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added GPR

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Ayzen
2026-03-19 19:29:08 +03:00
parent bdefe3f581
commit 9581730e41
39 changed files with 3830 additions and 201 deletions
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python_app/storage/npz/snapshot_numpy.py
+93
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@@ -137,6 +137,7 @@ def save_result_history_binary(stage_dir: Path, history: list[ResultCollection])
{
"collection_id": collection.collection_id,
"monotonic_ns": collection.monotonic_ns,
"collection_payload_count": len(collection.collection_payloads),
"block_count": len(collection.blocks),
},
indent=2,
@@ -190,6 +191,66 @@ def save_result_history_numpy(stage_dir: Path, history: list[ResultCollection])
collection_dir = stage_dir / collection_dir_name(index, collection.collection_id, collection.monotonic_ns)
collection_dir.mkdir(parents=True, exist_ok=False)
collection_payload_meta: list[dict[str, int | str | float]] = []
for payload_index, payload in enumerate(collection.collection_payloads):
safe_name = sanitize_path_component(payload.processing_name or "processor")
base_name = f"collection_{payload_index:03d}_{safe_name}_kind{payload.kind}"
if payload.kind == 1:
freq = np.asarray(payload.frequency_hz, dtype=np.float32)
trace = np.asarray(payload.trace, dtype=np.complex64)
np.save(collection_dir / f"{base_name}_freq.npy", freq)
np.save(collection_dir / f"{base_name}_trace.npy", trace)
collection_payload_meta.append(
{
"kind": int(payload.kind),
"name": payload.processing_name,
"points": int(freq.size),
"freq_file": f"{base_name}_freq.npy",
"trace_file": f"{base_name}_trace.npy",
}
)
elif payload.kind == 2:
scalar = np.asarray([float(payload.scalar_value)], dtype=np.float32)
np.save(collection_dir / f"{base_name}_scalar.npy", scalar)
collection_payload_meta.append(
{
"kind": int(payload.kind),
"name": payload.processing_name,
"scalar_file": f"{base_name}_scalar.npy",
"scalar_value": float(payload.scalar_value),
}
)
elif payload.kind == 3:
image_x_axis = np.asarray(payload.image_x_axis, dtype=np.float32)
image_y_axis = np.asarray(payload.image_y_axis, dtype=np.float32)
image = np.asarray(payload.image, dtype=np.float32)
np.save(collection_dir / f"{base_name}_x_axis.npy", image_x_axis)
np.save(collection_dir / f"{base_name}_y_axis.npy", image_y_axis)
np.save(collection_dir / f"{base_name}_image.npy", image)
collection_payload_meta.append(
{
"kind": int(payload.kind),
"name": payload.processing_name,
"x_points": int(image_x_axis.size),
"y_points": int(image_y_axis.size),
"x_axis_file": f"{base_name}_x_axis.npy",
"y_axis_file": f"{base_name}_y_axis.npy",
"image_file": f"{base_name}_image.npy",
}
)
elif payload.kind == 4:
table = np.asarray(payload.table, dtype=np.float32)
np.save(collection_dir / f"{base_name}_table.npy", table)
collection_payload_meta.append(
{
"kind": int(payload.kind),
"name": payload.processing_name,
"rows": int(table.shape[0]) if table.ndim == 2 else 0,
"columns": int(table.shape[1]) if table.ndim == 2 else 0,
"table_file": f"{base_name}_table.npy",
}
)
blocks_meta: list[dict[str, int | str | list[dict[str, int | str | float]]]] = []
for block_index, block in enumerate(collection.blocks):
block_dir = collection_dir / f"block_{block_index:03d}_i{block.combo.input_pos}_o{block.combo.output_pos}"
@@ -224,6 +285,36 @@ def save_result_history_numpy(stage_dir: Path, history: list[ResultCollection])
"scalar_value": float(payload.scalar_value),
}
)
elif payload.kind == 3:
image_x_axis = np.asarray(payload.image_x_axis, dtype=np.float32)
image_y_axis = np.asarray(payload.image_y_axis, dtype=np.float32)
image = np.asarray(payload.image, dtype=np.float32)
np.save(block_dir / f"{base_name}_x_axis.npy", image_x_axis)
np.save(block_dir / f"{base_name}_y_axis.npy", image_y_axis)
np.save(block_dir / f"{base_name}_image.npy", image)
payload_meta.append(
{
"kind": int(payload.kind),
"name": payload.processing_name,
"x_points": int(image_x_axis.size),
"y_points": int(image_y_axis.size),
"x_axis_file": f"{base_name}_x_axis.npy",
"y_axis_file": f"{base_name}_y_axis.npy",
"image_file": f"{base_name}_image.npy",
}
)
elif payload.kind == 4:
table = np.asarray(payload.table, dtype=np.float32)
np.save(block_dir / f"{base_name}_table.npy", table)
payload_meta.append(
{
"kind": int(payload.kind),
"name": payload.processing_name,
"rows": int(table.shape[0]) if table.ndim == 2 else 0,
"columns": int(table.shape[1]) if table.ndim == 2 else 0,
"table_file": f"{base_name}_table.npy",
}
)
blocks_meta.append(
{
@@ -240,6 +331,8 @@ def save_result_history_numpy(stage_dir: Path, history: list[ResultCollection])
{
"collection_id": int(collection.collection_id),
"monotonic_ns": int(collection.monotonic_ns),
"collection_payload_count": len(collection.collection_payloads),
"collection_payloads": collection_payload_meta,
"block_count": len(collection.blocks),
"blocks": blocks_meta,
},