edit init files and md files

README.md

@@ -55,6 +55,7 @@ Here’s how we can define this problem in Python using the `ExampleProblem` cla
 
 ```python
 from numpy import power as pw
+import pycellga 
 
 class ExampleProblem:
 
@@ -68,18 +69,18 @@ class ExampleProblem:
 **Usage:**
 
 ```python
-result = optimizer.cga(
+result = pycellga.optimizer.cga(
     n_cols = 5,
     n_rows = 5,
     n_gen = 100,
     ch_size = 5,
-    gen_type = GeneType.REAL,
+    gen_type = pycellga.optimizer.GeneType.REAL,
     p_crossover = 0.9,
     p_mutation = 0.2,
     problem = ExampleProblem(),  # Replace with a real problem instance as needed
-    selection = optimizer.TournamentSelection,
-    recombination = optimizer.ByteOnePointCrossover,
-    mutation = optimizer.ByteMutationRandom,
+    selection = pycellga.optimizer.TournamentSelection,
+    recombination = pycellga.optimizer.ByteOnePointCrossover,
+    mutation = pycellga.optimizer.ByteMutationRandom,
     mins = [-32.768] * 5,  # Minimum values for each gene
     maxs = [32.768] * 5    # Maximum values for each gene
 )

paper/paper.md

@@ -73,6 +73,7 @@ Here’s how we can define this problem in Python using the `ExampleProblem` cla
 
 ```python
 from numpy import power as pw
+import pycellga 
 
 class ExampleProblem:
 
@@ -86,18 +87,18 @@ class ExampleProblem:
 **Usage:**
 
 ```python
-result = optimizer.cga(
+result = pycellga.optimizer.cga(
     n_cols = 5,
     n_rows = 5,
     n_gen = 100,
     ch_size = 5,
-    gen_type = GeneType.REAL,
+    gen_type = pycellga.optimizer.GeneType.REAL,
     p_crossover = 0.9,
     p_mutation = 0.2,
     problem = ExampleProblem(),  # Replace with a real problem instance as needed
-    selection = optimizer.TournamentSelection,
-    recombination = optimizer.ByteOnePointCrossover,
-    mutation = optimizer.ByteMutationRandom,
+    selection = pycellga.optimizer.TournamentSelection,
+    recombination = pycellga.optimizer.ByteOnePointCrossover,
+    mutation = pycellga.optimizer.ByteMutationRandom,
     mins = [-32.768] * 5,  # Minimum values for each gene
     maxs = [32.768] * 5    # Maximum values for each gene
 )

pycellga/__init__.py

@@ -0,0 +1,12 @@
+from . import example
+from . import mutation
+from . import neighborhoods
+from . import problems
+from . import recombination
+from . import selection
+from . import optimizer
+from . import population
+from . import individual
+from . import grid
+from . import byte_operators
+

pycellga/example/__init__.py

@@ -3,3 +3,8 @@
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 import optimizer
 from individual import GeneType
+from . import example_alpha_cga
+from . import example_ccga
+from . import example_cga
+from . import example_mcccga
+from . import example_sync_cga

pycellga/mutation/__init__.py

@@ -0,0 +1,9 @@
+from . import bit_flip_mutation
+from . import byte_mutation
+from . import byte_mutation_random
+from . import float_uniform_mutation
+from . import insertion_mutation
+from . import mutation_operator
+from . import shuffle_mutation
+from . import swap_mutation
+from . import two_opt_mutation

pycellga/neighborhoods/__init__.py

@@ -0,0 +1,6 @@
+from . import compact_9
+from . import compact_13
+from . import compact_21
+from . import compact_25
+from . import linear_5
+from . import linear_9

pycellga/problems/single_objective/continuous/__init__.py

@@ -0,0 +1,24 @@
+from . import ackley
+from . import bentcigar
+from . import bohachevsky
+from . import chichinadze
+from . import dropwave
+from . import fms
+from . import griewank
+from . import holzman
+from . import levy
+from . import matyas
+from . import pow
+from . import powell
+from . import rastrigin
+from . import rosenbrock
+from . import rothellipsoid
+from . import schaffer
+from . import schaffer2
+from . import schwefel
+from . import sphere
+from . import styblinskitang
+from . import sumofdifferentpowers
+from . import threehumps
+from . import zakharov
+from . import zettle

pycellga/problems/single_objective/discrete/binary/__init__.py

@@ -0,0 +1,9 @@
+from . import count_sat
+from . import ecc
+from . import fms
+from . import maxcut20_01
+from . import maxcut20_09
+from . import maxcut100
+from . import mmdp
+from . import one_max
+from . import peak

pycellga/problems/single_objective/discrete/permutation/__init__.py

@@ -0,0 +1 @@
+from . import tsp

pycellga/recombination/__init__.py

@@ -0,0 +1,12 @@
+from . import arithmetic_crossover
+from . import blxalpha_crossover
+from . import byte_one_point_crossover
+from . import byte_uniform_crossover
+from . import flat_crossover
+from . import linear_crossover
+from . import one_point_crossover
+from . import pmx_crossover
+from . import recombination_operator
+from . import two_point_crossover
+from . import unfair_avarage_crossover
+from . import uniform_crossover

pycellga/selection/__init__.py

@@ -0,0 +1,3 @@
+from . import roulette_wheel_selection
+from . import selection_operator
+from . import tournament_selection

setup.py

@@ -5,11 +5,12 @@
 
 setup(
     name='pycellga',  
-    version='0.1.8',  
+    version='0.2.1',  
     description='A Python Package for Improved Cellular Genetic Algorithms',  
     author='Sevgi Akten Karakaya, Mehmet Hakan Satman',  
     author_email='[email protected], [email protected]',  
-    packages=find_packages(),  
+    packages=find_packages(where="."),
+    package_dir={'pycellga': 'pycellga'},  
     install_requires=required, 
     classifiers=[
         'Programming Language :: Python :: 3',