Module: Rust::RBindings

Defined in:
lib/rust/core/rust.rb,
lib/rust/core/csv.rb,
lib/rust/plots/core.rb,
lib/rust/stats/tests.rb,
lib/rust/models/anova.rb,
lib/rust/stats/effsize.rb,
lib/rust/models/regression.rb,
lib/rust/stats/correlation.rb,
lib/rust/stats/descriptive.rb

Overview

Module that contains methods that allow to call R functions faster. Such methods have names resembling the ones available in R (e.g., cor, wilcox_test).

Instance Method Summary collapse

Instance Method Details

#aov(formula, data, **options) ⇒ Object 



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# File 'lib/rust/models/anova.rb', line 74

def aov(formula, data, **options)
    return ANOVAModel.generate(formula, data, **options)
end

#boxplot(*args, **options) ⇒ Object 



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# File 'lib/rust/plots/core.rb', line 362

def boxplot(*args, **options)
    result = Rust::Plots::BoxPlot.new
    options.each do |k, v|
        result[k] = v
    end
    
    result._do_not_override_options!
    
    args.each do |s|
        result.series(s)
    end
    
    result.show
end

#cliff_delta(d1, d2) ⇒ Object 



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# File 'lib/rust/stats/effsize.rb', line 95

def cliff_delta(d1, d2)
    Rust::EffectSize::CliffDelta.compute(d1, d2)
end

#cohen_d(d1, d2, **args) ⇒ Object 



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# File 'lib/rust/stats/effsize.rb', line 99

def cohen_d(d1, d2, **args)
    Rust::EffectSize::CohenD.compute(d1, d2)
end

#cor(d1, d2, **options) ⇒ Object 



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# File 'lib/rust/stats/correlation.rb', line 159

def cor(d1, d2, **options)
    return cor_test(d1, d2, **options).correlation
end

#cor_test(d1, d2, **options) ⇒ Object 



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# File 'lib/rust/stats/correlation.rb', line 163

def cor_test(d1, d2, **options)
    method = options[:method].to_s.downcase
    if "pearson".start_with?(method)
        return Rust::Correlation::Pearson.test(d1, d2)
    elsif "spearman".start_with?(method)
        return Rust::Correlation::Spearman.test(d1, d2)
    elsif "kendall".start_with?(method)
        return Rust::Correlation::Kendall.test(d1, d2)
    else
        raise "Unsupported method #{method}"
    end
end

#data_frame(*args) ⇒ Object 



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# File 'lib/rust/core/rust.rb', line 199

def data_frame(*args)
    Rust::DataFrame.new(*args)
end

#lm(formula, data, **options) ⇒ Object 



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# File 'lib/rust/models/regression.rb', line 241

def lm(formula, data, **options)
    independent = formula.right_part.split("+").map { |v| v.strip }
    return LinearRegressionModel.generate(formula.left_part, independent, data, **options)
end

#lmer(formula, data, **options) ⇒ Object 



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# File 'lib/rust/models/regression.rb', line 246

def lmer(formula, data, **options)
    independent = formula.right_part.split("+").map { |v| v.strip }
    
    RegressionModel.generate(
        LinearMixedEffectsModel,
        "lmer", 
        formula.left_part, 
        independent, 
        data,
        **options
    )
end

#mean(series) ⇒ Object 



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# File 'lib/rust/stats/descriptive.rb', line 138

def mean(series)
    Rust::Descriptive.mean(series)
end

#median(series) ⇒ Object 



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# File 'lib/rust/stats/descriptive.rb', line 142

def median(series)
    Rust::Descriptive.median(series)
end

#plot(x, y = (1..x.size).to_a, **options) ⇒ Object 



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# File 'lib/rust/plots/core.rb', line 350

def plot(x, y=(1..x.size).to_a, **options)
    result = Rust::Plots::ScatterPlot.new(x, y)
    
    options.each do |k, v|
        result[k] = v
    end
    
    result._do_not_override_options!
    
    result.show
end

#quantile(series, percentiles = [0.0, 0.25, 0.5, 0.75, 1.0]) ⇒ Object 



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# File 'lib/rust/stats/descriptive.rb', line 154

def quantile(series, percentiles = [0.0, 0.25, 0.5, 0.75, 1.0])
    Rust::Descriptive.quantile(series, percentiles)
end

#read_csv(filename, **options) ⇒ Object 



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# File 'lib/rust/core/csv.rb', line 119

def read_csv(filename, **options)
    Rust::CSV.read(filename, **options)
end

#sd(series) ⇒ Object 



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# File 'lib/rust/stats/descriptive.rb', line 150

def sd(series)
    Rust::Descriptive.standard_deviation(series)
end

#t_test(d1, d2, **args) ⇒ Object 



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# File 'lib/rust/stats/tests.rb', line 376

def t_test(d1, d2, **args)
    paired = args[:paired] || false
    if paired
        return Rust::StatisticalTests::T.paired(d1, d2)
    else
        return Rust::StatisticalTests::T.unpaired(d1, d2)
    end
end

#var(series) ⇒ Object 



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# File 'lib/rust/stats/descriptive.rb', line 146

def var(series)
    Rust::Descriptive.variance(series)
end

#wilcox_test(d1, d2, **args) ⇒ Object 



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# File 'lib/rust/stats/tests.rb', line 367

def wilcox_test(d1, d2, **args)
    paired = args[:paired] || false
    if paired
        return Rust::StatisticalTests::Wilcoxon.paired(d1, d2)
    else
        return Rust::StatisticalTests::Wilcoxon.unpaired(d1, d2)
    end
end

#write_csv(filename, dataframe, **options) ⇒ Object 



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# File 'lib/rust/core/csv.rb', line 123

def write_csv(filename, dataframe, **options)
    Rust::CSV.write(filename, dataframe, **options)
end