Annoy#

class scikitplot.cexternals.annoy.Annoy#

Compiled on GCC. Using 512-bit AVX instructions.

add_item()#

Adds item i (any nonnegative integer) with vector v.

Note that it will allocate memory for max(i)+1 items.

build()#

Builds a forest of n_trees trees.

More trees give higher precision when querying. After calling build, no more items can be added. n_jobs specifies the number of threads used to build the trees. n_jobs=-1 uses all available CPU cores.

f#: !! processed by numpydoc !!

get_distance()#: Returns the distance between items i and j.

get_item_vector()#: Returns the vector for item i that was previously added.

get_n_items()#: Returns the number of items in the index.

get_n_trees()#: Returns the number of trees in the index.

get_nns_by_item()#

Returns the n closest items to item i.

Parameters:: search_k – the query will inspect up to search_k nodes.

search_k gives you a run-time tradeoff between better accuracy and speed. search_k defaults to n_trees * n if not provided.

Parameters:: include_distances – If True, this function will return a

2 element tuple of lists. The first list contains the n closest items. The second list contains the corresponding distances.

get_nns_by_vector()#

Returns the n closest items to vector vector.

Parameters:: search_k – the query will inspect up to search_k nodes.

search_k gives you a run-time tradeoff between better accuracy and speed. search_k defaults to n_trees * n if not provided.

Parameters:: include_distances – If True, this function will return a

2 element tuple of lists. The first list contains the n closest items. The second list contains the corresponding distances.

load()#: Loads (mmaps) an index from disk.

on_disk_build()#: Build will be performed with storage on disk instead of RAM.

save()#: Saves the index to disk.

set_seed()#: Sets the seed of Annoy’s random number generator.

unbuild()#

Unbuilds the tree in order to allows adding new items.

build() has to be called again afterwards in order to run queries.

unload()#: Unloads an index from disk.

verbose()#

Annoy#

This Page