258 lines
13 KiB
Python
258 lines
13 KiB
Python
# Karoo GP (desktop + server combined)
|
|
# Use Genetic Programming for Classification and Symbolic Regression
|
|
# by Kai Staats, MSc; see LICENSE.md
|
|
# version 2.1 final for Python 2.7
|
|
|
|
'''
|
|
A word to the newbie, expert, and brave--
|
|
Even if you are highly experienced in Genetic Programming, it is recommended that you review the 'Karoo User Guide'
|
|
before running this application. While your computer will not burst into flames nor will the sun collapse into a black
|
|
hole if you do not, you will likely find more enjoyment of this particular flavour of GP with a little understanding
|
|
of its intent and design.
|
|
|
|
Without any command line arguments, Karoo GP relies upon user settings and the datasets located in karoo_gp/files/.
|
|
|
|
$ python karoo_gp_main.py
|
|
|
|
|
|
If you include the path to an external dataset, it will auto-load at launch:
|
|
|
|
$ python karoo_gp_main.py /[path]/[to_your]/[filename].csv
|
|
|
|
|
|
If you include one or more additional arguments, they will override the default values, as follows:
|
|
|
|
-ker [r,c,m] fitness function: (r)egression, (c)lassification, or (m)atching
|
|
-typ [f,g,r] Tree type: (f)ull, (g)row, or (r)amped half/half
|
|
-bas [3...10] maximum Tree depth for initial population
|
|
-max [3...10] maximum Tree depth for entire run
|
|
-min [3 to 2^(bas +1) - 1] minimum number of nodes
|
|
-pop [10...1000] number of trees in each generational population
|
|
-gen [1...100] number of generations
|
|
-tor [7 per 100] number of trees selected for tournament
|
|
-evr [0.0...1.0] decimal percent of pop generated through Reproduction
|
|
-evp [0.0...1.0] decimal percent of pop generated through Point Mutation
|
|
-evb [0.0...1.0] decimal percent of pop generated through Branch Mutation
|
|
-evc [0.0...1.0] decimal percent of pop generated through Crossover
|
|
|
|
If you include any of the above flags, then you *must* also include a flag to load an external dataset.
|
|
|
|
-fil [path]/[to]/[data].csv an external dataset
|
|
|
|
|
|
An example is given, as follows:
|
|
|
|
$ python karoo_gp_server.py -ker c -typ r -bas 4 -fil [path]/[to]/[data].csv
|
|
|
|
'''
|
|
|
|
import os
|
|
import sys; sys.path.append('modules/') # add directory 'modules' to the current path
|
|
import argparse
|
|
import karoo_gp_base_class; gp = karoo_gp_base_class.Base_GP()
|
|
|
|
os.system('clear')
|
|
print '\n\033[36m\033[1m'
|
|
print '\t ** ** ****** ***** ****** ****** ****** ******'
|
|
print '\t ** ** ** ** ** ** ** ** ** ** ** ** **'
|
|
print '\t ** ** ** ** ** ** ** ** ** ** ** ** **'
|
|
print '\t **** ******** ****** ** ** ** ** ** *** *******'
|
|
print '\t ** ** ** ** ** ** ** ** ** ** ** ** **'
|
|
print '\t ** ** ** ** ** ** ** ** ** ** ** ** **'
|
|
print '\t ** ** ** ** ** ** ** ** ** ** ** ** **'
|
|
print '\t ** ** ** ** ** ** ****** ****** ****** **'
|
|
print '\033[0;0m'
|
|
print '\t\033[36m Genetic Programming in Python - by Kai Staats, version 2.1\033[0;0m'
|
|
print ''
|
|
|
|
|
|
#++++++++++++++++++++++++++++++++++++++++++
|
|
# User Interface for Configuation |
|
|
#++++++++++++++++++++++++++++++++++++++++++
|
|
|
|
if len(sys.argv) < 3: # either no command line argument (1) or a filename (2) is provided
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Select (c)lassification, (r)egression, (m)atching, or (p)lay (default m): ')
|
|
if query not in ['c','r','m','p','']: raise ValueError()
|
|
else: kernel = query or 'm'; break
|
|
except ValueError: print '\t\033[32m Select from the options given. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
if kernel == 'p': # play mode
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Select (f)ull or (g)row (default g): ')
|
|
if query not in ['f','g','']: raise ValueError()
|
|
else: tree_type = query or 'f'; break
|
|
except ValueError: print '\t\033[32m Select from the options given. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Enter the depth of the Tree (default 1): ')
|
|
if query not in str(range(1,11)) or query == '0': raise ValueError()
|
|
elif query == '': tree_depth_base = 1; break
|
|
else: tree_depth_base = int(query); break
|
|
except ValueError: print '\t\033[32m Enter a number from 1 including 10. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
tree_depth_max = tree_depth_base
|
|
tree_depth_min = 3
|
|
tree_pop_max = 1
|
|
gen_max = 1
|
|
tourn_size = 0
|
|
display = 'm'
|
|
# evolve_repro, evolve_point, evolve_branch, evolve_cross, tourn_size, precision, filename are not required
|
|
|
|
else: # if any other kernel is selected
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Select (f)ull, (g)row, or (r)amped 50/50 method (default r): ')
|
|
if query not in ['f','g','r','']: raise ValueError()
|
|
else: tree_type = query or 'r'; break
|
|
except ValueError: print '\t\033[32m Select from the options given. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Enter depth of the \033[3minitial\033[0;0m population of Trees (default 3): ')
|
|
if query not in str(range(1,11)) or query == '0': raise ValueError()
|
|
elif query == '': tree_depth_base = 3; break
|
|
else: tree_depth_base = int(query); break
|
|
except ValueError: print '\t\033[32m Enter a number from 1 including 10. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Enter maximum Tree depth (default %s): ' %str(tree_depth_base))
|
|
if query not in str(range(tree_depth_base,11)) or query == '0': raise ValueError()
|
|
elif query == '': tree_depth_max = tree_depth_base; break
|
|
else: tree_depth_max = int(query); break
|
|
except ValueError: print '\t\033[32m Enter a number > or = the initial Tree depth. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
max_nodes = 2**(tree_depth_base+1)-1 # calc the max number of nodes for the given depth
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Enter minimum number of nodes for any given Tree (default 3; max %s): ' %str(max_nodes))
|
|
if query not in str(range(3,max_nodes + 1)) or query == '0' or query == '1' or query == '2': raise ValueError()
|
|
elif query == '': tree_depth_min = 3; break
|
|
else: tree_depth_min = int(query); break
|
|
except ValueError: print '\t\033[32m Enter a number from 3 including %s. Try again ...\n\033[0;0m' %str(max_nodes)
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
#while True:
|
|
#try:
|
|
#swim = raw_input('\t Select (p)artial or (f)ull operator inclusion (default p): ')
|
|
#if swim not in ['p','f','']: raise ValueError()
|
|
#swim = swim or 'p'; break
|
|
#except ValueError: print '\t\033[32m Select from the options given. Try again ...\n\033[0;0m'
|
|
#except KeyboardInterrupt: sys.exit()
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Enter number of Trees in each population (default 100): ')
|
|
if query not in str(range(1,1001)) or query == '0': raise ValueError()
|
|
elif query == '': tree_pop_max = 100; break
|
|
else: tree_pop_max = int(query); break
|
|
except ValueError: print '\t\033[32m Enter a number from 1 including 1000. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
# calculate the tournament size
|
|
tourn_size = int(tree_pop_max * 0.07) # default 7% can be changed by selecting (g)eneration and then 'ts'
|
|
if tourn_size < 2: tourn_size = 2 # forces some diversity for small populations
|
|
if tree_pop_max == 1: tourn_size = 1 # in theory, supports the evolution of a single Tree - NEED TO FIX 2018 04/19
|
|
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Enter max number of generations (default 10): ')
|
|
if query not in str(range(1,101)) or query == '0': raise ValueError()
|
|
elif query == '': gen_max = 10; break
|
|
gen_max = int(query); break
|
|
except ValueError: print '\t\033[32m Enter a number from 1 including 100. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
if gen_max > 1:
|
|
while True:
|
|
try:
|
|
query = raw_input('\t Display (i)nteractive, (g)eneration, (m)iminal, (s)ilent, or (d)e(b)ug (default m): ')
|
|
if query not in ['i','g','m','s','db','']: raise ValueError()
|
|
display = query or 'm'; break
|
|
except ValueError: print '\t\033[32m Select from the options given. Try again ...\n\033[0;0m'
|
|
except KeyboardInterrupt: sys.exit()
|
|
|
|
else: display = 's' # display mode is not used, but a value must be passed
|
|
|
|
### additional configuration parameters ###
|
|
|
|
evolve_repro = int(0.1 * tree_pop_max) # quantity of a population generated through Reproduction
|
|
evolve_point = int(0.0 * tree_pop_max) # quantity of a population generated through Point Mutation
|
|
evolve_branch = int(0.2 * tree_pop_max) # quantity of a population generated through Branch Mutation
|
|
evolve_cross = int(0.7 * tree_pop_max) # quantity of a population generated through Crossover
|
|
filename = '' # not required unless an external file is referenced
|
|
precision = 6 # number of floating points for the round function in 'fx_fitness_eval'
|
|
swim = 'p' # require (p)artial or (f)ull set of features (operators) for each Tree entering the gene_pool
|
|
mode = 'd' # pause at the (d)esktop when complete, awaiting further user interaction; or terminate in (s)erver mode
|
|
|
|
|
|
#++++++++++++++++++++++++++++++++++++++++++
|
|
# Command Line for Configuation |
|
|
#++++++++++++++++++++++++++++++++++++++++++
|
|
|
|
else: # two or more command line arguments provided
|
|
|
|
ap = argparse.ArgumentParser(description = 'Karoo GP Server')
|
|
ap.add_argument('-ker', action = 'store', dest = 'kernel', default = 'c', help = '[c,r,m] fitness function: (r)egression, (c)lassification, or (m)atching')
|
|
ap.add_argument('-typ', action = 'store', dest = 'type', default = 'r', help = '[f,g,r] Tree type: (f)ull, (g)row, or (r)amped half/half')
|
|
ap.add_argument('-bas', action = 'store', dest = 'depth_base', default = 4, help = '[3...10] maximum Tree depth for the initial population')
|
|
ap.add_argument('-max', action = 'store', dest = 'depth_max', default = 4, help = '[3...10] maximum Tree depth for the entire run')
|
|
ap.add_argument('-min', action = 'store', dest = 'depth_min', default = 3, help = 'minimum nodes, from 3 to 2^(base_depth +1) - 1')
|
|
ap.add_argument('-pop', action = 'store', dest = 'pop_max', default = 100, help = '[10...1000] number of trees per generation')
|
|
ap.add_argument('-gen', action = 'store', dest = 'gen_max', default = 10, help = '[1...100] number of generations')
|
|
ap.add_argument('-tor', action = 'store', dest = 'tor_size', default = 7, help = '[7 for each 100] recommended tournament size')
|
|
ap.add_argument('-evr', action = 'store', dest = 'evo_r', default = 0.1, help = '[0.0-1.0] decimal percent of pop generated through Reproduction')
|
|
ap.add_argument('-evp', action = 'store', dest = 'evo_p', default = 0.0, help = '[0.0-1.0] decimal percent of pop generated through Point Mutation')
|
|
ap.add_argument('-evb', action = 'store', dest = 'evo_b', default = 0.2, help = '[0.0-1.0] decimal percent of pop generated through Branch Mutation')
|
|
ap.add_argument('-evc', action = 'store', dest = 'evo_c', default = 0.7, help = '[0.0-1.0] decimal percent of pop generated through Crossover')
|
|
ap.add_argument('-fil', action = 'store', dest = 'filename', default = '', help = '/path/to_your/[data].csv')
|
|
|
|
args = ap.parse_args()
|
|
|
|
# pass the argparse defaults and/or user inputs to the required variables
|
|
kernel = str(args.kernel)
|
|
tree_type = str(args.type)
|
|
tree_depth_base = int(args.depth_base)
|
|
tree_depth_max = int(args.depth_max)
|
|
tree_depth_min = int(args.depth_min)
|
|
tree_pop_max = int(args.pop_max)
|
|
gen_max = int(args.gen_max)
|
|
tourn_size = int(args.tor_size)
|
|
evolve_repro = int(float(args.evo_r) * tree_pop_max)
|
|
evolve_point = int(float(args.evo_p) * tree_pop_max)
|
|
evolve_branch = int(float(args.evo_b) * tree_pop_max)
|
|
evolve_cross = int(float(args.evo_c) * tree_pop_max)
|
|
filename = str(args.filename)
|
|
|
|
display = 's' # display mode is set to (s)ilent
|
|
precision = 6 # number of floating points for the round function in 'fx_fitness_eval'
|
|
swim = 'p' # require (p)artial or (f)ull set of features (operators) for each Tree entering the gene_pool
|
|
mode = 's' # pause at the (d)esktop when complete, awaiting further user interaction; or terminate in (s)erver mode
|
|
|
|
|
|
#++++++++++++++++++++++++++++++++++++++++++
|
|
# Conduct the GP run |
|
|
#++++++++++++++++++++++++++++++++++++++++++
|
|
|
|
gp.fx_karoo_gp(kernel, tree_type, tree_depth_base, tree_depth_max, tree_depth_min, tree_pop_max, gen_max, tourn_size, filename, evolve_repro, evolve_point, evolve_branch, evolve_cross, display, precision, swim, mode)
|
|
|
|
print '\n\033[3m "It is not the strongest of the species that survive, nor the most intelligent,\033[0;0m'
|
|
print '\033[3m but the one most responsive to change."\033[0;0m --Charles Darwin\n'
|
|
print '\033[3m Congrats!\033[0;0m Your Karoo GP run is complete.\n'
|
|
sys.exit()
|
|
|
|
|