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group.hmm = hmm_data.get_default_hmm_atac_histone()
else:
group.hmm = hmm_data.get_default_hmm_dnase_histone()
# Creating scikit HMM list
for group in group_list:
if (group.flag_multiple_hmms):
hmm_list = []
for hmm_file_name in group.hmm:
try:
hmm_scaffold = HMM()
hmm_scaffold.load_hmm(hmm_file_name)
if (int(hmm_ver.split(".")[0]) <= 0 and int(hmm_ver.split(".")[1]) <= 1):
scikit_hmm = GaussianHMM(n_components=hmm_scaffold.states, covariance_type="full",
transmat=array(hmm_scaffold.A), startprob=array(hmm_scaffold.pi))
scikit_hmm.means_ = array(hmm_scaffold.means)
scikit_hmm.covars_ = array(hmm_scaffold.covs)
else:
scikit_hmm = GaussianHMM(n_components=hmm_scaffold.states, covariance_type="full")
scikit_hmm.startprob_ = array(hmm_scaffold.pi)
scikit_hmm.transmat_ = array(hmm_scaffold.A)
scikit_hmm.means_ = array(hmm_scaffold.means)
scikit_hmm.covars_ = array(hmm_scaffold.covs)
except Exception:
error_handler.throw_error("FP_HMM_FILES")
hmm_list.append(scikit_hmm)
group.hmm = hmm_list
scikit_hmm.means_ = array(hmm_scaffold.means)
scikit_hmm.covars_ = array(hmm_scaffold.covs)
except Exception:
error_handler.throw_error("FP_HMM_FILES")
hmm_list.append(scikit_hmm)
group.hmm = hmm_list
else:
scikit_hmm = None
try:
hmm_scaffold = HMM()
hmm_scaffold.load_hmm(group.hmm)
if (int(hmm_ver.split(".")[0]) <= 0 and int(hmm_ver.split(".")[1]) <= 1):
scikit_hmm = GaussianHMM(n_components=hmm_scaffold.states, covariance_type="full",
transmat=array(hmm_scaffold.A), startprob=array(hmm_scaffold.pi))
scikit_hmm.means_ = array(hmm_scaffold.means)
scikit_hmm.covars_ = array(hmm_scaffold.covs)
else:
scikit_hmm = GaussianHMM(n_components=hmm_scaffold.states, covariance_type="full")
scikit_hmm.startprob_ = array(hmm_scaffold.pi)
scikit_hmm.transmat_ = array(hmm_scaffold.A)
scikit_hmm.means_ = array(hmm_scaffold.means)
scikit_hmm.covars_ = array(hmm_scaffold.covs)
except Exception:
error_handler.throw_error("FP_HMM_FILES")
group.hmm = scikit_hmm