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version number sync

pull/4/head
Kai Staats 2016-07-14 23:58:24 -06:00
parent f705ce4f34
commit 2f6fc1784a
2 changed files with 27 additions and 12 deletions
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37
karoo_gp_base_class.py
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@ -2,7 +2,7 @@
# Define the methods and global variables used by Karoo GP
# by Kai Staats, MSc UCT / AIMS
# Much thanks to Emmanuel Dufourq and Arun Kumar for their support, guidance, and free psychotherapy sessions
# version 0.9.1.6c
# version 0.9.1.7
'''
A NOTE TO THE NEWBIE, EXPERT, AND BRAVE
@ -356,8 +356,9 @@ class Base_GP(object):
'''
As used by the method 'karoo_gp', this method constructs the initial population based upon the user-defined
Tree type and initial, maximum Tree depth. "Ramped half/half" is currently not ramped, rather split 50/50
Full/Grow. This will be updated with a future version of Karoo GP.
Tree type and initial, maximum Tree depth ('tree_depth_base'). "Ramped half/half" was defined by John Koza as
a means of building maximum diversity in the initial population. There are equal numbers of Full and Grow
methods trees, and an equal spread of Trees across depths 1 to 'tree_depth_base'.
Arguments required: tree_type, tree_depth_base
'''
@ -367,14 +368,26 @@ class Base_GP(object):
self.fx_karoo_pause(0)
if tree_type == 'r': # Ramped 50/50
for TREE_ID in range(1, int(self.tree_pop_max / 2) + 1):
self.fx_gen_tree_build(TREE_ID, 'f', tree_depth_base) # build 1/2 of the 1st generation of Trees as Full
self.fx_tree_append(self.tree) # append each Tree in the first generation to the list 'gp.population_a'
for TREE_ID in range(int(self.tree_pop_max / 2) + 1, self.tree_pop_max + 1):
self.fx_gen_tree_build(TREE_ID, 'g', tree_depth_base) # build 2/2 of the 1st generation of Trees as Grow
self.fx_tree_append(self.tree)
TREE_ID = 1
for n in range(1, int((self.tree_pop_max / 2) / tree_depth_base) + 1): # split the population into equal parts
for depth in range(1, tree_depth_base + 1): # build 2 Trees ats each depth
self.fx_gen_tree_build(TREE_ID, 'f', depth) # build a Full Tree
self.fx_tree_append(self.tree) # append Tree to the list 'gp.population_a'
TREE_ID = TREE_ID + 1
self.fx_gen_tree_build(TREE_ID, 'g', depth) # build a Grow Tree
self.fx_tree_append(self.tree) # append Tree to the list 'gp.population_a'
TREE_ID = TREE_ID + 1
if TREE_ID < self.tree_pop_max: # eg: split 100 by 2*3 and it will produce only 96 Trees ...
for n in range(self.tree_pop_max - TREE_ID + 1): # ... so we complete the run
self.fx_gen_tree_build(TREE_ID, 'g', tree_depth_base)
self.fx_tree_append(self.tree)
TREE_ID = TREE_ID + 1
else: pass
else: # Full or Grow
for TREE_ID in range(1, self.tree_pop_max + 1):
self.fx_gen_tree_build(TREE_ID, tree_type, tree_depth_base) # build the 1st generation of Trees
@ -1925,6 +1938,8 @@ class Base_GP(object):
crossover = int(branch_x[0]) # pointer to the top of the 1st parent branch passed from 'fx_karoo_crossover'
branch_top = int(branch_y[0]) # pointer to the top of the 2nd parent branch passed from 'fx_karoo_crossover'
if self.display == 'db': print '\n\n\033[33m *** Crossover *** \033[0;0m'
if len(branch_x) == 1: # if the branch from the parent contains only one node (terminal)
if self.display == 'i': print '\t\033[36m terminal crossover from \033[1mparent', parent[0][1], '\033[0;0m\033[36mto \033[1moffspring', offspring[0][1], '\033[0;0m\033[36mat node\033[1m', branch_top, '\033[0;0m'

2
karoo_gp_server.py
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@ -2,7 +2,7 @@
# Use Genetic Programming for Classification and Symbolic Regression
# by Kai Staats, MSc UCT / AIMS
# Much thanks to Emmanuel Dufourq and Arun Kumar for their support, guidance, and free psychotherapy sessions
# version 0.9.1.6
# version 0.9.1.7
'''
A word to the newbie, expert, and brave--