Mathematica 8's DictionaryLookup function uses "English" as the language by default. Is there any way to set the default language to "BritishEnglish" or "Spanish"?
Thanks in advance.
There does not appear to be an option for this, but you can modify the definition of DictionaryLookup to suit you.
The method I will use relies on the automatic ordering of DownValues and was written for version 7 so it may need adjustment. You can look at DownValues[DictionaryLookup] to see how the function is written as it is top-level Mathematica code.
$dictionaryLanguage = "Spanish";
Unprotect[DictionaryLookup];
DictionaryLookup[pat : Except[_List], x___] /;
! TrueQ[$dicLang] && ValueQ[$dictionaryLanguage] :=
Block[{$dicLang = True},
DictionaryLookup[{$dictionaryLanguage, pat}, x]
]
DownValues[DictionaryLookup] =
RotateRight # DownValues[DictionaryLookup];
Protect[DictionaryLookup];
With this definition, if $dictionaryLanguage is set that value will be used for the language. You can restore default behavior with $dictionaryLanguage =.. Examples:
$dictionaryLanguage = "Spanish";
DictionaryLookup["*orac*", 3]
{"adoración", "aminoración", "colaboración"}
$dictionaryLanguage =.;
DictionaryLookup["*orac*", 3]
{"coracle", "coracles", "Horace"}
Know that you call also do look-ups outside of DictionaryLookup. You can load the dictionary for a language like this:
DataPaclets`Dictionary`ReloadDictionary["Dutch"]
Which places the data in DataPaclets`Dictionary`$Dictionary. An example search:
Pick[#, # ~StringMatchQ~ "*fzand*"] ~Take~ 4 & # DataPaclets`Dictionary`$Dictionary
{"afzand", "afzandde", "afzandden", "afzanderij"}
The equivalent DictionaryLookup query:
DictionaryLookup[{"Dutch", "*fzand*"}, 4]
{"afzand", "afzandde", "afzandden", "afzanderij"}
If you use these tools often you could them in the context path with:
AppendTo[$ContextPath, "DataPaclets`Dictionary`"]
Then you could use ReloadDictionary and $Dictionary as is, without the context name.
Related
I want to make mathematica insensitive to the functions first capital letter. For example, it accepts both "Plot" and "plot" as plotting function.
I agree with george's sentiment: "You don't want to do that." It is common practice to start user Symbols with lowercase letters which both identifies them and prevents collisions with built-ins. Nevertheless you can do this in several ways. One is just to create aliases as george also suggested, e.g.
plot = Plot;
sin = Sin;
plot[sin[x], {x, 0, 6}]
This has the advantage of working even in packages because it does not rely on the Front End. However, because these are not true aliases it will fail in some cases, e.g.:
evaluate = Evaluate;
Hold[evaluate[2 + 2]]
Hold[evaluate[2 + 2]]
Whereas the "real" function behaves like this:
Hold[Evaluate[2 + 2]]
Hold[4]
To get complete equivalence, though only in the Front End, you can use $PreRead. (Example.) You will need to build a list of rules that replace the string form of each lowercase Symbol with the uppercase string. I shall do that only for all Symbols in the System` context.
With[{rules = Thread[ToLowerCase[#] -> #] & # Names["System`*"]},
$PreRead = # /. rules &
];
Now both of these examples work:
plot[sin[x], {x, 0, 6}]
hold[evaluate[2 + 2], 3 + 4]
The latter producing:
Hold[4, 3 + 4]
This is not a direct answer to your question and I strongly advise you against redefining Mathematica functions just for the sake of the letter-case.
Nevertheless, have you seen that there is an option Match case in command completion when you go to Edit -> Preferences -> Interface?
If you turn this off, then you can type plot in the notebook and you get the correct Plot as suggestion from the autocompletion. You only have to hit enter and the correct command is inserted.
I am looking for a general-purpose way of defining textual expressions which allow a value to be validated.
For example, I have a value which should only be set to 1, 2, 3, 10, 11, or 12.
Its constraint might be defined as: (value >= 1 && value <= 3) || (value >= 10 && value <= 12)
Or another value which can be 1, 3, 5, 7, 9 etc... would have a constraint like value % 2 == 1 or IsOdd(value).
(To help the user correct invalid values, I'd like to show the constraint - so something descriptive like IsOdd is preferable.)
These constraints would be evaluated both on client-side (after user input) and server-side.
Therefore a multi-platform solution would be ideal (specifically Win C#/Linux C++).
Is there an existing language/project which allows evaluation or parsing of similar simple expressions?
If not, where might I start creating my own?
I realise this question is somewhat vague as I am not entirely sure what I am after. Searching turned up no results, so even some terms as a starting point would be helpful. I can then update/tag the question accordingly.
You may want to investigate dependently typed languages like Idris or Agda.
The type system of such languages allows encoding of value constraints in types. Programs that cannot guarantee the constraints will simply not compile. The usual example is that of matrix multiplication, where the dimensions must match. But this is so to speak the "hello world" of dependently typed languages, the type system can do much more for you.
If you end up starting your own language I'd try to stay implementation-independent as long as possible. Look for the formal expression grammars of a suitable programming language (e.g. C) and add special keywords/functions as required. Once you have a formal definition of your language, implement a parser using your favourite parser generator.
That way, even if your parser is not portable to a certain platform you at least have a formal standard from where to start a separate parser implementation.
You may also want to look at creating a Domain Specific Language (DSL) in Ruby. (Here's a good article on what that means and what it would look like: http://jroller.com/rolsen/entry/building_a_dsl_in_ruby)
This would definitely give you the portability you're looking for, including maybe using IronRuby in your C# environment, and you'd be able to leverage the existing logic and mathematical operations of Ruby. You could then have constraint definition files that looked like this:
constrain 'wakeup_time' do
6 <= value && value <= 10
end
constrain 'something_else' do
check (value % 2 == 1), MustBeOdd
end
# constrain is a method that takes one argument and a code block
# check is a function you've defined that takes a two arguments
# MustBeOdd is the name of an exception type you've created in your standard set
But really, the great thing about a DSL is that you have a lot of control over what the constraint files look like.
there are a number of ways to verify a list of values across multiple languages. My preferred method is to make a list of the permitted values and load them into a dictionary/hashmap/list/vector (dependant on the language and your preference) and write a simple isIn() or isValid() function, that will check that the value supplied is valid based on its presence in the data structure. The beauty of this is that the code is trivial and can be implemented in just about any language very easily. for odd-only or even-only numeric validity again, a small library of different language isOdd() functions will suffice: if it isn't odd it must by definition be even (apart from 0 but then a simple exception can be set up to handle that, or you can simply specify in your code documentation that for logical purposes your code evaluates 0 as odd/even (your choice)).
I normally cart around a set of c++ and c# functions to evaluate isOdd() for similar reasons to what you have alluded to, and the code is as follows:
C++
bool isOdd( int integer ){ return (integer%2==0)?false:true; }
you can also add inline and/or fastcall to the function depending on need or preference; I tend to use it as an inline and fastcall unless there is a need to do otherwise (huge performance boost on xeon processors).
C#
Beautifully the same line works in C# just add static to the front if it is not going to be part of another class:
static bool isOdd( int integer ){ return (integer%2==0)?false:true; }
Hope this helps, in any event let me know if you need any further info:)
Not sure if it's what you looking for, but judging from your starting conditions (Win C#/Linux C++) you may not need it to be totally language agnostic. You can implement such a parser yourself in C++ with all the desired features and then just use it in both C++ and C# projects - thus also bypassing the need to add external libraries.
On application design level, it would be (relatively) simple - you create a library which is buildable cross-platform and use it in both projects. The interface may be something simple like:
bool VerifyConstraint_int(int value, const char* constraint);
bool VerifyConstraint_double(double value, const char* constraint);
// etc
Such interface will be usable both in Linux C++ (by static or dynamic linking) and in Windows C# (using P/Invoke). You can have same codebase compiling on both platforms.
The parser (again, judging from what you've described in the question) may be pretty simple - a tree holding elements of types Variable and Expression which can be Evaluated with a given Variable value.
Example class definitions:
class Entity {public: virtual VARIANT Evaluate() = 0;} // boost::variant may be used typedef'd as VARIANT
class BinaryOperation: public Entity {
private:
Entity& left;
Entity& right;
enum Operation {PLUS,MINUS,EQUALS,AND,OR,GREATER_OR_EQUALS,LESS_OR_EQUALS};
public:
virtual VARIANT Evaluate() override; // Evaluates left and right operands and combines them
}
class Variable: public Entity {
private:
VARIANT value;
public:
virtual VARIANT Evaluate() override {return value;};
}
Or, you can just write validation code in C++ and use it both in C# and C++ applications :)
My personal choice would be Lua. The downside to any DSL is the learning curve of a new language and how to glue the code with the scripts but I've found Lua has lots of support from the user base and several good books to help you learn.
If you are after making somewhat generic code that a non programmer can inject rules for allowable input it's going to take some upfront work regardless of the route you take. I highly suggest not rolling your own because you'll likely find people wanting more features that an already made DSL will have.
If you are using Java then you can use the Object Graph Navigation Library.
It enables you to write java applications that can parse,compile and evaluate OGNL expressions.
OGNL expressions include basic java,C,C++,C# expressions.
You can compile an expression that uses some variables, and then evaluate that expression
for some given variables.
An easy way to achieve validation of expressions is to use Python's eval method. It can be used to evaluate expressions just like the one you wrote. Python's syntax is easy enough to learn for simple expressions and english-like. Your expression example is translated to:
(value >= 1 and value <= 3) or (value >= 10 and value <= 12)
Code evaluation provided by users might pose a security risk though as certain functions could be used to be executed on the host machine (such as the open function, to open a file). But the eval function takes extra arguments to restrict the allowed functions. Hence you can create a safe evaluation environment.
# Import math functions, and we'll use a few of them to create
# a list of safe functions from the math module to be used by eval.
from math import *
# A user-defined method won't be reachable in the evaluation, as long
# as we provide the list of allowed functions and vars to eval.
def dangerous_function(filename):
print open(filename).read()
# We're building the list of safe functions to use by eval:
safe_list = ['math','acos', 'asin', 'atan', 'atan2', 'ceil', 'cos', 'cosh', 'degrees', 'e', 'exp', 'fabs', 'floor', 'fmod', 'frexp', 'hypot', 'ldexp', 'log', 'log10', 'modf', 'pi', 'pow', 'radians', 'sin', 'sinh', 'sqrt', 'tan', 'tanh']
safe_dict = dict([ (k, locals().get(k, None)) for k in safe_list ])
# Let's test the eval method with your example:
exp = "(value >= 1 and value <= 3) or (value >= 10 and value <= 12)"
safe_dict['value'] = 2
print "expression evaluation: ", eval(exp, {"__builtins__":None},safe_dict)
-> expression evaluation: True
# Test with a forbidden method, such as 'abs'
exp = raw_input("type an expression: ")
-> type an expression: (abs(-2) >= 1 and abs(-2) <= 3) or (abs(-2) >= 10 and abs(-2) <= 12)
print "expression evaluation: ", eval(exp, {"__builtins__":None},safe_dict)
-> expression evaluation:
-> Traceback (most recent call last):
-> File "<stdin>", line 1, in <module>
-> File "<string>", line 1, in <module>
-> NameError: name 'abs' is not defined
# Let's test it again, without any extra parameters to the eval method
# that would prevent its execution
print "expression evaluation: ", eval(exp)
-> expression evaluation: True
# Works fine without the safe dict! So the restrictions were active
# in the previous example..
# is odd?
def isodd(x): return bool(x & 1)
safe_dict['isodd'] = isodd
print "expression evaluation: ", eval("isodd(7)", {"__builtins__":None},safe_dict)
-> expression evaluation: True
print "expression evaluation: ", eval("isodd(42)", {"__builtins__":None},safe_dict)
-> expression evaluation: False
# A bit more complex this time, let's ask the user a function:
user_func = raw_input("type a function: y = ")
-> type a function: y = exp(x)
# Let's test it:
for x in range(1,10):
# add x in the safe dict
safe_dict['x']=x
print "x = ", x , ", y = ", eval(user_func,{"__builtins__":None},safe_dict)
-> x = 1 , y = 2.71828182846
-> x = 2 , y = 7.38905609893
-> x = 3 , y = 20.0855369232
-> x = 4 , y = 54.5981500331
-> x = 5 , y = 148.413159103
-> x = 6 , y = 403.428793493
-> x = 7 , y = 1096.63315843
-> x = 8 , y = 2980.95798704
-> x = 9 , y = 8103.08392758
So you can control the allowed functions that should be used by the eval method, and have a sandbox environment that can evaluate expressions.
This is what we used in a previous project I worked in. We used Python expressions in custom Eclipse IDE plug-ins, using Jython to run in the JVM. You could do the same with IronPython to run in the CLR.
The examples I used in part inspired / copied from the Lybniz project explanation on how to run a safe Python eval environment. Read it for more details!
You might want to look at Regular-Expressions or RegEx. It's proven and been around for a long time. There's a regex library all the major programming/script languages out there.
Libraries:
C++: what regex library should I use?
C# Regex Class
Usage
Regex Email validation
Regex to validate date format dd/mm/yyyy
What is the best way to define a numerical constant in Mathematica?
For example, say I want g to be the approximate acceleration due to gravity on the surface of the Earth. I give it a numerical value (in m/s^2), tell Mathematica it's numeric, positive and a constant using
Unprotect[g];
ClearAll[g]
N[g] = 9.81;
NumericQ[g] ^= True;
Positive[g] ^= True;
SetAttributes[g, Constant];
Protect[g];
Then I can use it as a symbol in symbolic calculations that will automatically evaluate to 9.81 when numerical results are called for. For example 1.0 g evaluates to 9.81.
This does not seem as well tied into Mathematica as built in numerical constants. For example Pi > 0 will evaluate to True, but g > 0 will not. (I could add g > 0 to the global $Assumptions but even then I need a call to Simplify for it to take effect.)
Also, Positive[g] returns True, but Positive[g^2] does not evaluate - compare this with the equivalent statements using Pi.
So my question is, what else should I do to define a numerical constant? What other attributes/properties can be set? Is there an easier way to go about this? Etc...
I'd recommend using a zero-argument "function". That way it can be given both the NumericFunction attribute and a numeric evaluation rule. that latter is important for predicates such as Positive.
SetAttributes[gravUnit, NumericFunction]
N[gravUnit[], prec_: $MachinePrecision] := N[981/100, prec]
In[121]:= NumericQ[gravitUnit[]]
Out[121]= True
In[122]:= Positive[gravUnit[]^2 - 30]
Out[122]= True
Daniel Lichtblau
May be I am naive, but to my mind your definitions are a good start. Things like g > 0->True can be added via UpValues. For Positive[g^2] to return True, you probably have to overload Positive, because of the depth-1 limitation for UpValues. Generally, I think the exact set of auto-evaluated expressions involving a constant is a moving target, even for built-in constants. In other words, those extra built-in rules seem to be determined from convenience and frequent uses, on a case-by-case basis, rather than from the first principles. I would just add new rules as you go, whenever you feel that you need them. You probably can not expect your constants to be as well integrated in the system as built-ins, but I think you can get pretty close. You will probably have to overload a number of built-in functions on these symbols, but again, which ones those will be, will depend on what you need from your symbol.
EDIT
I was hesitating to include this, since the code below is a hack, but it may be useful in some circumstances. Here is the code:
Clear[evalFunction];
evalFunction[fun_Symbol, HoldComplete[sym_Symbol]] := False;
Clear[defineAutoNValue];
defineAutoNValue[s_Symbol] :=
Module[{inSUpValue},
s /: expr : f_[left___, s, right___] :=
Block[{inSUpValue = True},
With[{stack = Stack[_]},
If[
expr === Unevaluated[expr] &&
(evalFunction[f, HoldComplete[s]] ||
MemberQ[
stack,
HoldForm[(op_Symbol /; evalFunction[op, HoldComplete[s]])
[___, x_ /; ! FreeQ[Unevaluated[x], HoldPattern#expr], ___]],
Infinity
]
),
f[left, N[s], right],
(* else *)
expr
]]] /; ! TrueQ[inSUpValue]];
ClearAll[substituteNumeric];
SetAttributes[substituteNumeric, HoldFirst];
substituteNumeric[code_, rules : {(_Symbol :> {__Symbol}) ..}] :=
Internal`InheritedBlock[{evalFunction},
MapThread[
Map[Function[f, evalFunction[f, HoldComplete[#]] = True], #2] &,
Transpose[List ### rules]
];
code]
With this, you may enable a symbol to auto-substitute its numerical value in places where we indicate some some functions surrounding those function calls may benefit from it. Here is an example:
ClearAll[g, f];
SetAttributes[g, Constant];
N[g] = 9.81;
NumericQ[g] ^= True;
defineAutoNValue[g];
f[g] := "Do something with g";
Here we will try to compute some expressions involving g, first normally:
In[391]:= {f[g],g^2,g^2>0, 2 g, Positive[2 g+1],Positive[2g-a],g^2+a^2,g^2+a^2>0,g<0,g^2+a^2<0}
Out[391]= {Do something with g,g^2,g^2>0,2 g,Positive[1+2 g],
Positive[-a+2 g],a^2+g^2,a^2+g^2>0,g<0,a^2+g^2<0}
And now inside our wrapper (the second argument gives a list of rules, to indicate for which symbols which functions, when wrapped around the code containing those symbols, should lead to those symbols being replaced with their numerical values):
In[392]:=
substituteNumeric[{f[g],g^2,g^2>0, 2 g, Positive[2 g+1],Positive[2g-a],g^2+a^2,g^2+a^2>0,
g<0,g^2+a^2<0},
{g:>{Positive,Negative,Greater}}]
Out[392]= {Do something with g,g^2,True,2 g,True,Positive[19.62\[VeryThinSpace]-a],
a^2+g^2,96.2361\[VeryThinSpace]+a^2>0,g<0,a^2+g^2<0}
Since the above is a hack, I can not guarantee anything about it. It may be useful in some cases, but that must be decided on a case-by-case basis.
You may want to consider working with units rather than just constants. There are a few options available in Mathematica
Units
Automatic Units
Designer units
There are quite a few technical issues and subtleties about working with units. I found the backgrounder at Designer Units very useful. There are also some interesting discussions on MathGroup. (e.g. here).
Mathematica provides many functions which are capable of handling Dynamic as an argument.
For example, the function FileNameSetter has the following variant:
FileNameSetter[Dynamic[name]]
uses the dynamically updated current value of name, with the
value of name being reset if a different file is chosen.
I wonder how one goes about defining a function pattern that takes a dynamic expression as an argument. For example, here is one attempt to wrap the dynamic variant of the function LocatorPane:
SinLocatorPane[Dynamic[sinvalue_]] :=
LocatorPane[Dynamic[x, (x = #; sinvalue = Sin[First[#]]) &],
Plot[Sin[x], {x, 0, 10}]]
What is the correct pattern to use for a dynamic expression argument? Are there any caveats with using the dynamic argument inside the function definition?
If you would like to write a function that updates the value of a certain variable, this is like passing a variable by reference. Standard way of achieving this in Mathematica is to use Hold* attributes on your function.
SetAttributes[SinLocatorPane, HoldFirst];
SinLocatorPane[sinvalue_] :=
LocatorPane[Dynamic[x, (x = #; sinvalue = Sin[First[#]]) &],
Plot[Sin[x], {x, 0, 10}]]
Then
{Dynamic[sv], SinLocatorPane[sv]}
would work as your expected. Your code worked because Dynamic has HoldFirst attributed and this allowed your code to update variable sinvalue. Otherwise Dynamic was not really needed
Is it possible to use Mathematica's manipulate to change variables that have already been declared?
Example:
changeme = 8;
p = SomeSortOfPlot[changeme];
manipulate[Show[p],{changeme,1,10}]
The basic idea is that I want to make a plot with a certain changable value but declare it outside of manipulate.
Any ideas?
One option is to use Dynamic[] and LocalizeVariables -> False.
Example:
changeme = 8;
p[x_] := Plot[Sin[t], {t, 1, x}];
{
Manipulate[p[changeme], {changeme, 2, 9}, LocalizeVariables -> False],
Dynamic[changeme] (* This line is NOT needed, inserted just to see the value *)
}
Evaluating "changeme" after the Manipulate action will retain the last Manipulate value.
HTH!
If you want anything reasonably complicated or flexible, it is best to use Dynamic and DynamicModule instead of Manipulate. The only exception is if you're writing a demonstration.
For example - a very basic way of doing what you want is
(in fact you don't even need the Row and Slider if you want to just change changeme by hand.)
changeme=8;
p[x_]:=Plot[Sin[t],{t,1,x}];
Row[{"x \[Element] (1, ",Dynamic[changeme],") ",Slider[Dynamic[changeme],{2,9}]}]
Dynamic[p[changeme]]