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30 lines
1.1 KiB
30 lines
1.1 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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from typing import Tuple
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import numpy as np
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from miplearn.h5 import H5File
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def _extract_bin_var_names_values(
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h5: H5File,
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) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
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bin_var_names, bin_var_indices = _extract_bin_var_names(h5)
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var_values = h5.get_array("mip_var_values")
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assert var_values is not None
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bin_var_values = var_values[bin_var_indices].astype(int)
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return bin_var_names, bin_var_values, bin_var_indices
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def _extract_bin_var_names(h5: H5File) -> Tuple[np.ndarray, np.ndarray]:
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var_types = h5.get_array("static_var_types")
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var_names = h5.get_array("static_var_names")
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assert var_types is not None
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assert var_names is not None
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bin_var_indices = np.where(var_types == b"B")[0]
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bin_var_names = var_names[bin_var_indices]
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assert len(bin_var_names.shape) == 1
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return bin_var_names, bin_var_indices
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