CLI: get-openaq

docs/cli.rst

@@ -18,6 +18,7 @@ any Python code::
 * |get-aqs|_ -- get AQS data
 * |get-ish|_ -- get ISH data
 * |get-ish-lite|_ -- get ISH-Lite data
+* |get-openaq|_ -- get OpenAQ data
 
 .. |run| replace:: ``run``
 .. _run: #melodies-monet-run
@@ -37,6 +38,9 @@ any Python code::
 .. |get-ish-lite| replace:: ``get-ish-lite``
 .. _get-ish-lite: #melodies-monet-get-ish-lite
 
+.. |get-openaq| replace:: ``get-openaq``
+.. _get-openaq: #melodies-monet-get-openaq
+
 .. click:: melodies_monet._cli:_typer_click_object
    :prog: melodies-monet
    :nested: full

melodies_monet/_cli.py

@@ -4,10 +4,17 @@
 """
 melodies-monet -- MELODIES MONET CLI
 """
+import os
 import time
 from contextlib import contextmanager
 from pathlib import Path
-from typing import List
+from typing import List, Tuple
+
+_LOGGING_LEVEL = os.environ.get("MM_LOGGING_LEVEL", None)
+if _LOGGING_LEVEL is not None:
+    import logging
+
+    logging.basicConfig(level=_LOGGING_LEVEL.upper())
 
 try:
     import typer
@@ -20,8 +27,6 @@
     )
     raise SystemExit(1)
 
-from typing import Tuple
-
 DEBUG = False
 INFO_COLOR = typer.colors.CYAN
 ERROR_COLOR = typer.colors.BRIGHT_RED
@@ -1160,6 +1165,246 @@ def get_aqs(
             ds.to_netcdf(dst / out_name)
 
 
+@app.command()
+def get_openaq(
+    start_date: str = typer.Option(..., "-s", "--start-date", help=f"Start date. {_DATE_FMT_NOTE}"),
+    end_date: str = typer.Option(..., "-e", "--end-date", help=f"End date. {_DATE_FMT_NOTE} {_DATE_END_NOTE}"),
+    out_name: str = typer.Option(None, "-o",
+        help=(
+            "Output file name (or full/relative path). "
+            "By default the name is generated like 'OpenAQ_<start-date>_<end-date>.nc'."
+        )
+    ),
+    dst: Path = typer.Option(".", "-d", "--dst", help=(
+            "Destination directory (to control output location "
+            "if using default output file name)."
+        )
+    ),
+    param: List[str] = typer.Option(["o3", "pm25", "pm10"], "-p", "--param", help=(
+            "Parameters. "
+            "Use '-p' more than once to get multiple parameters. "
+            "Other examples: 'no', 'no2', 'nox', 'so2', 'co', 'bc'. "
+            "Only applicable to the web API methods ('api-v2')."
+        )
+    ),
+    reference_grade: bool = typer.Option(True, help="Include reference-grade sensors."),
+    low_cost: bool = typer.Option(False, help="Include low-cost sensors."),
+    method: str = typer.Option("api-v2", "-m", "--method", help=(
+            "Method (reader) to use for fetching data. "
+            "Options: 'api-v2', 'openaq-fetches'."
+        )
+    ),
+    compress: bool = typer.Option(True, help=(
+            "If true, pack float to int and apply compression using zlib with complevel 7. "
+            "This can take time if the dataset is large, but can lead to "
+            "significant space savings."
+        )
+    ),
+    num_workers: int = typer.Option(1, "-n", "--num-workers", help="Number of download workers."),
+    verbose: bool = typer.Option(False),
+    debug: bool = typer.Option(
+        False, "--debug/", help="Print more messages (including full tracebacks)."
+    ),
+):
+    """Download hourly OpenAQ data using monetio and reformat for MM usage."""
+    import warnings
+
+    import monetio as mio
+    import pandas as pd
+
+    from .util.write_util import write_ncf
+
+    global DEBUG
+
+    DEBUG = debug
+
+    typer.echo(HEADER)
+
+    if method not in {"api-v2", "openaq-fetches"}:
+        typer.secho(f"Error: method {method!r} not recognized", fg=ERROR_COLOR)
+        raise typer.Exit(2)
+
+    start_date = pd.Timestamp(start_date)
+    end_date = pd.Timestamp(end_date)
+
+    if method in {"openaq-fetches"}:
+        dates = pd.date_range(start_date, end_date, freq="D")
+    elif method in {"api-v2"}:
+        dates = pd.date_range(start_date, end_date, freq="h")
+    else:
+        raise AssertionError
+    if verbose:
+        print("Dates:")
+        print(dates)
+
+    if verbose and method in {"api-v2"}:
+        print("Params:", param)
+
+    # Set destination and file name
+    fmt = r"%Y%m%d"
+    if out_name is None:
+        out_name = f"OpenAQ_{start_date:{fmt}}_{end_date:{fmt}}.nc"
+    else:
+        p = Path(out_name)
+        if p.name == out_name:
+            # `out_name` is just the file name
+            out_name = p.name
+        else:
+            # `out_name` has path
+            if dst != Path("."):
+                typer.echo(f"warning: overriding `dst` setting {dst.as_posix()!r} with `out_name` {p.as_posix()!r}")
+            dst = p.parent
+            out_name = p.name
+
+    sensor_types = []
+    if reference_grade:
+        sensor_types.append("reference grade")
+    if low_cost:
+        sensor_types.append("low-cost sensor")
+    if not sensor_types and method in {"api-v2"}:
+        typer.secho(
+            "Error: no sensor types selected. Use --reference-grade and/or --low-cost",
+            fg=ERROR_COLOR,
+        )
+        raise typer.Exit(2)
+
+    if verbose and method in {"openaq-fetches"}:
+        from dask.diagnostics import ProgressBar
+
+        ProgressBar().register()
+
+    with _timer("Fetching data with monetio"):
+        if method == "openaq-fetches":
+            with warnings.catch_warnings():
+                warnings.filterwarnings(
+                    "ignore",
+                    message="The (error|warn)_bad_lines argument has been deprecated"
+                )
+                df = mio.openaq.add_data(
+                    dates,
+                    n_procs=num_workers,
+                    # wide_fmt=True,
+                )
+
+            # Address time-wise non-unique site IDs
+            # Some (most?) are just slightly different lat/lon
+            # But seems like a few are actual time-wise lat/lon duplicates
+            df = df.drop_duplicates(["time", "siteid"])
+
+        elif method == "api-v2":
+            df = mio.obs.openaq_v2.add_data(
+                dates,
+                parameters=param,
+                sensor_type=sensor_types,
+                wide_fmt=True,
+                timeout=60,
+                retry=15,
+                threads=num_workers if num_workers > 1 else None,
+            )
+
+            dupes = df[df.duplicated(["time", "siteid"], keep=False)]
+            if not dupes.empty:
+                typer.echo(
+                    f"warning: {len(dupes)} unexpected time-siteid duplicated rows:"
+                )
+                if verbose:
+                    typer.echo(dupes)
+                df = df.drop_duplicates(["time", "siteid"])
+        else:
+            raise AssertionError
+
+        # Drop times not on the hour
+        good = df.time == df.time.dt.floor("H")
+        typer.echo(f"Dropping {(~good).sum()}/{len(good)} rows that aren't on the hour.")
+        df = df[good]
+
+    with _timer("Forming xarray Dataset"):
+        df = df.drop(columns=["index"], errors="ignore")
+        df = df.dropna(subset=["latitude", "longitude"])
+
+        if method == "openaq-fetches":
+            site_vns = [
+                "siteid",  # based on country and lat/lon
+                "latitude",
+                "longitude",
+                "utcoffset",
+                #
+                "city",
+                "country",  # 2-char codes
+                #
+                "sourceName",
+                "sourceType",  # "government"
+            ]
+            # NOTE: time_local not included since it varies in time as well
+        elif method == "api-v2":
+            site_vns = [
+                "siteid",  # real OpenAQ location ID
+                "latitude",
+                "longitude",
+                "utcoffset",
+                #
+                "location",
+                "city",
+                "country",
+                #
+                "entity",
+                "sensor_type",
+                "is_mobile",
+                "is_analysis",
+            ]
+            for vn in ["city", "is_analysis"]:  # may have been dropped for being all null
+                if vn not in df.columns:
+                    site_vns.remove(vn)
+
+        else:
+            raise AssertionError
+
+        ds_site = (
+            df[site_vns]
+            .groupby("siteid")
+            .first()
+            .to_xarray()
+            .swap_dims(siteid="x")
+        )
+
+        ds = (
+            df.drop(columns=[vn for vn in site_vns if vn not in ["siteid"]])
+            .set_index(["time", "siteid"])
+            .to_xarray()
+            .swap_dims(siteid="x")
+            .merge(ds_site)
+            .set_coords(["latitude", "longitude"])
+            .assign(x=range(ds_site.dims["x"]))
+        )
+
+        # Rename species vars and add units as attr
+        nice_us = {"ppm": "ppmv", "ugm3": "ug m-3", "ppb": "pbbv"}
+        for vn0 in [n for n in df.columns if n.endswith(("_ppm", "ppb", "_ugm3", "_umg3"))]:
+            i_last_underscore = vn0.rfind("_")
+            vn, u = vn0[:i_last_underscore], vn0[i_last_underscore + 1:]
+            if u == "umg3":
+                u = "ugm3"
+            nice_u = nice_us[u]
+            ds[vn0].attrs.update(units=nice_u)
+            ds = ds.rename_vars({vn0: vn})
+
+        # Fill in local time array
+        # (in the df, not all sites have rows for all times, so we have NaTs at this point)
+        ds["time_local"] = ds.time + ds.utcoffset
+
+        # Expand
+        ds = (
+            ds
+            .expand_dims("y")
+            .transpose("time", "y", "x")
+        )
+
+    with _timer("Writing netCDF file"):
+        if compress:
+            write_ncf(ds, dst / out_name, verbose=verbose)
+        else:
+            ds.to_netcdf(dst / out_name)
+
 cli = app
 
 _typer_click_object = typer.main.get_command(app)  # for sphinx-click in docs

melodies_monet/tests/test_get_data_cli.py

@@ -4,6 +4,7 @@
 """
 Check for consistency with the tutorial datasets and that options work.
 """
+import os
 import subprocess
 
 import numpy as np
@@ -30,6 +31,8 @@
 ds0_aeronet = xr.open_dataset(fetch_example("aeronet:2019-09"))
 ds0_airnow = xr.open_dataset(fetch_example("airnow:2019-09"))
 
+have_openaq_api_key = len(os.environ.get("OPENAQ_API_KEY", "")) > 0
+
 
 def test_get_aeronet(tmp_path):
     fn = "x.nc"
@@ -173,3 +176,47 @@ def test_get_aqs_hourly(tmp_path):
         for v in ds.data_vars
         if ds[v].dims == ("time", "y", "x")
     } == {"OZONE", "time_local"}
+
+
+@pytest.mark.skipif(not have_openaq_api_key, reason="OPENAQ_API_KEY not set")
+def test_get_openaq(tmp_path):
+    fn = "x.nc"
+    cmd = [
+        "melodies-monet", "get-openaq",
+        "-s", "2024-09-10", "-e" "2024-09-10 00:59",
+        "--dst", tmp_path.as_posix(), "-o", fn,
+    ]
+    subprocess.run(cmd, check=True)
+
+    ds = xr.open_dataset(tmp_path / fn)
+
+    assert ds.time.size == 1
+    assert {
+        v
+        for v in ds.data_vars
+        if ds[v].dims == ("time", "y", "x")
+    } == {"o3", "pm25", "pm10", "time_local"}
+    assert (ds.sensor_type == "reference grade").all()
+
+
+@pytest.mark.skipif(not have_openaq_api_key, reason="OPENAQ_API_KEY not set")
+def test_get_openaq_lowcost(tmp_path):
+    fn = "x.nc"
+    cmd = [
+        "melodies-monet", "get-openaq",
+        "-s", "2024-09-10", "-e" "2024-09-10 00:59",
+        "-p", "pm25",
+        "--no-reference-grade", "--low-cost",
+        "--dst", tmp_path.as_posix(), "-o", fn,
+    ]
+    subprocess.run(cmd, check=True)
+
+    ds = xr.open_dataset(tmp_path / fn)
+
+    assert ds.time.size == 1
+    assert {
+        v
+        for v in ds.data_vars
+        if ds[v].dims == ("time", "y", "x")
+    } == {"pm25", "time_local"}
+    assert (ds.sensor_type == "low-cost sensor").all()