mirror of
https://git.gfz-potsdam.de/naaice/model-training.git
synced 2025-12-13 12:18:22 +01:00
60 lines
1.7 KiB
Julia
60 lines
1.7 KiB
Julia
using HDF5
|
|
using RData
|
|
|
|
using DataFrames
|
|
|
|
# Load Training Data
|
|
# train_data = load("Barite_50_Data.rds")
|
|
|
|
# training_h5_name = "Barite_50_Data.h5"
|
|
# h5open(training_h5_name, "w") do fid
|
|
# for key in keys(train_data)
|
|
# group = create_group(fid, key)
|
|
# group["names"] = names(train_data[key])
|
|
# group["data", compress=3] = Matrix(train_data[key])
|
|
# # group = create_group(fid, key)
|
|
# # grou["names"] = coln
|
|
# end
|
|
# end
|
|
|
|
# List all .rds files starting with "iter" in a given directory
|
|
rds_files = filter(x -> startswith(x, "iter"), readdir("barite_out/"))
|
|
|
|
# remove "iter_0.rds" from the list
|
|
rds_files = rds_files[2:end]
|
|
|
|
big_df_in = DataFrame()
|
|
big_df_out = DataFrame()
|
|
|
|
for rds_file in rds_files
|
|
# Load the RDS file
|
|
data = load("barite_out/$rds_file")
|
|
# Convert the data to a DataFrame
|
|
df_T = DataFrame(data["T"])
|
|
df_C = DataFrame(data["C"])
|
|
# Append the DataFrame to the big DataFrame
|
|
append!(big_df_in, df_T)
|
|
append!(big_df_out, df_C)
|
|
end
|
|
|
|
# remove ID, Barite_p1, Celestite_p1 columns
|
|
big_df_in = big_df_in[:, Not([:ID, :Barite_p1, :Celestite_p1])]
|
|
big_df_out = big_df_out[:, Not([:ID, :Barite_p1, :Celestite_p1])]
|
|
|
|
inference_h5_name = "Barite_50_Data_inference.h5"
|
|
h5open(inference_h5_name, "w") do fid
|
|
fid["names"] = names(big_df_in)
|
|
fid["data", compress=9] = Matrix(big_df_in)
|
|
end
|
|
|
|
training_h5_name = "Barite_50_Data_training.h5"
|
|
h5open(training_h5_name, "w") do fid
|
|
group_in = create_group(fid, "design")
|
|
group_out = create_group(fid, "result")
|
|
|
|
group_in["names"] = names(big_df_in)
|
|
group_in["data", compress=9] = Matrix(big_df_in)
|
|
|
|
group_out["names"] = names(big_df_out)
|
|
group_out["data", compress=9] = Matrix(big_df_out)
|
|
end |