User Guide#
In this section we provide material how to use xradar.
Most of the material is distributed as jupyter notebooks to be able to interactively explore xradar functionality.
To use xradar in a project:
import xradar
Get started
- Data Model
- Importers
- Exporters
- Name mapping between formats
open_datatreewithengine=- Supported engines
- ODIM_H5
- CfRadial1
- CfRadial2
- NEXRAD Level II
- GAMIC
- IRIS
- Furuno
- Rainbow
- DataMet
- HPL (Halo Photonics)
- Metek MRR
- Universal Format (UF)
- IMD - single file via
engine="imd" - IMD - multi-file volume
- Common parameters
open_groups_as_dict— work with the raw dict- Deprecated
open_*_datatreeshims - Without
engine= - Files with one sweep each
- Unknown engine
- Open any format without
engine - Accessors
- Map Over Sweeps
- CfRadial1 to CfRadial2
Backends
Examples
- Assign GeoCoords
- Reproject Radar Coordinates
- Imports
- Read a sample radar file
- 1. Default georeferencing (AEQD, meters)
- 2. Reproject to geographic lon/lat (EPSG:4326)
- 3. Reproject to a projected CRS (UTM, Web Mercator)
- 4. Plot on a cartopy map
- 5. Side-by-side comparison of projections
- 6. Radar data on different map projections
- 7. Works on a single Dataset too
- Summary
- CfRadial1 - Export
- Work with AWS
- Plan Position Indicator
- Angle Reindexing
- NDPointIndex
- Step-by-step guide
- Timeseries of Sweeps
- Gridding with Py-ART and wradlib
- AWS Volumes to ARCO
- CfRadial1 <-> CfRadial2