Bug in Either map_over_sweeps or in to_cfradial1

[syedhamidali]

• xradar version: 0.8.1
• Python version: 3.12.7
• Operating System: MacOS

Description

When applying any operation on a datatree using map_over_sweeps, and then try to export it to cfradial1, it produces an error, although they look identical when compared to each other.

What I Did

import cmweather
import numpy as np
import xarray as xr
import xradar as xd
from open_radar_data import DATASETS
xd.__version__

'0.8.1.dev7+g830d86b'

file = DATASETS.fetch("swx_20120520_0641.nc")

dtree = xd.io.open_cfradial1_datatree(file)

xd.io.to_cfradial1(dtree, filename='test_cfradial1.nc')

dtree2 = xd.io.open_cfradial1_datatree("test_cfradial1.nc")

np.testing.assert_equal(dtree.groups, dtree2.groups)

np.testing.assert_equal(dtree, dtree2)

xd.io.to_cfradial1(dtree2, filename='test_cfradial2.nc')

dtree3 = dtree.xradar.georeference()
dtree3['sweep_0']['corrected_reflectivity_horizontal'].plot(x='x', y='y', vmin=-10, vmax=75, cmap='NWSRef')

def filter_radar(ds, vel_name='VELH', ref_name='DBZH'):
    vel_texture = ds[vel_name].rolling(range=30, min_periods=2, center=True).std()
    ds = ds.assign(velocity_texture=vel_texture)
    ds = ds.where((ds.velocity_texture<10) & ((ds[ref_name]>=-10) & (ds[ref_name]<=75)))
    return ds

dtree3 = dtree3.xradar.map_over_sweeps(filter_radar,
                                       vel_name='mean_doppler_velocity',
                                       ref_name='corrected_reflectivity_horizontal')

dtree3['sweep_0']['corrected_reflectivity_horizontal'].plot(x='x', y='y', vmin=-10, vmax=75, cmap='NWSRef')

xd.io.to_cfradial1(dtree3, 'test_cfradial_filt.nc')

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[37], line 1
----> 1 xd.io.to_cfradial1(dtree3, 'test_cfradial_filt.nc')

File ~/micromamba/envs/xradar_latest/lib/python3.12/site-packages/xradar/io/export/cfradial1.py:298, in to_cfradial1(dtree, filename, calibs)
    283 """
    284 Convert a radar xarray.DataTree to the CFRadial1 format
    285 and save it to a file. Ensure that the resulting dataset
   (...)
    295     Whether to include calibration parameters.
    296 """
    297 # Generate the initial ds_cf using the existing mapping functions
--> 298 dataset = _variable_mapper(dtree)
    300 # Handle calibration parameters
    301 if calibs:

File ~/micromamba/envs/xradar_latest/lib/python3.12/site-packages/xradar/io/export/cfradial1.py:105, in _variable_mapper(dtree, dim0)
     88 def _variable_mapper(dtree, dim0=None):
     89     """
     90     Map radar variables for different sweep groups.
     91 
   (...)
    102         Dataset containing mapped radar variables.
    103     """
--> 105     sweep_info = _sweep_info_mapper(dtree)
    106     vol_info = _main_info_mapper(dtree)
    107     if "fixed_angle" in vol_info:

File ~/micromamba/envs/xradar_latest/lib/python3.12/site-packages/xradar/io/export/cfradial1.py:198, in _sweep_info_mapper(dtree)
    184 sweep_vars = [
    185     "sweep_number",
    186     "sweep_mode",
   (...)
    192     "sweep_end_ray_index",
    193 ]
    195 for var_name in sweep_vars:
    196     var_data_list = [
    197         (
--> 198             np.unique(dtree[s][var_name].values[np.newaxis, ...])
    199             if var_name in dtree[s]
    200             else np.array([np.nan])
    201         )
    202         for s in dtree.groups
    203         if "sweep" in s
    204     ]
    206     var_attrs_list = [
    207         dtree[s][var_name].attrs if var_name in dtree[s] else {}
    208         for s in dtree.groups
    209         if "sweep" in s
    210     ]
    212     if not var_data_list:

File ~/micromamba/envs/xradar_latest/lib/python3.12/site-packages/numpy/lib/_arraysetops_impl.py:289, in unique(ar, return_index, return_inverse, return_counts, axis, equal_nan)
    287 ar = np.asanyarray(ar)
    288 if axis is None:
--> 289     ret = _unique1d(ar, return_index, return_inverse, return_counts, 
    290                     equal_nan=equal_nan, inverse_shape=ar.shape, axis=None)
    291     return _unpack_tuple(ret)
    293 # axis was specified and not None

File ~/micromamba/envs/xradar_latest/lib/python3.12/site-packages/numpy/lib/_arraysetops_impl.py:356, in _unique1d(ar, return_index, return_inverse, return_counts, equal_nan, inverse_shape, axis)
    354     aux = ar[perm]
    355 else:
--> 356     ar.sort()
    357     aux = ar
    358 mask = np.empty(aux.shape, dtype=np.bool)

TypeError: '<' not supported between instances of 'float' and 'str'

xr.testing.assert_identical(dtree['sweep_0'], dtree3['sweep_0'])

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
Cell In[43], line 1
----> 1 xr.testing.assert_identical(dtree['sweep_0'], dtree3['sweep_0'])

    [... skipping hidden 1 frame]

File ~/micromamba/envs/xradar_latest/lib/python3.12/site-packages/xarray/testing/assertions.py:181, in assert_identical(a, b)
    179     assert a.identical(b), formatting.diff_coords_repr(a, b, "identical")
    180 elif isinstance(a, DataTree):
--> 181     assert a.identical(b), diff_datatree_repr(a, b, "identical")
    182 else:
    183     raise TypeError(f"{type(a)} not supported by assertion comparison")

AssertionError: Left and right DataTree objects are not identical

Data at root node does not match:
    Differing data variables:
    L   diff_reflectivity                  (azimuth, range) float32 1MB 0.0 ... 0.0
    R   diff_reflectivity                  (azimuth, range) float32 1MB 0.0 ... nan
    L   recalculated_diff_phase            (azimuth, range) float32 1MB -0.0 ... ...
    R   recalculated_diff_phase            (azimuth, range) float32 1MB -0.0 ... nan
    L   diff_phase                         (azimuth, range) float32 1MB 0.0 ... nan
    R   diff_phase                         (azimuth, range) float32 1MB 0.0 ... nan
    L   proc_dp_phase_shift                (azimuth, range) float32 1MB 18.09 ......
    R   proc_dp_phase_shift                (azimuth, range) float32 1MB 18.09 ......
    L   corrected_reflectivity_horizontal  (azimuth, range) float32 1MB -5.617 .....
    R   corrected_reflectivity_horizontal  (azimuth, range) float32 1MB -5.617 .....
    L   specific_attenuation               (azimuth, range) float32 1MB 0.0004272...
    R   specific_attenuation               (azimuth, range) float32 1MB 0.0004272...
    L   mean_doppler_velocity              (azimuth, range) float32 1MB 0.0 ... -...
    R   mean_doppler_velocity              (azimuth, range) float32 1MB 0.0 ... nan
    L   rain_rate_A                        (azimuth, range) float32 1MB 0.0625 .....
    R   rain_rate_A                        (azimuth, range) float32 1MB 0.0625 .....
    L   norm_coherent_power                (azimuth, range) float32 1MB 1.0 ... 0.17
    R   norm_coherent_power                (azimuth, range) float32 1MB 1.0 ... nan
    L   copol_coeff                        (azimuth, range) float32 1MB 1.0 ... nan
    R   copol_coeff                        (azimuth, range) float32 1MB 1.0 ... nan
    L   sweep_mode                         <U20 80B 'azimuth_surveillance'
    R   sweep_mode                         (azimuth, range) object 2MB 'azimuth_s...
    L   sweep_fixed_angle                  float64 8B 0.5
    R   sweep_fixed_angle                  (azimuth, range) float64 2MB 0.5 ... nan
    L   sweep_number                       int32 4B 0
    R   sweep_number                       (azimuth, range) float64 2MB 0.0 ... nan
    L   unf_dp_phase_shift                 (azimuth, range) float32 1MB 0.0 ... 28.4
    R   unf_dp_phase_shift                 (azimuth, range) float32 1MB 0.0 ... nan
    L   dp_phase_shift                     (azimuth, range) float32 1MB 90.0 ... nan
    R   dp_phase_shift                     (azimuth, range) float32 1MB 90.0 ... nan
    L   reflectivity_horizontal            (azimuth, range) float32 1MB -6.203 .....
    R   reflectivity_horizontal            (azimuth, range) float32 1MB -6.203 .....
    Data variables only on the right object:
        velocity_texture                   (azimuth, range) float32 1MB 4.744 ......

I tried it on another dataset, and even though they look identical, they still can’t be exported or transformed to cfradial1 after applying any operation using map_over_sweeps