def __init__(self, *args):
unittest.TestCase.__init__(self, *args)
fname = "data/test_data/sequences/alignment.fa"
dl = DataLoader()
_, self.seq_x, self.ann_x, self.seq_y, self.ann_y = dl.loadSequence(fname)
self.seq_xs = Fasta.alnToSeq(self.seq_x)
self.seq_ys = Fasta.alnToSeq(self.seq_y)
def __init__(self, *args):
unittest.TestCase.__init__(self, *args)
fname = "data/test_data/sequences/alignment.fa"
dl = DataLoader()
_, self.seq_x, self.ann_x, self.seq_y, self.ann_y = dl.loadSequence(
fname)
self.seq_xs = Fasta.alnToSeq(self.seq_x)
self.seq_ys = Fasta.alnToSeq(self.seq_y)
def main(preparer_index):
path_to_data = "data/"
dp = config.preparers[preparer_index][0](constants.window_size)
clf_fname = 'data/clf/{}{}{}.clf'.format(
PairClassifier.get_name(),
config.preparers[preparer_index][2],
constants.window_size,
)
idp = config.preparers[preparer_index][1](0, constants.window_size)
iclf_fname = 'data/clf/{}{}{}{}.clf'.format(
PairClassifier.get_name(),
config.preparers[preparer_index][2],
constants.window_size,
'_indel',
)
dl = DataLoader()
# _, s_x, a_x, s_y, a_y = dl.loadSequence(
# path.join(path_to_data, 'sequences/train_sequences/simulated_alignment0.fa'),
# )
# x, y, _ = dp.prepare_training_data(s_x, a_x, s_y, a_y)
# ix, iy, _ = idp.prepare_training_data(s_x, a_x, s_y, a_y)
# c.fit(x, y)
# ic.fit(ix, iy)
_, s_x, a_x, s_y, a_y = dl.loadSequence(
path.join(
path_to_data,
'sequences/model_train_seq/simulated/simulated_alignment.fa'))
px, py, _ = dp.prepare_training_data(s_x, a_x, s_y, a_y)
ipx, ipy, _ = idp.prepare_training_data(s_x, a_x, s_y, a_y)
# plot(*compute_01graph_data(c, x, y))
# plot(*compute_01graph_data(ic, ix, iy))
# plot(*compute_01graph_data(c, px, py))
# plot(*compute_01graph_data(ic, ipx, ipy))
plot_clf(dp, px, py, clf_fname)
plt.savefig(path.splitext(clf_fname)[0] + "_test" + pic_suffix,
transparent=True,
bbox_inches='tight')
plot_clf(idp, ipx, ipy, iclf_fname)
plt.savefig(path.splitext(iclf_fname)[0] + "_test" + pic_suffix,
transparent=True,
bbox_inches='tight')
plt.show()
def main(preparer_index):
path_to_data = "data/"
dp = config.preparers[preparer_index][0](constants.window_size)
clf_fname = 'data/clf/{}{}{}.clf'.format(
PairClassifier.get_name(),
config.preparers[preparer_index][2],
constants.window_size,
)
idp = config.preparers[preparer_index][1](0, constants.window_size)
iclf_fname = 'data/clf/{}{}{}{}.clf'.format(
PairClassifier.get_name(),
config.preparers[preparer_index][2],
constants.window_size,
'_indel',
)
dl = DataLoader()
# _, s_x, a_x, s_y, a_y = dl.loadSequence(
# path.join(path_to_data, 'sequences/train_sequences/simulated_alignment0.fa'),
# )
# x, y, _ = dp.prepare_training_data(s_x, a_x, s_y, a_y)
# ix, iy, _ = idp.prepare_training_data(s_x, a_x, s_y, a_y)
# c.fit(x, y)
# ic.fit(ix, iy)
_, s_x, a_x, s_y, a_y = dl.loadSequence(
path.join(path_to_data, 'sequences/model_train_seq/simulated/simulated_alignment.fa')
)
px, py, _ = dp.prepare_training_data(s_x, a_x, s_y, a_y)
ipx, ipy, _ = idp.prepare_training_data(s_x, a_x, s_y, a_y)
# plot(*compute_01graph_data(c, x, y))
# plot(*compute_01graph_data(ic, ix, iy))
# plot(*compute_01graph_data(c, px, py))
# plot(*compute_01graph_data(ic, ipx, ipy))
plot_clf(dp, px, py, clf_fname)
plt.savefig(
path.splitext(clf_fname)[0] + "_test" + pic_suffix, transparent=True, bbox_inches='tight'
)
plot_clf(idp, ipx, ipy, iclf_fname)
plt.savefig(
path.splitext(iclf_fname)[0] + "_test" + pic_suffix, transparent=True, bbox_inches='tight'
)
plt.show()