#Programming_paradigms : #Array_programming (also vector or multidimensional)
Generalizes operations on scalars to apply transparently to vectors, matrices, and higher-dimensional arrays.
Is used in scientific and engineering settings.
e.g. APL, J, Fortran, #Ada, #MATLAB, #Perl Data Language (PDL) and the NumPy extension to #Python.
Vectorized operation
Operations applied at once to an entire set of values like arrays; regardless of whether it is executed on a vector processor or not.
Function rank
Analogous to tensor rank in mathematics
Functions that operate on data may be classified by the number of dimensions they act on.
• Ordinary multiplication, for example, is a scalar ranked function because it operates on zero-dimensional data (individual numbers).
• The cross product operation is an example of a vector rank function because it operates on vectors, not scalars.
• Matrix multiplication is an example of a 2-rank function, because it operates on 2-dimensional objects (matrices).
Collapse operators reduce the dimensionality of an input data array by one or more dimensions. For example, summing over elements collapses the input array by 1 dimension.
Generalizes operations on scalars to apply transparently to vectors, matrices, and higher-dimensional arrays.
Is used in scientific and engineering settings.
e.g. APL, J, Fortran, #Ada, #MATLAB, #Perl Data Language (PDL) and the NumPy extension to #Python.
Vectorized operation
Operations applied at once to an entire set of values like arrays; regardless of whether it is executed on a vector processor or not.
Function rank
Analogous to tensor rank in mathematics
Functions that operate on data may be classified by the number of dimensions they act on.
• Ordinary multiplication, for example, is a scalar ranked function because it operates on zero-dimensional data (individual numbers).
• The cross product operation is an example of a vector rank function because it operates on vectors, not scalars.
• Matrix multiplication is an example of a 2-rank function, because it operates on 2-dimensional objects (matrices).
Collapse operators reduce the dimensionality of an input data array by one or more dimensions. For example, summing over elements collapses the input array by 1 dimension.