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We have the following array:
[4, 13, 25, 33, 38, 41, 55, 71, 73, 84, 86, 92, 97]
To me it seems like there are only 3 comparisons needed to find 25, because:
First we pick the middle element 55. Now we perform two comparisons: 55 = 25? 55 > 25? None of these hold so we go to the left of the array. We get the subarray: [4, 13, 25, 33, 38, 41]
We divide this again and get 25 = 25? yes.. So it took 3 comparisons to get our match. My book says there are four comparisons needed to find 25. Why is this?
As the size of the left array is even, each algorithm could select one of the middle numbers. Hence, the comparison could be like the following with 4 comparison:
[4, 13, 25, 33, 38, 41, 55, 71, 73, 84, 86, 92, 97]
25 < 55 => [4, 13, 25, 33, 38, 41]
25 < 33 => [4, 13, 25]
25 > 13 => [25]
25 == 25 => Found.
list = [5, 10, 20, 40, 50, 42, 35, 26, 18]
So in this example, I don't want an element to exceed the value 40 and if it does, I want the element to have a value of 40, e.g. the element with the value 50 will become 40.
list.map! { |i| i > 40 ? 40 : i }
=> [5, 10, 20, 40, 40, 40, 35, 26, 18]
map method permits you to apply a transformation to all the elements of your collection so I think fits perfectly in this case.
Or, if you are populating your array one element at a time, you could insert the real value just if it's 40 or less, 40 otherwise.
If 40 is the max, you need the min from 40 and the element ;)
list = [5, 10, 20, 40, 50, 42, 35, 26, 18]
list.map{ |v| [40, v].min }
# => [5, 10, 20, 40, 40, 40, 35, 26, 18]
If you're using Ruby 2.4 or newer, you can make use of Comparable#clamp:
list.map { |n| n.clamp(0, 40) }
# => [5, 10, 20, 40, 40, 40, 35, 26, 18]
Note that this will also fix the minimum value to 0. This may or may not be useful in your case, and only applies if all items are expected to be non-negative numbers.
I got this question in an interview and got almost all the way to the answer but got stuck on the last part. If I want to get the multiplication table for 5, for instance, I want to get the output to be formatted like so:
1, 2, 3, 4, 5
2, 4, 6, 8, 10
3, 6, 9, 12, 15
4, 8, 12, 16, 20
5, 10, 15, 20, 25
My answer to this is:
def make_table(n)
s = ""
1.upto(n).each do |i|
1.upto(n).each do |j|
s += (i*j).to_s
end
s += "\n"
end
p s
end
But the output for make_table(5) is:
"12345\n246810\n3691215\n48121620\n510152025\n"
I've tried variations with array but I'm getting similar output.
What am I missing or how should I think about the last part of the problem?
You can use map and join to get a String in one line :
n = 5
puts (1..n).map { |x| (1..n).map { |y| x * y }.join(', ') }.join("\n")
It iterates over rows (x=1, x=2, ...). For each row, it iterates over cells (y=1, y=2, ...) and calculates x*y. It joins every cells in a row with ,, and joins every rows in the table with a newline :
1, 2, 3, 4, 5
2, 4, 6, 8, 10
3, 6, 9, 12, 15
4, 8, 12, 16, 20
5, 10, 15, 20, 25
If you want to keep the commas aligned, you can use rjust :
puts (1..n).map { |x| (1..n).map { |y| (x * y).to_s.rjust(3) }.join(',') }.join("\n")
It outputs :
1, 2, 3, 4, 5
2, 4, 6, 8, 10
3, 6, 9, 12, 15
4, 8, 12, 16, 20
5, 10, 15, 20, 25
You could even go fancy and calculate the width of n**2 before aligning commas :
n = 11
width = Math.log10(n**2).ceil + 1
puts (1..n).map { |x| (1..n).map { |y| (x * y).to_s.rjust(width) }.join(',') }.join("\n")
It outputs :
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22
3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33
4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44
5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55
6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66
7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77
8, 16, 24, 32, 40, 48, 56, 64, 72, 80, 88
9, 18, 27, 36, 45, 54, 63, 72, 81, 90, 99
10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110
11, 22, 33, 44, 55, 66, 77, 88, 99, 110, 121
Without spaces between the figures, the result is indeed unreadable. Have a look at the % operator, which formats strings and numbers. Instead of
s += (i*j).to_s
you could write
s += '%3d' % (i*j)
If you really want to get the output formatted in the way you explained in your posting (which I don't find that much readable), you could do a
s += "#{i*j}, "
This leaves you with two extra characters at the end of the line, which you have to remove. An alternative would be to use an array. Instead of the inner loop, you would have then something like
s += 1.upto(n).to_a.map {|j| i*j}.join(', ') + "\n"
You don't need to construct a string if you're only interested in printing the table and not returning the table(as a string).
(1..n).each do |a|
(1..n-1).each { |b| print "#{a * b}, " }
puts a * n
end
This is how I'd do it.
require 'matrix'
n = 5
puts Matrix.build(n) { |i,j| (i+1)*(j+1) }.to_a.map { |row| row.join(', ') }
1, 2, 3, 4, 5
2, 4, 6, 8, 10
3, 6, 9, 12, 15
4, 8, 12, 16, 20
5, 10, 15, 20, 25
See Matrix::build.
You can make it much shorter but here's my version.
range = Array(1..12)
range.each do |element|
range.map { |item| print "#{element * item} " } && puts
end
Is there any cool way in Ruby to create an array with 1 to 100 with only odd entries (1, 3 etc). I now have a loop for this but that is obviously not a cool way to do it! Any suggestions?
My current code:
def create_1_to_100_odd_array
array = [1]
i = 3
while i < 100
array.push i
i += 2
end
array
end
Thanks in advance
The Range class comes with a very cool feature for that purpose:
1.9.3-p286 :005 > (1..10).step(2).to_a
=> [1, 3, 5, 7, 9]
May not be efficient, but a short piece of code:
(1..100).select(&:odd?)
# => [1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99]
Just toying...
(0...50).map(&:object_id)
#or
1.step(100,2).to_a
Since you need a function, then:
def odd_to(n)
(1..n).step(2).to_a
end
Not very effective solution, but quite elegant:
(1..100).select {|a| a%2 != 0}
You can do it as a one-liner when you instantiate the array:
def create_array_of_odds_to(n)
Array.new((n + 1) / 2) {|i| 2 * i + 1}
end
create_array_of_odds_to 10 # => [1, 3, 5, 7, 9]
I'm looking to make a 3-column layout similar to that of piccsy.com. Given a number of images of the same width but varying height, what is a algorithm to order them so that the difference in column lengths is minimal? Ideally in Python or JavaScript...
Thanks a lot for your help in advance!
Martin
How many images?
If you limit the maximum page size, and have a value for the minimum picture height, you can calculate the maximum number of images per page. You would need this when evaluating any solution.
I think there were 27 pictures on the link you gave.
The following uses the first_fit algorithm mentioned by Robin Green earlier but then improves on this by greedy swapping.
The swapping routine finds the column that is furthest away from the average column height then systematically looks for a swap between one of its pictures and the first picture in another column that minimizes the maximum deviation from the average.
I used a random sample of 30 pictures with heights in the range five to 50 'units'. The convergenge was swift in my case and improved significantly on the first_fit algorithm.
The code (Python 3.2:
def first_fit(items, bincount=3):
items = sorted(items, reverse=1) # New - improves first fit.
bins = [[] for c in range(bincount)]
binsizes = [0] * bincount
for item in items:
minbinindex = binsizes.index(min(binsizes))
bins[minbinindex].append(item)
binsizes[minbinindex] += item
average = sum(binsizes) / float(bincount)
maxdeviation = max(abs(average - bs) for bs in binsizes)
return bins, binsizes, average, maxdeviation
def swap1(columns, colsize, average, margin=0):
'See if you can do a swap to smooth the heights'
colcount = len(columns)
maxdeviation, i_a = max((abs(average - cs), i)
for i,cs in enumerate(colsize))
col_a = columns[i_a]
for pic_a in set(col_a): # use set as if same height then only do once
for i_b, col_b in enumerate(columns):
if i_a != i_b: # Not same column
for pic_b in set(col_b):
if (abs(pic_a - pic_b) > margin): # Not same heights
# new heights if swapped
new_a = colsize[i_a] - pic_a + pic_b
new_b = colsize[i_b] - pic_b + pic_a
if all(abs(average - new) < maxdeviation
for new in (new_a, new_b)):
# Better to swap (in-place)
colsize[i_a] = new_a
colsize[i_b] = new_b
columns[i_a].remove(pic_a)
columns[i_a].append(pic_b)
columns[i_b].remove(pic_b)
columns[i_b].append(pic_a)
maxdeviation = max(abs(average - cs)
for cs in colsize)
return True, maxdeviation
return False, maxdeviation
def printit(columns, colsize, average, maxdeviation):
print('columns')
pp(columns)
print('colsize:', colsize)
print('average, maxdeviation:', average, maxdeviation)
print('deviations:', [abs(average - cs) for cs in colsize])
print()
if __name__ == '__main__':
## Some data
#import random
#heights = [random.randint(5, 50) for i in range(30)]
## Here's some from the above, but 'fixed'.
from pprint import pprint as pp
heights = [45, 7, 46, 34, 12, 12, 34, 19, 17, 41,
28, 9, 37, 32, 30, 44, 17, 16, 44, 7,
23, 30, 36, 5, 40, 20, 28, 42, 8, 38]
columns, colsize, average, maxdeviation = first_fit(heights)
printit(columns, colsize, average, maxdeviation)
while 1:
swapped, maxdeviation = swap1(columns, colsize, average, maxdeviation)
printit(columns, colsize, average, maxdeviation)
if not swapped:
break
#input('Paused: ')
The output:
columns
[[45, 12, 17, 28, 32, 17, 44, 5, 40, 8, 38],
[7, 34, 12, 19, 41, 30, 16, 7, 23, 36, 42],
[46, 34, 9, 37, 44, 30, 20, 28]]
colsize: [286, 267, 248]
average, maxdeviation: 267.0 19.0
deviations: [19.0, 0.0, 19.0]
columns
[[45, 12, 17, 28, 17, 44, 5, 40, 8, 38, 9],
[7, 34, 12, 19, 41, 30, 16, 7, 23, 36, 42],
[46, 34, 37, 44, 30, 20, 28, 32]]
colsize: [263, 267, 271]
average, maxdeviation: 267.0 4.0
deviations: [4.0, 0.0, 4.0]
columns
[[45, 12, 17, 17, 44, 5, 40, 8, 38, 9, 34],
[7, 34, 12, 19, 41, 30, 16, 7, 23, 36, 42],
[46, 37, 44, 30, 20, 28, 32, 28]]
colsize: [269, 267, 265]
average, maxdeviation: 267.0 2.0
deviations: [2.0, 0.0, 2.0]
columns
[[45, 12, 17, 17, 44, 5, 8, 38, 9, 34, 37],
[7, 34, 12, 19, 41, 30, 16, 7, 23, 36, 42],
[46, 44, 30, 20, 28, 32, 28, 40]]
colsize: [266, 267, 268]
average, maxdeviation: 267.0 1.0
deviations: [1.0, 0.0, 1.0]
columns
[[45, 12, 17, 17, 44, 5, 8, 38, 9, 34, 37],
[7, 34, 12, 19, 41, 30, 16, 7, 23, 36, 42],
[46, 44, 30, 20, 28, 32, 28, 40]]
colsize: [266, 267, 268]
average, maxdeviation: 267.0 1.0
deviations: [1.0, 0.0, 1.0]
Nice problem.
Heres the info on reverse-sorting mentioned in my separate comment below.
>>> h = sorted(heights, reverse=1)
>>> h
[46, 45, 44, 44, 42, 41, 40, 38, 37, 36, 34, 34, 32, 30, 30, 28, 28, 23, 20, 19, 17, 17, 16, 12, 12, 9, 8, 7, 7, 5]
>>> columns, colsize, average, maxdeviation = first_fit(h)
>>> printit(columns, colsize, average, maxdeviation)
columns
[[46, 41, 40, 34, 30, 28, 19, 12, 12, 5],
[45, 42, 38, 36, 30, 28, 17, 16, 8, 7],
[44, 44, 37, 34, 32, 23, 20, 17, 9, 7]]
colsize: [267, 267, 267]
average, maxdeviation: 267.0 0.0
deviations: [0.0, 0.0, 0.0]
If you have the reverse-sorting, this extra code appended to the bottom of the above code (in the 'if name == ...), will do extra trials on random data:
for trial in range(2,11):
print('\n## Trial %i' % trial)
heights = [random.randint(5, 50) for i in range(random.randint(5, 50))]
print('Pictures:',len(heights))
columns, colsize, average, maxdeviation = first_fit(heights)
print('average %7.3f' % average, '\nmaxdeviation:')
print('%5.2f%% = %6.3f' % ((maxdeviation * 100. / average), maxdeviation))
swapcount = 0
while maxdeviation:
swapped, maxdeviation = swap1(columns, colsize, average, maxdeviation)
if not swapped:
break
print('%5.2f%% = %6.3f' % ((maxdeviation * 100. / average), maxdeviation))
swapcount += 1
print('swaps:', swapcount)
The extra output shows the effect of the swaps:
## Trial 2
Pictures: 11
average 72.000
maxdeviation:
9.72% = 7.000
swaps: 0
## Trial 3
Pictures: 14
average 118.667
maxdeviation:
6.46% = 7.667
4.78% = 5.667
3.09% = 3.667
0.56% = 0.667
swaps: 3
## Trial 4
Pictures: 46
average 470.333
maxdeviation:
0.57% = 2.667
0.35% = 1.667
0.14% = 0.667
swaps: 2
## Trial 5
Pictures: 40
average 388.667
maxdeviation:
0.43% = 1.667
0.17% = 0.667
swaps: 1
## Trial 6
Pictures: 5
average 44.000
maxdeviation:
4.55% = 2.000
swaps: 0
## Trial 7
Pictures: 30
average 295.000
maxdeviation:
0.34% = 1.000
swaps: 0
## Trial 8
Pictures: 43
average 413.000
maxdeviation:
0.97% = 4.000
0.73% = 3.000
0.48% = 2.000
swaps: 2
## Trial 9
Pictures: 33
average 342.000
maxdeviation:
0.29% = 1.000
swaps: 0
## Trial 10
Pictures: 26
average 233.333
maxdeviation:
2.29% = 5.333
1.86% = 4.333
1.43% = 3.333
1.00% = 2.333
0.57% = 1.333
swaps: 4
This is the offline makespan minimisation problem, which I think is equivalent to the multiprocessor scheduling problem. Instead of jobs you have images, and instead of job durations you have image heights, but it's exactly the same problem. (The fact that it involves space instead of time doesn't matter.) So any algorithm that (approximately) solves either of them will do.
Here's an algorithm (called First Fit Decreasing) that will get you a very compact arrangement, in a reasonable amount of time. There may be a better algorithm but this is ridiculously simple.
Sort the images in order from tallest to shortest.
Take the first image, and place it in the shortest column.
(If multiple columns are the same height (and shortest) pick any one.)
Repeat step 2 until no images remain.
When you're done, you can re-arrange the elements in the each column however you choose if you don't like the tallest-to-shortest look.
Here's one:
// Create initial solution
<run First Fit Decreasing algorithm first>
// Calculate "error", i.e. maximum height difference
// after running FFD
err = (maximum_height - minimum_height)
minerr = err
// Run simple greedy optimization and random search
repeat for a number of steps: // e.g. 1000 steps
<find any two random images a and b from two different columns such that
swapping a and b decreases the error>
if <found>:
swap a and b
err = (maximum_height - minimum_height)
if (err < minerr):
<store as best solution so far> // X
else:
swap two random images from two columns
err = (maximum_height - minimum_height)
<output the best solution stored on line marked with X>