Ruby Code-Cutting (few lines as possible) - ruby

So the code below is what I'm trying to cut down to as few lines as possible. Any other ruby tricks out there I could use to shorten it? I appreciate all help anyone can offer.
Article Class:
class Article
attr_accessor :id, :price, :quantity
def initialize(id, price, quantity)
#id, #price, #quantity = id, Float(price), quantity.to_i
end
end
Order Class:
class Order
def initialize(name)
#a, i = [], 0
input = File.open(name, "r")
while(id = input.gets.chomp)
j, price = 0, input.gets.chomp
while(j<#a.length)
if(#a[j].id.eql?(id.to_i))
#a[j].quantity += 1
end
end
else
#a[i] = new Article(id,price,1)
i+=1
end
end
end
def orderCost
sum = 0
#a.each { |e| sum+=(e.price * e.quantity)}
sum = ((sum*1.07) + 2.99)
end
def displaySelectArticles
min, max = #a[0], #a[0]
#a.each do |e|
if(min.cost > e.cost)
min = e
end
if(max.cost < e.cost)
max = e
end
sum += e.cost*e.quantity and q += e.quantity
end
puts "Min: #{min.cost} | Max: #{max.cost} | Avg: #{Float(sum)/q}"
end
end

I did my best here but your initialize method didnt make any logical sense to me. Hopefully this can at least guide you into the right direction. Disclaimer: None of this was tested and I wrote it off of what methods I could remember.
class Order
def initialize(name)
#a, i = [], 0
File.readlines(name) do |line|
# This while loop makes no sense to me
# Seems like a surefire infiniteloop because if id = 3, it is always true
# Maybe you meant to do an operator like == for comparison
while(id = line)
j, price = 0, line
while j < #a.length
#a[j].quantity += 1 if(#a[j].id.eql?(id.to_i))
end
else
#a[i] = new Article(id, price, 1)
i += 1
end
end
end
def orderCost
# I would probably make this two lines because its unreadable
(#a.inject(0) { |accum, e| accum + (e.price * e.quantity) } * 1.07) + 2.99
end
def displaySelectArticles
min, max = #a[0], #a[0]
#a.each do |e|
min = e if min.cost > e.cost
max = e if max.cost < e.cost
sum += e.cost * e.quantity
q += e.quantity # I have no idea how you got a q
end
puts "Min: #{min.cost} | Max: #{max.cost} | Avg: #{Float(sum)/q}"
end
end

The Article class needs serious attention because of that jumble of junk where
three variables are assigned at the same time. Split that out into three very
simple assignments:
class Article
attr_accessor :id, :price, :quantity
def initialize(id, price, quantity)
#id = id
#price = price.to_f
#quantity = quantity.to_i
end
end
Using x.to_f is preferable to Float(x), it's a gentler approach to
converting. If you're doing financial calculations I'd stronly encourage
you to use something like BigDecimal
as floating point numbers are notoriously problematic. $1.99 has a way of
becoming $1.989999423489 which when rounded can appear to "lose" a cent here
or there. The BigDecimal class avoids this by representing values as exact.
The rest is basically attacking the problem of not using Enumerable
effectively and instead writing your own routines to do what should be simple:
class Order
def initialize(name)
#items = [ ]
File.open(name, "r") do |input|
while(id = input.gets.chomp)
price = input.gets.chomp
# find locates the first matching thing in the array, if any.
existing = #items.find do |item|
item.id == id
end
if (existing)
existing.quantity += 1
else
items << Article.new(id, price, 1)
end
end
end
def item_cost
# Inject is good at iterating and accumulating
#items.inject(0.0) do |sum, item|
sum + item.price * item.quantity
end
end
def item_count
#items.inject(0) do |sum, item|
sum + item.quantity
end
end
def order_cost
item_cost * 1.07 + 2.99
end
def display_select_articles
# minmax_by finds min and max entries based on arbitrary criteria
min, max = #items.minmax_by { |item| item.price }
sum = item_cost
count = item_count
puts "Min: %f | Max: %f | Avg: %f" % [
min ? min.cost : 0.0,
max ? max.cost : 0.0,
count > 0.0 ? (sum / count) : 0.0
]
end
end
Whenever possible go with the grain, and that means using Ruby's structures and their native methods. The more you deviate from this the more code you'll have to write, and the uglier your code will get. Sometimes you're solving a difficult problem and you have no choice, but this example is not one of those cases. Everything here is simpler if you just do it the Ruby way.

Related

ruby packing variables and monkey patching

Okay so this is the code:
class Board
attr_reader :size
def initialize n
#grid = Array.new(n) {Array.new(n,:N)}
#size = n * n
end
def [] position
row, col = position
#grid[row][col]
end
def []= position, val
row, col = position
#grid[row][col] = val
end
def num_ships
#grid.flatten.count(:S)
end
def attack position
if self[position] == :S
self[position] = :H
puts "you sunk my battleship"
return true
else
self[position] = :X
return false
end
end
def place_random_ships
max_ships = #size * 0.25
while self.num_ships < max_ships
row = rand(0...#grid.length)
col = rand(0...#grid.length)
position = [row,col]
self[position] = :S
end
end
end
But,
def place_random_ships
max_ships = #size * 0.25
while self.num_ships < max_ships
row = rand(0...#grid.length)
col = rand(0...#grid.length)
position = [row,col]
self[position] = :S
end
end
this works, and does what it's suppose to, but when I avoid packing [row,col] and add it directly it does not work.
def place_random_ships
max_ships = #size * 0.25
while self.num_ships < max_ships
row = rand(0...#grid.length)
col = rand(0...#grid.length)
self[row,col] = :S
end
end
I'm still new to programming, so please try to explain the issue to where I can understand it, or tell me the problem, so I can google it to get a better understanding please.
The issue is that you defined []= to take 2 argument, and array and a value.
def []= position, val
row, col = position
#grid[row][col] = val
end
With your current implementation you would need to call it like this
foo[[row,col]] = :S
What you might want to to is define []= like this:
def []= row, col, val
#grid[row][col] = val
end
then when you want to pass the array position you can use the array spread operator. With this implementation both of these calls will work.
position = [1,2]
foo[1,2] = :S
foo[*position] = :S
if you do that you probably would want to define [] the same way.
def [] row,col
#grid[row][col]
end

How to implement Java's Comparable module in Ruby

I'm currently going over Robert Sedgewick's Algorithms book. In the book for the implementation of a Priority Queue there is the use of the Comparable module. While going over the top k frequent elements leetcode problem I noticed that there would be an error in my Ruby implementation.
def top_k_frequent(nums, k)
ans = []
h = Hash.new(0)
nums.each do |num|
h[num] += 1
end
heap = Heap.new
h.each do |k,v|
heap.insert({k => v})
end
k.times do
a = heap.del_max
ans.push(a.keys[0])
end
ans
end
class Heap
def initialize
#n = 0
#pq = []
end
def insert(v)
#pq[#n += 1] = v
swim(#n)
end
def swim(k)
while k > 1 && less((k / 2).floor, k)
swap((k / 2).floor, k)
k = k/2
end
end
def swap(i, j)
temp = #pq[i]
#pq[i] = #pq[j]
#pq[j] = temp
end
def less(i, j)
#pq[i].values[0] < #pq[j].values[0]
end
def del_max
max = #pq[1]
swap(1, #n)
#n -= 1
#pq[#n + 1] = nil
sink(1)
max
end
def sink(k)
while 2 * k <= #n
j = 2 * k
if !#pq[j + 1].nil?
j += 1 if j > 1 && #pq[j].values[0] < #pq[j + 1].values[0]
end
break if !less(k, j)
swap(k, j)
k = j
end
end
end
Above is the Java Priority Queue implementation.
Ruby's comparable operator is <=> which will return one of -1, 0, 1 and nil (nil mean could not compare).
In order to compare two objects , both need to implement a method def <=>(other). This is not on Object, so is not available on any objects that don't implement it or extend from a class that does implement it. Numbers and Strings, for example, do have an implementation. Hashes do not.
I think in your case, the issue is slightly different.
When you call queue.insert(my_hash) what you're expecting is for the algorithm to break up my_hash and build from that. Instead, the algorithm takes the hash as a single, atomic object and inserts that.
If you add something like:
class Tuple
attr_accessor :key, :value
def initialize(key, value)
#key = key
#value = value
end
def <=>(other)
return nil unless other.is_a?(Tuple)
value <=> other.value
end
end
then this will allow you to do something like:
hsh = { 1 => 3, 2 => 2, 3 => 1}
tuples = hsh.map { |k, v| Tuple.new(k, v) }
tuples.each { |tuple| my_heap.insert(tuple) }
you will have all of your data in the heap.
When you retrieve an item, it will be a tuple, so you can just call item.key and item.value to access the data.

How do I fix a problem to call a function in Ruby?

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.

Euler 23 in Ruby

All right. I think I have the right idea to find the solution to Euler #23 (The one about finding the sum of all numbers that can't be expressed as the sum of two abundant numbers).
However, it is clear that one of my methods is too damn brutal.
How do you un-brute force this and make it work?
sum_of_two_abunds?(num, array) is the problematic method. I've tried pre-excluding certain numbers and it's still taking forever and I'm not even sure that it's giving the right answer.
def divsum(number)
divsum = 1
(2..Math.sqrt(number)).each {|i| divsum += i + number/i if number % i == 0}
divsum -= Math.sqrt(number) if Math.sqrt(number).integer?
divsum
end
def is_abundant?(num)
return true if divsum(num) > num
return false
end
def get_abundants(uptonum)
abundants = (12..uptonum).select {|int| is_abundant?(int)}
end
def sum_of_two_abunds?(num, array)
#abundant, and can be made from adding two abundant numbers.
array.each do |abun1|
array.each do |abun2|
current = abun1+abun2
break if current > num
return true if current == num
end
end
return false
end
def non_abundant_sum
ceiling = 28123
sum = (1..23).inject(:+) + (24..ceiling).select{|i| i < 945 && i % 2 != 0}.inject(:+)
numeri = (24..ceiling).to_a
numeri.delete_if {|i| i < 945 && i % 2 != 0}
numeri.delete_if {|i| i % 100 == 0}
abundants = get_abundants(ceiling)
numeri.each {|numerus| sum += numerus if sum_of_two_abunds?(numerus, abundants) == false}
return sum
end
start_time = Time.now
puts non_abundant_sum
#Not enough numbers getting excluded from the total.
duration = Time.now - start_time
puts "Took #{duration} s "
Solution 1
A simple way to make it a lot faster is to speed up your sum_of_two_abunds? method:
def sum_of_two_abunds?(num, array)
array.each do |abun1|
array.each do |abun2|
current = abun1+abun2
break if current > num
return true if current == num
end
end
return false
end
Instead of that inner loop, just ask the array whether it contains num - abun1:
def sum_of_two_abunds?(num, array)
array.each do |abun1|
return true if array.include?(num - abun1)
end
false
end
That's already faster than your Ruby code, since it's simpler and running faster C code. Also, now that that idea is clear, you can take advantage of the fact that the array is sorted and search num - abun1 with binary search:
def sum_of_two_abunds?(num, array)
array.each do |abun1|
return true if array.bsearch { |x| num - abun1 <=> x }
end
false
end
And making that Rubyish:
def sum_of_two_abunds?(num, array)
array.any? do |abun1|
array.bsearch { |x| num - abun1 <=> x }
end
end
Now you can get rid of your own special case optimizations and fix your incorrect divsum (which for example claims that divsum(4) is 5 ... you should really compare against a naive implementation that doesn't try any square root optimizations).
And then it should finish in well under a minute (about 11 seconds on my PC).
Solution 2
Or you could instead ditch sum_of_two_abunds? entirely and just create all sums of two abundants and nullify their contribution to the sum:
def non_abundant_sum
ceiling = 28123
abundants = get_abundants(ceiling)
numeri = (0..ceiling).to_a
abundants.each { |a| abundants.each { |b| numeri[a + b] = 0 } }
numeri.compact.sum
end
That runs on my PC in about 3 seconds.

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

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