Unevaluated form of a[[i]] - wolfram-mathematica

Consider following simple, illustrating example
cf = Block[{a, x, degree = 3},
With[{expr = Product[x - a[[i]], {i, degree}]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]
]
]
This is one of the possible ways to transfer code in the body of a Compile statement. It produces the Part::partd error, since a[[i]] is at the moment of evaluation not a list.
The easy solution is to just ignore this message or turn it off. There are of course other ways around it. For instance one could circumvent the evaluation of a[[i]] by replacing it inside the Compile-body before it is compiled
cf = ReleaseHold[Block[{a, x, degree = 3},
With[{expr = Product[x - a[i], {i, degree}]},
Hold[Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]] /.
a[i_] :> a[[i]]]
]
]
If the compiled function a large bit of code, the Hold, Release and the replacement at the end goes a bit against my idea of beautiful code. Is there a short and nice solution I have not considered yet?
Answer to the post of Szabolcs
Could you tell me though why you are using With here?
Yes, and it has to do with the reason why I cannot use := here. I use With, to have something like a #define in C, which means a code-replacement at the place I need it. Using := in With delays the evaluation and what the body of Compile sees is not the final piece of code which it is supposed to compile. Therefore,
<< CompiledFunctionTools`
cf = Block[{a, x, degree = 3},
With[{expr := Product[x - a[[i]], {i, degree}]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]]];
CompilePrint[cf]
shows you, that there is a call to the Mathematica-kernel in the compiled function
I4 = MainEvaluate[ Function[{x, a}, degree][ R0, T(R1)0]]
This is bad because Compile should use only the local variables to calculate the result.
Update
Szabolcs solution works in this case but it leaves the whole expression unevaluated. Let me explain, why it is important that the expression is expanded before it is compiled. I have to admit, my toy-example was not the best. So lets try a better one using With and SetDelayed like in the solution of Szabolcs
Block[{a, x}, With[
{expr := D[Product[x - a[[i]], {i, 3}], x]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]
]
]
Say I have a polynomial of degree 3 and I need the derivative of it inside the Compile. In the above code I want Mathematica to calculate the derivative for unassigned roots a[[i]] so I can use the formula very often in the compiled code. Looking at the compiled code above
one sees, that the D[..] cannot be compiled as nicely as the Product and stays unevaluated
11 R1 = MainEvaluate[ Hold[D][ R5, R0]]
Therefore, my updated question is: Is it possible to evaluate a piece of code without evaluating the Part[]-accesses in it better/nicer than using
Block[{a, x}, With[
{expr = D[Quiet#Product[x - a[[i]], {i, 3}], x]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]
]
]
Edit: I put the Quiet to the place it belongs. I had it in front of code block to make it visible to everyone that I used Quiet here to suppress the warning. As Ruebenko pointed already out, it should in real code always be as close as possible to where it belongs. With this approach you probably don't miss other important warnings/errors.
Update 2
Since we're moving away from the original question, we should move this discussion maybe to a new thread. I don't know to whom I should give the best answer-award to my question since we discussed Mathematica and Scoping more than how to suppress the a[[i]] issue.
Update 3
To give the final solution: I simply suppress (unfortunately like I did all the time) the a[[i]] warning with Quiet. In a real example below, I have to use Quiet outside the complete Block to suppress the warning.
To inject the required code into the body of Compile I use a pure function and give the code to inline as argument. This is the same approach Michael Trott is using in, e.g. his Numerics book. This is a bit like the where clause in Haskell, where you define stuff you used afterwards.
newtonC = Function[{degree, f, df, colors},
Compile[{{x0, _Complex, 0}, {a, _Complex, 1}},
Block[{x = x0, xn = 0.0 + 0.0 I, i = 0, maxiter = 256,
eps = 10^(-6.), zeroId = 1, j = 1},
For[i = 0, i < maxiter, ++i,
xn = x - f/(df + eps);
If[Abs[xn - x] < eps,
Break[]
];
x = xn;
];
For[j = 1, j <= degree, ++j,
If[Abs[xn - a[[j]]] < eps*10^2,
zeroId = j + 1;
Break[];
];
];
colors[[zeroId]]*(1 - (i/maxiter)^0.3)*1.5
],
CompilationTarget -> "C", RuntimeAttributes -> {Listable},
RuntimeOptions -> "Speed", Parallelization -> True]]##
(Quiet#Block[{degree = 3, polynomial, a, x},
polynomial = HornerForm[Product[x - a[[i]], {i, degree}]];
{degree, polynomial, HornerForm[D[polynomial, x]],
List ### (ColorData[52, #] & /# Range[degree + 1])}])
And this function is now fast enough to calculate the Newton-fractal of a polynomial where the position of the roots is not fixed. Therefore, we can adjust the roots dynamically.
Feel free to adjust n. Here it runs up to n=756 fluently
(* ImageSize n*n, Complex plange from -b-I*b to b+I*b *)
With[{n = 256, b = 2.0},
DynamicModule[{
roots = RandomReal[{-b, b}, {3, 2}],
raster = Table[x + I y, {y, -b, b, 2 b/n}, {x, -b, b, 2 b/n}]},
LocatorPane[Dynamic[roots],
Dynamic[
Graphics[{Inset[
Image[Reverse#newtonC[raster, Complex ### roots], "Real"],
{-b, -b}, {1, 1}, 2 {b, b}]}, PlotRange -> {{-b, b}, {-
b, b}}, ImageSize -> {n, n}]], {{-b, -b}, {b, b}},
Appearance -> Style["\[Times]", Red, 20]
]
]
]
Teaser:

Ok, here is the very oversimplified version of the code generation framework I am using for various purposes:
ClearAll[symbolToHideQ]
SetAttributes[symbolToHideQ, HoldFirst];
symbolToHideQ[s_Symbol, expandedSymbs_] :=! MemberQ[expandedSymbs, Unevaluated[s]];
ClearAll[globalProperties]
globalProperties[] := {DownValues, SubValues, UpValues (*,OwnValues*)};
ClearAll[getSymbolsToHide];
Options[getSymbolsToHide] = {
Exceptions -> {List, Hold, HoldComplete,
HoldForm, HoldPattern, Blank, BlankSequence, BlankNullSequence,
Optional, Repeated, Verbatim, Pattern, RuleDelayed, Rule, True,
False, Integer, Real, Complex, Alternatives, String,
PatternTest,(*Note- this one is dangerous since it opens a hole
to evaluation leaks. But too good to be ingored *)
Condition, PatternSequence, Except
}
};
getSymbolsToHide[code_Hold, headsToExpand : {___Symbol}, opts : OptionsPattern[]] :=
Join ## Complement[
Cases[{
Flatten[Outer[Compose, globalProperties[], headsToExpand]], code},
s_Symbol /; symbolToHideQ[s, headsToExpand] :> Hold[s],
Infinity,
Heads -> True
],
Hold /# OptionValue[Exceptions]];
ClearAll[makeHidingSymbol]
SetAttributes[makeHidingSymbol, HoldAll];
makeHidingSymbol[s_Symbol] :=
Unique[hidingSymbol(*Unevaluated[s]*) (*,Attributes[s]*)];
ClearAll[makeHidingRules]
makeHidingRules[symbs : Hold[__Symbol]] :=
Thread[List ## Map[HoldPattern, symbs] -> List ## Map[makeHidingSymbol, symbs]];
ClearAll[reverseHidingRules];
reverseHidingRules[rules : {(_Rule | _RuleDelayed) ..}] :=
rules /. (Rule | RuleDelayed)[Verbatim[HoldPattern][lhs_], rhs_] :> (rhs :> lhs);
FrozenCodeEval[code_Hold, headsToEvaluate : {___Symbol}] :=
Module[{symbolsToHide, hidingRules, revHidingRules, result},
symbolsToHide = getSymbolsToHide[code, headsToEvaluate];
hidingRules = makeHidingRules[symbolsToHide];
revHidingRules = reverseHidingRules[hidingRules];
result =
Hold[Evaluate[ReleaseHold[code /. hidingRules]]] /. revHidingRules;
Apply[Remove, revHidingRules[[All, 1]]];
result];
The code works by temporarily hiding most symbols with some dummy ones, and allow certain symbols evaluate. Here is how this would work here:
In[80]:=
FrozenCodeEval[
Hold[Compile[{{x,_Real,0},{a,_Real,1}},D[Product[x-a[[i]],{i,3}],x]]],
{D,Product,Derivative,Plus}
]
Out[80]=
Hold[Compile[{{x,_Real,0},{a,_Real,1}},
(x-a[[1]]) (x-a[[2]])+(x-a[[1]]) (x-a[[3]])+(x-a[[2]]) (x-a[[3]])]]
So, to use it, you have to wrap your code in Hold and indicate which heads you want to evaluate. What remains here is just to apply ReleseHold to it. Note that the above code just illustrates the ideas, but is still quite limited. The full version of my method involves other steps which make it much more powerful but also more complex.
Edit
While the above code is still too limited to accomodate many really interesting cases, here is one additional neat example of what would be rather hard to achieve with the traditional tools of evaluation control:
In[102]:=
FrozenCodeEval[
Hold[f[x_, y_, z_] :=
With[Thread[{a, b, c} = Map[Sqrt, {x, y, z}]],
a + b + c]],
{Thread, Map}]
Out[102]=
Hold[
f[x_, y_, z_] :=
With[{a = Sqrt[x], b = Sqrt[y], c = Sqrt[z]}, a + b + c]]

EDIT -- Big warning!! Injecting code using With or Function into Compile that uses some of Compile's local variables is not reliable! Consider the following:
In[63]:= With[{y=x},Compile[x,y]]
Out[63]= CompiledFunction[{x$},x,-CompiledCode-]
In[64]:= With[{y=x},Compile[{{x,_Real}},y]]
Out[64]= CompiledFunction[{x},x,-CompiledCode-]
Note the renaming of x to x$ in the first case. I recommend you read about localization here and here. (Yes, this is confusing!) We can guess about why this only happens in the first case and not the second, but my point is that this behaviour might not be intended (call it a bug, dark corner or undefined behaviour), so relying on it is fragile ...
Replace-based solutions, like my withRules function do work though (this was not my intended use for that function, but it fits well here ...)
In[65]:= withRules[{y->x},Compile[x,y]]
Out[65]= CompiledFunction[{x},x,-CompiledCode-]
Original answers
You can use := in With, like so:
cf = Block[{a, x, degree = 3},
With[{expr := Product[x - a[[i]], {i, degree}]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]
]
]
It will avoid evaluating expr and the error from Part.
Generally, = and := work as expected in all of With, Module and Block.
Could you tell me though why you are using With here? (I'm sure you have a good reason, I just can't see it from this simplified example.)
Additional answer
Addressing #halirutan's concern about degree not being inlined during compilation
I see this as exactly the same situation as if we had a global variable defined that we use in Compile. Take for example:
In[18]:= global=1
Out[18]= 1
In[19]:= cf2=Compile[{},1+global]
Out[19]= CompiledFunction[{},1+global,-CompiledCode-]
In[20]:= CompilePrint[cf2]
Out[20]=
No argument
3 Integer registers
Underflow checking off
Overflow checking off
Integer overflow checking on
RuntimeAttributes -> {}
I0 = 1
Result = I2
1 I1 = MainEvaluate[ Function[{}, global][ ]]
2 I2 = I0 + I1
3 Return
This is a common issue. The solution is to tell Compile to inline globals, like so:
cf = Block[{a, x, degree = 3},
With[{expr := Product[x - a[[i]], {i, degree}]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr,
CompilationOptions -> {"InlineExternalDefinitions" -> True}]]];
CompilePrint[cf]
You can check that now there's no callback to the main evaluator.
Alternatively you can inject the value of degree using an extra layer of With instead of Block. This will make you wish for something like this very much.
Macro expansion in Mathematica
This is somewhat unrelated, but you mention in your post that you use With for macro expansion. Here's my first (possibly buggy) go at implementing macro expansion in Mathematica. This is not well tested, feel free to try to break it and post a comment.
Clear[defineMacro, macros, expandMacros]
macros = Hold[];
SetAttributes[defineMacro, HoldAllComplete]
defineMacro[name_Symbol, value_] := (AppendTo[macros, name]; name := value)
SetAttributes[expandMacros, HoldAllComplete]
expandMacros[expr_] := Unevaluated[expr] //. Join ## (OwnValues /# macros)
Description:
macros is a (held) list of all symbols to be expanded.
defineMacro will make a new macro.
expandMacros will expand macro definitions in an expression.
Beware: I didn't implement macro-redefinition, this will not work while expansion is on using $Pre. Also beware of recursive macro definitions and infinite loops.
Usage:
Do macro expansion on all input by defining $Pre:
$Pre = expandMacros;
Define a to have the value 1:
defineMacro[a, 1]
Set a delayed definition for b:
b := a + 1
Note that the definition of b is not fully evaluated, but a is expanded.
?b
Global`b
b:=1+1
Turn off macro expansion ($Pre can be dangerous if there's a bug in my code):
$Pre =.

One way:
cf = Block[{a, x, degree = 3},
With[{expr = Quiet[Product[x - a[[i]], {i, degree}]]},
Compile[{{x, _Real, 0}, {a, _Real, 1}}, expr]]]
be careful though, it you really want this.

Original code:
newtonC = Function[{degree, f, df, colors},
Compile[{{x0, _Complex, 0}, {a, _Complex, 1}},
Block[{x = x0, xn = 0.0 + 0.0 I, i = 0, maxiter = 256,
...
RuntimeOptions -> "Speed", Parallelization -> True]]##
(Quiet#Block[{degree = 3, polynomial, a, x},
polynomial = HornerForm[Product[x - a[[i]], {i, degree}]];
...
Modified code:
newtonC = Function[{degree, f, df, colors},
Compile[{{x0, _Complex, 0}, {a, _Complex, 1}},
Block[{x = x0, xn = 0.0 + 0.0 I, i = 0, maxiter = 256,
...
RuntimeOptions -> "Speed", Parallelization -> True],HoldAllComplete]##
( (( (HoldComplete###)/.a[i_]:>a[[i]] )&)#Block[{degree = 3, polynomial, a, x},
polynomial = HornerForm[Product[x - a[i], {i, degree}]];
...
Add HoldAllComplete attribute to the function.
Write a[i] in place of a[[i]].
Replace Quiet with (( (HoldComplete###)/.a[i_]:>a[[i]] )&)
Produces the identical code, no Quiet, and all of the Hold stuff is in one place.

Related

Constructing a triadiagonal matrix in Mathematica where nonzero elements contain functions and variables

Suppose I want to construct a matrix A such that A[[i,i]]=f[x_,y_]+d[i], A[[i,i+1]]=u[i], A[[i+1,i]]=l[i], i=1,N . Say, f[x_,y_]=x^2+y^2.
How can I code this in Mathematica?
Additionally, if I want to integrate the first diagonal element of A, i.e. A[[1,1]] over x and y, both running from 0 to 1, how can I do that?
In[1]:= n = 4;
f[x_, y_] := x^2 + y^2;
A = Normal[SparseArray[{
{i_,i_}/;i>1 -> f[x,y]+ d[i],
{i_,j_}/;j-i==1 -> u[i],
{i_,j_}/;i-j==1 -> l[i-1],
{1, 1} -> Integrate[f[x,y]+d[1], {x,0,1}, {y,0,1}]},
{n, n}]]
Out[3]= {{2/3+d[1], l[1], 0, 0},
{u[1], x^2+y^2+ d[2], l[2], 0},
{0, u[2], x^2+y^2+d[3], l[3]},
{0, 0, u[3], x^2+y^2+d[4]}}
Band is tailored specifically for this:
myTridiagonalMatrix#n_Integer?Positive :=
SparseArray[
{ Band#{1, 1} -> f[x, y] + Array[d, n]
, Band#{1, 2} -> Array[u, n - 1]
, Band#{2, 1} -> Array[l, n - 1]}
, {n, n}]
Check it out (no need to define f, d, u, l):
myTridiagonalMatrix#5 // MatrixForm
Note that MatrixForm should not be part of a definition. For example, it's a bad idea to set A = (something) // MatrixForm. You will get a MatrixForm object instead of a table (= array of arrays) or a sparse array, and its only purpose is to be pretty-printed in FrontEnd. Trying to use MatrixForm in calculations will yield errors and will lead to unnecessary confusion.
Integrating the element at {1, 1}:
myTridiagonalMatrixWithFirstDiagonalElementIntegrated#n_Integer?Positive :=
MapAt[
Integrate[#, {x, 0, 1}, {y, 0, 1}]&
, myTridiagonalMatrix#n
, {1, 1}]
You may check it out without defining f or d, as well:
myTridiagonalMatrixWithFirstDiagonalElementIntegrated#5
The latter operation, however, looks suspicious. For example, it does not leave your matrix (or its corresponding linear system) invariant w.r.t. reasonable transformations. (This operation does not even preserve linearity of matrices.) You probably don't want to do it.
Comment on comment above: there's no need to define A[x_, y_] := … to Integrate[A[[1,1]], {x,0,1}, {y,0,1}]. Note that A[[1,1]] is totally different from A[1, 1]: the former is Part[A, 1, 1] which is a certain element of table A. A[1, 1] is a different expression: if A is some table then A[1, 1] is (that table)[1, 1], which is a valid expression but is normally considered meaningless.

Is it possible to access the partial list content while being Sow'ed or must one wait for it to be Reap'ed?

I've been learning Sow/Reap. They are cool constructs. But I need help to see if I can use them to do what I will explain below.
What I'd like to do is: Plot the solution of NDSolve as it runs. I was thinking I can use Sow[] to collect the solution (x,y[x]) as NDSolve runs using EvaluationMonitor. But I do not want to wait to the end, Reap it and then plot the solution, but wanted to do it as it is running.
I'll show the basic setup example
max = 30;
sol1 = y /.
First#NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1},
y, {x, 0, max}];
Plot[sol1[x], {x, 0, max}, PlotRange -> All, AxesLabel -> {"x", "y[x]"}]
Using Reap/Sow, one can collect the data points, and plot the solution at the end like this
sol = Reap[
First#NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1},
y, {x, 0, max}, EvaluationMonitor :> Sow[{x, y[x]}]]][[2, 1]];
ListPlot[sol, AxesLabel -> {"x", "y[x]"}]
Ok, so far so good. But what I want is to access the partially being build list, as it accumulates by Sow and plot the solution. The only setup I know how do this is to have Dynamic ListPlot that refreshes when its data changes. But I do not know how to use Sow to move the partially build solution to this data so that ListPlot update.
I'll show how I do it without Sow, but you see, I am using AppenedTo[] in the following:
ClearAll[x, y, lst];
max = 30;
lst = {{0, 0}};
Dynamic[ListPlot[lst, Joined -> False, PlotRange -> {{0, max}, All},
AxesLabel -> {"x", "y[x]"}]]
NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1}, y, {x, 0, max},
EvaluationMonitor :> {AppendTo[lst, {x, y[x]}]; Pause[0.01]}]
I was thinking of a way to access the partially build list by Sow and just use that to refresh the plot, on the assumption that might be more efficient than AppendTo[]
I can't just do this:
ClearAll[x, y, lst];
max = 30;
lst = {{0, 0}};
Dynamic[ListPlot[lst, Joined -> False, PlotRange -> All]]
NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1}, y, {x, 0, max},
EvaluationMonitor :> {lst = Reap[Sow[{x, y[x]}] ][[2, 1]]; Pause[0.01]}]
Since it now Sow one point, and Reap it, so I am just plotting one point at a time. The same as if I just did:
NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1}, y, {x, 0, max},
EvaluationMonitor :> {lst = Sow[{x, y[x]}]; Pause[0.01]}]
my question is, how to use Sow/Reap in the above, to avoid me having manage the lst by the use of AppendTo in this case. (or by pre-allocation using Table, but then I would not know the size to allocate) Since I assume that may be Sow/Reap would be more efficient?
ps. What would be nice, if Reap had an option to tell it to Reap what has been accumulated by Sow, but do not remove it from what has been Sow'ed so far. Like a passive Reap sort of. Well, just a thought.
thanks
Update: 8:30 am
Thanks for the answers and comments. I just wanted to say, that the main goal of asking this was just to see if there is a way to access part of the data while being Sowed. I need to look more at Bag, I have not used that before.
Btw, The example shown above, was just to give a context to where such a need might appear. If I wanted to simulate the solution in this specific case, I do not even have to do it as I did, I could obtain the solution data first, then, afterwords, animate it.
Hence no need to even worry about allocation of a buffer myself, or use AppenedTo. But there could many other cases where it will be easier to access the data as it is being accumulated by Sow. This example is just what I had at the moment.
To do this specific example more directly, one can simply used Animate[], afterwords, like this:
Remove["Global`*"];
max = 30;
sol = Reap[
First#NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1},
y, {x, 0, max}, EvaluationMonitor :> Sow[{x, y[x]}]]][[2, 1]];
Animate[ListPlot[sol[[1 ;; idx]], Joined -> False,
PlotRange -> {{0, max}, All}, AxesLabel -> {"x", "y[x]"}], {idx, 1,
Length[sol], 1}]
Or, even make a home grown animate, like this
Remove["Global`*"];
max = 30;
sol = Reap[
First#NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1},
y, {x, 0, max}, EvaluationMonitor :> Sow[{x, y[x]}]]][[2, 1]];
idx = 1;
Dynamic[idx];
Dynamic[ListPlot[sol[[1 ;; idx]], Joined -> False,
PlotRange -> {{0, max}, All}, AxesLabel -> {"x", "y[x]"}]]
Do[++idx; Pause[0.01], {i, 1, Length[sol] - 1}]
Small follow up question: Can one depend on using Internal``Bag now? Since it is in Internal context, will there be a chance it might be removed/changed/etc... in the future, breaking some code? I seems to remember reading somewhere that this is not likely, but I do not feel comfortable using something in Internal Context. If it is Ok for us to use it, why is it in Internal context then?
(so many things to lean in Mathematica, so little time)
Thanks,
Experimentation shows that both Internal`Bag and linked lists are slower than using AppendTo. After considering this I recalled what Sasha told me, which is that list (array) creation is what takes time.
Therefore, neither method above, nor a Sow/Reap in which the result is collected as a list at each step is going to be more efficient (in fact, less) than AppendTo.
I believe that only array pre-allocation can be faster among the native Mathematica constructs.
Old answer below for reference:
I believe this is the place for Internal`Bag, Internal`StuffBag, and Internal`BagPart.
I had to resort to a clumsy double variable method because the Bag does not seem to update inside Dynamic the way I expected.
ClearAll[x, y, lst];
max = 30;
bag = Internal`Bag[];
lst = {{}};
Dynamic#ListPlot[lst, Joined -> False, PlotRange -> All]
NDSolve[{y'[x] == y[x] Cos[x + y[x]], y[0] == 1}, y, {x, 0, max},
EvaluationMonitor :> {Internal`StuffBag[bag, {x, y[x]}];
lst = Internal`BagPart[bag, All];
Pause[0.01]}
]

Update Manipulate[]'d plots when parameters change

I've been fighting with Mathematica's Manipulate function for the last few days for a project.
I'm working on tweaking assumptions and boundary conditions that go into a physical model. For this, I want to be able to plot different equations and adjust the parameters and have the graphs update on the fly. Manipulate seems to be the perfect tool for the job -- except that I can't get it to work. The plots won't update when the parameters are changed.
Basic example:
a =.;
b =.;
c =.;
func1[x_] := a*x;
func2[x_] := a*x^2 + b*x + c;
funcNamesList := {"Linear", "Quadratic"};
funcList := {func1[x], func2[x]}
Manipulate[
Plot[function, {x, -5, 5}], {function,MapThread[Function[#1 -> #2],
{funcList, funcNamesList}]}, {a, -5, 5}, {b, -5, 5}, {c, -5, 5},
LocalizeVariables -> False
]
I can get, for example, func1 to refresh by clicking func1, adjusting a, and then clickingfunc1 again, but I'm hoping to have it update when I adjust a because the real functions I'm using are rather temperamental with respect to their parameters.
-Because I'll be dealing with long functions that have different parameters, using a list of functions is useful.
EDIT:
In case it produces any ideas for anyone, here are some working examples of the individual components of what I want to do (from the Wolfram documentation):
Plot graphs and have them update when parameters are changed:
Manipulate[
Plot[Sin[a x + b], {x, 0, 6}], {{a, 2, "Multiplier"}, 1, 4},
{{b, 0, "Phase Parameter"}, 0, 10}
]
Note: This breaks when the function is taken outside:
func[x] := Sin[a x + b];
Manipulate[
Plot[func[x], {x, 0, 6}], {{a, 2, "Multiplier"}, 1, 4},
{{b, 0, "Phase Parameter"}, 0, 10}, LocalizeVariables -> False
]
Example of changing the function being plotted:
Manipulate[
Plot[f[x], {x, 0, 2 Pi}], {f, {Sin -> "sine", Cos -> "cosine", Tan -> "tangent"}}
]
Edit 2
Changed func2 from a*x^2 to a*x^2 + b*x + c to reflect the fact that the functions may have different parameters.
Edit 3 Added the tidbit I use to get nice names on the function buttons.
There are two problems that prevent your Manipulate statement from working.
First, while the Manipulate variable a is global due to the LocalizeVariables -> False setting, the Plot variable x is not. x is local to the Plot expression.
The second problem is that Manipulate, by default, assumes TrackedSymbols -> Full. This means that only symbols that explicitly appear in the manipulated expression are tracked. Note that a does not appear in the expression, so it is not tracked.
We can correct both problems thus:
a =.;
function =.;
func1[x_] := a*x;
func2[x_] := a*x^2;
funcList := {func1, func2}
Manipulate[
Plot[function[x], {x, -5, 5}], {function, funcList}, {a, -5, 5},
LocalizeVariables -> False, TrackedSymbols :> {a, function}
]
The changes are:
funcList was changed to {func1, func2}
The Plot expression was changed to function[x], thereby referencing the local x variable.
The Manipulate option TrackedSymbols :> {a, function} was added.
function is initially unset.
I'd do this in a slightly different way:
func1[x_, a_] := a*x;
func2[x_, a_] := a*x^2;
funcList = {func1, func2};
Manipulate[
Plot[Evaluate[function[x, b]],
{x, -5, 5},
PlotLabel \[Rule] funcList
],
{function, funcList},
{b, -5, 5}
]
but this may be unsuitable for what you want. Do your functions have different signatures?
EDIT: I've renamed the parameter to b to make it clearer that is it just a parameter being passed, as opposed to a global variable as you were using it.

repeat a function n times in Mathematica

I want to repeat a function n times on a table, For n=2 I have the following code, How can I be sure that the function had run twice since my fc is differend every time?
smat = Table[{9, 8, 10}, {3}]
f[x_?Table] := ReplacePart[
x, {{2, 1} -> x[[2]][[1]] - #, {2, 2} -> x[[2]][[2]] + #}] &# fc[x[[2]][[1]]];
fc[k_?NumericQ] := Count[RandomReal[{0, 1}, k], x_ /; x < .1]
Nest[f, smat, 2]
This is probably what you want:
smat = Table[{9, 8, 10}, {3}]
ClearAll[f, fc];
f[x_List] :=
ReplacePart[
x, {{2, 1} -> x[[2]][[1]] - #, {2, 2} -> x[[2]][[2]] + #}] &#
fc[x[[2]][[1]]];
fc[k_?NumericQ] := Count[RandomReal[{0, 1}, k], x_ /; x < .1]
Nest[f, smat, 2]
ClearAll clears any previous definitions for those symbols (just in case). f[x_?Table] won't work; you want f[x_List], which means that the argument has a List head (Table is not a Head, and ? isn't what you want here).
I am not sure I have really answered your question though...
EDIT: To be clear, f[x_?something] means "apply something to x and, if it returns True, evaluate the right hand side of the := that follows. Look up PatternTest in Mathematica's documentation for more.
Acl covered the problems with the code pretty well, so I won't. To answer your question, though, I'd first separate your functions f and fc in separate cells, with fc being declared prior to f, and preface each cell with Clear[<function name>]. Now, to test if f is being applied twice, temporarily replace fc with
fc[_]:= a
or use another "dummy" value other than a, but it should be symbolic to increase readability. As a point of note, {1,2,3} + a == {1 + a, 2 + a, 3 + a}, so if f is applied twice, each term in x[[2]][[1]] and x[[2]][[2]] will have 2 a added to it.
Now, if you are unsure if fc is working correctly by itself, I'd apply it to a number separate cases without f, first.

Aggregating Tally counters

Many times I find myself counting occurrences with Tally[ ] and then, once I discarded the original list, having to add (and join) to that counters list the results from another list.
This typically happens when I am counting configurations, occurrences, doing some discrete statistics, etc.
So I defined a very simple but handy function for Tally aggregation:
aggTally[listUnTallied__List:{},
listUnTallied1_List,
listTallied_List] :=
Join[Tally#Join[listUnTallied, listUnTallied1], listTallied] //.
{a___, {x_, p_}, b___, {x_, q_}, c___} -> {a, {x, p + q}, b, c};
Such that
l = {x, y, z}; lt = Tally#l;
n = {x};
m = {x, y, t};
aggTally[n, {}]
{{x, 1}}
aggTally[m, n, {}]
{{x, 2}, {y, 1}, {t, 1}}
aggTally[m, n, lt]
{{x, 3}, {y, 2}, {t, 1}, {z, 1}}
This function has two problems:
1) Performance
Timing[Fold[aggTally[Range##2, #1] &, {}, Range[100]];]
{23.656, Null}
(* functional equivalent to *)
Timing[s = {}; j = 1; While[j < 100, s = aggTally[Range#j, s]; j++]]
{23.047, Null}
2) It does not validate that the last argument is a real Tallied list or null (less important for me, though)
Is there a simple, elegant, faster and more effective solution? (I understand that these are too many requirements, but wishing is free)
Perhaps, this will suit your needs?
aggTallyAlt[listUnTallied__List : {}, listUnTallied1_List, listTallied : {{_, _Integer} ...}] :=
{#[[1, 1]], Total##[[All, 2]]} & /#
GatherBy[Join[Tally#Join[listUnTallied, listUnTallied1], listTallied], First]
The timings are much better, and there is a pattern-based check on the last arg.
EDIT:
Here is a faster version:
aggTallyAlt1[listUnTallied__List : {}, listUnTallied1_List, listTallied : {{_, _Integer} ...}] :=
Transpose[{#[[All, 1, 1]], Total[#[[All, All, 2]], {2}]}] &#
GatherBy[Join[Tally#Join[listUnTallied, listUnTallied1], listTallied], First]
The timings for it:
In[39]:= Timing[Fold[aggTallyAlt1[Range##2, #1] &, {}, Range[100]];]
Timing[s = {}; j = 1; While[j < 100, s = aggTallyAlt1[Range#j, s]; j++]]
Out[39]= {0.015, Null}
Out[40]= {0.016, Null}
The following solution is just a small modification of your original function. It applies Sort before using ReplaceRepeated and can thus use a less general replacement pattern which makes it much faster:
aggTally[listUnTallied__List : {}, listUnTallied1_List,
listTallied : {{_, _Integer} ...}] :=
Sort[Join[Tally#Join[listUnTallied, listUnTallied1],
listTallied]] //. {a___, {x_, p_}, {x_, q_}, c___} -> {a, {x, p + q}, c};
Here's the fastest thing I've come up with yet, (ab)using the tagging available with Sow and Reap:
aggTally5[untallied___List, tallied_List: {}] :=
Last[Reap[
Scan[((Sow[#2, #] &) ### Tally[#]) &, {untallied}];
Sow[#2, #] & ### tallied;
, _, {#, Total[#2]} &]]
Not going to win any beauty contests, but it's all about speed, right? =)
If you stay purely symbolic, you may try something along the lines of
(Plus ## Times ### Join[#1, #2] /. Plus -> List /. Times -> List) &
for joining tally lists. This is stupid fast but returns something that isn't a tally list, so it needs some work (after which it may not be so fast anymore ;) ).
EDIT: So I've got a working version:
aggT = Replace[(Plus ## Times ### Join[#1, #2]
/. Plus -> List
/. Times[a_, b_] :> List[b, a]),
k_Symbol -> List[k, 1], {1}] &;
Using a couple of random symbolic tables I get
a := Tally#b;
b := Table[f[RandomInteger#99 + 1], {i, 100}];
Timing[Fold[aggT[#1, #2] &, a, Table[a, {i, 100}]];]
--> {0.104954, Null}
This version only adds tally lists, doesn't check anything, still returns some integers, and comparing to Leonid's function:
Timing[Fold[aggTallyAlt1[#2, #1] &, a, Table[b, {i, 100}]];]
--> {0.087039, Null}
it's already a couple of seconds slower :-(.
Oh well, nice try.

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