From d44782e11c14d533f796072762ce18b9ba0646c9 Mon Sep 17 00:00:00 2001 From: Leland McInnes Date: Sat, 14 Nov 2015 20:29:58 -0500 Subject: [PATCH] Update docs and requirements as we move to 0.5 --- README.rst | 16 +++++++++++++--- requirements.txt | 3 +++ setup.py | 2 +- 3 files changed, 17 insertions(+), 4 deletions(-) diff --git a/README.rst b/README.rst index a2124b6f..ce839de2 100644 --- a/README.rst +++ b/README.rst @@ -38,11 +38,12 @@ Performance ----------- Significant effort has been put into making the hdbscan implementation as fast as -possible. It is more than twice as fast as the reference implementation in Java +possible. It is more than ten as fast as the reference implementation in Java (full +benchmarks forthcoming), and is currently faster highly optimized single linkage implementations in C and C++. `version 0.3 performance can be seen in this notebook `_ . -Version 0.4 brings a new minimum spanning tree algorithm and dramatic speedups, particularly -for low dimensional data. +Versions 0.4 and 0.5 bring a new minimum spanning tree algorithm, and further +optimizations that provide dramatic speedups, particularly for low dimensional data. ------------------------ Additional functionality @@ -105,6 +106,15 @@ Fast install, presuming you have sklearn and all its requirements installed: pip install hdbscan +If pip is having difficulties pulling the dependencies then we'd suggest installing +the dependencies manually using anaconda followed by pulling hdscan from pip: + +.. code:: bash + + conda install cython + conda install sklearn + pip install hdbscan + For a manual install get this package: .. code:: bash diff --git a/requirements.txt b/requirements.txt index 4e460b25..d0b38b4a 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,5 @@ +cython>=0.22 +numpy>=1.9 +scipy >= 0.9 scikit-learn>=0.16 diff --git a/setup.py b/setup.py index cb3f017a..10e27ad1 100644 --- a/setup.py +++ b/setup.py @@ -34,7 +34,7 @@ def readme(): configuration = { 'name' : 'hdbscan', - 'version' : '0.4.2', + 'version' : '0.5', 'description' : 'Clustering based on density with variable density clusters', 'long_description' : readme(), 'classifiers' : [