Skipped python 2.7
@@ -11,6 +11,7 @@ source:
build:
number: 0
+ skip: true # [py27]
requirements:
build:
@@ -41,15 +42,20 @@ test:
about:
home: https://github.com/stat-ml/ncvis
- license_file: LICENSE
+ license_file:
+ - LICENSE
+ - lib/hnswlib/LICENSE
+ - lib/pcg-cpp/LICENSE-APACHE.txt
license: MIT
license_family: MIT
summary: 'Efficient solution for data visualization'
description: |
NCVis is an efficient solution for data visualization and dimensionality
- reduction. It uses HNSW to quickly construct the nearest neighbors graph
- and a parallel (batched) approach to build its embedding.
+ reduction. It uses HNSW <https://github.com/nmslib/hnswlib> to quickly
+ construct the nearest neighbors graph and a parallel (batched) approach
+ to build its embedding. Efficient random sampling is achieved via
+ PCGRandom <https://github.com/imneme/pcg-cpp>.
doc_url: https://github.com/stat-ml/ncvis-examples
dev_url: https://github.com/stat-ml/ncvis
