proposal for hook for loop function that allows plotting #139
Conversation
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Hi @larskotthoff and thanks for setting up this PR! Since For example, currently it is already possible to write a callback like the following: callback_plot = callback_optimization("plot",
on_optimizer_after_eval = function(callback, context) {
if (instance$archive$n_evals > 4) { # start after initial design which is 4 points in the example below
instance = context$instance
objective = context$instance$objective
surrogate = context$optimizer$surrogate
acq_function = context$optimizer$acq_function
xdt = instance$archive$data[instance$archive$n_evals, ]
plot_data = data.table(x = seq(objective$domain$lower, objective$domain$upper, length.out = 1001L))
plot_data[, y := instance$objective$eval_dt(plot_data[, "x", with = FALSE])]
plot_data[, acq_ei := acq_function$eval_dt(plot_data[, "x", with = FALSE])]
pred = surrogate$predict(plot_data)
plot_data[, pred_mean := pred$mean]
plot_data[, pred_se := pred$se]
p1 = ggplot(plot_data, aes(x = x, y = y)) +
geom_ribbon(aes(ymin = pred_mean - pred_se, ymax = pred_mean + pred_se), fill = "lightgray") +
geom_line() +
geom_line(aes(y = pred_mean), linetype = "dashed") +
geom_point(aes(x = x, y = surrogate$predict(data.table(x = x))$mean), data = xdt, color = "red") +
geom_point(aes(x = x, y = y), data = instance$archive$data[- instance$archive$n_evals, ], color = "darkgreen") +
theme(axis.title.x = element_blank(), axis.text.x = element_blank(), axis.ticks.x = element_blank()) +
theme_minimal()
p2 = ggplot(plot_data, aes(x = x, y = acq_ei)) +
geom_line() +
geom_point(aes(x = x, y = acq_ei), data = xdt, color = "red") +
theme_minimal()
p = plot_grid(p1, p2, ncol = 1, align = "v")
ggsave(p, file = paste("/tmp/mbo-", instance$archive$n_evals, ".pdf", sep = ""), width = 10, height = 5)
}
}
)(similarly one could write a We can then trigger this callback for example after or before the evaluation of a point/batch. obfun = ObjectiveRFun$new(
fun = function(xs) 2 * xs$x * sin(14 * xs$x),
domain = ps(x = p_dbl(lower = 0, upper = 1)),
codomain = ps(y = p_dbl(tags = "minimize")))
instance = OptimInstanceSingleCrit$new(
objective = obfun,
terminator = trm("evals", n_evals = 10),
callbacks = callback_plot)
surrogate = srlrn(default_gp())
acqfun = acqf("ei")
acqopt = acqo(
optimizer = opt("nloptr", algorithm = "NLOPT_GN_ORIG_DIRECT"),
terminator = trm("stagnation", iters = 100, threshold = 1e-5))
optimizer = opt("mbo",
loop_function = bayesopt_ego,
surrogate = surrogate,
acq_function = acqfun,
acq_optimizer = acqopt)
optimizer$optimize(instance)this then mimics the behavior of your hook function/callback above, e.g., we get the desired sequence of plots:
I guess I should start writing a section regarding callbacks and |
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Thanks, didn't know that you can have callbacks! The only case in which this wouldn't work as well is for an error condition (e.g. random interleaving), when the optimizer callback would "skip" an iteration. I don't think that this is really an issue, in particular given that it's much easier to implement and maintain with the optimizer callback. I'll close here and look forward to the improved documentation showing an example :) |
Initial proposal for some plotting functionality. Instead of providing this in the package itself, allow the user to specify a hook function in the MBO loop and give an example in the documentation. This avoids complex code that has to deal with all kinds of corner cases when plotting and allows the user to easily customize what they plot and how.
Really just meant as an initial, not yet perfect idea. Feedback welcome.
Would close #138.