//result_json = await d3.json ("https://data.hyphy.org/web/busted-ph/"+ phenotype +"_ags.json");
/*
average_pos = {
let keys = Object.keys(sorted[0])
keys = keys.filter(key => key != 'ID' && key != 'Selection associated with phenotype');
const len_bins = sorted.length/10 // len_bins = 31
let dummy_list = [] // to store 10 lines at a time
let bin_list = [] // to store average of dummy_list
for (let i = 0; i < 10; i++){
dummy_list = sorted.slice(i*len_bins, (i + 1) * len_bins + 1)
bin_list[i] = {}
for (let name of keys){
const average_val = dummy_list.reduce((total, next) => total + next[name], 0) / dummy_list.length
bin_list[i][name] = average_val
}
}
return bin_list
}
*/
//dotplot = Plot.dot(reduced_busted, {x: "w3_t", y: "w1_t", stroke: "Selection associated with phenotype"}).plot()
//dotplot2 = Plot.dot(reduced_pos, {x: "w3_t", y: "w1_t", stroke: "Selection associated with phenotype"}).plot()
//dotplot3 = Plot.dot(reduced_busted, {x: "w3_t", y: "FG p-value", stroke: "Selection associated with phenotype"}).plot()
/*hist = {
let w3_t_pos = []
for (let i = 0; i < pos_sel.length; i++){
w3_t_pos.push(pos_sel[i]["w3_t"])
}
var histGenerator = d3.bin()
.domain([Math.min(...w3_t_pos),Math.max(...w3_t_pos)])
.thresholds(10);
var bins = histGenerator(w3_t_pos);
return bins
}
*/
//lenend for figure from BUSTED-PH simulations (but the figure just looks like grass here)
/*
Legend(omega_color, {
title: "dN/dS",
tickFormat: ".2"
})
*/
//figure from busted-ph simulations (just looks like grass)
/*
canvas = {
const h = average_pos.length;
if (h) {
const w = 300;
const R = 2;
const context = DOM.context2d(w*R*2, 2*h*R, 1);
for (let i = 0; i < h; i++) {
let from = 0.;
let to = average_pos[i].p1_t;
context.fillStyle = omega_color (average_pos[i].w1_t);
context.fillRect( from*w*R, i*2*R, R*(to-from)*w, R );
from = to;
to += average_pos[i].p2_t;
context.fillStyle = omega_color (average_pos[i].w2_t);
context.fillRect( from*w*R, i*2*R, R*(to-from)*w, R );
from = to;
to += average_pos[i].p3_t;
context.fillStyle = omega_color (average_pos[i].w3_t);
context.fillRect( from*w*R, i*2*R, R*(to-from)*w, R );
from = 0.;
to = average_pos[i].p1_b;
context.fillStyle = omega_color (average_pos[i].w1_b);
context.fillRect( from*w*R, i*2*R + R, R*(to-from)*w, R );
from = to;
to += average_pos[i].p2_b;
context.fillStyle = omega_color (average_pos[i].w2_b);
context.fillRect( from*w*R, i*2*R + R , R*(to-from)*w, R );
from = to;
to += average_pos[i].p3_b;
context.fillStyle = omega_color (average_pos[i].w3_b);
context.fillRect( from*w*R, i*2*R + R , R*(to-from)*w, R );
}
return context.canvas;
}
return DOM.context2d(1,1,1).canvas;
}
*/
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
