..  cumsum(A, [dim])

Cumulative sum along a dimension ``dim`` (defaults to 1).
See also :func:`cumsum!` to use a preallocated output array,
both for performance and to control the precision of the
output (e.g. to avoid overflow).


The cumsum function in Julia calculates the cumulative sum along a specified dimension of an array. The default dimension is 1. Here are some examples of its usage:

  1. Cumulative sum of a 1-dimensional array:

    julia> A = [1, 2, 3, 4, 5];
    julia> cumsum(A)
    5-element Array{Int64,1}:

    This example calculates the cumulative sum of the elements in the array A along dimension 1.

  2. Cumulative sum of a 2-dimensional array along a specified dimension:

    julia> A = [1 2 3; 4 5 6; 7 8 9];
    julia> cumsum(A, 2)
    3×3 Array{Int64,2}:
    1   3   6
    4   9  15
    7  15  24

    It calculates the cumulative sum along dimension 2 of the 2-dimensional array A.

  3. Cumulative sum of a vector of floating-point numbers:
    julia> A = [1.2, 2.3, 3.4, 4.5];
    julia> cumsum(A)
    4-element Array{Float64,1}:

    This example demonstrates the cumulative sum calculation on a vector of floating-point numbers.

It is worth mentioning the cumsum! function, which can be used to perform the cumulative sum operation in-place for improved performance and control over precision.

See Also

abs2, beta, binomial, ceil, cell, cross, ctranspose, ctranspose!, cummin, cumprod, cumprod!, cumsum, cumsum!, cumsum_kbn, div, divrem, eigfact, eigfact!, eigmin, eps, erf, erfc, erfcinv, erfcx, erfi, erfinv, exp, exp10, exp2, expm1, exponent, factor, factorial, factorize, floor, gcd, invmod, log, log10, log1p, log2, logspace, max, min, mod, mod1, modf, next, nextpow, nextprod, num, primes, primesmask, prod, realmin, sqrt, sum!, sumabs, sumabs!, sumabs2, sumabs2!,

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