairs are cheap to set up. Per-pair scores and gradients are available too (batch.scores(), batch.grads(), batch.weighted_grad(weights), batch[i]), for objectives that weight each pair differently.

Good to know

  • Precision. The plain names (SeqPair, SeqPairBatch, nw_score, …) run the DP in float32; SeqPairDouble, SeqPairBatchDouble, nw_score_double, … run it in float64. Inputs and outputs are float64 either way.
  • Many short pairs. For millions of short pairs (e.g. miRNA × target site), batch.fill = "interpair" aligns several pairs per vector instruction — about 6× the default "striped" fill per pair on AVX2 — with bit-identical results; see SeqPairBatch.fill.
  • Stateless one-offs. Twelve functions (nw_score, sw_affine_grad, nw_affine_soft_grad, …) align a single pair without keeping any state.
  • C++. python -m nwgrad --include prints the path to the header-only library.

Documentation

License

MIT — see LICENSE.

Metadata

Release files for nwgrad 0.5.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for nwgrad 0.5.2
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nwgrad-0.5.2.tar.gz 143.7 kB Details

Built distributions (wheels)

Table of built distributions (wheels) for nwgrad 0.5.2
File
nwgrad-0.5.2-cp315-cp315t-musllinux_1_2_x86_64.whl CPython 3.15 CPython 3.15 free-threading Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp315-cp315t-musllinux_1_2_aarch64.whl CPython 3.15 CPython 3.15 free-threading Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp315-cp315t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.15 CPython 3.15 free-threading Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp315-cp315t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.15 CPython 3.15 free-threading Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
nwgrad-0.5.2-cp315-cp315t-macosx_11_0_arm64.whl CPython 3.15 CPython 3.15 free-threading macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp315-cp315-musllinux_1_2_x86_64.whl CPython 3.15 CPython 3.15 Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp315-cp315-musllinux_1_2_aarch64.whl CPython 3.15 CPython 3.15 Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp315-cp315-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.15 CPython 3.15 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp315-cp315-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.15 CPython 3.15 Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
nwgrad-0.5.2-cp315-cp315-macosx_11_0_arm64.whl CPython 3.15 CPython 3.15 macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp314-cp314t-musllinux_1_2_x86_64.whl CPython 3.14 CPython 3.14 free-threading Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp314-cp314t-musllinux_1_2_aarch64.whl CPython 3.14 CPython 3.14 free-threading Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 free-threading Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp314-cp314t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.14 CPython 3.14 free-threading Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 Details
nwgrad-0.5.2-cp314-cp314t-macosx_11_0_arm64.whl CPython 3.14 CPython 3.14 free-threading macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp314-cp314-musllinux_1_2_x86_64.whl CPython 3.14 CPython 3.14 Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp314-cp314-musllinux_1_2_aarch64.whl CPython 3.14 CPython 3.14 Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp314-cp314-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.14 CPython 3.14 Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
nwgrad-0.5.2-cp314-cp314-macosx_11_0_arm64.whl CPython 3.14 CPython 3.14 macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp313-cp313-musllinux_1_2_x86_64.whl CPython 3.13 CPython 3.13 Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp313-cp313-musllinux_1_2_aarch64.whl CPython 3.13 CPython 3.13 Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp313-cp313-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 Details
nwgrad-0.5.2-cp313-cp313-macosx_11_0_arm64.whl CPython 3.13 CPython 3.13 macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp312-cp312-musllinux_1_2_x86_64.whl CPython 3.12 CPython 3.12 Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp312-cp312-musllinux_1_2_aarch64.whl CPython 3.12 CPython 3.12 Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 Details
nwgrad-0.5.2-cp312-cp312-macosx_11_0_arm64.whl CPython 3.12 CPython 3.12 macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp311-cp311-musllinux_1_2_x86_64.whl CPython 3.11 CPython 3.11 Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp311-cp311-musllinux_1_2_aarch64.whl CPython 3.11 CPython 3.11 Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.11 CPython 3.11 Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
nwgrad-0.5.2-cp311-cp311-macosx_11_0_arm64.whl CPython 3.11 CPython 3.11 macOS 11.0+ ARM64 Details
nwgrad-0.5.2-cp310-cp310-musllinux_1_2_x86_64.whl CPython 3.10 CPython 3.10 Linux musl 1.2+ x86-64 Details
nwgrad-0.5.2-cp310-cp310-musllinux_1_2_aarch64.whl CPython 3.10 CPython 3.10 Linux musl 1.2+ ARM64 Details
nwgrad-0.5.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
nwgrad-0.5.2-cp310-cp310-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.10 CPython 3.10 Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 Details
nwgrad-0.5.2-cp310-cp310-macosx_11_0_arm64.whl CPython 3.10 CPython 3.10 macOS 11.0+ ARM64 Details

Total release size: 38.6 MB

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This release

0.5.2 This release

41 release files

0.4.0

36 release files

0.3.0

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0.2.0

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