diff --git a/.gitignore b/.gitignore index 0321294..5035a83 100644 --- a/.gitignore +++ b/.gitignore @@ -3,3 +3,4 @@ *.pyc __pycache__ .pytest_cache +tmp diff --git a/pyproject.toml b/pyproject.toml index 31d162a..827ea85 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,11 @@ version = "0.1.0" description = "BC ventilation index bulletin generator" readme = "README.md" requires-python = ">=3.9" -dependencies = [] +dependencies = [ + "cfgrib>=0.9.14.1", + "geopandas>=1.0.1", + "xarray>=2024.7.0", +] [tool.ruff] line-length = 120 diff --git a/tests/test_data_fetch.py b/tests/test_data_fetch.py index 7c77048..7169dc6 100644 --- a/tests/test_data_fetch.py +++ b/tests/test_data_fetch.py @@ -1,24 +1,228 @@ -import pytest +from datetime import datetime +from pandas import DataFrame from freezegun import freeze_time +from xarray import Dataset +from geopandas import GeoDataFrame -from utils.data_fetch import _build_urls +from utils.data_fetch import _build_geo_data_frames, _build_urls, _build_data_frames, _clean_data, _filter_data -class TestBuildUrls: - @freeze_time("2024-11-19") - def test_urls_correct(self): - offset1 = "012" - offset2 = "024" - offset3 = "048" - url1 = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km/00/012/20241119T00Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT012H.grib2" - url2 = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km/00/024/20241119T00Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT024H.grib2" - url3 = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km/00/048/20241119T00Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT048H.grib2" +@freeze_time("2024-11-19") +def test_build_urls(): + offset_1 = "012" + offset_2 = "024" + offset3 = "048" + url_1 = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km/00/012/20241119T00Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT012H.grib2" + url_2 = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km/00/024/20241119T00Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT024H.grib2" + url_3 = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km/00/048/20241119T00Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT048H.grib2" - urls = _build_urls() + urls = _build_urls() - assert offset1 in urls.keys() - assert offset2 in urls.keys() - assert offset3 in urls.keys() - assert urls[offset1] == url1 - assert urls[offset2] == url2 - assert urls[offset3] == url3 + assert offset_1 in urls.keys() + assert offset_2 in urls.keys() + assert offset3 in urls.keys() + assert urls[offset_1] == url_1 + assert urls[offset_2] == url_2 + assert urls[offset3] == url_3 + + +def test_build_dataframes(): + # This is an extremely minimal example of the structure of the data I've + # seen from Environment Canada for my purposes. I'm no data scientist, + # however. + dataset_1 = Dataset( + { + "unknown": (["loc"], [0.50]), + "latitude": (["loc"], [49]), + "longitude": (["loc"], [-130]), + }, + coords={ + "x": (["loc"], [1]), + "y": (["loc"], [1]), + }, + ) + dataset_2 = Dataset( + { + "unknown": (["loc"], [0.43]), + "latitude": (["loc"], [49]), + "longitude": (["loc"], [-130]), + }, + coords={ + "x": (["loc"], [1]), + "y": (["loc"], [1]), + }, + ) + + datasets = { + "012": dataset_1, + "024": dataset_2, + } + + result = _build_data_frames(datasets) + + assert "012" in result + assert isinstance(result["012"], DataFrame) + assert "024" in result + assert isinstance(result["024"], DataFrame) + + +def test_filter_data(): + data_frame_1 = DataFrame( + [ + { + "y": 1, + "x": 1, + "latitude": 49, + "longitude": -130, + "unknown": 0.50, + }, + { + "y": 2, + "x": 1, + "latitude": 49, + "longitude": -150, + "unknown": 0.67, + }, + ] + ) + data_frame_2 = DataFrame( + [ + { + "y": 1, + "x": 1, + "latitude": 49, + "longitude": -130, + "unknown": 0.43, + }, + { + "y": 2, + "x": 1, + "latitude": 49, + "longitude": -150, + "unknown": 0.21, + }, + ] + ) + data_frames = { + "012": data_frame_1, + "024": data_frame_2, + } + + result = _filter_data(data_frames) + + assert "012" in result + test_frame_1 = result["012"] + assert test_frame_1[test_frame_1["longitude"] == -150].empty + + assert "024" in result + test_frame_2 = result["024"] + assert test_frame_2[test_frame_2["longitude"] == -150].empty + + +def test_clean_data(): + data_frame_1 = DataFrame( + [ + { + "y": 1, + "x": 1, + "time": datetime.now(), + "step": 1, + "surface": 0, + "valid_time": 24, + "latitude": 49, + "longitude": -130, + "unknown": 0.50, + }, + ] + ) + data_frame_2 = DataFrame( + [ + { + "y": 1, + "x": 1, + "time": datetime.now(), + "step": 1, + "surface": 0, + "valid_time": 24, + "latitude": 49, + "longitude": -130, + "unknown": 0.43, + }, + ] + ) + data_frames = { + "012": data_frame_1, + "024": data_frame_2, + } + + result = _clean_data(data_frames) + + assert "012" in result + test_frame_1 = result["012"] + assert "time" not in test_frame_1.columns.values + assert "step" not in test_frame_1.columns.values + assert "surface" not in test_frame_1.columns.values + assert "valid_time" not in test_frame_1.columns.values + assert "x" in test_frame_1.columns.values + assert "y" in test_frame_1.columns.values + assert "latitude" in test_frame_1.columns.values + assert "longitude" in test_frame_1.columns.values + assert "ventilation_index" in test_frame_1.columns.values + + assert "024" in result + test_frame_2 = result["012"] + assert "time" not in test_frame_2.columns.values + assert "step" not in test_frame_2.columns.values + assert "surface" not in test_frame_2.columns.values + assert "valid_time" not in test_frame_2.columns.values + assert "x" in test_frame_2.columns.values + assert "y" in test_frame_2.columns.values + assert "latitude" in test_frame_2.columns.values + assert "longitude" in test_frame_2.columns.values + assert "ventilation_index" in test_frame_2.columns.values + + +def test_build_geo_data_frames(): + # This test generates false warnings. See: + # https://github.com/geopandas/geopandas/issues/3430 + # https://github.com/pyproj4/pyproj/issues/1307 + data_frame_1 = DataFrame( + [ + { + "y": 1, + "x": 1, + "latitude": 49, + "longitude": -130, + "ventilation_index": 0.50, + }, + ] + ) + data_frame_2 = DataFrame( + [ + { + "y": 1, + "x": 1, + "latitude": 49, + "longitude": -130, + "ventilation_index": 0.43, + }, + ] + ) + data_frames = { + "012": data_frame_1, + "024": data_frame_2, + } + + result = _build_geo_data_frames(data_frames) + + assert "012" in result + geo_data_frame_1 = result["012"] + assert isinstance(geo_data_frame_1, GeoDataFrame) + assert "geometry" in geo_data_frame_1.columns.values + assert geo_data_frame_1.crs.name == "WGS 84 / Pseudo-Mercator" + + assert "024" in result + geo_data_frame_2 = result["024"] + assert isinstance(geo_data_frame_2, GeoDataFrame) + assert "geometry" in geo_data_frame_2.columns.values + assert geo_data_frame_2.crs.name == "WGS 84 / Pseudo-Mercator" diff --git a/utils/data_fetch.py b/utils/data_fetch.py index 70902c4..16c7d5b 100644 --- a/utils/data_fetch.py +++ b/utils/data_fetch.py @@ -1,4 +1,9 @@ -import datetime +from datetime import date +from os import makedirs +from urllib.request import urlretrieve +from pandas import DataFrame +from xarray import load_dataset, Dataset +from geopandas import points_from_xy, GeoDataFrame BASE_URL = "https://dd.weather.gc.ca/model_hrdps/continental/2.5km" @@ -13,17 +18,116 @@ def _build_urls() -> dict[str, str]: # for the data posted at 00 (midnight). urls: dict[str, str] = {} # The date in the filename is represented as "YYYYmmdd" - today = datetime.date.today().strftime("%Y%m%d") + today = date.today().strftime("%Y%m%d") for offset in OFFSETS: urls[offset] = ( f"{BASE_URL}/{POSTING_TIME}/{offset}/{today}T{POSTING_TIME}Z_MSC_HRDPS_VI_Sfc_RLatLon0.0225_PT{offset}H.grib2" ) + info = "\n".join([url for _, url in urls.items()]) print(f"Generated URLs:\n{info}\n") return urls -def fetch_and_clean_data(): +def _fetch_data(urls: dict[str, str]): + # Download the 12h, 24h, and 48h ventillation index forecast files from the + # Environment Canada datamart. + for offset, url in urls.items(): + print(f"Fetching {url}...") + urlretrieve(url, f"./tmp/{offset}.grib2") + print("Done.\n") + + +def _read_data() -> dict[str, Dataset]: + # Load the data from files into memory. + datasets: dict[str, Dataset] = {} + for offset in OFFSETS: + datasets[offset] = load_dataset(f"./tmp/{offset}.grib2", engine="cfgrib") + + num_data_points = sum([dataset.sizes["x"] * dataset.sizes["y"] for dataset in datasets.values()]) + print(f"Loaded {num_data_points} data points.") + + return datasets + + +def _build_data_frames(datasets: dict[str, Dataset]) -> dict[str, DataFrame]: + data_frames: dict[str, DataFrame] = {} + for offset in datasets.keys(): + data_frames[offset] = datasets[offset].to_dataframe().reset_index() + + return data_frames + + +def _filter_data(canada_data_frames: dict[str, Dataset]) -> dict[str, DataFrame]: + # Filter the data to only include BC. + # From https://catalogue.data.gov.bc.ca/dataset/legally-defined-administrative-areas-of-bc/resource/d70a242e-ebc5-4b3d-a418-38abefa03fb2 + bc_data_frames: dict[str, DataFrame] = {} + for offset in canada_data_frames.keys(): + canada_data_frame = canada_data_frames[offset] + + # Filter to the legal bounds of BC. + bc_data_frames[offset] = canada_data_frame[ + (canada_data_frame["latitude"] > 48.0) + & (canada_data_frame["latitude"] < 60.0) + & (canada_data_frame["longitude"] > -139.5) + & (canada_data_frame["longitude"] < -113.5) + ] + + num_data_points = sum([dataframe.shape[0] for dataframe in bc_data_frames.values()]) + print(f"Filtered data to {num_data_points} data points.") + + return bc_data_frames + + +def _clean_data(data_frames: dict[str, DataFrame]) -> dict[str, DataFrame]: + # Filter unused columns. + trimmed_data_frames: dict[str, DataFrame] = {} + for offset in data_frames.keys(): + data_frame = data_frames[offset] + trimmed_data_frames[offset] = data_frame.drop(columns=["time", "step", "surface", "valid_time"], axis=1) + + # There is no label for the ventilation index column, so it gets the default label of "unknown". + renamed_data_frames: dict[str, DataFrame] = {} + for offset in data_frames.keys(): + data_frame = trimmed_data_frames[offset] + renamed_data_frames[offset] = data_frame.rename(columns={"unknown": "ventilation_index"}) + + print("Cleaned DataFrames.") + return renamed_data_frames + + +def _build_geo_data_frames(data_frames: dict[str, DataFrame]) -> dict[str, GeoDataFrame]: + geo_data_frames: dict[str, GeoDataFrame] = {} + for offset in data_frames.keys(): + geo_data_frame = GeoDataFrame( + data_frames[offset], + geometry=points_from_xy(data_frames[offset]["longitude"], data_frames[offset]["latitude"]), + ) + # This is the CRS for the 1984 GPS standard (latitude/longitude). + geo_data_frame.set_crs(epsg=4326, inplace=True) + # Converting it to web mercator to be compatible with ventilation index + # zones. + geo_data_frame.to_crs(epsg=3857, inplace=True) + geo_data_frames[offset] = geo_data_frame + + print("Built GeoDataFrames.") + return geo_data_frames + + +def fetch_and_clean_data() -> dict[str, GeoDataFrame]: + makedirs("./tmp", exist_ok=True) + urls = _build_urls() - pass + _fetch_data(urls) + datasets = _read_data() + data_frames = _build_data_frames(datasets) + filtered_data_frames = _filter_data(data_frames) + clean_data_frames = _clean_data(filtered_data_frames) + geo_data_frames = _build_geo_data_frames(clean_data_frames) + + return geo_data_frames + + +if __name__ == "__main__": + fetch_and_clean_data() \ No newline at end of file diff --git a/uv.lock b/uv.lock index c4d2282..d974c4c 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,124 @@ version = 1 requires-python = ">=3.9" +resolution-markers = [ + "python_full_version < '3.11'", + "python_full_version == '3.11.*'", + "python_full_version >= '3.12'", +] + +[[package]] +name = "attrs" +version = 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