From 39c2a7e4b6da99462c79909ed2a17bbfda465fef Mon Sep 17 00:00:00 2001 From: Adam Gayoso Date: Fri, 3 Feb 2023 09:46:27 -0800 Subject: [PATCH] custom near neigh algorithms in benchmarker (#78) * custom near neigh * fix * fix * make jax array * update tutorial * Add changelog * bump version --- .bumpversion.cfg | 2 +- .pre-commit-config.yaml | 28 +++ CHANGELOG.md | 4 + docs/api.md | 14 ++ docs/notebooks/large_scale.ipynb | 163 +++++++++++++----- docs/notebooks/lung_example.ipynb | 17 +- pyproject.toml | 7 +- src/scib_metrics/__init__.py | 3 +- src/scib_metrics/benchmark/_core.py | 42 +++-- .../nearest_neighbors/__init__.py | 9 + .../nearest_neighbors/_dataclass.py | 19 ++ src/scib_metrics/nearest_neighbors/_jax.py | 50 ++++++ .../nearest_neighbors/_pynndescent.py | 40 +++++ tests/test_benchmarker.py | 11 ++ tests/test_neighbors.py | 8 + 15 files changed, 340 insertions(+), 77 deletions(-) create mode 100644 src/scib_metrics/nearest_neighbors/__init__.py create mode 100644 src/scib_metrics/nearest_neighbors/_dataclass.py create mode 100644 src/scib_metrics/nearest_neighbors/_jax.py create mode 100644 src/scib_metrics/nearest_neighbors/_pynndescent.py create mode 100644 tests/test_neighbors.py diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 2184dbf..475d14b 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 0.1.1 +current_version = 0.2.0 tag = True commit = True diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 526e760..550e0d0 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -77,3 +77,31 @@ repos: Fix the merge conflicts manually and remove the .rej files. language: fail files: '.*\.rej$' + - repo: https://github.com/nbQA-dev/nbQA + rev: 1.6.1 + hooks: + - id: nbqa-pyupgrade + args: [--py38-plus] + - id: nbqa-black + - id: nbqa-isort + - id: nbqa-ruff + args: [--fix] + - id: nbqa + entry: nbqa blacken-docs + name: nbqa-blacken-docs + alias: nbqa-blacken-docs + additional_dependencies: [blacken-docs] + args: [--nbqa-md] + - id: nbqa + entry: nbqa mdformat + name: nbqa-mdformat + alias: nbqa-mdformat + additional_dependencies: + [ + mdformat, + mdformat-black, + mdformat-frontmatter, + mdformat-web, + mdformat-myst, + ] + args: [--nbqa-md] diff --git a/CHANGELOG.md b/CHANGELOG.md index 902ab28..f7696eb 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,6 +8,10 @@ and this project adheres to [Semantic Versioning][]. [keep a changelog]: https://keepachangelog.com/en/1.0.0/ [semantic versioning]: https://semver.org/spec/v2.0.0.html +## 0.2.0 (2022-02-02) + +- Allow custom nearest neighbors methods in Benchmarker ([#78][]) + ## 0.1.1 (2022-01-04) - Add new tutorial and fix scalability of lisi ([#71][]) diff --git a/docs/api.md b/docs/api.md index 6eae473..055fd88 100644 --- a/docs/api.md +++ b/docs/api.md @@ -71,6 +71,20 @@ scib_metrics.ilisi_knn(...) utils.diffusion_nn ``` +### Nearest neighbors + +```{eval-rst} +.. module:: scib_metrics.nearest_neighbors +.. currentmodule:: scib_metrics + +.. autosummary:: + :toctree: generated + + nearest_neighbors.pynndescent + nearest_neighbors.jax_approx_min_k + nearest_neighbors.NeighborsOutput +``` + ## Settings An instance of the {class}`~scib_metrics._settings.ScibConfig` is available as `scib_metrics.settings` and allows configuring scib_metrics. diff --git a/docs/notebooks/large_scale.ipynb b/docs/notebooks/large_scale.ipynb index 133ba26..29085e0 100644 --- a/docs/notebooks/large_scale.ipynb +++ b/docs/notebooks/large_scale.ipynb @@ -24,15 +24,22 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:lightning_fabric.utilities.seed:Global seed set to 0\n" + ] + } + ], "source": [ "import numpy as np\n", - "from anndata import AnnData\n", - "import matplotlib.pyplot as plt\n", "import scanpy as sc\n", - "from plottable import Table\n", + "from scvi.data import cellxgene\n", "\n", "from scib_metrics.benchmark import Benchmarker, BioConservation\n", + "\n", "%matplotlib inline" ] }, @@ -48,13 +55,18 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[34mINFO \u001b[0m File data/luca.h5ad already downloaded \n" + ] + } + ], "source": [ - "url = \"https://corpora-data-prod.s3.amazonaws.com/675354ab-8670-4e14-8503-fd57f2bccf63/local.h5ad?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIATLYQ5N5XQZTWN5WV%2F20230103%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20230103T191153Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEJD%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLXdlc3QtMiJHMEUCIQDCvhrZo9ArL5Ydq8ns%2Fy%2FFyD5iOm2A49mtm3UNhEqBAwIgaMEiDAZRIbgTCGdwca4J2C4wWSriyw59wlilsc3b29cq9AMI2f%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FARABGgwyMzE0MjY4NDY1NzUiDACXIEO5c4ctBJIQkSrIAxhrU87kxFa6RzD84SV6M8AyC1rfT9t7m3ygAPsu0ZUQ4IZdrwthcp6ZpwCc%2B7%2Fp6O9iboEKUP%2B723BqbeoGR6xit3xIqqRJrKxHoU5miYBbINFl%2Ft7C67q58SRN4Y6o3w5DePwQVjEg0FoA4R3%2FFqz8NSo7raQVIKRfxsEI7JdljWBFvEdzNBHhGnsM68mFYT8XbpmwT0gvq37JGhZMrKI1Lex9j1RRmXaE1c30K%2FN5mFaS0VBgp049pI1Wg0OM6lzY0IVQsE9Le%2FMrSJOA4eygEf7eJsDTijMvoW5IFREYJ9OECMxhs8y1FKk27ObCbKVkTWRNjN8uQx880f50VNMnY34kgChr2ZJHCKVYfrsyyEgUX5QhOjWJW2ETRBrPw5jkZAH2fCiKb%2FQMuzbJMUbjqkX1YP%2FH2XCBsmtNVeicoqpZ8CIs%2Fe1pJrxlamggThXL80EqzkFJwgbQe94hQVcvuF0PILoV7y3toaprbKUY0M7X2YAhJstDva0QXgkghOkfXqeadvRdOZnl26Tmrzwk1tRAvkhCBjhuwTCKGV26bM56%2F%2Fz09f76JOoX7THONzyvslGDK2RUkOB5KWZi9kUoh5Wv4jV%2FszDxotGdBjqlAeZ1qQFzabGDc8nq2Sl7QCbMqvVBkoqJmqMlkezHVTB7F1Ym2g7ixiJHWeTLu%2BRuuXc0R4QiAMb%2FGpjzEKg8n273%2B15kY4zivRJTwHT9HHKEVzNYcXKMK6EzxJdNlc2bHTdrEnEMAEwNQuAaLeJvn1dQ%2BD%2Fr44KDZFuLz%2FGKf%2FLuMj0hfRPN4PsbsHI%2BXCRe149XE0mWF%2FpfHreJtvO9obZujGLVPg%3D%3D&X-Amz-Signature=d11fa2ca2c37d763b87ad5bd4481025dedd0d3f747c5ecfc5fda039194e1c830\"\n", - "adata = sc.read(\n", - " \"data/luca.h5ad\",\n", - " backup_url=url,\n", - ")" + "url = \"https://cellxgene.cziscience.com/e/232f6a5a-a04c-4758-a6e8-88ab2e3a6e69.cxg/\"\n", + "adata = cellxgene(url, filename=\"luca.h5ad\", save_path=\"data/\")" ] }, { @@ -110,7 +122,6 @@ "metadata": {}, "outputs": [], "source": [ - "import pandas as pd\n", "adata.var[\"highly_variable\"] = np.asarray(adata.var[\"is_highly_variable\"].astype(bool))\n", "sc.tl.pca(adata)" ] @@ -173,24 +184,86 @@ "## Perform the benchmark" ] }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we use a custom nearest neighbor function to speed up the computation of the metrics. This is not necessary, but can be useful for large datasets.\n", + "\n", + "In particular we use [faiss](https://github.com/facebookresearch/faiss), which can be accelerated with a GPU.\n", + "\n", + "This can be installed as\n", + "\n", + "```bash\n", + "conda install -c conda-forge faiss-gpu\n", + "```\n", + "\n", + "When using approximate nearest neighbors, an issue can arise where each cell does not get a unique set of K neighbors. This issue happens with faiss hnsw below, so we use the brute force method instead, which is still faster than pynndescent approximate nearest neighbors on CPU." + ] + }, { "cell_type": "code", "execution_count": 8, "metadata": {}, + "outputs": [], + "source": [ + "import faiss\n", + "\n", + "from scib_metrics.nearest_neighbors import NeighborsOutput\n", + "\n", + "\n", + "def faiss_hnsw_nn(X: np.ndarray, k: int):\n", + " \"\"\"Gpu HNSW nearest neighbor search using faiss.\n", + "\n", + " See https://github.com/nmslib/hnswlib/blob/master/ALGO_PARAMS.md\n", + " for index param details.\n", + " \"\"\"\n", + " X = np.ascontiguousarray(X, dtype=np.float32)\n", + " res = faiss.StandardGpuResources()\n", + " M = 32\n", + " index = faiss.IndexHNSWFlat(X.shape[1], M, faiss.METRIC_L2)\n", + " gpu_index = faiss.index_cpu_to_gpu(res, 0, index)\n", + " index.add(X)\n", + " distances, indices = index.search(X, k)\n", + " del index\n", + " del gpu_index\n", + " # distances are squared\n", + " return NeighborsOutput(indices=indices, distances=np.sqrt(distances))\n", + "\n", + "\n", + "def faiss_brute_force_nn(X: np.ndarray, k: int):\n", + " \"\"\"Gpu brute force nearest neighbor search using faiss.\"\"\"\n", + " X = np.ascontiguousarray(X, dtype=np.float32)\n", + " res = faiss.StandardGpuResources()\n", + " index = faiss.IndexFlatL2(X.shape[1])\n", + " gpu_index = faiss.index_cpu_to_gpu(res, 0, index)\n", + " index.add(X)\n", + " distances, indices = index.search(X, k)\n", + " del index\n", + " del gpu_index\n", + " # distances are squared\n", + " return NeighborsOutput(indices=indices, distances=np.sqrt(distances))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Computing neighbors: 100%|██████████| 3/3 [25:19<00:00, 506.60s/it]\n", - "Embeddings: 100%|\u001b[32m██████████\u001b[0m| 3/3 [40:26<00:00, 808.83s/it] \n" + "Computing neighbors: 100%|██████████| 3/3 [11:53<00:00, 237.87s/it]\n", + "Embeddings: 100%|\u001b[32m██████████\u001b[0m| 3/3 [35:49<00:00, 716.59s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Time: 65 min 46 sec\n" + "Time: 47 min 43 sec\n" ] } ], @@ -200,9 +273,7 @@ "adata.obsm[\"Unintegrated\"] = adata.obsm[\"X_pca\"]\n", "\n", "biocons = BioConservation(\n", - " isolated_labels=False,\n", - " nmi_ari_cluster_labels_leiden=False, \n", - " nmi_ari_cluster_labels_kmeans=False\n", + " isolated_labels=False, nmi_ari_cluster_labels_leiden=False, nmi_ari_cluster_labels_kmeans=False\n", ")\n", "\n", "start = time.time()\n", @@ -215,9 +286,10 @@ " bio_conservation_metrics=biocons,\n", " n_jobs=-1,\n", ")\n", + "bm.prepare(neighbor_computer=faiss_brute_force_nn)\n", "bm.benchmark()\n", "end = time.time()\n", - "print(f\"Time: {int((end - start) / 60)} min {int((end - start) % 60)} sec\")\n" + "print(f\"Time: {int((end - start) / 60)} min {int((end - start) % 60)} sec\")" ] }, { @@ -230,12 +302,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -246,10 +318,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -260,12 +332,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -276,10 +348,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -298,7 +370,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -313,23 +385,23 @@ "\n", " iLISI KBET Graph connectivity \\\n", "Embedding \n", - "Unintegrated 0.001673 0.340941 0.773022 \n", - "scANVI 0.008524 0.457425 0.984871 \n", - "scVI 0.007782 0.444799 0.981359 \n", + "Unintegrated 0.001673 0.337002 0.773025 \n", + "scANVI 0.008524 0.45895 0.984871 \n", + "scVI 0.007782 0.447049 0.981359 \n", "Metric Type Batch correction Batch correction Batch correction \n", "\n", " PCR comparison Batch correction Bio conservation \\\n", "Embedding \n", - "Unintegrated 0.0 0.396298 0.76553 \n", - "scANVI 0.436682 0.521797 0.797344 \n", - "scVI 0.414185 0.516113 0.794974 \n", + "Unintegrated 0.0 0.395511 0.76553 \n", + "scANVI 0.436682 0.522102 0.797344 \n", + "scVI 0.414185 0.516563 0.794974 \n", "Metric Type Batch correction Aggregate score Aggregate score \n", "\n", " Total \n", "Embedding \n", - "Unintegrated 0.617837 \n", - "scANVI 0.687125 \n", - "scVI 0.68343 \n", + "Unintegrated 0.617522 \n", + "scANVI 0.687247 \n", + "scVI 0.68361 \n", "Metric Type Aggregate score \n", "\n" ], @@ -343,23 +415,23 @@ "\n", " iLISI KBET Graph connectivity \\\n", "Embedding \n", - "Unintegrated \u001b[1;36m0.001673\u001b[0m \u001b[1;36m0.340941\u001b[0m \u001b[1;36m0.773022\u001b[0m \n", - "scANVI \u001b[1;36m0.008524\u001b[0m \u001b[1;36m0.457425\u001b[0m \u001b[1;36m0.984871\u001b[0m \n", - "scVI \u001b[1;36m0.007782\u001b[0m \u001b[1;36m0.444799\u001b[0m \u001b[1;36m0.981359\u001b[0m \n", + "Unintegrated \u001b[1;36m0.001673\u001b[0m \u001b[1;36m0.337002\u001b[0m \u001b[1;36m0.773025\u001b[0m \n", + "scANVI \u001b[1;36m0.008524\u001b[0m \u001b[1;36m0.45895\u001b[0m \u001b[1;36m0.984871\u001b[0m \n", + "scVI \u001b[1;36m0.007782\u001b[0m \u001b[1;36m0.447049\u001b[0m \u001b[1;36m0.981359\u001b[0m \n", "Metric Type Batch correction Batch correction Batch correction \n", "\n", " PCR comparison Batch correction Bio conservation \\\n", "Embedding \n", - "Unintegrated \u001b[1;36m0.0\u001b[0m \u001b[1;36m0.396298\u001b[0m \u001b[1;36m0.76553\u001b[0m \n", - "scANVI \u001b[1;36m0.436682\u001b[0m \u001b[1;36m0.521797\u001b[0m \u001b[1;36m0.797344\u001b[0m \n", - "scVI \u001b[1;36m0.414185\u001b[0m \u001b[1;36m0.516113\u001b[0m \u001b[1;36m0.794974\u001b[0m \n", + "Unintegrated \u001b[1;36m0.0\u001b[0m \u001b[1;36m0.395511\u001b[0m \u001b[1;36m0.76553\u001b[0m \n", + "scANVI \u001b[1;36m0.436682\u001b[0m \u001b[1;36m0.522102\u001b[0m \u001b[1;36m0.797344\u001b[0m \n", + "scVI \u001b[1;36m0.414185\u001b[0m \u001b[1;36m0.516563\u001b[0m \u001b[1;36m0.794974\u001b[0m \n", "Metric Type Batch correction Aggregate score Aggregate score \n", "\n", " Total \n", "Embedding \n", - "Unintegrated \u001b[1;36m0.617837\u001b[0m \n", - "scANVI \u001b[1;36m0.687125\u001b[0m \n", - "scVI \u001b[1;36m0.68343\u001b[0m \n", + "Unintegrated \u001b[1;36m0.617522\u001b[0m \n", + "scANVI \u001b[1;36m0.687247\u001b[0m \n", + "scVI \u001b[1;36m0.68361\u001b[0m \n", "Metric Type Aggregate score \n" ] }, @@ -369,6 +441,7 @@ ], "source": [ "from rich import print\n", + "\n", "df = bm.get_results(min_max_scale=False)\n", "print(df)" ] diff --git a/docs/notebooks/lung_example.ipynb b/docs/notebooks/lung_example.ipynb index 8b4145d..88e1312 100644 --- a/docs/notebooks/lung_example.ipynb +++ b/docs/notebooks/lung_example.ipynb @@ -23,12 +23,10 @@ "outputs": [], "source": [ "import numpy as np\n", - "from anndata import AnnData\n", - "import matplotlib.pyplot as plt\n", "import scanpy as sc\n", - "from plottable import Table\n", "\n", "from scib_metrics.benchmark import Benchmarker\n", + "\n", "%matplotlib inline" ] }, @@ -120,7 +118,7 @@ ], "source": [ "sc.pp.highly_variable_genes(adata, n_top_genes=2000, flavor=\"cell_ranger\", batch_key=\"batch\")\n", - "sc.tl.pca(adata, n_comps=30, use_highly_variable=True)\n" + "sc.tl.pca(adata, n_comps=30, use_highly_variable=True)" ] }, { @@ -177,6 +175,7 @@ "source": [ "%%capture\n", "import scanorama\n", + "\n", "# List of adata per batch\n", "batch_cats = adata.obs.batch.cat.categories\n", "adata_list = [adata[adata.obs.batch == b].copy() for b in batch_cats]\n", @@ -211,6 +210,7 @@ ], "source": [ "import pyliger\n", + "\n", "bdata = adata.copy()\n", "# Pyliger normalizes by library size with a size factor of 1\n", "# So here we give it the count data\n", @@ -220,7 +220,7 @@ "for i, ad in enumerate(adata_list):\n", " ad.uns[\"sample_name\"] = batch_cats[i]\n", " # Hack to make sure each method uses the same genes\n", - " ad.uns['var_gene_idx'] = np.arange(bdata.n_vars)\n", + " ad.uns[\"var_gene_idx\"] = np.arange(bdata.n_vars)\n", "\n", "\n", "liger_data = pyliger.create_liger(adata_list, remove_missing=False, make_sparse=False)\n", @@ -270,7 +270,8 @@ ], "source": [ "from harmony import harmonize\n", - "adata.obsm[\"Harmony\"] = harmonize(adata.obsm[\"X_pca\"], adata.obs, batch_key = \"batch\")" + "\n", + "adata.obsm[\"Harmony\"] = harmonize(adata.obsm[\"X_pca\"], adata.obs, batch_key=\"batch\")" ] }, { @@ -303,6 +304,7 @@ "source": [ "%%capture\n", "import scvi\n", + "\n", "scvi.model.SCVI.setup_anndata(adata, layer=\"counts\", batch_key=\"batch\")\n", "vae = scvi.model.SCVI(adata, gene_likelihood=\"nb\", n_layers=2, n_latent=30)\n", "vae.train()\n", @@ -389,7 +391,7 @@ " embedding_obsm_keys=[\"Unintegrated\", \"Scanorama\", \"LIGER\", \"Harmony\", \"scVI\", \"scANVI\"],\n", " n_jobs=6,\n", ")\n", - "bm.benchmark()\n" + "bm.benchmark()" ] }, { @@ -585,6 +587,7 @@ ], "source": [ "from rich import print\n", + "\n", "df = bm.get_results(min_max_scale=False)\n", "print(df)" ] diff --git a/pyproject.toml b/pyproject.toml index 6b89613..bd7e405 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,7 @@ requires = ["hatchling"] [project] name = "scib-metrics" -version = "0.1.1" +version = "0.2.0" description = "Accelerated and Python-only scIB metrics" readme = "README.md" requires-python = ">=3.8" @@ -99,6 +99,11 @@ multi_line_output = 3 profile = "black" skip_glob = ["docs/*"] +[tool.ruff] +line-length = 88 +exclude = [".git","__pycache__","build","docs/","_build","dist"] +ignore = ["E402","E501", "F821", "E741"] + [tool.black] line-length = 120 target-version = ['py38'] diff --git a/src/scib_metrics/__init__.py b/src/scib_metrics/__init__.py index e78620f..58bcace 100644 --- a/src/scib_metrics/__init__.py +++ b/src/scib_metrics/__init__.py @@ -1,7 +1,7 @@ import logging from importlib.metadata import version -from . import utils +from . import nearest_neighbors, utils from ._graph_connectivity import graph_connectivity from ._isolated_labels import isolated_labels from ._kbet import kbet, kbet_per_label @@ -13,6 +13,7 @@ __all__ = [ "utils", + "nearest_neighbors", "isolated_labels", "pcr_comparison", "silhouette_label", diff --git a/src/scib_metrics/benchmark/_core.py b/src/scib_metrics/benchmark/_core.py index 480fb19..3d6f493 100644 --- a/src/scib_metrics/benchmark/_core.py +++ b/src/scib_metrics/benchmark/_core.py @@ -3,7 +3,7 @@ from dataclasses import asdict, dataclass from enum import Enum from functools import partial -from typing import Any, Dict, List, Optional, Union +from typing import Any, Callable, Dict, List, Optional, Union import matplotlib import matplotlib.pyplot as plt @@ -14,11 +14,11 @@ from plottable import ColumnDefinition, Table from plottable.cmap import normed_cmap from plottable.plots import bar -from pynndescent import NNDescent from sklearn.preprocessing import MinMaxScaler from tqdm import tqdm import scib_metrics +from scib_metrics.nearest_neighbors import NeighborsOutput, pynndescent Kwargs = Dict[str, Any] MetricType = Union[bool, Kwargs] @@ -156,8 +156,17 @@ def __init__( "Batch correction": self._batch_correction_metrics, } - def prepare(self) -> None: - """Prepare the data for benchmarking.""" + def prepare(self, neighbor_computer: Optional[Callable[[np.ndarray, int], NeighborsOutput]] = None) -> None: + """Prepare the data for benchmarking. + + Parameters + ---------- + neighbor_computer + Function that computes the neighbors of the data. If `None`, the neighbors will be computed + with :func:`~scib_metrics.utils.nearest_neighbors.pynndescent`. The function should take as input + the data and the number of neighbors to compute and return a :class:`~scib_metrics.utils.nearest_neighbors.NeighborsOutput` + object. + """ # Compute PCA if self._pre_integrated_embedding_obsm_key is None: # This is how scib does it @@ -173,24 +182,13 @@ def prepare(self) -> None: # Compute neighbors for ad in tqdm(self._emb_adatas.values(), desc="Computing neighbors"): - # Variables from umap (https://github.com/lmcinnes/umap/blob/3f19ce19584de4cf99e3d0ae779ba13a57472cd9/umap/umap_.py#LL326-L327) - # which is used by scanpy under the hood - n_trees = min(64, 5 + int(round((ad.X.shape[0]) ** 0.5 / 20.0))) - n_iters = max(5, int(round(np.log2(ad.X.shape[0])))) - max_candidates = 60 - - knn_search_index = NNDescent( - ad.X, - n_neighbors=max(self._neighbor_values), - random_state=0, - low_memory=True, - n_jobs=self._n_jobs, - compressed=False, - n_trees=n_trees, - n_iters=n_iters, - max_candidates=max_candidates, - ) - indices, distances = knn_search_index.neighbor_graph + if neighbor_computer is not None: + neigh_output = neighbor_computer(ad.X, max(self._neighbor_values)) + else: + neigh_output = pynndescent( + ad.X, n_neighbors=max(self._neighbor_values), random_state=0, n_jobs=self._n_jobs + ) + indices, distances = neigh_output.indices, neigh_output.distances for n in self._neighbor_values: sp_distances, sp_conns = sc.neighbors._compute_connectivities_umap( indices[:, :n], distances[:, :n], ad.n_obs, n_neighbors=n diff --git a/src/scib_metrics/nearest_neighbors/__init__.py b/src/scib_metrics/nearest_neighbors/__init__.py new file mode 100644 index 0000000..9b0529c --- /dev/null +++ b/src/scib_metrics/nearest_neighbors/__init__.py @@ -0,0 +1,9 @@ +from ._dataclass import NeighborsOutput +from ._jax import jax_approx_min_k +from ._pynndescent import pynndescent + +__all__ = [ + "pynndescent", + "jax_approx_min_k", + "NeighborsOutput", +] diff --git a/src/scib_metrics/nearest_neighbors/_dataclass.py b/src/scib_metrics/nearest_neighbors/_dataclass.py new file mode 100644 index 0000000..0e1d986 --- /dev/null +++ b/src/scib_metrics/nearest_neighbors/_dataclass.py @@ -0,0 +1,19 @@ +from dataclasses import dataclass + +import numpy as np + + +@dataclass +class NeighborsOutput: + """Output of the nearest neighbors function. + + Attributes + ---------- + distances : np.ndarray + Array of distances to the nearest neighbors. + indices : np.ndarray + Array of indices of the nearest neighbors. + """ + + indices: np.ndarray + distances: np.ndarray diff --git a/src/scib_metrics/nearest_neighbors/_jax.py b/src/scib_metrics/nearest_neighbors/_jax.py new file mode 100644 index 0000000..16be73b --- /dev/null +++ b/src/scib_metrics/nearest_neighbors/_jax.py @@ -0,0 +1,50 @@ +import functools + +import jax +import jax.numpy as jnp +import numpy as np + +from scib_metrics.utils import cdist, get_ndarray + +from ._dataclass import NeighborsOutput + + +@functools.partial(jax.jit, static_argnames=["k", "recall_target"]) +def _euclidean_ann(qy: jnp.ndarray, db: jnp.ndarray, k: int, recall_target: float = 0.95): + """Compute half squared L2 distance between query points and database points.""" + dists = cdist(qy, db) + return jax.lax.approx_min_k(dists, k=k, recall_target=recall_target) + + +def jax_approx_min_k( + X: np.ndarray, n_neighbors: int, recall_target: float = 0.95, chunk_size: int = 2048 +) -> NeighborsOutput: + """Run approximate nearest neighbor search using jax. + + On TPU backends, this is approximate nearest neighbor search. On other backends, this is exact nearest neighbor search. + + Parameters + ---------- + X + Data matrix. + n_neighbors + Number of neighbors to search for. + recall_target + Target recall for approximate nearest neighbor search. + chunk_size + Number of query points to search for at once. + """ + db = jnp.asarray(X) + # Loop over query points in chunks + neighbors = [] + dists = [] + for i in range(0, db.shape[0], chunk_size): + start = i + end = min(i + chunk_size, db.shape[0]) + qy = db[start:end] + dist, neighbor = _euclidean_ann(qy, db, k=n_neighbors, recall_target=recall_target) + neighbors.append(neighbor) + dists.append(dist) + neighbors = jnp.concatenate(neighbors, axis=0) + dists = jnp.concatenate(dists, axis=0) + return NeighborsOutput(indices=get_ndarray(neighbors), distances=get_ndarray(dists)) diff --git a/src/scib_metrics/nearest_neighbors/_pynndescent.py b/src/scib_metrics/nearest_neighbors/_pynndescent.py new file mode 100644 index 0000000..7fb3ee6 --- /dev/null +++ b/src/scib_metrics/nearest_neighbors/_pynndescent.py @@ -0,0 +1,40 @@ +import numpy as np +from pynndescent import NNDescent + +from ._dataclass import NeighborsOutput + + +def pynndescent(X: np.ndarray, n_neighbors: int, random_state: int = 0, n_jobs: int = 1) -> NeighborsOutput: + """Run pynndescent approximate nearest neighbor search. + + Parameters + ---------- + X + Data matrix. + n_neighbors + Number of neighbors to search for. + random_state + Random state. + n_jobs + Number of jobs to use. + """ + # Variables from umap (https://github.com/lmcinnes/umap/blob/3f19ce19584de4cf99e3d0ae779ba13a57472cd9/umap/umap_.py#LL326-L327) + # which is used by scanpy under the hood + n_trees = min(64, 5 + int(round((X.shape[0]) ** 0.5 / 20.0))) + n_iters = max(5, int(round(np.log2(X.shape[0])))) + max_candidates = 60 + + knn_search_index = NNDescent( + X, + n_neighbors=n_neighbors, + random_state=random_state, + low_memory=True, + n_jobs=n_jobs, + compressed=False, + n_trees=n_trees, + n_iters=n_iters, + max_candidates=max_candidates, + ) + indices, distances = knn_search_index.neighbor_graph + + return NeighborsOutput(indices=indices, distances=distances) diff --git a/tests/test_benchmarker.py b/tests/test_benchmarker.py index f1fc105..0a73874 100644 --- a/tests/test_benchmarker.py +++ b/tests/test_benchmarker.py @@ -1,6 +1,7 @@ import pandas as pd from scib_metrics.benchmark import BatchCorrection, Benchmarker, BioConservation +from scib_metrics.nearest_neighbors import jax_approx_min_k from tests.utils.data import dummy_benchmarker_adata @@ -39,3 +40,13 @@ def test_benchmarker_custom_metric_callable(): bm.benchmark() results = bm.get_results(clean_names=False) assert "clisi_knn" in results.columns + + +def test_benchmarker_custom_near_neighs(): + ad, emb_keys, batch_key, labels_key = dummy_benchmarker_adata() + bm = Benchmarker(ad, batch_key, labels_key, emb_keys) + bm.prepare(neighbor_computer=jax_approx_min_k) + bm.benchmark() + results = bm.get_results() + assert isinstance(results, pd.DataFrame) + bm.plot_results_table() diff --git a/tests/test_neighbors.py b/tests/test_neighbors.py new file mode 100644 index 0000000..00e1c24 --- /dev/null +++ b/tests/test_neighbors.py @@ -0,0 +1,8 @@ +from scib_metrics.nearest_neighbors import jax_approx_min_k +from tests.utils.data import dummy_benchmarker_adata + + +def test_jax_neighbors(): + ad, emb_keys, _, _ = dummy_benchmarker_adata() + output = jax_approx_min_k(ad.obsm[emb_keys[0]], 10) + assert output.distances.shape == (ad.n_obs, 10)