create_umap | R Documentation |
Proportional sample exposures will be used as input into the
umap
function to generate a two dimensional UMAP.
create_umap(
musica,
model_name,
modality = "SBS96",
result_name = "result",
n_neighbors = 30,
min_dist = 0.75,
spread = 1
)
musica |
A |
model_name |
The name of the desired model. |
modality |
The modality of the model. Must be "SBS96", "DBS78", or
"IND83". Default |
result_name |
Name of the result list entry containing the model.
Default |
n_neighbors |
The size of local neighborhood used for views of
manifold approximation. Larger values result in more global the manifold,
while smaller values result in more local data being preserved.
If |
min_dist |
The effective minimum distance between embedded points.
Smaller values will result in a more clustered/clumped embedding where
nearby points on the manifold are drawn closer together, while larger
values will result on a more even dispersal of points. Default |
spread |
The effective scale of embedded points. In combination with
‘min_dist’, this determines how clustered/clumped the embedded points are.
Default |
A musica
object with a new UMAP
stored in the UMAP
slot of the result_model
object for the model.
See plot_umap to display the UMAP and
umap
for more information on the individual parameters
for generating UMAPs.
data(res_annot)
create_umap(res_annot, model_name = "res_annot")
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