v0.0.0.9006

New features

• Highly experimental mixed data type support for metric: instead of specifying a single metric name (e.g. metric = "euclidean"), you can pass a list, where the name of each item is the metric to use and the value is a vector of the names of the columns to use with that metric, e.g. metric = list("euclidean" = c("A1", "A2"), "cosine" = c("B1", "B2", "B3")) treats columns A1 and A2 as one block, using the Euclidean distance to find nearest neighbors, whereas B1, B2 and B3 are treated as a second block, using the cosine distance.
• Factor columns can also be used in the metric, using the metric name categorical.
• y may now be a data frame or matrix if multiple target data is available.
• New parameter target_metric, to specify the distance metric to use with numerical y. This has the same capabilities as metric.
• Multiple external nearest neighbor data sources are now supported. Instead of passing a list of two matrices, pass a list of lists, one for each external metric.
• More details on mixed data types can be found at https://github.com/jlmelville/uwot#mixed-data-types.
• Compatibility with older versions of RcppParallel (contributed by sirusb).
• scale = "Z" To Z-scale each column of input (synonym for scale = TRUE or scale = "scale").
• New scaling option, scale = "colrange" to scale columns in the range (0, 1).