This is a companion gist to the article Sampling random variables and plotting histograms in Crystal
Your system has
Clone the files in this gist, then run the following once, to install the code dependencies.
shards install
You can now plot some histograms with
crystal normal_distribution.cr
and
crystal normal_vs_exp.cr
| require "statistics" | |
| require "ishi" | |
| require "tablo" | |
| include Statistics::Distributions | |
| # Turns a named tuple into tabular representation | |
| def table(data : NamedTuple) | |
| Tablo::Table.new(data.map { |k, v| [k, v] }, header_frequency: nil) { |t| | |
| t.add_column("coefficient") { |n| n[0] } | |
| t.add_column("value") { |n| n[1].as(Float64).round(3) } | |
| } | |
| end | |
| normal = Normal.new(mean: 0.8, std: 0.2) | |
| size = 10000 | |
| sample = (0...size).map { normal.rand } | |
| info = Statistics.describe(sample) | |
| puts table(info) | |
| bins = 100 | |
| sample_bins = Statistics.bin_count(sample, bins, edge: :centre) | |
| x = sample_bins.edges | |
| y = sample_bins.counts | |
| area = size * sample_bins.step | |
| normalized_y = y.map &./(area) | |
| # Evaluate the probability density function in `x` | |
| pdf = x.map { |x| normal.pdf(x) } | |
| Ishi.new do | |
| plot(x, normalized_y, title: "sample \\~ N(0.8, 0.04)", style: :boxes, fs: 0.25) | |
| .xlabel("value") | |
| .ylabel("frequency") | |
| plot(x, pdf, title: "N(0.8, 0.04)", lw: 2, ps: 0) | |
| end |
| require "statistics" | |
| require "ishi" | |
| include Statistics::Distributions | |
| normal = Normal.new(mean: 0.8, std: 0.2) | |
| expo = Exponential.new(lambda: 7) | |
| size = 10000 | |
| sample_1 = (0...size).map { normal.rand } | |
| sample_2 = (0...size).map { expo.rand } | |
| bins = 100 | |
| sample_1_bins = Statistics.bin_count(sample_1, bins, edge: :centre) | |
| sample_2_bins = Statistics.bin_count(sample_2, bins, edge: :centre) | |
| x_1 = sample_1_bins.edges | |
| area_1 = size * sample_1_bins.step | |
| y_1 = sample_1_bins.counts.map &./(area_1) | |
| normal_pdf = x_1.map { |x| normal.pdf(x) } | |
| x_2 = sample_2_bins.edges | |
| area_2 = size * sample_2_bins.step | |
| y_2 = sample_2_bins.counts.map &./(area_2) | |
| expo_pdf = x_2.map{|i| expo.pdf(i)} | |
| Ishi.new do | |
| plot(x_1, y_1, title: "X \\~ N(0.8, 0.04)", style: :boxes, fs: 0.25) | |
| plot(x_1, normal_pdf, title: "N(0.8, 0.04)", lw: 2, ps: 0) | |
| plot(x_2, y_2, title: "Y \\~ Exp(7)", style: :boxes, fs: 4) | |
| plot(x_2, expo_pdf, title: "Exp(7)", lw: 2, ps: 0) | |
| .xlabel("value") | |
| .ylabel("frequency") | |
| end |
| name: sampling_and_plotting | |
| version: 0.1.0 | |
| authors: | |
| - lbarasti <lbarasti@users.noreply.github.com> | |
| dependencies: | |
| ishi: | |
| github: toddsundsted/ishi | |
| branch: master | |
| statistics: | |
| github: lbarasti/statistics | |
| branch: master | |
| tablo: | |
| github: hutou/tablo | |
| version: 0.9.3 | |
| crystal: 0.34.0 | |
| license: MIT |
Output of normal_vs_exp.cr
Output of
normal_distribution.cr