# Finishing the Interval Push type in Klapaucius

Draft of 2016.07.09

May include: GP ↘ Push ↗ learning in public ↖ &c.

Continues “The Interval Push type in Klapaucius”

I’ll get straight to work this morning. I’m thinking of using this Wikipedia page on Interval Arithmetic as a simple guide, and creating pairs of instructions in which either two `:interval`

items or an `:interval`

and a `:scalar`

are involved, like `:interval-add`

and `:interval-offset`

for addition, and so on. Although there really isn’t a good reason to have a separate function adding a `:scalar`

to an `:interval`

, and another subtracting a `:scalar`

from an `:interval`

….

I’ll get to that. I have a suspicion, going in, that *division* (as ever) will be tricky and not especially fun, what with its contingencies and the description on the Wikipedia page of how `Infinity`

is used explicitly in the calculations of the most common algorithms. But I think I can manage.

## Adding adding

Interval addition is relatively simple. The sum is a new `:interval`

with `:min`

equal to the sum of the `:min`

of each argument, and the result’s `:min-open?`

will be `true`

if either argument’s was `true`

. And, of course, the same for `:max`

throughout.

As a side note, I realize this *only* works because I changed the unsorted `:start`

and `:end`

of `Span`

to a sorted `:min`

and `:max`

in `Interval`

. Otherwise I’d need to to all kinds of checks (as I will with `:interval-multiply`

, shortly).

(def interval-add (build-instruction interval-add "`:interval-add` pops the top two `:interval` items and pushes a new `:interval` which is the sum of the two. If either `:min` (or `:max`) is open, the result `:min` (or `:max`) is also open." :tags #{:interval} (consume-top-of :interval :as :i2) (consume-top-of :interval :as :i1) (calculate [:i1 :i2] #(interval/make-interval (+' (:min %1) (:min %2)) (+' (:max %1) (:max %2)) :min-open? (or (:min-open? %1) (:min-open? %2)) :max-open? (or (:max-open? %1) (:max-open? %2))) :as :result) (push-onto :interval :result)))

I write some tests, and realize an interesting thing about interval arithmetic: it’s not immediately obvious or intuitive what `Interval`

I should add to \([2,3]\) to “zero it out”. The “negative” interval, which I innocently wrote as \([-2,-3]\) in my test, is *actually* \([-3,-2]\) (because the constructor’s arguments are sorted in creating the interval proper). I don’t think there’s *any single* interval I can *add* to \([2,3]\) to “zero it out”. I can *subtract* an identical interval to get \([0,0]\), but apparently I can’t *add* one. Which strikes me as freaky somehow, and an interesting peek into some Group Theory stuff I didn’t know was lurking here.

Here are my tests for `:interval-add`

(tabular (fact ":interval-add returns the sum of two intervals" (register-type-and-check-instruction ?set-stack ?items interval-type ?instruction ?get-stack) => ?expected) ?set-stack ?items ?instruction ?get-stack ?expected :interval (list (s/make-interval 2 3) (s/make-interval 2 3)) :interval-add :interval (list (s/make-interval 4 6)) ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; :interval (list (s/make-interval 2 3) (s/make-interval -3 -1)) :interval-add :interval (list (s/make-interval -1 2)) ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; :interval (list (s/make-open-interval 2 3) (s/make-interval 2 3)) :interval-add :interval (list (s/make-open-interval 4 6)) ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; :interval (list (s/make-open-interval 2 3) (s/make-interval -3 -2)) :interval-add :interval (list (s/make-open-interval -1 1)) ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; :interval (list (s/make-interval 3 3 :min-open? true) (s/make-interval 2 2 :max-open? true)) :interval-add :interval (list (s/make-open-interval 5 5)) ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; )

## Subtraction

I decide to forge ahead and build subtraction, since (it seems at first glance that) it’s essentially identical to addition, only “backwards”. As soon as I start checking, it turns out that it isn’t though. Instead of addition, in which

\[[a,b]+[c,d]=[a+c,b+d]\]subtraction is

\[[a,b]-[c,d]=[a-d,b-c].\]*Whaaaaaat?*

OK, I can go with that. I’d feel a bit better if, for example, \(A-B=C\) implied that \(C+B=A\), but that is apparently not a thing I get to assume. So it’s not a group or a field or one of those math things I vaguely remember from our over-ambitious 11th-grade pre-calculus exposure to Group Theory *at all* in the sense I think of them. Ah well. I trust Wikipedia enough to copy from them. I suppose this has something to do with… well, something I can’t quite visualize.

Wish I had a picture.

Anyway, once I discover my confusion, I quickly work this out, which is quite similar to `:interval-addition`

:

(def interval-subtract (build-instruction interval-subtract "`:interval-subtract` pops the top two `:interval` items and pushes a new `:interval` which is the difference of the two. If either `:min` (or `:max`) is open, the result `:min` (or `:max`) is also open." :tags #{:interval} (consume-top-of :interval :as :i2) (consume-top-of :interval :as :i1) (calculate [:i1 :i2] #(interval/make-interval (-' (:min %1) (:max %2)) (-' (:max %1) (:min %2)) :min-open? (or (:min-open? %1) (:max-open? %2)) :max-open? (or (:max-open? %1) (:min-open? %2))) :as :result) (push-onto :interval :result)))

As for the openness of bounds, I assume it works more or less like addition, and try to keep things together. I’ve found a few IEEE standards and academic papers on how bounds are handled (and division, which is starting to worry me to be frank), but I literally can’t read them when they use symbols like upside-down-triangle-surrounding-plus and so forth. So I’m punting here.

At least now I have glanced at multiplication enough to understand what to expect.

## Multiplication

Multiplication is relatively simple, at least for determining the values of the bounds. The lower and upper bounds are the `min`

and `max`

, respectively, of {\(ac\), \(ad\), \(bc\), \(bd\)}, for two intervals \([a,b]\) and \([c,d]\).

The first part, the bounds calculation itself, is relatively straightforward:

(def interval-multiply (build-instruction interval-multiply "`:interval-multiply` pops the top two `:interval` items and pushes a new `:interval` which is the product of the two. If either `:min` (or `:max`) is open, the result `:min` (or `:max`) is also open." :tags #{:interval} (consume-top-of :interval :as :i2) (consume-top-of :interval :as :i1) (calculate [:i1 :i2] #(let [a (:min %1) b (:max %1) c (:min %2) d (:max %2)] interval/make-interval (min (*' a c) (*' a d) (*' b c) (*' b d)) (max (*' a c) (*' a d) (*' b c) (*' b d)) ;; :min-open? ??? ;; :max-open? ??? ) :as :result) (push-onto :interval :result)))

but as you can see, I really don’t know what to set as `:min-open?`

and `:max-open?`

in the result.

This starts to feel like *yet another* place where the association between a numerical bounds value and whether it’s open or not is important. Basically I’d like the result’s `:min-open?`

to be true if either of the bounds used to calculate it were open. Which means I need to know which of the four options was chosen….

I decide to associate the value and its openness up front, and see how messy the calculations get. Clojure seems to like me to fiddle complex structures, so let’s see what Clojure offers me as a mechanism for this task.

Later…

All I can say at this point is that I seem to have it *working*, based on my tests. But *sheesh*.

(defn product-of-bounds-from-pair "helper function for interval-multiply, which takes two [number, open?] tuples and returns the product of the number values" [t1 t2] (*' (first t1) (first t2))) (defn disjunction-of-bounds-from-pair "helper function for interval-multiply, which takes two [number, open?] tuples and returns the OR of the openness values" [t1 t2] (or (second t1) (second t2))) (def interval-multiply (build-instruction interval-multiply "`:interval-multiply` pops the top two `:interval` items and pushes a new `:interval` which is the product of the two. If either `:min` (or `:max`) is open, the result `:min` (or `:max`) is also open." :tags #{:interval} (consume-top-of :interval :as :i2) (consume-top-of :interval :as :i1) (calculate [:i1 :i2] #(let [a [(:min %1) (:min-open? %1)] b [(:max %1) (:max-open? %1)] c [(:min %2) (:min-open? %2)] d [(:max %2) (:max-open? %2)] pairs [[a c] [a d] [b c] [b d]] min-choice (apply min-key (fn [x] (apply product-of-bounds-from-pair x)) pairs) max-choice (apply max-key (fn [x] (apply product-of-bounds-from-pair x)) pairs)] (interval/make-interval (apply product-of-bounds-from-pair min-choice) (apply product-of-bounds-from-pair max-choice) :min-open? (apply disjunction-of-bounds-from-pair min-choice) :max-open? (apply disjunction-of-bounds-from-pair max-choice)) ) :as :result) (push-onto :interval :result) ))

So what I’m doing here is once again building a temporary association tuple with the value of a bound (`:min`

or `:max`

) and its openness (`:min-open?`

or `:max-open?`

). Then I create an explicit collection holding the four pairs of comparisons between *those tuples*; I could have possibly used some `combinatoric`

library stuff to get the powerset here, but I already know this will never be larger than four elements, so easier and tidier to make it explicit.

Then I invoke an extracted “helper function” I’ve called `product-of-bounds-from-pair`

, which reaches back *into* those two tuples being compared and calculates the product of their numerical values. The new `min-choice`

is thus the *pair of tuples* of the lowest-valued product, and the new `max-choice`

is the pair of tuples with the highest-valued product.

Finally, in constructing the resulting `Interval`

, I use that same `product-of-bounds-from-pair`

function to set `:min`

and `:max`

, and then invoke another “helper” `disjunction-of-bounds-from-pair`

to `or`

the openness values.

I hates it. But it works.

I spend some time trying to refactor it. But as before, I can’t really see a place to put a tool (as it were): no clean seams along which I could break off and extract a function, nothing repeated very often. If nothing else, there may be a problem with the verbosity of the PushDSL I’m responding too. But the function itself is essentially a relatively long calculation of the base numbers, and a lot of that is creating and juggling those `[number, open?]`

tuples.

I’d like to get done. Maybe division, with its particular oddities, will spark an insight that leads to a general simplification? We’ll see shortly.

## Reciprocals and Interval Division

At least based on the Wikipedia entry, the mathematical definition is broken into two steps. For \([a,b]÷[c,d]\), when \(0 \notin [c,d]\) the result is \([a,b] \times [c,d]^{-1}\), and \([c,d]^{-1} = [d^{-1},c^{-1}]\). For \([a,b]÷[c,d]\) when \(0 \in [c,d]\), we have a problem of diviing by zero, so we make a couple of adjustments. We define division by 0 as resulting in positive or negative infinity (depending on the sign of the dividend), and we *split* the interval \([c,d]\) into two intervals, \([c,0)\) and \([0,d]\).

An example might be good around now.

\[[2,3] \div [-2,3] \\ [2,3] \div [-2,0) \cup [2,3] \div [0,3] \\ [2,3] \times [-2,0)^{-1} \cup [2,3] \times [0,3]^{-1} \\ [2,3] \times (-\infty, -1/2] \cup [2,3] \times [1/3,\infty] \\ \ldots\]And so on.

So I see a few ways to approach this.

First I realize it wouldn’t be a bad thing to have an `:interval-reciprocal`

function on hand. Second—and more conveniently for me—I am reminded that in “idiomatic Push” it might be better to let the intermediate *product* of the dividend and the reciprocal be calculated by the actual application of `:interval-multiply`

. In other words, I am thinking that `:interval-divide`

will produce a *continuation form* that invokes `:interval-multiply`

and `:interval-reciprocal`

, and let those instructions do the subsequent work.

I won’t bore you with the wrestling and mistakes (and there were a few), but here’s the function I finally wrote for `interval-reciprocal`

in `push.type.definitions.interval`

:

(defn interval-reciprocal "Takes one Interval record, and returns its reciprocal. If the argument contains 0, then two intervals are returned in a list" [i] (let [s (:min i) e (:max i) so (:min-open? i) eo (:max-open? i) infty Double/POSITIVE_INFINITY ninfty Double/NEGATIVE_INFINITY] (cond (and (zero? s) (zero? e)) (make-interval ninfty infty) (zero? (:min i)) (make-interval (/ 1 (:max i)) infty :min-open? (:max-open? i)) (zero? (:max i)) (make-interval ninfty (/ 1 (:min i)) :max-open? (:min-open? i)) (interval-include? i 0) (list (interval-reciprocal (make-interval s 0 :min-open? so)) (interval-reciprocal (make-interval 0 e :max-open? eo))) :else (make-interval (/ 1 e) (/ 1 s) :min-open? eo :max-open? so) )))

I realized there is a “hidden” behavior tucked into my glib reading of the Wikipedia example, which is what happens when an interval *ends* in 0. Technically, “ending in zero” is “containing zero”, but really I am enforcing a more stringent criterion: that when the interval includes 0 but not as an end, then I should split it. Testing revealed another “edge case”, which is the interval \([0,0]\), and also made me wonder whether I should bother preserving the “openness” of an infinite bound. As a result, all bounds that are infinite are closed.

The nice thing, to me, was the realization that when splitting an interval I could re-process the components recursively. I always get a little thrill when I find a recursive solution like that. Your mileage may vary.

OK, so having some confidence (since I tested extensively in the process of writing it) of my `interval-reciprocal`

function, I will now implement the Push instruction, and then I think I have all the pieces for the Push `:interval-divide`

instruction as well.

Here’s the Push instruction I design:

(def interval-reciprocal (build-instruction interval-reciprocal "`:interval-reciprocal` pops the top `:scalar` item and pushes its reciprocal to `:exec`. If the span strictly covers zero, then a code block containing _two_ spans is pushed." :tags #{:interval} (consume-top-of :interval :as :i) (calculate [:i] #(interval/interval-reciprocal %1) :as :results) (push-onto :exec :results) ))

I’ve shunted most of the work to the definition of `interval-reciprocal`

, and it’s tempting to do the same with the `:interval-multiply`

instruction that bugged me earlier. I may still do that; don’t know.

One design decision I’ve made here is a common Push idiom that’s developed in the course of the project: When there’s any ambiguity in the return values of an instruction—for instance when the number of items or the type of the result might be contingent on the arguments—I prefer to return a *code block* containing all the arguments to the `:exec`

stack and let the interpreter’s router push those results to their correct homes. I have a sense (because of another feature coming soon) that this may become more of a rule than an occasional quirk, but for now I’m happy enough to notice it.

I think I have everything in place now for a version of the `:interval-divide`

instruction. Let’s see….

Here’s what the instruction definition ends up looking like:

(def interval-divide (build-instruction interval-divide "`:interval-divide` pops the top two `:interval` items (call them `B` and `A`, respectively) and pushes a continuation that will calculate their quotient(s) `A÷B` onto `:exec`. If `B` strictly covers zero, then two continuations are pushed: one for the positive and one for the negative regions." :tags #{:interval} (consume-top-of :interval :as :divisor) (consume-top-of :interval :as :dividend) (calculate [:divisor] #(interval/interval-reciprocal %1) :as :inverses) (calculate [:dividend :inverses] #(if (seq? %2) (list %1 (first %2) :interval-multiply %1 (second %2) :interval-multiply) (list %1 %2 :interval-multiply)) :as :results) (push-onto :exec :results) ))

That is, if the result of `interval-reciprocal`

are a collection, produce a long continuation that includes both partial calculations in turn; otherwise just one.

There’s a bit of a mathematical glitch I sense here, which is that the reciprocal of a zero-spanning `Interval`

will always produce *two* `Interval`

items. But I don’t really want to go through the trouble for now of creating some kind of multi-interval arithmetic, which retains the result as the *union* of two continuous regions. Besides, we’re *dividing by zero*—I should be happy there is any result at all, and that it makes some sense.

That said, there’s another thing that catches my attention, and that may be more salient when I start stress-testing these new instructions: the appearance of \(\infty\) values in the numeric values of Push items. If \(\infty\) is to be a valid `:scalar`

value, there will almost certainly be consequences somewhere down the line in genetic programming land….

But consequences are something evolutionary search is intended to work around. So let’s just remember this and move along.

Here’s the test that really exercises this “continuation form” approach:

(tabular (fact ":interval-divide works for zero-spanning intervals" (register-type-and-check-instruction ?set-stack ?items interval-type ?instruction ?get-stack) => ?expected) ?set-stack ?items ?instruction ?get-stack ?expected :interval (list (s/make-interval -2 3) (s/make-interval 2 3)) :interval-divide :exec (list (list (s/make-interval 2 3) (s/make-interval Double/NEGATIVE_INFINITY -1/2) :interval-multiply (s/make-interval 2 3) (s/make-interval 1/3 Double/POSITIVE_INFINITY) :interval-multiply)) ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; )

And that passes. It manages to break the zero-spanning interval across the origin, and results in a sufficient continuation that after a few more steps will produce two `Interval`

items that represent the two parts of the correct answer.

I think I’m done with arithmetic. I am still tempted to move some of the logic written explicitly into the `:interval-multiply`

instruction up to an `interval-multiply`

function in `push.type.definitions.interval`

, but I think I can save that for another day.

Looking over my list from several days ago, the remaining work is making sure the Push `:interval`

type is *connected* sufficiently, through conversion and manipulation instructions, to the basic types that comprise it. I can see a few of those already, and they should be (compared to the core arithmetic) relatively simple. Here’s what I think I can and should finish this morning:

`:interval-recenter`

move the center of the interval to zero`:interval-min`

push the`:min`

to`:scalar`

`:interval-max`

push the`:max`

to`:scalar`

`:interval-scale`

multiply`:min`

and`:max`

by a`:scalar`

`:interval-shift`

add a`:scalar`

to`:min`

and`:max`

`:interval-negate`

multiply`:min`

and`:max`

by -1

There are a few other pieces of functionality that I think should wait a few days. For instance, one of the reasons for having these numerical interval objects at all is to emulate Clojure’s sensible idiom of using a `set`

as a *filter* for a collection. Eventually I can see using something like \([2,3]\) as an argument in a suite of functional collection-munging instructions, something like `:scalars-retain`

, which would keep only the items in a `:scalars`

item that fall within a given `:interval`

; or `:tagspace-remove`

, which removes all entries from a given `:tagspace`

with keys falling within a given `:interval`

, and so forth.

But those are not for today.

## Wiring it up

Before I write those “simple” instructions I’ve just listed, I realize I should register the `:interval`

type I’ve been working on, and check that a Push interpreter can integrate these new instructions into the ecosystem of existing types and instructions.

That process is not yet very polished, and as I move towards a first “finished” release of the Klapaucius interpreter as semantic version `1.0.0`

I will want to improve that functionality. At the moment it boils down to three steps:

- add the new type to
`push.interpreter.templates.one-with-everything`

- fix a few badly-written tests that will fail because they check (explicitly) for the list of registered types, which I know is a bad thing but which didn’t I just say I was hoping to improve? Like
*literally*in the preceding paragraph? - run a few thousand
*stress tests*

As with the embarrassing tests I still need to clean up (which explicitly ask what the known types for a new `Interpreter`

instance are, and which of course fail as soon as you add a new type), the *stress test* I’ve built is rather primitive as of this writing. Think of it as an acceptance test that basically reads something like “There should be no exceptions at all when I construct 10000 random Push programs, with 20 random inputs each, and run them all 3000 steps each.”

The business of concocting “random programs” is necessarily slapdash in this library, since that responsibility really should reside in the search system one develops: there’s no reason for an interpreter made to *run* programs to know anything about *writing* programs. So in this case what I’ve done is simply bashed together the simplest possible “random program” maker. For most (maybe all?) of the defined types, it has a little function that can make a “random one”. A “random `:scalar`

” is some number in a given range, a “random `:boolean`

” is `true`

or `false`

with equal chance, a “random `:instruction`

” is any of the registered instruction names for a new `Interpreter`

, chosen uniformly, and so on.

Because I want to make relatively sure there are `Interval`

items being made and exercised, and especially because those `Infinity`

values floating around are starting to worry me, I add a little “random `:interval`

” function to my stress-testing harness before I trust the results:

(defn random-interval [] (interval/make-interval (random-float) (random-rational) :min-open? (random-boolean) :max-open? (random-boolean)))

I’m not showing the context because I hate it and I want to clean it all up before sharing more of it, but I think you can infer what’s happening here. I’m just slapping together some numbers—`random-float`

returns a float from 0 to 100000, and `random-rational`

is the ratio of two integers somewhere in `[1,200]`

, and setting the bounds open with uniform coin flips of `random-boolean`

. Literally no idea what the results will be, except they will be valid `Interval`

items because that’s how I defined them!

When I run this, my computer gets Very Hot (I am partly embarrassed by the code because I never even bothered to make this a parallel algorithm), but all of the 10000 random programs—which include both `Interval`

literals *and* all my new `:interval`

instructions—run to completion. Which is almost disturbing, so I do some poking around to check, but yes it seems things are working well. I think the recent change in the way numbers are handled (leading to the `:scalar`

unified type in Push, which contains all of Clojure’s `integer`

, `double`

, `float`

, `long`

, `rational`

, `biginteger`

and `bigdecimal`

in one huge pile) shook out a lot of the arithmetic errors I was expecting. I hope so fervently, at least.

So that actually makes `:interval`

an official Push type. Before I merge this branch with `master`

I’d like to add those “few extra” instructions. Then I believe we’re good!

## Leftovers and connections

I feel I’m on a roll, so I’ll just report what happens for each instruction on my list in turn

`:interval-recenter`

The tricky thing here is the possibility that an `Interval`

has one or both bounds infinite. I decide that if *either* bound is infinite, “centering” an infinite span should result in the span \([-\infty, \infty]\). Makes sense to me, at least.

In working through this, I realize I want a new predicate function, and it seems useful and general enough to be placed in `push.util.numerics`

for use elsewhere:

(defn infinite? [number] (or (= number Double/NEGATIVE_INFINITY) (= number Double/POSITIVE_INFINITY)))

Then the instruction itself (after this utility file has been added to the namespace) becomes

(def interval-recenter (build-instruction interval-recenter "`:interval-recenter` pops the top `:interval` item and pushes a new `:interval` with center at 0. If either bound of the argument is infinite, the result will be infinite in both directions." :tags #{:interval} (consume-top-of :interval :as :i) (calculate [:i] #(if (or (infinite? (:min %1)) (infinite? (:max %1))) (interval/make-interval Double/NEGATIVE_INFINITY Double/POSITIVE_INFINITY) (let [c (/ (-' (:max %1) (:min %1)) 2)] (interval/make-interval (- c) c :min-open? (:min-open? %1) :max-open? (:max-open? %1)))) :as :result) (push-onto :interval :result)))

`:interval-min`

These two are simple enough *getters* (if we were in Object Oriented territory). Here they are, with no fuss:

(def interval-min (build-instruction interval-min "`:interval-min` pops the top `:interval` item and pushes its `:min` value to `:scalar`." :tags #{:interval} (consume-top-of :interval :as :i) (calculate [:i] #(:min %1) :as :result) (push-onto :scalar :result))) (def interval-max (build-instruction interval-max "`:interval-max` pops the top `:interval` item and pushes its `:max` value to `:scalar`." :tags #{:interval} (consume-top-of :interval :as :i) (calculate [:i] #(:max %1) :as :result) (push-onto :scalar :result)))

`:interval-scale`

Without further ado:

(def interval-scale (build-instruction interval-scale "`:interval-scale` pops the top `:interval` item and top `:scalar` item, and pushes a new `:interval` with the original `:max` and `:min` multiplied by the `:scalar`." :tags #{:interval} (consume-top-of :interval :as :i) (consume-top-of :scalar :as :factor) (calculate [:i :factor] #( interval/make-interval (*' %2 (:min %1)) (*' %2 (:max %1)) :min-open? (:min-open? %1) :max-open? (:max-open? %1)) :as :result) (push-onto :interval :result) ))

`:interval-shift`

And:

(def interval-shift (build-instruction interval-shift "`:interval-shift` pops the top `:interval` item and top `:scalar` item, and pushes a new `:interval` with the original `:max` and `:min` added to the `:scalar`." :tags #{:interval} (consume-top-of :interval :as :i) (consume-top-of :scalar :as :factor) (calculate [:i :factor] #( interval/make-interval (+' %2 (:min %1)) (+' %2 (:max %1)) :min-open? (:min-open? %1) :max-open? (:max-open? %1)) :as :result) (push-onto :interval :result) ))

`:interval-negate`

I decide to call this one `:interval-reflect`

, since what I’d like it to do is literally flip the `:interval`

across zero. Thus, if the `:min`

of the argument is open, the `:max`

of the result will be, and so forth.

(def interval-reflect (build-instruction interval-reflect "`:interval-reflect` pops the top `:interval` item and pushes a new one with the signs of the `:min` and `:max` reversed, and also the boundedness of the ends." :tags #{:interval} (consume-top-of :interval :as :i) (calculate [:i] #( interval/make-interval (- (:max %1)) (- (:min %1)) :min-open? (:max-open? %1) :max-open? (:min-open? %1)) :as :result) (push-onto :interval :result) ))

## Cleanup

That *seems* to be it. I’ve constructed (finally) an `Interval`

record, added a bunch of functions to that, implemented it as a Push type, and added the requisite instructions to the Push interpreter definition. That’s registered (in the branch I am working in) with the “one-with-everything” interpreter template, and it seems to be passing the “stress” acceptance test.

I go over it all one last time, and notice some things to clean up. The fact that I dropped `interval-reciprocal`

into the “helper” functions, but not `interval-multiply`

bothers me, so I want to shift things over and make the Push instructions simply call the library that handles the type. That seems safer and more elegant, to be honest. Something about separation of responsibility and all, too.

That works simply, and I don’t even bother adding additional tests for the “new” `integer-multiply`

and its helpers. I’m comfortable enough seeing that the instruction, which is the only thing exercising `interval-multiply`

, produces correct results.

I say we ship it. Push now has an `:interval`

type.

## Reflections

I realize I should clean up and formalize the process at “both ends”. It should be easier to construct a new “empty” Push type (possibly with a generator function of some kind?), and it should *definitely* be simpler and easier to add all the types (and modules) to the universal `one-with-everything`

interpreter when I’m done.

When I (the best proxy so far for the proverbial “end user”) want to add a new type to the already-crowded Push ecosystem embodied in the Klapaucius interpreter, there’s a necessary but difficult bit of research that needs to be done. That is, one needs to be able to “look” in some sense at the interconnectedness of the old types and the new ones, as the instruction set transforms them into one another. A good deal of this might be solved with a dynamic visualization of the graph of transformations of arguments to results by all the instructions acting on all the types. But at least a little bit is a *reminder* that getters, setters, and the things that take structured types apart are important.

For some time I’ve felt that the types in Push should be defined *structurally* rather than in this sort of *ad hoc* way. For example, I think `:interval`

should be automatically recognized and detected—in some way I can’t quite put together yet—as a record containing two `:scalar`

and two `:boolean`

values, with appropriate labels. The labels are right there inside the Clojure `record`

, and it seems reasonable and appropriate to let Push also see the keys and do some introspection. But the next step, it seems to me, is to define something like an `Interval`

with this (pseudocode macro warning)

(defpushstructure :interval :min :scalar :max :scalar :min-open? :boolean :max-open? :boolean)

and *automatically* get instructions like

`:interval-min`

`:interval-max`

`:interval-min-open?`

`:interval-max-open?`

`:interval-setmin`

`:interval-setmax`

`:interval-setmin-open?`

`:interval-setmax-open?`

`:interval-new`

`:interval-parts`

- … and so on

I don’t think I should expect everybody two write those on their own, especially for more complex Clojure `record`

items I have planned, like `:graph`

or `:time-series`

.

But that is definitely for another day.

Finally, there are a few philosophical concerns I should check, involving the notion of `Infinity`

and numbers and how this plays out consistently in the Push language. At the moment, division by zero produces an `:error`

result for a `:scalar`

but a complex assortment of non-`:error`

results for an `:interval`

. But the results from dividing by an `:interval`

that spans zero will include bounds at `Infinity`

.

Specifically I’ve been relying on Clojure’s (and in turn, Java’s) `Double/POSITIVE_INFINITY`

and `Double/NEGATIVE_INFINITY`

constants. These are consistently handled by most of the Clojure functions mathematical functions I’ve checked so far; `(Math/sin ∞)`

is `NaN`

(reasonably, because what’s the phase at `∞`

?), `(/ 1 ∞)`

produces the `java.lang/Double`

value `0.0`

, and `(-' 7812318273M -∞)`

produces `∞`

… also reasonable.

What isn’t so clear is whether this will hold up over time. There will shortly be higher-order functions floating around, and instead of simply worrying about `:scalar`

and `:scalars`

, `:complex`

and `:complexes`

, `:interval`

and `:intervals`

, there will be a sort of combinatorial… well, not “explosion”, but “rapid low-temperature expansion” when those arise. Lots of stuff will be able to interact with lots of other stuff.

This makes me wonder whether I should make my own `Infinity`

, and what that might be, and how it would propagate. I think at the very least I should let Push pay attention to the Java/Clojure infinities when they crop up. The deeper question, though, is whether the behavior of `:scalar-divide`

and `:integer-divide`

are mathematically consistent now. I don’t know.

I commit and merge the changes, and I open some issues in the project repository on GitHub. I think we’re good to go.