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@@ -4,9 +4,10 @@ import shutil
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open_ml_problems_folder = 'OpenML_datasets'
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surrogate_data_path = 'data/surrogate/data/'
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-k_params = [100, 150, 200]
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-k_random = [0, 1]
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-k_reinit = [0, 1]
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+# fixed test params as first part
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+k_params = [100] # 100, 150, 200
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+k_random = [0] # 0, 1
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+k_reinit = [0] # 0, 1
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every_ls = 50
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n_times = 5
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@@ -47,12 +48,10 @@ def main():
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# - run new instance using specific data
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for k in k_params:
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for k_r in k_random:
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- # for k_init in k_reinit:
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+ for k_init in k_reinit:
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# if not use of k_reinit and use of random, then run multiple times this instance to do mean later
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- #if k_init == 0 and k_r == 1:
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- if k_r == 1:
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-
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+ if k_init == 0 and k_r == 1:
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for i in range(n_times):
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str_index = str(i)
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@@ -60,7 +59,7 @@ def main():
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while len(str_index) < 3:
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str_index = "0" + str_index
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- output_problem_name = f'{ml_problem_name}_everyLS_{every_ls}_k{k}_random{k_r}_{str_index}'
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+ output_problem_name = f'{ml_problem_name}_everyLS_{every_ls}_k{k}_random{k_r}_reinit{k_init}_{str_index}'
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# copy pre-computed real evaluation data for this instance
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current_output_real_eval_path = os.path.join(surrogate_data_path, output_problem_name)
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@@ -74,12 +73,12 @@ def main():
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f"--k_division {k} " \
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f"--k_random {k_r} " \
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f"--output {output_problem_name}"
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- #f"--k_dynamic {k_init} " \
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+ f"--k_dynamic {k_init} " \
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print(f'Running extraction data for {ml_problem_name} with [ils: {p_ils}, ls: {p_ls}, k: {k}, k_r: {k_r}, i: {i}]')
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os.system(ml_surrogate_multi_command)
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else:
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- output_problem_name = f'{ml_problem_name}_everyLS_{every_ls}_k{k}_random{k_r}'
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+ output_problem_name = f'{ml_problem_name}_everyLS_{every_ls}_k{k}_random{k_r}_reinit{k_init}'
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# copy pre-computed real evaluation data for this instance
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current_output_real_eval_path = os.path.join(surrogate_data_path, output_problem_name)
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@@ -93,7 +92,7 @@ def main():
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f"--k_division {k} " \
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f"--k_random {k_r} " \
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f"--output {output_problem_name}"
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- #f"--k_dynamic {k_init} " \
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+ f"--k_dynamic {k_init} " \
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print(f'Running extraction data for {ml_problem_name} with [ils: {p_ils}, ls: {p_ls}, k: {k}, k_r: {k_r}]')
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os.system(ml_surrogate_multi_command)
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