The Problem with the Implicit Version

Oct 13, 2025 by talynt.org 93 views

Introduction

In the documentation of Pyrimidine, an example is provided to demonstrate the equivalence of two different ways of defining an individual class. However, while the first approach runs without issues, the second one fails with a ValueError. This article aims to investigate the reason behind this discrepancy and provide a solution.

The Issue

The example in question is as follows:

# Define the individual class
class MyIndividual(MonoIndividual):
    element_class = BinaryChromosome // n_bags
    def _fitness(self) -> float:
        # To evaluate an individual!
        return _evaluate(self.chromosome)

""" Equiv. to
    MyIndividual = MonoIndividual[BinaryChromosome//n_bags].set_fitness(_evaluate)
"""

The second approach, which is stated to be equivalent, fails with a ValueError. The issue seems to be that the 'explicit' version passes MonoIndividual.chromosome to _evaluate, while the implicit version directly passes the MonoIndividual.

The Error Message

The error message is as follows:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

This error occurs when the code tries to evaluate the fitness of an individual using the _evaluate function.

The Solution

To fix this issue, we can wrap the _evaluate function in a lambda function to pass the chromosome attribute of the individual. The corrected code is as follows:

MyIndividual = MonoIndividual[BinaryChromosome//n_bags].set_fitness(lambda x: _evaluate(x.chromosome))

This solution works because the lambda function allows us to pass the chromosome attribute of the individual to the _evaluate function.

Conclusion

In conclusion, the stated equivalence in the example does not work due to the way the _evaluate function is called. By wrapping the _evaluate function in a lambda function, we can pass the chromosome attribute of the individual and fix the issue.

Understanding the Issue

To understand the issue, we need to look at the way the _evaluate function is called in the two different approaches. In the explicit version, the chromosome attribute of the individual is passed to the _evaluate function. However, in the implicit version, the MonoIndividual object is passed directly to the _evaluate function.

The Problem with the Implicit Version

The problem with the implicit version is that it does not pass the chromosome attribute of the individual to the _evaluate function. Instead, it passes the MonoIndividual object itself. This causes the _evaluate function to try to evaluate the fitness of the individual using the MonoIndividual object, which is not what we want.

The Solution: Wrapping the `_evaluate` Function

To fix this issue, we can wrap the _evaluate function in a lambda function. This allows us to pass the chromosome attribute of the individual to the _evaluate function, which is what we want.

The Corrected Code

The corrected code is as follows:

MyIndividual = MonoIndividual[BinaryChromosome//n_bags].set_fitness(lambda x: _evaluate(x.chromosome))

This code works because the lambda function allows us to pass the chromosome attribute of the individual to the _evaluate function.

Conclusion

Future Work

In the future, we can improve the documentation of Pyrimidine to make it clear that the implicit version of the code is not equivalent to the explicit version. We can also provide more examples and explanations to help users understand the issue and the solution.

References

Pyrimidine documentation: https://pyrimidine.readthedocs.io/en/latest/source/Examples.html
Stack Overflow: https://stackoverflow.com/questions/49261933/valueerror-the-truth-value-of-an-array-with-more-than-one-element-is-ambiguou
Stated Equivalence in Example Does Not Work: Q&A =====================================================

Q: What is the issue with the stated equivalence in the example?

A: The issue is that the implicit version of the code, which is stated to be equivalent to the explicit version, fails with a ValueError. This is because the _evaluate function is called with the MonoIndividual object instead of the chromosome attribute of the individual.

Q: What is the difference between the explicit and implicit versions of the code?

A: The explicit version of the code defines the individual class with a _fitness method that calls the _evaluate function with the chromosome attribute of the individual. The implicit version of the code defines the individual class with a set_fitness method that calls the _evaluate function with the MonoIndividual object.

Q: Why does the implicit version of the code fail with a ValueError?

A: The implicit version of the code fails with a ValueError because the _evaluate function is called with the MonoIndividual object instead of the chromosome attribute of the individual. This causes the _evaluate function to try to evaluate the fitness of the individual using the MonoIndividual object, which is not what we want.

Q: How can we fix the issue with the implicit version of the code?

A: We can fix the issue with the implicit version of the code by wrapping the _evaluate function in a lambda function. This allows us to pass the chromosome attribute of the individual to the _evaluate function, which is what we want.

Q: What is the corrected code for the implicit version of the example?

A: The corrected code for the implicit version of the example is as follows:

MyIndividual = MonoIndividual[BinaryChromosome//n_bags].set_fitness(lambda x: _evaluate(x.chromosome))

Q: Why is the explicit version of the code not equivalent to the implicit version?

A: The explicit version of the code is not equivalent to the implicit version because the _evaluate function is called with the chromosome attribute of the individual in the explicit version, but with the MonoIndividual object in the implicit version.

Q: What are the implications of this issue for users of Pyrimidine?

A: The implications of this issue for users of Pyrimidine are that they need to be aware of the difference between the explicit and implicit versions of the code, and use the explicit version if they want to call the _evaluate function with the chromosome attribute of the individual.

Q: How can users of Pyrimidine avoid this issue in the future?

A: Users of Pyrimidine can avoid this issue in the future by using the explicit version of the code, which defines the individual class with a _fitness method that calls the _evaluate function with the chromosome attribute of the individual.

Q: What is the next step for Pyrimidine developers to address this issue?

A: The next step for Pyrimidine developers is to update the documentation to reflect the difference between the explicit and implicit versions of the code, and to provide more examples and explanations to help users understand the issue and the solution.

Q: How can users of Pyrimidine provide feedback on this issue?

A: Users of Pyrimidine can provide feedback on this issue by submitting a bug report or a feature request to the Pyrimidine developers. They can also provide feedback by commenting on the issue on the Pyrimidine GitHub page.