Linting

doc/source/coregistration.md

@@ -167,7 +167,7 @@ See coregistration on real data in the **{ref}`examples-basic` and {ref}`example
 
 The [Nuth and Kääb (2011)](https://doi.org/10.5194/tc-5-271-2011) coregistration approach estimates a horizontal
 translation iteratively by solving a cosine equation between the terrain slope, aspect and the elevation differences.
-The iteration stops if it reaches the maximum number of iteration limit, or if the iterative shift amplitude falls 
+The iteration stops if it reaches the maximum number of iteration limit, or if the iterative shift amplitude falls
 below a specified tolerance.
 
 ```{code-cell} ipython3

doc/source/dem_class.md

@@ -178,7 +178,7 @@ print("Elevation errors at a distance of 1 km are correlated at {:.2f} %.".forma
 ```
 
 ```{note}
-We use `random_state` to ensure a fixed randomized output. It is **only necessary if you need your results to be exactly reproductible**. 
- 
+We use `random_state` to ensure a fixed randomized output. It is **only necessary if you need your results to be exactly reproductible**.
+
 For more details on quantifying random and structured errors, see the {ref}`uncertainty` page.
 ```

doc/source/ecosystem.md

@@ -28,7 +28,7 @@ wide range of terrain analysis for elevation data.
 
 ## R
 
-If you are working in R, the [MultiscaleDTM](https://ailich.github.io/MultiscaleDTM/) package provides modular tools 
+If you are working in R, the [MultiscaleDTM](https://ailich.github.io/MultiscaleDTM/) package provides modular tools
 for terrain analysis at multiple scales!
 
 ## Other community resources