How do I simplify this loop to some function like foreach or map or other thing with Scala? I want to put hitsArray inside that filter shipList.filter.
val hitsArray: Array[String] = T.split(" ");
for (hit <- hitsArray) {
shipSize = shipList.length
shipList = shipList.filter(!_.equalsIgnoreCase(hit))
}
if (shipList.length == 0) {
shipSunk = shipSunk + 1
} else if (shipList.length < shipSize) {
shipHit = shipHit + 1
}
To be fair, I don't understand why you are calling shipSize = shipList.length as you don't use it anywhere.
T.split(" ").foreach{ hit =>
shipList = shipList.filter(!_.equalsIgnoreCase(hit))
}
which gets you to where you want to go. I've made it 3 lines because you want to emphasize you're working via side effect in that foreach. That said, I don't see any advantage to making it a one-liner. What you had before was perfectly readable.
Something like this maybe?
shipList.filter(ship => T.split(" ").forall(!_.equalsIgnoreCase(ship)))
Although cleaner if shipList is already all lower case:
shipList.filterNot(T.split(" ").map(_.toLowerCase) contains _)
Or if your T is large, move it outside the loop:
val hits = T.split(" ").map(_.toLowerCase)
shipList.filterNot(hits contains _)
I have the following Scala snippet from my code. I am not able to convert it into functional style. I could do it at other places in my code but not able to change the below one to functional. Issue is once the code exhausts all pattern matching options, then only it should send back "NA". Following code is doing that, but it's not in functional style (for-yield)
var matches = new ListBuffer[List[String]]()
for (line <- caselist){
var count = 0
for (pat <- pattern if (!pat.findAllIn(line).isEmpty)){
count += 1
matches += pat.findAllIn(line).toList
}
if (count == 0){
matches += List("NA")
}
}
return matches.toList
}
Your question is not entirely complete, so I can't be sure, but I believe the following will do the job:
for {
line <- caselist
matches = pattern.map(_.findAllIn(line).toList)
} yield matches.flatten match {
case Nil => List("NA")
case ms => ms
}
This should do the job. Using foreach and filter to generate the matches and checking to make sure there is a match for each line will work.
caseList.foreach{ line =>
val results = pattern.foreach ( pat => pat.findAllIn(line).toList )
val filteredResults = results.filter( ! _.isEmpty )
if ( filteredResults.isEmpty ) List("NA")
else filteredResults
}
Functional doesn't mean you can't have intermediate named values.
In the following image you can see where i put the breakpoint and then debugged two step. You can also see that both assignments worked great they have the same count and are the same.
However if I do the following. Run the exact same call but only break on the third line directly then this happnes
set.QuestionSet.Questions should have count of 8 BEFORE the assigment, so it seems it's not properly assigned for some reason. I suspect this has something to do with how I fetch my data from DB.
Question and QuestionSet are normal POCOs and here is the code for the entire method.
public IEnumerable<QuestionSet> SearchAndFilterQuestionsAndSets(string searchString, int nrPerPage, int page, out int totalSearchCount)
{
searchString = searchString.ToLower();
List<QuestionSet> finalList = new List<QuestionSet>();
var result = ActiveContext.QuestionSets
.Select(x => new
{
QuestionSet = x,
Questions = x.Questions.Where(
y =>
y.Description.ToLower().Contains(searchString)
).OrderBy(
z => z.Description
)
})
.ToList();
foreach (var set in result)
{
//If our search matched the set itself we load all questions
if (set.QuestionSet.Name.ToLower().Contains(searchString))
{
//we dont bring empty sets
if (set.QuestionSet.Questions.Count() > 0)
{
set.QuestionSet.Questions = set.QuestionSet.Questions.ToList<Question>().OrderBy(x => x.Description).ToList<Question>();
finalList.Add(set.QuestionSet);
}
}
//We had one or more questions matching the search term
else if (set.Questions.Count() > 0)
{
var b = set.Questions.ToList<Question>();
set.QuestionSet.Questions = set.Questions.ToList<Question>();
finalList.Add(set.QuestionSet);
}
}
totalSearchCount = finalList.Count();
return finalList.Skip((page - 1) * nrPerPage).Take(nrPerPage);
}
UPDATE
If I do this instead in the failing else if
var a = new QuestionSet();
a.Id = set.QuestionSet.Id;
a.Name = set.QuestionSet.Name;
a.Questions = set.Questions.ToList<Question>();
finalList.Add(a);
Then it works, so the problem lies within the anonymous object, but why does it work when i step through with debugger and not otherwise?? call me puzzled.
Could be something to do with Late binding of anonymous types
I have the folowwing statement and I would like to have a LINQ equivalent:
SELECT *
FROM People
where Name like '%something%'
ORDER BY CASE
WHEN Name LIKE 'something%' then 1
WHEN Name LIKE '%something%' then 2
ELSE 3 END
Basically, I'm retrieving all the rows which contains a value (in this case 'something') and I'm ordering them: first the ones starting with that value, and then the remaining.
Any idea on how to do that in LinQ?
I've came out with the following solution.
var dc = new EntityContext();
var result = dc
// Condition part
.People.Where(x => x.Name.IndexOf("Foo") > -1) // This part is translated to like
// projection part
.Select(x => new { Person = x, Weight = x.Name.IndexOf("Bar") > -1 ? 1 : (x.Name.IndexOf("Baz") ? 2 : 0)})
// Order
.OrderBy(x => x.Weight)
// Final projection
.Select(x => x.Person);
I guess everything is self explanatory. First you select under your condition, then create a new object with weights necessary, then order it and finally take the necessary people.
I am not able to verify this, but something like this might work. The code can definitely be optimized/cleaned up, but in theory this just might work :)
The only question is whether the contains in the comparable delegate will translate the way it does in the Where. So, you might need to use an IndexOf or similar (as Oybek implemented)
var queryResult =
people
.Where(person=>person.name.Contains(#"/something/"))
.OrderBy(person=>person.Name,
delegate(string name1, string name2)
{
int result1, result2;
if(name1.Contains(#"something/")) result1 = 1;
else if(name1.Contains(#"/something/")) result1 = 2;
else result1 = 3;
if(name2.Contains(#"something/")) result2 = 1;
else if(name2.Contains(#"/something/")) result2 = 2;
else result2 = 3;
return result1.CompareTo(result2);
})
I have been using CouchDB for quite sometime without any issues. That is up until now. I recently saw something in my map/reduce results which I had overlooked!
This is before performing a sum on the "avgs" variable. I'm basically trying to find the average of all values pertaining to a particular key. Nothing fancy. The result is as expected.
Note the result for timestamp 1308474660000 (4th row in the table):
Now I sum the "avgs" array. Now here is something that is peculiar about the result. The sum for the key with timestamp 1308474660000 is a null!! Why is CouchDB spitting out nulls for a simple sum? I tried with a custom addition function and its the same problem.
Can someone explain to me why is there this issue with my map/reduce result?
CouchDB version: 1.0.1
UPDATE:
After doing a rereduce I get a reduce overflow error!
Error: reduce_overflow_error
Reduce output must shrink more rapidly: Current output: '["001,1,1,1,1,1,11,1,1,1,1,1,1,11,1,1,1,1,1,1,11,1,1,1,1,1,1,11,1,1,1,1,1,101,1,1,1,1,1,1,11,1,1,1,1'... (first 100 of 396 bytes)
This is my modified reduce function:
function (key, values, rereduce) {
if(!rereduce) {
var avgs = [];
for(var i=values.length-1; i>=0 ; i--) {
avgs.push(Number(values[i][0])/Number(values[i][1]));
}
return avgs;
} else {
return sum(values);
};
}
UPDATE 2:
Well now it has gotten worse. Its selectively rereducing. Also, the ones it has rereduced show wrong results. The length of the value in 4th row for timestamp (1308474660000) should be 2 and not 3.
UPDATE 3:
I finally got it to work. I hadn't understood the specifics of rereduce properly. AFAIK, Couchdb itself decides how to/when to rereduce. In this example, whenever the array was long enough to process, Couchdb would send it to rereduce. So I basically had to sum twice. Once in reduce, and again in rereduce.
function (key, values, rereduce) {
if(!rereduce) {
var avgs = [];
for(var i=values.length-1; i>=0 ; i--) {
avgs.push(Number(values[i][0])/Number(values[i][1]));
}
return sum(avgs);
} else {
return sum(values); //If my understanding of rereduce is correct, it only receives only the avgs that are large enough to not be processed by reduce.
}
}
Your for loop in the reduce function is probably not doing what you think it is. For example, it might be throwing an exception that you did not expect.
You are expecting an array of 2-tuples:
// Expectation
values = [ [value1, total1]
, [value2, total2]
, [value3, total3]
];
During a re-reduce, the function will get old results from itself before.
// Re-reduce values
values = [ avg1
, avg2
, avg3
]
Therefore I would begin by examining how your code works if and when rereduce is true. Perhaps something simple will fix it (although often I have to log() things until I find the problem.)
function(keys, values, rereduce) {
if(rereduce)
return sum(values);
// ... then the same code as before.
}
I will elaborate on my count/sum comment, just in case you are curious.
This code is not tested, but hopefully you will get the idea. The end result is always a simple object {"count":C, "sum":S} and you know the average by computing S / C.
function (key, values, rereduce) {
// Reduce function
var count = 0;
var sum = 0;
var i;
if(!rereduce) {
// `values` stores actual map output
for(i = 0; i < values.length; i++) {
count += Number(values[i][1]);
sum += Number(values[i][0]);
}
return {"count":count, "sum":sum};
}
else {
// `values` stores count/sum objects returned previously.
for(i = 0; i < values.length; i++) {
count += values[i].count;
sum += values[i].sum;
}
return {"count":count, "sum":sum};
}
}
I use the following code to do average. Hope it helps.
function (key, values) {
return sum(values)/values.length;
}