Simple newbie question in Clojure...
If I have an odd number of elements in a Clojure vector, how can I extract the "middle" value? I've been looking at this for a while and can't work out how to do it!
Some examples:
(middle-value [0]) should return [0]
(middle-value [0 1 2]) should return [1]
(middle-value [0 1 :abc 3 4]) should return [:abc]
(middle-value [0 1 2 "test" 4 5 6]) should return ["test"]
How about calculating the middle index and accessing by it?
(defn middle-value [vect]
(when-not (empty? vect)
(vect (quot (count vect) 2))))
A somewhat inefficient but fun implementation (works with sequence abstraction instead of concrete vector):
(defn middle [[fst & rst]]
(if-not rst fst
(recur (butlast rst))))
Returns nil in case of even amount of elements.
Less fun but more efficient:
(nth v (quot (count v) 2))
where v is the vector.
Get the number of items in the vector, halve it, floor the result and get the item at that index. Assuming a vector v:
(get v (floor (/ (count v) 2)))
Unfortunately floor isn't in clojure.core, you'll need to pull in another library for that or go directly to java.lang.Math.floor.
This code, of course, doesn't do anything about even-counted vectors, but I'm assuming you can handle those already.
Related
A reduce call has its f argument first. Visually speaking, this is often the biggest part of the form.
e.g.
(reduce
(fn [[longest current] x]
(let [tail (last current)
next-seq (if (or (not tail) (> x tail))
(conj current x)
[x])
new-longest (if (> (count next-seq) (count longest))
next-seq
longest)]
[new-longest next-seq]))
[[][]]
col))
The problem is, the val argument (in this case [[][]]) and col argument come afterward, below, and it's a long way for your eyes to travel to match those with the parameters of f.
It would look more readable to me if it were in this order instead:
(reduceb val col
(fn [x y]
...))
Should I implement this macro, or am I approaching this entirely wrong in the first place?
You certainly shouldn't write that macro, since it is easily written as a function instead. I'm not super keen on writing it as a function, either, though; if you really want to pair the reduce with its last two args, you could write:
(-> (fn [x y]
...)
(reduce init coll))
Personally when I need a large function like this, I find that a comma actually serves as a good visual anchor, and makes it easier to tell that two forms are on that last line:
(reduce (fn [x y]
...)
init, coll)
Better still is usually to not write such a large reduce in the first place. Here you're combining at least two steps into one rather large and difficult step, by trying to find all at once the longest decreasing subsequence. Instead, try splitting the collection up into decreasing subsequences, and then take the largest one.
(defn decreasing-subsequences [xs]
(lazy-seq
(cond (empty? xs) []
(not (next xs)) (list xs)
:else (let [[x & [y :as more]] xs
remainder (decreasing-subsequences more)]
(if (> y x)
(cons [x] remainder)
(cons (cons x (first remainder)) (rest remainder)))))))
Then you can replace your reduce with:
(apply max-key count (decreasing-subsequences xs))
Now, the lazy function is not particularly shorter than your reduce, but it is doing one single thing, which means it can be understood more easily; also, it has a name (giving you a hint as to what it's supposed to do), and it can be reused in contexts where you're looking for some other property based on decreasing subsequences, not just the longest. You can even reuse it more often than that, if you replace the > in (> y x) with a function parameter, allowing you to split up into subsequences based on any predicate. Plus, as mentioned it is lazy, so you can use it in situations where a reduce of any sort would be impossible.
Speaking of ease of understanding, as you can see I misunderstood what your function is supposed to do when reading it. I'll leave as an exercise for you the task of converting this to strictly-increasing subsequences, where it looked to me like you were computing decreasing subsequences.
You don't have to use reduce or recursion to get the descending (or ascending) sequences. Here we are returning all the descending sequences in order from longest to shortest:
(def in [3 2 1 0 -1 2 7 6 7 6 5 4 3 2])
(defn descending-sequences [xs]
(->> xs
(partition 2 1)
(map (juxt (fn [[x y]] (> x y)) identity))
(partition-by first)
(filter ffirst)
(map #(let [xs' (mapcat second %)]
(take-nth 2 (cons (first xs') xs'))))
(sort-by (comp - count))))
(descending-sequences in)
;;=> ((7 6 5 4 3 2) (3 2 1 0 -1) (7 6))
(partition 2 1) gives every possible comparison and partition-by allows you to mark out the runs of continuous decreases. At this point you can already see the answer and the rest of the code is removing the baggage that is no longer needed.
If you want the ascending sequences instead then you only need to change the < to a >:
;;=> ((-1 2 7) (6 7))
If, as in the question, you only want the longest sequence then put a first as the last function call in the thread last macro. Alternatively replace the sort-by with:
(apply max-key count)
For maximum readability you can name the operations:
(defn greatest-continuous [op xs]
(let [op-pair? (fn [[x y]] (op x y))
take-every-second #(take-nth 2 (cons (first %) %))
make-canonical #(take-every-second (apply concat %))]
(->> xs
(partition 2 1)
(partition-by op-pair?)
(filter (comp op-pair? first))
(map make-canonical)
(apply max-key count))))
I feel your pain...they can be hard to read.
I see 2 possible improvements. The simplest is to write a wrapper similar to the Plumatic Plumbing defnk style:
(fnk-reduce { :fn (fn [state val] ... <new state value>)
:init []
:coll some-collection } )
so the function call has a single map arg, where each of the 3 pieces is labelled & can come in any order in the map literal.
Another possibility is to just extract the reducing fn and give it a name. This can be either internal or external to the code expression containing the reduce:
(let [glommer (fn [state value] (into state value)) ]
(reduce glommer #{} some-coll))
or possibly
(defn glommer [state value] (into state value))
(reduce glommer #{} some-coll))
As always, anything that increases clarity is preferred. If you haven't noticed already, I'm a big fan of Martin Fowler's idea of Introduce Explaining Variable refactoring. :)
I will apologize in advance for posting a longer solution to something where you wanted more brevity/clarity.
We are in the new age of clojure transducers and it appears a bit that your solution was passing the "longest" and "current" forward for record-keeping. Rather than passing that state forward, a stateful transducer would do the trick.
(def longest-decreasing
(fn [rf]
(let [longest (volatile! [])
current (volatile! [])
tail (volatile! nil)]
(fn
([] (rf))
([result] (transduce identity rf result))
([result x] (do (if (or (nil? #tail) (< x #tail))
(if (> (count (vswap! current conj (vreset! tail x)))
(count #longest))
(vreset! longest #current))
(vreset! current [(vreset! tail x)]))
#longest)))))))
Before you dismiss this approach, realize that it just gives you the right answer and you can do some different things with it:
(def coll [2 1 10 9 8 40])
(transduce longest-decreasing conj coll) ;; => [10 9 8]
(transduce longest-decreasing + coll) ;; => 27
(reductions (longest-decreasing conj) [] coll) ;; => ([] [2] [2 1] [2 1] [2 1] [10 9 8] [10 9 8])
Again, I know that this may appear longer but the potential to compose this with other transducers might be worth the effort (not sure if my airity 1 breaks that??)
I believe that iterate can be a more readable substitute for reduce. For example here is the iteratee function that iterate will use to solve this problem:
(defn step-state-hof [op]
(fn [{:keys [unprocessed current answer]}]
(let [[x y & more] unprocessed]
(let [next-current (if (op x y)
(conj current y)
[y])
next-answer (if (> (count next-current) (count answer))
next-current
answer)]
{:unprocessed (cons y more)
:current next-current
:answer next-answer}))))
current is built up until it becomes longer than answer, in which case a new answer is created. Whenever the condition op is not satisfied we start again building up a new current.
iterate itself returns an infinite sequence, so needs to be stopped when the iteratee has been called the right number of times:
(def in [3 2 1 0 -1 2 7 6 7 6 5 4 3 2])
(->> (iterate (step-state-hof >) {:unprocessed (rest in)
:current (vec (take 1 in))})
(drop (- (count in) 2))
first
:answer)
;;=> [7 6 5 4 3 2]
Often you would use a drop-while or take-while to short circuit just when the answer has been obtained. We could so that here however there is no short circuiting required as we know in advance that the inner function of step-state-hof needs to be called (- (count in) 1) times. That is one less than the count because it is processing two elements at a time. Note that first is forcing the final call.
I wanted this order for the form:
reduce
val, col
f
I was able to figure out that this technically satisfies my requirements:
> (apply reduce
(->>
[0 [1 2 3 4]]
(cons
(fn [acc x]
(+ acc x)))))
10
But it's not the easiest thing to read.
This looks much simpler:
> (defn reduce< [val col f]
(reduce f val col))
nil
> (reduce< 0 [1 2 3 4]
(fn [acc x]
(+ acc x)))
10
(< is shorthand for "parameters are rotated left"). Using reduce<, I can see what's being passed to f by the time my eyes get to the f argument, so I can just focus on reading the f implementation (which may get pretty long). Additionally, if f does get long, I no longer have to visually check the indentation of the val and col arguments to determine that they belong to the reduce symbol way farther up. I personally think this is more readable than binding f to a symbol before calling reduce, especially since fn can still accept a name for clarity.
This is a general solution, but the other answers here provide many good alternative ways to solve the specific problem I gave as an example.
I have:
(defn keep?
(def sum [])
(loop [i 0]
(when (< i 10)
(conj sum 10)
(recur (inc i))))
sum
)
This just gives me and empty vector even though I am conj-ing 10 onto sum. Is this because it is not in-scope within the Loop? How would I achieve the same outcome. (btw, this example is deliberately simplified)
Thanks
conj does not modify its argument. In fact, without resorting to evil reflection tricks, nothing will modify a vector, it's an immutable data structure. This is one of the fundamental principles of Clojure.
In functional programming, instead of modifying data, we replace it with another immutable value. So you need to use the return value of conj, or it is effectively a noop.
(defn keep?
[]
(loop [i 0 sum []]
(if (< i 10)
(recur (inc i) (conj sum 10))
sum)))
Also, the second arg to defn must always be a vector.
conj is not destructive, it does not alter that collection, returns a new collection with the designated state (reference).
To achieve the desired result, you may:
Define sum in a loop-form, like i is defined, instead of using def
recur (inc i) (conj sum 10) to rebind sum to a new one on every iteration, so that state is built up to what you expect
Once the condition in when is not met, just return sum from your loop and it will bubble up to become the return value of this function. Uh hang on, when does not have an "else-branch", a possible alternative is if
Like so:
(defn keep? []
(loop [i 0
sum []]
(if (< i 10)
(recur (inc i)
(conj sum 10))
sum)))
Just to supplement the other answers, I almost never use the loop function. Here are a few ways to do it using the for function:
; return a lazy sequence
(for [i (range 10) ]
i)
;=> (0 1 2 3 4 5 6 7 8 9)
; return a concrete vector
(vec
(for [i (range 10) ]
i))
;=> [0 1 2 3 4 5 6 7 8 9]
; 'into' is very nice for converting one collection into another
(into #{}
(for [i (range 10) ]
i))
;=> #{0 7 1 4 6 3 2 9 5 8} ; hash-set is unique but unordered
Here is the function I'm trying to run...
(defn mongean [cards times]
(let [_cards (transient cards)]
(loop [i 0 c (get cards i) _count (count cards) _current (/ _count 2)]
(assoc! _cards _current c)
(if ((rem i 2) = 0)
(def _newcur (- _current (inc i)))
(def _newcur (+ _current (inc i))))
(if (<= i _count)
(recur (inc i) (get cards i) _count _newcur )))
(persistent! _cards)))
It's resulting in this Exception...
Exception in thread "main" java.lang.ClassCastException: clojure.lang.PersistentHashSet$TransientHashSet cannot be cast to clojure.lang.ITransientAssociative
Being new to clojure, I'd also appreciate any constructive criticism of my approach above. The goal is to take a List, and return a re-ordered list.
I assume that you are trying to implement the Mongean shuffle. Your approach is very imperative and you should try to use a more functional approach.
This would be a possible implementation, were we calculate the final order of the cards (as per Wikipedia formula) and then we use the built-in replace function to do the mapping:
(defn mongean [cards]
(let [num-cards (count cards)
final-order (concat (reverse (range 1 num-cards 2)) (range 0 num-cards 2))]
(replace cards final-order)))
user> (mongean [1 2 3 4 5 6 7 8])
(8 6 4 2 1 3 5 7)
How do you call that function? It looks like you're passing a set, so that its transient version will also be a set and hence can't be used with any of the assoc functions, as they work on associative data structures and vectors:
user=> (assoc #{} :a 1)
ClassCastException clojure.lang.PersistentHashSet cannot be cast to clojure.lang.Associative clojure.lang.RT.assoc (RT.java:691)
user=> (assoc! (transient #{}) :a 1)
ClassCastException clojure.lang.PersistentHashSet$TransientHashSet cannot be cast to clojure.lang.ITransientAssociative clojure.core/assoc! (core.clj:2959)
; the following works as it uses maps and vectors
user=> (assoc {} :a 1)
{:a 1}
user=> (assoc! (transient {}) :a 1)
#<TransientArrayMap clojure.lang.PersistentArrayMap$TransientArrayMap#65cd1dff>
user=> (assoc [] 0 :a)
[:a]
Now, let's try to discuss the code itself. It's a bit hard to follow your code and try to understand what the goal really is without some more hints on what you want to achieve, but as general comments:
you have a times input parameter you don't use at all
you are supposed to use the result of a transient mutation, not assume that the transient will mutate in place
avoid transients if you can, they're only meant as a performance optimization
the binding _current (/ _count 2) is probably not what you want, as (/ 5 2) really returns 5/2 and it seems that you want to use it as a position in the result
constants like _count don't need to be part of the loop binding, you can use the outer let so that you don't have to pass them at each and every iteration
use let instead of def for naming things inside a function
(if ((rem 1 2) = 0)) is definitely not what you want
Now, leaving aside the shuffling algorithm, if you need to rearrange a sequence you might just produce a sequence of new positions, map them with the original cards to produce pairs of [position card] and finally reduce them by placing the card at the new position, using the original sequence as the seed:
(defn generate [coll] ; counts down from (count coll) to 0, change to
; implement your shuffling algorithm
(range (dec (count coll)) -1 -1))
(defn mongean [cards times]
(let [positions (generate cards) ; get the new positions
assemble (fn [dest [pos card]] ; assoc the card at the wanted position
(assoc dest pos card))]
(reduce assemble cards (map vector positions cards))))
If you simply want to shuffle:
(defn mongean [cards times] (shuffle cards))
Coming from imperative programming languages, I am trying to wrap my head around Clojure in hopes of using it for its multi-threading capability.
One of the problems from 4Clojure is to write a function that generates a list of Fibonacci numbers of length N, for N > 1. I wrote a function, but given my limited background, I would like some input on whether or not this is the best Clojure way of doing things. The code is as follows:
(fn fib [x] (cond
(= x 2) '(1 1)
:else (reverse (conj (reverse (fib (dec x))) (+ (last (fib (dec x))) (-> (fib (dec x)) reverse rest first))))
))
The most idiomatic "functional" way would probably be to create an infinite lazy sequence of fibonacci numbers and then extract the first n values, i.e.:
(take n some-infinite-fibonacci-sequence)
The following link has some very interesting ways of generating fibonnaci sequences along those lines:
http://en.wikibooks.org/wiki/Clojure_Programming/Examples/Lazy_Fibonacci
Finally here is another fun implementation to consider:
(defn fib [n]
(let [next-fib-pair (fn [[a b]] [b (+ a b)])
fib-pairs (iterate next-fib-pair [1 1])
all-fibs (map first fib-pairs)]
(take n all-fibs)))
(fib 6)
=> (1 1 2 3 5 8)
It's not as concise as it could be, but demonstrates quite nicely the use of Clojure's destructuring, lazy sequences and higher order functions to solve the problem.
Here is a version of Fibonacci that I like very much (I took the implementation from the clojure wikibook: http://en.wikibooks.org/wiki/Clojure_Programming)
(def fib-seq (lazy-cat [0 1] (map + (rest fib-seq) fib-seq)))
It works like this: Imagine you already have the infinite sequence of Fibonacci numbers. If you take the tail of the sequence and add it element-wise to the original sequence you get the (tail of the tail of the) Fibonacci sequence
0 1 1 2 3 5 8 ...
1 1 2 3 5 8 ...
-----------------
1 2 3 5 8 13 ...
thus you can use this to calculate the sequence. You need two initial elements [0 1] (or [1 1] depending on where you start the sequence) and then you just map over the two sequences adding the elements. Note that you need lazy sequences here.
I think this is the most elegant and (at least for me) mind stretching implementation.
Edit: The fib function is
(defn fib [n] (nth fib-seq n))
Here's one way of doing it that gives you a bit of exposure to lazy sequences, although it's certainly not really an optimal way of computing the Fibonacci sequence.
Given the definition of the Fibonacci sequence, we can see that it's built up by repeatedly applying the same rule to the base case of '(1 1). The Clojure function iterate sounds like it would be good for this:
user> (doc iterate)
-------------------------
clojure.core/iterate
([f x])
Returns a lazy sequence of x, (f x), (f (f x)) etc. f must be free of side-effects
So for our function we'd want something that takes the values we've computed so far, sums the two most recent, and returns a list of the new value and all the old values.
(fn [[x y & _ :as all]] (cons (+ x y) all))
The argument list here just means that x and y will be bound to the first two values from the list passed as the function's argument, a list containing all arguments after the first two will be bound to _, and the original list passed as an argument to the function can be referred to via all.
Now, iterate will return an infinite sequence of intermediate values, so for our case we'll want to wrap it in something that'll just return the value we're interested in; lazy evaluation will stop the entire infinite sequence being evaluated.
(defn fib [n]
(nth (iterate (fn [[x y & _ :as all]] (cons (+ x y) all)) '(1 1)) (- n 2)))
Note also that this returns the result in the opposite order to your implementation; it's a simple matter to fix this with reverse of course.
Edit: or indeed, as amalloy says, by using vectors:
(defn fib [n]
(nth (iterate (fn [all]
(conj all (->> all (take-last 2) (apply +)))) [1 1])
(- n 2)))
See Christophe Grand's Fibonacci solution in Programming Clojure by Stu Halloway. It is the most elegant solution I have seen.
(defn fibo [] (map first (iterate (fn [[a b]] [b (+ a b)]) [0 1])))
(take 10 (fibo))
Also see
How can I generate the Fibonacci sequence using Clojure?
I have this deeply nested list (list of lists) and I want to replace a single arbitrary element in the list. How can I do this ? (The built-in replace might replace many occurrences while I need to replace only one element.)
As everyone else already said, using lists is really not a good idea if you need to do this kind of thing. Random access is what vectors are made for. assoc-in does this efficiently. With lists you can't get away from recursing down into the sublists and replacing most of them with altered versions of themselves all the way back up to the top.
This code will do it though, albeit inefficiently and clumsily. Borrowing from dermatthias:
(defn replace-in-list [coll n x]
(concat (take n coll) (list x) (nthnext coll (inc n))))
(defn replace-in-sublist [coll ns x]
(if (seq ns)
(let [sublist (nth coll (first ns))]
(replace-in-list coll
(first ns)
(replace-in-sublist sublist (rest ns) x)))
x))
Usage:
user> (def x '(0 1 2 (0 1 (0 1 2) 3 4 (0 1 2))))
#'user/x
user> (replace-in-sublist x [3 2 0] :foo)
(0 1 2 (0 1 (:foo 1 2) 3 4 (0 1 2)))
user> (replace-in-sublist x [3 2] :foo)
(0 1 2 (0 1 :foo 3 4 (0 1 2)))
user> (replace-in-sublist x [3 5 1] '(:foo :bar))
(0 1 2 (0 1 (0 1 2) 3 4 (0 (:foo :bar) 2)))
You'll get IndexOutOfBoundsException if you give any n greater than the length of a sublist. It's also not tail-recursive. It's also not idiomatic because good Clojure code shies away from using lists for everything. It's horrible. I'd probably use mutable Java arrays before I used this. I think you get the idea.
Edit
Reasons why lists are worse than vectors in this case:
user> (time
(let [x '(0 1 2 (0 1 (0 1 2) 3 4 (0 1 2)))] ;'
(dotimes [_ 1e6] (replace-in-sublist x [3 2 0] :foo))))
"Elapsed time: 5201.110134 msecs"
nil
user> (time
(let [x [0 1 2 [0 1 [0 1 2] 3 4 [0 1 2]]]]
(dotimes [_ 1e6] (assoc-in x [3 2 0] :foo))))
"Elapsed time: 2925.318122 msecs"
nil
You also don't have to write assoc-in yourself, it already exists. Look at the implementation for assoc-in sometime; it's simple and straightforward (compared to the list version) thanks to vectors giving efficient and easy random access by index, via get.
You also don't have to quote vectors like you have to quote lists. Lists in Clojure strongly imply "I'm calling a function or macro here".
Vectors (and maps, sets etc.) can be traversed via seqs. You can transparently use vectors in list-like ways, so why not use vectors and have the best of both worlds?
Vectors also stand out visually. Clojure code is less of a huge blob of parens than other Lisps thanks to widespread use of [] and {}. Some people find this annoying, I find it makes things easier to read. (My editor syntax-highlights (), [] and {} differently which helps even more.)
Some instances I'd use a list for data:
If I have an ordered data structure that needs to grow from the front, that I'm never going to need random-access to
Building a seq "by hand", as via lazy-seq
Writing a macro, which needs to return code as data
For the simple cases a recursive substitution function will give you just what you need with out much extra complexity. when things get a little more complex its time to crack open clojure build in zipper functions: "Clojure includes purely functional, generic tree walking and editing, using a technique called a zipper (in namespace zip)."
adapted from the example in: http://clojure.org/other_libraries
(defn randomly-replace [replace-with in-tree]
(loop [loc dz]
(if (zip/end? loc)
(zip/root loc)
(recur
(zip/next
(if (= 0 (get-random-int 10))
(zip/replace loc replace-with)
loc)))))
these will work with nested anything (seq'able) even xmls
It sort of doesn't answer your question, but if you have vectors instead of lists:
user=> (update-in [1 [2 3] 4 5] [1 1] inc)
[1 [2 4] 4 5]
user=> (assoc-in [1 [2 3] 4 5] [1 1] 6)
[1 [2 6] 4 5]
So if possible avoid lists in favour of vectors for the better access behaviour. If you have to work with lazy-seq from various sources, this is of course not much of an advice...
You could use this function and adapt it for your needs (nested lists):
(defn replace-item
"Returns a list with the n-th item of l replaced by v."
[l n v]
(concat (take n l) (list v) (drop (inc n) l)))
A simple-minded suggestion from the peanut gallery:
copy the inner list to a vector;
fiddle that vector's elements randomly and to your heart's content using assoc;
copy the vector back to a list;
replace the nested list in the outer list.
This might waste some performance; but if this was a performance sensitive operation you'd be working with vectors in the first place.