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3799002 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | """Train/test split (by numeric case id range) + k-fold cross-validation."""
import os, glob
import numpy as np
from .utils import numeric_id
def list_processed(proc_dir):
cases = [os.path.splitext(os.path.basename(p))[0]
for p in glob.glob(os.path.join(proc_dir, "*.npz"))]
return sorted(cases, key=numeric_id)
def _in(num, rng):
return bool(rng) and rng[0] <= num <= rng[1]
def make_split(proc_dir, cfg):
cases = list_processed(proc_dir)
sp = cfg["split"]
exclude_cases = set(sp.get("exclude_cases", []) or []) # specific case ids to drop
train, test = [], []
for c in cases:
n = numeric_id(c)
if n in exclude_cases:
continue
if _in(n, sp.get("exclude_range")):
continue
if _in(n, sp.get("test_range")):
test.append(c)
elif _in(n, sp.get("train_range")):
train.append(c)
return train, test
def kfold(train_cases, n_folds=5, seed=42):
rng = np.random.default_rng(seed)
idx = np.arange(len(train_cases))
rng.shuffle(idx)
folds = np.array_split(idx, n_folds)
out = []
for i in range(n_folds):
val_idx = folds[i]
tr_idx = np.concatenate([folds[j] for j in range(n_folds) if j != i]) \
if n_folds > 1 else val_idx
out.append(([train_cases[j] for j in tr_idx],
[train_cases[j] for j in val_idx]))
return out
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