# Reading Radolan RW files

**URL:** <https://openradar.discourse.group/t/reading-radolan-rw-files/39>\
**Category:** Openradar\
**Tags:** wradlib\
**Created:** [October 8, 2022, 5:53pm UTC](https://openradar.discourse.group/t/reading-radolan-rw-files/39 "2022-10-08T17:53:06Z")\
**Posts on this page:** 1\
**Showing post:** 8

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**Author:** ![kmuehlbauer](https://yyz2.discourse-cdn.com/free1/user_avatar/openradar.discourse.group/kmuehlbauer/32/439_2.png) [@kmuehlbauer](https://openradar.discourse.group/u/kmuehlbauer)\
**Post date:** [October 9, 2022, 3:38pm UTC](https://openradar.discourse.group/t/reading-radolan-rw-files/39/8 "2022-10-09T15:38:50Z")

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Hi Muru,

sorry that was my bad, I’ve made a mistake when adapting the solution from SO. I’ve fixed the notebook gist (see link above).

For corrected code to determine the wanted pixel see below. There are two changes. First, y/lat is the first dim of our 2d array. Second, we need to use `.isel` to select from the given index. The SO solution worked since in that example x and y didn’t have coordinates and a zero-based index is used with `.sel`.

```python
lat = 50.0
lon = 10.0

# find nearest xy-grid point to a specific latlon-coordinate   
abslat = np.abs(dsg.lat-lat)
abslon = np.abs(dsg.lon-lon)
c = np.maximum(abslon, abslat)

# Attention: y/lat is first dim, get
([yidx], [xidx]) = np.where(c == np.min(c))
    
# Select index location at the x/y dimension
# use isel as we select with index 
point_ds = dsg.isel(x=xidx, y=yidx)

display(point_ds.RW)

```

```auto
<xarray.DataArray 'RW' ()>
array(1.1, dtype=float32)
Coordinates:
    y float64 -4.326e+06
    x float64 37.83
    lon float64 9.994
    lat float64 50.0
Attributes:
    valid_min: 0
    valid_max: 4095
    standard_name: rainfall_rate
    long_name: RW
    unit: mm h-1    

```

As you can see, the lon/lat coordinates are now giving back our selected values (“nearest”).

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