Module: ViennaRna::Graphing::R

Defined in:
lib/vienna_rna/graphing/r.rb

Class Method Summary collapse

Class Method Details

.graph(&block) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 5

def graph(&block)
  begin
    (yield (r_instance = RinRuby.new)).tap { r_instance.close }
  rescue RuntimeError => e
    raise unless e.message == "Unsupported data type on R's end"
  end
end

.histogram(data, title: nil, x_label: "Bins", num_bins: false, bin_size: 1, x_arrow: false, relative: false, filename: false) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 125

def histogram(data, title: nil, x_label: "Bins", num_bins: false, bin_size: 1, x_arrow: false, relative: false, filename: false)
  half     = bin_size / 2.0
  range    = Range.new((data.min - half).floor, (data.max + half).ceil)
  breaks   = num_bins ? num_bins : (range.min + half).step(range.max + half, bin_size).to_a
  
  graph do |r|
    r.assign("histogram.data", data)
    r.assign("histogram.breaks", breaks)
    
    r.eval("%s('%s', 6, 6)" % [
      writing_file?(filename) ? "pdf" : "quartz", 
      writing_file?(filename) ? filename : "Histogram", 
    ])
    
    r.eval "hist(\nhistogram.data,\nbreaks   = histogram.breaks,\nxlab     = \#{expressionify(x_label)},\nmain     = \#{expressionify(title || \"Histogram\")},\nfreq     = \#{relative ? 'F' : 'T'},\ncex.main = 0.9,\ncex.lab  = 0.9,\ncex.axis = 0.9\n)\n"
    
    r.eval("abline(v = #{x_arrow}, lty = 'dashed')") if x_arrow
    
    r.eval("dev.off()") if writing_file?(filename)
  end
end

.line_graph(data, title: nil, type: ?l, x_label: "Independent", y_label: "Dependent", filename: false) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 77

def line_graph(data, title: nil, type: ?l, x_label: "Independent", y_label: "Dependent", filename: false)
  overlay([{ data: data }], title: title, type: type, x_label: x_label, y_label: y_label, legend: false, filename: filename)
end

.matrix_heatmap(x, y, z, title: nil, x_label: "Column index", y_label: "Row index", filename: false, num_colors: 64) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 158

def matrix_heatmap(x, y, z, title: nil, x_label: "Column index", y_label: "Row index", filename: false, num_colors: 64)
  graph do |r|
    if r.pull("ifelse('Matrix' %in% rownames(installed.packages()), 1, -1)") > 0
      if forced_square = (x.max != y.max)
        x << [x, y].map(&:max).max
        y << [x, y].map(&:max).max
        z << 0
      end
      
      r.assign("matrix.i", x)
      r.assign("matrix.j", y)
      r.assign("matrix.x", z)
      r.eval "require(\"Matrix\")\nmatrix.data <- sparseMatrix(\ni      = matrix.i,\nj      = matrix.j,\nx      = matrix.x,\nindex1 = F\n)\n"
      
      generate_graph("Heatmap") do
        "filtered.values <- Filter(function(i) { is.finite(i) & i != 0 }, matrix.x)\nprint(apply(as.matrix(matrix.data), 2, rev))\nprint(c(sort(filtered.values)[2], max(filtered.values)))\n\nimage(\nx    = 1:max(c(dim(matrix.data)[[1]], dim(matrix.data)[[2]])),\ny    = 1:max(c(dim(matrix.data)[[1]], dim(matrix.data)[[2]])),\nz    = as.matrix(matrix.data),\ncol  = rev(heat.colors(\#{num_colors})),\nzlim = \#{forced_square ? \"c(sort(filtered.values)[2], max(filtered.values))\" : \"c(min(filtered.values), max(filtered.values))\"},\nxlab = \"\#{x_label} (1-indexed)\",\nylab = \"\#{y_label} (1-indexed)\"\n)\ntitle(\#{expressionify(title || \"Matrix Heatmap\")})\n"
      end
    else
      puts "Please install the Matrix package for R before using this function."
    end
  end
end

.overlay(data, title: nil, type: ?l, x_label: "Independent", y_label: "Dependent", legend: "topleft", filename: false) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 13

def overlay(data, title: nil, type: ?l, x_label: "Independent", y_label: "Dependent", legend: "topleft", filename: false)
  # data: [{ data: [[x_0, y_0], ..., [x_n, y_n]], legend: "Line 1" }, ...]
  
  x_points = data.map { |hash| hash[:data].map(&:first) }
  y_points = data.map { |hash| hash[:data].map(&:last) }
  x_range  = Range.new(x_points.map(&:min).min.floor, x_points.map(&:max).max.ceil)
  y_range  = Range.new(y_points.map(&:min).min.floor, y_points.map(&:max).max.ceil)
  
  graph do |r|
    r.eval("%s('%s', 6, 6)" % [
      writing_file?(filename) ? "pdf" : "quartz", 
      writing_file?(filename) ? filename : "Graph", 
    ])
    
    r.assign("legend.titles", data.each_with_index.map { |hash, index| hash[:legend] || "Line #{index + 1}" })
    r.eval("line.colors <- rainbow(%d)" % data.size)
    r.eval("plot(0, 0, type = 'n', cex = .75, cex.axis = .9, xlab = '', ylab = '', xlim = c(%d, %d), ylim = c(%d, %d))" % [
      x_range.min, x_range.max, y_range.min, y_range.max
    ])
    
    data.each_with_index do |hash, index|
      r.assign("line_graph.x.%d" % index, x_points[index])
      r.assign("line_graph.y.%d" % index, y_points[index])
      
      r.eval "lines(\nline_graph.x.\#{index},\nline_graph.y.\#{index},\ncol  = line.colors[\#{index + 1}],\ntype = \"\#{type}\",\npch  = \#{index}\n)\n"
    end
    
    r.eval "title(\nxlab     = \#{expressionify(x_label)},\nylab     = \#{expressionify(y_label)},\nmain     = \#{expressionify(title || \"Line Graph\")},\ncex.main = .9,\ncex.lab  = .9\n)\n"
      
    if legend
      r.eval "legend(\n\"\#{legend}\",\nlegend.titles,\nbty = \"o\",\nbg  = rgb(1, 1, 1, .5, 1),\ncol = line.colors,\nlty = rep(1, \#{data.size}),\npch = 0:\#{data.size},\ncex = .6\n)\n"
    end
    
    r.eval("dev.off()") if writing_file?(filename)
  end
end

.roc(data, title: nil, baseline: true, filename: false) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 85

def roc(data, title: nil, baseline: true, filename: false)
  # data: [[-0.894, 1.0], [-0.950, 1.0], [0.516, -1.0], ..., [0.815, -1.0], [0.740, -1.0]]
  auc            = ROC.auc(data)
  title_with_auc = title ? "%s (AUC: %.4f)" % [title, auc] : "AUC: %.4f" % auc
  overlay(
    [{ data: ROC.curve_points(data) }, { data: [[0, 0], [1, 1]] }], 
    title:    title_with_auc, 
    x_label:  "False positive rate", 
    y_label:  "True positive rate", 
    legend:   false, 
    filename: filename
  )
end

.roc_overlay(data, title: nil, auc_in_legend: true, filename: false) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 99

def roc_overlay(data, title: nil, auc_in_legend: true, filename: false)
  # [{ data: [[-0.894, 1.0], [-0.950, 1.0], [0.516, -1.0], ..., [0.815, -1.0], [0.740, -1.0]], legend: "ROC 1" }, ...]
  formatted_data = data.map do |hash|
    curve_points = ROC.curve_points(hash[:data])
    
    if auc_in_legend
      auc    = ROC.auc(hash[:data])
      legend = hash[:legend] ? "%s (AUC: %.4f)" % [hash[:legend], auc] : "AUC: %.4f" % auc
      
      hash.merge({ data: curve_points, legend: legend })
    else
      hash.merge({ data: curve_points })
    end
  end
  
  
  overlay(
    formatted_data, 
    title:    title, 
    x_label:  "False positive rate", 
    y_label:  "True positive rate", 
    legend:   "bottomright", 
    filename: filename
  )
end

.scatterplot(data, title: nil, x_label: "Independent", y_label: "Dependent", filename: false) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 81

def scatterplot(data, title: nil, x_label: "Independent", y_label: "Dependent", filename: false)
  line_graph(data, title: title || "Scatterplot", type: ?p, x_label: x_label, y_label: y_label, filename: filename)
end