Compare commits
4 Commits
934a40fe1a
...
44aaa8a8b2
| Author | SHA1 | Date | |
|---|---|---|---|
|
44aaa8a8b2 | ||
|
|
cd954b379b | ||
|
|
16d25e7e7e | ||
|
|
f37a196b15 |
59
src/Base.zig
59
src/Base.zig
@ -3,34 +3,39 @@ const std = @import("std");
|
||||
// Adjust these imports to match your actual file names
|
||||
const Dimensions = @import("Dimensions.zig");
|
||||
const Scales = @import("Scales.zig");
|
||||
const Scalar = @import("Quantity.zig").Scalar;
|
||||
const Tensor = @import("Tensor.zig").Tensor;
|
||||
|
||||
fn PhysicalConstant(comptime d: Dimensions.ArgOpts, comptime val: f64, comptime s: Scales.ArgOpts) type {
|
||||
return struct {
|
||||
const dims = Dimensions.init(d);
|
||||
const scales = Scales.init(s);
|
||||
pub const dims = Dimensions.init(d);
|
||||
pub const scales = Scales.init(s);
|
||||
|
||||
/// Instantiates the constant into a specific numeric type.
|
||||
pub fn Of(comptime T: type) Scalar(T, d, s) {
|
||||
return .{ .data = @splat(@as(T, @floatCast(val))) };
|
||||
pub fn Of(comptime T: type) Tensor(T, d, s, &.{1}) {
|
||||
const casted_val: T = switch (@typeInfo(T)) {
|
||||
.float => @floatCast(val),
|
||||
.int => @intFromFloat(val),
|
||||
else => @compileError("Unsupported type for PhysicalConstant"),
|
||||
};
|
||||
return Tensor(T, d, s, &.{1}).splat(casted_val);
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
fn BaseScalar(comptime d: Dimensions.ArgOpts) type {
|
||||
return struct {
|
||||
const dims = Dimensions.init(d);
|
||||
pub const dims = Dimensions.init(d);
|
||||
|
||||
/// Creates a Scalar of this dimension using default scales.
|
||||
/// Example: const V = Quantities.Velocity.Base(f32);
|
||||
/// Example: const V = Quantities.Velocity.Of(f32);
|
||||
pub fn Of(comptime T: type) type {
|
||||
return Scalar(T, d, .{});
|
||||
return Tensor(T, d, .{}, &.{1});
|
||||
}
|
||||
|
||||
/// Creates a Scalar of this dimension using custom scales.
|
||||
/// Example: const Kmh = Quantities.Velocity.Scaled(f32, Scales.init(.{ .L = .k, .T = .hour }));
|
||||
/// Example: const Kmh = Quantities.Velocity.Scaled(f32, .{ .L = .k, .T = .hour });
|
||||
pub fn Scaled(comptime T: type, comptime s: Scales.ArgOpts) type {
|
||||
return Scalar(T, d, s);
|
||||
return Tensor(T, d, s, &.{1});
|
||||
}
|
||||
};
|
||||
}
|
||||
@ -107,7 +112,7 @@ pub const ElectricCapacitance = BaseScalar(.{ .T = 4, .L = -2, .M = -1, .I = 2 }
|
||||
pub const ElectricImpedance = ElectricResistance;
|
||||
pub const MagneticFlux = BaseScalar(.{ .M = 1, .L = 2, .T = -2, .I = -1 });
|
||||
pub const MagneticDensity = BaseScalar(.{ .M = 1, .T = -2, .I = -1 });
|
||||
pub const MagneticStrength = BaseScalar(.{ .L = -1, .I = 1 }); // Fixed typo from MagneticStrengh
|
||||
pub const MagneticStrength = BaseScalar(.{ .L = -1, .I = 1 });
|
||||
pub const MagneticMoment = BaseScalar(.{ .L = 2, .I = 1 });
|
||||
|
||||
// ==========================================
|
||||
@ -140,7 +145,7 @@ pub const ThermalHeat = Energy;
|
||||
pub const ThermalWork = Energy;
|
||||
pub const ThermalCapacity = BaseScalar(.{ .M = 1, .L = 2, .T = -2, .Tr = -1 });
|
||||
pub const ThermalCapacityPerMass = BaseScalar(.{ .L = 2, .T = -2, .Tr = -1 });
|
||||
pub const ThermalFluxDensity = BaseScalar(.{ .M = 1, .T = -3 }); // Fixed typo from ThermalluxDensity
|
||||
pub const ThermalFluxDensity = BaseScalar(.{ .M = 1, .T = -3 });
|
||||
pub const ThermalConductance = BaseScalar(.{ .M = 1, .L = 2, .T = -3, .Tr = -1 });
|
||||
pub const ThermalConductivity = BaseScalar(.{ .M = 1, .L = 1, .T = -3, .Tr = -1 });
|
||||
pub const ThermalResistance = BaseScalar(.{ .M = -1, .L = -2, .T = 3, .Tr = 1 });
|
||||
@ -152,20 +157,24 @@ pub const ThermalEntropy = BaseScalar(.{ .M = 1, .L = 2, .T = -2, .Tr = -1 });
|
||||
// ==========================================
|
||||
pub const Frequency = BaseScalar(.{ .T = -1 });
|
||||
pub const Viscosity = BaseScalar(.{ .M = 1, .L = -1, .T = -1 });
|
||||
pub const SurfaceTension = BaseScalar(.{ .M = 1, .T = -2 }); // Corrected from MT-2a
|
||||
pub const SurfaceTension = BaseScalar(.{ .M = 1, .T = -2 });
|
||||
|
||||
// ==========================================
|
||||
// Tests
|
||||
// ==========================================
|
||||
|
||||
test "BaseQuantities - Core dimensions instantiation" {
|
||||
// Basic types via generic wrappers
|
||||
const M = Meter.Of(f32);
|
||||
const distance = M.splat(100);
|
||||
try std.testing.expectEqual(100.0, distance.value());
|
||||
try std.testing.expectEqual(100.0, distance.data[0]);
|
||||
try std.testing.expectEqual(1, M.dims.get(.L));
|
||||
try std.testing.expectEqual(0, M.dims.get(.T));
|
||||
|
||||
// Test specific scale variants
|
||||
const Kmh = Speed.Scaled(f32, .{ .L = .k, .T = .hour });
|
||||
const speed = Kmh.splat(120);
|
||||
try std.testing.expectEqual(120.0, speed.value());
|
||||
try std.testing.expectEqual(120.0, speed.data[0]);
|
||||
try std.testing.expectEqual(.k, @TypeOf(speed).scales.get(.L));
|
||||
try std.testing.expectEqual(.hour, @TypeOf(speed).scales.get(.T));
|
||||
}
|
||||
@ -176,12 +185,12 @@ test "BaseQuantities - Kinematics equations" {
|
||||
|
||||
// Velocity = Distance / Time
|
||||
const v = d.div(t);
|
||||
try std.testing.expectEqual(25.0, v.value());
|
||||
try std.testing.expectEqual(25.0, v.data[0]);
|
||||
try std.testing.expect(Speed.dims.eql(@TypeOf(v).dims));
|
||||
|
||||
// Acceleration = Velocity / Time
|
||||
const a = v.div(t);
|
||||
try std.testing.expectEqual(12.5, a.value());
|
||||
try std.testing.expectEqual(12.5, a.data[0]);
|
||||
try std.testing.expect(Acceleration.dims.eql(@TypeOf(a).dims));
|
||||
}
|
||||
|
||||
@ -193,13 +202,13 @@ test "BaseQuantities - Dynamics (Force and Work)" {
|
||||
|
||||
// Force = mass * acceleration
|
||||
const f = m.mul(a);
|
||||
try std.testing.expectEqual(98, f.value());
|
||||
try std.testing.expectEqual(98, f.data[0]);
|
||||
try std.testing.expect(Force.dims.eql(@TypeOf(f).dims));
|
||||
|
||||
// Energy (Work) = Force * distance
|
||||
const distance = Meter.Of(f32).splat(5.0);
|
||||
const energy = f.mul(distance);
|
||||
try std.testing.expectEqual(490, energy.value());
|
||||
try std.testing.expectEqual(490, energy.data[0]);
|
||||
try std.testing.expect(Energy.dims.eql(@TypeOf(energy).dims));
|
||||
}
|
||||
|
||||
@ -209,26 +218,26 @@ test "BaseQuantities - Electric combinations" {
|
||||
|
||||
// Charge = Current * time
|
||||
const charge = current.mul(time);
|
||||
try std.testing.expectEqual(6.0, charge.value());
|
||||
try std.testing.expectEqual(6.0, charge.data[0]);
|
||||
try std.testing.expect(ElectricCharge.dims.eql(@TypeOf(charge).dims));
|
||||
}
|
||||
|
||||
test "Constants - Initialization and dimension checks" {
|
||||
// Speed of Light
|
||||
const c = Constants.SpeedOfLight.Of(f64);
|
||||
try std.testing.expectEqual(299792458.0, c.value());
|
||||
try std.testing.expectEqual(299792458.0, c.data[0]);
|
||||
try std.testing.expectEqual(1, @TypeOf(c).dims.get(.L));
|
||||
try std.testing.expectEqual(-1, @TypeOf(c).dims.get(.T));
|
||||
|
||||
// Electron Mass (verifying scale as well)
|
||||
const me = Constants.ElectronMass.Of(f64);
|
||||
try std.testing.expectEqual(9.1093837139e-31, me.value());
|
||||
try std.testing.expectEqual(9.1093837139e-31, me.data[0]);
|
||||
try std.testing.expectEqual(1, @TypeOf(me).dims.get(.M));
|
||||
try std.testing.expectEqual(.k, @TypeOf(me).scales.get(.M)); // Should be scaled to kg
|
||||
|
||||
// Boltzmann Constant (Complex derived dimensions)
|
||||
const kb = Constants.Boltzmann.Of(f64);
|
||||
try std.testing.expectEqual(1.380649e-23, kb.value());
|
||||
try std.testing.expectEqual(1.380649e-23, kb.data[0]);
|
||||
try std.testing.expectEqual(1, @TypeOf(kb).dims.get(.M));
|
||||
try std.testing.expectEqual(2, @TypeOf(kb).dims.get(.L));
|
||||
try std.testing.expectEqual(-2, @TypeOf(kb).dims.get(.T));
|
||||
@ -237,7 +246,7 @@ test "Constants - Initialization and dimension checks" {
|
||||
|
||||
// Vacuum Permittivity
|
||||
const eps0 = Constants.VacuumPermittivity.Of(f64);
|
||||
try std.testing.expectEqual(8.8541878188e-12, eps0.value());
|
||||
try std.testing.expectEqual(8.8541878188e-12, eps0.data[0]);
|
||||
try std.testing.expectEqual(-1, @TypeOf(eps0).dims.get(.M));
|
||||
try std.testing.expectEqual(-3, @TypeOf(eps0).dims.get(.L));
|
||||
try std.testing.expectEqual(4, @TypeOf(eps0).dims.get(.T));
|
||||
@ -245,7 +254,7 @@ test "Constants - Initialization and dimension checks" {
|
||||
|
||||
// Fine Structure Constant (Dimensionless)
|
||||
const alpha = Constants.FineStructure.Of(f64);
|
||||
try std.testing.expectEqual(0.0072973525643, alpha.value());
|
||||
try std.testing.expectEqual(0.0072973525643, alpha.data[0]);
|
||||
try std.testing.expectEqual(0, @TypeOf(alpha).dims.get(.M));
|
||||
try std.testing.expectEqual(0, @TypeOf(alpha).dims.get(.L));
|
||||
}
|
||||
|
||||
@ -51,17 +51,17 @@ data: std.EnumArray(Dimension, comptime_int),
|
||||
/// Unspecified dimensions default to 0.
|
||||
pub fn init(comptime init_val: ArgOpts) Self {
|
||||
var s = Self{ .data = std.EnumArray(Dimension, comptime_int).initFill(0) };
|
||||
inline for (std.meta.fields(@TypeOf(init_val))) |f|
|
||||
for (std.meta.fields(@TypeOf(init_val))) |f|
|
||||
s.data.set(@field(Dimension, f.name), @field(init_val, f.name));
|
||||
return s;
|
||||
}
|
||||
|
||||
pub fn initFill(comptime val: comptime_int) Self {
|
||||
return .{ .data = std.EnumArray(Dimension, comptime_int).initFill(val) };
|
||||
comptime return .{ .data = std.EnumArray(Dimension, comptime_int).initFill(val) };
|
||||
}
|
||||
|
||||
pub fn get(comptime self: Self, comptime key: Dimension) comptime_int {
|
||||
return self.data.get(key);
|
||||
comptime return self.data.get(key);
|
||||
}
|
||||
|
||||
pub fn set(comptime self: *Self, comptime key: Dimension, comptime val: i8) void {
|
||||
@ -70,40 +70,40 @@ pub fn set(comptime self: *Self, comptime key: Dimension, comptime val: i8) void
|
||||
|
||||
pub fn argsOpt(self: Self) ArgOpts {
|
||||
var args: ArgOpts = undefined;
|
||||
inline for (std.enums.values(Dimension)) |d|
|
||||
for (std.enums.values(Dimension)) |d|
|
||||
@field(args, @tagName(d)) = self.get(d);
|
||||
return args;
|
||||
comptime return args;
|
||||
}
|
||||
|
||||
/// Add exponents component-wise. Used internally by `mul`.
|
||||
pub fn add(comptime a: Self, comptime b: Self) Self {
|
||||
var result = Self.initFill(0);
|
||||
inline for (std.enums.values(Dimension)) |d|
|
||||
for (std.enums.values(Dimension)) |d|
|
||||
result.set(d, a.get(d) + b.get(d));
|
||||
return result;
|
||||
comptime return result;
|
||||
}
|
||||
|
||||
/// Subtract exponents component-wise. Used internally by `div`.
|
||||
pub fn sub(comptime a: Self, comptime b: Self) Self {
|
||||
var result = Self.initFill(0);
|
||||
inline for (std.enums.values(Dimension)) |d|
|
||||
for (std.enums.values(Dimension)) |d|
|
||||
result.set(d, a.get(d) - b.get(d));
|
||||
return result;
|
||||
comptime return result;
|
||||
}
|
||||
|
||||
/// Multiply exponents by a scalar integer. Used internally by `pow` in Scalar.
|
||||
pub fn scale(comptime a: Self, comptime exp: comptime_int) Self {
|
||||
var result = Self.initFill(0);
|
||||
inline for (std.enums.values(Dimension)) |d|
|
||||
for (std.enums.values(Dimension)) |d|
|
||||
result.set(d, a.get(d) * exp);
|
||||
return result;
|
||||
comptime return result;
|
||||
}
|
||||
|
||||
pub fn div(comptime a: Self, comptime exp: comptime_int) Self {
|
||||
var result = Self.initFill(0);
|
||||
inline for (std.enums.values(Dimension)) |d|
|
||||
result.set(d, a.get(d) / exp);
|
||||
return result;
|
||||
comptime return result;
|
||||
}
|
||||
|
||||
/// Returns true if every dimension exponent is equal. Used to enforce type compatibility in `add`, `sub`, `to`.
|
||||
|
||||
@ -1,5 +1,4 @@
|
||||
const std = @import("std");
|
||||
const hlp = @import("helper.zig");
|
||||
const Dimensions = @import("Dimensions.zig");
|
||||
const Dimension = @import("Dimensions.zig").Dimension;
|
||||
|
||||
@ -66,7 +65,7 @@ pub const UnitScale = enum(isize) {
|
||||
}
|
||||
|
||||
pub inline fn getFactor(self: @This()) comptime_float {
|
||||
return comptime switch (self) {
|
||||
comptime return switch (self) {
|
||||
// Standard SI Exponents
|
||||
inline .P, .T, .G, .M, .k, .h, .da, .none, .d, .c, .m, .u, .n, .p, .f => std.math.pow(f64, 10.0, @floatFromInt(@intFromEnum(self))),
|
||||
|
||||
@ -84,7 +83,7 @@ pub const UnitScale = enum(isize) {
|
||||
inline .lb => 453.59237,
|
||||
inline .st => 6350.29318,
|
||||
|
||||
inline else => @floatFromInt(@intFromEnum(self)),
|
||||
else => @floatFromInt(@intFromEnum(self)),
|
||||
};
|
||||
}
|
||||
};
|
||||
@ -99,16 +98,16 @@ data: std.EnumArray(Dimension, UnitScale),
|
||||
pub fn init(comptime init_val: ArgOpts) Self {
|
||||
comptime var s = Self{ .data = std.EnumArray(Dimension, UnitScale).initFill(.none) };
|
||||
inline for (std.meta.fields(@TypeOf(init_val))) |f| {
|
||||
if (comptime hlp.isInt(@TypeOf(@field(init_val, f.name))))
|
||||
if (comptime @typeInfo(@TypeOf(@field(init_val, f.name))) == .comptime_int)
|
||||
s.data.set(@field(Dimension, f.name), @enumFromInt(@field(init_val, f.name)))
|
||||
else
|
||||
s.data.set(@field(Dimension, f.name), @field(init_val, f.name));
|
||||
}
|
||||
return s;
|
||||
return comptime s;
|
||||
}
|
||||
|
||||
pub fn initFill(comptime val: UnitScale) Self {
|
||||
return comptime .{ .data = std.EnumArray(Dimension, UnitScale).initFill(val) };
|
||||
comptime return .{ .data = std.EnumArray(Dimension, UnitScale).initFill(val) };
|
||||
}
|
||||
|
||||
pub fn get(comptime self: Self, comptime key: Dimension) UnitScale {
|
||||
@ -116,7 +115,7 @@ pub fn get(comptime self: Self, comptime key: Dimension) UnitScale {
|
||||
}
|
||||
|
||||
pub fn set(comptime self: *Self, comptime key: Dimension, comptime val: UnitScale) void {
|
||||
comptime self.data.set(key, val);
|
||||
self.data.set(key, val);
|
||||
}
|
||||
|
||||
pub fn argsOpt(self: Self) ArgOpts {
|
||||
@ -145,5 +144,5 @@ pub inline fn getFactor(comptime s: Self, comptime d: Dimensions) comptime_float
|
||||
factor /= base;
|
||||
}
|
||||
}
|
||||
return comptime factor;
|
||||
comptime return factor;
|
||||
}
|
||||
|
||||
@ -1,47 +1,57 @@
|
||||
const std = @import("std");
|
||||
const hlp = @import("helper.zig");
|
||||
const Scales = @import("Scales.zig");
|
||||
const UnitScale = Scales.UnitScale;
|
||||
const Dimensions = @import("Dimensions.zig");
|
||||
const Dimension = Dimensions.Dimension;
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
// Comptime shape utilities
|
||||
// Comptime utilities
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
pub fn shapeTotal(comptime shape: []const usize) usize {
|
||||
var t: usize = 1;
|
||||
pub fn shapeTotal(comptime shape: []const comptime_int) usize {
|
||||
var t: comptime_int = 1;
|
||||
for (shape) |s| t *= s;
|
||||
return t;
|
||||
}
|
||||
|
||||
/// Check if two shapes are strictly identical.
|
||||
pub fn shapeEql(comptime a: []const comptime_int, comptime b: []const comptime_int) bool {
|
||||
if (a.len != b.len) return false;
|
||||
for (a, 0..) |v, i|
|
||||
if (v != b[i]) return false;
|
||||
return true;
|
||||
}
|
||||
|
||||
/// Row-major (C-order) strides: strides[i] = product(shape[i+1..]).
|
||||
/// e.g. shape {3, 4} → strides {4, 1}
|
||||
/// shape {2, 3, 4} → strides {12, 4, 1}
|
||||
pub fn shapeStrides(comptime shape: []const usize) [shape.len]usize {
|
||||
var st: [shape.len]usize = undefined;
|
||||
pub fn shapeStrides(comptime shape: []const comptime_int) [shape.len]comptime_int {
|
||||
var st: [shape.len]comptime_int = undefined;
|
||||
if (shape.len == 0) return st;
|
||||
st[shape.len - 1] = 1;
|
||||
if (shape.len > 1) {
|
||||
var i: usize = shape.len - 1;
|
||||
var i: comptime_int = shape.len - 1;
|
||||
while (i > 0) : (i -= 1) st[i - 1] = st[i] * shape[i];
|
||||
}
|
||||
return st;
|
||||
}
|
||||
|
||||
/// Return a copy of `shape` with the element at `axis` removed.
|
||||
pub fn shapeRemoveAxis(comptime shape: []const usize, comptime axis: usize) [shape.len - 1]usize {
|
||||
var out: [shape.len - 1]usize = undefined;
|
||||
var j: usize = 0;
|
||||
pub fn shapeRemoveAxis(comptime shape: []const comptime_int, comptime axis: comptime_int) [shape.len - 1]comptime_int {
|
||||
var out: [shape.len - 1]comptime_int = undefined;
|
||||
var j: comptime_int = 0;
|
||||
for (shape, 0..) |v, i| {
|
||||
if (i != axis) { out[j] = v; j += 1; }
|
||||
if (i != axis) {
|
||||
out[j] = v;
|
||||
j += 1;
|
||||
}
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
/// Concatenate two compile-time slices.
|
||||
pub fn shapeCat(comptime a: []const usize, comptime b: []const usize) [a.len + b.len]usize {
|
||||
var out: [a.len + b.len]usize = undefined;
|
||||
pub fn shapeCat(comptime a: []const comptime_int, comptime b: []const comptime_int) [a.len + b.len]comptime_int {
|
||||
var out: [a.len + b.len]comptime_int = undefined;
|
||||
for (a, 0..) |v, i| out[i] = v;
|
||||
for (b, 0..) |v, i| out[a.len + i] = v;
|
||||
return out;
|
||||
@ -50,11 +60,11 @@ pub fn shapeCat(comptime a: []const usize, comptime b: []const usize) [a.len + b
|
||||
/// Decode a flat row-major index into N-D coordinates.
|
||||
/// Called only in comptime contexts (all arguments are comptime).
|
||||
pub fn decodeFlatCoords(
|
||||
comptime flat: usize,
|
||||
comptime n: usize,
|
||||
comptime strd: [n]usize,
|
||||
comptime flat: comptime_int,
|
||||
comptime n: comptime_int,
|
||||
comptime strd: [n]comptime_int,
|
||||
) [n]usize {
|
||||
var coords: [n]usize = undefined;
|
||||
var coords: [n]comptime_int = undefined;
|
||||
var tmp = flat;
|
||||
for (0..n) |i| {
|
||||
coords[i] = if (strd[i] == 0) 0 else tmp / strd[i];
|
||||
@ -96,22 +106,48 @@ pub fn insertAxis(
|
||||
return out;
|
||||
}
|
||||
|
||||
fn isInt(comptime T: type) bool {
|
||||
return @typeInfo(T) == .int or @typeInfo(T) == .comptime_int;
|
||||
}
|
||||
|
||||
fn finerScales(comptime T1: type, comptime T2: type) Scales {
|
||||
const d1: Dimensions = T1.dims;
|
||||
const d2: Dimensions = T2.dims;
|
||||
const s1: Scales = T1.scales;
|
||||
const s2: Scales = T2.scales;
|
||||
comptime var out = Scales.initFill(.none);
|
||||
for (std.enums.values(Dimension)) |dim| {
|
||||
const scale1 = comptime s1.get(dim);
|
||||
const scale2 = comptime s2.get(dim);
|
||||
out.set(dim, if (comptime d1.get(dim) == 0 and d2.get(dim) == 0)
|
||||
.none
|
||||
else if (comptime d1.get(dim) == 0)
|
||||
scale2
|
||||
else if (comptime d2.get(dim) == 0)
|
||||
scale1
|
||||
else if (comptime scale1.getFactor() > scale2.getFactor())
|
||||
scale2
|
||||
else
|
||||
scale1);
|
||||
}
|
||||
comptime return out;
|
||||
}
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
// File-scope RHS normalisation helpers
|
||||
//
|
||||
// Any bare comptime_int / comptime_float / runtime T used as an arithmetic
|
||||
// or comparison RHS is wrapped into a dimensionless Tensor of shape {1}.
|
||||
// Actual Tensor types are passed through unchanged.
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
fn isTensor(comptime Rhs: type) bool {
|
||||
return comptime @typeInfo(Rhs) == .@"struct" and @hasDecl(Rhs, "ISTENSOR");
|
||||
}
|
||||
|
||||
fn RhsTensorType(comptime T: type, comptime Rhs: type) type {
|
||||
if (@hasDecl(Rhs, "ISTENSOR")) return Rhs;
|
||||
if (comptime isTensor(Rhs)) return Rhs;
|
||||
return Tensor(T, .{}, .{}, &.{1});
|
||||
}
|
||||
|
||||
fn toRhsTensor(comptime T: type, r: anytype) RhsTensorType(T, @TypeOf(r)) {
|
||||
const Rhs = @TypeOf(r);
|
||||
if (comptime @hasDecl(Rhs, "ISTENSOR")) return r;
|
||||
if (comptime isTensor(Rhs)) return r;
|
||||
const scalar: T = switch (comptime @typeInfo(Rhs)) {
|
||||
.comptime_int => switch (comptime @typeInfo(T)) {
|
||||
.float => @as(T, @floatFromInt(r)),
|
||||
@ -134,55 +170,44 @@ fn toRhsTensor(comptime T: type, r: anytype) RhsTensorType(T, @TypeOf(r)) {
|
||||
return Tensor(T, .{}, .{}, &.{1}){ .data = .{scalar} };
|
||||
}
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
// Tensor — unified dimensioned ND type.
|
||||
//
|
||||
// T : element numeric type (f32, f64, i32, i128, …)
|
||||
// d_opt : SI dimension exponents
|
||||
// s_opt : unit scales
|
||||
// shape_ : compile-time shape
|
||||
// &.{1} → scalar
|
||||
// &.{3} → 3-vector
|
||||
// &.{4, 4} → 4×4 matrix
|
||||
// &.{3, 3, 3} → 3D field
|
||||
//
|
||||
// Storage: flat @Vector(total, T) where total = product(shape_).
|
||||
// All arithmetic operates on the flat vector directly → SIMD wherever possible.
|
||||
//
|
||||
// Shape-related comptime constants exposed on every Tensor type:
|
||||
// dims : Dimensions — SI exponent struct
|
||||
// scales : Scales — unit scale struct
|
||||
// shape : []const usize
|
||||
// rank : usize = shape.len
|
||||
// total : usize = product(shape)
|
||||
// strides_arr : [rank]usize — row-major strides
|
||||
//
|
||||
// Index helper:
|
||||
// Tensor.idx(.{row, col}) → flat index (comptime, no runtime cost)
|
||||
//
|
||||
// GPU readiness:
|
||||
// tensor.asSlice() → []T (zero-copy pointer to the flat @Vector storage)
|
||||
//
|
||||
// Contraction (replaces dot / cross / matmul):
|
||||
// a.contract(b, axis_a, axis_b)
|
||||
// For rank-1 × rank-1 this is the dot product.
|
||||
// For rank-2 × rank-2 with axis_a=1, axis_b=0 this is matrix multiply.
|
||||
//
|
||||
// Removed from Quantity:
|
||||
// Scalar / Vector aliases, Vec3 / ScalarType, .value(), .vec(), .vec3(),
|
||||
// dot(), cross(), mulScalar(), divScalar(), eqScalar() and friends.
|
||||
// Use Tensor(..., &.{1}), .data[0], mul(), div(), eq() respectively.
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
pub fn printSuperscript(writer: *std.Io.Writer, n: i32) !void {
|
||||
if (n == 0) return;
|
||||
var val = n;
|
||||
if (val < 0) {
|
||||
try writer.writeAll("\u{207B}");
|
||||
val = -val;
|
||||
}
|
||||
var buf: [12]u8 = undefined;
|
||||
const str = std.fmt.bufPrint(&buf, "{d}", .{val}) catch return;
|
||||
for (str) |c| {
|
||||
const s = switch (c) {
|
||||
'0' => "\u{2070}",
|
||||
'1' => "\u{00B9}",
|
||||
'2' => "\u{00B2}",
|
||||
'3' => "\u{00B3}",
|
||||
'4' => "\u{2074}",
|
||||
'5' => "\u{2075}",
|
||||
'6' => "\u{2076}",
|
||||
'7' => "\u{2077}",
|
||||
'8' => "\u{2078}",
|
||||
'9' => "\u{2079}",
|
||||
else => unreachable,
|
||||
};
|
||||
try writer.writeAll(s);
|
||||
}
|
||||
}
|
||||
|
||||
pub fn Tensor(
|
||||
comptime T: type,
|
||||
comptime d_opt: Dimensions.ArgOpts,
|
||||
comptime s_opt: Scales.ArgOpts,
|
||||
comptime shape_: []const usize,
|
||||
comptime shape_: []const comptime_int,
|
||||
) type {
|
||||
comptime {
|
||||
std.debug.assert(shape_.len >= 1);
|
||||
for (shape_) |s| std.debug.assert(s >= 1);
|
||||
if (shape_.len == 0) @compileError("Tensor shape must have at least 1 dimension (rank >= 1).");
|
||||
for (shape_) |s| {
|
||||
if (s == 0) @compileError("Tensor shape dimensions must be strictly >= 1.");
|
||||
}
|
||||
}
|
||||
@setEvalBranchQuota(10_000_000);
|
||||
|
||||
@ -191,7 +216,6 @@ pub fn Tensor(
|
||||
const Vec = @Vector(_total, T);
|
||||
|
||||
return struct {
|
||||
/// Flat SIMD storage. All arithmetic operates here directly.
|
||||
data: Vec,
|
||||
|
||||
const Self = @This();
|
||||
@ -199,33 +223,25 @@ pub fn Tensor(
|
||||
pub const ValueType: type = T;
|
||||
pub const dims: Dimensions = Dimensions.init(d_opt);
|
||||
pub const scales: Scales = Scales.init(s_opt);
|
||||
pub const shape : []const usize = shape_;
|
||||
pub const rank : usize = shape_.len;
|
||||
pub const total : usize = _total;
|
||||
pub const strides_arr: [shape_.len]usize = _strides;
|
||||
pub const shape: []const comptime_int = shape_;
|
||||
pub const rank: comptime_int = shape_.len;
|
||||
pub const total: comptime_int = _total;
|
||||
pub const strides_arr: [shape_.len]comptime_int = _strides;
|
||||
pub const ISTENSOR = true;
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Index helper
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Convert N-D coords (row-major) to flat index — fully comptime.
|
||||
/// Usage: Tensor.idx(.{row, col})
|
||||
pub fn idx(comptime coords: [rank]usize) usize {
|
||||
pub inline fn idx(comptime coords: [rank]usize) usize {
|
||||
comptime {
|
||||
var flat: usize = 0;
|
||||
for (0..rank) |i| {
|
||||
std.debug.assert(coords[i] < shape[i]);
|
||||
if (coords[i] >= shape[i]) @compileError("idx: Coordinate out of bounds");
|
||||
flat += coords[i] * strides_arr[i];
|
||||
}
|
||||
return flat;
|
||||
}
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Constructors
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Broadcast a single value across all elements.
|
||||
pub inline fn splat(v: T) Self {
|
||||
return .{ .data = @splat(v) };
|
||||
@ -234,25 +250,17 @@ pub fn Tensor(
|
||||
pub const zero: Self = splat(0);
|
||||
pub const one: Self = splat(1);
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// GPU readiness
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Return a mutable slice to the flat storage — zero-copy WebGPU buffer mapping.
|
||||
pub inline fn asSlice(self: *Self) []T {
|
||||
return @as([*]T, @ptrCast(&self.data))[0..total];
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Internal: RHS normalisation
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
inline fn RhsT(comptime Rhs: type) type { return RhsTensorType(T, Rhs); }
|
||||
inline fn rhs(r: anytype) RhsT(@TypeOf(r)) { return toRhsTensor(T, r); }
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Internal: scalar broadcast (shape {1} → full Vec)
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
inline fn RhsT(comptime Rhs: type) type {
|
||||
return RhsTensorType(T, Rhs);
|
||||
}
|
||||
inline fn rhs(r: anytype) RhsT(@TypeOf(r)) {
|
||||
return toRhsTensor(T, r);
|
||||
}
|
||||
|
||||
inline fn broadcastToVec(comptime RhsType: type, r: RhsType) Vec {
|
||||
return if (comptime RhsType.total == 1 and total > 1)
|
||||
@ -261,57 +269,54 @@ pub fn Tensor(
|
||||
r.data;
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Arithmetic
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Element-wise add. Dimensions must match; scales resolve to finer.
|
||||
/// RHS must have the same element count as self, or total == 1 (broadcast).
|
||||
/// RHS must have the same shape as self, or total == 1 (broadcast).
|
||||
pub inline fn add(self: Self, r: anytype) Tensor(
|
||||
T,
|
||||
dims.argsOpt(),
|
||||
hlp.finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
shape_,
|
||||
) {
|
||||
const rhs_q = rhs(r);
|
||||
const RhsType = @TypeOf(rhs_q);
|
||||
if (comptime !dims.eql(RhsType.dims))
|
||||
@compileError("Dimension mismatch in add: " ++ dims.str() ++ " vs " ++ RhsType.dims.str());
|
||||
if (comptime RhsType.total != total and RhsType.total != 1)
|
||||
@compileError("Shape mismatch in add: element counts must match or RHS must be scalar (total=1).");
|
||||
if (comptime RhsType.total != 1 and !shapeEql(shape_, RhsType.shape))
|
||||
@compileError("Shape mismatch in add: element-wise operations require identical shapes, or a scalar RHS.");
|
||||
|
||||
const TargetType = Tensor(T, dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const TargetType = Tensor(T, dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const l: Vec = if (comptime Self == TargetType) self.data else self.to(TargetType).data;
|
||||
const rr: Vec = blk: {
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const rn = if (comptime RhsType == RhsNorm) rhs_q else rhs_q.to(RhsNorm);
|
||||
break :blk broadcastToVec(RhsNorm, rn);
|
||||
};
|
||||
return .{ .data = if (comptime hlp.isInt(T)) l +| rr else l + rr };
|
||||
return .{ .data = if (comptime isInt(T)) l +| rr else l + rr };
|
||||
}
|
||||
|
||||
/// Element-wise subtract. Dimensions must match; scales resolve to finer.
|
||||
/// Element-wise sub. Dimensions must match; scales resolve to finer.
|
||||
/// RHS must have the same shape as self, or total == 1 (broadcast).
|
||||
pub inline fn sub(self: Self, r: anytype) Tensor(
|
||||
T,
|
||||
dims.argsOpt(),
|
||||
hlp.finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
shape_,
|
||||
) {
|
||||
const rhs_q = rhs(r);
|
||||
const RhsType = @TypeOf(rhs_q);
|
||||
if (comptime !dims.eql(RhsType.dims))
|
||||
@compileError("Dimension mismatch in sub: " ++ dims.str() ++ " vs " ++ RhsType.dims.str());
|
||||
if (comptime RhsType.total != total and RhsType.total != 1)
|
||||
@compileError("Shape mismatch in sub.");
|
||||
if (comptime RhsType.total != 1 and !shapeEql(shape_, RhsType.shape))
|
||||
@compileError("Shape mismatch in sub: element-wise operations require identical shapes, or a scalar RHS.");
|
||||
|
||||
const TargetType = Tensor(T, dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const TargetType = Tensor(T, dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const l: Vec = if (comptime Self == TargetType) self.data else self.to(TargetType).data;
|
||||
const rr: Vec = blk: {
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const rn = if (comptime RhsType == RhsNorm) rhs_q else rhs_q.to(RhsNorm);
|
||||
break :blk broadcastToVec(RhsNorm, rn);
|
||||
};
|
||||
return .{ .data = if (comptime hlp.isInt(T)) l -| rr else l - rr };
|
||||
return .{ .data = if (comptime isInt(T)) l -| rr else l - rr };
|
||||
}
|
||||
|
||||
/// Element-wise multiply. Dimension exponents summed.
|
||||
@ -319,20 +324,20 @@ pub fn Tensor(
|
||||
pub inline fn mul(self: Self, r: anytype) Tensor(
|
||||
T,
|
||||
dims.add(RhsT(@TypeOf(r)).dims).argsOpt(),
|
||||
hlp.finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
shape_,
|
||||
) {
|
||||
const rhs_q = rhs(r);
|
||||
const RhsType = @TypeOf(rhs_q);
|
||||
if (comptime RhsType.total != total and RhsType.total != 1)
|
||||
@compileError("Shape mismatch in mul.");
|
||||
if (comptime RhsType.total != 1 and !shapeEql(shape_, RhsType.shape))
|
||||
@compileError("Shape mismatch in mul: element-wise operations require identical shapes, or a scalar RHS.");
|
||||
|
||||
const SelfNorm = Tensor(T, dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const SelfNorm = Tensor(T, dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const l: Vec = if (comptime Self == SelfNorm) self.data else self.to(SelfNorm).data;
|
||||
const rr_base = if (comptime RhsType == RhsNorm) rhs_q else rhs_q.to(RhsNorm);
|
||||
const rr: Vec = broadcastToVec(RhsNorm, rr_base);
|
||||
return .{ .data = if (comptime hlp.isInt(T)) l *| rr else l * rr };
|
||||
return .{ .data = if (comptime isInt(T)) l *| rr else l * rr };
|
||||
}
|
||||
|
||||
/// Element-wise divide. Dimension exponents subtracted.
|
||||
@ -340,32 +345,26 @@ pub fn Tensor(
|
||||
pub inline fn div(self: Self, r: anytype) Tensor(
|
||||
T,
|
||||
dims.sub(RhsT(@TypeOf(r)).dims).argsOpt(),
|
||||
hlp.finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
finerScales(Self, RhsT(@TypeOf(r))).argsOpt(),
|
||||
shape_,
|
||||
) {
|
||||
const rhs_q = rhs(r);
|
||||
const RhsType = @TypeOf(rhs_q);
|
||||
if (comptime RhsType.total != total and RhsType.total != 1)
|
||||
@compileError("Shape mismatch in div.");
|
||||
if (comptime RhsType.total != 1 and !shapeEql(shape_, RhsType.shape))
|
||||
@compileError("Shape mismatch in div: element-wise operations require identical shapes, or a scalar RHS.");
|
||||
|
||||
const SelfNorm = Tensor(T, dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const SelfNorm = Tensor(T, dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const l: Vec = if (comptime Self == SelfNorm) self.data else self.to(SelfNorm).data;
|
||||
const rr_base = if (comptime RhsType == RhsNorm) rhs_q else rhs_q.to(RhsNorm);
|
||||
const rr: Vec = broadcastToVec(RhsNorm, rr_base);
|
||||
if (comptime hlp.isInt(T)) {
|
||||
var result: Vec = undefined;
|
||||
inline for (0..total) |i| result[i] = @divTrunc(l[i], rr[i]);
|
||||
return .{ .data = result };
|
||||
if (comptime isInt(T)) {
|
||||
return .{ .data = @divTrunc(l, rr) };
|
||||
} else {
|
||||
return .{ .data = l / rr };
|
||||
}
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Unary
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Absolute value of every element.
|
||||
pub inline fn abs(self: Self) Self {
|
||||
return .{ .data = @bitCast(@abs(self.data)) };
|
||||
@ -378,19 +377,27 @@ pub fn Tensor(
|
||||
scales.argsOpt(),
|
||||
shape_,
|
||||
) {
|
||||
if (comptime hlp.isInt(T)) {
|
||||
var result: Vec = undefined;
|
||||
inline for (0..total) |i|
|
||||
result[i] = std.math.powi(T, self.data[i], exp) catch std.math.maxInt(T);
|
||||
return .{ .data = result };
|
||||
} else {
|
||||
const abs_exp = comptime @abs(exp);
|
||||
if (comptime exp == 0) return .{ .data = @splat(1) };
|
||||
if (comptime exp == 1) return self;
|
||||
|
||||
var base = self.data;
|
||||
var result: Vec = @splat(1);
|
||||
comptime var i = 0;
|
||||
inline while (i < abs_exp) : (i += 1) result *= self.data;
|
||||
if (comptime exp < 0) result = @as(Vec, @splat(1)) / result;
|
||||
return .{ .data = result };
|
||||
comptime var e = @abs(exp);
|
||||
|
||||
// $O(\log n)$ Exponentiation by squaring applied to the entire vector
|
||||
inline while (e > 0) {
|
||||
if (e % 2 == 1) {
|
||||
result = if (comptime isInt(T)) result *| base else result * base;
|
||||
}
|
||||
e /= 2;
|
||||
if (e > 0) {
|
||||
base = if (comptime isInt(T)) base *| base else base * base;
|
||||
}
|
||||
}
|
||||
if (comptime !isInt(T) and exp < 0) {
|
||||
result = @as(Vec, @splat(1)) / result;
|
||||
}
|
||||
return .{ .data = result };
|
||||
}
|
||||
|
||||
/// Square root of every element. All dimension exponents must be even.
|
||||
@ -403,15 +410,16 @@ pub fn Tensor(
|
||||
if (comptime !dims.isSquare())
|
||||
@compileError("Cannot take sqrt of " ++ dims.str() ++ ": exponents must be even.");
|
||||
if (comptime @typeInfo(T) == .float) {
|
||||
return .{ .data = @sqrt(self.data) };
|
||||
return .{ .data = @sqrt(self.data) }; // Float is natively vectorized!
|
||||
} else {
|
||||
var result: Vec = undefined;
|
||||
const arr: [total]T = self.data; // Add this!
|
||||
var res_arr: [total]T = undefined;
|
||||
const UnsignedT = @Int(.unsigned, @typeInfo(T).int.bits);
|
||||
inline for (0..total) |i| {
|
||||
const v = self.data[i];
|
||||
result[i] = if (v < 0) 0 else @as(T, @intCast(std.math.sqrt(@as(UnsignedT, @intCast(v)))));
|
||||
for (0..total) |i| {
|
||||
const v = arr[i];
|
||||
res_arr[i] = if (v < 0) 0 else @as(T, @intCast(std.math.sqrt(@as(UnsignedT, @intCast(v)))));
|
||||
}
|
||||
return .{ .data = result };
|
||||
return .{ .data = res_arr };
|
||||
}
|
||||
}
|
||||
|
||||
@ -420,13 +428,9 @@ pub fn Tensor(
|
||||
return .{ .data = -self.data };
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Conversion
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
/// Convert to a compatible Tensor type.
|
||||
/// • Dimension mismatch → compile error.
|
||||
/// • Dest.total must equal self.total, or Dest.total == 1 (scalar pattern).
|
||||
/// • Dest.shape must equal self.shape, or Dest.total == 1 (scalar pattern).
|
||||
/// • Scale ratio is computed fully at comptime; only a SIMD multiply at runtime.
|
||||
pub inline fn to(
|
||||
self: Self,
|
||||
@ -434,82 +438,92 @@ pub fn Tensor(
|
||||
) Tensor(Dest.ValueType, Dest.dims.argsOpt(), Dest.scales.argsOpt(), shape_) {
|
||||
const ActualDest = Tensor(Dest.ValueType, Dest.dims.argsOpt(), Dest.scales.argsOpt(), shape_);
|
||||
|
||||
if (comptime !dims.eql(ActualDest.dims))
|
||||
@compileError("Dimension mismatch in to: " ++ dims.str() ++ " vs " ++ ActualDest.dims.str());
|
||||
if (comptime Self == ActualDest) return self;
|
||||
|
||||
comptime std.debug.assert(Dest.total == total or Dest.total == 1);
|
||||
// Run validation checks FIRST before dealing with types
|
||||
if (comptime !dims.eql(ActualDest.dims))
|
||||
@compileError("Dimension mismatch in to: " ++ dims.str() ++ " vs " ++ ActualDest.dims.str());
|
||||
if (comptime Dest.total != 1 and !shapeEql(shape_, Dest.shape))
|
||||
@compileError("Shape mismatch in to: destination type must have the identical shape, or be a scalar.");
|
||||
|
||||
const DestT = ActualDest.ValueType;
|
||||
const ratio = comptime (scales.getFactor(dims) / ActualDest.scales.getFactor(ActualDest.dims));
|
||||
const DestT = ActualDest.ValueType;
|
||||
const DestVec = @Vector(total, DestT);
|
||||
|
||||
// ── Same numeric type ──────────────────────────────────────
|
||||
// If ratio is 1, handle type conversion correctly based on BOTH source and dest types
|
||||
if (comptime ratio == 1.0) {
|
||||
const T_info = @typeInfo(T);
|
||||
const Dest_info = @typeInfo(DestT);
|
||||
|
||||
return .{
|
||||
.data = if (comptime T_info == .int and Dest_info == .int)
|
||||
@as(DestVec, @intCast(self.data))
|
||||
else if (comptime T_info == .float and Dest_info == .float)
|
||||
@as(DestVec, @floatCast(self.data))
|
||||
else if (comptime T_info == .int and Dest_info == .float)
|
||||
@as(DestVec, @floatFromInt(self.data))
|
||||
else if (comptime T_info == .float and Dest_info == .int)
|
||||
@as(DestVec, @intFromFloat(self.data)) // Or @intFromFloat(@round(self.data)) if you want rounding
|
||||
else
|
||||
unreachable,
|
||||
};
|
||||
}
|
||||
|
||||
if (comptime T == DestT) {
|
||||
if (comptime @typeInfo(T) == .float)
|
||||
return .{ .data = self.data * @as(DestVec, @splat(@as(T, @floatCast(ratio)))) };
|
||||
|
||||
// Integer — branch prevents division-by-zero
|
||||
if (comptime ratio >= 1.0) {
|
||||
const mult: T = comptime @intFromFloat(@round(ratio));
|
||||
return .{ .data = self.data *| @as(Vec, @splat(mult)) };
|
||||
} else {
|
||||
const div_val: T = comptime @intFromFloat(@round(1.0 / ratio));
|
||||
const half: T = comptime @divTrunc(div_val, 2);
|
||||
var result: DestVec = undefined;
|
||||
inline for (0..total) |i| {
|
||||
const val = self.data[i];
|
||||
result[i] = if (val >= 0)
|
||||
@divTrunc(val + half, div_val)
|
||||
else
|
||||
@divTrunc(val - half, div_val);
|
||||
|
||||
if (comptime @typeInfo(T).int.signedness == .unsigned) {
|
||||
return .{ .data = @divTrunc(self.data + @as(Vec, @splat(half)), @as(Vec, @splat(div_val))) };
|
||||
} else {
|
||||
// Vectorized branchless negative handling
|
||||
const is_pos = self.data >= @as(Vec, @splat(0));
|
||||
const offsets = @select(T, is_pos, @as(Vec, @splat(half)), @as(Vec, @splat(-half)));
|
||||
return .{ .data = @divTrunc(self.data + offsets, @as(Vec, @splat(div_val))) };
|
||||
}
|
||||
return .{ .data = result };
|
||||
}
|
||||
}
|
||||
|
||||
// ── Cross numeric type ─────────────────────────────────────
|
||||
var result: DestVec = undefined;
|
||||
inline for (0..total) |i| {
|
||||
const float_val: f64 = switch (comptime @typeInfo(T)) {
|
||||
.float => @floatCast(self.data[i]),
|
||||
.int => @floatFromInt(self.data[i]),
|
||||
// Cross-type fully vectorized casting with scales
|
||||
const FVec = @Vector(total, f64);
|
||||
const float_vec: FVec = switch (comptime @typeInfo(T)) {
|
||||
.float => @floatCast(self.data),
|
||||
.int => @floatFromInt(self.data),
|
||||
else => unreachable,
|
||||
};
|
||||
const scaled = float_val * ratio;
|
||||
result[i] = switch (comptime @typeInfo(DestT)) {
|
||||
.float => @floatCast(scaled),
|
||||
.int => @intFromFloat(@round(scaled)),
|
||||
else => unreachable,
|
||||
};
|
||||
}
|
||||
return .{ .data = result };
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Comparisons
|
||||
//
|
||||
// Return type: bool when total == 1 (scalar semantics)
|
||||
// [total]bool when total > 1 (element-wise, flat-indexed)
|
||||
//
|
||||
// Whole-tensor equality check → eqAll / neAll (always returns bool).
|
||||
// A shape {1} RHS is broadcast automatically, unifying the old
|
||||
// eqScalar / gtScalar / … family into the plain eq / gt / … methods.
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
const scaled = float_vec * @as(FVec, @splat(ratio));
|
||||
|
||||
return switch (comptime @typeInfo(DestT)) {
|
||||
.float => .{ .data = @floatCast(scaled) },
|
||||
.int => .{ .data = @intFromFloat(@round(scaled)) },
|
||||
else => unreachable,
|
||||
};
|
||||
}
|
||||
|
||||
const CmpResult = if (total == 1) bool else [total]bool;
|
||||
|
||||
inline fn cmpResult(v: @Vector(total, bool)) CmpResult {
|
||||
return if (comptime total == 1) v[0] else @as([total]bool, v);
|
||||
return if (comptime total == 1) @reduce(.And, v) else @as([total]bool, v);
|
||||
}
|
||||
|
||||
/// Resolve both sides to the finer scale, broadcasting shape {1} RHS if needed.
|
||||
inline fn resolveScalePair(self: Self, rhs_q: anytype) struct { l: Vec, r: Vec } {
|
||||
const RhsType = @TypeOf(rhs_q);
|
||||
const TargetType = Tensor(T, dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
if (comptime RhsType.total != 1 and !shapeEql(shape_, RhsType.shape))
|
||||
@compileError("Shape mismatch in comparison: element-wise operations require identical shapes, or a scalar RHS.");
|
||||
|
||||
const TargetType = Tensor(T, dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), shape_);
|
||||
const l: Vec = if (comptime Self == TargetType) self.data else self.to(TargetType).data;
|
||||
const rr: Vec = blk: {
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), hlp.finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const RhsNorm = Tensor(T, RhsType.dims.argsOpt(), finerScales(Self, RhsType).argsOpt(), RhsType.shape);
|
||||
const rn = if (comptime RhsType == RhsNorm) rhs_q else rhs_q.to(RhsNorm);
|
||||
break :blk broadcastToVec(RhsNorm, rn);
|
||||
};
|
||||
@ -577,26 +591,6 @@ pub fn Tensor(
|
||||
return !self.eqAll(other);
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Contraction — generalised dot product / matrix multiply / einsum
|
||||
//
|
||||
// a.contract(b, axis_a, axis_b)
|
||||
//
|
||||
// Sums over dimension `axis_a` of `a` and `axis_b` of `b`.
|
||||
// Requires a.shape[axis_a] == b.shape[axis_b] (checked at comptime).
|
||||
//
|
||||
// Result shape = a.shape \ axis_a ++ b.shape \ axis_b
|
||||
// Result dims = a.dims + b.dims (exponents summed, as in mul)
|
||||
// Result scales = finer of a, b
|
||||
//
|
||||
// Special cases:
|
||||
// rank-1 × rank-1, axis 0 × 0 → dot product (result shape {1})
|
||||
// rank-2 × rank-2, axis 1 × 0 → matrix multiply
|
||||
// rank-1 × rank-2, axis 0 × 0 → vector–matrix product
|
||||
//
|
||||
// All index arithmetic is comptime; runtime cost is the multiply-add loop only.
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
pub inline fn contract(
|
||||
self: Self,
|
||||
other: anytype,
|
||||
@ -604,18 +598,18 @@ pub fn Tensor(
|
||||
comptime axis_b: usize,
|
||||
) blk: {
|
||||
const OT = @TypeOf(other);
|
||||
comptime std.debug.assert(axis_a < rank);
|
||||
comptime std.debug.assert(axis_b < OT.rank);
|
||||
comptime std.debug.assert(shape_[axis_a] == OT.shape[axis_b]);
|
||||
// Contracted-away free axes; empty joint → scalar shape {1}
|
||||
if (axis_a >= rank) @compileError("contract: axis_a out of bounds");
|
||||
if (axis_b >= OT.rank) @compileError("contract: axis_b out of bounds");
|
||||
if (shape_[axis_a] != OT.shape[axis_b]) @compileError("contract: shape mismatch at contraction axes");
|
||||
|
||||
const sa = shapeRemoveAxis(shape_, axis_a);
|
||||
const sb = shapeRemoveAxis(OT.shape, axis_b);
|
||||
const rs_raw = shapeCat(&sa, &sb);
|
||||
const rs: []const usize = if (rs_raw.len == 0) &.{1} else &rs_raw;
|
||||
const rs: []const comptime_int = if (rs_raw.len == 0) &.{1} else &rs_raw;
|
||||
break :blk Tensor(
|
||||
T,
|
||||
dims.add(OT.dims).argsOpt(),
|
||||
hlp.finerScales(Self, OT).argsOpt(),
|
||||
finerScales(Self, OT).argsOpt(),
|
||||
rs,
|
||||
);
|
||||
} {
|
||||
@ -625,55 +619,131 @@ pub fn Tensor(
|
||||
const sa = comptime shapeRemoveAxis(shape_, axis_a);
|
||||
const sb = comptime shapeRemoveAxis(OT.shape, axis_b);
|
||||
const rs_raw = comptime shapeCat(&sa, &sb);
|
||||
const rs: []const usize = comptime if (rs_raw.len == 0) &.{1} else &rs_raw;
|
||||
const rs: []const comptime_int = comptime if (rs_raw.len == 0) &.{1} else &rs_raw;
|
||||
|
||||
const ResultType = Tensor(
|
||||
T,
|
||||
dims.add(OT.dims).argsOpt(),
|
||||
hlp.finerScales(Self, OT).argsOpt(),
|
||||
finerScales(Self, OT).argsOpt(),
|
||||
rs,
|
||||
);
|
||||
|
||||
// Normalise scales before accumulation
|
||||
const SelfNorm = Tensor(T, dims.argsOpt(), hlp.finerScales(Self, OT).argsOpt(), shape_);
|
||||
const OtherNorm = Tensor(T, OT.dims.argsOpt(), hlp.finerScales(Self, OT).argsOpt(), OT.shape);
|
||||
const SelfNorm = Tensor(T, dims.argsOpt(), finerScales(Self, OT).argsOpt(), shape_);
|
||||
const OtherNorm = Tensor(T, OT.dims.argsOpt(), finerScales(Self, OT).argsOpt(), OT.shape);
|
||||
|
||||
const a_data = if (comptime Self == SelfNorm) self.data else self.to(SelfNorm).data;
|
||||
const b_data = if (comptime OT == OtherNorm) other.data else other.to(OtherNorm).data;
|
||||
|
||||
// Precompute result strides from rs_raw (for coord decoding)
|
||||
// FAST PATH: Dot Product
|
||||
if (comptime rank == 1 and OT.rank == 1 and axis_a == 0 and axis_b == 0) {
|
||||
if (comptime !isInt(T)) {
|
||||
return .{ .data = @splat(@reduce(.Add, a_data * b_data)) };
|
||||
} else {
|
||||
// For integers, we do a vectorized saturating multiply,
|
||||
// then convert to an array to do a saturating sum
|
||||
const mul_arr: [total]T = a_data *| b_data;
|
||||
var acc: T = 0;
|
||||
for (mul_arr) |val| acc +|= val;
|
||||
return .{ .data = @splat(acc) };
|
||||
}
|
||||
}
|
||||
|
||||
// --- ZERO-COST COERCION TO ARRAYS FOR RUNTIME INDEXING ---
|
||||
const a_arr: [total]T = a_data;
|
||||
const b_arr: [OT.total]T = b_data;
|
||||
|
||||
// FAST PATH: 2D Matrix Multiplication
|
||||
if (comptime rank == 2 and OT.rank == 2 and axis_a == 1 and axis_b == 0) {
|
||||
const rows = shape_[0];
|
||||
const cols = OT.shape[1];
|
||||
const inner = shape_[1];
|
||||
|
||||
// Create a mutable array for the result, NOT a Tensor struct
|
||||
var res_arr: [ResultType.total]T = undefined;
|
||||
|
||||
for (0..rows) |i| {
|
||||
for (0..cols) |j| {
|
||||
var acc: T = 0;
|
||||
for (0..inner) |id| {
|
||||
const a_flat = i * _strides[0] + id * _strides[1];
|
||||
const b_flat = id * OT.strides_arr[0] + j * OT.strides_arr[1];
|
||||
|
||||
// Use a_arr and b_arr here
|
||||
if (comptime isInt(T)) acc +|= a_arr[a_flat] *| b_arr[b_flat] else acc += a_arr[a_flat] * b_arr[b_flat];
|
||||
}
|
||||
// Write to the array
|
||||
res_arr[i * cols + j] = acc;
|
||||
}
|
||||
}
|
||||
// Return the initialized Tensor struct
|
||||
return .{ .data = res_arr };
|
||||
}
|
||||
|
||||
// FALLBACK PATH
|
||||
const rs_raw_strides = comptime shapeStrides(&rs_raw);
|
||||
|
||||
var result: ResultType = .{ .data = @splat(0) };
|
||||
// Create a mutable array for the result
|
||||
var result_arr: [ResultType.total]T = undefined;
|
||||
|
||||
inline for (0..ResultType.total) |res_flat| {
|
||||
// Decode result flat index into free coords using rs_raw layout.
|
||||
// When rs_raw.len == 0, decodeFlatCoords returns [0]usize{} — correct.
|
||||
const res_coords = comptime decodeFlatCoords(res_flat, rs_raw.len, rs_raw_strides);
|
||||
for (0..ResultType.total) |res_flat| {
|
||||
const res_coords = decodeFlatCoords(res_flat, rs_raw.len, rs_raw_strides);
|
||||
|
||||
const a_free: [sa.len]usize = comptime res_coords[0..sa.len].*;
|
||||
const b_free: [sb.len]usize = comptime res_coords[sa.len..].*;
|
||||
var a_free: [sa.len]usize = undefined;
|
||||
for (0..sa.len) |i| a_free[i] = res_coords[i];
|
||||
var b_free: [sb.len]usize = undefined;
|
||||
for (0..sb.len) |i| b_free[i] = res_coords[sa.len + i];
|
||||
|
||||
var acc: T = 0;
|
||||
inline for (0..k) |ki| {
|
||||
// Reinsert the contracted index into free coords → full coord arrays
|
||||
const a_coords = comptime insertAxis(rank, axis_a, ki, &a_free);
|
||||
const b_coords = comptime insertAxis(OT.rank, axis_b, ki, &b_free);
|
||||
const a_flat = comptime encodeFlatCoords(&a_coords, rank, _strides);
|
||||
const b_flat = comptime encodeFlatCoords(&b_coords, OT.rank, OT.strides_arr);
|
||||
for (0..k) |ki| {
|
||||
const a_coords = insertAxis(rank, axis_a, ki, &a_free);
|
||||
const b_coords = insertAxis(OT.rank, axis_b, ki, &b_free);
|
||||
const a_flat = encodeFlatCoords(&a_coords, rank, _strides);
|
||||
const b_flat = encodeFlatCoords(&b_coords, OT.rank, OT.strides_arr);
|
||||
|
||||
if (comptime hlp.isInt(T))
|
||||
acc +|= a_data[a_flat] *| b_data[b_flat]
|
||||
else
|
||||
acc += a_data[a_flat] * b_data[b_flat];
|
||||
// Use a_arr and b_arr here
|
||||
if (comptime isInt(T)) acc +|= a_arr[a_flat] *| b_arr[b_flat] else acc += a_arr[a_flat] * b_arr[b_flat];
|
||||
}
|
||||
result.data[res_flat] = acc;
|
||||
}
|
||||
return result;
|
||||
// Write to the array
|
||||
result_arr[res_flat] = acc;
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Reduction helpers
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Return the initialized Tensor struct
|
||||
return .{ .data = result_arr };
|
||||
}
|
||||
|
||||
/// 3D Cross Product. Only defined for Rank-1 tensors of length 3.
|
||||
/// Result dimensions are the sum of input dimensions.
|
||||
pub inline fn cross(self: Self, other: anytype) Tensor(
|
||||
T,
|
||||
dims.add(RhsT(@TypeOf(other)).dims).argsOpt(),
|
||||
finerScales(Self, RhsT(@TypeOf(other))).argsOpt(),
|
||||
&.{3},
|
||||
) {
|
||||
const rhs_q = rhs(other);
|
||||
const RhsType = @TypeOf(rhs_q);
|
||||
|
||||
if (comptime rank != 1 or shape[0] != 3 or RhsType.rank != 1 or RhsType.shape[0] != 3) {
|
||||
@compileError("cross product is only defined for 3D vectors (rank-1, length 3)");
|
||||
}
|
||||
|
||||
// Bring both to the same scale (e.g., mm vs m)
|
||||
const p = self.resolveScalePair(rhs_q);
|
||||
const l = p.l;
|
||||
const r = p.r;
|
||||
|
||||
var res: [3]T = undefined;
|
||||
if (comptime isInt(T)) {
|
||||
res[0] = (l[1] *| r[2]) -| (l[2] *| r[1]);
|
||||
res[1] = (l[2] *| r[0]) -| (l[0] *| r[2]);
|
||||
res[2] = (l[0] *| r[1]) -| (l[1] *| r[0]);
|
||||
} else {
|
||||
res[0] = (l[1] * r[2]) - (l[2] * r[1]);
|
||||
res[1] = (l[2] * r[0]) - (l[0] * r[2]);
|
||||
res[2] = (l[0] * r[1]) - (l[1] * r[0]);
|
||||
}
|
||||
|
||||
return .{ .data = res };
|
||||
}
|
||||
|
||||
/// Sum of squared elements. Cheaper than length(); use for ordering.
|
||||
pub inline fn lengthSqr(self: Self) T {
|
||||
@ -700,10 +770,6 @@ pub fn Tensor(
|
||||
return .{ .data = .{@reduce(.Mul, self.data)} };
|
||||
}
|
||||
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
// Formatting
|
||||
// ───────────────────────────────────────────────────────────────
|
||||
|
||||
pub fn formatNumber(
|
||||
self: Self,
|
||||
writer: *std.Io.Writer,
|
||||
@ -722,7 +788,8 @@ pub fn Tensor(
|
||||
}
|
||||
} else {
|
||||
try writer.writeAll("(");
|
||||
inline for (0..total) |i| {
|
||||
const max_to_print = 6;
|
||||
inline for (0..@min(total, max_to_print)) |i| {
|
||||
if (i > 0) try writer.writeAll(", ");
|
||||
switch (@typeInfo(T)) {
|
||||
.float, .comptime_float => try writer.printFloat(self.data[i], options),
|
||||
@ -734,6 +801,8 @@ pub fn Tensor(
|
||||
}),
|
||||
else => unreachable,
|
||||
}
|
||||
if (comptime i == max_to_print - 1 and total != max_to_print - 1)
|
||||
try writer.writeAll(", ...");
|
||||
}
|
||||
try writer.writeAll(")");
|
||||
}
|
||||
@ -751,7 +820,7 @@ pub fn Tensor(
|
||||
else
|
||||
try writer.print("{s}{s}", .{ uscale.str(), bu.unit() });
|
||||
|
||||
if (v != 1) try hlp.printSuperscript(writer, v);
|
||||
if (v != 1) try printSuperscript(writer, v);
|
||||
}
|
||||
}
|
||||
};
|
||||
@ -760,15 +829,6 @@ pub fn Tensor(
|
||||
// ═════════════════════════════════════════════════════════════════════════════
|
||||
// Tests
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
// Naming convention used throughout:
|
||||
// Tensor(T, d, s, &.{1}) → former Scalar
|
||||
// Tensor(T, d, s, &.{N}) → former Vector of length N
|
||||
// .data[0] → former .value()
|
||||
// .mul(x) → former .mulScalar(x) (x may be scalar Tensor or bare number)
|
||||
// .div(x) → former .divScalar(x)
|
||||
// .eq(x) → former .eqScalar(x) (broadcasts when x.total==1)
|
||||
// .contract(other, 0, 0) → former .dot(other) (for rank-1 tensors)
|
||||
// ═════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
// ─── Scalar tests ─────────────────────────────────────────────────────────
|
||||
|
||||
@ -1185,7 +1245,6 @@ test "Vector Comparisons" {
|
||||
}
|
||||
|
||||
test "Vector vs Scalar broadcast comparison" {
|
||||
// Replaces the old eqScalar / gtScalar — now just eq / gt with a shape-{1} rhs.
|
||||
const Meter3 = Tensor(f32, .{ .L = 1 }, .{}, &.{3});
|
||||
const KiloMeter1 = Tensor(f32, .{ .L = 1 }, .{ .L = .k }, &.{1});
|
||||
|
||||
@ -1210,7 +1269,6 @@ test "Vector contract — dot product (rank-1 × rank-1)" {
|
||||
const pos = Meter3{ .data = .{ 10.0, 0.0, 0.0 } };
|
||||
const force = Newton3{ .data = .{ 5.0, 5.0, 0.0 } };
|
||||
|
||||
// work = force · pos
|
||||
const work = force.contract(pos, 0, 0);
|
||||
try std.testing.expectEqual(50.0, work.data[0]);
|
||||
try std.testing.expectEqual(1, @TypeOf(work).dims.get(.M));
|
||||
@ -1219,23 +1277,12 @@ test "Vector contract — dot product (rank-1 × rank-1)" {
|
||||
}
|
||||
|
||||
test "Vector contract — matrix multiply (rank-2 × rank-2)" {
|
||||
// 2×3 matrix multiplied by 3×2 matrix → 2×2 result
|
||||
const A = Tensor(f32, .{}, .{}, &.{ 2, 3 });
|
||||
const B = Tensor(f32, .{}, .{}, &.{ 3, 2 });
|
||||
|
||||
// A = [[1, 2, 3],
|
||||
// [4, 5, 6]]
|
||||
const a = A{ .data = .{ 1, 2, 3, 4, 5, 6 } };
|
||||
// B = [[7, 8],
|
||||
// [9, 10],
|
||||
// [11, 12]]
|
||||
const b = B{ .data = .{ 7, 8, 9, 10, 11, 12 } };
|
||||
|
||||
// C = A @ B (contract over axis 1 of A × axis 0 of B)
|
||||
// C[0][0] = 1*7 + 2*9 + 3*11 = 7 + 18 + 33 = 58
|
||||
// C[0][1] = 1*8 + 2*10 + 3*12 = 8 + 20 + 36 = 64
|
||||
// C[1][0] = 4*7 + 5*9 + 6*11 = 28 + 45 + 66 = 139
|
||||
// C[1][1] = 4*8 + 5*10 + 6*12 = 32 + 50 + 72 = 154
|
||||
const c = a.contract(b, 1, 0);
|
||||
try std.testing.expectEqual(58, c.data[Tensor(f32, .{}, .{}, &.{ 2, 2 }).idx(.{ 0, 0 })]);
|
||||
try std.testing.expectEqual(64, c.data[Tensor(f32, .{}, .{}, &.{ 2, 2 }).idx(.{ 0, 1 })]);
|
||||
@ -1322,16 +1369,15 @@ test "Vector eq broadcast on dimensionless" {
|
||||
|
||||
test "Tensor idx helper and matrix access" {
|
||||
const Mat3x3 = Tensor(f32, .{}, .{}, &.{ 3, 3 });
|
||||
// Identity-like: set [0][0]=1, [1][1]=2, [2][2]=3
|
||||
var m: Mat3x3 = Mat3x3.zero;
|
||||
m.data[Mat3x3.idx(.{ 0, 0 })] = 1.0;
|
||||
m.data[Mat3x3.idx(.{ 1, 1 })] = 2.0;
|
||||
m.data[Mat3x3.idx(.{ 2, 2 })] = 3.0;
|
||||
|
||||
try std.testing.expectEqual(1.0, m.data[0]); // [0][0]
|
||||
try std.testing.expectEqual(2.0, m.data[4]); // [1][1] (stride 3 → 1*3+1=4)
|
||||
try std.testing.expectEqual(3.0, m.data[8]); // [2][2] (2*3+2=8)
|
||||
try std.testing.expectEqual(0.0, m.data[1]); // [0][1]
|
||||
try std.testing.expectEqual(1.0, m.data[0]);
|
||||
try std.testing.expectEqual(2.0, m.data[4]);
|
||||
try std.testing.expectEqual(3.0, m.data[8]);
|
||||
try std.testing.expectEqual(0.0, m.data[1]);
|
||||
}
|
||||
|
||||
test "Tensor strides_arr correctness" {
|
||||
@ -1,7 +1,6 @@
|
||||
const std = @import("std");
|
||||
const Io = std.Io;
|
||||
const Scalar = @import("Quantity.zig").Scalar;
|
||||
const Vector = @import("Quantity.zig").Vector;
|
||||
const Tensor = @import("Tensor.zig").Tensor;
|
||||
|
||||
var io: Io = undefined;
|
||||
pub fn main(init: std.process.Init) !void {
|
||||
@ -11,16 +10,16 @@ pub fn main(init: std.process.Init) !void {
|
||||
|
||||
io = init.io;
|
||||
|
||||
// try vectorSIMDvsNative(f64, &stdout_writer.interface);
|
||||
// try stdout_writer.flush();
|
||||
// try vectorSIMDvsNative(f32, &stdout_writer.interface);
|
||||
// try stdout_writer.flush();
|
||||
// try vectorSIMDvsNative(i32, &stdout_writer.interface);
|
||||
// try stdout_writer.flush();
|
||||
// try vectorSIMDvsNative(i64, &stdout_writer.interface);
|
||||
// try stdout_writer.flush();
|
||||
// try vectorSIMDvsNative(i128, &stdout_writer.interface);
|
||||
// try stdout_writer.flush();
|
||||
try vectorSIMDvsNative(f64, &stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try vectorSIMDvsNative(f32, &stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try vectorSIMDvsNative(i32, &stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try vectorSIMDvsNative(i64, &stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try vectorSIMDvsNative(i128, &stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
|
||||
try bench_Scalar(&stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
@ -97,9 +96,9 @@ fn bench_Scalar(writer: *std.Io.Writer) !void {
|
||||
|
||||
comptime var tidx: usize = 0;
|
||||
inline for (Types, TNames) |T, tname| {
|
||||
const M = Scalar(T, .{ .L = 1 }, .{});
|
||||
const KM = Scalar(T, .{ .L = 1 }, .{ .L = .k });
|
||||
const S = Scalar(T, .{ .T = 1 }, .{});
|
||||
const M = Tensor(T, .{ .L = 1 }, .{}, &.{1});
|
||||
const KM = Tensor(T, .{ .L = 1 }, .{ .L = .k }, &.{1});
|
||||
const S = Tensor(T, .{ .T = 1 }, .{}, &.{1});
|
||||
|
||||
inline for (Ops, 0..) |op_name, oidx| {
|
||||
var samples: [SAMPLES]f64 = undefined;
|
||||
@ -199,8 +198,8 @@ fn bench_vsNative(writer: *std.Io.Writer) !void {
|
||||
var native_total_ns: f64 = 0;
|
||||
var quantity_total_ns: f64 = 0;
|
||||
|
||||
const M = Scalar(T, .{ .L = 1 }, .{});
|
||||
const S = Scalar(T, .{ .T = 1 }, .{});
|
||||
const M = Tensor(T, .{ .L = 1 }, .{}, &.{1});
|
||||
const S = Tensor(T, .{ .T = 1 }, .{}, &.{1});
|
||||
|
||||
std.mem.doNotOptimizeAway({
|
||||
for (0..SAMPLES) |_| {
|
||||
@ -321,9 +320,9 @@ fn bench_crossTypeVsNative(writer: *std.Io.Writer) !void {
|
||||
var native_total_ns: f64 = 0;
|
||||
var quantity_total_ns: f64 = 0;
|
||||
|
||||
const M1 = Scalar(T1, .{ .L = 1 }, .{});
|
||||
const M2 = Scalar(T2, .{ .L = 1 }, .{});
|
||||
const S2 = Scalar(T2, .{ .T = 1 }, .{});
|
||||
const M1 = Tensor(T1, .{ .L = 1 }, .{}, &.{1});
|
||||
const M2 = Tensor(T2, .{ .L = 1 }, .{}, &.{1});
|
||||
const S2 = Tensor(T2, .{ .T = 1 }, .{}, &.{1});
|
||||
|
||||
std.mem.doNotOptimizeAway({
|
||||
for (0..SAMPLES) |_| {
|
||||
@ -429,9 +428,8 @@ fn bench_Vector(writer: *std.Io.Writer) !void {
|
||||
try writer.print("│ {s:<16} │ {s:<4} │", .{ op_name, tname });
|
||||
|
||||
inline for (Lengths) |len| {
|
||||
const Q_base = Scalar(T, .{ .L = 1 }, .{});
|
||||
const Q_time = Scalar(T, .{ .T = 1 }, .{});
|
||||
const V = Vector(len, Q_base);
|
||||
const Q_time = Tensor(T, .{ .T = 1 }, .{}, &.{1});
|
||||
const V = Tensor(T, .{ .L = 1 }, .{}, &.{len});
|
||||
|
||||
// cross product is only defined for len == 3
|
||||
const is_cross = comptime std.mem.eql(u8, op_name, "cross");
|
||||
@ -455,10 +453,10 @@ fn bench_Vector(writer: *std.Io.Writer) !void {
|
||||
_ = v1.div(V.splat(getVal(T, i +% 2, 63)));
|
||||
} else if (comptime std.mem.eql(u8, op_name, "mulScalar")) {
|
||||
const s_val = Q_time.splat(getVal(T, i +% 2, 63));
|
||||
_ = v1.mulScalar(s_val);
|
||||
_ = v1.mul(s_val);
|
||||
} else if (comptime std.mem.eql(u8, op_name, "dot")) {
|
||||
const v2 = V.splat(getVal(T, i +% 5, 63));
|
||||
_ = v1.dot(v2);
|
||||
_ = v1.contract(v2, 0, 0);
|
||||
} else if (comptime std.mem.eql(u8, op_name, "cross")) {
|
||||
// len == 3 guaranteed by the guard above
|
||||
const v2 = V.splat(getVal(T, i +% 5, 63));
|
||||
|
||||
@ -1,97 +0,0 @@
|
||||
const std = @import("std");
|
||||
|
||||
pub fn isInt(comptime T: type) bool {
|
||||
return @typeInfo(T) == .int or @typeInfo(T) == .comptime_int;
|
||||
}
|
||||
|
||||
pub fn printSuperscript(writer: *std.Io.Writer, n: i32) !void {
|
||||
if (n == 0) return;
|
||||
var val = n;
|
||||
if (val < 0) {
|
||||
try writer.writeAll("\u{207B}");
|
||||
val = -val;
|
||||
}
|
||||
var buf: [12]u8 = undefined;
|
||||
const str = std.fmt.bufPrint(&buf, "{d}", .{val}) catch return;
|
||||
for (str) |c| {
|
||||
const s = switch (c) {
|
||||
'0' => "\u{2070}",
|
||||
'1' => "\u{00B9}",
|
||||
'2' => "\u{00B2}",
|
||||
'3' => "\u{00B3}",
|
||||
'4' => "\u{2074}",
|
||||
'5' => "\u{2075}",
|
||||
'6' => "\u{2076}",
|
||||
'7' => "\u{2077}",
|
||||
'8' => "\u{2078}",
|
||||
'9' => "\u{2079}",
|
||||
else => unreachable,
|
||||
};
|
||||
try writer.writeAll(s);
|
||||
}
|
||||
}
|
||||
|
||||
const Scales = @import("Scales.zig");
|
||||
const Dimensions = @import("Dimensions.zig");
|
||||
const Dimension = @import("Dimensions.zig").Dimension;
|
||||
|
||||
pub fn finerScales(comptime T1: type, comptime T2: type) Scales {
|
||||
const d1: Dimensions = T1.dims;
|
||||
const d2: Dimensions = T2.dims;
|
||||
const s1: Scales = T1.scales;
|
||||
const s2: Scales = T2.scales;
|
||||
comptime var out = Scales.initFill(.none);
|
||||
inline for (std.enums.values(Dimension)) |dim| {
|
||||
const scale1 = comptime s1.get(dim);
|
||||
const scale2 = comptime s2.get(dim);
|
||||
out.set(dim, if (comptime d1.get(dim) == 0 and d2.get(dim) == 0)
|
||||
.none
|
||||
else if (comptime d1.get(dim) == 0)
|
||||
scale2
|
||||
else if (comptime d2.get(dim) == 0)
|
||||
scale1
|
||||
else if (comptime scale1.getFactor() > scale2.getFactor())
|
||||
scale2
|
||||
else
|
||||
scale1);
|
||||
}
|
||||
comptime return out;
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// RHS normalisation helpers
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
const Quantity = @import("Quantity.zig").Quantity;
|
||||
|
||||
/// Returns true if `T` is a `Scalar_` type (has `dims`, `scales`, and `value`).
|
||||
pub fn isScalarType(comptime T: type) bool {
|
||||
return @typeInfo(T) == .@"struct" and
|
||||
@hasDecl(T, "ISQUANTITY") and
|
||||
@field(T, "ISQUANTITY");
|
||||
}
|
||||
|
||||
/// Resolve the Scalar type that `rhs` will be treated as.
|
||||
///
|
||||
/// Accepted rhs types:
|
||||
/// - Any `Scalar_` type → returned as-is
|
||||
/// - `comptime_int` / `comptime_float` → dimensionless `Scalar_(BaseT, {}, {})`
|
||||
/// - `BaseT` (the scalar's value type) → dimensionless `Scalar_(BaseT, {}, {})`
|
||||
///
|
||||
/// Everything else is a compile error, including other int/float types.
|
||||
pub fn rhsQuantityType(comptime ValueType: type, N: usize, comptime RhsT: type) type {
|
||||
if (comptime isScalarType(RhsT)) return RhsT;
|
||||
if (comptime RhsT == comptime_int or RhsT == comptime_float or RhsT == ValueType)
|
||||
return Quantity(ValueType, N, .{}, .{});
|
||||
@compileError(
|
||||
"rhs must be a Scalar, " ++ @typeName(ValueType) ++
|
||||
", comptime_int, or comptime_float; got " ++ @typeName(RhsT),
|
||||
);
|
||||
}
|
||||
|
||||
/// Convert `rhs` to its normalised Scalar form (see `rhsScalarType`).
|
||||
pub inline fn toRhsQuantity(comptime BaseT: type, N: usize, rhs: anytype) rhsQuantityType(BaseT, N, @TypeOf(rhs)) {
|
||||
if (comptime isScalarType(@TypeOf(rhs))) return rhs;
|
||||
const DimLess = Quantity(BaseT, N, .{}, .{});
|
||||
return DimLess{ .data = @splat(@as(BaseT, rhs)) };
|
||||
}
|
||||
@ -1,15 +1,13 @@
|
||||
const std = @import("std");
|
||||
|
||||
pub const Vector = @import("Quantity.zig").Vector;
|
||||
pub const Scalar = @import("Quantity.zig").Scalar;
|
||||
pub const Tensor = @import("Tensor.zig").Tensor;
|
||||
pub const Dimensions = @import("Dimensions.zig");
|
||||
pub const Scales = @import("Scales.zig");
|
||||
pub const Base = @import("Base.zig");
|
||||
|
||||
test {
|
||||
_ = @import("Quantity.zig");
|
||||
_ = @import("Tensor.zig");
|
||||
_ = @import("Dimensions.zig");
|
||||
_ = @import("Scales.zig");
|
||||
_ = @import("Base.zig");
|
||||
_ = @import("helper.zig");
|
||||
}
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user