def pseknc(input_data, k, w, lamada, phyche_list, alphabet, extra_index_file=None, all_prop=False, theta_type=1):
"""This is a complete process in PseKNC.
:param k: int, the value of k-tuple.
:param phyche_list: list, the input physicochemical properties list.
:param extra_index_file: a file path includes the user-defined phyche_index.
:param all_prop: bool, choose all physicochemical properties or not.
"""
phyche_list = get_phyche_list(k, phyche_list,
extra_index_file=extra_index_file, alphabet=alphabet, all_prop=all_prop)
# Get phyche_vals.
if alphabet == index_list.DNA or alphabet == index_list.RNA:
if extra_index_file is not None:
extra_phyche_index = get_extra_index(extra_index_file)
from util import normalize_index
phyche_vals = get_phyche_value(k, phyche_list, alphabet,
normalize_index(extra_phyche_index, alphabet, is_convert_dict=True))
else:
phyche_vals = get_phyche_value(k, phyche_list, alphabet)
elif alphabet == index_list.PROTEIN:
phyche_vals = get_aaindex(phyche_list)
if extra_index_file is not None:
phyche_vals.extend(extend_aaindex(extra_index_file))
seq_list = get_data(input_data, alphabet)
return make_pseknc_vector(seq_list, phyche_vals, k, w, lamada, alphabet, theta_type)
def ipseknc(input_data, k, w, lamada, phyche_list, alphabet, extra_index_file=None, all_prop=False):
"""This is a complete process in iPseKNC, k is kmer, but the index is just for dinucleotide.
:param k: int, the value of k-tuple.
:param phyche_list: list, the input physicochemical properties list.
:param extra_index_file: a file path includes the user-defined phyche_index.
:param all_prop: bool, choose all physicochemical properties or not.
"""
phyche_list = get_phyche_list(k=2, phyche_list=phyche_list,
extra_index_file=extra_index_file, alphabet=alphabet, all_prop=all_prop)
# Get phyche_vals.
if extra_index_file is not None:
extra_phyche_index = get_extra_index(extra_index_file)
from util import normalize_index
phyche_vals = get_phyche_value(k=2, phyche_list=phyche_list, alphabet=alphabet,
extra_phyche_index=normalize_index(extra_phyche_index, alphabet,
is_convert_dict=True))
else:
phyche_vals = get_phyche_value(k=2, phyche_list=phyche_list, alphabet=alphabet)
seq_list = get_data(input_data, alphabet)
return make_pseknc_vector(seq_list, phyche_vals, k, w, lamada, alphabet, theta_type=3)
def ipseknc(input_data, k, w, lamada, phyche_list, alphabet, extra_index_file=None, all_prop=False):
"""This is a complete process in iPseKNC, k is kmer, but the index is just for dinucleotide.
:param k: int, the value of k-tuple.
:param phyche_list: list, the input physicochemical properties list.
:param extra_index_file: a file path includes the user-defined phyche_index.
:param all_prop: bool, choose all physicochemical properties or not.
"""
phyche_list = get_phyche_list(k=2, phyche_list=phyche_list,
extra_index_file=extra_index_file, alphabet=alphabet, all_prop=all_prop)
# Get phyche_vals.
if extra_index_file is not None:
extra_phyche_index = get_extra_index(extra_index_file)
from util import normalize_index
phyche_vals = get_phyche_value(k=2, phyche_list=phyche_list, alphabet=alphabet,
extra_phyche_index=normalize_index(extra_phyche_index, alphabet,
is_convert_dict=True))
else:
phyche_vals = get_phyche_value(k=2, phyche_list=phyche_list, alphabet=alphabet)
seq_list = get_data(input_data, alphabet)
return make_pseknc_vector(seq_list, phyche_vals, k, w, lamada, alphabet, theta_type=3)
def pseknc(input_data, k, w, lamada, phyche_list, alphabet, extra_index_file=None, all_prop=False, theta_type=1):
"""This is a complete process in PseKNC.
:param k: int, the value of k-tuple.
:param phyche_list: list, the input physicochemical properties list.
:param extra_index_file: a file path includes the user-defined phyche_index.
:param all_prop: bool, choose all physicochemical properties or not.
"""
phyche_list = get_phyche_list(k, phyche_list,
extra_index_file=extra_index_file, alphabet=alphabet, all_prop=all_prop)
# Get phyche_vals.
if alphabet == index_list.DNA or alphabet == index_list.RNA:
if extra_index_file is not None:
extra_phyche_index = get_extra_index(extra_index_file)
from util import normalize_index
phyche_vals = get_phyche_value(k, phyche_list, alphabet,
normalize_index(extra_phyche_index, alphabet, is_convert_dict=True))
else:
phyche_vals = get_phyche_value(k, phyche_list, alphabet)
elif alphabet == index_list.PROTEIN:
phyche_vals = get_aaindex(phyche_list)
if extra_index_file is not None:
phyche_vals.extend(extend_aaindex(extra_index_file))
seq_list = get_data(input_data, alphabet)
return make_pseknc_vector(seq_list, phyche_vals, k, w, lamada, alphabet, theta_type)
def acc(input_data,
k,
lag,
phyche_list,
alphabet,
extra_index_file=None,
all_prop=False,
theta_type=1):
"""This is a complete acc in PseKNC.
:param k: int, the value of k-tuple.
:param phyche_list: list, the input physicochemical properties list.
:param extra_index_file: a file path includes the user-defined phyche_index.
:param all_prop: bool, choose all physicochemical properties or not.
:param theta_type: the value 1, 2 and 3 for ac, cc or acc.
"""
phyche_list = get_phyche_list(k,
phyche_list,
extra_index_file=extra_index_file,
alphabet=alphabet,
all_prop=all_prop)
# print(phyche_list)
# Get phyche_vals.
if alphabet == index_list.DNA or alphabet == index_list.RNA:
if extra_index_file is not None:
extra_phyche_index = get_extra_index(extra_index_file)
from util import normalize_index
phyche_vals = get_phyche_value(
k, phyche_list, alphabet,
normalize_index(extra_phyche_index,
alphabet,
is_convert_dict=True))
else:
phyche_vals = get_phyche_value(k, phyche_list, alphabet)
elif alphabet == index_list.PROTEIN:
phyche_vals = get_aaindex(phyche_list)
# print(phyche_vals)
if extra_index_file is not None:
phyche_vals.extend(extend_aaindex(extra_index_file))
seqs = get_data(input_data, alphabet)
if alphabet == index_list.PROTEIN:
# Transform the data format to dict {acid: [phyche_vals]}.
phyche_keys = phyche_vals[0].index_dict.keys()
phyche_vals = [e.index_dict.values() for e in phyche_vals]
new_phyche_vals = zip(*[e for e in phyche_vals])
phyche_vals = {
key: list(val)
for key, val in zip(phyche_keys, new_phyche_vals)
}
if theta_type == 1:
return make_ac_vec(seqs, lag, phyche_vals, k)
elif theta_type == 2:
return make_cc_vec(seqs, lag, phyche_vals, k)
elif theta_type == 3:
return make_acc_vec(seqs, lag, phyche_vals, k)
def acc(input_data, k, lag, phyche_list, alphabet, extra_index_file=None, all_prop=False, theta_type=1):
"""This is a complete acc in PseKNC.
:param k: int, the value of k-tuple.
:param phyche_list: list, the input physicochemical properties list.
:param extra_index_file: a file path includes the user-defined phyche_index.
:param all_prop: bool, choose all physicochemical properties or not.
:param theta_type: the value 1, 2 and 3 for ac, cc or acc.
"""
phyche_list = get_phyche_list(
k, phyche_list, extra_index_file=extra_index_file, alphabet=alphabet, all_prop=all_prop
)
# print(phyche_list)
# Get phyche_vals.
if alphabet == index_list.DNA or alphabet == index_list.RNA:
if extra_index_file is not None:
extra_phyche_index = get_extra_index(extra_index_file)
from util import normalize_index
phyche_vals = get_phyche_value(
k, phyche_list, alphabet, normalize_index(extra_phyche_index, alphabet, is_convert_dict=True)
)
else:
phyche_vals = get_phyche_value(k, phyche_list, alphabet)
elif alphabet == index_list.PROTEIN:
phyche_vals = get_aaindex(phyche_list)
# print(phyche_vals)
if extra_index_file is not None:
phyche_vals.extend(extend_aaindex(extra_index_file))
seqs = get_data(input_data, alphabet)
if alphabet == index_list.PROTEIN:
# Transform the data format to dict {acid: [phyche_vals]}.
phyche_keys = phyche_vals[0].index_dict.keys()
phyche_vals = [e.index_dict.values() for e in phyche_vals]
new_phyche_vals = zip(*[e for e in phyche_vals])
phyche_vals = {key: list(val) for key, val in zip(phyche_keys, new_phyche_vals)}
if theta_type == 1:
return make_ac_vec(seqs, lag, phyche_vals, k)
elif theta_type == 2:
return make_cc_vec(seqs, lag, phyche_vals, k)
elif theta_type == 3:
return make_acc_vec(seqs, lag, phyche_vals, k)
]]
print('Begin PseDNC')
psednc = PseDNC()
vec = psednc.make_psednc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
psednc = PseDNC(lamada=2, w=0.1)
vec = psednc.make_psednc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
vec = psednc.make_psednc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'],
extra_phyche_index=normalize_index(
phyche_index, is_convert_dict=True))
print(vec)
print(len(vec[0]))
print('Begin PseKNC')
pseknc = PseKNC()
vec = pseknc.make_pseknc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
pseknc = PseKNC(k=2, lamada=1, w=0.05)
vec = pseknc.make_pseknc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
if seq.no != 1:
print("Error, the basic function get_data5")
error = True
# Normalization of physicochemical index.
from util import normalize_index
phyche_index = [[
0.026, 0.036, 0.031, 0.033, 0.016, 0.026, 0.014, 0.031, 0.025, 0.025,
0.026, 0.036, 0.017, 0.025, 0.016, 0.026
],
[
0.038, 0.038, 0.037, 0.036, 0.025, 0.042, 0.026, 0.037,
0.038, 0.036, 0.042, 0.038, 0.018, 0.038, 0.025, 0.038
]]
if normalize_index(phyche_index) \
!= [[0.06, 1.5, 0.78, 1.07, -1.38, 0.06, -1.66, 0.78, -0.08, -0.08, 0.06, 1.5, -1.23, -0.08, -1.38, 0.06],
[0.5, 0.5, 0.36, 0.22, -1.36, 1.08, -1.22, 0.36, 0.5, 0.22, 1.08, 0.5, -2.37, 0.5, -1.36, 0.5]]:
print("Error, the basic function normalize_index")
error = True
print("Basic function test end!")
# ######################################################################################
# Nucleic acid Composition
# Basic kmer
from nac import Kmer
kmer = Kmer(k=2)
if kmer.make_kmer_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC']) \
if seq.seq != 'GACTGAACTGCACTTTGGTTTCATATTATTTGCTC':
print("Error, the basic function get_data4")
error = True
if seq.no != 1:
print("Error, the basic function get_data5")
error = True
# Normalization of physicochemical index.
from util import normalize_index
phyche_index = [
[0.026, 0.036, 0.031, 0.033, 0.016, 0.026, 0.014, 0.031, 0.025, 0.025, 0.026, 0.036, 0.017, 0.025, 0.016,
0.026],
[0.038, 0.038, 0.037, 0.036, 0.025, 0.042, 0.026, 0.037, 0.038, 0.036, 0.042, 0.038, 0.018, 0.038, 0.025,
0.038]]
if normalize_index(phyche_index) \
!= [[0.06, 1.5, 0.78, 1.07, -1.38, 0.06, -1.66, 0.78, -0.08, -0.08, 0.06, 1.5, -1.23, -0.08, -1.38, 0.06],
[0.5, 0.5, 0.36, 0.22, -1.36, 1.08, -1.22, 0.36, 0.5, 0.22, 1.08, 0.5, -2.37, 0.5, -1.36, 0.5]]:
print("Error, the basic function normalize_index")
error = True
print("Basic function test end!")
# ######################################################################################
# Nucleic acid Composition
# Basic kmer
from nac import Kmer
kmer = Kmer(k=2)
if kmer.make_kmer_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC']) \
self.k = 2
check_psenac(self.lamada, self.w, self.k)
def make_psednc_vec(self, input_data, phyche):
sequence_list = get_data(input_data)
#sequence_list, phyche_value = get_sequence_list_and_phyche_value_psednc(input_data, extra_phyche_index)
phyche_value = phyche
from psenacutil import make_pseknc_vector
vector = make_pseknc_vector(sequence_list,
self.lamada,
self.w,
self.k,
phyche_value,
theta_type=1)
return vector
phy = pd.read_csv('phy.csv', header=-1, index_col=None)
phyche_index = np.array(phy)
phyche_index_dict = normalize_index(phyche_index, is_convert_dict=True)
psednc = PseDNC(lamada=23, w=0.05)
vec = psednc.make_psednc_vec(open('S_data.txt'), phyche=phyche_index_dict)
#print(len(vec[0]))
feature = np.array(vec)
data_new = np.matrix(feature)
data_PseDNC = pd.DataFrame(data=data_new)
data_PseDNC.to_csv('PseDNC_S.csv')
-0.654, 0.567, 1.019]]
print('Begin PseDNC')
psednc = PseDNC()
vec = psednc.make_psednc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
psednc = PseDNC(lamada=2, w=0.1)
vec = psednc.make_psednc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
vec = psednc.make_psednc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'],
extra_phyche_index=normalize_index(phyche_index, is_convert_dict=True))
print(vec)
print(len(vec[0]))
print('Begin PseKNC')
pseknc = PseKNC()
vec = pseknc.make_pseknc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
pseknc = PseKNC(k=2, lamada=1, w=0.05)
vec = pseknc.make_pseknc_vec(['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'])
print(vec)
print(len(vec[0]))
