MaxFrame Tensor# The following pages describe Numpy-compatible routines. These functions cover a subset of NumPy routines. Tensor Creation Routines From shape or value From existing data Building matrices Numerical ranges Tensor Indexing Routines Generating index arrays Indexing-like operations Inserting data into arrays Tensor Manipulation Routines Basic operations Changing array shape Transpose-like operations Changing number of dimensions Joining tensors Splitting arrays Tiling arrays Adding and removing elements Rearranging elements Binary Operations Elementwise bit operations Discrete Fourier Transform Standard FFTs Real FFTs Hermitian FFTs Helper routines Linear Algebra Matrix and vector products Decompositions Norms and other numbers Solving equations and inverting matrices Logic Functions Truth value testing Array contents Array type testing Logic operations Comparison Mathematical Functions Trigonometric functions Hyperbolic functions Rounding Sums, products, differences Exponential and logarithms Other special functions Floating point routines Arithmetic operations Handling complex numbers Miscellaneous Random Sampling Sample random data Distributions Random number generator Set routines Making proper sets Boolean operations Sorting, Searching, and Counting Sorting Searching Counting Special Functions Airy functions Information Theory functions Bessel functions Error functions and fresnel integrals Ellipsoidal harmonics Elliptic functions and integrals Gamma and related functions Sigmoidal functions Other special functions Convenience functions Statistics Order statistics Average and variances Correlating Histograms