I'm a college student in Taiwan and I'm doing a research about "how much wind turbines and solar photovoltaic panels should be installed to satisfy the require of minimum energy penetration rate in a semiconductor factory".
My professor hope I can display each variable in each period, but I don't know what code I should write.
Maybe there will be "execute" and "writeln" in my code? But there is nothing happened.
The following is my brief code:
{string} product = ...;
range time = 1..2;
{string} GreenPower = ...;
string NonGreenPower = ...；
dvar float InPut[product][time]; //In t period, amount of input of products
dvar float working[product][time]; //In t period, amount of working of products
dvar float OutPut[product][time]; //In t period, amount of output of products
So, I want to see the change in IntPut in each time, how to do it.
Thanks for your reading and tolerating my grammatical or spelling mistakes QQ
In order to print the solution to a console, you can use a post-processing block. A post-processing block is implemented by putting an execute block after the constraint specification (after the subject to block).
A post-processing block to print variables could look like this (untested code):
execute {
for (var p in product) {
for (var t in time) {
writeln(p + ", " + t + ": " + InPut[p][t] + ", " + working[p][t] + ", " + OutPut[p][t]);
}
}
}
Many of the examples shipped with CPLEX use post processing to display solutions to the console. You can look through them to learn what can be done in post processing and what are different ways to visualize solutions in the console.
Related
I am trying to write a Macro in IJ1 which would ask the user:
the number of event they want to record
to name those events
I started using Script Parameters as follow:
// # Integer (label="How many events do you want to record ?", min=1, max=50, value=1, persist=false) events
for (event=1; event<=events; event++) {
mLabel = "Name event number " + event + ":";
varname = "event" + event;
// # String (label="mLabel") varname
print(varname);
}
This doesn't work as it doesn't ask for the String. And even if it does, I guess it won't be very elegant as it would pop up a window to ask a Name n times (if 50, it'll be a nightmare...)
Ultimately, I want:
Box ask Number of Event
Answer is 3
Box ask Name of Event1, Event2, Event3
I would be really glad to have any help ! Thank you in advance !
When writing macros it is very useful to have the list of macros functions open https://imagej.net/developer/macro/functions.html
This should do the trick:
defaultname="event";
events=getNumber("How many events shall be run", 0);
for (event=1; event<=events; event++) {
eventname=getString("Please define name of event "+event+":", defaultname+event);
print(eventname);
}
I am developing an application using Apache Jena to work with RDF triples and OWL ontologies.
The problem
What I am currently trying to do is to get a model from a TDB triplestore, to infer on this model and to find some statements in the inferred model. This is done thanks to the StmtIterator listStatements(Resource s, Property p, RDFNode o) method. And then a really simple while(iter.hasNext()) loop is made to iterate over the statements.
At first glance, it seems to work well but it is really slow.
For my reasonably small model, it takes approximately 5 minutes while it takes only a few milliseconds on the (not inferred) model.
An example with the Pizza ontology
In this example, I am using the Pizza ontology available here. The code looks like :
public class TestInferedModel {
private static final String INPUT_FILE_NAME = "path/to/file";
private static final String URI = "http://www.co-ode.org/ontologies/pizza/pizza.owl#";
private static final Logger logger = Logger.getLogger(TestInferedModel.class);
public static void main(String[] args) {
Model model = ModelFactory.createOntologyModel();
model.read(INPUT_FILE_NAME);
Reasoner reasoner = ReasonerRegistry.getOWLReasoner();
reasoner = reasoner.bindSchema(model);
Model infmodel = ModelFactory.createInfModel(reasoner, model);
logger.debug("Model size : " + model.size() + " and inferred model size : " + infmodel.size());
// prints Model size : 2028 and inferred model size : 4881
StmtIterator iter = infmodel.listStatements();
while (iter.hasNext()) { // <----- Performance issue seems to come from this line
// Operations with the next statement
Statement stmt = iter.nextStatement();
logger.info(stmt);
}
model.close();
}
}
Here, the model size is approximately two thousands triples while the inferred model is made of a bit less than five thousands triples. However, running the code above takes much more time than running the same piece of code after editing StmtIterator iter = infmodel.listStatements(); to StmtIterator iter = model.listStatements();. Plus, when trying to add parameters to restrict the statements, the program seems to be running in an infinite loop.
I tried to add a couple of logger.debug() message to see where the program is wasting so much time and it seems that the issue comes from the while(iter.hasNext()) line.
The question
I thought the listStatements() method is of polynomial (or linear) complexity, not exponential, isn't it ? Is it normal that it takes so much time for the inferred model ? How can I avoid that ?
I'd like to be able to list statements and to manipulate the inferred model without requiring the user to wait ten minutes for an answer...
This issue seems similar to this one. However the answer is not really helping me to understand.
I have a panel data set for which I would like to calculate moving averages across years.
Each year is a variable for which there is an observation for each state, and I would like to create a new variable for the average of every three year period.
For example:
P1947=rmean(v1943 v1944 v1945), P1947=rmean(v1944 v1945 v1946)
I figured I should use a foreach loop with the egen command, but I'm not sure about how I should refer to the different variables within the loop.
I'd appreciate any guidance!
This data structure is quite unfit for purpose. Assuming an identifier id you need to reshape, e.g.
reshape long v, i(id) j(year)
tsset id year
Then a moving average is easy. Use tssmooth or just generate, e.g.
gen mave = (L.v + v + F.v)/3
or (better)
gen mave = 0.25 * L.v + 0.5 * v + 0.25 * F.v
More on why your data structure is quite unfit: Not only would calculation of a moving average need a loop (not necessarily involving egen), but you would be creating several new extra variables. Using those in any subsequent analysis would be somewhere between awkward and impossible.
EDIT I'll give a sample loop, while not moving from my stance that it is poor technique. I don't see a reason behind your naming convention whereby P1947 is a mean for 1943-1945; I assume that's just a typo. Let's suppose that we have data for 1913-2012. For means of 3 years, we lose one year at each end.
forval j = 1914/2011 {
local i = `j' - 1
local k = `j' + 1
gen P`j' = (v`i' + v`j' + v`k') / 3
}
That could be written more concisely, at the expense of a flurry of macros within macros. Using unequal weights is easy, as above. The only reason to use egen is that it doesn't give up if there are missings, which the above will do.
FURTHER EDIT
As a matter of completeness, note that it is easy to handle missings without resorting to egen.
The numerator
(v`i' + v`j' + v`k')
generalises to
(cond(missing(v`i'), 0, v`i') + cond(missing(v`j'), 0, v`j') + cond(missing(v`k'), 0, v`k')
and the denominator
3
generalises to
!missing(v`i') + !missing(v`j') + !missing(v`k')
If all values are missing, this reduces to 0/0, or missing. Otherwise, if any value is missing, we add 0 to the numerator and 0 to the denominator, which is the same as ignoring it. Naturally the code is tolerable as above for averages of 3 years, but either for that case or for averaging over more years, we would replace the lines above by a loop, which is what egen does.
There is a user written program that can do that very easily for you. It is called mvsumm and can be found through findit mvsumm
xtset id time
mvsumm observations, stat(mean) win(t) gen(new_variable) end
I am generating a unique and random alphanumeric string segment to represent certain links that will be generated by the users. For doing that I was approaching with "uuid" number to ensure it's uniqueness and randomness, but, as per my requirements the string shouldn't be more than 5 characters long. So I dropped that idea.
Then I decided to generate such a string using random function of ruby and current time stamp.
The code for my random string goes like this:-
temp=DateTime.now
temp=temp + rand(DateTime.now.to_i)
temp= hash.abs.to_s(36)
What I did is that I stored the current DateTime in a temp variable and then I generated a random number passing the current datetime as parameter. Then in the second line actually added current datetime and random number together to make a unique and random string.
Soon I found,while I was testing my application in two different machines and send the request at the same time, it generated the same string(Though it's rare) once after more than 100 trials.
Now I'm thinking that I should add one more parameter like mac address or client ip address before passing to_s(36) on temp variable. But can't figure out how to do it and even then whether it will be unique or nor...
Thanks....
SecureRandom in ruby uses process id (if available) and current time. You can use the urlsafe_base64(n= 16) class method to generate the sequence you need. According to your requirements I think this is your best bet.
Edit: After a bit of testing, I still think that this approach will generate non-unique keys. The way I solved this problem for barcode generation was:
barcode= barcode_sql_id_hash("#{sql_id}#{keyword}")
Here, your keyword can be time + pid.
If you are certain that you will never need more than a given M amount of unique values, and you don't need more than rudimentary protection against guessing the next generated id, you can use a Linear Congruentual Generator to generate your identificators. All you have to do is remember the last id generated, and use that to generate a new one using the following formula:
newid = (A * oldid + B) mod M
If 2³² distinct id values are enough to suit your needs, try:
def generate_id
if #lcg
#lcg = (1664525 * #lcg + 1013904223) % (2**32)
else
#lcg = rand(2**32) # Random seed
end
end
Now just pick a suitable set of characters to represent the id in as little as 6 character. Uppercase and lowercase letters should do the trick, since (26+26)^6 > 2^32:
ENCODE_CHARS = [*?a..?z, *?A..?Z]
def encode(n)
6.times.map { |i|
n, mod = n.divmod(ENCODE_CHARS.size)
ENCODE_CHARS[mod]
}.join
end
Example:
> 10.times { n = generate_id ; puts "%10d = %s" % [n, encode(n)] }
2574974483 = dyhjOg
3636751446 = QxyuDj
368621501 = bBGvYa
1689949688 = yuTgxe
1457610999 = NqzsRd
3936504298 = MPpusk
133820481 = PQLpsa
2956135596 = yvXpOh
3269402651 = VFUhFi
724653758 = knLfVb
Due to the nature of the LCG, the generated id will not repeat until all 2³² values have been used exactly once each.
There is no way you can generate a unique UUID with only five chars, with chars and numbers you have a basic space of around 56 chars, so there is a max of 56^5 combinations , aprox 551 million (Around 2^29).
If with this scheme you were about to generate 10.000 UUIDs (A very low number of UUIDs) you would have a probability of 1/5.000 of generating a collision.
When using crypto, the standard definition of a big enough space to avert collisions is around 2^80.
To put this into perspective, your algorithm would be better off if it generated just a random integer (a 32 bit uint is 2^32, 8 times the size you are proposing) which is clearly a bad idea.
I just saw in the new OpenCV 2.4.3 that they added a universal parallel_for. So following this example, I tried to implement it myself. I got it all functioning with my code, but when I timed its processing vs a similar loop done in a typical serial fashion with a regular "for" command, the results were insignificantly faster, or often a tiny bit slower!
I thought maybe this had something to do with my pushing into vectors or something (I'm a pretty big noob to parallel processing), so I set up a test loop of just running through a big number and it still doesn't work.
Code:
class Parallel_Test : public cv::ParallelLoopBody
{
private:
double* const mypointer;
public:
Parallel_Test(double* pointer)
: mypointer(pointer){
}
void operator() (const Range& range) const
{
//This constructor needs to be here otherwise it is considered an abstract class.
// qDebug()<<"This should never be called";
}
void operator ()(const cv::BlockedRange& range) const
{
for (int x = range.begin(); x < range.end(); ++x){
mypointer[x]=x;
}
}
};
//TODO Loop pixels in parallel
double t = (double)getTickCount();
//TEST PARALELL LOOPING AT ALL
double data1[1000000];
cv::parallel_for(BlockedRange(0, 1000000), Parallel_Test(data1));
t = ((double)getTickCount() - t)/getTickFrequency();
qDebug() << "Parallel TEST time " << t << endl;
t = (double)getTickCount();
for(int i =0; i<1000000; i++){
data1[i]=i;
}
t = ((double)getTickCount() - t)/getTickFrequency();
qDebug() << "SERIAL Scan time " << t << endl;
output:
Parallel TEST time 0.00415479
SERIAL Scan time 0.00204597
Wow! I found the answer! "parallel_for" and "parallel_for_" (with a trailing underscore!) are totally different. You need the trailing underscore to make it work! Otherwise it will just run your loop in serial and you will have to use a BLOCKEDRANGE instead of a range! AHH!
Thanks to #Daniil Osokin and especially #Vladislav Vinogradov for pointing this out!
So again you code will need to look something like this:
cv::parallel_for_(Range(0, 1000000), Parallel_Test(data1));
More updated details at: http://answers.opencv.org/question/3730/how-to-use-parallel_for/
The problem is most likely that your loop body is too small.
It appears all you are doing is assigning a pointer in one vector to another.
You really need to think of a parallel for as an inefficient for loop, that is the work inside each iteration needs to be large enough so that you wouldn't dream of getting speedups by unrolling the loop because in addition to the usual decrement, compare and jump that can go on you also have a few interlocked instructions and perhaps a virtual function call or two and some allocations.
So instead of copying a pointer try doing a good amount of real math or work on a large array of data.