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 80

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(\n        histogram.data, \n        breaks   = histogram.breaks, \n        xlab     = \"\#{x_label}\", \n        main     = \"\#{title || 'Histogram'}\", \n        freq     = \#{relative ? 'F' : 'T'},\n        cex.main = 0.9,\n        cex.lab  = 0.9,\n        cex.axis = 0.9\n      )\n    STR\n    \n    r.eval(\"abline(v = \#{x_arrow}, lty = 'dashed')\") if x_arrow\n    \n    r.eval(\"dev.off()\") if writing_file?(filename)\n  end\nend\n"

.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 76

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 113

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\")\n        matrix.data <- sparseMatrix(\n        i      = matrix.i,\n        j      = matrix.j,\n        x      = matrix.x,\n        index1 = F\n        )\n      STR\n      \n      generate_graph(\"Heatmap\") do\n        <<-STR\n          filtered.values <- Filter(function(i) { is.finite(i) & i != 0 }, matrix.x)\n          print(apply(as.matrix(matrix.data), 2, rev))\n          print(c(sort(filtered.values)[2], max(filtered.values)))\n        \n          image(\n            x    = 1:max(c(dim(matrix.data)[[1]], dim(matrix.data)[[2]])), \n            y    = 1:max(c(dim(matrix.data)[[1]], dim(matrix.data)[[2]])), \n            z    = as.matrix(matrix.data),\n            col  = rev(heat.colors(\#{num_colors})),\n            zlim = \#{forced_square ? \"c(sort(filtered.values)[2], max(filtered.values))\" : \"c(min(filtered.values), max(filtered.values))\"},\n            xlab = \"\#{x_label} (1-indexed)\",\n            ylab = \"\#{y_label} (1-indexed)\"\n          )\n          title(\"\#{title || 'Matrix Heatmap'}\")\n        STR\n      end\n    else\n      puts \"Please install the Matrix package for R before using this function.\"\n    end\n  end\nend\n"

.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(\n          line_graph.x.\#{index}, \n          line_graph.y.\#{index}, \n          col  = line.colors[\#{index + 1}],\n          type = \"\#{type}\",\n          pch  = \#{index}\n        )\n      STR\n    end\n    \n    r.eval <<-STR\n      title(\n        xlab     = \"\#{x_label}\", \n        ylab     = \"\#{y_label}\", \n        main     = \"\#{title || 'Line Graph'}\",\n        cex.main = .9,\n        cex.lab  = .9\n      )\n    STR\n      \n    if legend\n      r.eval <<-STR\n        legend(\n          \"\#{legend}\",\n          legend.titles,\n          bty = \"n\",\n          col = line.colors,\n          lty = rep(1, \#{data.size}),\n          pch = 0:\#{data.size},\n          cex = .9\n        )\n      STR\n    end\n    \n    r.eval(\"dev.off()\") if writing_file?(filename)\n  end\nend\n"

.roc(data, title = "", options = {}) ⇒ Object 



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# File 'lib/vienna_rna/graphing/r.rb', line 159

def roc(data, title = "", options = {})
  # data = [[true_score_1, true_score_2, ...], [false_score_1, false_score_2, ...]]

  if R.pull("ifelse('ROCR' %in% rownames(installed.packages()), 1, -1)") > 0

  else
    puts "Please install the ROCR package for R before using this function."
  end

  # roc_curve = ROC.curve_points({ 1 => data[0], -1 => data[1] }.inject([]) { |data, (truth, values)| data.concat(values.map { |i| [i, truth] })})
  # area      = roc_curve.each_cons(2).inject(0) do |sum, (a, b)| 
  #   delta_x, delta_y = b[0] - a[0], b[1] - a[1]
  #   sum + (delta_x * delta_y / 2 + delta_x * [a[1], b[1]].min)
  # end
  
  # options.merge!(output: "file") if options[:filename]
  # options.merge!({ plot: { title: "%s %s %.4f" % [title, "AUC:", area] } })
    
  # plot([{ x: roc_curve.map(&:first), y: roc_curve.map(&:last), style: "lines" }], options)
end