range

The method I've devised so far is this: func randRange (lower : Int , upper : Int) -> Int { let difference = upper - lower return Int(Float(rand())/Float(RAND_MAX) * Float(difference + 1)) + lower } This generates random integers between lower and upper inclusive. Here's a somewhat lighter version of it: func randRange (lower: Int , upper: Int) -> Int { return lower + Int(arc4random_uniform(UInt32(upper - lower + 1))) } This can be simplified even further if you decide this function works with unsigned values only: func randRange (lower: UInt32 , upper: UInt32) -> UInt32 { return lower +

This question already has an answer here: Determine Whether Integer Is Between Two Other Integers? 8 answers Suppose I want to check if x belongs to range 0 to 0.5. How can I do it? No, you can't do that. range() expects integer arguments. If you want to know if x is inside this range try some form of this: print 0.0 <= x <= 0.5 Be careful with your upper limit. If you use range() it is excluded ( range(0, 5) does not include 5!) print 'yes' if 0 < x < 0.5 else 'no' range() is for generating arrays of consecutive integers >>> s = 1.1 >>> 0<= s <=0.2 False >>> 0<= s <=1.2 True I would use the

I'm trying to store a selection of a contentEditable element and restore it later. I want to observe the paste event and store the HTML as it was before, clear the html and then manually insert the pasted text with some changes at the selected position. Take a look at this example: jsfiddle.net/gEhjZ When you select a part of the text, hit store , remove the selection again and hit restore , it's working as expected. But when you first hit store , then replace the HTML with the exact same HTML by hitting overwrite html and then try to restore , nothing happens. I thought that using .cloneRange

Angles in my program are expressed in 0 to 2pi. I want a way to add two angles and have it wrap around the 2pi to 0 if the result is higher than 2pi. Or if I subtracted an angle from an angle and it was below 0 it would wrap around 2pi. Is there a way to do this? Thanks. What you are looking for is the modulus. The fmod function will not work because it calculates the remainder and not the arithmetic modulus. Something like this should work: inline double wrapAngle( double angle ) { double twoPi = 2.0 * 3.141592865358979; return angle - twoPi * floor( angle / twoPi ); } Edit: The remainder is

I want to be able to dynamically select a range of cells (the heading row), where the row is 1 but the columns with be for 1 to last column, where "A" is the first Column and where "M" is the last column. I know how to find the last column, but I don't know how to modified the below range to input the first and last column as "A" and "M". Range("A1:M1").Select If you want to select a variable range containing all headers cells: Dim sht as WorkSheet Set sht = This Workbook.Sheets("Data") 'Range(Cells(1,1),Cells(1,Columns.Count).End(xlToLeft)).Select '<<< NOT ROBUST sht.Range(sht.Cells(1,1),sht

Problem: I have seen questions like: count the number of 0s between 0 and N? count the number of 1s between 0 and N? count the number of 2s between 0 and N? ... ... These kinds of questions are very similar of asking to find the total number that Ks (i.e. K=0,1,2,...,9) are shown in number range [0, N] . Example: Input: K=2, N=35 Output: 14 Detail: list of 2 s between [0,35] : 2, 12, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32 , note that 22 will be counted as twice (as 22 contains two 2 s) What we have: There are solutions for each of them (available if you search for it). Usually, O(log N)

When iterating over a large array with a range expression, should I use Python's built-in range function, or numpy's arange to get the best performance? My reasoning so far: arange probably resorts to a native implementation and might be faster therefore. On the other hand, arange returns a full array, which occupies memory, so there might be an overhead. Python 3's range expression is a generator, which does not hold all the values in memory. bmu For large arrays numpy should be the faster solution. In numpy you should use combinations of vectorized calculations, ufuncs and indexing to solve