Mathematica Notation and syntax mods - syntax

I am experimenting with syntax mods in Mathematica, using the Notation package.
I am not interested in mathematical notation for a specific field, but general purpose syntax modifications and extensions, especially notations that reduce the verbosity of Mathematica's VeryLongFunctionNames, clean up unwieldy constructs, or extend the language in a pleasing way.
An example modification is defining Fold[f, x] to evaluate as Fold[f, First#x, Rest#x]
This works well, and is quite convenient.
Another would be defining *{1,2} to evaluate as Sequence ## {1,2} as inspired by Python; this may or may not work in Mathematica.
Please provide information or links addressing:
Limits of notation and syntax modification
Tips and tricks for implementation
Existing packages, examples or experiments
Why this is a good or bad idea

Not a really constructive answer, just a couple of thoughts. First, a disclaimer - I don't suggest any of the methods described below as good practices (perhaps generally they are not), they are just some possibilities which seem to address your specific question. Regarding the stated goal - I support the idea very much, being able to reduce verbosity is great (for personal needs of a solo developer, at least). As for the tools: I have very little experience with Notation package, but, whether or not one uses it or writes some custom box-manipulation preprocessor, my feeling is that the whole fact that the input expression must be parsed into boxes by Mathematica parser severely limits a number of things that can be done. Additionally, there will likely be difficulties with using it in packages, as was mentioned in the other reply already.
It would be easiest if there would be some hook like $PreRead, which would allow the user to intercept the input string and process it into another string before it is fed to the parser. That would allow one to write a custom preprocessor which operates on the string level - or you can call it a compiler if you wish - which will take a string of whatever syntax you design and generate Mathematica code from it. I am not aware of such hook (it may be my ignorance of course). Lacking that, one can use for example the program style cells and perhaps program some buttons which read the string from those cells and call such preprocessor to generate the Mathematica code and paste it into the cell next to the one where the original code is.
Such preprocessor approach would work best if the language you want is some simple language (in terms of its syntax and grammar, at least), so that it is easy to lexically analyze and parse. If you want the Mathematica language (with its full syntax modulo just a few elements that you want to change), in this approach you are out of luck in the sense that, regardless of how few and "lightweight" your changes are, you'd need to re-implement pretty much completely the Mathematica parser, just to make those changes, if you want them to work reliably. In other words, what I am saying is that IMO it is much easier to write a preprocessor that would generate Mathematica code from some Lisp-like language with little or no syntax, than try to implement a few syntactic modifications to otherwise the standard mma.
Technically, one way to write such a preprocessor is to use standard tools like Lex(Flex) and Yacc(Bison) to define your grammar and generate the parser (say in C). Such parser can be plugged back to Mathematica either through MathLink or LibraryLink (in the case of C). Its end result would be a string, which, when parsed, would become a valid Mathematica expression. This expression would represent the abstract syntax tree of your parsed code. For example, code like this (new syntax for Fold is introduced here)
"((1|+|{2,3,4,5}))"
could be parsed into something like
"functionCall[fold,{plus,1,{2,3,4,5}}]"
The second component for such a preprocessor would be written in Mathematica, perhaps in a rule-based style, to generate Mathematica code from the AST. The resulting code must be somehow held unevaluated. For the above code, the result might look like
Hold[Fold[Plus,1,{2,3,4,5}]]
It would be best if analogs of tools like Lex(Flex)/Yacc(Bison) were available within Mathematica ( I mean bindings, which would require one to only write code in Mathematica, and generate say C parser from that automatically, plugging it back to the kernel either through MathLink or LibraryLink). I may only hope that they will become available in some future versions. Lacking that, the approach I described would require a lot of low-level work (C, or Java if your prefer). I think it is still doable however. If you can write C (or Java), you may try to do some fairly simple (in terms of the syntax / grammar) language - this may be an interesting project and will give an idea of what it will be like for a more complex one. I'd start with a very basic calculator example, and perhaps change the standard arithmetic operators there to some more weird ones that Mathematica can not parse properly itself, to make it more interesting. To avoid MathLink / LibraryLink complexity at first and just test, you can call the resulting executable from Mathematica with Run, passing the code as one of the command line arguments, and write the result to a temporary file, that you will then import into Mathematica. For the calculator example, the entire thing can be done in a few hours.
Of course, if you only want to abbreviate certain long function names, there is a much simpler alternative - you can use With to do that. Here is a practical example of that - my port of Peter Norvig's spelling corrector, where I cheated in this way to reduce the line count:
Clear[makeCorrector];
makeCorrector[corrector_Symbol, trainingText_String] :=
Module[{model, listOr, keys, words, edits1, train, max, known, knownEdits2},
(* Proxies for some commands - just to play with syntax a bit*)
With[{fn = Function, join = StringJoin, lower = ToLowerCase,
rev = Reverse, smatches = StringCases, seq = Sequence, chars = Characters,
inter = Intersection, dv = DownValues, len = Length, ins = Insert,
flat = Flatten, clr = Clear, rep = ReplacePart, hp = HoldPattern},
(* body *)
listOr = fn[Null, Scan[If[# =!= {}, Return[#]] &, Hold[##]], HoldAll];
keys[hash_] := keys[hash] = Union[Most[dv[hash][[All, 1, 1, 1]]]];
words[text_] := lower[smatches[text, LetterCharacter ..]];
With[{m = model},
train[feats_] := (clr[m]; m[_] = 1; m[#]++ & /# feats; m)];
With[{nwords = train[words[trainingText]],
alphabet = CharacterRange["a", "z"]},
edits1[word_] := With[{c = chars[word]}, join ### Join[
Table[
rep[c, c, #, rev[#]] &#{{i}, {i + 1}}, {i, len[c] - 1}],
Table[Delete[c, i], {i, len[c]}],
flat[Outer[#1[c, ##2] &, {ins[#1, #2, #3 + 1] &, rep},
alphabet, Range[len[c]], 1], 2]]];
max[set_] := Sort[Map[{nwords[#], #} &, set]][[-1, -1]];
known[words_] := inter[words, keys[nwords]]];
knownEdits2[word_] := known[flat[Nest[Map[edits1, #, {-1}] &, word, 2]]];
corrector[word_] := max[listOr[known[{word}], known[edits1[word]],
knownEdits2[word], {word}]];]];
You need some training text with a large number of words as a string to pass as a second argument, and the first argument is the function name for a corrector. Here is the one that Norvig used:
text = Import["http://norvig.com/big.txt", "Text"];
You call it once, say
In[7]:= makeCorrector[correct, text]
And then use it any number of times on some words
In[8]:= correct["coputer"] // Timing
Out[8]= {0.125, "computer"}
You can make your custom With-like control structure, where you hard-code the short names for some long mma names that annoy you the most, and then wrap that around your piece of code ( you'll lose the code highlighting however). Note, that I don't generally advocate this method - I did it just for fun and to reduce the line count a bit. But at least, this is universal in the sense that it will work both interactively and in packages. Can not do infix operators, can not change precedences, etc, etc, but almost zero work.

(my first reply/post.... be gentle)
From my experience, the functionality appears to be a bit of a programming cul-de-sac. The ability to define custom notations seems heavily dependent on using the 'notation palette' to define and clear each custom notation. ('everything is an expression'... well, except for some obscure cases, like Notations, where you have to use a palette.) Bummer.
The Notation package documentation mentions this explicitly, so I can't complain too much.
If you just want to define custom notations in a particular notebook, Notations might be useful to you. On the other hand, if your goal is to implement custom notations in YourOwnPackage.m and distribute them to others, you are likely to encounter issues. (unless you're extremely fluent in Box structures?)
If someone can correct my ignorance on this, you'd make my month!! :)
(I was hoping to use Notations to force MMA to treat subscripted variables as symbols.)

Not a full answer, but just to show a trick I learned here (more related to symbol redefinition than to Notation, I reckon):
Unprotect[Fold];
Fold[f_, x_] :=
Block[{$inMsg = True, result},
result = Fold[f, First#x, Rest#x];
result] /; ! TrueQ[$inMsg];
Protect[Fold];
Fold[f, {a, b, c, d}]
(*
--> f[f[f[a, b], c], d]
*)
Edit
Thanks to #rcollyer for the following (see comments below).
You can switch the definition on or off as you please by using the $inMsg variable:
$inMsg = False;
Fold[f, {a, b, c, d}]
(*
->f[f[f[a,b],c],d]
*)
$inMsg = True;
Fold[f, {a, b, c, d}]
(*
->Fold::argrx: (Fold called with 2 arguments; 3 arguments are expected.
*)
Fold[f, {a, b, c, d}]
That's invaluable while testing

Related

Working with real functions in mathematica

In general, mathematica always assumes the most general case, that is, if I set a function
a[s_]:={a1[s],a2[s],a3[s]}
and want to compute its norm Norm[a[s]], for example, it will return:
Sqrt[Abs[a1[s]]^2 + Abs[a2[s]]^2 + Abs[a3[s]]^2]
However, if I know that all ai[s] are real, I can invoke:
Assuming[{a1[s], a2[s], a3[s]} \[Element] Reals, Simplify[Norm[a[s]]]]
which will return:
Sqrt[a1[s]^2 + a2[s]^2 + a3[s]^2]
Which is what I expect.
Problem happens when trying to, for example, derive a[s] and then (note the D):
Assuming[{a1[s], a2[s], a3[s]} \[Element] Reals, Simplify[Norm[D[a[s],s]]]]
Returns again a result involving absolute values - coming from the assumption that the numbers may be imaginary.
What is the way to overcome this problem? I want to define a real-valued function, and work with it as such. That is, for instance, I want its derivatives to be real.
I would use a custom function instead, e.g.
vecNorm[vec_?VectorQ] := Sqrt[ vec.vec ]
Then
In[20]:= vecNorm[D[{a1[s], a2[s], a3[s]}, s]]
Out[20]= Sqrt[
Derivative[1][a1][s]^2 + Derivative[1][a2][s]^2 +
Derivative[1][a3][s]^2]
Warning: I don't have much practical experience with this, so the examples below are not thoroughly tested (i.e. I don't know if too general assumptions can break anything I haven't thought of).
You can use $Assumptions to define permanent assumptions:
We could say that all of a1[s], a2[s], a3[s] are reals:
$Assumptions = {(a1[s] | a2[s] | a3[s]) \[Element] Reals}
But if you have e.g. a1[x] (not a1[s]), then it won't work. So we can improve it a bit using patterns:
$Assumptions = {(a1[_] | a2[_] | a3[_]) \[Element] Reals}
Or just say that all values of a[_] are real:
$Assumptions = {a[_] \[Element] Reals}
Or even be bold and say that everything is real:
$Assumptions = {_ \[Element] Reals}
(I wonder what this breaks)
AppendTo is useful for adding to $Assumptions and keeping previous assumptions.
Just like Assuming, this will only work for functions like Simplify or Integrate that have an Assumtpions option. D is not such a function.
Some functions like Reduce, FindInstance, etc. have an option to work only on the domain of Reals, Integers, etc., which assumes that all expressions and subexpressions they work with are real.
ComplexExpand[] and sometimes FunctionExpand[] may also be useful in similar situations (but not really here). Examples: ComplexExpand[Abs[z]^2, TargetFunctions -> {Sign}] and FunctionExpand[Abs'[x], Assumptions -> {x \[Element] Reals}].
Generally, as far as I know, there is no mathematical way to tell Mathematica that a variable is real. It is only possible to do this in a formal way, using patterns, and only for certain functions that have the Assumptions option. By "formal" I mean that if you tell it that a[x] is real, it will not know automatically that a'[x] is also real.
You could use ComplexExpand in this case albeit with a workaround. For example
ComplexExpand[Norm[a'[s], t]] /. t -> 2
returns
Sqrt[Derivative[1][a1][s]^2 + Derivative[1][a2][s]^2 + Derivative[1][a3][s]^2]
Note that doing something like ComplexExpand[Norm[a'[s], 2]] (or indeed ComplexExpand[Norm[a'[s], p]] where p is a rational number) doesn't work for some reason.
For older Mathematica versions there used to be an add-on package RealOnly that put Mathematica in a reals-only mode. There is a version available in later versions and online with minimal compatibility upgrades. It reduces many situations to a real-only solution, but doesn't work for your Norm case:

What is the recommended way to check that a list is a list of numbers in argument of a function?

I've been looking at the ways to check arguments of functions. I noticed that
MatrixQ takes 2 arguments, the second is a test to apply to each element.
But ListQ only takes one argument. (also for some reason, ?ListQ does not have a help page, like ?MatrixQ does).
So, for example, to check that an argument to a function is a matrix of numbers, I write
ClearAll[foo]
foo[a_?(MatrixQ[#, NumberQ] &)] := Module[{}, a + 1]
What would be a good way to do the same for a List? This below only checks that the input is a List
ClearAll[foo]
foo[a_?(ListQ[#] &)] := Module[{}, a + 1]
I could do something like this:
ClearAll[foo]
foo[a_?(ListQ[#] && (And ## Map[NumberQ[#] &, # ]) &)] := Module[{}, a + 1]
so that foo[{1, 2, 3}] will work, but foo[{1, 2, x}] will not (assuming x is a symbol). But it seems to me to be someone complicated way to do this.
Question: Do you know a better way to check that an argument is a list and also check the list content to be Numbers (or of any other Head known to Mathematica?)
And a related question: Any major run-time performance issues with adding such checks to each argument? If so, do you recommend these checks be removed after testing and development is completed so that final program runs faster? (for example, have a version of the code with all the checks in, for the development/testing, and a version without for production).
You might use VectorQ in a way completely analogous to MatrixQ. For example,
f[vector_ /; VectorQ[vector, NumericQ]] := ...
Also note two differences between VectorQ and ListQ:
A plain VectorQ (with no second argument) only gives true if no elements of the list are lists themselves (i.e. only for 1D structures)
VectorQ will handle SparseArrays while ListQ will not
I am not sure about the performance impact of using these in practice, I am very curious about that myself.
Here's a naive benchmark. I am comparing two functions: one that only checks the arguments, but does nothing, and one that adds two vectors (this is a very fast built-in operation, i.e. anything faster than this could be considered negligible). I am using NumericQ which is a more complex (therefore potentially slower) check than NumberQ.
In[2]:= add[a_ /; VectorQ[a, NumericQ], b_ /; VectorQ[b, NumericQ]] :=
a + b
In[3]:= nothing[a_ /; VectorQ[a, NumericQ],
b_ /; VectorQ[b, NumericQ]] := Null
Packed array. It can be verified that the check is constant time (not shown here).
In[4]:= rr = RandomReal[1, 10000000];
In[5]:= Do[add[rr, rr], {10}]; // Timing
Out[5]= {1.906, Null}
In[6]:= Do[nothing[rr, rr], {10}]; // Timing
Out[6]= {0., Null}
Homogeneous non-packed array. The check is linear time, but very fast.
In[7]:= rr2 = Developer`FromPackedArray#RandomInteger[10000, 1000000];
In[8]:= Do[add[rr2, rr2], {10}]; // Timing
Out[8]= {1.75, Null}
In[9]:= Do[nothing[rr2, rr2], {10}]; // Timing
Out[9]= {0.204, Null}
Non-homogeneous non-packed array. The check takes the same time as in the previous example.
In[10]:= rr3 = Join[rr2, {Pi, 1.0}];
In[11]:= Do[add[rr3, rr3], {10}]; // Timing
Out[11]= {5.625, Null}
In[12]:= Do[nothing[rr3, rr3], {10}]; // Timing
Out[12]= {0.282, Null}
Conclusion based on this very simple example:
VectorQ is highly optimized, at least when using common second arguments. It's much faster than e.g. adding two vectors, which itself is a well optimized operation.
For packed arrays VectorQ is constant time.
#Leonid's answer is very relevant too, please see it.
Regarding the performance hit (since your first question has been answered already) - by all means, do the checks, but in your top-level functions (which receive data directly from the user of your functionality. The user can also be another independent module, written by you or someone else). Don't put these checks in all your intermediate functions, since such checks will be duplicate and indeed unjustified.
EDIT
To address the problem of errors in intermediate functions, raised by #Nasser in the comments: there is a very simple technique which allows one to switch pattern-checks on and off in "one click". You can store your patterns in variables inside your package, defined prior to your function definitions.
Here is an example, where f is a top-level function, while g and h are "inner functions". We define two patterns: for the main function and for the inner ones, like so:
Clear[nlPatt,innerNLPatt ];
nlPatt= _?(!VectorQ[#,NumericQ]&);
innerNLPatt = nlPatt;
Now, we define our functions:
ClearAll[f,g,h];
f[vector:nlPatt]:=g[vector]+h[vector];
g[nv:innerNLPatt ]:=nv^2;
h[nv:innerNLPatt ]:=nv^3;
Note that the patterns are substituted inside definitions at definition time, not run-time, so this is exactly equivalent to coding those patterns by hand. Once you test, you just have to change one line: from
innerNLPatt = nlPatt
to
innerNLPatt = _
and reload your package.
A final question is - how do you quickly find errors? I answered that here, in sections "Instead of returning $Failed, one can throw an exception, using Throw.", and "Meta-programming and automation".
END EDIT
I included a brief discussion of this issue in my book here. In that example, the performance hit was on the level of 10% increase of running time, which IMO is borderline acceptable. In the case at hand, the check is simpler and the performance penalty is much less. Generally, for a function which is any computationally-intensive, correctly-written type checks cost only a small fraction of the total run-time.
A few tricks which are good to know:
Pattern-matcher can be very fast, when used syntactically (no Condition or PatternTest present in the pattern).
For example:
randomString[]:=FromCharacterCode#RandomInteger[{97,122},5];
rstest = Table[randomString[],{1000000}];
In[102]:= MatchQ[rstest,{__String}]//Timing
Out[102]= {0.047,True}
In[103]:= MatchQ[rstest,{__?StringQ}]//Timing
Out[103]= {0.234,True}
Just because in the latter case the PatternTest was used, the check is much slower, because evaluator is invoked by the pattern-matcher for every element, while in the first case, everything is purely syntactic and all is done inside the pattern-matcher.
The same is true for unpacked numerical lists (the timing difference is similar). However, for packed numerical lists, MatchQ and other pattern-testing functions don't unpack for certain special patterns, moreover, for some of them the check is instantaneous.
Here is an example:
In[113]:=
test = RandomInteger[100000,1000000];
In[114]:= MatchQ[test,{__?IntegerQ}]//Timing
Out[114]= {0.203,True}
In[115]:= MatchQ[test,{__Integer}]//Timing
Out[115]= {0.,True}
In[116]:= Do[MatchQ[test,{__Integer}],{1000}]//Timing
Out[116]= {0.,Null}
The same, apparently, seems to be true for functions like VectorQ, MatrixQ and ArrayQ with certain predicates (NumericQ) - these tests are extremely efficient.
A lot depends on how you write your test, i.e. to what degree you reuse the efficient Mathematica structures.
For example, we want to test that we have a real numeric matrix:
In[143]:= rm = RandomInteger[10000,{1500,1500}];
Here is the most straight-forward and slow way:
In[144]:= MatrixQ[rm,NumericQ[#]&&Im[#]==0&]//Timing
Out[144]= {4.125,True}
This is better, since we reuse the pattern-matcher better:
In[145]:= MatrixQ[rm,NumericQ]&&FreeQ[rm,Complex]//Timing
Out[145]= {0.204,True}
We did not utilize the packed nature of the matrix however. This is still better:
In[146]:= MatrixQ[rm,NumericQ]&&Total[Abs[Flatten[Im[rm]]]]==0//Timing
Out[146]= {0.047,True}
However, this is not the end. The following one is near instantaneous:
In[147]:= MatrixQ[rm,NumericQ]&&Re[rm]==rm//Timing
Out[147]= {0.,True}
Since ListQ just checks that the head is List, the following is a simple solution:
foo[a:{___?NumberQ}] := Module[{}, a + 1]

What does // mean in Mathematica?

Examples:
In
CT = Table[Prepend[10^4*x[range2] /.
NDSolve[{...series of equations here...}, {t, range1, range2},
MaxSteps -> 10000,
PrecisionGoal -> 11], delay],
{delay, delaymin, delaymax, 0.1}]; // Timing
what does it mean this // Timing after the semicolon?
In
Dρ = -I*((H0 + V).ρ - ρ.(H0 + V)) - Γ*ρ // Simplify;
And this // Simplify here?
I can't find this explanation anywhere!
Thanks in advance,
Thiago
This is Mathematica's postfix notation.
Basically x//f is the same as f[x]
Yes, argument // function is postfix function application.
Useful about it is that it has a different, lower binding power relative to prefix application (f # x).
In fact it is lower than most other things (exceptions include CompoundExpression ; and Set =), and therefore it can often be considered as "apply to everything before this."
You say: "I can't find this explanation anywhere!". I assume this means you are not aware of the documentation center that's right under your fingertips whenever you're using Mathematica.
All you have to do is to place your cursor on the // and press F1 and you'll get some sort of explanation, or a list with relevant (hopefully) matches. In this case the PostFix page, which is not extremely helpful. However, it has some links at the bottom (assuming you have versions 6, 7 or 8) that provide more insight, among which a link to the syntax overview page (click the Mathematica syntax link, or enter "guide/Syntax" in the search box).
expr // f is essentially equivalent to f[expr]. Sometimes, it's called postfix notation. I read expr // f as "pass the expression expr to the function f".
a // f
is, I believe, the same thing as
f[a]
(which incidentally, any sane mathematician I know would write as
f(a)
just as it is done in most computer languages.)
As others have mentioned, // is the postfix notation and expr//f means f[expr] in mathematica and f(expr) in math.
Although there might be more subtleties involved, my usage of // has often been in cases where I've started writing out an expression and then realized I wanted to operate a function on it. So instead of moving the cursor all the way back to type f#expr or f[expr], I can simply finish typing what I had in mind, and use expr//f.
Example:
Plot[Sin[x],{x,0,Pi}]
%//Export["test.pdf",#]&
The graphics is passed to the export function and is saved as test.pdf.
As your question has already got very good answers, I want to add just a clarification on usage.
The three expressions
Sin[x]
Sin#x
x // Sin
Are equivalent.
Although, to my knowledge, the last two can't be used with functions with more than one argument. So
Plot[Sin[x], {x, 0, Pi}]
Can't be invoked in prefix or postfix notation without tricks like
Sin[x] // Plot[#, {x, 0, Pi}] &
or
Plot[#, {x, 0, Pi}] &#Sin[x]
The prefix notation is usually seen when using simple functions like Sin#x or Sort#list, while most uses of the postfix involve a reasoning like "and now do whatever with this thing I got", for example
(Sin#x+ ...) // Timing
where you decided what to calculate, and then you also want it timed.
One more note:
Really there is much more under the scenes, as the priority of each of these functional constructs is different, but I think that is a much deeper subject and you have to experiment a little before going for subtleties.

Using nested slots (#)

Suppose I want to construct something like
Array[#1^#2 == 3 &, {3, 3}]
And now I want to replace the "3" with a variable. I can do, for example:
f[x_] := Array[#1^#2 == x &, {x, x}]
The question is: Is there a way using only slots and & as the functional notation?
Not really the answer to the original question, but I noticed that many people got interested in #0 stuff, so here I put a couple of non-trivial examples, hope they will be useful.
Regarding the statement that for nested functions one should use functions with named arguments: while this is generally true, one should always keep in mind that lexical scoping for pure functions (and generally) is emulated in Mathematica, and can be broken. Example:
In[71]:=
Clear[f,g];
f[fun_,val_]:=val/.x_:>fun[x];
g[fn_,val_]:=f[Function[{x},fn[#1^#2==x&,{x,x}]],val];
g[Array,3]
During evaluation of In[71]:= Function::flpar: Parameter specification {3} in
Function[{3},Array[#1^#2==3&,{3,3}]] should be a symbol or a list of symbols. >>
During evaluation of In[71]:= Function::flpar: Parameter specification {3} in
Function[{3},Array[#1^#2==3&,{3,3}]] should be a symbol or a list of symbols. >>
Out[74]= Function[{3},Array[#1^#2==3&,{3,3}]][3]
This behavior has to do with the intrusive nature of rule substitutions - that is, with the fact that Rule and RuleDelayed don't care about possible name collisions between names in scoping constructs which may be present in expressions subject to rule applications, and names of pattern variables in rules. What makes things worse is that g and f work completely fine when taken separately. It is when they are mixed together, that this entanglement happens, and only because we were unlucky to use the same pattern variable x in the body of f, as in a pure function. This makes such bugs very hard to catch, while such situations do happen sometimes in practice, so I'd recommend against passing pure functions with named arguments as parameters into higher-order functions defined through patterns.
Edit:
Expanding a bit on emulation of the lexical scoping. What I mean is that, for example, when I create a pure function (which is a lexical scoping construct that binds the variable names in its body to the values of passed parameters), I expect that I should not be able to alter this binding after I have created a function. This means that, no matter where I use Function[x,body-that-depends-on-x], I should be able to treat it as a black box with input parameters and resulting outputs. But, in Mathematica, Function[x,x^2] (for instance) is also an expression, and as such, can be modified like any other expression. For example:
In[75]:=
x = 5;
Function[Evaluate[x],x^2]
During evaluation of In[75]:= Function::flpar: Parameter specification 5 in Function[5,x^2] should
be a symbol or a list of symbols. >>
Out[76]= Function[5,x^2]
or, even simpler (the essence of my previous warning):
In[79]:= 1/.x_:>Function[x,x^2]
During evaluation of In[79]:= Function::flpar: Parameter specification 1 in Function[1,1^2] should
be a symbol or a list of symbols. >>
Out[79]= Function[1,1^2]
I was bitten by this last behavior a few times pretty painfully. This behavior was also noted by #WReach at the bottom of his post on this page - obviously he had similar experiences. There are other ways of breaking the scope, based on exact knowledge of how Mathematica renames variables during the conflicts, but those are comparatively less harmful in practice. Generally, I don't think these sorts of things can be avoided if one insists on the level of transparency represented by Mathematica expressions. It just seems to be "over-transparent" for pure functions (and lexical scoping constructs generally), but on the other hand this has its uses as well, for example we can forge a pure function at run-time like this:
In[82]:= Block[{x},Function##{x,Integrate[HermiteH[10,y],{y,0,x}]}]
Out[82]= Function[x,-30240 x+100800 x^3-80640 x^5+23040 x^7-2560 x^9+(1024 x^11)/11]
Where the integral is computed only once, at definition-time (could use Evaluate as well). So, this looks like a tradeoff. In this way, the functional abstraction is better integrated into Mathematica, but is leaky, as #WReach noted. Alternatively, it could have been "waterproof", but perhaps for the price of being less exposed. This was clearly a design decision.
How about
Map[Last, #] & /# Array[#1^#2 == #3 &, {#, #, #}] &[3]
Horrendously ugly element extraction, and very interestingly Map[Last, #]& gives me a different result than Last /#. Is this due to the fact that Map has different attributes than &?
I guess you know what the documentation says about nested pure functions.
Use explicit names to set up nested
pure functions (for example):
Function[u, Function[v, f[u, v]]][x]
Anyway, here's the best I could come up with without following the above advice:
f[x_] := Array[#1^#2 == x &, {x, x}]
g = Array[With[{x = #}, #1^#2 == x &], {#, #}] &
g is functionally identical to your original f, but is not really better than the recommended
h = Function[x, Array[#1^#2 == x &, {x, x}]]
How about With[{x = #1}, Array[#1^#2 == x &, {x, x}]] &?
Perhaps
Array[#1^#2 &, {#, #}] /. i_Integer :> i == # &[3]
Or
Thread /# Thread[# == Array[#1^#2 &, {#, #}]] &[3]

Are there Mathematica packages for presenting proofs/derivations?

When I write out a proof or derivation on paper I frequently make sign errors or drop terms as I move from one step to the next. I'd like to use Mathematica to save myself from these silly mistakes. I don't want Mathematica to solve the expression, I just want to use it carry out and display a series of algebraic manipulations. For a (trivial) example
In[111]:= MultBothSides[Equal[a_, b_], c_] := Equal[c a, c b];
In[112]:= expression = 2 a == a b
Out[112]= 2 a == a b
In[113]:= MultBothSides[expression, 1/a]
Out[113]= 2 == b
Can anyone point me to a package that would support this kind of manipulation?
Edit
Thanks for the input, not quite what I'm looking for though. The symbol manipulation isn't really the problem. I'm really looking for something that will make explicit the algebraic or mathematical justification of each step of a derivation. My goal here is really pedagogical.
Mathematica also provides a number of high-level functions for manipulating algebraic. Among these are Expand, Apart and Together, and Cancel, though there are quite a few more.
Also, for your specific example of applying the same transformation to both sides of an equation (that is, and expression with the head Equal), you can use the Thread function, which works just like your MultBothSides function, but with a great deal more generality.
In[1]:= expression = 2 a == a b
Out[1]:= 2 a == a b
In[2]:= Thread[expression /a, Equal]
Out[2]:= 2 == b
In[3]:= Thread[expression - c, Equal]
Out[3]:= 2 a - c == a b - c
In either of the presented solutions, it should be relatively easy to see what the step entailed. If you want something a little more explicit, you can write your own function like so:
In[4]:= ApplyToBothSides[f_, eq_Equal] := Map[f, eq]
In[5]:= ApplyToBothSides[4 * #&, expression]
Out[5]:= 8 a == 4 a b
It's a generalization of your MultBothSides function that takes advantage of the fact that Map works on expressions with any head, not just head List. If you're trying to communicate with an audience that is unfamiliar with Mathematica, using these sorts of names can help you communicate more clearly. In a related vein, if you want to use replacement rules as suggested by Ira Baxter, it may be helpful to write out Replace or ReplaceAll instead of using the /. syntactic sugar.
In[6]:= ReplaceAll[expression, a -> (x + y)]
Out[6]:= 2 (x + y) == b (x + y)
If you think it would be clearer to have the actual equation, instead of the variable name expression, in your input, and you're using the notebook interface, highlight the word expression with your mouse, call up the contextual menu, and select "Evaluate in Place".
The notebook interface is also a very pleasant environment for doing "literate programming", so you can also explain any steps that are not immediately obvious in words. I believe this is a good practice when writing mathematical proofs regardless of the medium.
I don't think you need a package. What you want to do is to manipulate each formula according to an inference rule. In MMa, you can model inference rules on a formula using transformations. So, if you have a formula f, you can apply an inference rule I by executing (my MMa syntax is 15 years rusty)
f ./ I
to produce the next formula in your sequence.
MMa will of course try to simplify your formulas if they contain standard algebraic operators and terms, such as constant numbers and arithmetic operators. You can prevent MMa from applying its own "inference" rules by enclosing your formula in a Hold[...] form.

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