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35 lines
1.3 KiB
Python
35 lines
1.3 KiB
Python
import numpy as np
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import warnings
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from .. import kern
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def build_lcm(input_dim, num_outputs, CK = [], NC = [], W_columns=1,W=None,kappa=None):
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#TODO build_icm or build_lcm
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"""
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Builds a kernel for a linear coregionalization model
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:input_dim: Input dimensionality
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:num_outputs: Number of outputs
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:param CK: List of coregionalized kernels (i.e., this will be multiplied by a coregionalize kernel).
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:param K: List of kernels that will be added up together with CK, but won't be multiplied by a coregionalize kernel
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:param W_columns: number tuples of the corregionalization parameters 'coregion_W'
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:type W_columns: integer
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"""
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for k in CK:
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if k.input_dim <> input_dim:
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k.input_dim = input_dim
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warnings.warn("kernel's input dimension overwritten to fit input_dim parameter.")
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for k in NC:
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if k.input_dim <> input_dim + 1:
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k.input_dim = input_dim + 1
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warnings.warn("kernel's input dimension overwritten to fit input_dim parameter.")
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kernel = CK[0].prod(kern.coregionalize(num_outputs,W_columns,W,kappa),tensor=True)
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for k in CK[1:]:
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k_coreg = kern.coregionalize(num_outputs,W_columns,W,kappa)
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kernel += k.prod(k_coreg,tensor=True)
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for k in NC:
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kernel += k
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return kernel
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