sequence absent in Maxima - maxima

I was trying to see if I can collect information from list based on the depth of nesting of sub-lists.
But I realized that it should be accomplish-able only by tree. I learned programming binary tree in lisp to some extent but it won't be helpful and I will have to try tree with any number of child nodes.
I also found out that there is 'sequence' function in lisp which can make the the work easier as I can do
li:[g,f,t,h,[a,b,c],[[t,y,u]]]
/*after filtering out non-list elements li=[[a,b,c],[[t,y,u]]]*/
IN::map(lambda([x],apply(sequence,[x]),li)
OUT:: [a,b,c,[t,y,u]]
/*Again filtering out and repeating the process will leave me with [t,y,u].*/
In this way I can collect sub-lists at different labels. I couldn't see this sequence function in Maxima. Is there any certain reason it wasn't included ?

Not sure what you want to accomplish. Maybe append has the desired effect?
(%i1) li : [[a, b, c], [[t, y, u]]] $
(%i2) apply (append, li);
(%o2) [a, b, c, [t, y, u]]

Related

Array product given a dynamic number of arguments

I have a function that does an array product:
arrayProduct(l1,l2,l3) = [[a, b, c] |
a := l1[_]
b := l2[_]
c := l3[_]
]
If I have three arrays defined as follows:
animals1 = ["hippo", "giraffe"]
animals2 = ["lion", "zebra"]
animals3 = ["deer", "bear"]
Then the output of arrayProduct(animals1, animals2, animals3) would be:
[["hippo","lion","deer"],["hippo","lion","bear"],["hippo","zebra","deer"],["hippo","zebra","bear"],["giraffe","lion","deer"],["giraffe","lion","bear"],["giraffe","zebra","deer"],["giraffe","zebra","bear"]]
If I can guarantee that the inputs will always be lists is there away I could make a function that would do the same thing except it could accept a dynamic number of lists as input instead of just 3?
I'm also exploring if it would also be possible to do this with only one argument containing all the arrays within it as opposed to accepting multiple arguments. For example:
[["hippo", "giraffe"], ["lion", "zebra"], ["deer", "bear"], ["ostrich", "flamingo"]]
Any insight into a solution with either approach would be appreciated.
There's no known way to compute an arbitrary N-way cross product in Rego without a builtin.
Why something can't be written in a language can be tricky to explain because it amounts to a proof-sketch. We need to make the argument that there is no policy in Rego that computes an N-way cross product. The formal proofs of expressiveness/complexity have not been worked out, so the best we can do is try to articulate why it might not be possible.
For the N-way cross product, it boils down to the fact that Rego guarantees termination for all policies on all inputs, and to do that it restricts how deeply nested iteration can be. In your example (using some and indentation for clarity) you have 3 nested loops with indexes i, j, k.
arrayProduct(l1,l2,l3) = [[a, b, c] |
some i
a := l1[i]
some j
b := l2[j]
some k
c := l3[k]
]
To implement an N-way cross product arrayProduct([l1, l2, ..., ln]) you would need something equivalent to N nested loops:
# NOT valid Rego
arrayProduct([l1,l2,...,ln]) = [[a, b, ..., n] |
some i1
a := l1[i1]
some i2
b := l2[i2]
...
n := ln[in]
]
where importantly the degree of nested iteration N depends on the input.
To guarantee termination, Rego restricts the degree of nested iteration in a policy. You can only nest iteration as many times as you have some (or more properly variables) appearing in your policy. This is analogous to SQL restricting the number of JOINs to those that appear in the query and view definitions.
Since the degree of nesting required for an N-way cross product is N, and N can be larger than the number of somes in the policy, there is no way to implement the N-way cross product.
As a point of contrast, the number of keys or values that are iterated over inside any one loop CAN and usually DO depend on the input. It's the number of loops that cannot depend on the input.
It's not possible to compute an n-ary product of lists/arrays (or sets or objects) in Rego without adding a built-in function.
In the scenario described above, providing a dynamic number of arrays as input to the function would be equivalent to passing an array of arrays (like you mentioned at the end):
arrayProduct([arr1, arr2, ..., arrN])
This works, except that when we try to implement arrayProduct we get stuck because Rego does not permit recursion and iteration only occurs when you inject a variable into a reference. In your original example l1[_] is a reference to the elements in the first list and _ is a unique variable referring to the array indices in that list.
OPA/Rego evaluates that expression by finding assignments to each _ that satisfy the query. The "problem" is that this requires one variable for each list in the input. If the length of the array of arrays is unknown, we would need an infinite number of variables.
If you really need an n-ary product function I would suggest you implement a custom built-in function for now.

How do I tell Maxima about valid approximations of subexpressions of a large expression?

I have a fairly large expression that involves a lot of subexpressions of the form (100*A^3 + 200*A^2 + 100*A)*x or (-A^2 - A)*y or (100*A^2 + 100*A)*z
I know, but I don't know how to tell Maxima this, that it in this case is valid to make the approximation A+1 ~ A, thereby effectively removing anything but the highest power of A in each coefficient.
I'm now looking for functions, tools, or methods that I can use to guide Maxima in dropping various terms that aren't important.
I have attempted with subst, but that requires me to specify each and every factor separately, because:
subst([A+1=B], (A+2)*(A+1)*2);
subst([A+1=B], (A+2)*(A*2+2));
(%o1) 2*(A+2)*B
(%o2) (A+2)*(2*A+2)
(that is, I need to add one expression for each slightly different variant)
I tried with ratsimp, but that's too eager to change every occurrence:
ratsubst(B, A+1, A*(A+1)*2);
ratsubst(B, A+1, A*(A*2+2));
(%o3) 2*B^2-2*B
(%o4) 2*B^2-2*B
which isn't actually simpler, as I would have preferred the answer to have been given as 2*B^2.
In another answer, (https://stackoverflow.com/a/22695050/5999883) the functions let and letsimp were suggested for the task of substituting values, but I fail to get them to really do anything:
x:(A+1)*A;
let ( A+1, B );
letsimp(x);
(x)A*(A+1)
(%o6) A+1 --\> B
(%o7) A^2+A
Again, I'd like to approximate this expression to A^2 (B^2, whatever it's called).
I understand that this is, in general, a hard problem (is e.g. A^2 + 10^8*A still okay to approximate as A^2?) but I think that what I'm looking for is a function or method of calculation that would be a little bit smarter than subst and can recognize that the same substitution could be done in the expression A^2+A as in the expression 100*A^2+100*A or -A^2-A instead of making me create a list of three (or twenty) individual substitutions when calling subst. The "nice" part of the full expression that I'm working on is that each of these A factors are of the form k*A^n*(A+1)^m for various small integers n, m, so I never actually end up with the degenerate case mentioned above.
(I was briefly thinking of re-expressing my expression as a polynomial in A, but this will not work as the only valid approximation of the expression (A^3+A^2+A)*x + y is A^3*x + y -- I know nothing about the relative sizes of x and y.

Erlang flatten function time complexity

I need a help with following:
flatten ([]) -> [];
flatten([H|T]) -> H ++ flatten(T).
Input List contain other lists with a different length
For example:
flatten([[1,2,3],[4,7],[9,9,9,9,9,9]]).
What is the time complexity of this function?
And why?
I got it to O(n) where n is a number of elements in the Input list.
For example:
flatten([[1,2,3],[4,7],[9,9,9,9,9,9]]) n=3
flatten([[1,2,3],[4,7],[9,9,9,9,9,9],[3,2,4],[1,4,6]]) n=5
Thanks for help.
First of all I'm not sure your code will work, at least not in the way standard library works. You could compare your function with lists:flatten/1 and maybe improve on your implementation. Try lists such as [a, [b, c]] and [[a], [b, [c]], [d]] as input and verify if you return what you expected.
Regarding complexity it is little tricky due to ++ operator and functional (immutable) nature of the language. All lists in Erlang are linked lists (not arrays like in C++), and you can not just add something to end of one without modifying it; before it was pointing to end of list, now you would like it to link to something else. And again, since it is not mutable language you have to make copy of whole list left of ++ operator, which increases complexity of this operator.
You could say that complexity of A ++ B is length(A), and it makes complexity of your function little bit greater. It would go something like length(FirstElement) + (lenght(FirstElement) + length(SecondElement)) + .... up to (without) last, which after some math magic could be simplified to (n -1) * 1/2 * k * k where n is number of elements, and k is average length of element. Or O(n^3).
If you are new to this it might seem little bit odd, but with some practice you can get hang of it. I would recommend going through few resources:
Good explanation of lists and how they are created
Documentation on list handling with DO and DO NOT parts
Short description of ++ operator myths and best practices
Chapter about recursion and tail-recursion with examples using ++ operator

Pathfinding in Prolog

I'm trying to teach myself Prolog. Below, I've written some code that I think should return all paths between nodes in an undirected graph... but it doesn't. I'm trying to understand why this particular code doesn't work (which I think differentiates this question from similar Prolog pathfinding posts). I'm running this in SWI-Prolog. Any clues?
% Define a directed graph (nodes may or may not be "room"s; edges are encoded by "leads_to" predicates).
room(kitchen).
room(living_room).
room(den).
room(stairs).
room(hall).
room(bathroom).
room(bedroom1).
room(bedroom2).
room(bedroom3).
room(studio).
leads_to(kitchen, living_room).
leads_to(living_room, stairs).
leads_to(living_room, den).
leads_to(stairs, hall).
leads_to(hall, bedroom1).
leads_to(hall, bedroom2).
leads_to(hall, bedroom3).
leads_to(hall, studio).
leads_to(living_room, outside). % Note "outside" is the only node that is not a "room"
leads_to(kitchen, outside).
% Define the indirection of the graph. This is what we'll work with.
neighbor(A,B) :- leads_to(A, B).
neighbor(A,B) :- leads_to(B, A).
Iff A --> B --> C --> D is a loop-free path, then
path(A, D, [B, C])
should be true. I.e., the third argument contains the intermediate nodes.
% Base Rule (R0)
path(X,Y,[]) :- neighbor(X,Y).
% Inductive Rule (R1)
path(X,Y,[Z|P]) :- not(X == Y), neighbor(X,Z), not(member(Z, P)), path(Z,Y,P).
Yet,
?- path(bedroom1, stairs, P).
is false. Why? Shouldn't we get a match to R1 with
X = bedroom1
Y = stairs
Z = hall
P = []
since,
?- neighbor(bedroom1, hall).
true.
?- not(member(hall, [])).
true.
?- path(hall, stairs, []).
true .
?
In fact, if I evaluate
?- path(A, B, P).
I get only the length-1 solutions.
Welcome to Prolog! The problem, essentially, is that when you get to not(member(Z, P)) in R1, P is still a pure variable, because the evaluation hasn't gotten to path(Z, Y, P) to define it yet. One of the surprising yet inspiring things about Prolog is that member(Ground, Var) will generate lists that contain Ground and unify them with Var:
?- member(a, X).
X = [a|_G890] ;
X = [_G889, a|_G893] ;
X = [_G889, _G892, a|_G896] .
This has the confusing side-effect that checking for a value in an uninstantiated list will always succeed, which is why not(member(Z, P)) will always fail, causing R1 to always fail. The fact that you get all the R0 solutions and none of the R1 solutions is a clue that something in R1 is causing it to always fail. After all, we know R0 works.
If you swap these two goals, you'll get the first result you want:
path(X,Y,[Z|P]) :- not(X == Y), neighbor(X,Z), path(Z,Y,P), not(member(Z, P)).
?- path(bedroom1, stairs, P).
P = [hall]
If you ask for another solution, you'll get a stack overflow. This is because after the change we're happily generating solutions with cycles as quickly as possible with path(Z,Y,P), only to discard them post-facto with not(member(Z, P)). (Incidentally, for a slight efficiency gain we can switch to memberchk/2 instead of member/2. Of course doing the wrong thing faster isn't much help. :)
I'd be inclined to convert this to a breadth-first search, which in Prolog would imply adding an "open set" argument to contain solutions you haven't tried yet, and at each node first trying something in the open set and then adding that node's possibilities to the end of the open set. When the open set is extinguished, you've tried every node you could get to. For some path finding problems it's a better solution than depth first search anyway. Another thing you could try is separating the path into a visited and future component, and only checking the visited component. As long as you aren't generating a cycle in the current step, you can be assured you aren't generating one at all, there's no need to worry about future steps.
The way you worded the question leads me to believe you don't want a complete solution, just a hint, so I think this is all you need. Let me know if that's not right.

Find all possible pairs between the subsets of N sets with Erlang

I have a set S. It contains N subsets (which in turn contain some sub-subsets of various lengths):
1. [[a,b],[c,d],[*]]
2. [[c],[d],[e,f],[*]]
3. [[d,e],[f],[f,*]]
N. ...
I also have a list L of 'unique' elements that are contained in the set S:
a, b, c, d, e, f, *
I need to find all possible combinations between each sub-subset from each subset so, that each resulting combination has exactly one element from the list L, but any number of occurrences of the element [*] (it is a wildcard element).
So, the result of the needed function working with the above mentioned set S should be (not 100% accurate):
- [a,b],[c],[d,e],[f];
- [a,b],[c],[*],[d,e],[f];
- [a,b],[c],[d,e],[f],[*];
- [a,b],[c],[d,e],[f,*],[*];
So, basically I need an algorithm that does the following:
take a sub-subset from the subset 1,
add one more sub-subset from the subset 2 maintaining the list of 'unique' elements acquired so far (the check on the 'unique' list is skipped if the sub-subset contains the * element);
Repeat 2 until N is reached.
In other words, I need to generate all possible 'chains' (it is pairs, if N == 2, and triples if N==3), but each 'chain' should contain exactly one element from the list L except the wildcard element * that can occur many times in each generated chain.
I know how to do this with N == 2 (it is a simple pair generation), but I do not know how to enhance the algorithm to work with arbitrary values for N.
Maybe Stirling numbers of the second kind could help here, but I do not know how to apply them to get the desired result.
Note: The type of data structure to be used here is not important for me.
Note: This question has grown out from my previous similar question.
These are some pointers (not a complete code) that can take you to right direction probably:
I don't think you will need some advanced data structures here (make use of erlang list comprehensions). You must also explore erlang sets and lists module. Since you are dealing with sets and list of sub-sets, they seems like an ideal fit.
Here is how things with list comprehensions will get solved easily for you: [{X,Y} || X <- [[c],[d],[e,f]], Y <- [[a,b],[c,d]]]. Here i am simply generating a list of {X,Y} 2-tuples but for your use case you will have to put real logic here (including your star case)
Further note that with list comprehensions, you can use output of one generator as input of a later generator e.g. [{X,Y} || X1 <- [[c],[d],[e,f]], X <- X1, Y1 <- [[a,b],[c,d]], Y <- Y1].
Also for removing duplicates from a list of things L = ["a", "b", "a"]., you can anytime simply do sets:to_list(sets:from_list(L)).
With above tools you can easily generate all possible chains and also enforce your logic as these chains get generated.

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