noiseFunction = d3.randomNormal(0, Math.sqrt(dt))
simulatedTrajectories = {
// Initialise an array of trajectories
const data = []
// For each trajectory…
for( let r = 0; r < numberOfTrajectories; r++){
// Determine the starting point of the run in the data array so each run is added consecutively in the array.
const startingArrayPos = r * steps
// Initialise the start of each run with the initialValue and reset the timeStep to 0
data[startingArrayPos] = {timeStep: 0, value: initialValue, run: r, time: 0}
// Step through each timeStep
for(let t = 1; t < steps; t++){
// Determine the previous value
const previousValue = data[startingArrayPos+t-1]['value']
// Calculate the new value, by applying the formula above.
//const newValue = previousValue * Math.exp((mu * dt) + (sigma * noiseFunction()))
const newValue = previousValue * Math.exp(((mu - (sigma ** 2)/2) * dt) + (sigma * noiseFunction()))
data[startingArrayPos+t] = {timeStep: t, value: newValue, run: r, time: dt * t}
}
}
return data
}
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.
