// Generated by CoffeeScript 1.9.2 (function() { var get_z_scores, redraw_prob_plot, root; root = typeof exports !== "undefined" && exports !== null ? exports : this; get_z_scores = function(n) { var i, j, osm_uniform, ref, x; osm_uniform = new Array(n); osm_uniform[n - 1] = Math.pow(0.5, 1.0 / n); osm_uniform[0] = 1 - osm_uniform[n - 1]; for (i = j = 1, ref = n - 2; 1 <= ref ? j <= ref : j >= ref; i = 1 <= ref ? ++j : --j) { osm_uniform[i] = (i + 1 - 0.3175) / (n + 0.365); } return (function() { var k, len, results; results = []; for (k = 0, len = osm_uniform.length; k < len; k++) { x = osm_uniform[k]; results.push(jStat.normal.inv(x, 0, 1)); } return results; })(); }; redraw_prob_plot = function(samples, sample_group) { var container, h, margin, totalh, totalw, w; h = 600; w = 500; margin = { left: 60, top: 40, right: 40, bottom: 40, inner: 5 }; totalh = h + margin.top + margin.bottom; totalw = w + margin.left + margin.right; container = $("#prob_plot_container"); container.width(totalw); container.height(totalh); return nv.addGraph((function(_this) { return function() { var W, all_samples, chart, data, intercept, make_data, names, pvalue, pvalue_str, slope, sorted_names, sorted_values, sw_result, test_str, x, z_scores; chart = nv.models.scatterChart().width(w).height(h).showLegend(true).color(d3.scale.category10().range()); chart.pointRange([50, 50]); chart.legend.updateState(false); chart.xAxis.axisLabel("Expected Z score").axisLabelDistance(20).tickFormat(d3.format('.02f')); chart.tooltipContent(function(obj) { return '' + obj.point.name + ''; }); all_samples = samples[sample_group]; names = (function() { var j, len, ref, results; ref = _.keys(all_samples); results = []; for (j = 0, len = ref.length; j < len; j++) { x = ref[j]; if (all_samples[x] !== null) { results.push(x); } } return results; })(); sorted_names = names.sort(function(x, y) { return all_samples[x].value - all_samples[y].value; }); max_decimals = 0 sorted_values = (function() { var j, len, results; results = []; for (j = 0, len = sorted_names.length; j < len; j++) { x = sorted_names[j]; results.push(all_samples[x].value); if (all_samples[x].value.countDecimals() > max_decimals) { max_decimals = all_samples[x].value.countDecimals()-1 } } return results; })(); //ZS: 0.1 indicates buffer, increase to increase buffer y_domain = [sorted_values[0] - (sorted_values.slice(-1)[0] - sorted_values[0])*0.1, sorted_values.slice(-1)[0] + (sorted_values.slice(-1)[0] - sorted_values[0])*0.1] chart.yDomain(y_domain) chart.yAxis.axisLabel("Trait value").axisLabelDistance(10).tickFormat(d3.format('.0'+max_decimals.toString()+'f')); sw_result = ShapiroWilkW(sorted_values); W = sw_result.w.toFixed(3); pvalue = sw_result.p.toFixed(3); pvalue_str = pvalue > 0.05 ? pvalue.toString() : "" + pvalue + ""; test_str = "Shapiro-Wilk test statistic is " + W + " (p = " + pvalue_str + ")"; z_scores = get_z_scores(sorted_values.length); //ZS: 0.1 indicates buffer, increase to increase buffer x_domain = [z_scores[0] - (z_scores.slice(-1)[0] - z_scores[0])*0.1, z_scores.slice(-1)[0] + (z_scores.slice(-1)[0] - z_scores[0])*0.1] chart.xDomain(x_domain) slope = jStat.stdev(sorted_values); intercept = jStat.mean(sorted_values); make_data = function(group_name) { var sample, value, z_score; return { key: js_data.sample_group_types[group_name], slope: slope, intercept: intercept, values: (function() { var j, len, ref, ref1, results; ref = _.zip(get_z_scores(sorted_values.length), sorted_values, sorted_names); results = []; for (j = 0, len = ref.length; j < len; j++) { ref1 = ref[j], z_score = ref1[0], value = ref1[1], sample = ref1[2]; if (sample in samples[group_name]) { results.push({ x: z_score, y: value, name: sample }); } } return results; })() }; }; data = [make_data('samples_primary'), make_data('samples_other')]; d3.select("#prob_plot_container svg").datum(data).call(chart); if (js_data.trait_symbol != null) { $("#prob_plot_title").html("