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utility_evaluation4.R
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# Utility Evaluation for Synthetic Data
# Team: Destatis
### utility graphs:
# histogram
# corrplot
# utility tables
### utility metrics:
# KS Test
# pMSE Propensity Score
# pMSE tables
# sdcMicro::IL_variables
library(synthpop)
library(sdcMicro)
library(corrplot)
load("satgpa.rda")
satgpa <- as.data.frame(satgpa)
load("syn_sat_mnorm_simple.RData")
load("syn_sat_mnorm_complex.RData")
syn_sat_mnorm_complex <- syn_sat_mnorm_complex.RData
load("pums.RData")
load("pums_syn_syndatcart.RData")
# help functions
h_dat_acs <- function(df){
names_acs <- c("X", "PUMA", "YEAR", "HHWT", "GQ", "PERWT", "SEX", "AGE", "MARST", "RACE", "HISPAN", "CITIZEN", "SPEAKENG", "HCOVANY",
"HCOVPRIV", "HINSEMP", "HINSCAID", "HINSCARE", "EDUC", "EMPSTAT", "EMPSTATD", "LABFORCE", "WRKLSTWK",
"ABSENT", "LOOKING", "AVAILBLE", "WRKRECAL", "WORKEDYR", "INCTOT", "INCWAGE", "INCWELFR", "INCINVST",
"INCEARN", "POVERTY", "DEPARTS", "ARRIVES", "sim_individual_id")
w_num <- c("X","HHWT", "PERWT", "AGE", "INCTOT", "INCWAGE", "INCWELFR", "INCINVST", "INCEARN",
"POVERTY", "DEPARTS", "ARRIVES", "sim_individual_id")
w_cat <- names_acs[!names_acs%in%w_num]
for(i in w_cat){
try(df[,i] <- as.factor(as.character(df[,i])))
}
for(i in w_num){
try(df[,i] <- as.numeric(df[,i]))
}
df$PUMA <- NULL
df$sim_individual_id <- NULL
df$X <- NULL
return(df)
}
h_dat_sat <- function(df){
w_num <- c("sat_v", "sat_m", "sat_sum", "hs_gpa", "fy_gpa")
w_cat <- "sex"
for(i in w_cat){
try(df[,i] <- as.factor(as.character(df[,i])))
}
for(i in w_num){
try(df[,i] <- as.numeric(df[,i]))
}
return(df)
}
ks_check <- function(df_syn, df_orig){
p <- c()
for(i in 1:dim(df_orig)[2]){
p[i] <- ks.test(as.numeric(df_syn[,i]), as.numeric(df_orig[,i]))$p.value
}
return(p)
}
cio <- function(df_syn, df_orig, y.vars){
vars <- names(df_syn)
ci_all <- matrix(NA,1,4)
ms_df <- matrix(NA,1,4)
mhd_05 <- c()
for(i in y.vars){
y <- i
x <- vars[vars != y]
f <- as.formula(paste(y, paste(x, collapse = " + "), sep = " ~ "))
try(reg <- lm(formula = f, data = df_orig))
try(reg_o <- lm(formula = f, data = df_syn))
try(coef <- coef(reg))
try(coef_o <- coef(reg_o))
try(se <- sqrt(diag(vcov(reg))))
try(se_o <- sqrt(diag(vcov(reg_o))))
try(mhd <- t(coef - coef_o)%*%vcov(reg_o)%*%(coef - coef_o) )
try(mhd_sig <- ifelse(mhd > qchisq(0.95, length(coef)), 1, 0))
ms_df <- rbind(ms_df, cbind(coef, coef_o, se, se_o))
mhd_05 <- c(mhd_05, mhd_sig)
}
mhd_05 <- mhd_05
ms_df <- as.data.frame(ms_df)
res_list <- list(ms_df = as.data.frame(ms_df),
mrd_coef = mean(na.omit(ms_df$coef/ms_df$coef_o-1)),
mrd_se = mean(na.omit(ms_df$se/ms_df$se_o-1)),
mhd_05 = mean(na.omit(mhd_05)) )
return(res_list)
}
# Beginn Analyse SAT
y.vars <- c("sat_v", "sat_m", "sat_sum", "hs_gpa", "fy_gpa")
orig_sat <- h_dat_sat(as.data.frame(satgpa))
syn_sat_mnorm_simple <- h_dat_sat(syn_sat_mnorm_simple)
# Simulated Data Simple
results_syn_sat_mnorm_simple <- list(
comp = compare(syn_sat_mnorm_simple, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(syn_sat_mnorm_simple, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(syn_sat_mnorm_simple, orig_sat, y.vars),
ks = ks_check(orig_sat, syn_sat_mnorm_simple),
il = IL_variables(orig_sat, syn_sat_mnorm_simple),
ug = utility.gen(syn_sat_mnorm_simple, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(syn_sat_mnorm_simple), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
# Simulated Data Complex
orig_sat <- as.data.frame(orig_sat)
syn_sat_mnorm_complex <- h_dat_sat(syn_sat_mnorm_complex.RData)
results_syn_sat_mnorm_complex <- list(
comp = compare(syn_sat_mnorm_complex, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(syn_sat_mnorm_complex, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(syn_sat_mnorm_complex, orig_sat, y.vars),
ks = ks_check(orig_sat, syn_sat_mnorm_complex),
il = IL_variables(orig_sat, syn_sat_mnorm_complex),
ug = utility.gen(syn_sat_mnorm_complex, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(syn_sat_mnorm_complex), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
# sm_sat_ipso_regsdc_hs_fy_no_corrections
load("~/GitHub/Synthetic_Data_Challenge/results/sm_sat_ipso_regsdc_hs_fy_no_corrections.rda")
sm_ipso_regsdc_conf_hs_fy <- as.data.frame(h_dat_sat(sm_ipso_regsdc_conf_hs_fy))
orig_sat <- as.data.frame(orig_sat)
results_sm_ipso_regsdc_conf_hs_fy <- list(
comp = compare(sm_ipso_regsdc_conf_hs_fy, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(sm_ipso_regsdc_conf_hs_fy, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(sm_ipso_regsdc_conf_hs_fy, orig_sat, y.vars),
ks = ks_check(orig_sat, sm_ipso_regsdc_conf_hs_fy),
il = IL_variables(orig_sat, sm_ipso_regsdc_conf_hs_fy),
ug = utility.gen(sm_ipso_regsdc_conf_hs_fy, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(sm_ipso_regsdc_conf_hs_fy), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
# sm_sat_gan_ctgan_epoch1000
load("~/GitHub/Synthetic_Data_Challenge/results/sm_sat_gan_ctgan_epoch1000.rda")
sm_sat_gan_ctgan_epoch1000 <- h_dat_sat(result_gan)
orig_sat <- as.data.frame(orig_sat)
results_sm_sat_gan_ctgan_epoch1000 <- list(
comp = compare(sm_sat_gan_ctgan_epoch1000, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(sm_sat_gan_ctgan_epoch1000, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(sm_sat_gan_ctgan_epoch1000, orig_sat, y.vars),
ks = ks_check(orig_sat, sm_sat_gan_ctgan_epoch1000),
il = IL_variables(orig_sat, sm_sat_gan_ctgan_epoch1000),
ug = utility.gen(sm_sat_gan_ctgan_epoch1000, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(sm_sat_gan_ctgan_epoch1000), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
# sm_sat_gan_ctgan
load("~/GitHub/Synthetic_Data_Challenge/results/sm_sat_gan_ctgan.rda")
sm_sat_gan_ctgan <- h_dat_sat(result_gan)
orig_sat <- as.data.frame(orig_sat)
results_sm_sat_gan_ctgan <- list(
comp = compare(sm_sat_gan_ctgan, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(sm_sat_gan_ctgan, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(sm_sat_gan_ctgan, orig_sat, y.vars),
ks = ks_check(orig_sat, sm_sat_gan_ctgan),
il = IL_variables(orig_sat, sm_sat_gan_ctgan),
ug = utility.gen(sm_sat_gan_ctgan, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(sm_sat_gan_ctgan), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
# sm_sat_fcs_cart
load("~/GitHub/Synthetic_Data_Challenge/results/sm_sat_fcs_cart.rda")
sm_sat_fcs_cart <- h_dat_sat(sm_sat_fcs_cart)
orig_sat <- as.data.frame(orig_sat)
results_sm_sat_fcs_cart <- list(
comp = compare(sm_sat_fcs_cart, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(sm_sat_fcs_cart, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(sm_sat_fcs_cart, orig_sat, y.vars),
ks = ks_check(orig_sat, sm_sat_fcs_cart),
il = IL_variables(orig_sat, sm_sat_fcs_cart),
ug = utility.gen(sm_sat_fcs_cart, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(sm_sat_fcs_cart), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
save(list = c("results_syn_sat_mnorm_simple",
"results_syn_sat_mnorm_complex",
"results_sm_ipso_regsdc_conf_hs_fy",
"results_sm_sat_gan_ctgan_epoch1000",
"results_sm_sat_gan_ctgan",
"results_sm_sat_fcs_cart"), file = paste0(getwd(), "/results/results_sat2.RData"))
load(paste0(getwd(), "/results/results_sat2.RData"))
# copulagan
load("~/GitHub/SynDatCh/results/sm_sat_gan_copulagan.rda")
result_copulagan <- h_dat_sat(result_copulagan)
orig_sat <- as.data.frame(orig_sat)
results_sm_sat_copulagan <- list(
comp = compare(result_copulagan, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(result_copulagan, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(result_copulagan, orig_sat, y.vars),
ks = ks_check(orig_sat, result_copulagan),
il = IL_variables(orig_sat, result_copulagan),
ug = utility.gen(result_copulagan, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(result_copulagan), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
save(list = c("results_sm_sat_copulagan"), file = paste0(getwd(), "/results/results_sat_copulagan_2.RData"))
# minute
load("~/GitHub/SynDatCh/results/sm_sat_minuteman.rda")
sm_sat_minuteman <- h_dat_sat(as.data.frame(sm_sat_minuteman))
orig_sat <- as.data.frame(orig_sat)
set.seed(3280)
orig_sat <- orig_sat[sample(1:1000, size = nrow(sm_sat_minuteman)),]
results_sm_sat_minute <- list(
comp = compare(sm_sat_minuteman, orig_sat, var = names(orig_sat)),
cp1 = corrplot(cor(sapply(orig_sat, as.numeric)), method = "color", type = "lower", main = "Original"),
cp2 = corrplot(cor(sapply(sm_sat_minuteman, as.numeric)), method = "color", type = "lower", main = "Synthetic"),
cio = cio(sm_sat_minuteman, orig_sat, y.vars),
ks = ks_check(orig_sat, sm_sat_minuteman),
il = IL_variables(orig_sat, sm_sat_minuteman),
ug = utility.gen(sm_sat_minuteman, as.data.frame(orig_sat)),
ut = utility.tables(as.data.frame(sm_sat_minuteman), as.data.frame(orig_sat), vars = names(orig_sat), max.scale = 20, tab.stats = c("pMSE", "S_pMSE", "MabsDD"))
)
save(list = c("results_sm_sat_minute"), file = paste0(getwd(), "/results/results_sat_minute_2.RData"))