data_root = "/scratch/stats_flux/timtu/smogllim/bootstrap"
file_list = dir(data_root)
file_len = length(file_list)
smogllim_df = NULL
gllim_df = NULL
for(file_index in 1:file_len){
d = new.env()
load(file.path(data_root, file_list[file_index]), envir=d)
cat(sprintf("(%d/%d) SMoGLLiM: cvID:%d K: %d, Lw: %d, M: %d, minSize: %d, dropTh: %.2f\n",
file_index, file_len, d$cvID, d$K, d$Lw, d$M, d$minSize, d$dropTh))
train_num = dim(d$train_y)[2]
data_type = array("train", train_num)
smogllim_sse = apply(d$smogllim_train_diff^2, 2, sum)
temp_smogllim_df = data.frame(cvID=d$cvID,
img_size=d$target_size,
data_type=data_type,
index=d$train_index,
K=d$K,
Lw=d$Lw,
M=d$M,
minSize=d$minSize,
dropTh=d$dropTh,
SSE=smogllim_sse
)
smogllim_df = rbind(smogllim_df, temp_smogllim_df)
gllim_sse = apply(d$gllim_train_diff^2, 2, sum)
temp_gllim_df = data.frame(cvID=d$cvID,
img_size=d$target_size,
data_type=data_type,
index=d$train_index,
K=d$K,
Lw=d$Lw,
SSE=gllim_sse
)
gllim_df = rbind(gllim_df, temp_gllim_df)
test_num = dim(d$test_y)[2]
data_type = array("test", test_num)
smogllim_sse = apply(d$smogllim_test_diff^2, 2, sum)
temp_smogllim_df = data.frame(cvID=d$cvID,
img_size=d$target_size,
data_type=data_type,
index=d$test_index,
K=d$K,
Lw=d$Lw,
M=d$M,
minSize=d$minSize,
dropTh=d$dropTh,
SSE=smogllim_sse
)
smogllim_df = rbind(smogllim_df, temp_smogllim_df)
gllim_sse = apply(d$gllim_test_diff^2, 2, sum)
temp_gllim_df = data.frame(cvID=d$cvID,
img_size=d$target_size,
data_type=data_type,
index=d$test_index,
K=d$K,
Lw=d$Lw,
SSE=gllim_sse
)
gllim_df = rbind(gllim_df, temp_gllim_df)
}
save.image("face_bootstrap_results.Rdata")
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