Update NEWS and README for new release.

NEWS.md

@@ -1,8 +1,25 @@
+# uwot 0.0.0.9003 (September 22 2018)
+
+## New features
+
+* New parameter `ret_nn`: when `TRUE` returns nearest neighbor matrices
+as a `nn` list: indices in item `idx` and distances in item `dist`. Embedded
+coordinates are in `embedding`. Both `ret_nn` and `ret_model` can be `TRUE`,
+and should not cause any compatibility issues with supervised embeddings.
+* `nn_method` can now take precomputed nearest neighbor data. Must be a list of
+two matrices: `idx`, containing integer indexes, and `dist` containing 
+distances. By no coincidence, this is the format return by `ret_nn`.
+
+## Bug fixes and minor improvements
+
+* Embedding to `n_components = 1` was broken (https://github.com/jlmelville/uwot/issues/6)
+* User-supplied matrices to `init` parameter were being modified, in defiance of basic R pass-by-copy semantics.
+
 # uwot 0.0.0.9002 (August 14 2018)
 
 ## Bug fixes and minor improvements
 
-* `metric = "cosine"` is working again for `n_threads` greater than `0`. 
+* `metric = "cosine"` is working again for `n_threads` greater than `0` (https://github.com/jlmelville/uwot/issues/5)
 
 # uwot 0.0.0.9001
 

README.md

@@ -10,9 +10,13 @@ the basic method.
 
 ## News
 
-*August 14 2018*. I had broken `metric = cosine` for all cases except when
-specifying `n_threads = 0`. Thanks to [ONeillMB1](https://github.com/ONeillMB1) 
-for reporting this.
+*September 2018*. You can now return the nearest neighbor data via 
+`umap_result <- umap(..., ret_nn = TRUE)`, and it
+can be re-used by setting 
+`umap_newresult <- umap(..., nn_method = umap_result$nn)`. As the nearest
+neighbor calculations is likely to be the bottleneck with default settings, this
+can save a lot of time if you are fiddling with epochs, initialization, output
+distance functions and so on. It also works with `lvish`.
 
 ## Installing
 
@@ -50,8 +54,18 @@ mnist_train <- head(mnist, 60000)
 mnist_test <- tail(mnist, 70000)
 
 # You must set ret_model = TRUE to return extra data we need
+# coordinates are in mnist_train_umap$embedding
 mnist_train_umap <- umap(mnist_train, verbose = TRUE, ret_model = TRUE)
 mnist_test_umap <- umap_transform(mnist_test, mnist_train_umap, verbose = TRUE)
+
+# Save the nearest neighbor data
+mnist_nn <- umap(mnist, ret_nn = TRUE)
+# coordinates are now in mnist_nn$embedding
+
+# Re-use the nearest neighor data and save a lot of time
+mnist_nn_spca <- umap(mnist, nn_method = mnist_nn$nn, init = spca)
+
+# No problem to have ret_nn = TRUE and ret_model = TRUE at the same time
 ```
 
 ## Documentation