update README

README.Rmd

@@ -27,7 +27,7 @@ The R package fCWTr is a simple wrapper invoking the [fCWT library](https://gith
 
 See the original paper by Arts, L.P.A., van den Broek, E.L. The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time–frequency analysis. Nat Comput Sci 2, 47–58 (2022). <https://doi.org/10.1038/s43588-021-00183-z>
 
-## Dependencies
+## System dependencies
 
 -   R \>= 4.1
 -   [fftw](https://www.fftw.org/) library (used by [fCWT](https://github.com/fastlib/fCWT))
@@ -94,7 +94,7 @@ We can also directly plot the resulting scalogram:
 plot(output, time_unit = "ms")
 ```
 
-For long sequences, the required memory can exceed your local memory. In this case it can be useful to reduce the time resolution of the result and process the data in batches. This can be done with `fcwt_batch()`. In case the batch size is not explicitly provided, some heuristics are used to determine a batch size automatically:
+For long sequences, the required memory can exceed your available local memory. In this case it can be useful to reduce the time resolution of the result and process the data in batches. This can be done with `fcwt_batch()`. In case the batch size is not explicitly provided, some heuristics are used to determine a batch size automatically:
 
 ```{r example_long_df, results='hide'}
 batch_result <-

README.md

@@ -27,7 +27,7 @@ continuous wavelet transformation (fCWT) for real-time, high-quality,
 noise-resistant time–frequency analysis. Nat Comput Sci 2, 47–58 (2022).
 <https://doi.org/10.1038/s43588-021-00183-z>
 
-## Dependencies
+## System dependencies
 
 - R \>= 4.1
 - [fftw](https://www.fftw.org/) library (used by
@@ -121,11 +121,11 @@ plot(output, time_unit = "ms")
 
 <img src="man/figures/README-example_plot-1.png" width="100%" />
 
-For long sequences, the required memory can exceed your local memory. In
-this case it can be useful to reduce the time resolution of the result
-and process the data in batches. This can be done with `fcwt_batch()`.
-In case the batch size is not explicitly provided, some heuristics are
-used to determine a batch size automatically:
+For long sequences, the required memory can exceed your available local
+memory. In this case it can be useful to reduce the time resolution of
+the result and process the data in batches. This can be done with
+`fcwt_batch()`. In case the batch size is not explicitly provided, some
+heuristics are used to determine a batch size automatically:
 
 ``` r
 batch_result <-