Related to : Calculating the distance between 2 points using getY() and getX()

Calculating the distance between 2 given points 
Here :
class Point{
int x;
int y;
.....
.....
public double distance(int x, int y) {
double d = Math.sqrt( Math.pow(x2x1, 2) + Math.pow(y2y1, 2)
); //ERROR IN THIS LINE
return distance; //ERROR HERE TOO...(2)
}
}
There is no x1,x2,y1,y2 defined in the class or in the method
parameter.
Swap it with the following line:
double d = Math.sqrt(

RadBeacon Tag distance calculating 
You can get the best results for a specific device by measuring RSSI
at various distances and doing a regression against the above formula
to find coefficients for the best fit. You can read an explanation of
the recommended distances here:
http://altbeacon.github.io/androidbeaconlibrary/distancecalculations.html
You can then import the data into R (the free statistical computing
software) a

calculating minimum Euclidean distance within a data frame 
If I followed your question correctly then it would seem that you want
something like this:
minxED = min(abs(x(2:end)  x(1:end1)));
which gets the L1 distance between adjacent elements in the vector x
and then finds the minimum distance.

Calculating distance between word/document vectors from a nested dictionary 
The first bit is easy enough. You want to build up a dictionary
containing file numbers, and the sum of the squares of the values for
each file number, something like this (untested) should do it:
fileVectors = {}
for wordDict in myDict.itervalues():
for fileNumber, wordCount in wordDict.iteritems():
fileVectors[fileNumber] = fileVectors.get(fileNumber, 0) +
(wordCount ** 2)

Calculate Euclidean Distance of pairs over 3 points? 
When you transform your data.frame into a matrix, all values become
characters, I don't think that is what you want... (moreover, you're
trying to compute distance with the "class" names as one of the
variables...)
The best would be to put your "Class" as row.names and then compute
your distances and hclust :
mm<Median[,1]
row.names(mm)<Median[,1]
Then you can compute the euclidean di
