Suppose you have a 2x2 design and you're testing differences between those 4 groups using ANOVA in SPSS.
This is a graph of your data:
After performing ANOVA, there are 6 possible pairwise comparisons between groups that we can perform. These are:
A - C
B - D
A - D
B - C
A - B
C - D
If I want to perform pairwise comparisons, I would usually use this script after the UNIANOVA command:
/EMMEANS=TABLES(Var1*Var2) COMPARE (Var1) ADJ(LSD)
/EMMEANS=TABLES(Var1*Var2) COMPARE (Var2) ADJ(LSD)
However, after running this script, the output only contains 4 of the 6 possible comparisons - there are two pairwise comparisons that are missing, and those are:
A - B
C - D
How can I calculate those comparisons?
EMMEANS in UNIANOVA does not provide all pairwise comparisons among the cells in an interaction like this. There are some other procedures, such as GENLIN, that do offer these, but use large-sample chi-square statistics rather than t or F statistics. In UNIANOVA, you can get these using the LMATRIX subcommand, or you can use some trickery with EMMEANS.
For the trickery with EMMEANS, create a single factor with four levels that index the 2x2 layout of cells, then handle that as a one-way model. The main effect for that is the same as the overall 3 degree of freedom model for the 2x2 layout, and of course EMMEANS with COMPARE works fine on that.
Without creating a new variable, you can use LMATRIX with:
/LMATRIX "(1,1) - (2,2)" var1 1 -1 var2 1 -1 var1*var2 1 0 0 -1
/LMATRIX "(1,2) - (2,1)" var1 1 -1 var1 -1 1 var1*var2 0 1 -1 0
The quoted pieces are labels, indicating the cells in the 2x2 design being compared.
Another trick you can use to make specifying the LMATRIX simpler, but without creating a new variable, is to specify the DESIGN with just the interaction term and suppress the intercept. That makes the parameter estimates just the four cell means:
UNIANOVA Y BY var1 var2
/INTERCEPT=EXCLUDE
/DESIGN var1*var1
/LMATRIX "(1,1) - (2,2)" var1*var2 1 0 0 -1
/LMATRIX "(1,2) - (2,1)" var1*var1 0 1 -1 0.
In this case the one effect shown in the ANOVA table is a 4 df effect testing all means against 0, so it's not of interest, but the comparisons you want are easily obtained. Note that this trick only works with procedures that don't reparameterize to full rank.
I want to use Maxima to get the prime factorization of a random positive integer, e.g. 12=2^2*3^1.
What I have tried so far:
a:random(20);
aa:abs(a);
fa:ifactors(aa);
ka:length(fa);
ta:1;
pfza: for i:1 while i<=ka do ta:ta*(fa[i][1])^(fa[i][2]);
ta;
This will be implemented in STACK for Moodle as part of a online exercise for students, so the exact implementation will be a little bit different from this, but I broke it down to these 7 lines.
I generate a random number a, make sure that it is a positive integer by using aa=|a|+1 and want to use the ifactors command to get the prime factors of aa. ka tells me the number of pairwise distinct prime factors which I then use for the while loop in pfza. If I let this piece of code run, it returns everything fine, execpt for simplifying ta, that is I don't get ta as a product of primes with some exponents but rather just ta=aa.
I then tried to turn off the simplifier, manually simplifying everything else that I need:
simp:false$
a:random(20);
aa:ev(abs(a),simp);
fa:ifactors(aa);
ka:ev(length(fa),simp);
ta:1;
pfza: for i:1 while i<=ka do ta:ta*(fa[i][1])^(fa[i][2]);
ta;
This however does not compile; I assume the problem is somewhere in the line for pfza, but I don't know why.
Any input on how to fix this? Or another method of getting the factorizing in a non-simplified form?
(1) The for-loop fails because adding 1 to i requires 1 + 1 to be simplified to 2, but simplification is disabled. Here's a way to make the loop work without requiring arithmetic.
(%i10) for f in fa do ta:ta*(f[1]^f[2]);
(%o10) done
(%i11) ta;
2 2 1
(%o11) ((1 2 ) 2 ) 3
Hmm, that's strange, again because of the lack of simplification. How about this:
(%i12) apply ("*", map (lambda ([f], f[1]^f[2]), fa));
2 1
(%o12) 2 3
In general I think it's better to avoid explicit indexing anyway.
(2) But maybe you don't need that at all. factor returns an unsimplified expression of the kind you are trying to construct.
(%i13) simp:true;
(%o13) true
(%i14) factor(12);
2
(%o14) 2 3
I think it's conceptually inconsistent for factor to return an unsimplified, but anyway it seems to work here.
I am writing a parser for a query engine. My parser DCG query is not deterministic.
I will be using the parser in a relational manner, to both check and synthesize queries.
Is it appropriate for a parser DCG to not be deterministic?
In code:
If I want to be able to use query/2 both ways, does it require that
?- phrase(query, [q,u,e,r,y]).
true;
false.
or should I be able to obtain
?- phrase(query, [q,u,e,r,y]).
true.
nevertheless, given that the first snippet would require me to use it as such
?- bagof(X, phrase(query, [q,u,e,r,y]), [true]).
true.
when using it to check a formula?
The first question to ask yourself, is your grammar deterministic, or in the terminology of grammars, unambiguous. This is not asking if your DCG is deterministic, but if the grammar is unambiguous. That can be answered with basic parsing concepts, no use of DCG is needed to answer that question. In other words, is there only one way to parse a valid input. The standard book for this is "Compilers : principles, techniques, & tools" (WorldCat)
Now you are actually asking about three different uses for parsing.
A recognizer.
A parser.
A generator.
If your grammar is unambiguous then
For a recognizer the answer should only be true for valid input that can be parsed and false for invalid input.
For the parser it should be deterministic as there is only one way to parse the input. The difference between a parser and an recognizer is that a recognizer only returns true or false and a parser will return something more, typically an abstract syntax tree.
For the generator, it should be semi-deterministic so that it can generate multiple results.
Can all of this be done with one, DCG, yes. The three different ways are dependent upon how you use the input and output of the DCG.
Here is an example with a very simple grammar.
The grammar is just an infix binary expression with one operator and two possible operands. The operator is (+) and the operands are either (1) or (2).
expr(expr(Operand_1,Operator,Operand_2)) -->
operand(Operand_1),
operator(Operator),
operand(Operand_2).
operand(operand(1)) --> "1".
operand(operand(2)) --> "2".
operator(operator(+)) --> "+".
recognizer(Input) :-
string_codes(Input,Codes),
DCG = expr(_),
phrase(DCG,Codes,[]).
parser(Input,Ast) :-
string_codes(Input,Codes),
DCG = expr(Ast),
phrase(DCG,Codes,[]).
generator(Generated) :-
DCG = expr(_),
phrase(DCG,Codes,[]),
string_codes(Generated,Codes).
:- begin_tests(expr).
recognizer_test_case_success("1+1").
recognizer_test_case_success("1+2").
recognizer_test_case_success("2+1").
recognizer_test_case_success("2+2").
test(recognizer,[ forall(recognizer_test_case_success(Input)) ] ) :-
recognizer(Input).
recognizer_test_case_fail("2+3").
test(recognizer,[ forall(recognizer_test_case_fail(Input)), fail ] ) :-
recognizer(Input).
parser_test_case_success("1+1",expr(operand(1),operator(+),operand(1))).
parser_test_case_success("1+2",expr(operand(1),operator(+),operand(2))).
parser_test_case_success("2+1",expr(operand(2),operator(+),operand(1))).
parser_test_case_success("2+2",expr(operand(2),operator(+),operand(2))).
test(parser,[ forall(parser_test_case_success(Input,Expected_ast)) ] ) :-
parser(Input,Ast),
assertion( Ast == Expected_ast).
parser_test_case_fail("2+3").
test(parser,[ forall(parser_test_case_fail(Input)), fail ] ) :-
parser(Input,_).
test(generator,all(Generated == ["1+1","1+2","2+1","2+2"]) ) :-
generator(Generated).
:- end_tests(expr).
The grammar is unambiguous and has only 4 valid strings which are all unique.
The recognizer is deterministic and only returns true or false.
The parser is deterministic and returns a unique AST.
The generator is semi-deterministic and returns all 4 valid unique strings.
Example run of the test cases.
?- run_tests.
% PL-Unit: expr ........... done
% All 11 tests passed
true.
To expand a little on the comment by Daniel
As Daniel notes
1 + 2 + 3
can be parsed as
(1 + 2) + 3
or
1 + (2 + 3)
So 1+2+3 is an example as you said is specified by a recursive DCG and as I noted a common way out of the problem is to use parenthesizes to start a new context. What is meant by starting a new context is that it is like getting a new clean slate to start over again. If you are creating an AST, you just put the new context, items in between the parenthesizes, as a new subtree at the current node.
With regards to write_canonical/1, this is also helpful but be aware of left and right associativity of operators. See Associative property
e.g.
+ is left associative
?- write_canonical(1+2+3).
+(+(1,2),3)
true.
^ is right associative
?- write_canonical(2^3^4).
^(2,^(3,4))
true.
i.e.
2^3^4 = 2^(3^4) = 2^81 = 2417851639229258349412352
2^3^4 != (2^3)^4 = 8^4 = 4096
The point of this added info is to warn you that grammar design is full of hidden pitfalls and if you have not had a rigorous class in it and done some of it you could easily create a grammar that looks great and works great and then years latter is found to have a serious problem. While Python was not ambiguous AFAIK, it did have grammar issues, it had enough issues that when Python 3 was created, many of the issues were fixed. So Python 3 is not backward compatible with Python 2 (differences). Yes they have made changes and libraries to make it easier to use Python 2 code with Python 3, but the point is that the grammar could have used a bit more analysis when designed.
The only reason why code should be non-deterministic is that your question has multiple answers. In that case, you'd of course want your query to have multiple solutions. Even then, however, you'd like it to not leave a choice point after the last solution, if at all possible.
Here is what I mean:
"What is the smaller of two numbers?"
min_a(A, B, B) :- B < A.
min_a(A, B, A) :- A =< B.
So now you ask, "what is the smaller of 1 and 2" and the answer you expect is "1":
?- min_a(1, 2, Min).
Min = 1.
?- min_a(2, 1, Min).
Min = 1 ; % crap...
false.
?- min_a(2, 1, 2).
false.
?- min_a(2, 1, 1).
true ; % crap...
false.
So that's not bad code but I think it's still crap. This is why, for the smaller of two numbers, you'd use something like the min() function in SWI-Prolog.
Similarly, say you want to ask, "What are the even numbers between 1 and 10"; you write the query:
?- between(1, 10, X), X rem 2 =:= 0.
X = 2 ;
X = 4 ;
X = 6 ;
X = 8 ;
X = 10.
... and that's fine, but if you then ask for the numbers that are multiple of 3, you get:
?- between(1, 10, X), X rem 3 =:= 0.
X = 3 ;
X = 6 ;
X = 9 ;
false. % crap...
The "low-hanging fruit" are the cases where you as a programmer would see that there cannot be non-determinism, but for some reason your Prolog is not able to deduce that from the code you wrote. In most cases, you can do something about it.
On to your actual question. If you can, write your code so that there is non-determinism only if there are multiple answers to the question you'll be asking. When you use a DCG for both parsing and generating, this sometimes means you end up with two code paths. It feels clumsy but it is easier to write, to read, to understand, and probably to make efficient. As a word of caution, take a look at this question. I can't know that for sure, but the problems that OP is running into are almost certainly caused by unnecessary non-determinism. What probably happens with larger inputs is that a lot of choice points are left behind, there is a lot of memory that cannot be reclaimed, a lot of processing time going into book keeping, huge solution trees being traversed only to get (as expected) no solutions.... you get the point.
For examples of what I mean, you can take a look at the implementation of library(dcg/basics) in SWI-Prolog. Pay attention to several things:
The documentation is very explicit about what is deterministic, what isn't, and how non-determinism is supposed to be useful to the client code;
The use of cuts, where necessary, to get rid of choice points that are useless;
The implementation of number//1 (towards the bottom) that can "generate extract a number".
(Hint: use the primitives in this library when you write your own parser!)
I hope you find this unnecessarily long answer useful.
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.
I'm writing a small parser, which will have an OR operator and an AND operator. When you see a series of ORs and ANDs, which do you expect will be more binding? Given the expression a & b | c, do you expect it to mean (a&b)|c or a&(b|c)? Can you give any reason to prefer one over the other?
Do what everyone else does; AND binds tighter than OR (see e.g. C Operator Precedence Table). This is the convention that everyone expects, so adopt the principle of least surprise.
This choice isn't arbitrary. It stems from the fact that AND and OR follow a similar relationship to multiply and add, respectively; see e.g. http://en.wikipedia.org/wiki/Boolean_logic#Other_notations.
Note also that users of your language should be heavily encouraged to use parentheses to make their intentions clear to readers of their code. But that's up to them!
AND and OR in Boolean algebra are equivalent to * and - in regular algebra, so it makes sense that AND binds harder than OR just like * binds harder than +:
A B A*B A&B A+B A|B
0 0 0 0 0 0
0 1 0 0 1 1
1 0 0 0 1 1
1 1 1 1 1(>0) 1
If you consider it like you would discrete maths, I'd say PEMDAS leads you to say that the AND is more binding. That's not always the case though.
I recommend you recommending your users to use parentheses wherever there's ambiguity.
Usually & has a precedence over | in many scenarios. But you can restrict expressions to be in a full parenthesis form.