From c8ce35bf9b506beec81232b19cfaf57e178e4e85 Mon Sep 17 00:00:00 2001 From: Hans Dembinski Date: Sun, 10 Apr 2016 13:21:48 -0400 Subject: [PATCH] tweaking readme --- README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index de49fc56..ec71af79 100644 --- a/README.md +++ b/README.md @@ -19,8 +19,9 @@ My goal is to submit this project to the [Boost](http://www.boost.org) libraries * N-dimensional histogram * Intuitive and convenient interface, everything *just works* * Support for different binning scenarios, including binning of angles -* High-performance, cache-friendly design -* Space-efficient memory storage +* Optional underflow- and overflow-bins +* High-performance through cache-friendly design +* Space-efficient memory storage that dynamically grows as needed * Serialization support with zero-suppression * Multi-language support: C++ and Python * Numpy support @@ -50,7 +51,7 @@ I designed the histogram based on a decade of experience collected in working wi ### Interface convenience, language transparency -A histogram should have the same consistent interface whatever the dimension. Like `std::vector` it should *just work*, users shouldn't be forced to make *a priori* choices among several histogram classes and options everytime they encounter a new data set. Python is a great language for data analysis, so the histogram should have Python bindings. Data analysis in Python is Numpy-based, so Numpy support is a must. The histogram should be usable as an interface between a complex simulation or data-storage system written in C++ and data-analysis/plotting in Python: define the histogram in Python, let it be filled on the C++ side, and then get it back for further data analysis or plotting. +A histogram should have the same consistent interface whatever the dimension. Like `std::vector` it should *just work*, users shouldn't be forced to make *a priori* choices among several histogram classes and options everytime they encounter a new data set. Python is a great language for data analysis, so the histogram needs Python bindings. Data analysis in Python is Numpy-based, so Numpy support is a must. The histogram should be usable as an interface between a complex simulation or data-storage system written in C++ and data-analysis/plotting in Python: define the histogram in Python, let it be filled on the C++ side, and then get it back for further data analysis or plotting. ### Powerful binning strategies