Universal Format (UF)#

import cmweather  # noqa
import xarray as xr
from open_radar_data import DATASETS

import xradar as xd

Download#

Fetching Universal Format radar data file from open-radar-data repository.

import atexit
from pathlib import Path
from tempfile import TemporaryDirectory

tmpdir_obj = TemporaryDirectory()
atexit.register(tmpdir_obj.cleanup)  # remove even if you forget
tmpdir = Path(tmpdir_obj.name)


def get_temp_file(fname):
    import gzip
    import shutil

    fnamei = Path(DATASETS.fetch(fname))
    fnameo = tmpdir / fnamei.stem
    with gzip.open(fnamei) as fin:
        with open(fnameo, "wb") as fout:
            shutil.copyfileobj(fin, fout)
            fout.flush()
            fout.close()
    return fnameo


fname = get_temp_file("20110427_164233_rvp8-rel_v001_SUR.uf.gz")

Downloading file '20110427_164233_rvp8-rel_v001_SUR.uf.gz' from 'https://github.com/openradar/open-radar-data/raw/main/data/20110427_164233_rvp8-rel_v001_SUR.uf.gz' to '/home/docs/.cache/open-radar-data'.

open_uf_datatree#

The same works analoguous with the datatree loader. But additionally we can provide a sweep string, number or list.

help(xd.io.open_uf_datatree)

Help on function open_uf_datatree in module xradar.io.backends.uf:

open_uf_datatree(
    filename_or_obj,
    mask_and_scale=True,
    decode_times=True,
    concat_characters=True,
    decode_coords=True,
    drop_variables=None,
    use_cftime=None,
    decode_timedelta=None,
    sweep=None,
    first_dim='auto',
    reindex_angle=False,
    fix_second_angle=False,
    site_as_coords=True,
    optional=True,
    optional_groups=False,
    lock=None,
    **kwargs
)
    Open a Universal Format (UF) dataset as :py:class:`xarray.DataTree`.

    This function loads UF radar data into a DataTree structure, which
    organizes radar sweeps as separate nodes. Provides options for decoding time
    and applying various transformations to the data.

    Parameters
    ----------
    filename_or_obj : str, Path, file-like, or DataStore
        The path or file-like object representing the radar file.
        Path-like objects are interpreted as local or remote paths.

    mask_and_scale : bool, optional
        If True, replaces values in the dataset that match `_FillValue` with NaN
        and applies scale and offset adjustments. Default is True.

    decode_times : bool, optional
        If True, decodes time variables according to CF conventions. Default is True.

    concat_characters : bool, optional
        If True, concatenates character arrays along the last dimension, forming
        string arrays. Default is True.

    decode_coords : bool, optional
        If True, decodes the "coordinates" attribute to identify coordinates in the
        resulting dataset. Default is True.

    drop_variables : str or list of str, optional
        Specifies variables to exclude from the dataset. Useful for removing problematic
        or inconsistent variables. Default is None.

    use_cftime : bool, optional
        If True, uses cftime objects to represent time variables; if False, uses
        `np.datetime64` objects. If None, chooses the best format automatically.
        Default is None.

    decode_timedelta : bool, optional
        If True, decodes variables with units of time (e.g., seconds, minutes) into
        timedelta objects. If False, leaves them as numeric values. Default is None.

    sweep : int or list of int, optional
        Sweep numbers to extract from the dataset. If None, extracts all sweeps into
        a list. Default is the first sweep.

    first_dim : {"time", "auto"}, optional
        Defines the first dimension for each sweep. If "time," uses time as the
        first dimension. If "auto," determines the first dimension based on the sweep
        type (azimuth or elevation). Default is "auto."

    reindex_angle : bool or dict, optional
        Controls angle reindexing. If True or a dictionary, applies reindexing with
        specified settings (if given). Only used if `decode_coords=True`. Default is False.

    fix_second_angle : bool, optional
        If True, corrects errors in the second angle data, such as misaligned
        elevation or azimuth values. Default is False.

    site_as_coords : bool, optional
        Attaches radar site coordinates to the dataset if True. Default is True.

    optional : bool, optional
        If True, suppresses errors for optional dataset attributes, making them
        optional instead of required. Default is True.

    kwargs : dict
        Additional keyword arguments passed to `xarray.open_dataset`.

    Returns
    -------
    dtree : xarray.DataTree
        An `xarray.DataTree` representing the radar data organized by sweeps.

Plot Sweep Range vs. Time#

dtree["sweep_4"].ds.DBZH.sortby("time").plot(y="time", cmap="HomeyerRainbow")

<matplotlib.collections.QuadMesh at 0x7a1152f29310>

../_images/c560c1ac281d8e36ab57e0539c3ba20964f6b5e0b1f504c5a6d73fa2fcd3028c.png

Plot Sweep Range vs. Azimuth#

dtree["sweep_4"].ds.DBZH.plot(cmap="HomeyerRainbow")

<matplotlib.collections.QuadMesh at 0x7a1136f0e490>

../_images/2f70cb7158cc6e8797e3b6d16915234a07b7f3d4fd841c22e505a770afb449db.png

dtree["sweep_0"]["sweep_fixed_angle"].values

array(0.703125)

dtree["sweep_8"]["sweep_fixed_angle"].values

array(10.)

clean up#

import time

for node in dtree.values():
    if hasattr(node, "close"):
        node.close()
for file in tmpdir.iterdir():
    if file.is_file():
        for _ in range(5):
            try:
                file.unlink()
                break
            except PermissionError:
                time.sleep(0.5)