While learning python, I decided to try create genetic algorithm and got stuck in the mutation step.

I will be glad for any advice both on solving this problem and in general on the architecture and style of the code.

one_generation = genlib.create_generation()
print(genlib.almost_generation(one_generation))

This code return error:

Traceback (most recent call last):
File "/home/rosrobot/PycharmProjects/gen2/main.py", line 23, in \<module\>
print(genlib.almost_generation(one_generation))

File "/home/rosrobot/PycharmProjects/gen2/genlib.py", line 83, in almost_generation
updated_generation.loc\[creature_index\] = sample\[updated_generation.columns\]

File "/home/rosrobot/PycharmProjects/gen2/venv/lib64/python3.10/site-packages/pandas/core/indexing.py", line 716, in __setitem__
iloc.\_setitem_with_indexer(indexer, value, self.name)

File "/home/rosrobot/PycharmProjects/gen2/venv/lib64/python3.10/site-packages/pandas/core/indexing.py", line 1682, in \_setitem_with_indexer
self.\_setitem_with_indexer_missing(indexer, value)

File "/home/rosrobot/PycharmProjects/gen2/venv/lib64/python3.10/site-packages/pandas/core/indexing.py", line 1998, in \_setitem_with_indexer_missing
raise ValueError("cannot set a row with mismatched columns")
ValueError: cannot set a row with mismatched columns

Process finished with exit code 1

Functions in 'genlib' file:

import random as rnd
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

pd.plotting.register_matplotlib_converters()

def create_creature(gen_length=10,
                    creature_name='one'):
    creature = pd.Series(data=[rnd.randint(0, 1) for i in range(gen_length)],
                         name=creature_name)
    return creature

def create_generation(generation_size=50,
                      gen_length=10):
    generation = pd.DataFrame(data=[create_creature(creature_name=(str(i   1))   'th',
                                                    gen_length=gen_length) for i in range(generation_size)])
    generation['quality'] = generation.sum(axis=1)
    return generation

def __indexes_of_quality(generation):
    """
    :rtype: pd.Series
    """
    for i in generation.quality.unique():
        print('quality = ', i, ': ',
              generation.loc[generation.quality == i, 'quality'].index.values,
              '\n',
              '__')

def create_many_generations(number_of_generations=10,
                            generation_size=50,
                            gen_length=10):
    list_of_dataframes = pd.Series(data=[create_generation(generation_size=generation_size,
                                                           gen_length=gen_length
                                                           ) for i in range(number_of_generations)],
                                   name='creature_name')

    return list_of_dataframes

def one_generation_pyplot(generation):
    sns.barplot(x=generation.index,
                y=generation.sort_values('quality').quality)
    plt.show()

def many_generations_pyplot(list_of_generations):
    qualities = [sum(generation.quality) for generation in list_of_generations]
    sns.lineplot(data=qualities)
    plt.show()

def __mutation(creature: pd.Series) -> pd.Series:
    point = rnd.randint(0, len(creature))
    creature[point] = int(not creature[point].values)
    return creature

def almost_generation(generation):
    sample = generation.sample()
    sample = __mutation(sample)

    updated_generation = pd.DataFrame(columns=generation.columns)
    for creature_index in generation.index:
        if creature_index == sample.index:
            print(creature_index, ' == ', sample.index)
            updated_generation.loc[creature_index] = sample[updated_generation.columns]
        else:
            updated_generation.loc[creature_index] = generation.loc[creature_index]
    return updated_generation

I tried to convert "sample" to str, and also tried using loc, iloc and append

CodePudding user response：

In your almost generation function, change the line within your if block to assign values:

if creature_index == sample.index:
    print(creature_index, ' == ', sample.index)
    updated_generation.loc[creature_index] = sample[updated_generation.columns].values

You can just simplify your entire function as follows:

def almost_generation(generation):
    sample = generation.sample()
    sample = __mutation(sample)
    generation.loc[sample.index] = sample[generation.columns].values
    return generation