Routines

The following pages describe NumPy-compatible routines. These functions cover a subset of NumPy routines.

• Array creation routines
  • From shape or value
  • From existing data
  • Numerical ranges
  • Building matrices
  • The Matrix class
• Array manipulation routines
  • Basic operations
  • Changing array shape
  • Transpose-like operations
  • Changing number of dimensions
  • Changing kind of array
  • Joining arrays
  • Splitting arrays
  • Tiling arrays
  • Adding and removing elements
  • Rearranging elements
• Bit-wise operations
  • Element-wise bit operations
  • Bit packing
  • Output formatting
• Data type routines
  • dpnp.can_cast
  • dpnp.result_type
  • Creating data types
  • Data type information
  • Data type testing
  • Miscellaneous
• Discrete Fourier Transform
  • Standard FFTs
  • Real FFTs
  • Hermitian FFTs
  • Helper routines
• Functional programming
  • dpnp.apply_along_axis
  • dpnp.apply_over_axes
• Indexing routines
  • Generating index arrays
  • Indexing-like operations
  • Inserting data into arrays
  • Iterating over arrays
• Linear algebra
  • Matrix and vector products
  • Decompositions
  • Matrix eigenvalues
  • Norms and other numbers
  • Solving linear equations
  • Other matrix operations
  • Exceptions
• Logic functions
  • Truth value testing
  • Infinities and NaNs
  • Array type testing
  • Logic operations
  • Comparison
• Mathematical functions
  • Trigonometric functions
  • Hyperbolic functions
  • Rounding
  • Sums, products, differences
  • Exponents and logarithms
  • Other special functions
  • Floating point routines
  • Rational routines
  • Arithmetic operations
  • Handling complex numbers
  • Extrema finding
  • Miscellaneous
• Random sampling (dpnp.random)
  • Simple random data
  • Permutations
  • Distributions
  • Random generator
• Sorting, searching, and counting
  • Sorting
  • Searching
  • Counting
• Statistics
  • Order statistics
  • Averages and variances
  • Correlations
  • Histograms