sta�c dispatch, i.e. you need to annotate a func�on as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Func�on. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source 51.2. MATHEMATICAL FUNCTIONS 607 Base.log1p – Func�on

sta�c dispatch, i.e. you need to annotate a func�on as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Func�on. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source 590 CHAPTER 51. MATHEMATICS Base.log1p – Func�on.

sta�c dispatch, i.e. you need to annotate a func�on as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Func�on. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log1p – Func�on. log1p(x) 588 CHAPTER 51. MATHEMATICS

sta�c dispatch, i.e. you need to annotate a func�on as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Func�on. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source 52.2. MATHEMATICAL FUNCTIONS 609 Base.log1p – Func�on

static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Function. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source CHAPTER 43. MATHEMATICS 616 Base.log1p – Function.

static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Function. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source CHAPTER 43. MATHEMATICS 617 Base.log1p – Function.

static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Function. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source CHAPTER 43. MATHEMATICS 616 Base.log1p – Function.

static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Function. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source 43.2. MATHEMATICAL FUNCTIONS 639 Base.log1p – Function

static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Function. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source CHAPTER 43. MATHEMATICS 616 Base.log1p – Function.

static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods julia> log2(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log10 – Function. log10(x) Compute the logarithm julia> log10(-2) ERROR: DomainError with -2.0: NaN result for non-NaN input. Stacktrace: [1] nan_dom_err at ./math.jl:325 [inlined] [...] source Base.log1p – Function. log1p(x) 43.2. MATHEMATICAL