Search Results for "numpy array"
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Showing 17 open source projects for "numpy array"
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NumPy
The fundamental package for scientific computing with Python
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. -
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Awkward Array
Manipulate JSON-like data with NumPy-like idioms
Awkward Array is a library for nested, variable-sized data, including arbitrary-length lists, records, mixed types, and missing data, using NumPy-like idioms. Arrays are dynamically typed, but operations on them are compiled and fast. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not. -
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CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. -
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NumCpp
C++ implementation of the Python Numpy library
A Templatized Header Only C++ Implementation of the Python NumPy Library. The main data structure in NumCpp is the NdArray. It is inherently a 2D array class, with 1D arrays being implemented as 1xN arrays. There is also a DataCube class that is provided as a convenience container for storing an array of 2D NdArrays, but it has limited usefulness past a simple container. -
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Numba
NumPy aware dynamic Python compiler using LLVM
...Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions that broadcast over NumPy arrays just like NumPy functions do. Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks, like Dask and Spark. -
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PyVista
3D plotting and mesh analysis through a streamlined interface
3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK). PyVista is a helper module for the Visualization Toolkit (VTK) that takes a different approach on interfacing with VTK through NumPy and direct array access. This package provides a Pythonic, well-documented interface exposing VTK’s powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets. This module can be used for scientific plotting for presentations and research papers as well as a supporting module for other mesh-dependent Python modules. ... -
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SciPy
SciPy library main repository
...The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. Both SciPy and NumPy run on all popular operating systems, are fast and easy to install, and are powerful yet easy to use. They’re currently depended upon by numerous leading scientists and engineers all over the world. Try them for yourself! -
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tslearn
The machine learning toolkit for time series analysis in Python
The machine learning toolkit for time series analysis in Python. tslearn expects a time series dataset to be formatted as a 3D numpy array. The three dimensions correspond to the number of time series, the number of measurements per time series and the number of dimensions respectively (n_ts, max_sz, d). In order to get the data in the right format. -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. ... -
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spyder
The scientific Python development environment
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. Spyder’s multi-language Editor integrates a number of powerful tools... -
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werpy
Python package for fast Word Error Rate (WER) calculation and analysis
Werpy is a robust yet lightweight Python package, engineered to swiftly compute and analyzes the Word Error Rate (WER) between two text sets. It boasts versatility in managing various types of input data, including strings, lists, and numpy arrays. The library encompasses an extensive array of functionalities, encompassing text normalization to accommodate discrepancies in data collection. It also empowers users to effortlessly allocate distinct weights or penalties to specific error categories such as insertions, deletions, and substitutions. Moreover, the summary function furnishes a comprehensive breakdown of the computed outcomes, facilitating a swift and detailed analysis of individual errors. -
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Numerical Python
A package for scientific computing with Python
NEWS: NumPy 1.11.2 is the last release that will be made on sourceforge. Wheels for Windows, Mac, and Linux as well as archived source distributions can be found on PyPI. Numerical Python adds a fast and sophisticated array facility to the Python language. NumPy is the most recent and most actively supported package. Numarray and Numeric are no longer supported. -
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pymatlab
A pythonic interface to MATLAB
This package lets Python users interface and communicate with MATLAB from Python. Pymatlab makes it easier for users to integrate a project with a large MATLAB codebase into python scripts by using MATLAB scripts as a part of the python program. The basic functionality of this package is to send data from Python to MATLAB's workspace to be able to run Matlab function on the data. After processing you retrieve back data to... -
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ATpy (Astronomical Tables in Python) is a Python module aimed at dealing with tables of astronomical data with a common API. To date, the following formats are supported: FITS, VO, and IPAC tables, and SQLite, MySQL, and PostgreSQL databases
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Larry Project
larry is a labeled Numpy array
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PySimpleTable
Lightweight Python 2D table object with column headers
...Once the 2D object is created, call an included method to convert it to a more efficient and powerful Numpy Array or Pandas DataFrame for the real work. A PySimpleTable has column headers names. Cells are referenced by: tbl[row_num][col_num] tbl[row_num]['colname'] Rows are added easily. Columns cannot be added or removed. Other features include: - sorting by column(s) - filter by function - convert to Numpy Array or Pandas DataFrame -
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Simple Python class for managing tables of data in memory using NumPy. It allows to give names to views of array. The package contains few classes built on top of the basic one to be used as post processing tools for particle optics computations.
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