Commit 43f16298 authored by floriandeboissieu's avatar floriandeboissieu

modified PCA param section in vignette

parent cb23d901
......@@ -83,10 +83,13 @@ In this example, the spatial resolution of the input raster is 10m. Setting `win
window_size = 10
```
## PCA filtering
If set to `TRUE`, a second filtering based on PCA outliers is processed.
## PCA
These parameters are related to the PCA method (`PCA` or `SPCA`, default is `SPCA`) and the filtering of PCA results.
Set FilterPCA to `TRUE` if a second filtering based on PCA outliers is required.
```{r PCA filtering}
```{r PCA method and filtering}
TypePCA = 'SPCA'
FilterPCA = FALSE
```
......@@ -146,7 +149,7 @@ Here is the code to perform PCA and select PCA bands:
```{r PCA}
print("PERFORM PCA ON RASTER")
PCA_Output = perform_PCA(Input_Image_File, Input_Mask_File, Output_Dir,
FilterPCA = TRUE, nbCPU = nbCPU,MaxRAM = MaxRAM)
TypePCA = TypePCA, FilterPCA = TRUE, nbCPU = nbCPU,MaxRAM = MaxRAM)
# path for the PCA raster
PCA_Files = PCA_Output$PCA_Files
# number of pixels used for each partition used for k-means clustering
......@@ -214,7 +217,6 @@ The following code computes $\alpha$ and $\beta$ diversity from field plots and
```{r alpha and beta diversity indices from vector layer}
# location of the spectral species raster needed for validation
TypePCA = 'SPCA'
Dir.Raster = file.path(Output.Dir,basename(Input.Image.File),TypePCA,'SpectralSpecies')
Name.Raster = 'SpectralSpecies'
Path.Raster = file.path(Dir.Raster,Name.Raster)
......
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