Recurrence Relation of function with a Loop - recurrence

I have been trying to find recurrence relation that represents the runtime of the following function. I know how to solve recurrence relations and functions without loop but I have 0 clue about the following function
function derp(n):
if n == 0
return 1
sum = 0
for i = 1 to 3
sum = sum + derp(n-1)
return sum

Ok, so answering myself,
We know that $T(0)=0$.
Otherwise, for $n>0$, we have:
$T(n)= 3T(n−1)$
This can be verified by using recursion tree

Related

Finding the consecutive win in Cypher query language

from fig we can see that Arsenal have won three match consecutively but I could not write the query.
Here is a query that should return the maximum number of consecutive wins for Arsenal:
MATCH (a:Club {name:'Arsenal FC'})-[r:played_with]-(:Club)
WITH ((CASE a.name WHEN r.home THEN 1 ELSE -1 END) * (TOINT(r.score[0]) - TOINT(r.score[1]))) > 0 AS win, r
ORDER BY TOINT(r.time)
RETURN REDUCE(s = {max: 0, curr: 0}, w IN COLLECT(win) |
CASE WHEN w
THEN {
max: CASE WHEN s.max < s.curr + 1 THEN s.curr + 1 ELSE s.max END,
curr: s.curr + 1}
ELSE {max: s.max, curr: 0}
END
).max AS result;
The WITH clause sets the win variable to true iff Arsenal won a particular game. Notice that the ORDER BY clause converts the time property to an integer, because the ordering of numeric strings does not work properly if the strings could be of different lengths (I am being a bit picky here, admittedly). The REDUCE function is used to calculate the maximum number of consecutive wins.
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Finally, here are some suggestions for some improvements to your data model. For example:
It looks like your played_with relationship always points from the home team to the away team. If so, you can get rid of the redundant home and away properties, and you can also rename the relationship type to HOSTED to make the direction of the relationship more clear.
The scores and time should be stored as integers, not strings. That would make your queries more efficient, and easier to write and understand.
You could also consider splitting the scores property into two scalar properties, say homeScore and awayScore, which would make your code more clear. There seems to be no advantage to storing the scores in an array.
If you made all the above suggested changes, then you would just need to change the beginning of the above query to this:
MATCH (a:Club {name:'Arsenal FC'})-[r:HOSTED]-(:Club)
WITH ((CASE a WHEN STARTNODE(r) THEN 1 ELSE -1 END) * (r.homeScore - r.awayScore)) > 0 AS win, r
ORDER BY r.time
...

SET in combination with CASE statement in cypher

I am tryin to set two different relationship properties to a count, with a case construct depending on the value of another relationship property. There is a console at http://console.neo4j.org/?id=rt1ld5
the cnt column contains the number of times r.value occurs. The two first rows of the initial query in the console indicate that the term "Car" is linked to 1 document that is considered relevant, and to two documents that are considered not relevant.
I want to SET a property on the [:INTEREST] relation between (user) and (term) with two properties, indicating how many times an interest is linked to a document that is considered relevant or not. So for (John)-[r:INTEREST]->(Car) I want r.poscnt=1 and r.negcnt=2
I.m struggling with the CASE construct. I tried various ways, this was the closest I got.
MATCH (u:user)-[int:INTEREST]->(t:term)<-[:ISABOUT]-(d:doc)<- [r:RELEVANCE]-(u)
WITH int, t.name, r.value, count(*) AS cnt
CASE
WHEN r.value=1 THEN SET int.poscnt=cnt
WHEN r.value=-1 THEN SET int.negcnt=cnt
END
But it's returning an error
Error: Invalid input 'A': expected 'r/R' (line 3, column 2)
"CASE"
^
This did it! Also see console at http://console.neo4j.org/?id=rq2i7j
MATCH (u:user)-[int:INTEREST]->(t:term)<-[:ISABOUT]-(d:doc)<-[r:RELEVANCE]-(u)
WITH int, t,
SUM(CASE WHEN r.value= 1 THEN 1 ELSE 0 END ) AS poscnt,
SUM(CASE WHEN r.value= -1 THEN 1 ELSE 0 END ) AS negcnt
SET int.pos=poscnt,int.neg=negcnt
RETURN t.name,int.pos,int.neg
Is it important for you to keep positive and negative count separate? It seems you could have a score property summing positive and negative values.
MATCH (u:user)-[int:INTEREST]->()<-[:ISABOUT]-()<-[r:RELEVANCE]-(u)
SET int.score = SUM(r.value)
RETURN t.name, int.score
You already seem to have found a working solution but I'll add a note about CASE as I understand it. While CASE provides branching, I think it's correct to say that it is an expression and not a statement. It resembles a ternary operator more than a conditional statement.
As the expression
a > b ? x : y;
is resolved to a value, either x or y, that can be used in a statement, so also
CASE WHEN a > b THEN x ELSE y END
resolves to a value. You can then assign this value
result = CASE WHEN a > b THEN x ELSE y END
Your original query used the CASE expression like a conditional statement
CASE WHEN a > b THEN result = x ELSE result = y END
which resembles if-else
if a > b { result = x; } else { result = y; }
Someone may want to correct the terminology, the point is that in your working query you correctly let CASE resolve to a value to be used by SUM rather than put a conditional assignment inside CASE.

ternary operator/default value in neo4j cypher

I need to implement something of a ternary operator that can help me return some default values from cypher query itself.
Scenario is -
if an employee's city is Delhi, return 5 else return 10
Something like a ternary operator.
start employee = node(5)
return employee.city == 'DELHI' ? 5 : 10 as val;
I tried things like
start employee = node(5)
return coalesce (employee.city == 'DELHI', 5)
but no luck.
Is there a way to implement such a scenario in neo4j be it Cypher or Traversal.
Unfortunately it is not supported out of the box but here is a hack to do it, using filter, head and collection literals.
The idea is to have a two element list and a filter expression that becomes true for the first element for your "true-branch" and alternatively true for the second element in the list whic represents the value of your false-branch.
see this console example: http://console.neo4j.org/r/6tig7g
start n=node(5) return head(filter( a in [5,10] : n.city = 'DELHI' OR a = 10))
so generally:
head(filter( a in [true-result,false-result] : CONDITION OR a = false-result))
I know this is a really old question, but since Google landed me here and I have an answer (Cypher in Neo4J 3.5+):
MATCH (employee:Employee)
RETURN
CASE employee.city WHEN "DELHI" THEN 5 ELSE 10 END AS val

Rails: Count specific records then do calculation

I am attempting to do a rails record count then do a calculation from those records to give me a final number:
Example
100 Records = A
30 Records = B
Total Records = C
A+(-B)=C
I am not even going to show you what I tried... in retrospect I am very new to rails and it made no logical sense!
UPDATE:
To further expand:
When implementing this I realized that there might be some slight difference from what it solves above.
I have a MVC called "POST" It was some records within the table one specifically is called "VOTE" the vote integer will consist of 1 or (-1). Each post will have a VOTE column that represent a value of 1 or (-1). I am trying to create an analytic metric that consists of the following:
TOTAL = (Total posts with Value 1) + (Total posts with Value -1)
Example
1234 = 2000 + (-776)
Thank you in advance!
In general,
C = A.count + B.count
If you want C to be the union of A and B, then do
C = A & B
C.count # Number of elements in C
For your specific case:
yes_votes = POST.where('VOTE = ?', 1)
no_votes = POST.where('VOTE = ?', -1)
total = yes_votes.count - no_votes.count

How to calculate mean based on number of votes/scores/samples/etc?

For simplicity say we have a sample set of possible scores {0, 1, 2}. Is there a way to calculate a mean based on the number of scores without getting into hairy lookup tables etc for a 95% confidence interval calculation?
dreeves posted a solution to this here: How can I calculate a fair overall game score based on a variable number of matches?
Now say we have 2 scenarios ...
Scenario A) 2 votes of value 2 result in SE=0 resulting in the mean to be 2
Scenario B) 10000 votes of value 2 result in SE=0 resulting in the mean to be 2
I wanted Scenario A to be some value less than 2 because of the low number of votes, but it doesn't seem like this solution handles that (dreeve's equations hold when you don't have all values in your set equal to each other). Am I missing something or is there another algorithm I can use to calculate a better score.
The data available to me is:
n (number of votes)
sum (sum of votes)
{set of votes} (all vote values)
Thanks!
You could just give it a weighted score when ranking results, as opposed to just displaying the average vote so far, by multiplying with some function of the number of votes.
An example in C# (because that's what I happen to know best...) that could easily be translated into your language of choice:
double avgScore = Math.Round(sum / n);
double rank = avgScore * Math.Log(n);
Here I've used the logarithm of n as the weighting function - but it will only work well if the number of votes is neither too small or too large. Exactly how large is "optimal" depends on how much you want the number of votes to matter.
If you like the logarithmic approach, but base 10 doesn't really work with your vote counts, you could easily use another base. For example, to do it in base 3 instead:
double rank = avgScore * Math.Log(n, 3);
Which function you should use for weighing is probably best decided by the order of magnitude of the number of votes you expect to reach.
You could also use a custom weighting function by defining
double rank = avgScore * w(n);
where w(n) returns the weight value depending on the number of votes. You then define w(n) as you wish, for example like this:
double w(int n) {
// caution! ugly example code ahead...
// if you even want this approach, at least use a switch... :P
if (n > 100) {
return 10;
} else if (n > 50) {
return 8;
} else if (n > 40) {
return 6;
} else if (n > 20) {
return 3;
} else if (n > 10) {
return 2;
} else {
return 1;
}
}
If you want to use the idea in my other referenced answer (thanks!) of using a pessimistic lower bound on the average then I think some additional assumptions/parameters are going to need to be injected.
To make sure I understand: With 10000 votes, every single one of which is "2", you're very sure the true average is 2. With 2 votes, each a "2", you're very unsure -- maybe some 0's and 1's will come in and bring down the average. But how to quantify that, I think is your question.
Here's an idea: Everyone starts with some "baggage": a single phantom vote of "1". The person with 2 true "2" votes will then have an average of (1+2+2)/3 = 1.67 where the person with 10000 true "2" votes will have an average of 1.9997. That alone may satisfy your criteria. Or to add the pessimistic lower bound idea, the person with 2 votes would have a pessimistic average score of 1.333 and the person with 10k votes would be 1.99948.
(To be absolutely sure you'll never have the problem of zero standard error, use two different phantom votes. Or perhaps use as many phantom votes as there are possible vote values, one vote with each value.)

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