eytan

# due to balandat

from botorch.models import SingleTaskGP
from torch import Tensor
 
class LinearSingleTaskGP(SingleTaskGP):
    def __init__(self, train_X: Tensor, train_Y: Tensor, **kwargs):
        super().__init__(train_X, train_Y, **kwargs)
        self.mean_module = LinearMean(batch_shape=train_X.shape[:-2], input_size=train_X.size(-1))

eytan

library(dplyr)
library(broom)
library(foreach)
library(ggplot2)

N <- 1e4

# generates simulated experiment data where we have two experiments,
# where E1=1 with probability p0, and E2=0 with probability p1
# interaction is the size of the treatment interaction, expressed in terms

eytan

This choropleth encodes unemployment rates from 2008 with a quantize scale ranging from 0 to 15%. A threshold scale is a useful alternative for coloring arbitrary ranges.