diff --git a/.github/workflows/_tests.yml b/.github/workflows/_tests.yml index b4ae8ebe..030732c8 100644 --- a/.github/workflows/_tests.yml +++ b/.github/workflows/_tests.yml @@ -8,10 +8,10 @@ jobs: strategy: matrix: os: [ubuntu-latest] - python-version: ["3.8", "3.9", "3.10", "3.11"] + python-version: ["3.8", "3.9", "3.10"] include: - os: macos-latest - python-version: "3.11" + python-version: "3.10" env: OS: ${{ matrix.os }} PYTHON: ${{ matrix.python-version }} diff --git a/.gitignore b/.gitignore index 5d5fecff..8a1296c4 100644 --- a/.gitignore +++ b/.gitignore @@ -140,3 +140,6 @@ requirements.txt # osmnx cache/ + +# pytorch lightning +lightning_logs/ diff --git a/CHANGELOG.md b/CHANGELOG.md index 11539272..bea84970 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,6 +8,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ### Added - GTFS Loader from gtfs2vec paper +- GTFS2Vec Model from gtfs2vec paper +- GTFS2Vec Embedder using gtfs2vec model - OSMTagLoader ### Changed diff --git a/examples/embedders/README.md b/examples/embedders/README.md new file mode 100644 index 00000000..be85ff88 --- /dev/null +++ b/examples/embedders/README.md @@ -0,0 +1,6 @@ +# Embedders + +Examples illustrating the usage of every Joiner. + +- [CountEmbedder](count_embedder.ipynb) +- [GTFS2VecEmbedder](gtfs2vec_embedder.ipynb) diff --git a/examples/embedders/gtfs2vec_embedder.ipynb b/examples/embedders/gtfs2vec_embedder.ipynb new file mode 100644 index 00000000..eb9fb865 --- /dev/null +++ b/examples/embedders/gtfs2vec_embedder.ipynb @@ -0,0 +1,166 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from srai.embedders import GTFS2VecEmbedder\n", + "import pandas as pd\n", + "from shapely.geometry import Polygon\n", + "import geopandas as gpd\n", + "from pytorch_lightning import seed_everything" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Example on artificial data" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define features and regions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "features_gdf = gpd.GeoDataFrame(\n", + " {\n", + " \"trip_count_at_6\": [1, 0, 0],\n", + " \"trip_count_at_7\": [1, 1, 0],\n", + " \"trip_count_at_8\": [0, 0, 1],\n", + " \"directions_at_6\": [\n", + " {\"A\", \"A1\"},\n", + " {\"B\", \"B1\"},\n", + " {\"C\"},\n", + " ],\n", + " },\n", + " geometry=gpd.points_from_xy([1, 2, 5], [1, 2, 2]),\n", + " index=[1, 2, 3],\n", + ")\n", + "features_gdf.index.name = \"stop_id\"\n", + "features_gdf" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "regions_gdf = gpd.GeoDataFrame(\n", + " {\n", + " \"region_id\": [\"ff1\", \"ff2\", \"ff3\"],\n", + " },\n", + " geometry=[\n", + " Polygon([(0, 0), (0, 3), (3, 3), (3, 0)]),\n", + " Polygon([(4, 0), (4, 3), (7, 3), (7, 0)]),\n", + " Polygon([(8, 0), (8, 3), (11, 3), (11, 0)]),\n", + " ],\n", + ").set_index(\"region_id\")\n", + "regions_gdf" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ax = regions_gdf.plot()\n", + "features_gdf.plot(ax=ax, color=\"red\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "joint_gdf = gpd.GeoDataFrame()\n", + "joint_gdf.index = pd.MultiIndex.from_tuples(\n", + " [(\"ff1\", 1), (\"ff1\", 2), (\"ff2\", 3)],\n", + " names=[\"region_id\", \"stop_id\"],\n", + ")\n", + "joint_gdf" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Get features without embedding them" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "embedder = GTFS2VecEmbedder(skip_autoencoder=True)\n", + "res = embedder.transform(regions_gdf, features_gdf, joint_gdf)\n", + "res" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Fit and train the embedder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "seed_everything(42)\n", + "embedder = GTFS2VecEmbedder(hidden_size=2, embedding_size=4)\n", + "embedder.fit(regions_gdf, features_gdf, joint_gdf)\n", + "res = embedder.transform(regions_gdf, features_gdf, joint_gdf)\n", + "res" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.14" + }, + "vscode": { + "interpreter": { + "hash": "f39c7279c85c8be5d827e53eddb5011e966102d239fe8b81ca4bd9f0123eda8f" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pdm.lock b/pdm.lock index 185e6683..54796be8 100644 --- a/pdm.lock +++ b/pdm.lock @@ -1,3 +1,30 @@ +# This file is @generated by PDM. +# It is not intended for manual editing. + +[[package]] +name = "aiohttp" +version = "3.8.4" +requires_python = ">=3.6" +summary = "Async http client/server framework (asyncio)" +dependencies = [ + "aiosignal>=1.1.2", + "async-timeout<5.0,>=4.0.0a3", + "attrs>=17.3.0", + "charset-normalizer<4.0,>=2.0", + "frozenlist>=1.1.1", + "multidict<7.0,>=4.5", + "yarl<2.0,>=1.0", +] + +[[package]] +name = "aiosignal" +version = "1.3.1" +requires_python = ">=3.7" +summary = "aiosignal: a list of registered asynchronous callbacks" +dependencies = [ + "frozenlist>=1.1.0", +] + [[package]] name = "anyio" version = "3.6.2" @@ -60,6 +87,12 @@ dependencies = [ "six", ] +[[package]] +name = "async-timeout" +version = "4.0.2" +requires_python = ">=3.6" +summary = "Timeout context manager for asyncio programs" + [[package]] name = "attrs" version = "21.4.0" @@ -404,6 +437,30 @@ version = "1.5.1" requires_python = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" summary = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" +[[package]] +name = "frozenlist" +version = "1.3.3" +requires_python = ">=3.7" +summary = "A list-like structure which implements collections.abc.MutableSequence" + +[[package]] +name = "fsspec" +version = "2023.1.0" +requires_python = ">=3.7" +summary = "File-system specification" + +[[package]] +name = "fsspec" +version = "2023.1.0" +extras = ["http"] +requires_python = ">=3.7" +summary = "File-system specification" +dependencies = [ + "aiohttp!=4.0.0a0,!=4.0.0a1", + "fsspec==2023.1.0", + "requests", +] + [[package]] name = "future" version = "0.18.3" @@ -443,7 +500,7 @@ dependencies = [ [[package]] name = "griffe" -version = "0.25.4" +version = "0.25.5" requires_python = ">=3.7" summary = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API." dependencies = [ @@ -501,7 +558,7 @@ dependencies = [ [[package]] name = "importlib-resources" -version = "5.10.2" +version = "5.12.0" requires_python = ">=3.7" summary = "Read resources from Python packages" dependencies = [ @@ -658,7 +715,7 @@ dependencies = [ [[package]] name = "jupyter-client" -version = "8.0.2" +version = "8.0.3" requires_python = ">=3.8" summary = "Jupyter protocol implementation and client libraries" dependencies = [ @@ -799,6 +856,16 @@ dependencies = [ "tomli<3,>=2.0.1", ] +[[package]] +name = "lightning-utilities" +version = "0.7.0" +requires_python = ">=3.7" +summary = "PyTorch Lightning Sample project." +dependencies = [ + "packaging>=17.1", + "typing-extensions", +] + [[package]] name = "lxml" version = "4.9.2" @@ -864,7 +931,7 @@ summary = "McCabe checker, plugin for flake8" [[package]] name = "mdit-py-plugins" -version = "0.3.3" +version = "0.3.4" requires_python = ">=3.7" summary = "Collection of plugins for markdown-it-py" dependencies = [ @@ -1033,6 +1100,12 @@ dependencies = [ "mkdocstrings==0.20.0", ] +[[package]] +name = "multidict" +version = "6.0.4" +requires_python = ">=3.7" +summary = "multidict implementation" + [[package]] name = "munch" version = "2.5.0" @@ -1066,7 +1139,7 @@ summary = "Simple yet flexible natural sorting in Python." [[package]] name = "nbclassic" -version = "0.5.1" +version = "0.5.2" requires_python = ">=3.7" summary = "Jupyter Notebook as a Jupyter Server extension." dependencies = [ @@ -1077,7 +1150,6 @@ dependencies = [ "jinja2", "jupyter-client>=6.1.1", "jupyter-core>=4.6.1", - "jupyter-server>=1.17.0", "jupyter-server>=1.8", "nbconvert>=5", "nbformat", @@ -1199,6 +1271,41 @@ version = "1.24.2" requires_python = ">=3.8" summary = "Fundamental package for array computing in Python" +[[package]] +name = "nvidia-cublas-cu11" +version = "11.10.3.66" +requires_python = ">=3" +summary = "CUBLAS native runtime libraries" +dependencies = [ + "setuptools", + "wheel", +] + +[[package]] +name = "nvidia-cuda-nvrtc-cu11" +version = "11.7.99" +requires_python = ">=3" +summary = "NVRTC native runtime libraries" + +[[package]] +name = "nvidia-cuda-runtime-cu11" +version = "11.7.99" +requires_python = ">=3" +summary = "CUDA Runtime native Libraries" +dependencies = [ + "setuptools", + "wheel", +] + +[[package]] +name = "nvidia-cudnn-cu11" +version = "8.5.0.96" +requires_python = ">=3" +summary = "cuDNN runtime libraries" +dependencies = [ + "nvidia-cublas-cu11", +] + [[package]] name = "osmium" version = "3.6.0" @@ -1225,6 +1332,21 @@ dependencies = [ "requests>=2.28", ] +[[package]] +name = "osmpythontools" +version = "0.3.5" +summary = "A library to access OpenStreetMap related services" +dependencies = [ + "beautifulsoup4", + "geojson", + "lxml", + "matplotlib", + "numpy", + "pandas", + "ujson", + "xarray", +] + [[package]] name = "overpass" version = "0.7" @@ -1347,8 +1469,8 @@ summary = "Python client for the Prometheus monitoring system." [[package]] name = "prompt-toolkit" -version = "3.0.36" -requires_python = ">=3.6.2" +version = "3.0.37" +requires_python = ">=3.7.0" summary = "Library for building powerful interactive command lines in Python" dependencies = [ "wcwidth", @@ -1538,10 +1660,27 @@ dependencies = [ [[package]] name = "python-json-logger" -version = "2.0.6" +version = "2.0.7" requires_python = ">=3.6" summary = "A python library adding a json log formatter" +[[package]] +name = "pytorch-lightning" +version = "1.9.3" +requires_python = ">=3.7" +summary = "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate." +dependencies = [ + "PyYAML>=5.4", + "fsspec[http]>2021.06.0", + "lightning-utilities>=0.6.0.post0", + "numpy>=1.17.2", + "packaging>=17.1", + "torch>=1.10.0", + "torchmetrics>=0.7.0", + "tqdm>=4.57.0", + "typing-extensions>=4.0.0", +] + [[package]] name = "pytz" version = "2022.7.1" @@ -1691,7 +1830,7 @@ summary = "Send file to trash natively under Mac OS X, Windows and Linux." [[package]] name = "setuptools" -version = "67.3.2" +version = "67.4.0" requires_python = ">=3.7" summary = "Easily download, build, install, upgrade, and uninstall Python packages" @@ -1802,6 +1941,31 @@ dependencies = [ "shapely", ] +[[package]] +name = "torch" +version = "1.13.1" +requires_python = ">=3.7.0" +summary = "Tensors and Dynamic neural networks in Python with strong GPU acceleration" +dependencies = [ + "nvidia-cublas-cu11==11.10.3.66; platform_system == \"Linux\"", + "nvidia-cuda-nvrtc-cu11==11.7.99; platform_system == \"Linux\"", + "nvidia-cuda-runtime-cu11==11.7.99; platform_system == \"Linux\"", + "nvidia-cudnn-cu11==8.5.0.96; platform_system == \"Linux\"", + "typing-extensions", +] + +[[package]] +name = "torchmetrics" +version = "0.11.1" +requires_python = ">=3.7" +summary = "PyTorch native Metrics" +dependencies = [ + "numpy>=1.17.2", + "packaging", + "torch>=1.8.1", + "typing-extensions; python_version < \"3.9\"", +] + [[package]] name = "tornado" version = "6.2" @@ -1810,7 +1974,7 @@ summary = "Tornado is a Python web framework and asynchronous networking library [[package]] name = "tox" -version = "4.4.5" +version = "4.4.6" requires_python = ">=3.7" summary = "tox is a generic virtualenv management and test command line tool" dependencies = [ @@ -1861,12 +2025,12 @@ dependencies = [ [[package]] name = "types-docutils" -version = "0.19.1.4" +version = "0.19.1.5" summary = "Typing stubs for docutils" [[package]] name = "types-setuptools" -version = "67.3.0.1" +version = "67.3.0.2" summary = "Typing stubs for setuptools" dependencies = [ "types-docutils", @@ -1878,6 +2042,12 @@ version = "4.5.0" requires_python = ">=3.7" summary = "Backported and Experimental Type Hints for Python 3.7+" +[[package]] +name = "ujson" +version = "5.7.0" +requires_python = ">=3.7" +summary = "Ultra fast JSON encoder and decoder for Python" + [[package]] name = "untokenize" version = "0.1.1" @@ -1967,17 +2137,131 @@ dependencies = [ "notebook>=4.4.1", ] +[[package]] 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'nvidia-cublas-cu11', # uses NVIDIA license + 'nvidia-cuda-nvrtc-cu11', # uses NVIDIA license ] diff --git a/srai/embedders/__init__.py b/srai/embedders/__init__.py index fd373493..c3c9c54d 100644 --- a/srai/embedders/__init__.py +++ b/srai/embedders/__init__.py @@ -2,5 +2,6 @@ from .base import BaseEmbedder from .count_embedder import CountEmbedder +from .gtfs2vec_embedder import GTFS2VecEmbedder -__all__ = ["BaseEmbedder", "CountEmbedder"] +__all__ = ["BaseEmbedder", "CountEmbedder", "GTFS2VecEmbedder"] diff --git a/srai/embedders/base.py b/srai/embedders/base.py index 96d6b24a..840719e1 100644 --- a/srai/embedders/base.py +++ b/srai/embedders/base.py @@ -3,20 +3,73 @@ import abc import geopandas as gpd +import pandas as pd class BaseEmbedder(abc.ABC): """Base abstract class for embedders.""" @abc.abstractmethod - def transform(self, gdf: gpd.GeoDataFrame) -> gpd.GeoDataFrame: # pragma: no cover + def transform( + self, + regions_gdf: gpd.GeoDataFrame, + features_gdf: gpd.GeoDataFrame, + joint_gdf: gpd.GeoDataFrame, + ) -> pd.DataFrame: # pragma: no cover """ - Embed a given GeoDataFrame. + Embed regions using features. Args: - gdf (gpd.GeoDataFrame): GeoDataFrame to be embedded. + regions_gdf (gpd.GeoDataFrame): Region indexes and geometries. + features_gdf (gpd.GeoDataFrame): Feature indexes, geometries and feature values. + joint_gdf (gpd.GeoDataFrame): Joiner result with region-feature multi-index. Returns: - np.ndarray with embedding for each row. + pd.DataFrame: Embedding and geometry index for each region in regions_gdf. + + Raises: + ValueError: If features_gdf is empty and self.expected_output_features is not set. + ValueError: If any of the gdfs index names is None. + ValueError: If joint_gdf.index is not of type pd.MultiIndex or doesn't have 2 levels. + ValueError: If index levels in gdfs don't overlap correctly. """ raise NotImplementedError + + def _validate_indexes( + self, + regions_gdf: gpd.GeoDataFrame, + features_gdf: gpd.GeoDataFrame, + joint_gdf: gpd.GeoDataFrame, + ) -> None: + if regions_gdf.index.name is None: + raise ValueError("regions_gdf must have a named index.") + + if features_gdf.index.name is None: + raise ValueError("features_gdf must have a named index.") + + if not isinstance(joint_gdf.index, pd.MultiIndex): + raise ValueError( + f"joint_gdf.index must be of type pandas.MultiIndex, not {type(joint_gdf.index)}" + ) + + if len(joint_gdf.index.names) != 2: + raise ValueError( + f"joint_gdf.index must have 2 levels, has {len(joint_gdf.index.names)}" + ) + + if regions_gdf.index.name != joint_gdf.index.names[0]: + raise ValueError( + f"Name of regions_gdf.index ({regions_gdf.index.name}) must be equal to the name of" + f" the 1st level of joint_gdf.index ({joint_gdf.index.names[0]})" + ) + + if features_gdf.index.name != joint_gdf.index.names[1]: + raise ValueError( + f"Name of features_gdf.index ({features_gdf.index.name}) must be equal to the name" + f" of the 2nd level of joint_gdf.index ({joint_gdf.index.names[1]})" + ) + + def _remove_geometry_if_present(self, data: gpd.GeoDataFrame) -> pd.DataFrame: + if "geometry" in data.columns: + data = data.drop(columns="geometry") + return pd.DataFrame(data) diff --git a/srai/embedders/count_embedder.py b/srai/embedders/count_embedder.py index 394d2eac..62ec9dbb 100644 --- a/srai/embedders/count_embedder.py +++ b/srai/embedders/count_embedder.py @@ -8,8 +8,10 @@ import geopandas as gpd import pandas as pd +from srai.embedders import BaseEmbedder -class CountEmbedder: + +class CountEmbedder(BaseEmbedder): """Simple Embedder that counts occurences of feature values.""" def __init__(self, expected_output_features: Optional[List[str]] = None) -> None: @@ -83,41 +85,6 @@ def transform( return region_embedding_df - def _validate_indexes( - self, - regions_gdf: gpd.GeoDataFrame, - features_gdf: gpd.GeoDataFrame, - joint_gdf: gpd.GeoDataFrame, - ) -> None: - if regions_gdf.index.name is None: - raise ValueError("regions_gdf must have a named index.") - - if features_gdf.index.name is None: - raise ValueError("features_gdf must have a named index.") - - if not isinstance(joint_gdf.index, pd.MultiIndex): - raise ValueError( - f"joint_gdf.index must be of type pandas.MultiIndex, not {type(joint_gdf.index)}" - ) - - print(joint_gdf.index.names) - if len(joint_gdf.index.names) != 2: - raise ValueError( - f"joint_gdf.index must have 2 levels, has {len(joint_gdf.index.names)}" - ) - - if regions_gdf.index.name != joint_gdf.index.names[0]: - raise ValueError( - f"Name of regions_gdf.index ({regions_gdf.index.name}) must be equal to the name of" - f" the 1st level of joint_gdf.index ({joint_gdf.index.names[0]})" - ) - - if features_gdf.index.name != joint_gdf.index.names[1]: - raise ValueError( - f"Name of features_gdf.index ({features_gdf.index.name}) must be equal to the name" - f" of the 2nd level of joint_gdf.index ({joint_gdf.index.names[1]})" - ) - def _filter_to_expected_features(self, region_embeddings: pd.DataFrame) -> pd.DataFrame: """ Add missing and remove excessive columns from embeddings. @@ -134,8 +101,3 @@ def _filter_to_expected_features(self, region_embeddings: pd.DataFrame) -> pd.Da region_embeddings[missing_features] = 0 region_embeddings = region_embeddings[self.expected_output_features] return region_embeddings - - def _remove_geometry_if_present(self, data: gpd.GeoDataFrame) -> pd.DataFrame: - if "geometry" in data.columns: - data = data.drop(columns="geometry") - return pd.DataFrame(data) diff --git a/srai/embedders/gtfs2vec_embedder.py b/srai/embedders/gtfs2vec_embedder.py new file mode 100644 index 00000000..1b50cee9 --- /dev/null +++ b/srai/embedders/gtfs2vec_embedder.py @@ -0,0 +1,267 @@ +""" +gtfs2vec embedder. + +This module contains embedder from gtfs2vec paper [1]. + +References: + [1] https://doi.org/10.1145/3486640.3491392 +""" + + +from functools import reduce +from typing import Any, Dict, List, Optional + +import geopandas as gpd +import numpy as np +import pandas as pd +import pytorch_lightning as pl +import torch +from torch.utils.data import DataLoader + +from srai.embedders import BaseEmbedder +from srai.loaders.gtfs_loader import GTFS2VEC_DIRECTIONS_PREFIX, GTFS2VEC_TRIPS_PREFIX +from srai.models import GTFS2VecModel +from srai.utils.exceptions import ModelNotFitException + + +class GTFS2VecEmbedder(BaseEmbedder): + """GTFS2Vec Embedder.""" + + def __init__( + self, hidden_size: int = 48, embedding_size: int = 64, skip_autoencoder: bool = False + ) -> None: + """ + Init GTFS2VecEmbedder. + + Args: + hidden_size (int, optional): Hidden size in encoder and decoder. Defaults to 48. + embedding_size (int, optional): Embedding size. Defaults to 64. + skip_autoencoder (bool, optional): Skip using autoencoder as part of embedding. + Defaults to False. + """ + self._model: Optional[GTFS2VecModel] = None + self._hidden_size = hidden_size + self._embedding_size = embedding_size + self._skip_autoencoder = skip_autoencoder + + def transform( + self, + regions_gdf: gpd.GeoDataFrame, + features_gdf: gpd.GeoDataFrame, + joint_gdf: gpd.GeoDataFrame, + ) -> pd.DataFrame: + """ + Embed a given data. + + Args: + regions_gdf (gpd.GeoDataFrame): Region indexes and geometries. + features_gdf (gpd.GeoDataFrame): Feature indexes, geometries and feature values. + joint_gdf (gpd.GeoDataFrame): Joiner result with region-feature multi-index. + + Returns: + pd.DataFrame: Embedding and geometry index for each region in regions_gdf. + + Raises: + ValueError: If any of the gdfs index names is None. + ValueError: If joint_gdf.index is not of type pd.MultiIndex or doesn't have 2 levels. + ValueError: If index levels in gdfs don't overlap correctly. + ValueError: If number of features is incosistent with the model. + ModelNotFitException: If model is not fit. + """ + self._validate_indexes(regions_gdf, features_gdf, joint_gdf) + features = self._prepare_features(regions_gdf, features_gdf, joint_gdf) + + if self._skip_autoencoder: + return features + return self._embed(features) + + def fit( + self, + regions_gdf: gpd.GeoDataFrame, + features_gdf: gpd.GeoDataFrame, + joint_gdf: gpd.GeoDataFrame, + ) -> None: + """ + Fit model to a given data. + + Args: + regions_gdf (gpd.GeoDataFrame): Region indexes and geometries. + features_gdf (gpd.GeoDataFrame): Feature indexes, geometries and feature values. + joint_gdf (gpd.GeoDataFrame): Joiner result with region-feature multi-index. + + Raises: + ValueError: If any of the gdfs index names is None. + ValueError: If joint_gdf.index is not of type pd.MultiIndex or doesn't have 2 levels. + ValueError: If index levels in gdfs don't overlap correctly. + """ + self._validate_indexes(regions_gdf, features_gdf, joint_gdf) + features = self._prepare_features(regions_gdf, features_gdf, joint_gdf) + + if not self._skip_autoencoder: + self._model = self._train_model_unsupervised(features) + + def fit_transform( + self, + regions_gdf: gpd.GeoDataFrame, + features_gdf: gpd.GeoDataFrame, + joint_gdf: gpd.GeoDataFrame, + ) -> pd.DataFrame: + """ + Fit model and transform a given data. + + Args: + regions_gdf (gpd.GeoDataFrame): Region indexes and geometries. + features_gdf (gpd.GeoDataFrame): Feature indexes, geometries and feature values. + joint_gdf (gpd.GeoDataFrame): Joiner result with region-feature multi-index. + + Returns: + pd.DataFrame: Embedding and geometry index for each region in regions_gdf. + + Raises: + ValueError: If any of the gdfs index names is None. + ValueError: If joint_gdf.index is not of type pd.MultiIndex or doesn't have 2 levels. + ValueError: If index levels in gdfs don't overlap correctly. + """ + self._validate_indexes(regions_gdf, features_gdf, joint_gdf) + features = self._prepare_features(regions_gdf, features_gdf, joint_gdf) + + if self._skip_autoencoder: + return features + else: + self._model = self._train_model_unsupervised(features) + return self._embed(features) + + def _maybe_get_model(self) -> GTFS2VecModel: + """Check if model is fit and return it.""" + if self._model is None: + raise ModelNotFitException("Model not fit! Run fit() or fit_transform() first.") + return self._model + + def _prepare_features( + self, + regions_gdf: gpd.GeoDataFrame, + features_gdf: gpd.GeoDataFrame, + joint_gdf: gpd.GeoDataFrame, + ) -> pd.DataFrame: + """ + Prepare features for embedding. + + Args: + regions_gdf (gpd.GeoDataFrame): Region indexes and geometries. + features_gdf (gpd.GeoDataFrame): Feature indexes, geometries and feature values. + joint_gdf (gpd.GeoDataFrame): Joiner result with region-feature multi-index. + """ + regions_gdf = self._remove_geometry_if_present(regions_gdf) + features_gdf = self._remove_geometry_if_present(features_gdf) + joint_gdf = self._remove_geometry_if_present(joint_gdf) + + joint_features = ( + joint_gdf.join(features_gdf, on=features_gdf.index.name) + .groupby(regions_gdf.index.name) + .agg(self._get_columns_aggregation(features_gdf.columns)) + ) + + regions_features = ( + regions_gdf.join(joint_features, on=regions_gdf.index.name).fillna(0).astype(int) + ) + regions_features = self._normalize_features(regions_features) + return regions_features + + def _get_columns_aggregation(self, columns: List[str]) -> Dict[str, Any]: + """ + Get aggregation dict for given columns. + + Args: + columns (list): List of columns. + + Returns: + dict: Aggregation dict. + """ + agg_dict: Dict[str, Any] = {} + + for column in columns: + if column.startswith(GTFS2VEC_TRIPS_PREFIX): + agg_dict[column] = "sum" + elif column.startswith(GTFS2VEC_DIRECTIONS_PREFIX): + agg_dict[column] = lambda x: len(reduce(set.union, x)) + return agg_dict + + def _normalize_columns_group(self, df: pd.DataFrame, columns: List[str]) -> pd.DataFrame: + """ + Normalize given columns in df. + + Args: + df (pd.DataFrame): DataFrame to normalize. + columns (list): List of columns. + """ + df[columns] = (df[columns] - df[columns].min().min()) / ( + df[columns].max().max() - df[columns].min().min() + ) + return df + + def _normalize_features(self, features: pd.DataFrame) -> pd.DataFrame: + """ + Normalize features. + + Args: + features (pd.DataFrame): Features. + + Returns: + pd.DataFrame: Normalized features. + """ + norm_columns = [ + [ + column + for column in features.columns + if column.startswith(GTFS2VEC_DIRECTIONS_PREFIX) + ], + [column for column in features.columns if column.startswith(GTFS2VEC_TRIPS_PREFIX)], + ] + + for columns in norm_columns: + features = self._normalize_columns_group(features, columns) + + return features + + def _train_model_unsupervised(self, features: pd.DataFrame) -> GTFS2VecModel: + """ + Train model unsupervised. + + Args: + features (pd.DataFrame): Features. + """ + model = GTFS2VecModel( + n_features=len(features.columns), + n_hidden=self._hidden_size, + n_embed=self._embedding_size, + ) + X = features.to_numpy().astype(np.float32) + x_dataloader = DataLoader(X, batch_size=24, shuffle=True, num_workers=4) + trainer = pl.Trainer(max_epochs=10) + + trainer.fit(model, x_dataloader) + + return model + + def _embed(self, features: pd.DataFrame) -> pd.DataFrame: + """ + Embed features. + + Args: + features (pd.DataFrame): Features. + + Returns: + pd.DataFrame: Embeddings. + """ + model = self._maybe_get_model() + if len(features.columns) != model.n_features: + raise ValueError( + f"Features must have {model.n_features} columns but has {len(features.columns)}." + ) + + embeddings = model(torch.Tensor(features.to_numpy().astype(np.float32))).detach().numpy() + + return pd.DataFrame( + data=embeddings, + index=features.index, + ) diff --git a/srai/loaders/gtfs_loader.py b/srai/loaders/gtfs_loader.py index 132ed457..3377eca4 100644 --- a/srai/loaders/gtfs_loader.py +++ b/srai/loaders/gtfs_loader.py @@ -23,6 +23,9 @@ if TYPE_CHECKING: # pragma: no cover from gtfs_kit import Feed +GTFS2VEC_DIRECTIONS_PREFIX = "directions_at_" +GTFS2VEC_TRIPS_PREFIX = "trips_at_" + class GTFSLoader: """ @@ -108,7 +111,7 @@ def _load_trips(self, feed: "Feed") -> pd.DataFrame: df = pd.DataFrame(records, columns=["stop_id", "hour", "num_trips"]) df = df.pivot_table(index="stop_id", columns="hour", values="num_trips", fill_value=0) - df = df.add_prefix("trip_count_at_") + df = df.add_prefix(GTFS2VEC_TRIPS_PREFIX) return df @@ -134,7 +137,7 @@ def _load_directions(self, feed: "Feed") -> gpd.GeoDataFrame: pivoted = df.pivot_table( values="trip_headsign", index="stop_id", columns="hour", aggfunc=set ) - pivoted = pivoted.add_prefix("directions_at_") + pivoted = pivoted.add_prefix(GTFS2VEC_DIRECTIONS_PREFIX) return pivoted diff --git a/srai/models/__init__.py b/srai/models/__init__.py new file mode 100644 index 00000000..b5e07f24 --- /dev/null +++ b/srai/models/__init__.py @@ -0,0 +1,5 @@ +"""Models.""" + +from .gtfs2vec_model import GTFS2VecModel + +__all__ = ["GTFS2VecModel"] diff --git a/srai/models/gtfs2vec_model.py b/srai/models/gtfs2vec_model.py new file mode 100644 index 00000000..79a891e8 --- /dev/null +++ b/srai/models/gtfs2vec_model.py @@ -0,0 +1,72 @@ +""" +Embedding model for gtfs2vec. + +This module contains embedding model from gtfs2vec paper [1]. + +References: + [1] https://doi.org/10.1145/3486640.3491392 +""" +from typing import Any + +import torch +from pytorch_lightning import LightningModule +from torch import nn +from torch.nn import functional as F + + +class GTFS2VecModel(LightningModule): # type: ignore + """Autoencoder based embedding model for gtfs2vec.""" + + def __init__( + self, + n_features: int, + n_hidden: int = 48, + n_embed: int = 64, + ) -> None: + """ + Init GTFS2VecModel. + + Args: + n_features (int): Number of features. + n_hidden (int, optional): Number of hidden units. Defaults to 48. + n_embed (int, optional): Embedding size. Defaults to 64. + """ + super().__init__() + self.n_features = n_features + + self.encoder = nn.Sequential( + nn.Linear(n_features, n_hidden), nn.ReLU(), nn.Linear(n_hidden, n_embed) + ) + self.decoder = nn.Sequential( + nn.Linear(n_embed, n_hidden), nn.ReLU(), nn.Linear(n_hidden, n_features) + ) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + """ + Forward pass. + + Args: + x (torch.Tensor): Input tensor. + """ + embedding: torch.Tensor = self.encoder(x) + return embedding + + def configure_optimizers(self) -> torch.optim.Optimizer: + """Configure optimizer.""" + optimizer = torch.optim.Adam(self.parameters(), lr=1e-3) + return optimizer + + def training_step(self, batch: torch.Tensor, batch_idx: Any) -> torch.Tensor: + """ + Training step. + + Args: + batch (torch.Tensor): Batch. + batch_idx (Any): Batch index. + """ + x = batch + z = self.encoder(x) + x_hat = self.decoder(z) + loss = F.mse_loss(x_hat, x) + self.log("train_loss", loss) + return loss diff --git a/srai/utils/exceptions.py b/srai/utils/exceptions.py new file mode 100644 index 00000000..5f7bbbca --- /dev/null +++ b/srai/utils/exceptions.py @@ -0,0 +1,13 @@ +"""Custom exceptions for the SRAI package.""" + + +class SRAIException(Exception): + """Base class for all SRAI exceptions.""" + + pass + + +class ModelNotFitException(SRAIException): + """Exception raised when a model is not fit.""" + + pass diff --git a/tests/embedders/test_gtfs2vec_embedder.py b/tests/embedders/test_gtfs2vec_embedder.py new file mode 100644 index 00000000..2f465d3c --- /dev/null +++ b/tests/embedders/test_gtfs2vec_embedder.py @@ -0,0 +1,235 @@ +"""GTFS2VecEmbedder tests.""" + +from typing import Any + +import geopandas as gpd +import numpy as np +import pandas as pd +import pytest +from pytest_mock import MockerFixture +from pytorch_lightning import seed_everything +from shapely.geometry import Polygon + +from srai.embedders import GTFS2VecEmbedder +from srai.utils.exceptions import ModelNotFitException + + +@pytest.fixture # type: ignore +def gtfs2vec_features() -> gpd.GeoDataFrame: + """Get GTFS2Vec features GeoDataFrame.""" + features_gdf = gpd.GeoDataFrame( + { + "trips_at_6": [1, 0, 0], + "trips_at_7": [1, 1, 0], + "trips_at_8": [0, 0, 1], + "directions_at_6": [ + {"A", "A1"}, + {"B", "B1"}, + {"C"}, + ], + }, + geometry=gpd.points_from_xy([1, 2, 5], [1, 2, 2]), + index=[1, 2, 3], + ) + features_gdf.index.name = "stop_id" + return features_gdf + + +@pytest.fixture # type: ignore +def gtfs2vec_regions() -> gpd.GeoDataFrame: + """Get GTFS2Vec regions GeoDataFrame.""" + regions_gdf = gpd.GeoDataFrame( + { + "region_id": ["ff1", "ff2", "ff3"], + }, + geometry=[ + Polygon([(0, 0), (0, 3), (3, 3), (3, 0)]), + Polygon([(4, 0), (4, 3), (7, 3), (7, 0)]), + Polygon([(8, 0), (8, 3), (11, 3), (11, 0)]), + ], + ).set_index("region_id") + return regions_gdf + + +@pytest.fixture # type: ignore +def gtfs2vec_joint() -> gpd.GeoDataFrame: + """Get GTFS2Vec joint GeoDataFrame.""" + joint_gdf = gpd.GeoDataFrame() + joint_gdf.index = pd.MultiIndex.from_tuples( + [("ff1", 1), ("ff1", 2), ("ff2", 3)], + names=["region_id", "stop_id"], + ) + return joint_gdf + + +@pytest.fixture # type: ignore +def features_not_embedded() -> pd.DataFrame: + """Get features not embedded.""" + return pd.DataFrame( + { + "trips_at_6": [0.5, 0.0, 0.0], + "trips_at_7": [1.0, 0.0, 0.0], + "trips_at_8": [0.0, 0.5, 0.0], + "directions_at_6": [1.0, 0.25, 0.0], + "region_id": ["ff1", "ff2", "ff3"], + }, + ).set_index("region_id") + + +@pytest.fixture # type: ignore +def features_embedded() -> pd.DataFrame: + """Get features embedded.""" + embeddings = np.array( + [ + [0.642446, 0.001230, -0.038590], + [0.960088, 0.433973, 0.401301], + [0.224951, -0.135296, -0.157667], + [0.782488, 0.212641, 0.177253], + ], + dtype=np.float32, + ) + features = pd.DataFrame(embeddings.T) + features.index = pd.Index(["ff1", "ff2", "ff3"], name="region_id") + features.columns = pd.RangeIndex(0, 4, 1) + return features + + +@pytest.mark.parametrize( # type: ignore + "regions_fixture,features_fixture,joint_fixture,expectation", + [ + ( + "gdf_unnamed_single_index", + "gdf_features", + "gdf_joint", + pytest.raises(ValueError), + ), + ( + "gdf_regions", + "gdf_unnamed_single_index", + "gdf_joint", + pytest.raises(ValueError), + ), + ( + "gdf_regions", + "gdf_features", + "gdf_unnamed_single_index", + pytest.raises(ValueError), + ), + ( + "gdf_regions", + "gdf_features", + "gdf_three_level_multi_index", + pytest.raises(ValueError), + ), + ( + "gdf_incorrectly_named_single_index", + "gdf_features", + "gdf_joint", + pytest.raises(ValueError), + ), + ( + "gdf_regions", + "gdf_incorrectly_named_single_index", + "gdf_joint", + pytest.raises(ValueError), + ), + ], +) +def test_incorrect_indexes( + regions_fixture: str, + features_fixture: str, + joint_fixture: str, + expectation: Any, + request: Any, +) -> None: + """Test GTFS2VecEmbedder with incorrect input dataframes.""" + regions_gdf = request.getfixturevalue(regions_fixture) + features_gdf = request.getfixturevalue(features_fixture) + joint_gdf = request.getfixturevalue(joint_fixture) + + with expectation: + embedder = GTFS2VecEmbedder(skip_autoencoder=True) + embedder.transform(regions_gdf, features_gdf, joint_gdf) + + with expectation: + embedder = GTFS2VecEmbedder(skip_autoencoder=True) + embedder.fit(regions_gdf, features_gdf, joint_gdf) + + with expectation: + embedder = GTFS2VecEmbedder(skip_autoencoder=True) + embedder.fit_transform(regions_gdf, features_gdf, joint_gdf) + + +def test_transform_with_unfit_model( + gtfs2vec_regions: gpd.GeoDataFrame, + gtfs2vec_features: gpd.GeoDataFrame, + gtfs2vec_joint: gpd.GeoDataFrame, +) -> None: + """Test GTFS2VecEmbedder transform with unfitted model.""" + embedder = GTFS2VecEmbedder(skip_autoencoder=False) + with pytest.raises(ModelNotFitException): + embedder.transform(gtfs2vec_regions, gtfs2vec_features, gtfs2vec_joint) + + +def test_transform_with_mismatched_features_count( + gtfs2vec_regions: gpd.GeoDataFrame, + gtfs2vec_features: gpd.GeoDataFrame, + gtfs2vec_joint: gpd.GeoDataFrame, + mocker: MockerFixture, +) -> None: + """Test GTFS2VecEmbedder transform with mismatched features count.""" + embedder = GTFS2VecEmbedder(skip_autoencoder=False) + mock_model = mocker.MagicMock() + mock_model.configure_mock(**{"n_fetures": 42}) + embedder._model = mock_model + + with pytest.raises(ValueError): + embedder.transform(gtfs2vec_regions, gtfs2vec_features, gtfs2vec_joint) + + +@pytest.mark.parametrize( # type: ignore + "regions_fixture,features_fixture,joint_fixture,embedding", + [ + ( + "gtfs2vec_regions", + "gtfs2vec_features", + "gtfs2vec_joint", + True, + ), + ( + "gtfs2vec_regions", + "gtfs2vec_features", + "gtfs2vec_joint", + False, + ), + ], +) +def test_embedder( + regions_fixture: str, + features_fixture: str, + joint_fixture: str, + embedding: bool, + request: Any, +) -> None: + """Test GTFS2VecEmbedder results.""" + regions_gdf = request.getfixturevalue(regions_fixture) + features_gdf = request.getfixturevalue(features_fixture) + joint_gdf = request.getfixturevalue(joint_fixture) + + if embedding: + expected_features = request.getfixturevalue("features_embedded") + else: + expected_features = request.getfixturevalue("features_not_embedded") + + embedder = GTFS2VecEmbedder(hidden_size=2, embedding_size=4, skip_autoencoder=not embedding) + + seed_everything(42) + embedder.fit(regions_gdf, features_gdf, joint_gdf) + features_embedded = embedder.transform(regions_gdf, features_gdf, joint_gdf) + + pd.testing.assert_frame_equal(features_embedded, expected_features, atol=1e-3) + + seed_everything(42) + features_embedded = embedder.fit_transform(regions_gdf, features_gdf, joint_gdf) + + pd.testing.assert_frame_equal(features_embedded, expected_features, atol=1e-3) diff --git a/tests/loaders/conftest.py b/tests/loaders/conftest.py index 87922356..995b4e65 100644 --- a/tests/loaders/conftest.py +++ b/tests/loaders/conftest.py @@ -8,7 +8,7 @@ from pytest_mock import MockerFixture -@pytest.fixture(scope="session") # type: ignore +@pytest.fixture # type: ignore def gtfs_validation_ok() -> pd.DataFrame: """Get GTFS validation result with no errors.""" return pd.DataFrame( @@ -21,7 +21,7 @@ def gtfs_validation_ok() -> pd.DataFrame: ) -@pytest.fixture(scope="session") # type: ignore +@pytest.fixture # type: ignore def gtfs_validation_error() -> pd.DataFrame: """Get GTFS validation result with errors.""" return pd.DataFrame( @@ -34,7 +34,7 @@ def gtfs_validation_error() -> pd.DataFrame: ) -@pytest.fixture(scope="session") # type: ignore +@pytest.fixture # type: ignore def stop_time_series() -> pd.DataFrame: """Get mocked stop time series.""" ts = pd.DataFrame.from_dict( @@ -54,7 +54,7 @@ def stop_time_series() -> pd.DataFrame: return ts -@pytest.fixture(scope="session") # type: ignore +@pytest.fixture # type: ignore def stop_times() -> pd.DataFrame: """Get mocked stop times.""" return pd.DataFrame( @@ -67,7 +67,7 @@ def stop_times() -> pd.DataFrame: ) -@pytest.fixture(scope="session") # type: ignore +@pytest.fixture # type: ignore def trips() -> pd.DataFrame: """Get mocked trips.""" return pd.DataFrame( @@ -78,7 +78,7 @@ def trips() -> pd.DataFrame: ) -@pytest.fixture(scope="session") # type: ignore +@pytest.fixture # type: ignore def stops() -> pd.DataFrame: """Get mocked stops.""" return pd.DataFrame( diff --git a/tests/loaders/test_gtfs_loader.py b/tests/loaders/test_gtfs_loader.py index e9eee2b2..f9a64c6a 100644 --- a/tests/loaders/test_gtfs_loader.py +++ b/tests/loaders/test_gtfs_loader.py @@ -8,6 +8,7 @@ from pytest_mock import MockerFixture from srai.loaders import GTFSLoader +from srai.loaders.gtfs_loader import GTFS2VEC_DIRECTIONS_PREFIX, GTFS2VEC_TRIPS_PREFIX ut = TestCase() @@ -58,10 +59,10 @@ def test_gtfs_loader(feed: Any, mocker: MockerFixture, gtfs_validation_ok: pd.Da ut.assertCountEqual( features.columns, [ - "trip_count_at_12", - "trip_count_at_13", - "directions_at_12", - "directions_at_13", + f"{GTFS2VEC_TRIPS_PREFIX}12", + f"{GTFS2VEC_TRIPS_PREFIX}13", + f"{GTFS2VEC_DIRECTIONS_PREFIX}12", + f"{GTFS2VEC_DIRECTIONS_PREFIX}13", "geometry", ], )