55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
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'''
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This module calculates the reduction ratio for trust-region methods.
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Translated from Zaikun Zhang's modern-Fortran reference implementation in PRIMA.
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Dedicated to late Professor M. J. D. Powell FRS (1936--2015).
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Python translation by Nickolai Belakovski.
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'''
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from .consts import DEBUGGING, REALMAX
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import numpy as np
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def redrat(ared, pred, rshrink):
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'''
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This function evaluates the reduction ratio of a trust-region step, handling inf/nan properly.
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'''
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# Preconditions
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if DEBUGGING:
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assert rshrink >= 0
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#====================#
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# Calculation starts #
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#====================#
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if np.isnan(ared):
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# This should not happen in unconstrained problems due to the moderated extreme barrier.
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ratio = -REALMAX
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elif np.isnan(pred) or pred <= 0:
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# The trust-region subproblem solver fails in this rare case. Instead of terminating as Powell's
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# original code does, we set ratio as follows so that the solver may continue to progress.
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if ared > 0:
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# The trial point will be accepted, but the trust-region radius will be shrunk if rshrink>0
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ratio = rshrink/2
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else:
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# Set the ration to a large negative number to signify a bad trust-region step, so that the
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# solver will check whether to take a geometry step or reduce rho.
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ratio = -REALMAX
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elif np.isposinf(pred) and np.isposinf(ared):
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ratio = 1 # ared/pred = NaN if calculated directly
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elif np.isposinf(pred) and np.isneginf(ared):
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ratio = -REALMAX # ared/pred = NaN if calculated directly
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else:
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ratio = ared/pred
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#==================#
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# Calculation ends #
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#==================#
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# Postconditions
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if DEBUGGING:
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assert not np.isnan(ratio)
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return ratio
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