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fixed menu bug

pull/13/head
kstaats 2018-05-19 00:39:56 -07:00
parent 2ca722875f
commit 667e9d0da8
2 changed files with 57 additions and 45 deletions
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6
RELEASE_NOTES.txt
View File

@ -1,3 +1,9 @@
2018 05/18
Fixed a bug which automically re-engaged the run after selecting a pause menu option if mid generation. Now, it
correctly again require an ENTER before continuing.
2018 05/10
Returned full_path = os.path.realpath(__file__) (approx. line 342) to support bash scripting of automated runs. This

96
modules/karoo_gp_base_class.py
View File

@ -2,7 +2,7 @@
# Define the methods and global variables used by Karoo GP
# by Kai Staats, MSc; see LICENSE.md
# Thanks to Emmanuel Dufourq and Arun Kumar for support during 2014-15 devel; TensorFlow support provided by Iurii Milovanov
# version 2.1.1
# version 2.1.2
'''
A NOTE TO THE NEWBIE, EXPERT, AND BRAVE
@ -169,7 +169,8 @@ class Base_GP(object):
### 2) construct first generation of Trees ###
self.fx_data_load(filename)
self.gen_id = 1 # set initial generation ID
self.population_a = ['Karoo GP by Kai Staats, Generation ' + str(self.gen_id)] # list to store all Tree arrays, one generation at a time
self.population_a = ['Karoo GP by Kai Staats, Generation ' + str(self.gen_id)] # initialise population_a to host the first generation
self.population_b = ['placeholder'] # initialise population_b to satisfy fx_karoo_pause()
self.fx_init_construct(tree_type, tree_depth_base) # construct the first population of Trees
if self.kernel == 'p': # EOL for Play mode
@ -212,7 +213,7 @@ class Base_GP(object):
elif mode == 'd': # provide the user with the option to reconfigure and continue
# self.fx_data_params_write('Desktop') # removed 2018 04/22 as this is executed in fx_karoo_pause / 'quit'
print '\n\t\033[36m Enter \033[1m?\033[0;0m\033[36m to review your options or \033[1mq\033[0;0m\033[36m to quit.\033[0;0m'
eol = self.fx_karoo_pause()
eol = self.fx_karoo_pause(1)
### 5) archive populations and return to karoo_gp.py to terminate the run ###
target = open(self.filename['f'], 'w'); target.close() # initialize the .csv file for the final population
@ -221,22 +222,17 @@ class Base_GP(object):
return
def fx_karoo_pause(self):
def fx_karoo_pause(self, pause):
'''
Pause the program execution and engage the user, providing a number of options.
The "eol" parameter instructs this
method to display a different screen for run-time or end-of-line, and to dive back into the current run, or do
nothing, accordingly.
Called by: throughout this base_class library
Arguments required: none
'''
### 1) reset and pack values to send to menu.pause ###
menu_dict = {'input_a':'',
'input_b':0,
'display':self.display,
@ -268,9 +264,7 @@ class Base_GP(object):
self.evolve_cross = menu_dict['evolve_cross']
### 3) execute the user queries returned from menu.pause ###
eol = 0
if menu_dict['input_a'] == 'esc': return eol # ENTER enables next step in generational, interactive, and debug display
if menu_dict['input_a'] == 'esc': return 0 # ENTER enables next step in generational, interactive, and debug display
elif menu_dict['input_a'] == 'test': # evaluate a Tree against the TEST data
expr = str(self.algo_sym) # might change this to algo_raw for more correct expression evaluation
@ -315,9 +309,21 @@ class Base_GP(object):
elif menu_dict['input_a'] == 'quit': # quit and save run-time parameters to disk
self.fx_data_params_write('Desktop')
print '\n\t \033[32mYour Trees and runtime parameters are archived in karoo_gp/runs/[date-time]/\033[0;0m'
eol = 1
return eol
if pause == 0: sys.exit() # force quit due to being one level below the while loop
else: return 1
if pause == 0: # ENTER enables next step in generational, interactive, and debug display
while True:
try:
query = raw_input('\n\t\033[36m (pause) \033[0;0m')
if query not in ['']: raise ValueError()
else: break
except ValueError: print '\t\033[32m Select from the options given. Try again ...\033[0;0m'
except KeyboardInterrupt: print '\n\t\033[32m Enter q to quit\033[0;0m'
else: pass
return 0
#+++++++++++++++++++++++++++++++++++++++++++++
@ -638,7 +644,7 @@ class Base_GP(object):
if self.display == 'i' or self.display == 'g':
print '\n\t Type \033[1m?\033[0;0m at any (pause) to review your options, or \033[1mENTER\033[0;0m to continue.\033[0;0m'
self.fx_karoo_pause()
self.fx_karoo_pause(0)
if tree_type == 'r': # Ramped 50/50
@ -756,7 +762,7 @@ class Base_GP(object):
self.pop_node_c2 = 3
self.pop_node_c3 = 4
else: print '\n\t\033[31m ERROR! In fx_init_root_build: pop_node_arity =', self.pop_node_arity, '\033[0;0m'; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_init_root_build: pop_node_arity =', self.pop_node_arity, '\033[0;0m'; self.fx_karoo_pause(0)
self.pop_node_type = 'root'
@ -958,7 +964,7 @@ class Base_GP(object):
self.pop_node_c2 = c_buffer + 1
self.pop_node_c3 = c_buffer + 2
else: print '\n\t\033[31m ERROR! In fx_init_child_link: pop_node_arity =', self.pop_node_arity, '\033[0;0m'; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_init_child_link: pop_node_arity =', self.pop_node_arity, '\033[0;0m'; self.fx_karoo_pause(0)
return
@ -1082,7 +1088,7 @@ class Base_GP(object):
if self.display != 's':
if self.display == 'i': print ''
print '\n Evaluate all Trees in Generation', self.gen_id
if self.display == 'i': self.fx_karoo_pause()
if self.display == 'i': self.fx_karoo_pause(0)
for tree_id in range(1, len(self.population_b)): # renumber all Trees in given population - merged fx_evolve_tree_renum 2018 04/12
self.population_b[tree_id][0][1] = tree_id
@ -1169,7 +1175,7 @@ class Base_GP(object):
# self.fittest_dict.update({tree_id:self.algo_sym}) # add to dictionary
print '\n\033[36m ', len(self.fittest_dict.keys()), 'trees\033[1m', np.sort(self.fittest_dict.keys()), '\033[0;0m\033[36moffer the highest fitness scores.\033[0;0m'
if self.display == 'g': self.fx_karoo_pause()
if self.display == 'g': self.fx_karoo_pause(0)
return
@ -1501,7 +1507,7 @@ class Base_GP(object):
# tourn_lead remains unchanged
# tourn_test remains unchanged
else: print '\n\t\033[31m ERROR! In fx_fitness_tournament: fitness =', fitness, 'and tourn_test =', tourn_test, '\033[0;0m'; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_fitness_tournament: fitness =', fitness, 'and tourn_test =', tourn_test, '\033[0;0m'; self.fx_karoo_pause(0)
elif self.fitness_type == 'min': # if the fitness function is Minimising
@ -1524,7 +1530,7 @@ class Base_GP(object):
# tourn_lead remains unchanged
# tourn_test remains unchanged
else: print '\n\t\033[31m ERROR! In fx_fitness_tournament: fitness =', fitness, 'and tourn_test =', tourn_test, '\033[0;0m'; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_fitness_tournament: fitness =', fitness, 'and tourn_test =', tourn_test, '\033[0;0m'; self.fx_karoo_pause(0)
tourn_winner = np.copy(self.population_a[tourn_lead]) # copy full Tree so as to not inadvertantly modify the original tree
@ -1560,7 +1566,7 @@ class Base_GP(object):
'''
self.gene_pool = []
if self.display == 'i': print '\n Prepare a viable gene pool ...'; self.fx_karoo_pause()
if self.display == 'i': print '\n Prepare a viable gene pool ...'; self.fx_karoo_pause(0)
for tree_id in range(1, len(self.population_a)):
@ -1580,12 +1586,12 @@ class Base_GP(object):
# build your selection process
# if self.display == 'i': print '\t\033[36m Tree', tree_id, '[screen readout for interactive mode]\033[0;0m'
if len(self.gene_pool) > 0 and self.display == 'i': print '\n\t The total population of the gene pool is', len(self.gene_pool); self.fx_karoo_pause()
if len(self.gene_pool) > 0 and self.display == 'i': print '\n\t The total population of the gene pool is', len(self.gene_pool); self.fx_karoo_pause(0)
elif len(self.gene_pool) <= 0: # the evolutionary constraints were too tight, killing off the entire population
# self.gen_id = self.gen_id - 1 # revert the increment of the 'gen_id'
# self.gen_max = self.gen_id # catch the unused "cont" values in the 'fx_karoo_pause' method
print "\n\t\033[31m\033[3m 'They're dead Jim. They're all dead!'\033[0;0m There are no Trees in the gene pool. You should archive your population and (q)uit."; self.fx_karoo_pause()
print "\n\t\033[31m\033[3m 'They're dead Jim. They're all dead!'\033[0;0m There are no Trees in the gene pool. You should archive your population and (q)uit."; self.fx_karoo_pause(0)
return
@ -1695,7 +1701,7 @@ class Base_GP(object):
if self.display != 's':
if self.display == 'i': print ''
print ' Perform', self.evolve_repro, 'Reproductions ...'
if self.display == 'i': self.fx_karoo_pause()
if self.display == 'i': self.fx_karoo_pause(0)
for n in range(self.evolve_repro): # quantity of Trees to be copied without mutation
tourn_winner = self.fx_fitness_tournament(self.tourn_size) # perform tournament selection for each reproduction
@ -1721,7 +1727,7 @@ class Base_GP(object):
if self.display != 's':
if self.display == 'i': print ''
print ' Perform', self.evolve_point, 'Point Mutations ...'
if self.display == 'i': self.fx_karoo_pause()
if self.display == 'i': self.fx_karoo_pause(0)
for n in range(self.evolve_point): # quantity of Trees to be generated through mutation
tourn_winner = self.fx_fitness_tournament(self.tourn_size) # perform tournament selection for each mutation
@ -1749,7 +1755,7 @@ class Base_GP(object):
if self.display != 's':
if self.display == 'i': print ''
print ' Perform', self.evolve_branch, 'Branch Mutations ...'
if self.display == 'i': self.fx_karoo_pause()
if self.display == 'i': self.fx_karoo_pause(0)
for n in range(self.evolve_branch): # quantity of Trees to be generated through mutation
tourn_winner = self.fx_fitness_tournament(self.tourn_size) # perform tournament selection for each mutation
@ -1792,7 +1798,7 @@ class Base_GP(object):
if self.display != 's':
if self.display == 'i': print ''
print ' Perform', self.evolve_cross, 'Crossovers ...'
if self.display == 'i': self.fx_karoo_pause()
if self.display == 'i': self.fx_karoo_pause(0)
for n in range(self.evolve_cross / 2): # quantity of Trees to be generated through Crossover, accounting for 2 children each
@ -1844,11 +1850,11 @@ class Base_GP(object):
rnd = np.random.randint(0, len(self.terminals) - 1) # call the previously loaded .csv which contains all terminals
tree[6][node] = self.terminals[rnd] # replace terminal (variable)
else: print '\n\t\033[31m ERROR! In fx_evolve_point_mutate, node_type =', tree[5][node], '\033[0;0m'; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_evolve_point_mutate, node_type =', tree[5][node], '\033[0;0m'; self.fx_karoo_pause(0)
tree = self.fx_evolve_fitness_wipe(tree) # wipe fitness data
if self.display == 'db': print '\n\033[36m This is tourn_winner after node\033[1m', node, '\033[0;0m\033[36mmutation and updates:\033[0;0m\n', tree; self.fx_karoo_pause()
if self.display == 'db': print '\n\033[36m This is tourn_winner after node\033[1m', node, '\033[0;0m\033[36mmutation and updates:\033[0;0m\n', tree; self.fx_karoo_pause(0)
return tree, node # 'node' is returned only to be assigned to the 'tourn_trees' record keeping
@ -1887,7 +1893,7 @@ class Base_GP(object):
tree = self.fx_evolve_fitness_wipe(tree) # wipe fitness data
if self.display == 'db': print '\n\033[36m This is tourn_winner after nodes\033[1m', branch, '\033[0;0m\033[36mwere mutated and updated:\033[0;0m\n', tree; self.fx_karoo_pause()
if self.display == 'db': print '\n\033[36m This is tourn_winner after nodes\033[1m', branch, '\033[0;0m\033[36mwere mutated and updated:\033[0;0m\n', tree; self.fx_karoo_pause(0)
return tree
@ -1922,7 +1928,7 @@ class Base_GP(object):
if branch_depth < 0: # this has never occured ... yet
print '\n\t\033[31m ERROR! In fx_evolve_grow_mutate: branch_depth < 0\033[0;0m'
print '\t branch_depth =', branch_depth; self.fx_karoo_pause()
print '\t branch_depth =', branch_depth; self.fx_karoo_pause(0)
elif branch_depth == 0: # the point of mutation ('branch_top') chosen resides at the maximum allowable depth, so mutate term to term
@ -1932,7 +1938,7 @@ class Base_GP(object):
rnd = np.random.randint(0, len(self.terminals) - 1) # call the previously loaded .csv which contains all terminals
tree[6][branch_top] = self.terminals[rnd] # replace terminal (variable)
if self.display == 'db': print '\n\033[36m This is tourn_winner after terminal\033[1m', branch_top, '\033[0;0m\033[36mmutation, branch deletion, and updates:\033[0;0m\n', tree; self.fx_karoo_pause()
if self.display == 'db': print '\n\033[36m This is tourn_winner after terminal\033[1m', branch_top, '\033[0;0m\033[36mmutation, branch deletion, and updates:\033[0;0m\n', tree; self.fx_karoo_pause(0)
else: # the point of mutation ('branch_top') chosen is at least one depth from the maximum allowed
@ -1955,7 +1961,7 @@ class Base_GP(object):
tree = self.fx_evolve_child_link_fix(tree) # fix all child links
tree = self.fx_evolve_node_renum(tree) # renumber all 'NODE_ID's
if self.display == 'db': print '\n\033[36m This is tourn_winner after terminal\033[1m', branch_top, '\033[0;0m\033[36mmutation, branch deletion, and updates:\033[0;0m\n', tree; self.fx_karoo_pause()
if self.display == 'db': print '\n\033[36m This is tourn_winner after terminal\033[1m', branch_top, '\033[0;0m\033[36mmutation, branch deletion, and updates:\033[0;0m\n', tree; self.fx_karoo_pause(0)
if type_mod == 'func': # mutate 'branch_top' to a function (a new 'gp.tree' will be copied, node by node, into 'tourn_winner')
@ -1965,7 +1971,7 @@ class Base_GP(object):
self.fx_init_tree_build('mutant', self.pop_tree_type, branch_depth) # build new Tree ('gp.tree') with a maximum depth which matches 'branch'
if self.display == 'db': print '\n\033[36m This is the new Tree to be inserted at node\033[1m', branch_top, '\033[0;0m\033[36min tourn_winner:\033[0;0m\n', self.tree; self.fx_karoo_pause()
if self.display == 'db': print '\n\033[36m This is the new Tree to be inserted at node\033[1m', branch_top, '\033[0;0m\033[36min tourn_winner:\033[0;0m\n', self.tree; self.fx_karoo_pause(0)
tree = self.fx_evolve_branch_insert(tree, branch) # insert new 'branch' at point of mutation 'branch_top' in tourn_winner 'tree'
# because we already know the maximum depth to which this branch can grow, there is no need to prune after insertion
@ -2002,7 +2008,7 @@ class Base_GP(object):
if self.display == 'db':
print '\n\033[36m In a copy of one parent:\033[0;0m\n', offspring
print '\n\033[36m ... we remove nodes\033[1m', branch_y, '\033[0;0m\033[36mand replace node\033[1m', branch_top, '\033[0;0m\033[36mwith a terminal from branch_x\033[0;0m'; self.fx_karoo_pause()
print '\n\033[36m ... we remove nodes\033[1m', branch_y, '\033[0;0m\033[36mand replace node\033[1m', branch_top, '\033[0;0m\033[36mwith a terminal from branch_x\033[0;0m'; self.fx_karoo_pause(0)
offspring[5][branch_top] = 'term' # replace type
offspring[6][branch_top] = parent[6][crossover] # replace label with that of a particular node in 'branch_x'
@ -2012,7 +2018,7 @@ class Base_GP(object):
offspring = self.fx_evolve_child_link_fix(offspring) # fix all child links
offspring = self.fx_evolve_node_renum(offspring) # renumber all 'NODE_ID's
if self.display == 'db': print '\n\033[36m This is the resulting offspring:\033[0;0m\n', offspring; self.fx_karoo_pause()
if self.display == 'db': print '\n\033[36m This is the resulting offspring:\033[0;0m\n', offspring; self.fx_karoo_pause(0)
else: # we are working with a branch from 'parent' >= depth 1 (min 3 nodes)
@ -2024,10 +2030,10 @@ class Base_GP(object):
if self.display == 'db':
print '\n\033[36m From one parent:\033[0;0m\n', parent
print '\n\033[36m ... we copy branch_x\033[1m', branch_x, '\033[0;0m\033[36mas a new, sub-tree:\033[0;0m\n', self.tree; self.fx_karoo_pause()
print '\n\033[36m ... we copy branch_x\033[1m', branch_x, '\033[0;0m\033[36mas a new, sub-tree:\033[0;0m\n', self.tree; self.fx_karoo_pause(0)
if self.display == 'db':
print '\n\033[36m ... and insert it into a copy of the second parent in place of the selected branch\033[1m', branch_y,':\033[0;0m\n', offspring; self.fx_karoo_pause()
print '\n\033[36m ... and insert it into a copy of the second parent in place of the selected branch\033[1m', branch_y,':\033[0;0m\n', offspring; self.fx_karoo_pause(0)
offspring = self.fx_evolve_branch_insert(offspring, branch_y) # insert new 'branch_y' at point of mutation 'branch_top' in tourn_winner 'offspring'
offspring = self.fx_evolve_tree_prune(offspring, self.tree_depth_max) # prune to the max Tree depth + adjustment - tested 2016 07/10
@ -2096,7 +2102,7 @@ class Base_GP(object):
if self.display == 'db':
print '\n\t ... inserted node 1 of', len(self.tree[3])-1
print '\n\033[36m This is the Tree after a new node is inserted:\033[0;0m\n', tree; self.fx_karoo_pause()
print '\n\033[36m This is the Tree after a new node is inserted:\033[0;0m\n', tree; self.fx_karoo_pause(0)
### 2) insert branch_body from 'gp.tree' into 'tree' ###
@ -2126,7 +2132,7 @@ class Base_GP(object):
if self.display == 'db':
print '\n\t ... inserted node', node_count, 'of', len(self.tree[3])-1
print '\n\033[36m This is the Tree after a new node is inserted:\033[0;0m\n', tree; self.fx_karoo_pause()
print '\n\033[36m This is the Tree after a new node is inserted:\033[0;0m\n', tree; self.fx_karoo_pause(0)
node_count = node_count + 1 # exit loop when 'node_count' reaches the number of columns in the array 'gp.tree'
@ -2243,7 +2249,7 @@ class Base_GP(object):
tree[10][node] = c_buffer + 1
tree[11][node] = c_buffer + 2
else: print '\n\t\033[31m ERROR! In fx_evolve_child_link: node', node, 'has arity', tree[8][node]; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_evolve_child_link: node', node, 'has arity', tree[8][node]; self.fx_karoo_pause(0)
return tree
@ -2280,7 +2286,7 @@ class Base_GP(object):
'''
if int(tree[8][node]) == 0: # if arity = 0
print '\n\t\033[31m ERROR! In fx_evolve_child_insert: node', node, 'has arity 0\033[0;0m'; self.fx_karoo_pause()
print '\n\t\033[31m ERROR! In fx_evolve_child_insert: node', node, 'has arity 0\033[0;0m'; self.fx_karoo_pause(0)
elif int(tree[8][node]) == 1: # if arity = 1
tree = np.insert(tree, c_buffer, '', axis=1) # insert node for 'node_c1'
@ -2315,7 +2321,7 @@ class Base_GP(object):
tree[4][c_buffer + 2] = int(tree[4][node]) + 1 # node_depth
tree[7][c_buffer + 2] = int(tree[3][node]) # parent ID
else: print '\n\t\033[31m ERROR! In fx_evolve_child_insert: node', node, 'arity > 3\033[0;0m'; self.fx_karoo_pause()
else: print '\n\t\033[31m ERROR! In fx_evolve_child_insert: node', node, 'arity > 3\033[0;0m'; self.fx_karoo_pause(0)
return tree