def __init__(self, *args, **kwargs):
check_args(*args, **kwargs)
self._fmap = {}
self._bmap = {}
self._rawmap = args[0]
self._rflag = False
self._fmap = parse(args, flag=self._rflag)
self._bmap = parse(args, flag=not self._rflag)
parse.add_argument('-no_all_index', dest='a', action='store_false',
help="Do not choose all physicochemical indices, default.")
parse.set_defaults(a=False)
parse.add_argument('-f', default='tab', choices=['tab', 'svm', 'csv'],
help="The output format (default = tab).\n"
"tab -- Simple format, delimited by TAB.\n"
"svm -- The libSVM training data format.\n"
"csv -- The format that can be loaded into a spreadsheet program.")
parse.add_argument('-l', default='+1', choices=['+1', '-1'],
help="The libSVM output file label.")
args = parse.parse_args()
args.k = read_k(args.alphabet, args.method, args.k)
# print(args)
if check_args(args, 'pse.py'):
print("Calculating...")
start_time = time.time()
main(args)
print("Done.")
print("Used time: %ss" % (time.time() - start_time))
# Test dna type1.
# print("Test di_dna, type1.")
# alphabet = index_list.DNA
# res = pseknc(input_data=['GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'], k=2, w=0.5, lamada=1,
# phyche_list=['Tilt', 'Roll', 'Rise', 'Slide', 'Shift'],
# extra_index_file="data/test_ext_dna.txt", alphabet=alphabet)
#
# for e in res:
# print(len(e), e)
'-f',
default='tab',
choices=['tab', 'svm', 'csv'],
help="The output format (default = tab).\n"
"tab -- Simple format, delimited by TAB.\n"
"svm -- The libSVM training data format.\n"
"csv -- The format that can be loaded into a spreadsheet program.")
parse.add_argument('-l',
default='+1',
choices=['+1', '-1'],
help="The libSVM output file label.")
args = parse.parse_args()
# print(args)
if check_args(args, 'acc.py'):
print("Calculating...")
start_time = time.time()
main(args)
print("Done.")
print("Used time: %ss" % (time.time() - start_time))
# # Test ACC for DNA.
# print("Test ACC for DNA.")
# print(acc(open('data/test_dna.fasta'), k=2, lag=2, theta_type=3,
# phyche_list=['Tilt'], alphabet=index_list.DNA, extra_index_file='data/test_ext_dna.txt'))
#
# from repDNA.ac import DACC
# dacc = DACC(lag=2)
# print(dacc.make_dacc_vec(open('data/test_dna.fasta'), phyche_index=['Tilt', 'Twist']))
#
def spectral_flatness(file_path: str) -> np.ndarray:
y, sr = librosa.load(librosa.util.example_audio_file())
values = librosa.feature.spectral_flatness(y=y)
return values
def spectral_rolloff(file_path: str) -> np.ndarray:
y, sr = librosa.load(librosa.util.example_audio_file())
values = librosa.feature.spectral_rolloff(y=y)
return values
if __name__ == '__main__':
mode = None
file_path = None
analysis_modes = {
'centroid': Analysis.spectral_centroid,
'flatness': Analysis.spectral_flatness,
'rolloff': Analysis.spectral_rolloff
}
try:
(mode, file_path) = util.check_args(num_expected=2)
except ValueError:
util.show_usage('analysis', analysis_modes)
try:
values = analysis_modes[mode](file_path)
show_info(values)
except KeyError:
util.show_usage('analysis', analysis_modes)
parse.set_defaults(a=False)
parse.add_argument(
"-f",
default="tab",
choices=["tab", "svm", "csv"],
help="The output format (default = tab).\n"
"tab -- Simple format, delimited by TAB.\n"
"svm -- The libSVM training data format.\n"
"csv -- The format that can be loaded into a spreadsheet program.",
)
parse.add_argument("-l", default="+1", choices=["+1", "-1"], help="The libSVM output file label.")
args = parse.parse_args()
# print(args)
if check_args(args, "acc.py"):
print("Calculating...")
start_time = time.time()
main(args)
print("Done.")
print("Used time: %ss" % (time.time() - start_time))
# # Test ACC for DNA.
# print("Test ACC for DNA.")
# print(acc(open('data/test_dna.fasta'), k=2, lag=2, theta_type=3,
# phyche_list=['Tilt'], alphabet=index_list.DNA, extra_index_file='data/test_ext_dna.txt'))
#
# from repDNA.ac import DACC
# dacc = DACC(lag=2)
# print(dacc.make_dacc_vec(open('data/test_dna.fasta'), phyche_index=['Tilt', 'Twist']))
#
action='store_false',
help="Do not choose all physicochemical indices, default.")
parse.set_defaults(a=False)
parse.add_argument(
'-f',
default='tab',
choices=['tab', 'svm', 'csv'],
help="The output format (default = tab).\n"
"tab -- Simple format, delimited by TAB.\n"
"svm -- The libSVM training data format.\n"
"csv -- The format that can be loaded into a spreadsheet program.")
parse.add_argument(
'-labels',
nargs='*',
help="The labels of the input files.\n"
"For binary classification problem, the labels can only be '+1' or '-1'.\n"
"For multiclass classification problem, the labels can be set as a list of integers."
)
args = parse.parse_args()
args.k = read_k(args.alphabet, args.method, args.k)
# print(args)
if check_args(args, 'pse.py'):
print("Calculating...")
start_time = time.time()
main(args)
print("Done.")
print("Used time: %.2fs" % (time.time() - start_time))
