# PYODIM
A simple ODIM H5 (Opera Data Information Model - Hierarchical Data Format
version 5) radar reader in Python. It outputs the radar date in an xarray
Dataset. The goal is to be as barebone as possible while providing an xarray,
so that it can easily scale up (production) or just a very lean reader for
quicklooks into the data.
## Example
```python
import pyodim
filename = "/path/to/radar/file.h5"
rset = pyodim.read_odim(filename, lazy_load=True) # Lazy load does not load the data in memory to save time if you are interested in only a specific sweep
radar = rset[0].compute() # All sweeps are in a list (elevation ascending), so the 1st item of the list is the bottom sweep.
print(radar)
```
This code will output the radar data for the first sweep (lowest elevation
scan) in the radar file as an xarray Dataset, for example:
```python
<xarray.Dataset>
Dimensions: (azimuth: 360, range: 1283, elevation: 1, time: 360)
Coordinates:
* range (range) float32 125.0 375.0 625.0 ... 3.204e+05 3.206e+05
* azimuth (azimuth) float32 0.01111 1.011 2.011 ... 357.0 358.0 359.0
* elevation (elevation) float32 0.5
* time (time) datetime64[ns] 2024-01-16T02:49:29.337047353 ... 2024-...
Data variables: (12/17)
DBZH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan
SNRH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan
VRADH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan
WRADH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan
KDP (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan
... ...
x (azimuth, range) float32 0.02424 0.07271 ... -5.595e+03
y (azimuth, range) float32 125.0 375.0 ... 3.203e+05 3.206e+05
z (azimuth, range) float32 45.09 47.27 ... 2.84e+03 2.842e+03
longitude (azimuth, range) float32 144.8 144.8 144.8 ... 144.7 144.7 144.7
latitude (azimuth, range) float32 -37.85 -37.85 -37.85 ... -34.97 -34.96
Attributes: (12/15)
Conventions: ODIM_H5/V2_4
latitude: -37.85200119018555
longitude: 144.75199890136722
height: 44.0
date: 2024-01-16T02:45:21
object: PVOL
... ...
beamwV: 1.0
wavelength: 10.489999771118164
NI: 36.5052
highprf: 696.0
start_time: 20240116_024928
end_time: 20240116_024958
```
PYODIM reads the ODIM radar data and metadata. It also provides some quality of
life feature like automatically creating the x, y, z and latitude/longitude
coordinates for all radar gates (using the azimuthal equidistant - `aeqd` - projection). By
default it uses `dask.delayed` to *lazily* load the data, meaning that it will
not actually load all the sweeps in memory, as for many applications we often
don't need all the radar sweeps. Instead, by calling the `.compute()` method
like in the example above, PYODIM will only read and load in memory the sweep
that you want, saving time. If you want to read all the sweeps at once in a
list, then just set `lazy_load=False`.
## Dependencies
Mandatory:
- [numpy][1]
- [xarray][2]
- [pyproj][3]
- [dask][4]
And optionally (it will automatically populate the fields metadata using pyart
if available):
- [Py-ART][5]
[1]: http://www.scipy.org/
[2]: http://numba.pydata.org
[3]: https://pypi.org/project/pyproj/
[4]: https://www.dask.org/
[5]: https://github.com/ARM-DOE/pyart
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"description": "# PYODIM\r\n\r\nA simple ODIM H5 (Opera Data Information Model - Hierarchical Data Format \r\nversion 5) radar reader in Python. It outputs the radar date in an xarray \r\nDataset. The goal is to be as barebone as possible while providing an xarray, \r\nso that it can easily scale up (production) or just a very lean reader for \r\nquicklooks into the data.\r\n\r\n## Example\r\n\r\n```python\r\n\r\nimport pyodim\r\n\r\nfilename = \"/path/to/radar/file.h5\"\r\nrset = pyodim.read_odim(filename, lazy_load=True) # Lazy load does not load the data in memory to save time if you are interested in only a specific sweep\r\nradar = rset[0].compute() # All sweeps are in a list (elevation ascending), so the 1st item of the list is the bottom sweep.\r\nprint(radar)\r\n```\r\n\r\nThis code will output the radar data for the first sweep (lowest elevation \r\nscan) in the radar file as an xarray Dataset, for example:\r\n\r\n```python\r\n<xarray.Dataset>\r\nDimensions: (azimuth: 360, range: 1283, elevation: 1, time: 360)\r\nCoordinates:\r\n * range (range) float32 125.0 375.0 625.0 ... 3.204e+05 3.206e+05\r\n * azimuth (azimuth) float32 0.01111 1.011 2.011 ... 357.0 358.0 359.0\r\n * elevation (elevation) float32 0.5\r\n * time (time) datetime64[ns] 2024-01-16T02:49:29.337047353 ... 2024-...\r\nData variables: (12/17)\r\n DBZH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan\r\n SNRH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan \r\n VRADH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan\r\n WRADH (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan\r\n KDP (azimuth, range) float64 nan nan nan nan nan ... nan nan nan nan\r\n ... ...\r\n x (azimuth, range) float32 0.02424 0.07271 ... -5.595e+03\r\n y (azimuth, range) float32 125.0 375.0 ... 3.203e+05 3.206e+05\r\n z (azimuth, range) float32 45.09 47.27 ... 2.84e+03 2.842e+03\r\n longitude (azimuth, range) float32 144.8 144.8 144.8 ... 144.7 144.7 144.7\r\n latitude (azimuth, range) float32 -37.85 -37.85 -37.85 ... -34.97 -34.96\r\nAttributes: (12/15)\r\n Conventions: ODIM_H5/V2_4\r\n latitude: -37.85200119018555\r\n longitude: 144.75199890136722\r\n height: 44.0\r\n date: 2024-01-16T02:45:21\r\n object: PVOL\r\n ... ...\r\n beamwV: 1.0\r\n wavelength: 10.489999771118164\r\n NI: 36.5052\r\n highprf: 696.0\r\n start_time: 20240116_024928\r\n end_time: 20240116_024958\r\n```\r\n\r\nPYODIM reads the ODIM radar data and metadata. It also provides some quality of \r\nlife feature like automatically creating the x, y, z and latitude/longitude \r\ncoordinates for all radar gates (using the azimuthal equidistant - `aeqd` - projection). By \r\ndefault it uses `dask.delayed` to *lazily* load the data, meaning that it will \r\nnot actually load all the sweeps in memory, as for many applications we often \r\ndon't need all the radar sweeps. Instead, by calling the `.compute()` method \r\nlike in the example above, PYODIM will only read and load in memory the sweep \r\nthat you want, saving time. If you want to read all the sweeps at once in a \r\nlist, then just set `lazy_load=False`.\r\n\r\n## Dependencies\r\n\r\nMandatory:\r\n- [numpy][1]\r\n- [xarray][2]\r\n- [pyproj][3]\r\n- [dask][4]\r\n\r\nAnd optionally (it will automatically populate the fields metadata using pyart \r\nif available): \r\n- [Py-ART][5] \r\n\r\n[1]: http://www.scipy.org/\r\n[2]: http://numba.pydata.org\r\n[3]: https://pypi.org/project/pyproj/\r\n[4]: https://www.dask.org/\r\n[5]: https://github.com/ARM-DOE/pyart\r\n",
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