def test_basic():
if has_alamo_flag:
ndata = 10
x = np.random.uniform([-2, -1], [2, 1], (ndata, 2))
z = [0] * ndata
# specify simulator as examples.sixcamel
sim = examples.sixcamel
for i in range(ndata):
z[i] = sim(x[i][0], x[i][1])
# Use alamopy's python function wrapper to avoid using ALAMO's I/O format
almsim = wrapwriter(sim)
# Call alamo through the alamopy wrapper
res = alamo(x,
z,
almname='cam6',
monomialpower=(1, 2, 3, 4, 5, 6),
multi2power=(1, 2),
simulator=almsim,
expandoutput=True,
maxiter=20) #,cvfun=True)
#conf_inv = almconfidence(res)
#print('Model: {}'.format(res['model']))
#print('Confidence Intervals : {}'.format(conf_inv['conf_inv']))
almplot(res, show=False)
def main():
# Specify number of poitns to be used in the training set
# Validation data can be provided optionally
ndata= 50
nval = 500
lb = [-15,-15]
ub = [15,15]
x = np.random.uniform(lb,ub,(ndata,2))
xval = np.random.uniform(lb,ub,(nval,2))
z = [0]*ndata
zval = [0]*nval
# specify simulator as examples.sixcamel
sim = examples.ackley
for i in range(ndata):
z[i]=sim(x[i][0],x[i][1])
for i in range(nval):
zval[i] = sim(xval[i][0],xval[i][1])
# Use alamopy's python function wrapper to avoid using ALAMO's I/O format
almsim = alamopy.wrapwriter(sim)
# Call alamo through the alamopy wrapper
res = alamopy.doalamo(x,z,xval=xval,zval=zval,almname='ackley',monomialpower=(1,2,3,4,5,6),expfcns=1,multi2power=(1,2),expandoutput=True)
# Calculate confidence intervals
conf_inv = alamopy.almconfidence(res)
print('Model: {}'.format(res['model']))
print('Confidence Intervals : {}'.format(conf_inv['conf_inv']))
def test_single_input_CV():
if not alamopy.has_alamo():
return False
# Specify number of points to be used in the training set
# Validation data can be provided optionally
ndata = 10
x = np.random.uniform([-2, -1], [2, 1], (ndata, 2))
z = np.zeros((ndata, 1))
# specify simulator as examples.sixcamel
sim = sixcamel
for i in range(ndata):
z[i, 0] = sim(x[i][0], x[i][1])
# z[i,1] = sim(x[i][0], x[i][1])
# # Use alamopy's python function wrapper to avoid using ALAMO's I/O format
almsim = alamopy.wrapwriter(sim)
# NON GENERIC
alamo_settings = {
'almname': "cam6",
'monomialpower': (1, 2, 3, 4, 5, 6),
'multi2power': (1, 2),
'simulator': almsim,
'maxiter': 20,
'cvfun': True
}
res = alamopy.doalamo(x, z, lmo=3)
def _main():
# Specify number of poitns to be used in the training set
# Validation data can be provided optionally
ndata = 10
x = np.random.uniform([-2, -1], [2, 1], (ndata, 2))
z = [0] * ndata
# specify simulator as examples.sixcamel
sim = examples.sixcamel
for i in range(ndata):
z[i] = sim(x[i][0], x[i][1])
# Use alamopy's python function wrapper to avoid using ALAMO's I/O format
almsim = alamopy.wrapwriter(sim)
# Call alamo through the alamopy wrapper
res = alamopy.doalamo(
x,
z,
almname="cam6",
monomialpower=(1, 2, 3, 4, 5, 6),
multi2power=(1, 2),
simulator=almsim,
expandoutput=True,
maxiter=20,
cvfun=True,
)
# print res
print("Model: {}".format(res["model"]))
def buildSimWrapper(data, debug):
""" Builds an executable simulator to sample for data
Args:
data: shared alamo data options
debug: Additional options may be specified and will be applied
to the .alm
"""
if not isinstance(data["stropts"]["simulator"], type("string")):
try:
data["stropts"]["simulator"] = data["stropts"][
"simulator"].__name__
except Exception:
raise almerror.AlamoInputError(
"Simulator must be provided as a string"
"and obey ALAMOs simulator conventions"
"OR must be a python function whose name"
"can be obtained via .__name__")
data["stropts"]["simulator"] = alamopy.wrapwriter(
data["stropts"]["simulator"])
debug["simwrap"] = True
