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Additional program information is available on NOAA's [website](https://www.aoml.noaa.gov/global-drifter-program/). + Download data from: https://www.ngdc.noaa.gov/eog/data/GDP/ -Ungzip data +Potential secondary source to download data here: +https://www.aoml.noaa.gov/phod/gdp/real-time_data.php + +Unzip data diff --git a/datasets/ookla_speedtest/README.md b/datasets/ookla_speedtest/README.md new file mode 100644 index 00000000..c304380c --- /dev/null +++ b/datasets/ookla_speedtest/README.md @@ -0,0 +1,6 @@ +# Ookla Speedtest Dataset +--- + +The Global Broadband Speed Test is collected by Ookla, which gathers data on mobile and broadband network speeds. + +The dataset contains geospatial data of fixed and mobile performance statistics by fiscal quarter ranging from 2019 to 2024. Information may be found on Ookla's Open Data Initiative Website [here](https://www.ookla.com/ookla-for-good/open-data). Ookla's datasets are public access via AWS S3 buckets; moreover, additional information regarding data location may be found [here](https://registry.opendata.aws/speedtest-global-performance/) diff --git a/datasets/ookla_speedtest/config.toml b/datasets/ookla_speedtest/config.toml index e69de29b..bc4a8da8 100644 --- a/datasets/ookla_speedtest/config.toml +++ b/datasets/ookla_speedtest/config.toml @@ -0,0 +1,37 @@ +# Paths of input and output directories +# raw_dir = "/sciclone/aiddata10/REU/geo/raw/esa_landcover" +# process_dir = "/tmp" +# output_dir = "/sciclone/aiddata10/REU/geo/data/rasters/esa_landcover" + +years = [ 2019] +# 2020, 2021, 2022, 2023, 2024 + +# Overwrite existing files? +overwrite_download = false +overwrite_processing = false + + +[run] +backend = "local" +task_runner = "concurrent" +run_parallel = false +max_workers = 4 +bypass_error_wrapper = true +# log_dir = "/sciclone/aiddata10/REU/geo/raw/ookla_speedtest/logs" +log_dir = "./logs" + + +[repo] +url = "https://github.com/aiddata/geo-datasets.git" +branch = "master" +directory = "datasets/ookla_speedtest" + + +[deploy] +deployment_name = "ookla_speedtest" +image_tag = "05dea6e" +version = 3 +flow_file_name = "main" +flow_name = "ookla_speedtest" +work_pool = "geodata-pool" +data_manager_version = "0.4.0" diff --git a/datasets/ookla_speedtest/main.py b/datasets/ookla_speedtest/main.py new file mode 100644 index 00000000..7cb02957 --- /dev/null +++ b/datasets/ookla_speedtest/main.py @@ -0,0 +1,108 @@ +from pathlib import Path +from typing import List +import os +from data_manager import BaseDatasetConfiguration, Dataset, get_config +from src.download_dataset import download_files +from src.helpers import GEOPARQUET_DIR, RASTER_OUTPUT_DIR + + +class OoklaSpeedtestConfiguration(BaseDatasetConfiguration): + raw_dir: str = GEOPARQUET_DIR + output_dir: str = RASTER_OUTPUT_DIR + years: List[int] = [2019, 2020, 2021, 2022, 2023, 2024] + overwrite_download: bool + overwrite_processing: bool + + +class OoklaSpeedtest(Dataset): + name = "Ookla Speedtest" + + def __init__(self, config: OoklaSpeedtestConfiguration): + self.raw_dir = Path(config.raw_dir) + self.output_dir = Path(config.output_dir) + self.years = config.years + self.overwrite_download = config.overwrite_download + self.overwrite_processing = config.overwrite_processing + + def download(self, year: int, output_file_path=None) -> List[Path]: + """ + Downloading a single year's worth of data + """ + logger = self.get_logger() + logger.info(f"Downloading parquet files for year {year}") + return download_files(year) + + def process(self, input_path: Path, output_path: Path): + logger = self.get_logger() + + if self.overwrite_download and not self.overwrite_processing: + logger.warning("Overwrite download set but not overwrite processing.") + if output_path.exists() and not self.overwrite_processing: + logger.info(f"Processed layer exists: {output_path}") + else: + logger.info( + f"Processing file: {input_path}. Ouput will be saved to: {output_path}" + ) + + # importing from src files + from src.helpers import GRID_SIZE, NUM_BANDS, BAND16_COLS, BAND32_COLS + from src.transform_populate import read_parquet + from src.generate_raster import ( + make_raster_profile, + write_multiband_raster_chunks, + ) + + # going through pipeline processing steps + gdf = read_parquet(str(input_path)) + profile = make_raster_profile(num_bands=NUM_BANDS, grid_size=GRID_SIZE) + + write_multiband_raster_chunks( + gdf=gdf, + band32_cols=BAND32_COLS, + band16_cols=BAND16_COLS, + profile=profile, + output_path=output_path, + ) + return + + def main(self): + logger = self.get_logger() + + # os.makedirs(self.raw_dir / "compressed", exist_ok=True) + # os.makedirs(self.raw_dir / "uncompressed", exist_ok=True) + os.makedirs(self.raw_dir, exist_ok=True) # maybe necessary? + + # Download data + logger.info("Running data download") + download = self.run_tasks(self.download, [[y] for y in self.years]) + self.log_run(download) + + os.makedirs(self.output_dir, exist_ok=True) + + # Process data + logger.info("Running processing") + all_downloads = [f for result in download.results() for f in result] + # ensuring output_path name name matches with the input_path name + process_inputs = [ + (input_path, self.output_dir / f"{input_path.stem}.tif") + for input_path in all_downloads + ] + process = self.run_tasks(self.process, process_inputs) + self.log_run(process) + + +# ---- BEGIN BOILERPLATE ---- +try: + from prefect import flow +except Exception: + pass +else: + + @flow + def ookla_speedtest(config: OoklaSpeedtestConfiguration): + OoklaSpeedtest(config).run(config.run) + + +if __name__ == "__main__": + config = get_config(OoklaSpeedtestConfiguration) + OoklaSpeedtest(config).run(config.run) diff --git a/datasets/ookla_speedtest/src/download_dataset.py b/datasets/ookla_speedtest/src/download_dataset.py new file mode 100644 index 00000000..b236f135 --- /dev/null +++ b/datasets/ookla_speedtest/src/download_dataset.py @@ -0,0 +1,69 @@ +import boto3 +import os +from pathlib import Path +import logging +from botocore import UNSIGNED +from botocore.client import BaseClient +from botocore.config import Config +from src.helpers import GEOPARQUET_DIR, BUCKET_NAME, REGION_NAME, QUARTERS + +# Configure logging (less noise from botocore) +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) +logging.getLogger("botocore").setLevel( + logging.WARNING +) # suppressing botocore checksum spam + +# Making the directory +# os.makedirs(GEOPARQUET_DIR, exist_ok=True) + + +# Creating the s3 client with anonymous token +def create_s3_client() -> BaseClient: + return boto3.client( + "s3", region_name=REGION_NAME, config=Config(signature_version=UNSIGNED) + ) + + +# Creating the download file function and creating the loggers +def prepare_download( + s3_client: BaseClient, + s3_key: str, + output_path: str = GEOPARQUET_DIR, + target_bucket_name=BUCKET_NAME, +) -> None: + filename = os.path.basename(s3_key) + # checking if directory exists + os.makedirs(output_path, exist_ok=True) + local_file_path = os.path.join(output_path, filename) + if os.path.exists(local_file_path): + logger.info(f"File {local_file_path} already exists. Skipping download.") + return + logger.info(f"Downloading s3://{target_bucket_name}/{s3_key} to {local_file_path}") + try: + s3_client.download_file(target_bucket_name, s3_key, local_file_path) + logger.info(f"Successfully downloaded {local_file_path}") + except Exception as e: + logger.error(f"Error downloading s3://{target_bucket_name}/{s3_key}: {e}") + + +# Doing the actual downloading; calling the S3 client, and putting the S3 filenames together +def download_files(year: int, quarters: dict = QUARTERS) -> None: + """ + Downloads the performance data files from the target Ookla S3 bucket for 1 year to a local directory + Disclaimer: there is similarity in the naming convention download_file and download_files, which cannot be changed + because of a requirement by botocore. Please note the difference. + """ + s3_client = create_s3_client() + downloaded_files = [] + formats = ["parquet"] # "shapefiles" is an option to download too + service_types = ["mobile", "fixed"] + for quarter, month in quarters.items(): + for format_type in formats: + for service_type in service_types: + filename = f"{year}-{month}-01_performance_{service_type}_tiles.parquet" + s3_key = f"{format_type}/performance/type={service_type}/year={year}/quarter={quarter}/{filename}" + prepare_download(s3_client, s3_key, GEOPARQUET_DIR, BUCKET_NAME) + local_file_path = Path(GEOPARQUET_DIR) / filename + downloaded_files.append(local_file_path) + return downloaded_files diff --git a/datasets/ookla_speedtest/src/generate_raster.py b/datasets/ookla_speedtest/src/generate_raster.py new file mode 100644 index 00000000..f0494234 --- /dev/null +++ b/datasets/ookla_speedtest/src/generate_raster.py @@ -0,0 +1,104 @@ +from src.helpers import ( + GRID_SIZE, + NUM_BANDS, + OUTPUT_RASTER_FILE, + MAP_BOUNDS, + BAND16_COLS, + BAND32_COLS, +) +from src.transform_populate import create_band_array +from rasterio.transform import from_bounds +from rasterio.crs import CRS +import rasterio +import geopandas as gpd +import numpy as np +import logging +import sys +import gc +from typing import Dict, List + +# instantiating the logging +logging.basicConfig(level=logging.INFO, stream=sys.stdout) +logger = logging.getLogger(__name__) + + +def make_raster_profile( + num_bands: int = NUM_BANDS, + grid_size: int = GRID_SIZE, + map_bounds: tuple[float, float, float, float] = MAP_BOUNDS, +) -> Dict[str, object]: + """ + Creates the raster metadata profile for writing the GeoTIFF file. + Profile includes CRS, transform, and dtype information. + --- + Args: + grid_size (int): dimensions of the raster grid (width x height) + num_bands (int): number of raster bands included in the raster + map_bounds (tuple): bounds in projected coordinates + Returns: + Dict[str, object]: raster metadata profile + """ + left, bottom, right, top = map_bounds + transform = from_bounds(left, bottom, right, top, grid_size, grid_size) + profile = { + "driver": "GTiff", + "count": num_bands, + "dtype": "uint32", + "crs": CRS.from_epsg(3857), + "compress": "lzw", + "transform": transform, + "width": grid_size, + "height": grid_size, + } + return profile + + +def write_multiband_raster_chunks( + gdf: gpd.GeoDataFrame, + profile: dict, + output_path: str = OUTPUT_RASTER_FILE, + band32_cols: List[str] = BAND32_COLS, + band16_cols: List[str] = BAND16_COLS, +) -> None: + """ + Writes a multiband GeoTIFF raster file from the GeoDataFrame. Completes this + one band at a time then deletes in order to maximize computational expense. + Each band is created from create_band_array(), converted to dense 2D array, + flipped vertically for top-left origin, and written to the output raster file. + --- + Args: + gdf (gpd.GeoDataFrame) is the input GeoDataFrame + profile (dict) is the profile outputted from make_raster_profile() + output_path (str) the target file path for saving the GeoTIFF + band32_cols (List[str]) are the column names for the uint32 bands + band16_cols (List[str]) are the column names for the uint16 bands + Returns: None + """ + total_bands = len(band32_cols) + len(band16_cols) + profile = profile.copy() + profile["count"] = total_bands + profile["BIGTIFF"] = "YES" + profile["dtype"] = "uint32" # this is a placeholder + + # Writing the uint32 bands + with rasterio.open(output_path, "w", **profile) as dst: + for i, col in enumerate(band32_cols): + logger.info(f"Writing uint32 band {i + 1}: {col}") + band_sparse = create_band_array(gdf, col, dtype=np.uint32) + band_dense = band_sparse.toarray() + band_dense = np.flip(band_dense, axis=0) + dst.write(band_dense.astype(np.uint32), i + 1) + del band_sparse, band_dense + gc.collect() + # Then writing in the uint16 bands + for j, col in enumerate(band16_cols): + band_index = len(band32_cols) + j + 1 + logger.info(f"Writing uint16 band {band_index}: {col}") + band_sparse = create_band_array(gdf, col, dtype=np.uint16) + band_dense = band_sparse.toarray() + band_dense = np.flip(band_dense, axis=0) + dst.write(band_dense.astype(np.uint16), band_index) + del band_sparse, band_dense + gc.collect() + logger.info(f"All {total_bands} bands written to {output_path}.") + return None diff --git a/datasets/ookla_speedtest/src/helpers.py b/datasets/ookla_speedtest/src/helpers.py new file mode 100644 index 00000000..579675c0 --- /dev/null +++ b/datasets/ookla_speedtest/src/helpers.py @@ -0,0 +1,38 @@ +import os + +# Constants +BUCKET_NAME = "ookla-open-data" +REGION_NAME = "us-west-2" +QUARTERS = {1: "01", 2: "04", 3: "07", 4: "10"} + +# Paths (Relative to Project Root) +BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) + +GEOPARQUET_DIR = os.path.join(BASE_DIR, "data", "datasets") +RASTER_OUTPUT_DIR = os.path.join(BASE_DIR, "visualizations") + +os.makedirs(GEOPARQUET_DIR, exist_ok=True) +os.makedirs(RASTER_OUTPUT_DIR, exist_ok=True) + +# WILL NEED TO DEVELOP EITHER A NAMING CONVENTION OR JUST REPLACING +## THE TEST_PARQUET_FILE AND OUTPUT_RASTER_FILE FOR FINAL CHANGES +# Other Constants +TEST_PARQUET_FILE = "2019-01-01_performance_fixed_tiles.parquet" +OUTPUT_RASTER_FILE = os.path.join( + RASTER_OUTPUT_DIR, TEST_PARQUET_FILE.replace(".parquet", ".tif") +) + +# Raster Processing Constants +ZOOM_LEVEL = 16 +GRID_SIZE = 2**ZOOM_LEVEL +BAND32_COLS = ["avg_d_kbps", "avg_u_kbps"] +BAND16_COLS = ["avg_lat_ms", "tests", "devices"] +NUM_BANDS = 5 + +# For EPSG 3857 +MAP_BOUNDS = ( + -20037508.342789244, + -20037508.342789244, + 20037508.342789244, + 20037508.342789244, +) diff --git a/datasets/ookla_speedtest/src/make_geopackage.py b/datasets/ookla_speedtest/src/make_geopackage.py new file mode 100644 index 00000000..fa38f283 --- /dev/null +++ b/datasets/ookla_speedtest/src/make_geopackage.py @@ -0,0 +1,27 @@ +import geopandas as gpd +import os +import logging +import sys + +# instantiating the logging +logging.basicConfig(level=logging.INFO, stream=sys.stdout) +logger = logging.getLogger(__name__) + + +def make_geopackage(gdf: gpd.GeoDataFrame, output_path: str): + """ + Saves a GeoDataFrame as a GeoPackage (.gpkg) + Note: this is not a crucial step to obtaining raster output + and is just an option for additional visualization functionality + """ + try: + if gdf is not None and isinstance(gdf, gpd.GeoDataFrame): + output_dir = os.path.dirname(output_path) + if not os.path.exists(output_dir): + os.makedirs(output_dir) + gdf.to_file(output_path, driver="GPKG") + logger.info(f"Saved data as GeoPackage: {output_path}") + else: + logger.warning("Invalid GeoDataFrame provided to make_geopackage.") + except Exception as e: + logger.error(f"Failed to save GeoPackage: {e}") diff --git a/datasets/ookla_speedtest/src/transform_populate.py b/datasets/ookla_speedtest/src/transform_populate.py new file mode 100644 index 00000000..c17e1f94 --- /dev/null +++ b/datasets/ookla_speedtest/src/transform_populate.py @@ -0,0 +1,95 @@ +from src.helpers import GEOPARQUET_DIR, GRID_SIZE +import geopandas as gpd +import pandas as pd +import numpy as np +import logging +from pyquadkey2.quadkey import QuadKey +from scipy.sparse import coo_matrix +import sys +import os +from tqdm import tqdm + +# Logging +logging.basicConfig(level=logging.INFO, stream=sys.stdout) +logger = logging.getLogger(__name__) + + +def read_parquet(parquet_file: str) -> gpd.GeoDataFrame: + """ + Reads the Parquet file and converts the 'tile' column into a geometry column + and creates a GeoDataFrame + ---- + Args: + parquet_file (str) is the path to the parquet file + Returns: + gpd.GeoDataFrame or nothing if the parquet file isn't found + """ + if os.path.exists(parquet_file): + logger.info(f"Reading Parquet file: {parquet_file}") + parquet_data = pd.read_parquet(parquet_file) + parquet_data["geometry"] = gpd.GeoSeries.from_wkt(parquet_data["tile"]) + gdf = gpd.GeoDataFrame(parquet_data) + # logger.info(gdf.head()) # Checking the geoDataFrame + return gdf + else: + logger.warning(f"Parquet file not found: {parquet_file}") + return None + + +def quadkey_to_tile(quadkey: str, grid_size: int = GRID_SIZE) -> tuple[int, int]: + """ + Converts a quadkey to grid coordinates (x,y) adjusted based on GRID_SIZE + ---- + Args: + quadkey (str) is a QuadKey string representing a tile + grid_size (int) is the size of the raster grid (width x height) + Returns: + tuple[int, int] represent the (x,y) coordinates within the grid + """ + quadkey_obj = QuadKey(quadkey) + x, y = quadkey_obj.tile + x_idx = x % grid_size + y_idx = grid_size - 1 - (y % grid_size) + return x_idx, y_idx + + +def create_band_array( + gdf: gpd.GeoDataFrame, + band_column: str, + grid_size: int = GRID_SIZE, + dtype=np.float32, +) -> coo_matrix: + """ + Creates a sparse 2D raster band array from GeoDataFrame using + quadkeys, transformed from quadkey_to_tile() + ---- + Args: + gdf (GeoDataFrame): input geospatial data + band_column (str): column name to populate the band + grid_size (int): the dimensions of the raster (width x height) + dtype (np.dtype): data type of values + Returns: + coo_matrix: 2D array of shape (GRID_SIZE, GRID_SIZE) + """ + # lists for coordinates and band array values + coords_y = [] + coords_x = [] + values = [] + # looping for the length of the geoDataFrame + for idx in tqdm(range(len(gdf))): + try: + row = gdf.iloc[idx] + quadkey = row["quadkey"] + x, y = quadkey_to_tile(quadkey) + value = row.get(band_column, np.nan) + if not np.isnan(value): + coords_y.append(y) + coords_x.append(x) + values.append(value) + except Exception as e: + logger.error(f"Error processing row {idx} for band '{band_column}': {e} ") + sparse_array = coo_matrix( + (values, (coords_y, coords_x)), shape=(grid_size, grid_size), dtype=dtype + ) + logger.info(f"Successfully created sparse array for band '{band_column}'") + return sparse_array diff --git a/pyproject.toml b/pyproject.toml index f2fc6c99..a5d53379 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,29 +5,16 @@ description = "Dataset import scripts for GeoQuery" readme = "README.md" requires-python = ">=3.11.9" dependencies = [ - "affine>=2.4.0", - "beautifulsoup4>=4.13.4", - "bokeh>=2.4.3", - "boto3>=1.37.35", - "boxsdk[jwt]>=3.6.1", - "click>=8.1.8", - "dask-jobqueue>=0.8.1", - "dask-kubernetes>=2025.4.1", + "boto3>=1.37.1", "data-manager", - "distancerasters>=0.3.3", - "distributed>=2023.3.1", - "fiona>=1.10.1", "geopandas>=1.0.1", - "h5py>=3.13.0", - "lz4>=4.3.2", - "netcdf4>=1.7.2", - "pandas>=2.1.0", - "prefect>=2.20.10", - "proj>=0.2.0", - 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