Search results
Results from the WOW.Com Content Network
GNU Octave also allows vectorization and half-vectorization with vec(A) and vech(A) respectively. Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [ note 1 ] while in R the desired effect can be achieved via the c() or as.vector() functions.
Qalculate! supports common mathematical functions and operations, multiple bases, autocompletion, complex numbers, infinite numbers, arrays and matrices, variables, mathematical and physical constants, user-defined functions, symbolic derivation and integration, solving of equations involving unknowns, uncertainty propagation using interval arithmetic, plotting using Gnuplot, unit and currency ...
2022 (version 0.5.0) Free MIT: Cross-platform (command-line version) Browsers with WebAssembly support (web version) SVGcode (uses Potrace) Thomas Steiner 2021 2023 (version ?) Free GPL-2.0-or-later: Android, web , Windows Primitive: Michael Fogleman Free MIT: MAC OS X, with Python & Go packages and a JavaScript port KVEC: K. Kuhl Freeware
The fundamental idea behind array programming is that operations apply at once to an entire set of values. This makes it a high-level programming model as it allows the programmer to think and operate on whole aggregates of data, without having to resort to explicit loops of individual scalar operations.
The P program can be used for studies with dichotomous, continuous, or survival response measures. The user specifies the alternative hypothesis in terms of differing response rates, means, survival times, relative risks, or odds ratios.
In this case, if we make a very large matrix with complex exponentials in the rows (i.e., cosine real parts and sine imaginary parts), and increase the resolution without bound, we approach the kernel of the Fredholm integral equation of the 2nd kind, namely the Fourier operator that defines the continuous Fourier transform. A rectangular ...
In mathematics, low-rank approximation refers to the process of approximating a given matrix by a matrix of lower rank. More precisely, it is a minimization problem, in which the cost function measures the fit between a given matrix (the data) and an approximating matrix (the optimization variable), subject to a constraint that the approximating matrix has reduced rank.
Automatic vectorization, a compiler optimization that transforms loops to vector operations Image tracing , the creation of vector from raster graphics Word embedding , mapping words to vectors, in natural language processing