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19
reproduction_effort/functions/get_experiments.py
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reproduction_effort/functions/get_experiments.py
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import torch
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import os
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import glob
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@torch.no_grad()
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def get_experiments(path: str) -> torch.Tensor:
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filename_np: str = os.path.join(
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path,
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"Exp*_Part001.npy",
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)
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list_str = glob.glob(filename_np)
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list_int: list[int] = []
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for i in range(0, len(list_str)):
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list_int.append(int(list_str[i].split("Exp")[-1].split("_Trial")[0]))
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list_int = sorted(list_int)
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return torch.tensor(list_int).unique()
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reproduction_effort/functions/get_parts.py
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reproduction_effort/functions/get_parts.py
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import torch
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import os
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import glob
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@torch.no_grad()
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def get_parts(path: str, experiment_id: int, trial_id: int) -> torch.Tensor:
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filename_np: str = os.path.join(
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path,
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f"Exp{experiment_id:03d}_Trial{trial_id:03d}_Part*.npy",
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)
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list_str = glob.glob(filename_np)
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list_int: list[int] = []
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for i in range(0, len(list_str)):
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list_int.append(int(list_str[i].split("_Part")[-1].split(".npy")[0]))
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list_int = sorted(list_int)
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return torch.tensor(list_int).unique()
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reproduction_effort/functions/get_trials.py
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reproduction_effort/functions/get_trials.py
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import torch
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import os
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import glob
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@torch.no_grad()
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def get_trials(path: str, experiment_id: int) -> torch.Tensor:
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filename_np: str = os.path.join(
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path,
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f"Exp{experiment_id:03d}_Trial*_Part001.npy",
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)
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list_str = glob.glob(filename_np)
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list_int: list[int] = []
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for i in range(0, len(list_str)):
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list_int.append(int(list_str[i].split("_Trial")[-1].split("_Part")[0]))
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list_int = sorted(list_int)
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return torch.tensor(list_int).unique()
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