(Beginner's) issue with redundant case statement in SML - functional-programming

I'm trying to write a function in SML to compute the partial sum of an alternating harmonic series, and for the life of me I can't figure out why the compiler says one of the cases is redundant. I haven't used case statements before(or local, for that matter), but the order of these cases seems right to me.
local
fun altHarmAux (x:int, y:real) =
case x of
1 => 1.0
| evenP => altHarmAux(x-1, y - y/(real x))
| oddP => altHarmAux(x-1, y + y/(real x))
in
fun altHarmonic (a:int) = altHarmAux(a, real a)
end

Even if you have defined the two predicate functions somewhere, they can't be used in a case like that.
whatever you write on the left hand of => will be bound to the value you are matching on, thus the two last matches in your case will match the same input, rendering the last one useless, as the first one will always be used
You will have to apply your predicate function to the value directly, and then match on the result
local
fun altHarmAux (x, y) =
case (x, evenP x) of
(1, _) => 1.0
| (_ true) => altHarmAux(x-1, y - y/(real x))
| (_, false) => altHarmAux(x-1, y + y/(real x))
in
fun altHarmonic a = altHarmAux(a, real a)
end
or perhaps simpler
local
fun altHarmAux (1, _) = 1.0
| altHarmAux (x, y) =
altHarmAux (x-1, y + (if evenP x then ~y else y) / (real x))
in
fun altHarmonic a = altHarmAux (a, real a)
end
or
local
fun altHarmAux (1, _) = 1.0
| altHarmAux (x, y) =
if evenP x then
altHarmAux (x-1, y - y/(real x))
else
altHarmAux (x-1, y + y/(real x))
in
fun altHarmonic a = altHarmAux (a, real a)
end

Related

Difference between let+, let* and let()?

As the documentation on OCaml is sparse, i would appreciate if some one can explain the difference in different flavors of let usage.
I tried looking into https://dev.realworldocaml.org/toc.html, but there is no easy way to search in the website. Google search landed me to some articles, but did not get the exact explanation.
The basic form of let expressions is:
let p1 = e1
and p2 = e2
...
and pN = eN
in e
where N is at least 1. In this form, let expressions pattern matches the value that results from evaluating the RHS expressions against the LHS patterns, then evaluates the body with the new bindings defined by the LHS patterns in scope. For example,
let x, y = 1, 2 in
x + y
evaluates to 3.
When let has an operator name attached, it is the application of what is called a "let operator" or "binding operator" (to give you easier terms to search up). For example:
let+ x, y = 1, 2 in
x + y
desugars to (let+) (1, 2) (fun (x, y) -> x + y). (Similar to how one surrounds the operator + in parentheses, making it (+), to refer to its identifier, the identifier for the let operator let+, as it appears in a let expression, would be (let+).)
Finally, when a let binding has an operator name attached, all the and bindings must have operator names attached as well.
let* x = 1
and+ y = 2
and* z = 3 in
x + y + z
desugars to (let*) ((and+) 1 ((and*) 2 3)) (fun ((x, y), z) ->).
The following program is invalid and has no meaning because the let binding is being used as an operator, but the and binding is not:
let* x = 1
and y = 2 in
x + y
Binding operators are covered in the "language extensions" section of the OCaml documentation.
let () = e is merely the non-operator form of a pattern match, where () is the pattern that matches the only value of the unit type. The unit type is conventionally the type of expressions that don't evaluate to a meaningful value, but exist for side effects (e.g. print_endline "Hello world!"). Matching against () ensures that the expression has type (), catching partial application errors. The following typechecks:
let f x y =
print_endline x;
print_endline y
let () =
f "Hello" "World"
The following does not:
let f x y =
print_endline x;
print_endline y
let () =
f "Hello" (* Missing second argument, so expression has type string -> unit, not unit *)
Note that the binding operators are useful for conveniently using "monads" and "applicatives," so you may hear these words when learning about binding operators. However, binding operators are not inherently related to these concepts. All they do is desugar to the expressions that I describe above, and any other significance (such as relation to monads) results from how the operator was defined.
Consider the following code from the OCaml page on let operators.
let ( let* ) o f =
match o with
| None -> None
| Some x -> f x
let return x = Some x
If we create a very simply map:
module M = Map.Make (Int)
let m = M.(empty |> add 1 4 |> add 2 3 |> add 3 7)
If we wanted to write a function that takes a map and two keys and adds the values at those keys, returning int option, we might write:
let add_values m k1 k2 =
match M.find_opt k1 m with
| None -> None
| Some v1 ->
match M.find_opt k2 m with
| None -> None
| Some v2 ->
Some (v1 + v2)
Now, of course there are multiple ways of defining this. We could:
let add_values m k1 k2 =
match (M.find_opt k1 m, M.find_opt k2 m) with
| (None, _) | (_, None) -> None
| (Some v1, Some v2) -> Some (v1 + v2)
Or take advantage of exceptions:
let add_values m k1 k2 =
try
Some (M.find k1 m + M.find k2 m)
with
| Not_found -> None
Let operators let us write:
let add_values m k1 k2 =
let* v1 = M.find_opt k1 m in
let* v2 = M.find_opt k2 m in
return (v1 + v2)

Symply.py for getting coefficients for ALL combination of the variables of a multivariable polynomial

How to get coefficients for ALL combinations of the variables of a multivariable polynomial using sympy.jl or another Julia package for symbolic computation?
Here is an example from MATLAB,
syms a b y
[cxy, txy] = coeffs(ax^2 + by, [y x], ‘All’)
cxy =
[ 0, 0, b]
[ a, 0, 0]
txy =
[ x^2y, xy, y]
[ x^2, x, 1]
My goal is to get
[ x^2y, xy, y]
[ x^2, x, 1]
instead of [x^2, y]
I asked the same question at
https://github.com/JuliaPy/SymPy.jl/issues/482
and
https://discourse.julialang.org/t/symply-jl-for-getting-coefficients-for-all-combination-of-the-variables-of-a-multivariable-polynomial/89091
but I think I should ask if this can be done using Sympy.py.
Using Julia, I tried the following,
julia> #syms x, y, a, b
julia> ff = sympy.Poly(ax^2 + by, (x,y))
Poly(ax**2 + by, x, y, domain='ZZ[a,b]')
julia> [prod(ff.gens.^i) for i in ff.monoms()]
2-element Vector{Sym}:
x^2
y
This is a longer form rewrite of the one-liner in the comment.
It uses Pipe.jl to write expressions 'functionally', so familiarity with pipe operator (|>) and Pipe.jl will help.
using SymPy
using Pipe
#syms x, y, a, b
ff = sympy.Poly(a*x^2 + b*y, (x,y))
max_degrees =
#pipe ff.monoms() .|> collect |> hcat(_...) |>
reduce(max, _, dims=2) |> vec
degree_iter =
#pipe max_degrees .|> UnitRange(0, _) |>
tuple(_...) |> CartesianIndices
result = [prod(ff.gens.^Tuple(I)) for I in degree_iter] |>
reverse |> eachcol |> collect
or using more of the python methods:
[prod(ff.gens.^I) for
I in Iterators.product((0:d for d in ff.degree.(ff.gens))...)] |>
reverse |> eachcol |> collect
Both give the desired result:
2-element Vector{...}:
[x^2*y, x*y, y]
[x^2, x, 1]
UPDATE:
In case there are more than 2 generators, the result needs to be a Array with higher dimension. The last bits of matrix transposes is immaterial and the expressions become:
Method 1:
max_degrees =
#pipe ff.monoms() .|> collect |> hcat(_...) |>
reduce(max, _, dims=2) |> vec
degree_iter =
#pipe max_degrees .|> UnitRange(0, _) |>
tuple(_...) |> CartesianIndices
result = [prod(ff.gens.^Tuple(I)) for I in degree_iter]
Method 2:
result = [prod(ff.gens.^Tuple(I)) for I in degree_iter]
Thanks a lot #Dan Getz. Your solution works for the TOY example from MATLAB. My real case is more complicated, which has more variables and polynominals. I tried your method for 3 variables,
using SymPy
#syms x, y, z, a, b
ff = sympy.Poly(a*x^2 + b*y + z^2 + x*y + y*z, (x, y, z))
[prod(ff.gens.^Tuple(I)) for I in CartesianIndices(tuple(UnitRange.(0,vec(reduce(max, hcat(collect.(ff.monoms())...), dims=1)))...))]
I got the following error,
ERROR: LoadError: DimensionMismatch: arrays could not be broadcast to a common size; got a dimension with lengths 3 and 5
Stacktrace:
How to generate your method to any number of variables with different degrees, e.g., x^3 + y^3 + z^3 + xyz + xy^2z?
You can find the degree of each of the two variables of interest and then use them to create the matrix of generators; you can use them to get the coefficients of interest. I am not sure what you expect if the equation were like a*x**2 + b*y + c...
>>> from sympy import *
>>> from sympy.abc import a, b, x, y
>>> eq = a*x**2 + b*y
>>> deg = lambda x: Poly(eq, x).degree() # helper to give degree in "x"
>>> v = (Matrix([x**i for i in range(deg(x),-1,-1)]
... )*Matrix([y**i for i in range(deg(y),-1,-1)]).T).T; v
Matrix([[x**2*y, x*y, y], [x**2, x, 1]])
>>> Matrix(*v.shape, [eq.coeff(i) if i.free_symbols else eq.as_coeff_Add()[0]
... for i in v])
Matrix([[0, 0, b], [a, 0, 0]])
From #jverzani (thanks)
using SymPy;
#syms a b x y;
eq = a*x^2 + b*y;
deg = x -> sympy.Poly(eq, x).degree();
xs, ys = [x^i for i ∈ range(deg(x):-1:0], [y^i for i ∈ deg(y):-1:0];
v = permutedims(xs .* permutedims(ys));
M = [x^2*y x*y y; x^2 x 1];
[length(free_symbols(i)) > 0 ? eq.coeff(i) : eq.as_coeff_add()[1] for i ∈ v];
[0 0 b; a 0 0]

SML syntax error

Logic:
eploy(list, constant)
if list is empty then
return:
0;
else
return:
(first_element + constant*eploy(rest_of_the_elements, constant)
I have written following code:
fun eploy(xs, x1:int) =
if null xs
then (0)
else (x::xs') => x + x1*eploy(xs',x1)
eploy([1,2],4);
If you want to do pattern matching then you need to use case:
fun eploy(xs, x1) =
case xs of
nil => 0
| x::xs' => x + x1*eploy(xs', x1)
You can also merge that into the function definition by using clauses:
fun eploy(nil, x1) = 0
| eploy(x::xs', x1) = x + x1*eploy(xs', x1)

Prolog predicate makelist

Define a Prolog predicate makelist/3 such that makelist(Start, End, List) is true if
List is a list of all integers from the integer Start to the integer End. For example:
makelist(3, 7, [3, 4, 5, 6, 7]) should be true.
Can't understand why my code doesn't work
makelist(H, L, _) :-
L is H+1.
makelist(H, L, List) :-
append([], [H], List), H1 is H+1.
makelist(H1, L, List) :-
append(List, [H1], List1), last(List1, R),
R \= L+1, makelist(N, L, List1), N is H1+1.
You can simplify your code, let's take your predicate and examine what is what you really need to do:
% makelist(X,Y,L)
Since your recursive call is increasing by 1 the first parameter, let's call it X, then your base case would be when X is the same than Y:
makelist(X,X,[X]) .
and your recursive call: it will be when X is smaller than Y, you need to increase X and add the value to the list:
makelist(X,Y,[X|L]) :- X < Y ,
X1 is X + 1 ,
makelist(X1, Y, L).

polynomial equation standard ml

I'm trying to make a function that will solve a univariante polynomial equation in Standard ML, but it keeps giving me error.
The code is below
(* Eval Function *)
- fun eval (x::xs, a:real):real =
let
val v = x (* The first element, since its not multiplied by anything *)
val count = 1 (* We start counting from the second element *)
in
v + elms(xs, a, count)
end;
(* Helper Function*)
- fun pow (base:real, 0) = 1.0
| pow (base:real, exp:int):real = base * pow(base, exp - 1);
(* A function that solves the equation except the last element in the equation, the constant *)
- fun elms (l:real list, a:real, count:int):real =
if (length l) = count then 0.0
else ((hd l) * pow(a, count)) + elms((tl l), a, count + 1);
now the input should be the coefficient if the polynomial elements and a number to substitute the variable, ie if we have the function 3x^2 + 5x + 1, and we want to substitute x by 2, then we would call the eval as follows:
eval ([1.0, 5.0, 3.0], 2.0);
and the result should be 23.0, but sometimes on different input, its giving me different answers, but on this imput its giving me the following error
uncaught exception Empty raised at:
smlnj/init/pervasive.sml:209.19-209.24
what could be my problem here?
Empty is raised when you run hd or tl on an empty list. hd and tl are almost never used in ML; lists are almost always deconstructed using pattern matching instead; it's much prettier and safer. You don't seem to have a case for empty lists, and I didn't go through your code to figure out what you did, but you should be able to work it out yourself.
After some recursive calls, elms function gets empty list as its argument. Since count is always greater than 0, (length l) = count is always false and the calls hd and tl on empty list are failed right after that.
A good way to fix it is using pattern matching to handle empty lists on both eval and elms:
fun elms ([], _, _) = 0.0
| elms (x::xs, a, count) = (x * pow(a, count)) + elms(xs, a, count + 1)
fun eval ([], _) = 0.0
| eval (x::xs, a) = x + elms(xs, a, 1)

Resources