recursion method inside ruby minesweeper game stack level too deep - ruby
I am triggering endless recursion when trying to make a method that pulls up tiles when they are a zero. I have been testing by entering the following in irb:
class Board
attr_accessor :size, :board
def initialize(size = gets.chomp.to_i)
#size = size
#board = (1..#size).map { |x| ["L"] * #size }
end
def print_board
#board.map { |row| puts row.join }
end
end
class Mine
attr_accessor :proxi, :row, :col
def initialize(proxi)
#proxi = proxi
#row = 0
#col = 0
#random = Random.new
check_position
end
def check_position
if #proxi.board[#row - 1][#col - 1] != "L"
#row = #random.rand(1..#proxi.board.length)
#col = #random.rand(1..#proxi.board[0].length)
check_position
else
map_position
end
end
def map_position
#proxi.board[#row - 1][#col - 1] = "*"
end
end
b = Board.new(20)
m = (1..b.size * 2).map { |i| i = Mine.new(b) }
class Detector
attr_accessor :board, :proxi, :row, :col, :value
def initialize(board, proxi)
#board = board
#proxi = proxi
#row = 0
#col = 0
#value = 0
end
def mine?
if #proxi.board[#row - 1][#col - 1] == "*"
true
else
false
end
end
def detect
(#row - 1..#row + 1).each do |r|
(#col - 1..#col + 1).each do |c|
unless (r - 1 < 0 || r - 1 > #proxi.size - 1) || (c - 1 < 0 || c - 1 > #proxi.size - 1)
#value += 1 if #proxi.board[r - 1][c - 1] == "*"
end
end
end
end
def map_position
#proxi.board[#row - 1][#col - 1] = #value
#board.board[#row - 1][#col - 1] = #value
end
def recursion
if #proxi.board[#row - 1][#col - 1] == 0
(#row - 1..#row + 1).each do |r|
(#col - 1..#col + 1).each do |c|
unless (r - 1 < 0 || r - 1 > #proxi.size - 1) || (c - 1 < 0 || c - 1 > #proxi.size - 1)
#row, #col = r, c
detect
map_position
recursion
end
end
end
end
end
def reset
#row, #col, #value = 0, 0, 0
end
end
d = Detector.new(b, b)
b.print_board
If the output has plenty of free space in the upper right corner proceed to pasting the next part, else repaste.
d.row = 1
d.col = 1
d.mine?
d.detect
d.map_position
d.recursion
b.print_board
It will error out with a stack level too deep error at the recursion method. I know this is because it is having issues ending the recursive pattern. I thought my two unless statements deterring it from searching off the board would limit it to the area in the board. Plus the mines would force it to be limited in zeros it can expose. Maybe it is somehow writing spaces off the board or overwriting things on the board?
You don’t need a recursion here. Simply check each position for mines around:
Please always use 0-based arrays to eliminate lots of #blah - 1.
In detect you need to return immediately if there is a mine and set the #value otherwise:
def detect
return if #proxi.board[#row][#col] == '*'
value = 0 # no need to be global anymore
(#row - 1..#row + 1).each do |r|
(#col - 1..#col + 1).each do |c|
unless r < 0 || r >= #proxi.size || c < 0 || c >= #proxi.size
value += 1 if #proxi.board[r][c] == "*"
end
end
end
#proxi.board[#row][#col] = value
end
Now you don’t need map_position method at all. Simply check all the cells:
def check
(0..#proxi.size - 1).each do |r|
(0..#proxi.size - 1).each do |c|
#row, #col = r, c
detect
end
end
end
Hope it helps.
Exceeding the stack size is usually an indication that your recursion does not have the correct terminating condition. In your case, what mechanism is in place to prevent recursion from being called multiple times with the same #row #col pair? Note that of the 9 pairs that (#row - 1..#row + 1) (#col - 1..#col + 1) produce, one of those pairs is #row #col itself. The function will call itself infinitely many times!
A simple way to solve this would be to have something like a revealed array that keeps track of visited cells. Then recursion would mark each cell it visits as visited and return immediately if it is called on an already visited cell.
Additionally, your use of instance variables is extremely fragile here. Recursion relies on the fact that each function call has its own scope, but every call of recursion shares the same instance variables - which you're using to pass arguments! You should be using method arguments to keep the scopes distinct.
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I'm trying to use some ruby code that I've found in Github. I've downloaded the code and did the necessary imports the "requires" and tried to run it as it is described in the readme file on github repository. The code is the following: In the file pcset_test.rb the code is the following: require './pcset.rb' require 'test/unit' # # When possible, test cases are adapted from # Introduction to Post-Tonal Theory by Joseph N. Straus, # unless obvious or otherwise noted. # class PCSetTest < Test::Unit::TestCase def test_init #assert_raise(ArgumentError) {PCSet.new []} assert_raise(ArgumentError) {PCSet.new [1, 2, 3, 'string']} assert_raise(ArgumentError) {PCSet.new "string"} assert_raise(ArgumentError) {PCSet.new [1, 2, 3.6, 4]} assert_equal([0, 1, 2, 9], PCSet.new([0, 1, 2, 33, 13]).pitches) assert_equal([3, 2, 1, 11, 10, 0], PCSet.new_from_string('321bac').pitches) assert_equal([0,2,4,5,7,11,9], PCSet.new([12,2,4,5,7,11,9]).pitches) assert_nothing_raised() {PCSet.new []} end def test_inversion end def test_transposition end def test_multiplication end # # set normal prime forte # # 0,2,4,7,8,11 7,8,11,0,2,4 0,1,4,5,7,9 6-31 # 0,1,2,4,5,7,11 11,0,1,2,4,5,7 0,1,2,3,5,6,8 7-Z36 # 0,1,3,5,6,7,9,10,11 5,6,7,9,10,11,0,1,3 0,1,2,3,4,6,7,8,10 9-8 # def test_normal_form testPC = PCSet.new [0,4,8,9,11] assert_kind_of(PCSet, testPC.normal_form) assert_equal([8,9,11,0,4], testPC.normal_form.pitches) assert_equal([10,1,4,6], PCSet.new([1,6,4,10]).normal_form.pitches) assert_equal([2,4,8,10], PCSet.new([10,8,4,2]).normal_form.pitches) assert_equal([7,8,11,0,2,4], PCSet.new([0,2,4,7,8,11]).normal_form.pitches) assert_equal([11,0,1,2,4,5,7], PCSet.new([0,1,2,4,5,7,11]).normal_form.pitches) assert_equal([5,6,7,9,10,11,0,1,3], PCSet.new([0,1,3,5,6,7,9,10,11]).normal_form.pitches) end def test_prime_form assert_equal([0,1,2,6], PCSet.new([5,6,1,7]).prime.pitches) assert_equal([0,1,4], PCSet.new([2,5,6]).prime.pitches) assert_equal([0,1,4,5,7,9], PCSet.new([0,2,4,7,8,11]).prime.pitches) assert_equal([0,1,2,3,5,6,8], PCSet.new([0,1,2,4,5,7,11]).prime.pitches) assert_equal([0,1,2,3,4,6,7,8,10], PCSet.new([0,1,3,5,6,7,9,10,11]).prime.pitches) end def test_set_class testPcs = PCSet.new([2,5,6]) testPrime = testPcs.prime assert_equal([ [2,5,6], [3,6,7], [4,7,8], [5,8,9], [6,9,10], [7,10,11], [8,11,0],[9,0,1], [10,1,2],[11,2,3],[0,3,4], [1,4,5], [6,7,10],[7,8,11],[8,9,0], [9,10,1],[10,11,2],[11,0,3], [0,1,4], [1,2,5], [2,3,6], [3,4,7], [4,5,8], [5,6,9] ].sort, PCSet.new([2,5,6]).set_class.map{|x| x.pitches}) assert_equal(testPcs.set_class.map{|x| x.pitches}, testPrime.set_class.map{|x| x.pitches}) end def test_interval_vector assert_equal([2,1,2,1,0,0], PCSet.new([0,1,3,4]).interval_vector) assert_equal([2,5,4,3,6,1], PCSet.new([0,1,3,5,6,8,10]).interval_vector) assert_equal([0,6,0,6,0,3], PCSet.new([0,2,4,6,8,10]).interval_vector) end def test_complement assert_equal([6,7,8,9,10,11], PCSet.new([0,1,2,3,4,5]).complement.pitches) assert_equal([3,4,5], PCSet.new([0,1,2], 6).complement.pitches) end # # Test values from (Morris 1991), pages 105-111 # Citation: # Morris. Class Notes for Atonal Music Theory # Lebanon, NH. Frog Peak Music, 1991. # def test_invariance_vector assert_equal([1,0,0,0,5,6,5,5],PCSet.new([0,2,5]).invariance_vector) assert_equal([2,2,2,2,6,6,6,6],PCSet.new([0,1,6,7]).invariance_vector) assert_equal([6,6,6,6,6,6,6,6],PCSet.new([0,2,4,6,8,10]).invariance_vector) assert_equal([1,0,0,0,0,0,0,0],PCSet.new([0,1,2,3,4,5,8]).invariance_vector) assert_equal([1,0,0,1,0,0,0,0],PCSet.new([0,1,2,3,5,6,8]).invariance_vector) assert_equal([12,12,12,12,0,0,0,0],PCSet.new([0,1,2,3,4,5,6,7,8,9,10,11]).invariance_vector) end # # Test values from (Huron 1994). Huron rounds, thus the 0.01 margin of error. # Citation: # Huron. Interval-Class Content in Equally Tempered Pitch-Class Sets: # Common Scales Exhibit Optimum Tonal Consonance. # Music Perception (1994) vol. 11 (3) pp. 289-305 # def test_huron h1 = PCSet.new([0,1,2,3,4,5,6,7,8,9,10,11]).huron assert_in_delta(-0.2, h1[0], 0.01) assert_in_delta(0.21, h1[1], 0.01) h2 = PCSet.new([0,2,4,5,7,9,11]).huron assert_in_delta(4.76, h2[0], 0.01) assert_in_delta(0.62, h2[1], 0.01) end def test_coherence end end And in the file pcset.rb the folloing code: # # => PCSet Class for Ruby # => Beau Sievers # => Hanover, Fall 2008. # # # TODO: Make this a module to avoid namespace collisions. # Lilypond and MusicXML output # include Math def choose(n, k) return [[]] if n.nil? || n.empty? && k == 0 return [] if n.nil? || n.empty? && k > 0 return [[]] if n.size > 0 && k == 0 c2 = n.clone c2.pop new_element = n.clone.pop choose(c2, k) + append_all(choose(c2, k-1), new_element) end def append_all(lists, element) lists.map { |l| l << element } end def array_to_binary(array) array.inject(0) {|sum, n| sum + 2**n} end # the following method is horrifically inelegant # but avoids monkey-patching. # TODO: do this right, incl. error checking def pearsons(x, y) if !x.is_a?(Array) || !y.is_a?(Array) then raise StandardError, "x and y must be arrays", caller end if x.size != y.size then raise StandardError, "x and y must be same size", caller end sum_x = x.inject(0) {|sum, n| sum + n} sum_y = y.inject(0) {|sum, n| sum + n} sum_square_x = x.inject(0) {|sum, n| sum + n * n} sum_square_y = y.inject(0) {|sum, n| sum + n * n} xy = [] x.zip(y) {|a, b| xy.push(a * b)} sum_xy = xy.inject(0) {|sum, n| sum + n} num = sum_xy - ((sum_x * sum_y)/x.size) den = Math.sqrt((sum_square_x - ((sum_x*sum_x)/x.size)) * (sum_square_y - ((sum_y*sum_y)/x.size))) (num/den) end class PCSet include Comparable attr_reader :pitches, :base, :input def initialize(pcarray, base = 12) if pcarray.instance_of?(Array) && pcarray.all?{|pc| pc.instance_of?(Fixnum)} #base, #input = base, pcarray #pitches = pcarray.map{ |x| x % #base }.uniq else raise ArgumentError, "Improperly formatted PC array", caller end end def PCSet.new_from_string(pcstring, base = 12) if base > 36 then raise StandardError, "Use PCSet.new to create pcsets with a base larger than 36", caller end pcarray = [] pcstring.downcase.split(//).each do |c| if c <= 'z' and c >= '0' then pcarray.push(c.to_i(36)) end end PCSet.new pcarray, base end def <=>(pcs) #pitches <=> pcs.pitches end def [](index) #pitches[index] end # Intersection def &(other) PCSet.new #pitches & other.pitches end # Union def |(other) PCSet.new #pitches | other.pitches end def inspect #pitches.inspect end def length #pitches.length end def invert(axis = 0) PCSet.new #pitches.map {|x| (axis-x) % #base} end def invert!(axis = 0) #pitches.map! {|x| (axis-x) % #base} end def transpose(interval) PCSet.new #pitches.map {|x| (x + interval) % #base} end def transpose!(interval) #pitches.map! {|x| (x + interval) % #base} end def multiply(m = 5) PCSet.new #pitches.map {|x| (x * m) % #base} end def multiply!(m = 5) #pitches.map! {|x| (x * m) % #base} end def zero transpose(-1 * #pitches[0]) end def zero! transpose!(-1 * #pitches[0]) end def transpositions (0..(#base-1)).to_a.map{|x| #pitches.map {|y| (y + x) % #base}}.sort.map {|x| PCSet.new x} end def transpositions_and_inversions(axis = 0) transpositions + invert(axis).transpositions end # # Normal form after Straus. Morris and AthenaCL do this differently. # def normal_form tempar = #pitches.sort arar = [] # [[1,4,7,8,10],[4,7,8,10,1], etc.] get each cyclic variation tempar.each {arar.push PCSet.new(tempar.unshift(tempar.pop))} most_left_compact(arar) end def normal_form! #pitches = normal_form.pitches end def is_normal_form? self.pitches == self.normal_form.pitches end def set_class transpositions_and_inversions.map{|pcs| pcs.normal_form}.sort end def prime most_left_compact([normal_form.zero, invert.normal_form.zero]) end def prime! self.pitches = self.prime.pitches end def is_prime? self.pitches == self.prime.pitches end def complement new_pitches = [] #base.times do |p| if !#pitches.include? p then new_pitches.push p end end PCSet.new new_pitches end def full_interval_vector pairs = choose(#pitches, 2) # choose every pc pair intervals = pairs.map {|x| (x[1] - x[0]) % #base} # calculate every interval i_vector = Array.new(#base-1).fill(0) intervals.each {|x| i_vector[x-1] += 1} # count the intervals i_vector end def interval_vector i_vector = full_interval_vector (0..((#base-1)/2)-1).each {|x| i_vector[x] += i_vector.pop} i_vector end # # Morris's invariance vector # def invariance_vector(m = 5) t = transpositions.map!{|pcs| self & pcs} ti = invert.transpositions.map!{|pcs| self & pcs} tm = multiply(m).transpositions.map!{|pcs| self & pcs} tmi = invert.multiply(m).transpositions.map!{|pcs| self & pcs} tc = complement.transpositions.map!{|pcs| self & pcs} tic = complement.invert.transpositions.map!{|pcs| self & pcs} tmc = complement.multiply(m).transpositions.map!{|pcs| self & pcs} tmic = complement.invert.multiply(m).transpositions.map!{|pcs| self & pcs} [t, ti, tm, tmi, tc, tic, tmc, tmic].map{|x| x.reject{|pcs| pcs.pitches != #pitches}.length} end # Huron's aggregate dyadic consonance measure. # Huron. Interval-Class Content in Equally Tempered Pitch-Class Sets: # Common Scales Exhibit Optimum Tonal Consonance. # Music Perception (1994) vol. 11 (3) pp. 289-305 def huron if #base != 12 then raise StandardError, "PCSet.huron only makes sense for mod 12 pcsets", caller end # m2/M7 M2/m7 m3/M6 M3/m6 P4/P5 A4/d5 huron_table = [-1.428, -0.582, 0.594, 0.386, 1.240, -0.453] interval_consonance = [] interval_vector.zip(huron_table) {|x, y| interval_consonance.push(x * y) } aggregate_dyadic_consonance = interval_consonance.inject {|sum, n| sum + n} [aggregate_dyadic_consonance, pearsons(interval_vector, huron_table)] end # # Balzano's vector of relations. Citation for all Balzano methods: # # Balzano. "The Pitch Set as a Level of Description for Studying Musical # Pitch Perception" in Music, Mind, and Brain ed. Clynes. Plenum Press. 1982. # def vector_of_relations (0..length-1).to_a.map do |i| (0..length-1).to_a.map do |j| (#pitches[(i + j) % length] - #pitches[i]) % #base end end end # # Checks if the set satisfies Balzano's uniqueness. # def is_unique? vector_of_relations.uniq.size == vector_of_relations.size end # # Checks if the set satisfies Balzano's scalestep-semitone coherence. # For all s[i] and s[i1]: # j < k => v[i][j] < v[i1][k] # Where j and k are scalestep-counting indices. # And unless v[i][j] == 6 (a tritone), in which case the strict inequality is relaxed. # def is_coherent? v = vector_of_relations truth_array = [] all_pair_indices = choose((0..length-1).to_a, 2) all_pair_indices.each do |i, i1| all_pair_indices.each do |j, k| if v[i][j] == 6 truth_array.push(v[i][j] <= v[i1][k]) else truth_array.push(v[i][j] < v[i1][k]) end if v[i1][j] == 6 truth_array.push(v[i1][j] <= v[i][k]) else truth_array.push(v[i1][j] < v[i][k]) end end end !truth_array.include?(false) end # # Strict Balzano coherence, no inequality relaxation for tritones. # def is_strictly_coherent? v = vector_of_relations truth_array = [] all_pair_indices = choose((0..length-1).to_a, 2) all_pair_indices.each do |i, i1| all_pair_indices.each do |j, k| truth_array.push(v[i][j] < v[i1][k]) truth_array.push(v[i1][j] < v[i][k]) end end !truth_array.include?(false) end def notes(middle_c = 0) noteArray = ['C','C#','D','D#','E','F','F#','G','G#','A','A#','B'] if #base != 12 then raise StandardError, "PCSet.notes only makes sense for mod 12 pcsets", caller end out_string = String.new transpose(-middle_c).pitches.each do |p| out_string += noteArray[p] + ", " end out_string.chop.chop end def info print "modulo: #{#base}\n" print "raw input: #{#input.inspect}\n" print "pitch set: #{#pitches.inspect}\n" print "notes: #{notes}\n" print "normal: #{normal_form.inspect}\n" print "prime: #{prime.inspect}\n" print "interval vector: #{interval_vector.inspect}\n" print "invariance vector: #{invariance_vector.inspect}\n" print "huron ADC: #{huron[0]} pearsons: #{huron[1]}\n" print "balzano coherence: " if is_strictly_coherent? print "strictly coherent\n" elsif is_coherent? print "coherent\n" else print "false\n" end end # def lilypond # # end # # def musicXML # # end ############################################################################### private # # Convert every pitch array to a binary representation, e.g.: # [0,2,4,8,10] -> 010100010101 # 2^n: BA9876543210 # The smallest binary number is the most left-compact. # def most_left_compact(pcset_array) if !pcset_array.all? {|pcs| pcs.length == pcset_array[0].length} raise ArgumentError, "PCSet.most_left_compact: All PCSets must be of same cardinality", caller end zeroed_pitch_arrays = pcset_array.map {|pcs| pcs.zero.pitches} binaries = zeroed_pitch_arrays.map {|array| array_to_binary(array)} winners = [] binaries.each_with_index do |num, i| if num == binaries.min then winners.push(pcset_array[i]) end end winners.sort[0] end end I'm calling them as follows: > my_pcset = PCSet.new([0,2,4,6,8,10]) > my_pcset2 = PCSet.new([1,5,9]) It shoud return: > my_pcset = PCSet.new([0,2,4,6,8,10]) => [0, 2, 4, 6, 8, 10] > my_pcset2 = PCSet.new([1,5,9]) => [1, 5, 9] But is returning nothing. The code is available on github Thanks
Try this in terminal: irb -r ./path_to_directory/pcset.rb and then initialize the objects.
I think the documentation for the repo is bad as it does not explain how you should be running this. The result of my_pcset = PCSet.new([0,2,4,6,8,10]) should set my_pcset to an instance of a PCSet not an array, so these lines from the README file are confusing at best. 3. How to use it Make new PCSets: my_pcset = PCSet.new([0,2,4,6,8,10]) => [0, 2, 4, 6, 8, 10] my_pcset2 = PCSet.new([1,5,9]) => [1, 5, 9] Looking at the code, I see inspect has been delegated to #pitches def inspect #pitches.inspect end I think if you inspect my_pcset you will get the expected result. my_pcset = PCSet.new([0,2,4,6,8,10]) p my_pcset # will print [0, 2, 4, 6, 8, 10] or `my_pcset.inspect` will return what you are expecting.
very simple ruby programing, getting into infinite loop
I'm asked to write the ruby program that generate the output based the given command, The full description I'm really new in ruby (maybe few hours that I have started ruby) When I run the program I get into infinite loop, I don't understand why. Thank you. What I have done so far: # MyVector Class class MyVector def initialize (a) if !(a.instance_of? Array) raise "ARGUMENT OF INITIALIZER MUST BE AN ARRAY" else #array = a end end def array #array end def to_s #array.to_s end def length #array.length end def [](i) #array[i] end def each2(a) raise Error, "INTEGER IS NOT LIKE VECTOR" if a.kind_of?(Integer) Vector.Raise Error if length != a.length return to_enum(:each2, a) unless block_given? length.times do |i| yield #array[i], a[i] end self end def * (a) Vector.Raise Error if length != a.length p = 0 each2(a) {|a1, a2|p += a1 * a2} p end end # MyMatrix Class class MyMatrix def initialize a #array=Array.new(a.length) i=0 while(i<a.length) #array[i]=MyVector.new(a[i]) end end def to_s #array.to_s end def transpose size=vectors[0].length arr= Array.new(size) i=0 while i<size a=Array.new(vector.length) j=0 while j<a.length a[j]=vectors[j].arr[i] j+=1 end arr[i]=a i+=1 end arr[i]=a i+=1 end def *m if !(m instance_of? MyMatrix) raise Error a=Array.new(#array.length) i=0 while (i<#array.length) a[i]=#array[i]*m i=i+1 end end end end Input: Test code v = MyVector.new([1,2,3]) puts "v = " + v.to_s v1 = MyVector.new([2,3,4]) puts "v1 = " + v1.to_s puts "v * v1 = " + (v * v1).to_s m = MyMatrix.new([[1,2], [1, 2], [1, 2]]) puts "m = " + m.to_s + "\n" puts "v * m = " + (v * m).to_s m1 = MyMatrix.new([[1, 2, 3], [2, 3, 4]]) puts "m1 = " + m1.to_s + "\n" puts "m * m1 = " + (m * m1).to_s puts "m1 * m = " + (m1 * m).to_s Desired Output: v = 1 2 3 v1 = 2 3 4 v * v1 = 20 m = 1 2 1 2 1 2 v * m = 6 12 m1 = 1 2 3 2 3 4 m * m1 = 5 8 11 5 8 11 5 8 11 m1 * m = 6 12 9 18
To answer the infinite loop issue, it looks like you forgot to add a i += 1 in the #initialize method of Matrix class. However, you will encounter more errors further in the code since, for example, you're checking length of the Matrix object which is undefined, and iterating over the Matrix object in each2 defined inside of the Vector class which needs the object to be an Enumerable (Array/Hash etc). These will throw an error as the Matrix class is not an Enumerator. These are some good resources to help you learn how the powerful Enumerator module works. Once you get familiar with the syntax and structure, be sure to use the Pry tool. It will be your best friend for debugging Ruby code.
Ruby Pascal's triangle generator with memoization
I am attempting to memoize my implementation of a Pascal's triangle generator, as a Ruby learning experiment. I have the following working code: module PascalMemo #cache = {} def PascalMemo::get(r,c) if #cache[[r,c]].nil? then if c == 0 || c == r then #cache[[r,c]] = 1 else #cache[[r,c]] = PascalMemo::get(r - 1, c) + PascalMemo::get(r - 1, c - 1) end end #cache[[r,c]] end end def pascal_memo (r,c) PascalMemo::get(r,c) end Can this be made more concise? Specifically, can I create a globally-scoped function with a local closure more simply than this?
def pascal_memo cache = [[1]] get = lambda { |r, c| ( cache[r] or cache[r] = [1] + [nil] * (r - 1) + [1] )[c] or cache[r][c] = get.(r - 1, c) + get.(r - 1, c - 1) } end p = pascal_memo p.( 10, 7 ) #=> 120 Please note that the above construct does achieve memoization, it is not just a simple recursive method.
Can this be made more concise? It seems pretty clear, IMO, and moduleing is usually a good instinct. can I create a globally-scoped function with a local closure more simply than this? Another option would be a recursive lambda: memo = {} pascal_memo = lambda do |r, c| if memo[[r,c]].nil? if c == 0 || c == r memo[[r,c]] = 1 else memo[[r,c]] = pascal_memo[r - 1, c] + pascal_memo[r - 1, c - 1] end end memo[[r,c]] end pascal_memo[10, 2] # => 45
I have found a way to accomplish what I want that is slightly more satisfactory, since it produces a function rather than a lambda: class << self cache = {} define_method :pascal_memo do |r,c| cache[[r,c]] or (if c == 0 or c == r then cache[[r,c]] = 1 else nil end) or cache[[r,c]] = pascal_memo(r-1,c) + pascal_memo(r-1,c-1) end end This opens up the metaclass/singleton class for the main object, then uses define_method to add a new method that closes over the cache variable, which then falls out of scope for everything except the pascal_memo method.
Stack level too deep error in ruby's recursive call
I am trying to implement the quick sort algorithm using ruby. See what I did: class Array def quick_sort #line 14 less=[];greater=[] if self.length<=1 self[0] else i=1 while i<self.length if self[i]<=self[0] less << self[i] else greater << self[i] end i=i+1 end end less.quick_sort + self[0] + greater.quick_sort #line 29 end end [1,3,2,5,4].quick_sort #line 32 This generated the error: bubble_sort.rb:29:in `quick_sort': stack level too deep (SystemStackError) from bubble_sort.rb:29:in `quick_sort' from bubble_sort.rb:32 Why is this happening?
I think the problem in your example was you needed an explicit return. if self.length<=1 self[0] should have been return [] if self == [] and less.quick_sort + self[0] + greater.quick_sort #line 29 should have been less.quick_sort + [self[0]] + greater.quick_sort #line 29 Here is a working example class Array def quick_sort return [] if self == [] pivotal = self.shift; less, greater = [], [] self.each do |x| if x <= pivotal less << x else greater << x end end return less.quick_sort + [pivotal] + greater.quick_sort end end [1,3,2,5,4].quick_sort # => [1, 2, 3, 4, 5]
less.quick_sort + self[0] + greater.quick_sort This line is outside of the if statement, so it gets executed whether self.length<=1 is true or not. Consequently the method recurses infinitely, which causes the stack to overflow. It should also be pointed out that self[0] does not return an array (unless self is an array of arrays), so it does not make sense to use Array#+ on it. Nor does it make sense as a return value for your quick_sort method.
In that part you should not handle the "=" case. Only < and > should be handled. Therefore your algorithm never stops and causes an infinite recursion. if self[i]<=self[0] less << self[i] else greater << self[i] end
more ruby way of doing project euler #2
I'm trying to learn Ruby, and am going through some of the Project Euler problems. I solved problem number two as such: def fib(n) return n if n < 2 vals = [0, 1] n.times do vals.push(vals[-1]+vals[-2]) end return vals.last end i = 1 s = 0 while((v = fib(i)) < 4_000_000) s+=v if v%2==0 i+=1 end puts s While that works, it seems not very ruby-ish—I couldn't come up with any good purely Ruby answer like I could with the first one ( puts (0..999).inject{ |sum, n| n%3==0||n%5==0 ? sum : sum+n }).
For a nice solution, why don't you create a Fibonacci number generator, like Prime or the Triangular example I gave here. From this, you can use the nice Enumerable methods to handle the problem. You might want to wonder if there is any pattern to the even Fibonacci numbers too. Edit your question to post your solution... Note: there are more efficient ways than enumerating them, but they require more math, won't be as clear as this and would only shine if the 4 million was much higher. As demas' has posted a solution, here's a cleaned up version: class Fibo class << self include Enumerable def each return to_enum unless block_given? a = 0; b = 1 loop do a, b = b, a + b yield a end end end end puts Fibo.take_while { |i| i < 4000000 }. select(&:even?). inject(:+)
My version based on Marc-André Lafortune's answer: class Some #a = 1 #b = 2 class << self include Enumerable def each 1.upto(Float::INFINITY) do |i| #a, #b = #b, #a + #b yield #b end end end end puts Some.take_while { |i| i < 4000000 }.select { |n| n%2 ==0 } .inject(0) { |sum, item| sum + item } + 2
def fib first, second, sum = 1,2,0 while second < 4000000 sum += second if second.even? first, second = second, first + second end puts sum end
You don't need return vals.last. You can just do vals.last, because Ruby will return the last expression (I think that's the correct term) by default.
fibs = [0,1] begin fibs.push(fibs[-1]+fibs[-2]) end while not fibs[-1]+fibs[-2]>4000000 puts fibs.inject{ |sum, n| n%2==0 ? sum+n : sum }
Here's what I got. I really don't see a need to wrap this in a class. You could in a larger program surely, but in a single small script I find that to just create additional instructions for the interpreter. You could select even, instead of rejecting odd but its pretty much the same thing. fib = Enumerator.new do |y| a = b = 1 loop do y << a a, b = b, a + b end end puts fib.take_while{|i| i < 4000000} .reject{|x| x.odd?} .inject(:+)
That's my approach. I know it can be less lines of code, but maybe you can take something from it. class Fib def first #p0 = 0 #p1 = 1 1 end def next r = if #p1 == 1 2 else #p0 + #p1 end #p0 = #p1 #p1 = r r end end c = Fib.new f = c.first r = 0 while (f=c.next) < 4_000_000 r += f if f%2==0 end puts r
I am new to Ruby, but here is the answer I came up with. x=1 y=2 array = [1,2] dar = [] begin z = x + y if z % 2 == 0 a = z dar << a end x = y y = z array << z end while z < 4000000 dar.inject {:+} puts "#{dar.sum}"
def fib_nums(num) array = [1, 2] sum = 0 until array[-2] > num array.push(array[-1] + array[-2]) end array.each{|x| sum += x if x.even?} sum end