def _check_daal_supported_parameters(self):
_class_name = self.__class__.__name__
if self.n_jobs != 1:
warnings.warn(_class_name +
' ignores non-default settings of n_jobs')
if self.verbose != 0:
warnings.wanr(_class_name +
' ignores non-default settings of verbose')
if self.warm_start:
warnings.warn(_class_name +
' ignores non-default settings of warm_start')
if self.criterion != "gini":
warnings.warn(_class_name +
' currently only supports criterion="gini"')
if self.min_impurity_decrease != 0.0:
warnings.warn(
_class_name +
" currently does not support min_impurity_decrease."
"It currently supports min_impurity_split to control tree growth."
)
if self.max_leaf_nodes is not None:
warnings.warn(_class_name +
" currently does not support non-default "
"setting for max_leaf_nodes.")
if self.min_weight_fraction_leaf != 0.0:
warnings.warn(_class_name +
" currently does not support non-default "
"setting for min_weight_fraction_leaf.")
if self.min_samples_leaf != 1:
warnings.warn(_class_name +
" currently does not support non-default "
"setting for min_samples_leaf.")
def memd(*args):
x, seq, t, ndir, N_dim, N, sd, sd2, tol, nbit, MAXITERATIONS, stop_crit, stp_cnt = set_value(
args)
r = x
n_imf = 1
q = []
while stop_emd(r, seq, ndir, N_dim) == False:
# current mode
m = r
# computation of mean and stopping criterion
if stop_crit == 'stop':
stop_sift, env_mean = stop(m, t, sd, sd2, tol, seq, ndir, N, N_dim)
else:
counter = 0
stop_sift, env_mean, counter = fix(m, t, seq, ndir, stp_cnt,
counter, N, N_dim)
# In case the current mode is so small that machine precision can cause
# spurious extrema to appear
if np.max(np.abs(m)) < (1e-10) * (np.max(np.abs(x))):
if stop_sift == False:
warnings.warn('emd:warning',
'forced stop of EMD : too small amplitude')
else:
print('forced stop of EMD : too small amplitude')
break
# sifting loop
while stop_sift == False and nbit < MAXITERATIONS:
# sifting
m = m - env_mean
# computation of mean and stopping criterion
if stop_crit == 'stop':
stop_sift, env_mean = stop(m, t, sd, sd2, tol, seq, ndir, N,
N_dim)
else:
stop_sift, env_mean, counter = fix(m, t, seq, ndir, stp_cnt,
counter, N, N_dim)
nbit = nbit + 1
if nbit == (MAXITERATIONS - 1) and nbit > 100:
warnings.wanr('emd:warning',
'forced stop of sifting : too many erations')
q.append(m.transpose())
n_imf = n_imf + 1
r = r - m
nbit = 0
# Stores the residue
q.append(r.transpose())
q = np.asarray(q)
# sprintf('Elapsed time: %f\n',toc);
return (q)