62 lines
1.9 KiB
Nim
62 lines
1.9 KiB
Nim
# Code excerpt from https://github.com/andreaferretti/linear-algebra
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type
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Matrix32*[M, N: static[int]] = object
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order: OrderType
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data: ref array[N * M, float32]
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OrderType* {.size: sizeof(int).} = enum
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rowMajor = 101, colMajor = 102
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template elem(m, i, j: untyped): untyped =
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if m.order == colMajor: m.data[j * m.M + i]
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else: m.data[i * m.N + j]
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template slowEqPrivate(m, n: untyped) =
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if m.M != n.M or m.N != n.N:
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return false
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for i in 0 ..< m.M:
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for j in 0 ..< m.N:
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if elem(m, i, j) != elem(n, i, j):
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return false
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return true
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proc slowEq[M, N: static[int]](m, n: Matrix32[M, N]): bool = slowEqPrivate(m, n)
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proc `==`*(m, n: Matrix32): bool =
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if m.order == n.order: m.data[] == n.data[]
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elif m.order == colMajor: slowEq(m, n)
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else: slowEq(n, m)
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template constantSMatrixPrivate(M, N, x, order, result: untyped) =
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new result.data
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result.order = order
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for i in 0 ..< (M * N):
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result.data[i] = x
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proc constantSMatrix(M, N: static[int], x: float32, order: OrderType = colMajor): Matrix32[M, N] =
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constantSMatrixPrivate(M, N, x, order, result)
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proc zeros*(M, N: static[int], A: typedesc[float32], order: OrderType = colMajor): Matrix32[M, N] =
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constantSMatrix(M, N, 0'f32, order)
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proc eye*(N: static[int], A: typedesc[float32], order: OrderType = colMajor): Matrix32[N, N] =
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result = zeros(N, N, float32, order)
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for i in 0 ..< N:
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result.data[i + N * i] = 1'f32
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when isMainModule:
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import drchaos
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{.experimental: "strictFuncs".}
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proc default[M, N: static[int]](_: typedesc[Matrix32[M, N]]): Matrix32[M, N] =
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zeros(M, N, float32)
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func fuzzTarget(x: Matrix32[3, 3]) =
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when defined(dumpFuzzInput): debugEcho(x)
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# Here you could multiply `x` with the identity matrix and make sure it doesn't change.
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#doAssert x * eye(3, float32) =~ x
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doAssert x != eye(3, float32)
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defaultMutator(fuzzTarget)
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