Probelm in pyart.map.grid_from_radars when I created a radar object with pyart.testing.make_empty_ppi_radar

[gokul123kit]

I have a Netcdf file with radar variables with 240 grids(range dimension), 361 azimuth (dimension) and 14 elevation(Sweep) finally the reflectivity with shape (240, 361, 14) . Then I created a radar object with using pyart.testing.make_empty_ppi_radar. with shape

radar = pyart.testing.make_empty_ppi_radar(240, 361, 14)

and added the field as mentioned in "Basic ingest of a netcdf file" https://arm-doe.github.io/pyart/notebooks/basic_ingest_using_test_radar_object.html (But the example only contain 1 sweep( elevation))

after creating the radar object I tried to grid it with pyart.map.grid_from_radars

grid_shape = (41, 480, 480)
grid_limits = ((0, 10000), (-120000.0, 120000.0), (-120000.0, 120000.0))
grid_roi = 2000

```python
grid = pyart.map.grid_from_radars(
        [radar],
        grid_shape = grid_shape,
        grid_limits = grid_limits,
        weighting_function = 'Barnes',
        gridding_algo = 'map_gates_to_grid',
        roi_func='constant', constant_roi = grid_roi,
        fields=['reflectivity'])

and got the error

ValueError Traceback (most recent call last)

Cell In[605], line 1
----> 1 grid = pyart.map.grid_from_radars(
      2         [radar],
      3         grid_shape = grid_shape,
      4         grid_limits = grid_limits,
      5         weighting_function = 'Barnes',
      6         gridding_algo = 'map_gates_to_grid',
      7         roi_func='constant', constant_roi = grid_roi,
      8         fields=['reflectivity'])


File ~\AppData\Local\anaconda3\Lib\site-packages\pyart\map\grid_mapper.py:93, in grid_from_radars(radars, grid_shape, grid_limits, gridding_algo, copy_field_dtypes, **kwargs)
     91     grids = map_to_grid(radars, grid_shape, grid_limits, **kwargs)
     92 elif gridding_algo == "map_gates_to_grid":
---> 93     grids = map_gates_to_grid(radars, grid_shape, grid_limits, **kwargs)
     94 else:
     95     raise ValueError("invalid gridding_algo")


File ~\AppData\Local\anaconda3\Lib\site-packages\pyart\map\gates_to_grid.py:169, in map_gates_to_grid(radars, grid_shape, grid_limits, grid_origin, grid_origin_alt, grid_projection, fields, gatefilters, map_roi, weighting_function, toa, roi_func, constant_roi, z_factor, xy_factor, min_radius, h_factor, nb, bsp, dist_factor, **kwargs)
    167 for i, field in enumerate(fields):
    168     fdata = radar.fields[field]["data"]
--> 169     field_data[:, :, i] = np.ma.getdata(fdata)
    170     field_mask[:, :, i] = np.ma.getmaskarray(fdata)
    172 # find excluded gates from the gatefilter


ValueError: could not broadcast input array from shape (240,361,14) into shape (5054,240)

How can I resolve this???? Gridding worked when I used one sweep but not for field with 14 sweeps

[zssherman]

@gokul123kit Hello! Question I had was, did reading in the file with read_cfradial not work? Second the reflectivity field needs to be two dimensional so in this case you would need to use the start and end sweepray index to plug in the reflectivity for each sweep. The error is most likely due to the 3 dimensions your using, were pyart expects two.

[gokul123kit]

1. my radar data is in .h5 format ('scan-ldr-120km-5_20001_20180606000836_00.h5') and could not import that in pyart, so I made .NC file with different radar data attributes and tried to make PPI from that.

2. So should I change My reflectivity with shape (240, 361, 14) to (240, 361) ?
   How can I give start and end sweepray index? Could you please give some information about that?

[zssherman]

@gokul123kit Did you try one of the h5 readers in Py-ART's Aux io module?

[gokul123kit]

Yes, This is the error I am getting

KeyError Traceback (most recent call last)
Cell In[17], line 4
1 file_path = 'L:/Measurements/Radar/dwsr-2501c/scan-ldr-120km-5/2021/06/23/scan-ldr-120km-5_20001_20210623162850_00.h5'
3 # Open the file with Py-ART's ODIM HDF5 reader
----> 4 radar = pyart.aux_io.read_odim_h5(file_path)

File ~\AppData\Local\anaconda3\Lib\site-packages\pyart\aux_io\odim_h5.py:164, in read_odim_h5(filename, field_names, additional_metadata, file_field_names, exclude_fields, include_fields, include_datasets, exclude_datasets, **kwargs)
162 # metadata
163 metadata = filemetadata("metadata")
--> 164 metadata["source"] = _to_str(hfile["what"].attrs["source"])
165 metadata["original_container"] = "odim_h5"
166 metadata["odim_conventions"] = _to_str(hfile.attrs["Conventions"])

File h5py\_objects.pyx:54, in h5py._objects.with_phil.wrapper()

File h5py\_objects.pyx:55, in h5py._objects.with_phil.wrapper()

File ~\AppData\Local\anaconda3\Lib\site-packages\h5py_hl\attrs.py:56, in AttributeManager.getitem(self, name)
52 @with_phil
53 def getitem(self, name):
54 """ Read the value of an attribute.
55 """
---> 56 attr = h5a.open(self._id, self._e(name))
57 shape = attr.shape
59 # shape is None for empty dataspaces

File h5py\_objects.pyx:54, in h5py._objects.with_phil.wrapper()

File h5py\_objects.pyx:55, in h5py._objects.with_phil.wrapper()

File h5py\h5a.pyx:80, in h5py.h5a.open()

KeyError: "Can't open attribute (can't locate attribute: 'source')"

[zssherman]

Gotcha, with your current work flow you can transpose you ref array so we can index it by sweep and plug that in by sweep like so:

from pyart.config import get_metadata
ref_dict = get_metadata("reflectivity")

new_ref = your_reflectivity_array.transpose(2, 1, 0)
ref = np.zeros((radar.nrays, radar.ngates))
for sweep in radar.sweep_number['data']:
    start, end = radar.get_start_end(sweep)
    ref[start:end+1, :] = new_ref[sweep]

ref_dict["data"] = ref
radar.fields = {"reflectivity": ref_dict}

I believe that should work...

[gokul123kit]

It worked, Thank you