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vincentchin/imageblur.rb

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Last active August 29, 2015 14:27
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imageblur.rb
class Image
attr_accessor :array
def initialize(array)
@array = array
@cells = []
@new_array = @array.map {|e| Array.new(e.size) }
end
def all_array_indexes
#Returns all possible array indexes within the size of the array
column_index = @array.first.size - 1
row_index = @array.size - 1
(0..row_index).to_a.product((0..column_index).to_a)
end
def manhattan_cells(x,y,n)
#Selects only cells within a manhattan distance of n relevant to a specified point
#Stores all cells into instance variable @cells
@cells = all_array_indexes.select { |i,j| ( (x-i).abs ) + ( (y-j).abs ) <= n }
end
def update_cells
#Goes through each value in @cells and plugs the row index (a) and column index (b) in @new_array[a][b]
@cells.uniq.each do |a,b|
@new_array[a][b] = 1
end
end
def output_image
@array.each do |i|
puts i.join("")
end
end
def blur(n)
#Where it all comes together
@array.each_with_index do |row,x|
row.each_with_index do |cell,y|
if @array[x][y] == 1
manhattan_cells(x,y,n)
update_cells
else
@new_array[x][y] ||= @array[x][y]
#Sets value to 0 in @new_array since it was also 0 in @array
end
end
end
return Image.new(@new_array).output_image
end
end
image = Image.new([
[0, 0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1],
])
image.blur(4)
Raw
imageblur2_spec.rb
require 'rspec'
require_relative 'imageblur'
describe Image do
describe '#blur' do
context 'with a 5 by 5 array and n of 2' do
it 'moves a manhattan distance of 2' do
image = Image.new([
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]
])
new_image = Image.new([
[0, 0, 1, 0, 0],
[0, 1, 1, 1, 0],
[1, 1, 1, 1, 1],
[0, 1, 1, 1, 0],
[0, 0, 1, 0, 0]
])
expect(image.blur(2)).to eql(new_image.output_image)
end
end
context 'with a 9 by 12 array and n of 3' do
it 'moves a manhattan distance of 3' do
image = Image.new([
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1],
])
new_image = Image.new([
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 1, 1, 1, 1],
])
expect(image.blur(3)).to eql(new_image.output_image)
end
end
describe '#all array indexes' do
it 'returns all possible array indexes based on size of array' do
image = Image.new([
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]
])
result = [
[0, 0], [0, 1], [0, 2], [0, 3],
[0, 4], [1, 0], [1, 1], [1, 2],
[1, 3], [1, 4], [2, 0], [2, 1],
[2, 2], [2, 3], [2, 4], [3, 0],
[3, 1], [3, 2], [3, 3], [3, 4],
[4, 0], [4, 1], [4, 2], [4, 3],
[4, 4]
]
expect(image.all_array_indexes).to eql(result)
end
context 'when array is 12 by 9' do
it 'returns all possible array indexes in a 12 by 9 array' do
image = Image.new([
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
])
result = [
[0, 0], [0, 1], [0, 2], [0, 3],
[0, 4], [0, 5], [0, 6], [0, 7],
[0, 8], [1, 0], [1, 1], [1, 2], [1, 3],
[1, 4], [1, 5], [1, 6], [1, 7], [1, 8],
[2, 0], [2, 1], [2, 2], [2, 3], [2, 4],
[2, 5], [2, 6], [2, 7], [2, 8], [3, 0],
[3, 1], [3, 2], [3, 3], [3, 4], [3, 5],
[3, 6], [3, 7], [3, 8], [4, 0], [4, 1],
[4, 2], [4, 3], [4, 4], [4, 5], [4, 6],
[4, 7], [4, 8], [5, 0], [5, 1], [5, 2],
[5, 3], [5, 4], [5, 5], [5, 6], [5, 7],
[5, 8], [6, 0], [6, 1], [6, 2], [6, 3],
[6, 4], [6, 5], [6, 6], [6, 7], [6, 8],
[7, 0], [7, 1], [7, 2], [7, 3], [7, 4],
[7, 5], [7, 6], [7, 7], [7, 8], [8, 0],
[8, 1], [8, 2], [8, 3], [8, 4], [8, 5],
[8, 6], [8, 7], [8, 8], [9, 0], [9, 1],
[9, 2], [9, 3], [9, 4], [9, 5], [9, 6],
[9, 7], [9, 8], [10, 0], [10, 1], [10, 2],
[10, 3], [10, 4], [10, 5], [10, 6], [10, 7],
[10, 8], [11, 0], [11, 1], [11, 2], [11, 3],
[11, 4], [11, 5], [11, 6], [11, 7], [11, 8]
]
expect(image.all_array_indexes).to eql(result)
end
end
end
describe '#manhattan cells' do
it 'selects and returns only cells within n manhattan distance' do
image = Image.new([
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]
])
cells = [
[0, 2], [1, 1], [1, 2], [1, 3],
[2, 0], [2, 1], [2, 2], [2, 3],
[2, 4], [3, 1], [3, 2], [3, 3],
[4, 2]
]
expect(image.manhattan_cells(2,2,2)).to eql(cells)
end
context 'when pixel is in a corner' do
it 'return only cells in the dimensions of the array' do
image = Image.new([
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1],
])
cells = [
[9,8],[10,7],[10,8],[11,6],[11,7],[11,8]
]
expect(image.manhattan_cells(11,8,2)).to eql(cells)
end
end
end
end
end
@framallo
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Great work! congrats!

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