(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially

(typemin(Float32),typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for the distance between two adjacent representable floating-point numbers, which is often known as machine epsilon. Julia provides eps, which gives the distance between 1.0 and the next larger representable antic- ipate. For example, the fib(n::Integer) function above works equally well for Int arguments (machine integers) and BigInt arbitrary-precision integers (see BigFloats and BigInts), which is especially