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-rw-r--r--build.zig92
-rw-r--r--src/monkey_brain/main.zig5
-rw-r--r--src/monkey_brain/multi_layer_perceptron.zig0
-rw-r--r--src/monkey_brain/perceptron.zig83
-rw-r--r--src/monkey_brain/test.zig5
5 files changed, 140 insertions, 45 deletions
diff --git a/build.zig b/build.zig
index 5a00841..dbaf428 100644
--- a/build.zig
+++ b/build.zig
@@ -15,61 +15,63 @@ pub fn build(b: *std.Build) void {
     // set a preferred release mode, allowing the user to decide how to optimize.
     const optimize = b.standardOptimizeOption(.{});
 
-    const exe = b.addExecutable(.{
-        .name = "tinkerbunk",
-        .root_source_file = b.path("src/main.zig"),
-        .target = target,
-        .optimize = optimize,
-    });
+    if (target.query.os_tag == .linux) {
+        const exe = b.addExecutable(.{
+            .name = "tinkerbunk",
+            .root_source_file = b.path("src/main.zig"),
+            .target = target,
+            .optimize = optimize,
+        });
 
-    // linking for linux only
-    // TODO: link for mac later
-    exe.linkSystemLibrary("SDL2");
-    exe.linkSystemLibrary("mpg123");
-    exe.linkSystemLibrary("asound");
-    exe.linkLibC();
-    exe.addCSourceFile(.{ .file = b.path("csrc/cbrr.c"), .flags = &.{} });
-    exe.addIncludePath(b.path("./csrc"));
+        exe.linkSystemLibrary("SDL2");
+        exe.linkSystemLibrary("mpg123");
+        exe.linkSystemLibrary("asound");
+        exe.linkLibC();
+        exe.addCSourceFile(.{ .file = b.path("csrc/cbrr.c"), .flags = &.{} });
+        exe.addIncludePath(b.path("./csrc"));
 
-    // This declares intent for the executable to be installed into the
-    // standard location when the user invokes the "install" step (the default
-    // step when running `zig build`).
-    b.installArtifact(exe);
+        b.installArtifact(exe);
 
-    // This *creates* a Run step in the build graph, to be executed when another
-    // step is evaluated that depends on it. The next line below will establish
-    // such a dependency.
-    const run_cmd = b.addRunArtifact(exe);
+        const run_cmd = b.addRunArtifact(exe);
+        run_cmd.step.dependOn(b.getInstallStep());
 
-    // By making the run step depend on the install step, it will be run from the
-    // installation directory rather than directly from within the cache directory.
-    // This is not necessary, however, if the application depends on other installed
-    // files, this ensures they will be present and in the expected location.
-    run_cmd.step.dependOn(b.getInstallStep());
+        // This allows the user to pass arguments to the application in the build
+        // command itself, like this: `zig build run -- arg1 arg2 etc`
+        if (b.args) |args| {
+            run_cmd.addArgs(args);
+        }
 
-    // This allows the user to pass arguments to the application in the build
-    // command itself, like this: `zig build run -- arg1 arg2 etc`
-    if (b.args) |args| {
-        run_cmd.addArgs(args);
-    }
+        const run_step = b.step("run", "Run the app");
+        run_step.dependOn(&run_cmd.step);
 
-    // This creates a build step. It will be visible in the `zig build --help` menu,
-    // and can be selected like this: `zig build run`
-    // This will evaluate the `run` step rather than the default, which is "install".
-    const run_step = b.step("run", "Run the app");
-    run_step.dependOn(&run_cmd.step);
+        const exe_unit_tests = b.addTest(.{
+            .root_source_file = b.path("src/main.zig"),
+            .target = target,
+            .optimize = optimize,
+        });
+        const run_exe_unit_tests = b.addRunArtifact(exe_unit_tests);
+        const test_step = b.step("test", "Run unit tests");
+        test_step.dependOn(&run_exe_unit_tests.step);
+    }
 
-    const exe_unit_tests = b.addTest(.{
-        .root_source_file = b.path("src/main.zig"),
+    // monkey brains
+    const monkey_brain = b.addExecutable(.{
+        .name = "monkey_brain",
+        .root_source_file = b.path("src/monkey_brain/main.zig"),
         .target = target,
         .optimize = optimize,
     });
+    b.installArtifact(monkey_brain);
+
+    const monkey_brain_run = b.addRunArtifact(monkey_brain);
+    monkey_brain_run.step.dependOn(b.getInstallStep());
+
+    const monkey_run_step = b.step("monkey_run", "Run the monkey brain");
+    monkey_run_step.dependOn(&monkey_brain_run.step);
 
-    const run_exe_unit_tests = b.addRunArtifact(exe_unit_tests);
+    const monkey_test_exec = b.addTest(.{ .root_source_file = b.path("src/monkey_brain/test.zig"), .target = target, .optimize = optimize });
 
-    // Similar to creating the run step earlier, this exposes a `test` step to
-    // the `zig build --help` menu, providing a way for the user to request
-    // running the unit tests.
-    const test_step = b.step("test", "Run unit tests");
-    test_step.dependOn(&run_exe_unit_tests.step);
+    const monkey_test_run = b.addRunArtifact(monkey_test_exec);
+    const monkey_test_step = b.step("monkey_test", "Run monkey brain cells test");
+    monkey_test_step.dependOn(&monkey_test_run.step);
 }
diff --git a/src/monkey_brain/main.zig b/src/monkey_brain/main.zig
new file mode 100644
index 0000000..611dcd1
--- /dev/null
+++ b/src/monkey_brain/main.zig
@@ -0,0 +1,5 @@
+const perceptron = @import("perceptron.zig");
+
+pub fn main() !void {
+    try perceptron.demo();
+}
diff --git a/src/monkey_brain/multi_layer_perceptron.zig b/src/monkey_brain/multi_layer_perceptron.zig
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/src/monkey_brain/multi_layer_perceptron.zig
diff --git a/src/monkey_brain/perceptron.zig b/src/monkey_brain/perceptron.zig
new file mode 100644
index 0000000..893bb16
--- /dev/null
+++ b/src/monkey_brain/perceptron.zig
@@ -0,0 +1,83 @@
+const std = @import("std");
+const testing = std.testing;
+const math = std.math;
+
+const input_size: usize = 2;
+const training_set_size: usize = 4;
+const learning_rate: f64 = 0.1;
+const epochs: u64 = 1000000;
+
+// https://en.wikipedia.org/wiki/Sigmoid_function - more details
+// https://www.youtube.com/watch?v=TPqr8t919YM
+fn sigmoid(x: f64) f64 {
+    return 1.0 / (1.0 + math.exp(-x));
+}
+
+fn sigmoid_derivative(output: f64) f64 {
+    return output * (1.0 - output);
+}
+
+fn predict(weights: [input_size]f64, bias: f64, inputs: [input_size]f64) f64 {
+    var total: f64 = bias;
+    for (inputs, 0..) |input, i| {
+        total += weights[i] * input;
+    }
+    return sigmoid(total);
+}
+
+fn train(weights: *[input_size]f64, bias: *f64, training_data: [training_set_size][input_size]f64, labels: [training_set_size]f64) void {
+    for (0..epochs) |_| {
+        for (training_data, labels) |inputs, label| {
+            const prediction = predict(weights.*, bias.*, inputs);
+            const err = label - prediction;
+            const adjustment = err * sigmoid_derivative(prediction);
+            for (inputs, 0..) |input, j| {
+                weights[j] += learning_rate * adjustment * input;
+            }
+            bias.* += learning_rate * adjustment;
+        }
+    }
+}
+
+pub fn demo() !void {
+    var weights = [_]f64{ std.crypto.random.float(f64), std.crypto.random.float(f64) };
+    var bias: f64 = std.crypto.random.float(f64);
+
+    const training_data = [_][input_size]f64{
+        .{ 0, 0 },
+        .{ 0, 1 },
+        .{ 1, 0 },
+        .{ 1, 1 },
+    };
+    const labels = [_]f64{ 0, 1, 1, 1 }; // OR operation
+
+    train(&weights, &bias, training_data, labels);
+
+    std.debug.print("Trained weights: {d}, {d}\n", .{ weights[0], weights[1] });
+    std.debug.print("Trained bias: {d}\n", .{bias});
+
+    for (training_data, labels) |inputs, expected| {
+        const prediction = predict(weights, bias, inputs);
+        std.debug.print("Input: {d}, {d}, Predicted: {d:.4}, Expected: {d}\n", .{ inputs[0], inputs[1], prediction, expected });
+    }
+}
+
+test "OR gate" {
+    var weights = [_]f64{ 0, 0 };
+    var bias: f64 = 0;
+
+    const training_data = [_][input_size]f64{
+        .{ 0, 0 },
+        .{ 0, 1 },
+        .{ 1, 0 },
+        .{ 1, 1 },
+    };
+    const labels = [_]f64{ 0, 1, 1, 1 };
+
+    train(&weights, &bias, training_data, labels);
+
+    for (training_data, labels) |inputs, expected| {
+        const prediction = predict(weights, bias, inputs);
+        try testing.expect((prediction - expected) < 0.1);
+    }
+}
diff --git a/src/monkey_brain/test.zig b/src/monkey_brain/test.zig
new file mode 100644
index 0000000..4d4a04b
--- /dev/null
+++ b/src/monkey_brain/test.zig
@@ -0,0 +1,5 @@
+pub const perceptron = @import("perceptron.zig");
+
+test {
+    @import("std").testing.refAllDecls(@This());
+}