def mutateIndividual(ind, indpb=0.05):
'''for each param, with prob indpb randomly sample another choice'''
options = makemodel.getoptions()
for (param, choices) in options.items():
if np.random.rand() < indpb:
ind[param] = randParam(param, choices)
return (ind, )
def randomIndividual():
ret = dict()
options = makemodel.getoptions()
for (param, choices) in options.items():
ret[param] = randParam(param, choices)
return cleanparams(ret)
def mutateIndividual(ind, indpb=0.05):
'''for each param, with prob indpb randomly sample another choice'''
options = makemodel.getoptions()
for (param,choices) in options.iteritems():
if np.random.rand() < indpb:
ind[param] = randParam(param, choices)
return (ind,)
def randomIndividual():
ret = dict()
options = makemodel.getoptions()
for (param,choices) in options.iteritems():
ret[param] = randParam(param, choices)
return cleanparams(ret)
def crossover(ind1, ind2, indpdb=0.5):
'''swap choices with probability indpb'''
options = makemodel.getoptions()
for (param, choices) in options.items():
if np.random.rand() < indpdb:
tmp = ind1[param]
ind1[param] = ind2[param]
ind2[param] = tmp
return (ind1, ind2)
def crossover(ind1, ind2, indpdb=0.5):
'''swap choices with probability indpb'''
options = makemodel.getoptions()
for (param,choices) in options.iteritems():
if np.random.rand() < indpdb:
tmp = ind1[param]
ind1[param] = ind2[param]
ind2[param] = tmp
return (ind1,ind2)
def makejson():
'''return dictionary of config options from makemodel'''
opts = makemodel.getoptions()
d=OrderedDict()
for (name,vals) in sorted(opts.items()):
paramsize=1
if type(vals) == tuple:
options=map(str,vals)
paramtype="enum"
data=OrderedDict([("name",name), ("type", paramtype), ("size", paramsize),("options",options)])
elif isinstance(vals, makemodel.Range):
parammin = vals.min
parammax = vals.max
paramtype="float"
data=OrderedDict([("name",name), ("type", paramtype), ("min", parammin), ("max", parammax), ("size", paramsize)])
else:
print "Unknown type"
sys.exit(-1)
d[name]=data
return d
def makejson():
'''return dictionary of config options from makemodel'''
opts = makemodel.getoptions()
d = OrderedDict()
for (name, vals) in sorted(opts.items()):
paramsize = 1
if type(vals) == tuple:
options = map(str, vals)
paramtype = "enum"
data = OrderedDict([("name", name), ("type", paramtype),
("size", paramsize), ("options", options)])
elif isinstance(vals, makemodel.Range):
parammin = vals.min
parammax = vals.max
paramtype = "float"
data = OrderedDict([("name", name), ("type", paramtype),
("min", parammin), ("max", parammax),
("size", paramsize)])
else:
print "Unknown type"
sys.exit(-1)
d[name] = data
return d
#!/usr/bin/env python
'''Given a results.csv file and password for db, put the contents into google sql'''
import sys, re, MySQLdb
import pandas as pd
import makemodel
import numpy as np
conn = MySQLdb.connect(host="35.196.158.205",
user="******",
passwd=sys.argv[1],
db="opt2")
cursor = conn.cursor()
opts = makemodel.getoptions()
params = makemodel.getdefaults()
params['id'] = 'REQUESTED'
#do 5 variations
for split in range(5):
params['split'] = split
params['seed'] = np.random.randint(0, 100000)
data = pd.DataFrame([params])
row = data.iloc[0]
insert = 'INSERT INTO params (%s) VALUES (%s)' % (','.join(
row.index), ','.join(['%s'] * len(row)))
cursor.execute(insert, row)
conn.commit()
conn.autocommit(True)
cursor = conn.cursor(DictCursor)
return cursor
parser = argparse.ArgumentParser(description='Generate more configurations if needed')
parser.add_argument('--host',type=str,help='Database host',required=True)
parser.add_argument('-p','--password',type=str,help='Database password',required=True)
parser.add_argument('--db',type=str,help='Database name',default='opt1')
parser.add_argument('--pending_threshold',type=int,default=12,help='Number of pending jobs that triggers an update')
parser.add_argument('-n','--num_configs',type=int,default=4,help='Number of configs to generate - will add 6X as many jobs')
parser.add_argument('-s','--spearmint',type=str,help='Location of spearmint-lite.py',required=True)
args = parser.parse_args()
opts = makemodel.getoptions()
# first see how many id=REQUESTED jobs there are
cursor = getcursor()
cursor.execute('SELECT COUNT(*) FROM params WHERE id = "REQUESTED"')
rows = cursor.fetchone()
pending = rows.values()[0]
cursor.close()
print "Pending jobs:",pending
#if more than pending_threshold, quit
if pending > args.pending_threshold:
sys.exit(0)
default='INCREMENTAL.info')
parser.add_argument(
'--mingroup',
type=int,
help='required number of evaluations of a model for it to count',
default=5)
args = parser.parse_args()
# first see how many id=REQUESTED jobs there are
cursor = getcursor()
cursor.execute('SELECT COUNT(*) FROM params WHERE id = "REQUESTED"')
rows = cursor.fetchone()
pending = list(rows.values())[0]
#get options
options = sorted(makemodel.getoptions().items())
#print "Pending jobs:",pending
sys.stdout.write('%d ' % pending)
sys.stdout.flush()
#if more than pending_threshold, quit
if pending > args.pending_threshold:
sys.exit(0)
#create gnina-spearmint directory if it doesn't exist already
if not os.path.exists('gnina-spearmint-incremental'):
os.makedirs('gnina-spearmint-incremental')
#read in prioritized list of parameters
params = args.priority.read().rstrip().split()
parser.add_argument('--model_threshold',type=int,default=12,help='Number of unique models to evaluate at a level before giving up and going to the next level')
parser.add_argument('--priority',type=file,help='priority order of parameters',required=True)
parser.add_argument('--info',type=str,help='incremental information file',default='INCREMENTAL.info')
parser.add_argument('--mingroup',type=int,help='required number of evaluations of a model for it to count',default=5)
args = parser.parse_args()
# first see how many id=REQUESTED jobs there are
cursor = getcursor()
cursor.execute('SELECT COUNT(*) FROM params WHERE id = "REQUESTED"')
rows = cursor.fetchone()
pending = rows.values()[0]
#get options
options = sorted(makemodel.getoptions().items())
#print "Pending jobs:",pending
sys.stdout.write('%d '%pending)
sys.stdout.flush()
#if more than pending_threshold, quit
if pending > args.pending_threshold:
sys.exit(0)
#create gnina-spearmint directory if it doesn't exist already
if not os.path.exists('gnina-spearmint-incremental'):
os.makedirs('gnina-spearmint-incremental')
#read in prioritized list of parameters
params = args.priority.read().rstrip().split()
