I am plowing TCL source code and get confused at macro NEXT_INST_F and NEXT_INST_V in tclExecute.c. Specifically the cleanup parameter of the macro.
Initially I thought cleanup means the net number of slots consumed/popped from the stack, e.g. when 3 objects are popped out and 1 object pushed in, cleanup is 2.
But I see INST_LOAD_STK has cleanup set to 1, shouldn't it be zero since one object is popped out and 1 object is pushed in?
I am lost reading the code of NEXT_INST_F and NEXT_INST_V, there are too many jumps.
Hope you can clarify the semantic of cleanup for me.
The NEXT_INST_F and NEXT_INST_V macros (in the implementation of Tcl's bytecode engine) clean up the state of the operand stack and push the result of the operation before going to the next instruction. The only practical difference between the two is that one is designed to be highly efficient when the number of stack locations to be cleaned up is a constant number (from a small range: 0, 1 and 2 — this is the overwhelming majority of cases), and the other is less efficient but can handle a variable number of locations to clean up or a number outside the small range. So NEXT_INST_F is basically an optimised version of NEXT_INST_V.
The place where macros are declared in tclExecute.c has this to say about them:
/*
* The new macro for ending an instruction; note that a reasonable C-optimiser
* will resolve all branches at compile time. (result) is always a constant;
* the macro NEXT_INST_F handles constant (nCleanup), NEXT_INST_V is resolved
* at runtime for variable (nCleanup).
*
* ARGUMENTS:
* pcAdjustment: how much to increment pc
* nCleanup: how many objects to remove from the stack
* resultHandling: 0 indicates no object should be pushed on the stack;
* otherwise, push objResultPtr. If (result < 0), objResultPtr already
* has the correct reference count.
*
* We use the new compile-time assertions to check that nCleanup is constant
* and within range.
*/
However, instructions can also directly manipulate the stack. This complicates things quite a lot. Most don't, but that's not the same as all. If you were to view this particular load of code as one enormous pile of special cases, you'd not be very wrong.
INST_LOAD_STK (a.k.a loadStk if you're reading disassembly of some Tcl code) is an operation that will pop an unparsed variable name from the stack and push the value read from the variable with that name. (Or an error will be thrown.) It is totally expected to pop one value and push another (from objResultPtr) since we are popping (and decrementing the reference count) of the variable name value, and pushing and incrementing the reference count of a different value that was read from the variable.
The code to read and write variables is among the most twisty in the bytecode engine. Far more goto than is good for your health.
I was reading up on the std::string class in C++ and noticed there are quite a few different constructors available giving us a wide set of initialization features. This got me wondering how a compiler picks which constructor to choose when given parameters, or in the case of overloads, how a compiler matches a function signature with a given set of parameters.
If we have the following functions declared in pseudo-code:
function f1(int numberHere) {
//....do something
}
function f1(int numberHere, string stringHere) {
//....do something
}
And I decide to call f1(4), there are obviously two options to choose from, but what if there are 10000 options/signatures? Would it take proportionally longer? If so, what takes longer? Does the compiler have some sneaky O(n) way to index overloads such that it can call the right one in O(1) time once the program is running or would it compile in O(1) no matter how many overloads exist but take longer to run the finished result because of on-the-fly signature matching?
Can this question even be answered effectively?
Thanks!
Matching function signatures is actually not different from any other search or lookup problem. There are three basic ways to do it depending on the data structure you are storing the available function signatures in:
Use an unsorted list or array and get O(n) time complexity.
Use a sorted array or a tree-like structure and get O(log(n)). (You can sort by type of 1st argument, then 2nd and so on, assuming that each type has an integer id assigned to it.)
Use a hash map and get O(1).
But I doubt that time complxity has any practical relevance in this case. It describes the asymptotic behaviour of algorithms for large values of n. Even for n=100, an unsorted array search might be faster than hash map lookup because it has less overhead.
And from a usability point of view it is a very bad idea to design an API having functions with 10 or even 100 overloads.
The question
What are the ways of coercing octave to create a real copy of whatever object? Structures are the main interest.
My underlying problem
In my problem I'm obtaining a rather large structure from another function in a loop but for the current task only a few pieces of it are needed. For example:
for i=1:many
res=solver(params);
store1{i}=res.string1;
store2{i}=res.arr(:,1);
end
res is a sizable chunk of data and due to lazy-copy those store-s are references to tiny portions of bytes in that chunk. After I store those tiny portions, I don't need res itself, however, since middle of that chunk is referenced by store, the memory area is unfit for res obtained on the next iteration (they are of the same size) and thus another sizable piece of memory is allocated, which is then again crossed by few tiny links an so on.
Without storing parts of res, the program successfully keeps the memory consumption same after first couple of iterations.
So how do I make a complete copy of structure field?
I've tried using struct-related functions like rmfield but those keep references instead of their own objects.
I've tried to wrap the assignment of in its own function:
new_struct=copy( rmfield(old_struct,"bigdata"));
function c=copy(a);
c=a;
end;
This by the way doesn't work even for arrays.
I'm interested in method applicable to any generic variable.
Minimal working example of the problem
a=cell(3,1);
for i=1:length(a);
r=rand(100000,1000);
a{i}=r(1:100,end);
whos; fflush(stdout);
pause(2);
end;
The above code will cause memory usage to gradually grow by far more than 8.08 kb reported by whos due to references stored by a{i} blocking bigger memory block than they actually need. If you force the proper copy, the problem is not present.
Numerical arrays
For numeric types addition of zero is enough to warrant a new array.
c=a+0;
Strings
For string which is 1 x n char array, something along the following lines will work:
c=[a "a"](1:end-1);
Multidimensional char arrays will require concatenation with a column:
c=[a true(size(a,1),1)](:,1:end-1);
Here true is used to generate dummy array of size compatible with char. (There seems to be no procedural method of generating char array of arbitrary size) char(zeros(size(a,1),1)) and char(true(size(a,1),1)) caused excess memory usage during their creation on some calls.
Note that empty concatenation c=[a ""]; will not result in a copying. Also it is possible to do c=[a+0 ""]; which will result in a copying due to +0 but that one infers type conversions to and from double which is 8 times larger in size. (char(zeros( doesn't seem to cause that)
Other types
In general you can use casting for the types allowed by it in order to not tailor the expressions manually as I had to do above:
typelist={"double","single","char"}; %full list of supported types is available in the link
class_of_a = typelist{ isa(a,typelist) };
c=typecast( [typecast(a,'single'); single(1)] (1:end-1), class_of_a);
Single is seemingly smallest datatype available in octave.
Note that logical is not supported by this method.
Copying structures
Apparently you'd have to write your own function to go around struct fields, copy them with above methods and recursively go to substructs.
(As it doesn't involve complexities relevant here, I'd rather leave that to be done by those who actually needs that, my own problem being solved by +0's.)
So say I have a variable, which holds a song number. -> song_no
Depending upon the value of this variable, I wish to call a function.
Say I have many different functions:
Fcn1
....
Fcn2
....
Fcn3
So for example,
If song_no = 1, call Fcn1
If song_no = 2, call Fcn2
and so forth...
How would I do this?
you should have compare function in the instruction set (the post suggests you are looking for assembly solution), the result for that is usually set a True bit or set a value in a register. But you need to check the instruction set for that.
the code should look something like:
load(song_no, $R1)
cmpeq($1,R1) //result is in R3
jmpe Fcn1 //jump if equal
cmpeq ($2,R1)
jmpe Fcn2
....
Hope this helps
I'm not well acquainted with the pic, but these sort of things are usually implemented as a jump table. In short, put pointers to the target routines in an array and call/jump to the entry indexed by your song_no. You just need to calculate the address into the array somehow, so it is very efficient. No compares necessary.
To elaborate on Jens' reply the traditional way of doing on 12/14-bit PICs is the same way you would look up constant data from ROM, except instead of returning an number with RETLW you jump forward to the desired routine with GOTO. The actual jump into the jump table is performed by adding the offset to the program counter.
Something along these lines:
movlw high(table)
movwf PCLATH
movf song_no,w
addlw table
btfsc STATUS,C
incf PCLATH
addwf PCL
table:
goto fcn1
goto fcn2
goto fcn3
.
.
.
Unfortunately there are some subtleties here.
The PIC16 only has an eight-bit accumulator while the address space to jump into is 11-bits. Therefore both a directly writable low-byte (PCL) as well as a latched high-byte PCLATH register is available. The value in the latch is applied as MSB once the jump is taken.
The jump table may cross a page, hence the manual carry into PCLATH. Omit the BTFSC/INCF if you know the table will always stay within a 256-instruction page.
The ADDWF instruction will already have been read and be pointing at table when PCL is to be added to. Therefore a 0 offset jumps to the first table entry.
Unlike the PIC18 each GOTO instruction fits in a single 14-bit instruction word and PCL addresses instructions not bytes, so the offset should not be multiplied by two.
All things considered you're probably better off searching for general PIC16 tutorials. Any of these will clearly explain how data/jump tables work, not to mention begin with the basics of how to handle the chip. Frankly it is a particularly convoluted architecture and I would advice staying with the "free" hi-tech C compiler unless you particularly enjoy logic puzzles or desperately need the performance.
The word seems to get used in a number of contexts. The best I can figure is that they mean a variable that can't change. Isn't that what constants/finals (darn you Java!) are for?
An invariant is more "conceptual" than a variable. In general, it's a property of the program state that is always true. A function or method that ensures that the invariant holds is said to maintain the invariant.
For instance, a binary search tree might have the invariant that for every node, the key of the node's left child is less than the node's own key. A correctly written insertion function for this tree will maintain that invariant.
As you can tell, that's not the sort of thing you can store in a variable: it's more a statement about the program. By figuring out what sort of invariants your program should maintain, then reviewing your code to make sure that it actually maintains those invariants, you can avoid logical errors in your code.
It is a condition you know to always be true at a particular place in your logic and can check for when debugging to work out what has gone wrong.
The magic of wikipedia: Invariant (computer science)
In computer science, a predicate that,
if true, will remain true throughout a
specific sequence of operations, is
called (an) invariant to that
sequence.
This answer is for my 5 year old kid. Do not think of an invariant as a constant or fixed numerical value. But it can be. However, it is more than that.
Rather, an invariant is something like of a fixed relationship between varying entities. For example, your age will always be less than that compared to your biological parents. Both your age, and your parent's age changes in the passage of time, but the relationship that i mentioned above is an invariant.
An invariant can also be a numerical constant. For example, the value of pi is an invariant ratio between the circle's circumference over its diameter. No matter how big or small the circle is, that ratio will always be pi.
I usually view them more in terms of algorithms or structures.
For example, you could have a loop invariant that could be asserted--always true at the beginning or end of each iteration. That is, if your loop was supposed to process a collection of objects from one stack to another, you could say that |stack1|+|stack2|=c, at the top or bottom of the loop.
If the invariant check failed, it would indicate something went wrong. In this example, it could mean that you forgot to push the processed element onto the final stack, etc.
As this line states:
In computer science, a predicate that, if true, will remain true throughout a specific sequence of operations, is called (an) invariant to that sequence.
To better understand this hope this example in C++ helps.
Consider a scenario where you have to get some values and get the total count of them in a variable called as count and add them in a variable called as sum
The invariant (again it's more like a concept):
// invariant:
// we have read count grades so far, and
// sum is the sum of the first count grades
The code for the above would be something like this,
int count=0;
double sum=0,x=0;
while (cin >> x) {
++count;
sum+=x;
}
What the above code does?
1) Reads the input from cin and puts them in x
2) After one successful read, increment count and sum = sum + x
3) Repeat 1-2 until read stops ( i.e ctrl+D)
Loop invariant:
The invariant must be True ALWAYS. So initially you start out your code with just this
while(cin>>x){
}
This loop reads data from standard input and stores in x. Well and good. But the invariant becomes false because the first part of our invariant wasn't followed (or kept true).
// we have read count grades so far, and
How to keep the invariant true?
Simple! increment count.
So ++count; would do good!. Now our code becomes something like this,
while(cin>>x){
++count;
}
But
Even now our invariant (a concept which must be TRUE) is False because now we didn't satisfy the second part of our invariant.
// sum is the sum of the first count grades
So what to do now?
Add x to sum and store it in sum ( sum+=x) and the next time
cin>>x will read a new value into x.
Now our code becomes something like this,
while(cin>>x){
++count;
sum+=x;
}
Let's check
Whether code matches our invariant
// invariant:
// we have read count grades so far, and
// sum is the sum of the first count grades
code:
while(cin>>x){
++count;
sum+=x;
}
Ah!. Now the loop invariant is True always and code works fine.
The above example was taken and modified from the book Accelerated C++ by Andrew-koening and Barbara-E
Something that doesn't change within a block of code
All the answers here are great, but i felt that i can shed more light on the matter:
Invariant from a language point of view means something that never changes. The concept though comes actually from math, it's one of the popular proof techniques when combined with induction.
Here is how a proof goes, If you can find an invariant that is in the initial state, And that this invariant persists regardless of any [legal] transformation applied to the state, then you can prove that If a certain state does not have this invariant then it can never occur, no matter what sequence of transformations are applied to the initial state.
Now the previous way of thinking (again combined with induction) makes it possible to predicate the logic of computer software. Especially important when the execution goes in loops, in which an invariant can be used to prove that a certain loop will yield a certain result or that it will never change the state of a program in a certain way.
When invariant is used to predicate a loop logic its called loop invariant. It can be used outside loops, but for loops it is really important, because you often have a lot of possibilities, or an infinite number of possibilities.
Notice that i use the word "predicate" the logic of a computer software, and not prove. And that's because while in math invariant can be used as a proof, it can never prove that the computer software when executed will yield what is expected, due to the fact that the software is executed on top of many abstractions, that can never be proved that they will yield what is expected (think of the hardware abstraction for example).
Finally while theoretically and rigorously predicting software logic is only important for high critical applications like Medical, and Military ones. Invariant can still be used to aid the typical programmer when debugging. It can be used to know where at a certain location The program failed because it has failed to maintain a certain invariant - many of us use it anyway without giving a thought about it.
Class Invariant
Class Invariant is a condition which should be always true before and after calling relevant function
For example balanced tree has an Invariant which is called isBalanced. When you modify your tree through some methods (e.g. addNode, removeNode...) - isBalanced should be always true before and after modifying the tree
Following on from what it is, invariants are quite useful in writing clean code, since knowing conceptually what invariants should be present in your code allows you to easily decide how to organize your code to reach those aims. As mentioned ealier, they're also useful in debugging, as checking to see if the invariant's being maintained is often a good way of seeing if whatever manipulation you're attempting to perform is actually doing what you want it to.
It's typically a quantity that does not change under certain mathematical operations.
An example is a scalar, which does not change under rotations. In magnetic resonance imaging, for example, it is useful to characterize a tissue property by a rotational invariant, because then its estimation ideally does not depend on the orientation of the body in the scanner.
The ADT invariant specifes relationships
among the data fields (instance variables)
that must always be true before and after
the execution of any instance method.
There is an excellent example of an invariant and why it matters in the book Java Concurrency in Practice.
Although Java-centric, the example describes some code that is responsible for calculating the factors of a provided integer. The example code attempts to cache the last number provided, and the factors that were calculated to improve performance. In this scenario there is an invariant that was not accounted for in the example code which has left the code susceptible to race conditions in a concurrent scenario.