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merged redundant BOEngine.__init__s

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swim
2026-08-14 19:28:54 +09:00
parent 1ddfc9d246
commit 785760d23d
3 changed files with 60 additions and 121 deletions
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bo/sobo.py
-56
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@@ -21,34 +21,6 @@ from bo.base import BOEngine
class SingleObjectiveBOEngine(BOEngine):
def __init__(self, config):
super().__init__(config)
self.params = [key for key, spec in config["bo"]["params"].items() if spec is not None]
self.param_types = {key: config["bo"]["params"][key].get("type", "float") for key in self.params}
self.integer_indices = [i for i, param in enumerate(self.params) if self.param_types[param] == 'int']
self.bounds = np.empty((2, len(self.params)))
for i, param in enumerate(self.params):
center = config["ptycho"]["params"][param]
radius = config["bo"]["params"][param]["radius"]
self.bounds[0, i] = center - radius
self.bounds[1, i] = center + radius
self.train_x = np.empty((0, len(self.params))) # shape: (BOiter, BOparam)
self.train_y = np.empty((0,)) # shape: (BOiter,)
train_x_path = config["bo"].get("train_x")
train_y_path = config["bo"].get("train_y")
if train_x_path is not None and train_y_path is not None:
if os.path.exists(train_x_path) and os.path.exists(train_y_path):
train_x = np.load(train_x_path)
train_y = np.load(train_y_path)
assert train_x.ndim == 2, "loaded train_x must be 2D"
assert train_x.shape[1] == len(self.params), "loaded train_x shape(1) does not match number of variable parameters"
assert train_y.ndim == 1, "loaded train_y must be 1D"
assert train_y.shape[0] == train_x.shape[0], "loaded train_x and train_y shape(0) have unequal iterations"
self.train_x = train_x
self.train_y = train_y
self.acquisition = config['bo']['acquisition']
@@ -146,34 +118,6 @@ class SingleObjectiveBOEngine(BOEngine):
return X_out
def tell(self, job_config, y_value):
config = self.config
x_value = []
for param in self.params:
x_value.append(job_config['ptycho']['params'][param])
self.train_x = np.vstack([
self.train_x,
np.array(x_value).reshape(1, -1)
])
self.train_y = np.concatenate([
self.train_y,
np.array([y_value])
])
train_x_path = config['bo'].get('tain_x')
train_y_path = config['bo'].get('train_y')
if train_x_path is not None and train_y_path is not None:
np.save(train_x_path, self.train_x)
np.save(train_y_path, self.train_y)
else:
result_dir = config['io']['result_dir']
np.save(os.path.join(result_dir, 'train_x.npy'), self.train_x)
np.save(os.path.join(result_dir, 'train_y.npy'), self.train_y)