i'm getting the error IllegalArgumentException Don't know how to create ISeq from: java.lang.Long clojure.lang.RT.seqFrom (RT.java:487) when executing the following code:
(defn phrase-length [phr]
(loop [n 0 b () s ()]
(if (= n (count phr))
(concat #(reduce + b) #(reduce + s))
(recur (inc n)
(cons (nth (nth (nth phr n) 1) 0) b)
(cons (nth (nth (nth phr n) 1) 1) s)))))
The error is occurring in the line of the concat. It must be something with trying to reduce while also concatting.
You're trying to concat #(reduce + b) and #(reduce + s). That doesn't work, #(reduce + b) expands to (fn* [] (clojure.core/reduce clojure.core/+ your-namespace/b)). You can't concat functions. Maybe you meant (reduce + b) but that doesn't make any sense either because the result of that is a number, and you can't concat numbers either. Maybe you meant
[(reduce + b) (reduce + s)] or (map + b s) or (+ (reduce + b) (reduce + s)) but I can't do more than blindly guess here without knowing what you're actually trying to achieve.
These lines:
(cons (nth (nth (nth phr n) 1) 0) b)
(cons (nth (nth (nth phr n) 1) 1) s)
are weird too. Is phr a seq of seqs of seqs of longs?
Is your collection of this form [[[0 0 ,,,] [0 1 ,,,] ,,,] ,,,] (you'd cons 0 to b and 1 to s here)? If so, you should probably write functions for accessing those values, as it is it's a chore to find out what's going on.
nth returns a value.
When you do (cons (nth (nth (nth phr n) 1) 0) b), after the evaluation of the (nth phr n) you will apply the next nth in a value, not in a Seq.
Testing your code with something like (phrase-length "123") will raise the error that you are getting.
Related
problem formulation
Informally speaking, I want to write a function which, taking as input a function that generates binary factorizations and an element (usually neutral), creates an arbitrary length factorization generator. To be more specific, let us first define the function nfoldr in Clojure.
(defn nfoldr [f e]
(fn rec [n]
(fn [s]
(if (zero? n)
(if (empty? s) e)
(if (seq s)
(if-some [x ((rec (dec n)) (rest s))]
(f (list (first s) x))))))))
Here nil is used with the meaning "undefined output, input not in function's domain". Additionally, let us view the inverse relation of a function f as a set-valued function defining inv(f)(y) = {x | f(x) = y}.
I want to define a function nunfoldr such that inv(nfoldr(f , e)(n)) = nunfoldr(inv(f) , e)(n) when for every element y inv(f)(y) is finite, for each binary function f, element e and natural number n.
Moreover, I want the factorizations to be generated as lazily as possible, in a 2-dimensional sense of laziness. My goal is that, when getting some part of a factorization for the first time, there does not happen (much) computation needed for next parts or next factorizations. Similarly, when getting one factorization for the first time, there does not happen computation needed for next ones, whereas all the previous ones get in effect fully realized.
In an alternative formulation we can use the following longer version of nfoldr, which is equivalent to the shorter one when e is a neutral element.
(defn nfoldr [f e]
(fn [n]
(fn [s]
(if (zero? n)
(if (empty? s) e)
((fn rec [n]
(fn [s]
(if (= 1 n)
(if (and (seq s) (empty? (rest s))) (first s))
(if (seq s)
(if-some [x ((rec (dec n)) (rest s))]
(f (list (first s) x)))))))
n)))))
a special case
This problem is a generalization of the problem of generating partitions described in that question. Let us see how the old problem can be reduced to the current one. We have for every natural number n:
npt(n) = inv(nconcat(n)) = inv(nfoldr(concat2 , ())(n)) = nunfoldr(inv(concat2) , ())(n) = nunfoldr(pt2 , ())(n)
where:
npt(n) generates n-ary partitions
nconcat(n) computes n-ary concatenation
concat2 computes binary concatenation
pt2 generates binary partitions
So the following definitions give a solution to that problem.
(defn generate [step start]
(fn [x] (take-while some? (iterate step (start x)))))
(defn pt2-step [[x y]]
(if (seq y) (list (concat x (list (first y))) (rest y))))
(def pt2-start (partial list ()))
(def pt2 (generate pt2-step pt2-start))
(def npt (nunfoldr pt2 ()))
I will summarize my story of solving this problem, using the old one to create example runs, and conclude with some observations and proposals for extension.
solution 0
At first, I refined/generalized the approach I took for solving the old problem. Here I write my own versions of concat and map mainly for a better presentation and, in the case of concat, for some added laziness. Of course we can use Clojure's versions or mapcat instead.
(defn fproduct [f]
(fn [s]
(lazy-seq
(if (and (seq f) (seq s))
(cons
((first f) (first s))
((fproduct (rest f)) (rest s)))))))
(defn concat' [s]
(lazy-seq
(if (seq s)
(if-let [x (seq (first s))]
(cons (first x) (concat' (cons (rest x) (rest s))))
(concat' (rest s))))))
(defn map' [f]
(fn rec [s]
(lazy-seq
(if (seq s)
(cons (f (first s)) (rec (rest s)))))))
(defn nunfoldr [f e]
(fn rec [n]
(fn [x]
(if (zero? n)
(if (= e x) (list ()) ())
((comp
concat'
(map' (comp
(partial apply map)
(fproduct (list
(partial partial cons)
(rec (dec n))))))
f)
x)))))
In an attempt to get inner laziness we could replace (partial partial cons) with something like (comp (partial partial concat) list). Although this way we get inner LazySeqs, we do not gain any effective laziness because, before consing, most of the computation required for fully realizing the rest part takes place, something that seems unavoidable within this general approach. Based on the longer version of nfoldr, we can also define the following faster version.
(defn nunfoldr [f e]
(fn [n]
(fn [x]
(if (zero? n)
(if (= e x) (list ()) ())
(((fn rec [n]
(fn [x] (println \< x \>)
(if (= 1 n)
(list (list x))
((comp
concat'
(map' (comp
(partial apply map)
(fproduct (list
(partial partial cons)
(rec (dec n))))))
f)
x))))
n)
x)))))
Here I added a println call inside the main recursive function to get some visualization of eagerness. So let us demonstrate the outer laziness and inner eagerness.
user=> (first ((npt 5) (range 3)))
< (0 1 2) >
< (0 1 2) >
< (0 1 2) >
< (0 1 2) >
< (0 1 2) >
(() () () () (0 1 2))
user=> (ffirst ((npt 5) (range 3)))
< (0 1 2) >
< (0 1 2) >
< (0 1 2) >
< (0 1 2) >
< (0 1 2) >
()
solution 1
Then I thought of a more promising approach, using the function:
(defn transpose [s]
(lazy-seq
(if (every? seq s)
(cons
(map first s)
(transpose (map rest s))))))
To get the new solution we replace the previous argument in the map' call with:
(comp
(partial map (partial apply cons))
transpose
(fproduct (list
repeat
(rec (dec n)))))
Trying to get inner laziness we could replace (partial apply cons) with #(cons (first %) (lazy-seq (second %))) but this is not enough. The problem lies in the (every? seq s) test inside transpose, where checking a lazy sequence of factorizations for emptiness (as a stopping condition) results in realizing it.
solution 2
A first way to tackle the previous problem that came to my mind was to use some additional knowledge about the number of n-ary factorizations of an element. This way we can repeat a certain number of times and use only this sequence for the stopping condition of transpose. So we will replace the test inside transpose with (seq (first s)), add an input count to nunfoldr and replace the argument in the map' call with:
(comp
(partial map #(cons (first %) (lazy-seq (second %))))
transpose
(fproduct (list
(partial apply repeat)
(rec (dec n))))
(fn [[x y]] (list (list ((count (dec n)) y) x) y)))
Let us turn to the problem of partitions and define:
(defn npt-count [n]
(comp
(partial apply *)
#(map % (range 1 n))
(partial comp inc)
(partial partial /)
count))
(def npt (nunfoldr pt2 () npt-count))
Now we can demonstrate outer and inner laziness.
user=> (first ((npt 5) (range 3)))
< (0 1 2) >
(< (0 1 2) >
() < (0 1 2) >
() < (0 1 2) >
() < (0 1 2) >
() (0 1 2))
user=> (ffirst ((npt 5) (range 3)))
< (0 1 2) >
()
However, the dependence on additional knowledge and the extra computational cost make this solution unacceptable.
solution 3
Finally, I thought that in some crucial places I should use a kind of lazy sequences "with a non-lazy end", in order to be able to check for emptiness without realizing. An empty such sequence is just a non-lazy empty list and overall they behave somewhat like the lazy-conss of the early days of Clojure. Using the definitions given below we can reach an acceptable solution, which works under the assumption that always at least one of the concat'ed sequences (when there is one) is non-empty, something that holds in particular when every element has at least one binary factorization and we are using the longer version of nunfoldr.
(def lazy? (partial instance? clojure.lang.IPending))
(defn empty-eager? [x] (and (not (lazy? x)) (empty? x)))
(defn transpose [s]
(lazy-seq
(if-not (some empty-eager? s)
(cons
(map first s)
(transpose (map rest s))))))
(defn concat' [s]
(if-not (empty-eager? s)
(lazy-seq
(if-let [x (seq (first s))]
(cons (first x) (concat' (cons (rest x) (rest s))))
(concat' (rest s))))
()))
(defn map' [f]
(fn rec [s]
(if-not (empty-eager? s)
(lazy-seq (cons (f (first s)) (rec (rest s))))
())))
Note that in this approach the input function f should produce lazy sequences of the new kind and the resulting n-ary factorizer will also produce such sequences. To take care of the new input requirement, for the problem of partitions we define:
(defn pt2 [s]
(lazy-seq
(let [start (list () s)]
(cons
start
((fn rec [[x y]]
(if (seq y)
(lazy-seq
(let [step (list (concat x (list (first y))) (rest y))]
(cons step (rec step))))
()))
start)))))
Once again, let us demonstrate outer and inner laziness.
user=> (first ((npt 5) (range 3)))
< (0 1 2) >
< (0 1 2) >
(< (0 1 2) >
() < (0 1 2) >
() < (0 1 2) >
() () (0 1 2))
user=> (ffirst ((npt 5) (range 3)))
< (0 1 2) >
< (0 1 2) >
()
To make the input and output use standard lazy sequences (sacrificing a bit of laziness), we can add:
(defn lazy-end->eager-end [s]
(if (seq s)
(lazy-seq (cons (first s) (lazy-end->eager-end (rest s))))
()))
(defn eager-end->lazy-end [s]
(lazy-seq
(if-not (empty-eager? s)
(cons (first s) (eager-end->lazy-end (rest s))))))
(def nunfoldr
(comp
(partial comp (partial comp eager-end->lazy-end))
(partial apply nunfoldr)
(fproduct (list
(partial comp lazy-end->eager-end)
identity))
list))
observations and extensions
While creating solution 3, I observed that the old mechanism for lazy sequences in Clojure might not be necessarily inferior to the current one. With the transition, we gained the ability to create lazy sequences without any substantial computation taking place but lost the ability to check for emptiness without doing the computation needed to get one more element. Because both of these abilities can be important in some cases, it would be nice if a new mechanism was introduced, which would combine the advantages of the previous ones. Such a mechanism could use again an outer LazySeq thunk, which when forced would return an empty list or a Cons or another LazySeq or a new LazyCons thunk. This new thunk when forced would return a Cons or perhaps another LazyCons. Now empty? would force only LazySeq thunks while first and rest would also force LazyCons. In this setting map could look like this:
(defn map [f s]
(lazy-seq
(if (empty? s) ()
(lazy-cons
(cons (f (first s)) (map f (rest s)))))))
I have also noticed that the approach taken from solution 1 onwards lends itself to further generalization. If inside the argument in the map' call in the longer nunfoldr we replace cons with concat, transpose with some implementation of Cartesian product and repeat with another recursive call, we can then create versions that "split at different places". For example, using the following as the argument we can define a nunfoldm function that "splits in the middle" and corresponds to an easy-to-imagine nfoldm. Note that all "splitting strategies" are equivalent when f is associative.
(comp
(partial map (partial apply concat))
cproduct
(fproduct (let [n-half (quot n 2)]
(list (rec n-half) (rec (- n n-half))))))
Another natural modification would allow for infinite factorizations. To achieve this, if f generated infinite factorizations, nunfoldr(f , e)(n) should generate the factorizations in an order of type ω, so that each one of them could be produced in finite time.
Other possible extensions include dropping the n parameter, creating relational folds (in correspondence with the relational unfolds we consider here) and generically handling algebraic data structures other than sequences as input/output. This book, which I have just discovered, seems to contain valuable relevant information, given in a categorical/relational language.
Finally, to be able to do this kind of programming more conveniently, we could transfer it into a point-free, algebraic setting. This would require constructing considerable "extra machinery", in fact almost making a new language. This paper demonstrates such a language.
Still very new to Clojure and programming in general so forgive the stupid question.
The problem is:
Find n and k such that the sum of numbers up to n (exclusive) is equal to the sum of numbers from n+1 to k (inclusive).
My solution (which works fine) is to define the following functions:
(defn addd [x] (/ (* x (+ x 1)) 2))
(defn sum-to-n [n] (addd(- n 1)))
(defn sum-to-k [n=1 k=4] (- (addd k) (addd n)))
(defn is-right[n k]
(= (addd (- n 1)) (sum-to-k n k)))
And then run the following loop:
(loop [n 1 k 2]
(cond
(is-right n k) [n k]
(> (sum-to-k n k) (sum-to-n n) )(recur (inc n) k)
:else (recur n (inc k))))
This only returns one answer but if I manually set n and k I can get different values. However, I would like to define a function which returns a lazy sequence of all values so that:
(= [6 8] (take 1 make-seq))
How do I do this as efficiently as possible? I have tried various things but haven't had much luck.
Thanks
:Edit:
I think I came up with a better way of doing it, but its returning 'let should be a vector'. Clojure docs aren't much help...
Heres the new code:
(defn calc-n [n k]
(inc (+ (* 2 k) (* 3 n))))
(defn calc-k [n k]
(inc (+ (* 3 k)(* 4 n))))
(defn f
(let [n 4 k 6]
(recur (calc-n n k) (calc-k n k))))
(take 4 (f))
Yes, you can create a lazy-seq, so that the next iteration will take result of the previous iteration. Here is my suggestion:
(defn cal [n k]
(loop [n n k k]
(cond
(is-right n k) [n k]
(> (sum-to-k n k) (sum-to-n n) )(recur (inc n) k)
:else (recur n (inc k)))))
(defn make-seq [n k]
(if-let [[n1 k1] (cal n k)]
(cons [n1 k1]
(lazy-seq (make-seq (inc n1) (inc k1))))))
(take 5 (make-seq 1 2))
;;=> ([6 8] [35 49] [204 288] [1189 1681] [6930 9800])
just generating lazy seq of candidatess with iterate and then filtering them should probably be what you need:
(def pairs
(->> [1 2]
(iterate (fn [[n k]]
(if (< (sum-to-n n) (sum-n-to-k n k))
[(inc n) k]
[n (inc k)])))
(filter (partial apply is-right))))
user> (take 5 pairs)
;;=> ([6 8] [35 49] [204 288] [1189 1681] [6930 9800])
semantically it is just like manually generating a lazy-seq, and should be as efficient, but this one is probably more idiomatic
If you don't feel like "rolling your own", here is an alternate solution. I also cleaned up the algorithm a bit through renaming/reformating.
The main difference is that you treat your loop-recur as an infinite loop inside of the t/lazy-gen form. When you find a value you want to keep, you use the t/yield expression to create a lazy-sequence of outputs. This structure is the Clojure version of a generator function, just like in Python.
(ns tst.demo.core
(:use tupelo.test )
(:require [tupelo.core :as t] ))
(defn integrate-to [x]
(/ (* x (+ x 1)) 2))
(defn sum-to-n [n]
(integrate-to (- n 1)))
(defn sum-n-to-k [n k]
(- (integrate-to k) (integrate-to n)))
(defn sums-match[n k]
(= (sum-to-n n) (sum-n-to-k n k)))
(defn recur-gen []
(t/lazy-gen
(loop [n 1 k 2]
(when (sums-match n k)
(t/yield [n k]))
(if (< (sum-to-n n) (sum-n-to-k n k))
(recur (inc n) k)
(recur n (inc k))))))
with results:
-------------------------------
Clojure 1.10.1 Java 13
-------------------------------
(take 5 (recur-gen)) => ([6 8] [35 49] [204 288] [1189 1681] [6930 9800])
You can find all of the details in the Tupelo Library.
This first function probably has a better name from math, but I don't know math very well. I'd use inc (increment) instead of (+ ,,, 1), but that's just personal preference.
(defn addd [x]
(/ (* x (inc x)) 2))
I'll slightly clean up the spacing here and use the dec (decrement) function.
(defn sum-to-n [n]
(addd (dec n)))
(defn sum-n-to-k [n k]
(- (addd k) (addd n)))
In some languages predicates, functions that return booleans,
have names like is-odd or is-whatever. In clojure they're usually
called odd? or whatever?.
The question-mark is not syntax, it's just part of the name.
(defn matching-sums? [n k]
(= (addd (dec n)) (sum-n-to-k n k)))
The loop special form is kind of like an anonymous function
for recur to jump back to. If there's no loop form, recur jumps back
to the enclosing function.
Also, dunno what to call this so I'll just call it f.
(defn f [n k]
(cond
(matching-sums? n k) [n k]
(> (sum-n-to-k n k) (sum-to-n n)) (recur (inc n) k)
:else (recur n (inc k))))
(comment
(f 1 2) ;=> [6 8]
(f 7 9) ;=> [35 49]
)
Now, for your actual question. How to make a lazy sequence. You can use the lazy-seq macro, like in minhtuannguyen's answer, but there's an easier, higher level way. Use the iterate function. iterate takes a function and a value and returns an infinite sequence of the value followed by calling the function with the value, followed by calling the function on that value etc.
(defn make-seq [init]
(iterate (fn [n-and-k]
(let [n (first n-and-k)
k (second n-and-k)]
(f (inc n) (inc k))))
init))
(comment
(take 4 (make-seq [1 2])) ;=> ([1 2] [6 8] [35 49] [204 288])
)
That can be simplified a bit by using destructuring in the argument-vector of the anonymous function.
(defn make-seq [init]
(iterate (fn [[n k]]
(f (inc n) (inc k)))
init))
Edit:
About the repeated calculations in f.
By saving the result of the calculations using a let, you can avoid calculating addd multiple times for each number.
(defn f [n k]
(let [to-n (sum-to-n n)
n-to-k (sum-n-to-k n k)]
(cond
(= to-n n-to-k) [n k]
(> n-to-k to-n) (recur (inc n) k)
:else (recur n (inc k)))))
I want to write the function collect which can combine the sublists into a list, like:
user=> (collect '(a b c d e) 1)
((a)(b)(c)(d)(e))
user=> (collect '(a b c d e) 2)
((a b)(c d)(e))
user=> (collect '(a b c d e) 5)
(a b c d e))
this is my code:
(defn collect [lst num]
(loop [l lst res (atom ())]
(if (<= (count l) num) #res
(recur (drop num l) (swap! res conj (take num (drop num l)))))))
But when I run
user=> (collect '(a b c d e) 1)
I got the error:
ClassCastException clojure.lang.PersistentList cannot be cast to clojure.lang.IAtom clojure.core/swap!
why I cannot get the res when I use "swap!" ? Thank you.
It's blowing up in the second pass through the loop.
swap returns the value that was put into the atom, not the atom it's self. So the first pass is updating the atom, and then passing the value it just put into the atom to the second pass through the loop. in the second pass it's trying to use the value as the atom, and getting the exception above.
To "fix" this use a do to update the atom, then pass the atom to the next pass through the loop once it contains the correct value.
user> (defn collect [lst num]
(loop [l lst res (atom ())]
(if (<= (count l) num) #res
(recur (drop num l)
(do (swap! res conj (take num (drop num l)))
res)))))
#'user/collect
user> (collect '(a b c d e) 2)
((e) (c d))
You can also in this case, just remove the atom completely and get exactly the same result (I fixed on ordering problem from your example by using a [] instead of () in the initial value of res):
user> (defn collect [lst num]
(loop [l lst res []]
(if (<= (count l) num) res
(recur (drop num l)
(conj res (take num (drop num l)))))))
#'user/collect
user> (collect '(a b c d e) 2)
[(c d) (e)]
and of course you can also use partition-all as glts mentions above.
;; this would be a correct way to do it
(defn collect [coll n]
(partition-all n coll))
;; this would be a clumsy way to do it
(defn collect
"using a loop (there is not point to do that but at least you can see the logic working as in your example)"
[coll n]
(lazy-seq
(loop [res []
coll coll]
(if (empty? coll)
res
(recur (conj res (take n coll)) (drop n coll))))))
Regarding your error, on the second loop, res is a list-like value, not an atom anymore. That would lead us to :
(defn collect [coll n]
(lazy-seq (loop [res (atom [])
coll coll]
(if (empty? coll)
#res
(recur (do (swap! res conj (take n coll))
;; return the atom instead of the value'
res)
(drop n coll))))))
Note that in order to preserve the order in the solution, I use a vector (litteral []) instead of a list (litteral '()). This is because of the behaviour of conj described here.
I have completed this problem on hackerrank and my solution passes most test cases but it is not fast enough for 4 out of the 11 test cases.
My solution looks like this:
(ns scratch.core
(require [clojure.string :as str :only (split-lines join split)]))
(defn ascii [char]
(int (.charAt (str char) 0)))
(defn process [text]
(let [parts (split-at (int (Math/floor (/ (count text) 2))) text)
left (first parts)
right (if (> (count (last parts)) (count (first parts)))
(rest (last parts))
(last parts))]
(reduce (fn [acc i]
(let [a (ascii (nth left i))
b (ascii (nth (reverse right) i))]
(if (> a b)
(+ acc (- a b))
(+ acc (- b a))))
) 0 (range (count left)))))
(defn print-result [[x & xs]]
(prn x)
(if (seq xs)
(recur xs)))
(let [input (slurp "/Users/paulcowan/Downloads/input10.txt")
inputs (str/split-lines input)
length (read-string (first inputs))
texts (rest inputs)]
(time (print-result (map process texts))))
Can anyone give me any advice about what I should look at to make this faster?
Would using recursion instead of reduce be faster or maybe this line is expensive:
right (if (> (count (last parts)) (count (first parts)))
(rest (last parts))
(last parts))
Because I am getting a count twice.
You are redundantly calling reverse on every iteration of the reduce:
user=> (let [c [1 2 3]
noisey-reverse #(doto (reverse %) println)]
(reduce (fn [acc e] (conj acc (noisey-reverse c) e))
[]
[:a :b :c]))
(3 2 1)
(3 2 1)
(3 2 1)
[(3 2 1) :a (3 2 1) :b (3 2 1) :c]
The reversed value could be calculated inside the containing let, and would then only need to be calculated once.
Also, due to the way your parts is defined, you are doing linear time lookups with each call to nth. It would be better to put parts in a vector and do indexed lookup. In fact you wouldn't need a reversed parts, and could do arithmetic based on the count of the vector to find the item to look up.
I want to indent the following piece of code.
How would a lisper indent this?
I am especially confused about where to put newlines.
(defn primes [n]
(letfn [(sieve [table removal]
(assoc table removal false))
(primebools [i table]
(cond
(= i n) table
(table i) (recur (inc i)
(reduce sieve
table
(range (* i i) n i)))
:else (recur (inc i)
table)))]
(let [prime? (primebools 2 (apply vector (repeat n true)))]
(filter prime? (range 2 n)))))
(defn primes [n]
(letfn [(sieve [table removal]
(assoc table removal false))
(primebools [i table]
(cond
(= i n) table
(table i) (recur (inc i)
(reduce sieve table
(range (* i i) n i)))
:else (recur (inc i) table)))]
(let [prime? (primebools 2 (apply vector (repeat n true)))]
(filter prime? (range 2 n)))))
Is how I would do it.
In addition to #dnolen's answer, I usually put a new line when there's
a new function (like your first two lines)
to indent long or important argument to a function (like the cond block)
logically keep each line to less than 80 characters and break up long ideas to smaller chunks
most importantly, be consistent!
Then just align and indent lines so that the identations are for the same depth of code.