## Table of Contents

## Ray Tracing in Lua

*This is a work-in-progress. I'll keep posting as I work through the book!!*

*Last update:*

I've never done much graphics programming, but I've always wanted to explore it. I think the most common approach is to go straight to OpenGL, but I tend to approach a domain from first principles, especially when I'm coding for fun, so I turned to Amazon and found Ray Tracing in One Weekend for $3. It tackles everything in C++, and I thought it would be a fun exercise to follow the algorithms laid out in the book, and I could focus on learning how ray tracing works while porting all the code to Lua.

Lua might seem like exactly the wrong choice for ray tracing, which requires high performance and lends itself to a language that can parallelize the compuation, but I enjoy working in small languages that use few data structures to accomplish many things, so I'm curious to see how far I can get in Lua. I'm going to stick with `luajit`

, however, as it is quite a bit faster than `lua5.3`

. As such, the code will be `lua5.1`

compatible, since that's the version of the language `luajit`

targets.

### Chapter 1 - Graphical Hello World

The first step is to produce a PPM file that demonstrates we can create images at all. All it does is alter the red and green channel during iteration over the pixels to create a color gradient. Our image size is defined at the top. In the C++ code, it is locked to a 200px x 100px image, but I found that that scaling it by 3x to 600x300 is more visually engaging, so I switched in the Lua code to reflect that. PPM files are easy to create, but very inefficient. In the spirit of "make it work, make it right, make it fast", I'll worry about optimizing the file format later, and probably only if needed.

#! /usr/bin/env luajit nx = 600 ny = 300 print(string.format("P3\n%s %s\n255\n", nx, ny)) for j = ny-1, 0, -1 do for i = 0, nx-1 do r = i/nx g = j/ny b = 0.2 ir = math.floor(256*r) ig = math.floor(256*g) ib = math.floor(256*b) print(string.format("%s %s %s", ir, ig, ib)) end end

I keep a running Emacs `shell`

buffer alongside my code, and I can run this command to display the image after I change the code:

./ray.lua | convert - chapter1.png && emacsclient -n chapter1.png

The result looks like this:

### Chapter 2 - The `Vector3`

Class

This chapter defines the `Vector3`

class, which I understand will be used for all sorts of vectors in later chapters. I thought a bit about whether to change to a more functional approach since I'm in Lua, and decided that I'd learn a bit more and have a bit of fun by using Lua's metatables to retain the object-oriented approach in the original C++. So I did a bit of research about how objects are approached in Lua put together `Vector3`

, a Lua interpretation of the C++ version's `vec3`

.

Vectors are simply Lua tables, and since they are generic, they have accessors supporting both cartesian and RGB interpretations. This is unconventional, but follows the pattern in the book.

Vector3 = {} function Vector3:new(o) o = o or {} self.__index = self setmetatable(o, self) return o end -- Accessors for cartesian coords function Vector3:x() return self[1] end function Vector3:y() return self[2] end function Vector3:z() return self[3] end -- Accessors for RGB values function Vector3:r() return self[1] end function Vector3:g() return self[2] end function Vector3:b() return self[3] end

Since I'm trying out all my code using the Lua REPL, I also want a nice string representation for vectors. It's easy to attach the `tostring`

method to the metamethod `__tostring`

, which is used by the REPL when printing out results.

-- REPL usability function Vector3:tostring() return string.format("Vector3{%s, %s, %s}", self[1], self[2], self[3]) end Vector3.__tostring = Vector3.tostring

Next, I implement a straight port of the C++ mathematical functions for vectors, attaching them to Lua's metamethods where available.

-- Mathematical operations function Vector3:add(vec) return Vector3:new{self[1] + vec[1], self[2] + vec[2], self[3] + vec[3]} end Vector3.__add = Vector3.add function Vector3:sub(vec) return Vector3:new{self[1] - vec[1], self[2] - vec[2], self[3] - vec[3]} end Vector3.__sub = Vector3.sub function Vector3:mul(val) local t = type(val) if t == "number" then return self:nmul(val) elseif t == "table" then return self:vmul(val) end end Vector3.__mul = Vector3.mul function Vector3:div(val) local t = type(val) if t == "number" then return self:ndiv(val) elseif t == "table" then return self:vdiv(val) end end Vector3.__div = Vector3.div function Vector3:negate() return Vector3:new{-self[1], -self[2], -self[3]} end Vector3.__unm = Vector3.negate function Vector3:length() return math.sqrt(self:squared_length()) end function Vector3:squared_length() return self[1]*self[1] + self[2]*self[2] + self[3]*self[3] end function Vector3:dot(vec) return self[1] * vec[1] + self[2] * vec[2] + self[3] * vec[3] end function Vector3:cross(vec) return Vector3:new{ self[2] * vec[3] - self[3] * vec[2], self[3] * vec[1] - self[1] * vec[3], self[1] * vec[2] - self[2] * vec[1] } end function Vector3:unit_vector() local l = self:length() return Vector3:new{self[1]/l, self[2]/l, self[3]/l} end -- Destructive functions function Vector3:make_unit_vector() k = 1 / self:length() self[1] = self[1]*k self[2] = self[2]*k self[3] = self[3]*k end

Many of the functions above are defined in the C++ code as `inline`

and `const`

. I'm not well-versed in C++, but after reading up on these keywords, I think they are both compiler hints that improve performance: `inline`

inlines the function so we avoid dispatch overhead, and `const`

allows the compiler to assume the value won't change, allowing further optimizations. Neither is present in Lua, so I've ignored them above. The C++ implementation also leverages static dispatch for performance, but Lua isn't statically typed, so my implementation will be dynamically dispatched. In the case of `mul`

and `div`

, which can accept either a `number`

(scalar context) or a `table`

(vector context), I use reflection via the `type`

method to determine context and then dispatch to the appropriate implementation. The actual implementations are below.

-- Internal implementations function Vector3:nmul(num) return Vector3:new{self[1]*num, self[2]*num, self[3]*num} end function Vector3:vmul(vec) return Vector3:new{self[1]*vec[1], self[2]*vec[2], self[3]*vec[3]} end function Vector3:ndiv(num) return Vector3:new{self[1]/num, self[2]/num, self[3]/num} end function Vector3:vdiv(vec) return Vector3:new{self[1]/vec[1], self[2]/vec[2], self[3]/vec[3]} end

This completes our Lua implementation of `Vector3`

. A notable omission from the C++ implementation are the `+=`

, `-=`

, `*=`

, and `/=`

operators, which have no associated metamethods in Lua due to its single-pass parse model. As a result, I'm leaving them out for now, but I might add them later if the ray tracing code becomes to unweildy without them.

The code at the end of the chapter uses the new `vec3`

abstraction. We can use our `Vector3`

class instead.

nx = 600 ny = 300 print(string.format("P3\n%s %s\n255\n", nx, ny)) for j = ny-1, 0, -1 do for i = 0, nx-1 do v = Vector3:new{i/nx, j/ny, 0.2} ir = math.floor(256*v[1]) ig = math.floor(256*v[2]) ib = math.floor(256*v[3]) print(string.format("%s %s %s", ir, ig, ib))- end end

With this new libary to handle vectors, we can take a look at modeling how light moves!

### Chapter 3 - Rays, Camera, Background

We start by defining a `Ray`

class:

-- Ray Class Ray = {} -- Parameters: -- origin: Vector3 -- direction: Vector3 -- Example: -- Ray:new{Vector3:new{0, 0, 0}, Vector3:new{0, 0, -1}} function Ray:new(o) o = o or {} self.__index = self setmetatable(o, self) return o end function Ray:origin() return self[1] end function Ray:direction() return self[2] end function Ray:point_at_parameter(t) return self[1] + self[2] * t end

While we're here, we can add our usual handy `tostring`

method and bind it.

function Ray:tostring() return string.format("Ray{origin: %s, direction: %s}", self[1], self[2]) end Ray.__tostring = Ray.tostring

#### The Color Method

Now we can add the `color`

method:

function Ray:color() unit_direction = self:direction():unit_vector() t = 0.5 * (unit_direction:y() + 1) return Vector3:new{1, 1, 1} * (1 - t) + Vector3:new{0.5, 0.7, 1} * t end

The `color`

method is worth an explanation. It first generates the unit vector for the direction, clamping the length to 1. It then computes `t`

, which takes the unit vector's vertical component (which can vary from -1 to 1, since that's the y-value of the bottom and top of our virtual screen, as you'll see below), adds one to get a value between 0 and 2, and then compresses the range to 0 to 1 by multiplying by 0.5. This is mathematically attractive because `t`

can now be used as a scaling factor for our color vectors. The final part of `color`

is to calculate the color of the pixel.

The general strategy is to blend pure white (an RGB vector of 1, 1, 1) and light blue (an RGB vector of 0.5, 0.7, 1) proportionally to the value of `t`

, which again is really an expression of the vertical offset of the pixel. This means the pixels at the top of the image will be pure blue and the pixels at the bottom will be pure white, with pixels in between blending the two.

You'll notice that it's not a pure vertical gradient, though. That's because the vertical offset when clamping the ray's direction to a unit vector is diminished for pixels with a high horizontal offset, so pixels near the corners avoid extreme values of pure white and pure blue, instead remaining a blend. This produces a very natural effect that looks like the sky.

#### Adding Color to Each Pixel

I then put together the main function, and simply inlined it at the end of the file.

nx = 200 ny = 100 print(string.format("P3\n%s %s\n255\n", nx, ny)) lower_left_corner = Vector3:new{-2, -1, -1} horizontal = Vector3:new{4, 0, 0} vertical = Vector3:new{0, 2, 0} origin = Vector3:new{0, 0, 0} for j = ny-1, 0, -1 do for i = 0, nx-1 do u = i / nx v = j / ny r = Ray:new{origin, lower_left_corner + (horizontal * u) + (vertical * v)} col = r:color() ir = math.floor(256 * col[1]) ig = math.floor(256 * col[2]) ib = math.floor(256 * col[3]) print(string.format("%s %s %s", ir, ig, ib)) end end

This new approach introduces the notion of an `origin`

, which is where the camera is placed. It also introduces the notion of a screen, and places it one unit away, with a `Z`

value of `-1`

. The screen is defined in terms of its `lower_left_corner`

and its `horizontal`

and `vertical`

dimensions. The screen is twice as wide as it is high, with a width of `4`

units and a height of `2`

units.

In every graphics application, there needs to be some way to map the scene-space the world is calculated in to the pixels in the image being generated. Above, this is handled at the moment we shoot a ray out from the camera. Each `Ray`

requires two vectors: an `origin`

and a `direction`

. The `origin`

of that ray is the camera, but the direction requires some computation.

We're trying to determine the color of a pixel, so our computation in based on the coordinates of that pixel in image-space, but the final value needs to be in scene-space to match the `origin`

vector. We compute the direction by starting from lower left corner of our image and calculating the offset of the current pixel in the x and y direction. Since we're iterating over each pixel in our image (defined by `nx`

and `ny`

), this offset is calulated in terms of a the ratio of we are along the x and y axis to the total image size in that dimension. We then convert to "scene-space" by multiplying by the coodinate dimensions of the image ((`horizontal`

and `vertical`

) to get the final direction vector. Our ray is now fully defined, and we can ask it what its color is.

In the original C++, most vector multiplication by a scalar, like in the `color`

function for a `Ray`

, are performed by multiplying the number by the vector, rather than the vector by the number. Mathematically it doesn't make a difference, but the order matters during dispatch, and numbers don't have a `__mul`

operator that works with `Vector3`

. To remedy this, I changed the order of the parameters in the Lua implementation. After converting to `png`

, the output of the program matches the C++ version.

### Chapter 4 - Adding a Sphere

I'd previously made the decision to move the `color`

function into the `Ray`

class simply because a ray's color can be expected to be constant for a given scene, and I envision all this code running in the context of a constant scene. Chapter 4 modifies `Ray`

's `color`

function to call an additional check called `hit_sphere`

, so I've baked that function into the `Ray`

class as well. This clearly isn't sustainable, since binding scene logic to the `Ray`

class is madness. But for now, it's great, and I'll change it when need be.

The modification to `color`

is straightforward: if the ray would hit a sphere centered at \(\{0, 0, -1\}\) with a radius of 0.5, return red. Otherwise, compute the value for the blue/white gradient we defined in Chapter 3.

function Ray:color() if (self:hit_sphere(Vector3:new{0, 0, -1}, 0.5)) then return Vector3:new{1, 0, 0} end unit_direction = self:direction():unit_vector() t = 0.5 * (unit_direction:y() + 1) return Vector3:new{1, 1, 1} * (1 - t) + Vector3:new{0.5, 0.7, 1} * t end

Next, we need to define `hit_sphere`

, which is responsible for whether or not the `Ray`

intersects the sphere.

The original text has a great explanation on how to approach this for implementing a numerical method in a ray tracer. If you consider a sphere centered at \((cx, cy, cz)\) with a radius \(R\), the text leverages the insight that points on that sphere must satisfy \(cx^2 + cy^2 + cz^2 = R^2\). This is a scalar equation, however, and we want to leverage our vector-based abstractions. Following this line of reasoning, the text observes that, letting C represent the center of the sphere, point \(p\) is on the sphere if \((p-c) \cdot (p-c) = R^2\). This is a useful insight, but we need to somehow map its notion of \(p\) onto our notion of a `Ray`

, which takes a parameter, \(t\). If we simply substitute \(p(t)\) in for \(p\), and then utilize \(p(t) = A + tB\), we obtain \((A + tB - C) \cdot (A + tB - C)) = R^2\).

-- Parameters: -- center: Vector3 -- radius: number -- Returns: boolean -- -- Returns true iff this Ray intersects the sphere specified -- by the provided center and radius, otherwise false. function Ray:hit_sphere(center, radius) offset = self:origin() - center a = self:direction():dot(self:direction()) b = offset:dot(self:direction()) * 2.0 c = offset:dot(offset) - radius * radius discriminant = b * b - a * c * 4 return discriminant > 0 end

Running this, we obtain the expected result: a red ball in the middle of the screen!

### Chapter 5 - Surface Normals and Multiple Objects

Surface normals are vectors that point directly *away* from the surface of an object. It's really just the the point where the ray hits the object minus the center of the object. In more geometric terms, it's an arrow pointing from the center of the sphere outward towards where the ray hit the sphere. That's it.

#### Visualizing Normals

To visualize that we're computing this correctly, we can, as an intermittent step, simply visualize the normals by converting them to colors. To do this, we need to first modify `hit_sphere`

to calculate the normal, and instead of returning a `boolean`

to indicate whether the sphere was hit, we instead return the point on the sphere where the ray hit it. If the ray does not intersect the sphere, we use a sentinel value of -1 to indicate that.

-- Parameters: -- center: Vector3 -- radius: number -- Returns: [Vector3] the point on the sphere where the ray hit it -- -- Returns true iff this Ray intersects the sphere specified -- by the provided center and radius, otherwise false. function Ray:hit_sphere(center, radius) oc = self:origin() - center a = self:direction():dot(self:direction()) b = oc:dot(self:direction()) * 2.0 c = oc:dot(oc) - radius * radius discriminant = b * b - a * c * 4 if discriminant < 0 then return -1 else return (-b - math.sqrt(discriminant)) / 2 * a end end

Previously, however, the `color`

method relied on `hit_sphere`

returning a `boolean`

value, and it also assumed the color of the sphere was always red. Let's update `color`

to make use of the point at which the ray hits the sphere and create a color based on it's normal.

function Ray:color() t = self:hit_sphere(Vector3:new{0, 0, -1}, 0.5) if t > 0 then normal = (self:point_at_parameter(t) - Vector3:new{0, 0, -1}):unit_vector() return Vector3:new{normal:x()+1, normal:y()+1, normal:z()+1} * 0.5 end unit_direction = self:direction():unit_vector() t = 0.5 * (unit_direction:y() + 1) return Vector3:new{1, 1, 1} * (1 - t) + Vector3:new{0.5, 0.7, 1} * t end

This yields sort of rainbow effect since it visualizes the vector space of all the normals as colors:

#### Creating Objects

The current code bakes the sphere we've been rendering into the render path itself, but we'll want to have the rendering code independent of what objects it is rendering, so we need an abstraction. One useful way to approach this is based on the insight that we're dealing with objects that a `Ray`

could hit. Naming objects in object-oriented languages is challenging, so *Ray Tracing in One Weekend* opted to called them `hitable`

. Since we're in a dynamic language, I can elide the contract boilerplate in the original C++, but I need to ensure each object we want to render has a `hit`

method attached. The first step is to pull out the logic for our sphere into a dedicated class, which we can then attach a `hit`

method to.

Sphere = {} -- Parameters: -- origin: Vector3 -- radius: number -- Example: -- Sphere:new{Vector3:new{0, 0, 0}, 0.5} function Sphere:new(o) o = o or {} self.__index = self setmetatable(o, self) return o end function Sphere:center() return self[1] end function Sphere:radius() return self[2] end

As we did with `Ray`

, it's nice to have a good string representation available on the REPL.

function Sphere:tostring() return string.format("Sphere{center: %s, radius: %s}", self[1], self[2]) end Sphere.__tostring = Sphere.tostring

#### Making Objects Hitable

The `hit`

method itself has an interesting contract that depends upon a `hit_record`

. The Lua version of `hit_record`

looks something like this:

HitRecord = {} -- Parameters -- t: [number] time at which impact occurred -- p [Vector3] point of impact -- normal [Vector3] normal from point of impact function HitRecord:new(o) o = o or {} self.__index = self setmetatable(o, self) return o end function HitRecord:t() return self[1] end function HitRecord:p() return self[2] end function HitRecord:normal() return self[3] end

This implementation covers the three values included in the C++ version, but that version returns a `boolean`

value indicating whether the object was hit or not as well. If a hit does occur, the C++ code destructively modifies the `hit_record`

parameter passed in. This is typical in C and C++, but not idiomatic in Lua. For the Lua version, we can provide a field in `hit_record`

to record whether a hit occurred, and then simply return the `hit_record`

regardless of whether a hit occurred:

function HitRecord:hit() return self[1] end function HitRecord:t() return self[2] end function HitRecord:p() return self[3] end function HitRecord:normal() return self[4] end

This alters the contract to make it less surprising in Lua, but doesn't yet make a `Sphere`

hitable. If we follow the original C++, this requires implementing a `hit`

method for `Sphere`

. This is a moment to pause and consider our architecture, since I'd previously decided to attach the hit method to `Ray`

class. Ultimately, we'll have a table that contains a whole bunch of objects (we'll assume that's called the `world`

) that support the `hit`

method, and as we render the scene, we'll create rays one-by-one and ask them what `color`

they are. Should every `Ray`

contain a reference to the `world`

? Will we want to ask a `Ray`

for its color in the context of more than one `world`

? It doesn't seem likely, since we often think of a ray-traced image as a visual representation of a particular `world`

. The overhead of passing the `world`

pointer to each ray as it is constructed is likely negligible, so we'll assume for now that the `hit`

method will move from the `Ray`

class to the object classes (making them hitable!) and that later on, we'll pass the whole scene/world to each `Ray`

when we construct it. Let's do it!

function Sphere:hit(ray, t_min, t_max) oc = ray:origin() - self:center() a = ray:direction():dot(ray:direction()) b = oc:dot(ray:direction()) c = oc:dot(oc) - self:radius() * self:radius() discriminant = b * b - a * c if discriminant > 0 then time = (-b - math.sqrt(discriminant)) / a if time < t_max and time > t_min then return self:hit_record(ray, time) end time = (-b + math.sqrt(discriminant)) / a if time < t_max and time > t_min then return self:hit_record(ray, time) end end return HitRecord:new{false} end

You'll notice that this method delegates to a method I created for this implementation called `hit_record`

. I did this to minimize the duplication of code within `Sphere`

. Here it is:

function Sphere:hit_record(ray, time) point_of_impact = ray:point_at_parameter(time) return HitRecord:new{ true, time, point_of_impact, (point_of_impact - self:center()) / self:radius() } end

#### Creating the World

Now that we have the notion of a hitable object, we can make it easy to test whether a `Ray`

hits any of them by creating a `World`

object. In the original code, this is called `hitable_list`

, and it has a `hit`

method just as hitable objects do. We'll apply the same parameter transformation that we did for `Sphere`

and elide the hit record from the parameter list.

World = {} function World:new(o) o = o or {} self.__index = self setmetatable(o, self) return o end function World:hit(ray, t_min, t_max) closest_hit_record = HitRecord:new{false, t_max} for idx, obj in pairs(self) do hit_record = obj:hit(ray, t_min, closest_hit_record:t()) if hit_record:hit() then closest_hit_record = hit_record end end return closest_hit_record end

A couple of notes here. First, we have to iterate through every object no matter what, because we need to return the point that the ray hits that is closest to the camera. We can't be sure we got it right unless we check every object. This also means that the order of iteration through the objects in the world doesn't matter, so I use `pairs`

instead of `ipairs`

. I'm not sure if it is actually slower to use `ipairs`

in `luajit`

, but given that it adds an additional constraint to the iteration, I suspect it may be. Secondly, the use of `HitRecord`

as the sole return value from the this method significantly cleans up the code when compared to the corresponding C++ code with uses destructive modification. Since it's allocating a new table on each call, however, I suspect there's a significant performance penalty in terms of at least GC, if not allocation. We'll revisit this decision if it becomes a problem, but cleaner code takes precedence, all other things being equal.

We now need to make sure that `Ray`

gets a reference to `world`

when it is created. Since the way we're crafting constructors is very liberal, only the documentation needs to be updated. But we still need to define an accessor.

function Ray:world() return self[3] end

But we still haven't update `Ray:color`

to remove the hardcoded reference to a sphere. Let's update that.

function Ray:color() hit_record = self:world():hit(self, 0, math.huge) if hit_record:hit() then normal = hit_record:normal() return Vector3:new{normal:x()+1, normal:y()+1, normal:z()+1} * 0.5 end unit_direction = self:direction():unit_vector() t = 0.5 * (unit_direction:y() + 1) return Vector3:new{1, 1, 1} * (1 - t) + Vector3:new{0.5, 0.7, 1} * t end

This method is largely symmetric with the version we used in Chapter 4, returning the normal-vector-as-a-color if a hit is detected, and otherwise returning the blue background gradient from Chapter 3.

Finally, we can update our entry point to make use of all our new machinery!

nx = 600 ny = 300 print(string.format("P3\n%s %s\n255\n", nx, ny)) lower_left_corner = Vector3:new{-2, -1, -1} horizontal = Vector3:new{4, 0, 0} vertical = Vector3:new{0, 2, 0} origin = Vector3:new{0, 0, 0} small_sphere = Sphere:new{Vector3:new{0, 0, -1}, 0.5} big_sphere = Sphere:new{Vector3:new{0, -100.5, -1}, 100} world = World:new{small_sphere, big_sphere} for j = ny-1, 0, -1 do for i = 0, nx-1 do u = i / nx v = j / ny ray = Ray:new{origin, lower_left_corner + (horizontal * u) + (vertical * v), world} col = ray:color() ir = math.floor(256 * col[1]) ig = math.floor(256 * col[2]) ib = math.floor(256 * col[3]) print(string.format("%s %s %s", ir, ig, ib)) end end

Aside from the "world creation" code just before the iteration, there's remarkably little different from the earlier iterations. Here's the result:

### Chapter 6 - Antialiasing

If you look at the images above, particularly if you zoom in, you'll notice "jaggies": the image is jagged at the edges of the spheres. That's because in our current implementation, each pixel either hits the object (and takes on that object's color at that point), or it simply takes on the color of the background at that location: there is no in-between. Antialiasing is a technique that randomly samples multiple points *within* a pixel, and then blends the colors at each point within that pixel to compute the final color the pixel should be. Antialiasing is measured in terms of the number of samples taken per-pixel, all the way from 2x antialiasing to 16x antialiasing. I gather that there's actually a lot more to antialiasing than this, but this is my understanding so far from reading this book and my previous knowledge from tweaking video game settings to trade off between performance and quality.

#### Introducing the Camera

If we're going to shoot multiple rays per pixel, where should the logic live? The `Ray`

class seems inappropriate, as does `World`

and `Vector3`

. In the real world, analog cameras (using film!) do this naturally. Perhaps a solution is to introduce a class that represents the camera. Rather than the main method, the camera can encapsulate the screen dimensions and ray generation instead.

Camera = {} function Camera:new(o) base = { lower_left_corner=Vector3:new{-2, -1, -1}, horizontal=Vector3:new{4, 0, 0}, vertical=Vector3:new{0, 2, 0}, origin=Vector3:new{0, 0, 0} } o = o or {} for k,v in pairs(base) do o[k] = v end self.__index = self setmetatable(o, self) return o end -- Accessors to maintain symmetric access via function calls function Camera:lower_left_corner() return self.lower_left_corner end function Camera:horizontal() return self.horizontal end function Camera:vertical() return self.vertical end function Camera:origin() return self.origin end

In addition to capturing the basic screen dimensions we're working with, we also want the camera to generate rays for us. To do this, though, it needs a reference to the `world`

. So, we define an accessor, and then proceed with `get_ray`

:

function Camera:world() return self[1] end function Camera:get_ray(u, v) return Ray:new{ self.origin, self.lower_left_corner + (self.horizontal * u) + (self.vertical * v) - self.origin, self:world() } end

This is essentially the exact same logic that was previously in the main method, but now encapsulated. But that means we need to update `main`

to request that the camera generate multiple rays per pixel.

function main() nx = 600 ny = 300 ns = 100 print(string.format("P3\n%s %s\n255\n", nx, ny)) small_sphere = Sphere:new{Vector3:new{0, 0, -1}, 0.5} big_sphere = Sphere:new{Vector3:new{0, -100.5, -1}, 100} world = World:new{small_sphere, big_sphere} camera = Camera:new{world} for j = ny-1, 0, -1 do for i = 0, nx-1 do col = Vector3:new{0, 0, 0} for s = 0, ns do u = (i + math.random()) / nx v = (j + math.random()) / ny ray = camera:get_ray(u, v) col = col + ray:color() end col = col / (ns + 1) ir = math.floor(256 * col[1]) ig = math.floor(256 * col[2]) ib = math.floor(256 * col[3]) print(string.format("%s %s %s", ir, ig, ib)) end end end

The notable addition here is that we now sample each pixel 100 times and average the color that is returned. Running this takes about 24 seconds on my laptop, and produces this result: