def generate_valid_sobol(self, sample_size, failure_multiplier):
step_size = failure_multiplier * sample_size
parameters = {}
info("pkeys: " + str([k for k in self.parameter_ranges.keys()]))
info("axisnames: " + str([n for n in self.axis_names]))
for p in self.parameter_ranges.keys():
parameters[p] = FloatVector([self.parameter_ranges[p][1] - 1.0])
parameters = DataFrame(parameters)
info("Computed parameter ranges:")
info(str(parameters))
r_snippet = """library(randtoolbox)
library(stringr)
library(tibble)
ranges <- %s
sobol_n <- %s
sobol_dim <- %s
temp_sobol <- sobol(n = sobol_n,
dim = sobol_dim,
scrambling = 3,
seed = as.integer((99999 - 10000) * runif(1) + 10000),
init = TRUE)
rm(temp_sobol)
gc()
design <- sobol(n = sobol_n,
dim = sobol_dim,
scrambling = 3,
seed = as.integer((99999 - 10000) * runif(1) + 10000),
init = FALSE)
encoded_matrix <- round(design %%*%% diag(ranges))
mode(encoded_matrix) <- "integer"
encoded_design <- data.frame(encoded_matrix)
names(encoded_design) <- names(ranges)
range_list <- %s
convert_parameters <- function(name) {
encoded_design[, name] <- range_list[[name]][encoded_design[, name] + 1]
}
converted_design <- data.frame(sapply(names(encoded_design), convert_parameters))
constraint <- "%s" %%>%%
str_replace_all(c("True and " = "TRUE & ",
"==" = "== ",
"<=" = "<= ",
"or" = " |",
"and" = "&",
"\\\\*" = "\\\\* ",
" \\\\)" = "\\\\)",
"%%" = " %%%% ")) %%>%%
rlang::parse_expr()
print(str(constraint))
valid_design <- converted_design %%>%%
rownames_to_column() %%>%%
filter(!!!constraint)
result_design <- encoded_design[valid_design$rowname, ]
rm(encoded_design)
rm(converted_design)
rm(valid_design)
gc()
result_design[ , %s]""" % (parameters.r_repr(), step_size,
len(self.axis_names),
self.range_matrix.r_repr(), self.constraint,
StrVector(self.axis_names).r_repr())
candidate_lhs = robjects.r(r_snippet)
gc.collect()
info("Valid Design:")
info(str(self.base.summary_default(candidate_lhs)))
return self.encode_data(candidate_lhs)
def validate_sample(self, sample, selected):
decoded_sample = self.rsm.decode_data(sample)
parameters = {}
info("pkeys: " + str([k for k in self.parameter_ranges.keys()]))
info("axisnames: " + str([n for n in self.axis_names]))
for p in self.parameter_ranges.keys():
parameters[p] = FloatVector([self.parameter_ranges[p][1] - 1.0])
parameters = DataFrame(parameters)
info("Computed parameter ranges:")
info(str(parameters))
r_snippet = """ library(stringr)
library(tibble)
ranges <- %s
print("Ranges:")
print(str(ranges))
constraint <- "%s" %%>%%
str_replace_all(c("True and " = "TRUE & ",
"==" = "== ",
"<=" = "<= ",
"or" = " |",
"and" = "&",
"\\\\*" = "\\\\* ",
" \\\\)" = "\\\\)",
"%%" = " %%%% ")) %%>%%
rlang::parse_expr()
print(str(constraint))
sample <- %s
print(str(sample))
encoded_matrix <- round(sample)
print(str(encoded_matrix))
encoded_design <- data.frame(encoded_matrix)
range_list <- %s
convert_parameters <- function(name) {
encoded_design[, name] <- range_list[[name]][encoded_design[, name] + 1]
}
converted_design <- data.frame(sapply(names(encoded_design), convert_parameters))
valid_sample <- converted_design %%>%%
rownames_to_column() %%>%%
filter(!!!constraint)
valid_sample$rowname""" % (parameters.r_repr(), self.constraint,
decoded_sample.r_repr(),
self.range_matrix.r_repr())
valid_sample = robjects.r(r_snippet)
validated_sample = sample.rx(valid_sample[1:selected], True)
info("Validated Sample:")
info(str(self.base.summary_default(validated_sample)))
self.complete_search_space = self.base.rbind(
self.complete_search_space, validated_sample)
return validated_sample
def generate_valid_lhs(self, sample_size):
# TODO: Expose step size as parameter!
step_size = 150 * sample_size
parameters = {}
info("pkeys: " + str([k for k in self.parameter_ranges.keys()]))
info("axisnames: " + str([n for n in self.axis_names]))
for p in self.parameter_ranges.keys():
parameters[p] = FloatVector([self.parameter_ranges[p][1] - 1.0])
parameters = DataFrame(parameters)
info("Computed parameter ranges:")
info(str(parameters))
r_snippet = """library(DiceDesign)
library(stringr)
library(tibble)
ranges <- %s
output <- lhsDesign(n = %s, dimension = %s)
design <- output$design
encoded_matrix <- round(design %%*%% diag(ranges))
mode(encoded_matrix) <- "integer"
encoded_design <- data.frame(encoded_matrix)
names(encoded_design) <- names(ranges)
range_list <- %s
convert_parameters <- function(name) {
encoded_design[, name] <- range_list[[name]][encoded_design[, name] + 1]
}
converted_design <- data.frame(sapply(names(encoded_design), convert_parameters))
constraint <- "%s" %%>%%
str_replace_all(c("True and " = "TRUE & ",
"==" = "== ",
"<=" = "<= ",
"or" = " |",
"and" = "&",
"\\\\*" = "\\\\* ",
" \\\\)" = "\\\\)",
"%%" = " %%%% ")) %%>%%
rlang::parse_expr()
print(str(constraint))
valid_design <- converted_design %%>%%
rownames_to_column() %%>%%
filter(!!!constraint)
encoded_design <- encoded_design[valid_design$rowname, ]
encoded_design[ , %s]""" % (
parameters.r_repr(), step_size, len(
self.axis_names), self.range_matrix.r_repr(), self.constraint,
StrVector(self.axis_names).r_repr())
candidate_lhs = robjects.r(r_snippet)
info("Candidate LHS:")
info(str(self.base.summary_default(candidate_lhs)))
return self.encode_data(candidate_lhs)
