NumCpp
EiGen
| NumCpp | EiGen | |
|---|---|---|
| 4 | 1 | |
| 3,641 | 2 | |
| 1.6% | - | |
| 2.5 | 8.9 | |
| 9 days ago | 5 months ago | |
| C++ | C | |
| MIT License | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
NumCpp
-
Machine Learning using C++ vs Python
Yeah, as someone who writes C++ daily for their ML related job, I concur that the cost of executing a convolutions dwarves the overhead of calling from Python. So as much as I like C++ over Python (because static compilation to find little typos or type mismatches ahead of time is much nicer than exploding 5 minutes later into my batched vision recognition problem 😠), generally for small problems, Python is a nice quick and dirty approach. I do have my eye though on this little C++ numpy clone.
-
Can i use numpy with c or c++ ?
Despite being written in C itself, the primary external API is for Python, and though it is possible to call via C, it's quite ungainly (several ref-counted Py_* calls and structs). It's probably easier to just consume a library that targets C++ directly like xtensor (https://xtensor.readthedocs.io/en/latest/numpy.html) or NumCpp (https://github.com/dpilger26/NumCpp).
-
trouble with linspace functions
I am trying to feed 2 different 3 column 1 row arrays into a linspace function using the NumCPP package, but i'm getting errors such as:
- Read python pickle files in C++
EiGen
-
Tilde, My LLVM Alternative
Cool. The author has set himself a huge task if he wants to build something like LLVM. An alternative would be to participate in a project with similar goals that is already quite progressed, such as QBE or Eigen (https://github.com/EigenCompilerSuite/); both so far lack optimizers. I consider Eigen very attractive because it supports much more targets and includes assemblers and linkers for all targets. I see the advantage in having a C implementation; Eigen is unfortunately developed in C++17, but I managed to backport the parts I'm using to a moderate C++11 subset (https://github.com/rochus-keller/Eigen). There are different front-ends available, two C compilers among them. And - as mentioned - an optimizer would be great.
What are some alternatives?
eigen
parallel-hashmap - A family of header-only, very fast and memory-friendly hashmap and btree containers.
RxCpp - Reactive Extensions for C++
vinum - Vinum is a SQL processor for Python, designed for data analysis workflows and in-memory analytics.
examples - Example data structures and algorithms
casadi - CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
Tiger - C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators
tuninglib - A C++ Class and Template Library for Performance Critical Applications
Data-Structures-and-Algorithms - Data Structures and Algorithms implemented In Python, C, C++, Java or any other languages. Aimed to help strengthen the concepts of DSA. Give a Star 🌟 if it helps you.
tfds - A collection of data structures in C++
pymport - Use Python libraries from Node.js
data-structures-and-algorithms - Database of well known algorithms organized by category.