Generic

docs/user-guide/generic.md

@@ -10,16 +10,26 @@ The generic module contains functionality that works for all types of dfs (dfs0,
 * [`avg_time()`](`mikeio.generic.avg_time`) - Create a temporally averaged dfs file
 * [`quantile()`](`mikeio.generic.quantile`) - Create a dfs file with temporal quantiles
 
+## When to use the generic module
 
+* The processing is not tied to the spatial dimension of the data
+* When the files are large and you want to avoid reading the entire file into memory
 
-All methods in the generic module creates a new dfs file.
+## When not to use the generic module
+
+* When you need processing depending on the spatial information in the file. For example, spatial interpolation, subsetting, etc.
+* When you need more complex processing, not covered by the generic module
+* When the input files data are not dfs files
+* When the end result is not a dfs file
+
+## Example
 
 ```python
 >>> from mikeio import generic
 >>> generic.concat(["fileA.dfs2", "fileB.dfs2"], "new_file.dfs2")
 ```
 
-## Generic example notebooks
+## More examples
 
 See the [Generic notebook](../examples/Generic.qmd) for more examples.