I have the numbers: 1 2 3 4 and want to build a vector (or any kind of seq) from them, so I want [1 2 3 4].
As in (= (__ 1 8 3 4) 8), without using max.
Here is what I have so far :
(= (reduce #(if (< %1 %2) %2 %1) 1 8 3 4) 8)
But I get an ArityException, and therefore want to build a vector of [1 8 3 4].
How can I convert the single numbers to be items of a collection ?
Use vector :
;; create a vector the long way
user=> (vector 1 2 3 4)
Note that if you are talking about hardcoded values, the advantage of having code as data is that you can represent them exactly like that in your code :
;; this is code, equivalent to the code above
[1 2 3 4]
If you are talking about generating a sequence of numbers, have a look at range :
user=> (range 1 5)
(1 2 3 4)
vec will take a collection and turn into a vector :
user=> (vec (range 1 5))
[1 2 3 4]
Taking into account your comment :
user=> (reduce #(if (< %1 %2) %2 %1) (vector 1 8 3 4))
8
user=> (= (reduce #(if (< %1 %2) %2 %1) (vector 1 8 3 4)) 8)
true
But as you surely know, you could use max :
user=> (max 1 2 3 4)
4
user=> (apply max [1 2 3 4])
4
If you really wish not to use max, a concise way of getting the max would be :
user=> (last (sort [1 2 3 4]))
4
Or as an anonymous function, using a threading macro :
user=> #(-> % sort last) ;; % stand for all arguments, as a sequence
4
Ok, i am sorry Pointy, i was just a bit in hurry. This was the original question: (= (__ 1 8 3 4) 8) and i was trying to find out the maximum value amongst the numbers without using max. I thought i usereduce which by the way takes a collection as argument. Now i ended up filling the blank like this: (= ((fn [& x]
(let [arg (apply vector x)]
(reduce #(if (< %1 %2) %2 %1) arg)))
1 2 3 4 8) 8). I used destructuring and it works true (although maybe not looking elegant!)
Related
Given a list of integers from 1 do 10 with size of 5, how do I check if there are only 2 same integers in the list?
For example
(check '(2 2 4 5 7))
yields yes, while
(check '(2 1 4 4 4))
or
(check '(1 2 3 4 5))
yields no
Here is a solution using frequencies to count occurrences and filter to count the number of values that occur only twice:
(defn only-one-pair? [coll]
(->> coll
frequencies ; map with counts of each value in coll
(filter #(= (second %) 2)) ; Keep values that have 2 occurrences
count ; number of unique values with only 2 occurrences
(= 1))) ; true if only one unique val in coll with 2 occurrences
Which gives:
user=> (only-one-pair? '(2 1 4 4 4))
false
user=> (only-one-pair? '(2 2 4 5 7))
true
user=> (only-one-pair? '(1 2 3 4 5))
false
Intermediate steps in the function to get a sense of how it works:
user=> (->> '(2 2 4 5 7) frequencies)
{2 2, 4 1, 5 1, 7 1}
user=> (->> '(2 2 4 5 7) frequencies (filter #(= (second %) 2)))
([2 2])
user=> (->> '(2 2 4 5 7) frequencies (filter #(= (second %) 2)) count)
1
Per a suggestion, the function could use a more descriptive name and it's also best practice to give predicate functions a ? at the end of it in Clojure. So maybe something like only-one-pair? is better than just check.
Christian Gonzalez's answer is elegant, and great if you are sure you are operating on a small input. However, it is eager: it forces the entire input list even when itcould in principle tell sooner that the result will be false. This is a problem if the list is very large, or if it is a lazy list whose elements are expensive to compute - try it on (list* 1 1 1 (range 1e9))! I therefore present below an alternative that short-circuits as soon as it finds a second duplicate:
(defn exactly-one-duplicate? [coll]
(loop [seen #{}
xs (seq coll)
seen-dupe false]
(if-not xs
seen-dupe
(let [x (first xs)]
(if (contains? seen x)
(and (not seen-dupe)
(recur seen (next xs) true))
(recur (conj seen x) (next xs) seen-dupe))))))
Naturally it is rather more cumbersome than the carefree approach, but I couldn't see a way to get this short-circuiting behavior without doing everything by hand. I would love to see an improvement that achieves the same result by combining higher-level functions.
(letfn [(check [xs] (->> xs distinct count (= (dec (count xs)))))]
(clojure.test/are [input output]
(= (check input) output)
[1 2 3 4 5] false
[1 2 1 4 5] true
[1 2 1 2 1] false))
but I like a shorter (but limited to exactly 5 item lists):
(check [xs] (->> xs distinct count (= 4)))
In answer to Alan Malloy's plea, here is a somewhat combinatory solution:
(defn check [coll]
(let [accums (reductions conj #{} coll)]
(->> (map contains? accums coll)
(filter identity)
(= (list true)))))
This
creates a lazy sequence of the accumulating set;
tests it against each corresponding new element;
filters for the true cases - those where the element is already present;
tests whether there is exactly one of them.
It is lazy, but does duplicate the business of scanning the given collection. I tried it on Alan Malloy's example:
=> (check (list* 1 1 1 (range 1e9)))
false
This returns instantly. Extending the range makes no difference:
=> (check (list* 1 1 1 (range 1e20)))
false
... also returns instantly.
Edited to accept Alan Malloy's suggested simplification, which I have had to modify to avoid what appears to be a bug in Clojure 1.10.0.
you can do something like this
(defn check [my-list]
(not (empty? (filter (fn[[k v]] (= v 2)) (frequencies my-list)))))
(check '(2 4 5 7))
(check '(2 2 4 5 7))
Similar to others using frequencies - just apply twice
(-> coll
frequencies
vals
frequencies
(get 2)
(= 1))
Positive case:
(def coll '(2 2 4 5 7))
frequencies=> {2 2, 4 1, 5 1, 7 1}
vals=> (2 1 1 1)
frequencies=> {2 1, 1 3}
(get (frequencies #) 2)=> 1
Negative case:
(def coll '(2 1 4 4 4))
frequencies=> {2 1, 1 1, 4 3}
vals=> (1 1 3)
frequencies=> {1 2, 3 1}
(get (frequencies #) 2)=> nil
I want to map over a sequence in order but want to carry an accumulator value forward, like in a reduce.
Example use case: Take a vector and return a running total, each value multiplied by two.
(defn map-with-accumulator
"Map over input but with an accumulator. func accepts [value accumulator] and returns [new-value new-accumulator]."
[func accumulator collection]
(if (empty? collection)
nil
(let [[this-value new-accumulator] (func (first collection) accumulator)]
(cons this-value (map-with-accumulator func new-accumulator (rest collection))))))
(defn double-running-sum
[value accumulator]
[(* 2 (+ value accumulator)) (+ value accumulator)])
Which gives
(prn (pr-str (map-with-accumulator double-running-sum 0 [1 2 3 4 5])))
>>> (2 6 12 20 30)
Another example to illustrate the generality, print running sum as stars and the original number. A slightly convoluted example, but demonstrates that I need to keep the running accumulator in the map function:
(defn stars [n] (apply str (take n (repeat \*))))
(defn stars-sum [value accumulator]
[[(stars (+ value accumulator)) value] (+ value accumulator)])
(prn (pr-str (map-with-accumulator stars-sum 0 [1 2 3 4 5])))
>>> (["*" 1] ["***" 2] ["******" 3] ["**********" 4] ["***************" 5])
This works fine, but I would expect this to be a common pattern, and for some kind of map-with-accumulator to exist in core. Does it?
You should look into reductions. For this specific case:
(reductions #(+ % (* 2 %2)) 2 (range 2 6))
produces
(2 6 12 20 30)
The general solution
The common pattern of a mapping that can depend on both an item and the accumulating sum of a sequence is captured by the function
(defn map-sigma [f s] (map f s (sigma s)))
where
(def sigma (partial reductions +))
... returns the sequence of accumulating sums of a sequence:
(sigma (repeat 12 1))
; (1 2 3 4 5 6 7 8 9 10 11 12)
(sigma [1 2 3 4 5])
; (1 3 6 10 15)
In the definition of map-sigma, f is a function of two arguments, the item followed by the accumulator.
The examples
In these terms, the first example can be expressed
(map-sigma (fn [_ x] (* 2 x)) [1 2 3 4 5])
; (2 6 12 20 30)
In this case, the mapping function ignores the item and depends only on the accumulator.
The second can be expressed
(map-sigma #(vector (stars %2) %1) [1 2 3 4 5])
; (["*" 1] ["***" 2] ["******" 3] ["**********" 4] ["***************" 5])
... where the mapping function depends on both the item and the accumulator.
There is no standard function like map-sigma.
General conclusions
Just because a pattern of computation is common does not imply that
it merits or requires its own standard function.
Lazy sequences and the sequence library are powerful enough to tease
apart many problems into clear function compositions.
Rewritten to be specific to the question posed.
Edited to accommodate the changed second example.
Reductions is the way to go as Diego mentioned however to your specific problem the following works
(map #(* % (inc %)) [1 2 3 4 5])
As mentioned you could use reductions:
(defn map-with-accumulator [f init-value collection]
(map first (reductions (fn [[_ accumulator] next-elem]
(f next-elem accumulator))
(f (first collection) init-value)
(rest collection))))
=> (map-with-accumulator double-running-sum 0 [1 2 3 4 5])
(2 6 12 20 30)
=> (map-with-accumulator stars-sum 0 [1 2 3 4 5])
("*" "***" "******" "**********" "***************")
It's only in case you want to keep the original requirements. Otherwise I'd prefer to decompose f into two separate functions and use Thumbnail's approach.
I'm trying to implement a Overhand Shuffle in Clojure as a bit of a learning exercise
So I've got this code...
(defn overhand [cards]
(let [ card_count (count cards)
_new_cards '()
_rand_ceiling (if (> card_count 4) (int (* 0.2 card_count)) 1)]
(take card_count
(reduce into (mapcat
(fn [c]
(-> (inc (rand-int _rand_ceiling))
(take cards)
(cons _new_cards)))
cards)))))
It is very close to doing what I want, but it is repeatedly taking the first (random) N number of cards off the front, but I want it to progress through the list...
calling as
(overhand [1 2 3 4 5 6 7 8 9])
instead of ending up with
(1 2 3 1 2 1 2 3 4)
I want to end up with
(7 8 9 5 6 1 2 3 4)
Also, as a side note this feels like a really ugly way to indent/organize this function, is there a more obvious way?
this function is creating a list of lists, transforming each of them, and cating them back together. the problem it that it is pulling from the same thing every time and appending to a fixed value. essentially it is running the same operation every time and so it is repeating the output over with out progressing thgough the list. If you break the problem down differently and split the creation of random sized chunks from the stringing them together it gets a bit easier to see how to make it work correctly.
some ways to split the sequence:
(defn random-partitions [cards]
(let [card_count (count cards)
rand_ceiling (if (> card_count 4) (inc (int (* 0.2 card_count))) 1)]
(partition-by (ƒ [_](= 0 (rand-int rand_ceiling))) cards)))
to keep the partitions less than length four
(defn random-partitions [cards]
(let [[h t] (split-at (inc (rand-int 4)) cards)]
(when (not-empty h) (lazy-seq (cons h (random-partition t))))))
or to keep the partitions at the sizes in your original question
(defn random-partitions [cards]
(let [card_count (count cards)
rand_ceiling (if (> card_count 4) (inc (int (* 0.2 card_count))) 1)
[h t] (split-at (inc (rand-int rand_ceiling)) cards)]
(when (not-empty h) (lazy-seq (cons h (random-partition t))))))
(random-partitions [1 2 3 4 5 6 7 8 9 10])
((1 2 3 4) (5) (6 7 8 9) (10))
this can also be written without directly using lazy-seq:
(defn random-partitions [cards]
(->> [[] cards]
(iterate
(ƒ [[h t]]
(split-at (inc (rand-int 4)) t)))
rest ;iterate returns its input as the first argument, drop it.
(map first)
(take-while not-empty)))
which can then be reduced back into a single sequence:
(reduce into (random-partitions [1 2 3 4 5 6 7 8 9 10]))
(10 9 8 7 6 5 4 3 1 2)
if you reverse the arguments to into it looks like a much better shuffle
(reduce #(into %2 %1) (random-partitions [1 2 3 4 5 6 7 8 9 10]))
(8 7 1 2 3 4 5 6 9 10)
Answering your indentation question, you could refactor your function. For instance, pull out the lambda expression from mapcat, defn it, then use its name in the call to mapcat. You'll not only help with the indentation, but your mapcat will be clearer.
For instance, here's your original program, refactored. Please note that issues with your program have not been corrected, I'm just showing an example of refactoring to improve the layout:
(defn overhand [cards]
(let [ card_count (count cards)
_new_cards '()
_rand_ceiling (if (> card_count 4) (int (* 0.2 card_count)) 1)]
(defn f [c]
(-> (inc (rand-int _rand_ceiling))
(take cards)
(cons _new_cards)))
(take card_count (reduce into (mapcat f cards)))))
You can apply these principles to your fixed code.
A great deal of indentation issues can be resolved by simply factoring out complex expressions. It also helps readability in general.
A better way to organise the function is to separate the shuffling action from the random selection of splitting points that drive it. Then we can test the shuffler with predictable splitters.
The shuffling action can be expressed as
(defn shuffle [deck splitter]
(if (empty? deck)
()
(let [[taken left] (split-at (splitter (count deck)) deck)]
(concat (shuffle left splitter) taken))))
where
deck is the sequence to be shuffled
splitter is a function that chooses where to split deck, given its
size.
We can test shuffle for some simple splitters:
=> (shuffle (range 10) (constantly 3))
(9 6 7 8 3 4 5 0 1 2)
=> (shuffle (range 10) (constantly 2))
(8 9 6 7 4 5 2 3 0 1)
=> (shuffle (range 10) (constantly 1))
(9 8 7 6 5 4 3 2 1 0)
It works.
Now let's look at the way you choose your splitting point. We can illustrate your choice of _rand_ceiling thus:
=> (map
(fn [card_count] (if (> card_count 4) (int (* 0.2 card_count)) 1))
(range 20))
(1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3)
This implies that you will take just one or two cards from any deck of less than ten. By the way, a simpler way to express the function is
(fn [card_count] (max (quot card_count 5) 1))
So we can express your splitter function as
(fn [card_count] (inc (rand-int (max (quot card_count 5) 1))))
So the shuffler we want is
(defn overhand [deck]
(let [splitter (fn [card_count] (inc (rand-int (max (quot card_count 5) 1))))]
(shuffle deck splitter)))
(def tmp = [ 1 2 3 9 4 8])
I'm trying to create pairs of 2, then for each pair, subtract the second number from the first.
desired result: (1 6 4)
Here is what I was trying:
(map #(apply - %2 %1) (partition 2 tmp))
how can I do this?
Partition produces a sequence of sequences so the function you map over them needs to expect a sequence of two items. There are several ways to express this:
(def tmp [ 1 2 3 9 4 8])
user> (map #(- (second %) (first %)) (partition-all 2 tmp ))
(1 6 4)
user> (map #(apply - (reverse %)) (partition-all 2 tmp ))
(1 6 4)
user> (map (fn [[small large]] (- large small)) (partition-all 2 tmp ))
(1 6 4)
The version using apply is different because it will still "work" on odd length lists:
user> (map #(apply - (reverse %)) (partition-all 2 [1 2 3 4 5 6 7] ))
(1 1 1 -7)
The others will crash on invalid input, which you may prefer.
Here's a solution using reduce
(reduce #(conj %1 (apply - (reverse %2))) [] (partition-all 2 [1 2 3 9 4 8]))
=> [1 6 4]
I wonder why this solution was overlooked...
Since switching the order of subtraction is simply the negative of the original subtraction, (a-b=-(b-a)),
the solution becomes more efficient (only in this particular case!!)
(map #(- (apply - %)) (partition-all 2 [1 2 3 9 4 8]))
Pedagogically, Arthur's solution is correct. This is just a solution that is more suited the specfic question.
In Clojure, what would be the nicest way to have a sliding window over a (finite, not too large) seq? Should I just use drop and take and keep track of the current index or is there a nicer way I'm missing?
I think that partition with step 1 does it:
user=> (partition 3 1 [3 1 4 1 5 9])
((3 1 4) (1 4 1) (4 1 5) (1 5 9))
If you want to operate on the windows, it can also be convenient to do this with map:
user=> (def a [3 1 4 1 5 9])
user=> (map (partial apply +) (partition 3 1 a))
(8 6 10 15)
user=> (map + a (next a) (nnext a))
(8 6 10 15)
I didn't know partition could do this so I implemented it this way
(defn sliding-window [seq length]
(loop [result ()
remaining seq]
(let [chunk (take length remaining)]
(if (< (count chunk) length)
(reverse result)
(recur (cons chunk result) (rest remaining))))))