defprotocol Numy.Tz do @moduledoc """ Interface to Tensor. """ @doc """ Get number of dimensions ## Examples iex(1)> tensor = Numy.Lapack.new_tensor([1,2,3,4,5]) iex(2)> Numy.Tz.ndim(tensor) 5 iex(3)> Numy.Tz.nelm(tensor) 120 """ def ndim(tensor) @doc """ Get number of elements """ def nelm(tensor) def assign(tensor, list) def data(tensor, nelm \\ -1) end defprotocol Numy.Mx do @moduledoc """ Interface to Matrix """ end defprotocol Numy.Vc do @moduledoc """ Interface to Vector """ @doc "Assign 0.0 to each element of the vector." def assign_zeros(v) @doc "Assign 1.0 to each element of the vector." def assign_ones(v) @doc "Assign random values to the elements." def assign_random(v) @doc "Assign some value to all elements." def assign_all(v, val) @doc "Return true if vector is empty." def empty?(v) @doc "Get data as a list" def data(v) @doc "Get value of N-th element by index, return default in case of error." def at(v, index, default \\ nil) @doc "Check if elements of 2 vectors are practically the same." def equal?(v1,v2) @doc "Add 2 vectors, cᵢ ← aᵢ + bᵢ" def add(v1, v2) @doc "Subtract one vector from other, cᵢ ← aᵢ - bᵢ" def sub(v1, v2) @doc "Multiply 2 vectors, cᵢ ← aᵢ×bᵢ" def mul(v1, v2) @doc "Divide 2 vectors, cᵢ ← aᵢ÷bᵢ" def div(v1, v2) @doc "Multiply each element by a constant, aᵢ ← aᵢ×scale_factor" def scale(v, factor) @doc "Add a constant to each element, aᵢ ← aᵢ + offset" def offset(v, off) @doc "Dot product of 2 vectors, ∑aᵢ×bᵢ" def dot(v1, v2) @doc "Sum of all elements, ∑aᵢ" def sum(v) @doc "Average (∑aᵢ)/length" def average(v) @doc "Return max value" def max(v) @doc "Return min value" def min(v) @doc "Return index of max value" def max_index(v) @doc "Return index of min value" def min_index(v) @doc "Step function, aᵢ ← 0 if aᵢ < 0 else 1" def apply_heaviside(v, cutoff \\ 0.0) @doc "f(x) = 1/(1 + e⁻ˣ)" def apply_sigmoid(v) @doc "Sort elements" def sort(v) @doc "Reverse" def reverse(v) end defprotocol Numy.Vcm do @moduledoc """ Interface to mutable Vector. Native objects do not follow Elixir/Erlang model where an object is always immutable. We purposefully allow native objects to be mutable in order to get better performance in numerical computing. """ @doc """ Mutate a vector by adding other to it, v1 = v1 + v2. Return mutated vector. """ def add!(v1, v2) def sub!(v1, v2) def mul!(v1, v2) def div!(v1, v2) @doc "Multiply each element by a constant, aᵢ ← aᵢ×scale_factor" def scale!(v, factor) @doc "Add a constant to each element, aᵢ ← aᵢ + offset" def offset!(v, off) @doc "Step function, aᵢ ← 0 if aᵢ < 0 else 1" def apply_heaviside!(v, cutoff \\ 0.0) @doc "f(x) = 1/(1 + e⁻ˣ)" def apply_sigmoid!(v) @doc "Sort elements of vector in-place" def sort!(v) @doc "Reverse elements of vector in-place" def reverse!(v) @doc "Set N-th element to a new value" def set_at!(v, index, val) @doc "aᵢ ← aᵢ×factor_a + bᵢ×factor_b" def axpby!(v1, v2, f1, f2) end