def test_simple_dense(self):
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "mat2", "-o", self.dir_, "--input_format", "dm",
"--output_format", "dm"
])
s1 = Space.build(data=self.dir_ + "mat2.dm", format="dm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat2.dm", format="dm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat2.pkl", Space)
self._test_equal_spaces_dense(s1, s2)
self._test_equal_spaces_dense(s1, s3)
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "CORE_SS.mat2", "-o", self.dir_, "--input_format",
"pkl", "--output_format", "dm"
])
s1 = io_utils.load(self.dir_ + "CORE_SS.CORE_SS.mat2.pkl", Space)
s3 = io_utils.load(self.dir_ + "CORE_SS.mat2.pkl", Space)
self._test_equal_spaces_dense(s1, s3)
def test_simple_dense(self):
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat2",
"-o", self.dir_,
"--input_format", "dm",
"--output_format", "dm"
])
s1 = Space.build(data = self.dir_ + "mat2.dm", format = "dm")
s2 = Space.build(data = self.dir_ + "CORE_SS.mat2.dm", format="dm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat2.pkl", Space)
self._test_equal_spaces_dense(s1, s2)
self._test_equal_spaces_dense(s1, s3)
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "CORE_SS.mat2",
"-o", self.dir_,
"--input_format", "pkl",
"--output_format", "dm"
])
s1 = io_utils.load(self.dir_ + "CORE_SS.CORE_SS.mat2.pkl", Space)
s3 = io_utils.load(self.dir_ + "CORE_SS.mat2.pkl", Space)
self._test_equal_spaces_dense(s1, s3)
def setUp(self):
self.dir_ = data_dir + "pipelines_test_resources/"
#use as a conversion tool, creates the files we want
bcs.main([
"build_core_space.py",
"-l",
self.dir_ + "log1.txt",
"-i",
self.dir_ + "N_mat",
"-o",
self.dir_,
"--input_format",
"dm",
])
bcs.main([
"build_core_space.py",
"-l",
self.dir_ + "log1.txt",
"-i",
self.dir_ + "AN_mat",
"-o",
self.dir_,
"--input_format",
"dm",
])
def test_simple_sparse_zipped(self):
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat1",
"-o", self.dir_,
"--input_format", "sm",
"--output_format", "sm",
"--gz", "True"
])
s1 = Space.build(data=self.dir_ + "mat1.sm.gz",
cols= self.dir_ + "mat1.cols",
format = "sm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat1.sm",
cols=self.dir_ + "CORE_SS.mat1.cols",
format="sm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat1.pkl", Space)
s4 = Space.build(data=self.dir_ + "mat1.sm",
cols= self.dir_ + "mat1.cols",
format = "sm")
self._test_equal_spaces_sparse(s1, s2)
self._test_equal_spaces_sparse(s1, s3)
self._test_equal_spaces_sparse(s1, s4)
def test_simple_nmf(self):
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log_nmf.txt", "-i",
self.dir_ + "mat3", "-w", "raw", "-r", "nmf_2", "-o", self.dir_,
"--input_format", "dm", "--output_format", "dm"
])
s1 = Space.build(data=self.dir_ + "CORE_SS.mat3.raw.nmf_2.dm",
format="dm")
self.assertEqual(s1.cooccurrence_matrix.mat.shape, (3, 2))
def test_simple_ops(self):
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat3",
"-w", "raw",
"-s", "top_sum_3,top_length_3,top_sum_4",
"-r", "svd_2,svd_1",
"-o", self.dir_,
"--input_format", "dm",
"--output_format", "dm"
])
core_mats = ["CORE_SS.mat3.raw.top_sum_3.svd_2",
"CORE_SS.mat3.raw.top_sum_3.svd_1",
"CORE_SS.mat3.raw.top_length_3.svd_2",
"CORE_SS.mat3.raw.top_length_3.svd_1",
"CORE_SS.mat3.raw.top_sum_4.svd_2",
"CORE_SS.mat3.raw.top_sum_4.svd_1"
]
core_spaces = [Space.build(data=self.dir_ + suffix + ".dm", format="dm") for suffix in core_mats]
for i, core_mat in enumerate(core_mats):
bps.main(["build_peripheral_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat3",
"-o", self.dir_,
"-c", self.dir_ + core_mat + ".pkl",
"--input_format", "dm",
"--output_format", "dm"
])
s1 = core_spaces[i]
data_file = self.dir_ + "PER_SS.mat3." + core_mats[i] + ".dm"
s2 = Space.build(data=data_file, format="dm")
self._test_equal_spaces_dense(s1, s2)
bps.main(["build_peripheral_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat3",
"-o", self.dir_,
"-c", self.dir_ + core_mat + ".pkl",
"--input_format", "sm",
"--output_format", "dm"
])
s1 = core_spaces[i]
data_file = self.dir_ + "PER_SS.mat3." + core_mats[i] + ".dm"
s2 = Space.build(data=data_file, format="dm")
self._test_equal_spaces_dense(s1, s2)
def space(tmpdir, data_dir, pipelines_test_resources):
"""Create the spaces required in the tests."""
path = tmpdir.mkdir('space')
bcs.main([
"build_core_space.py", "-l",
str(path.join('space_creation.log')), "-i",
str(pipelines_test_resources.join('mat3')), "-w", "raw", "-s",
"top_sum_3", "-r", "svd_2", "-o",
str(path), "--input_format", "dm"
])
return path
def test_simple_nmf(self):
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log_nmf.txt",
"-i", self.dir_ + "mat3",
"-w", "raw",
"-r", "nmf_2",
"-o", self.dir_,
"--input_format", "dm",
"--output_format", "dm"
])
s1 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.nmf_2.dm", format="dm")
self.assertEqual(s1.cooccurrence_matrix.mat.shape, (3,2))
def setUp(self):
self.dir_ = data_dir
self.log_dir = toolkit_dir + "/log/"
#create the spaces required in the tests
bcs.main(["build_core_space.py",
"-l", self.dir_ + "pipelines_test_resources/log1.txt",
"-i", self.dir_ + "pipelines_test_resources/mat3",
"-w", "raw",
"-s", "top_sum_3",
"-r", "svd_2",
"-o", self.dir_ + "pipelines_test_resources/",
"--input_format", "dm"
])
def setUp(self):
self.dir_ = data_dir
self.log_dir = toolkit_dir + "/log/"
#create the spaces required in the tests
bcs.main(["build_core_space.py",
"-l", self.dir_ + "pipelines_test_resources/log1.txt",
"-i", self.dir_ + "pipelines_test_resources/mat3",
"-w", "raw",
"-s", "top_sum_3",
"-r", "svd_2",
"-o", self.dir_ + "pipelines_test_resources/",
"--input_format", "dm"
])
def space(tmpdir, data_dir, pipelines_test_resources):
"""Create the spaces required in the tests."""
path = tmpdir.mkdir('space')
bcs.main([
"build_core_space.py",
"-l", str(path.join('space_creation.log')),
"-i", str(pipelines_test_resources.join('mat3')),
"-w", "raw",
"-s", "top_sum_3",
"-r", "svd_2",
"-o", str(path),
"--input_format", "dm"
])
return path
def setUp(self):
self.dir_ = data_dir + "pipelines_test_resources/"
#use as a conversion tool, creates the files we want
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "N_mat",
"-o", self.dir_,
"--input_format", "dm",
])
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "AN_mat",
"-o", self.dir_,
"--input_format", "dm",
])
def setUp(self):
self.dir_ = data_dir
self.log_dir = toolkit_dir + "/log/"
self.cos = np.array([1.0, 0.585984772383, 1.0, 0.585984772383])
self.dot_prod = np.array([28.0, 1483.0, 14.0, 2966.0])
self.euclidean = np.array(
[0.21089672206, 0.00148105508243, 1.0, 0.00148583482109])
self.lin = np.array([1.0, 0.995623769303, 1.0, 0.991242564101])
#create the spaces required in the tests
bcs.main([
"build_core_space.py", "-l",
self.dir_ + "pipelines_test_resources/log1.txt", "-i",
self.dir_ + "pipelines_test_resources/mat3", "-w", "raw", "-s",
"top_sum_3", "-r", "svd_2", "-o",
self.dir_ + "pipelines_test_resources/", "--input_format", "dm"
])
def setUp(self):
self.dir_ = data_dir
self.log_dir = toolkit_dir + "/log/"
self.cos = np.array([1.0, 0.585984772383, 1.0, 0.585984772383])
self.dot_prod = np.array([28.0, 1483.0, 14.0, 2966.0])
self.euclidean = np.array([0.21089672206, 0.00148105508243, 1.0, 0.00148583482109])
self.lin = np.array([1.0, 0.995623769303, 1.0, 0.991242564101])
#create the spaces required in the tests
bcs.main(["build_core_space.py",
"-l", self.dir_ + "pipelines_test_resources/log1.txt",
"-i", self.dir_ + "pipelines_test_resources/mat3",
"-w", "raw",
"-s", "top_sum_3",
"-r", "svd_2",
"-o", self.dir_ + "pipelines_test_resources/",
"--input_format", "dm"
])
def test_simple_sparse(self):
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "mat1", "-o", self.dir_, "--input_format", "sm",
"--output_format", "sm"
])
s1 = Space.build(data=self.dir_ + "mat1.sm",
cols=self.dir_ + "mat1.cols",
format="sm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat1.sm",
cols=self.dir_ + "CORE_SS.mat1.cols",
format="sm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat1.pkl", Space)
self._test_equal_spaces_sparse(s1, s2)
self._test_equal_spaces_sparse(s1, s3)
def setUp(self):
self.dir_ = data_dir + "pipelines_test_resources/"
#use as a conversion tool, creates the files we want
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "N_mat", "-o", self.dir_, "--input_format", "dm"
])
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "AN_mat", "-o", self.dir_, "--input_format", "dm"
])
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "A_mat", "-o", self.dir_, "--input_format", "dm"
])
tc.main([
"train_composition.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "an_train_data.txt", "-o", self.dir_, "-m",
"lexical_func", "-p", self.dir_ + "CORE_SS.AN_mat.pkl", "-a",
self.dir_ + "CORE_SS.N_mat.pkl", "-r", "lstsq", "--intercept",
"False", "--export_params", "True"
])
def test_as_conversion_tool(self):
bcs.main(["build_core_space.py",
"-i", self.dir_ + "mat3",
"-o", self.dir_,
"--input_format", "sm",
"--output_format", "sm"
])
s1 = Space.build(data=self.dir_ + "mat3.sm",
cols= self.dir_ + "mat3.cols",
format = "sm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat3.sm",
rows=self.dir_ + "CORE_SS.mat3.rows",
cols=self.dir_ + "CORE_SS.mat3.cols",
format="sm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat3.pkl", Space)
self._test_equal_spaces_sparse(s1, s2)
self._test_equal_spaces_sparse(s1, s3)
bcs.main(["build_core_space.py",
"-i", self.dir_ + "mat3",
"-o", self.dir_,
"--input_format", "sm",
"--output_format", "dm"
])
s1 = Space.build(data=self.dir_ + "mat3.dm",
cols=self.dir_ + "CORE_SS.mat3.cols",
format = "dm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat3.dm",
rows=self.dir_ + "CORE_SS.mat3.rows",
cols=self.dir_ + "CORE_SS.mat3.cols",
format = "dm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat3.pkl", Space)
self._test_equal_spaces_dense(s1, s2)
s3.to_dense()
self._test_equal_spaces_dense(s1, s3)
bcs.main(["build_core_space.py",
"-i", self.dir_ + "mat3",
"-o", self.dir_,
"--input_format", "dm",
"--output_format", "dm"
])
s1 = Space.build(data=self.dir_ + "CORE_SS.mat3.dm",
cols=self.dir_ + "CORE_SS.mat3.cols",
format = "dm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat3.pkl", Space)
s3.to_dense()
self._test_equal_spaces_dense(s1, s3)
def test_as_conversion_tool(self):
bcs.main([
"build_core_space.py", "-i", self.dir_ + "mat3", "-o", self.dir_,
"--input_format", "sm", "--output_format", "sm"
])
s1 = Space.build(data=self.dir_ + "mat3.sm",
cols=self.dir_ + "mat3.cols",
format="sm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat3.sm",
rows=self.dir_ + "CORE_SS.mat3.rows",
cols=self.dir_ + "CORE_SS.mat3.cols",
format="sm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat3.pkl", Space)
self._test_equal_spaces_sparse(s1, s2)
self._test_equal_spaces_sparse(s1, s3)
bcs.main([
"build_core_space.py", "-i", self.dir_ + "mat3", "-o", self.dir_,
"--input_format", "sm", "--output_format", "dm"
])
s1 = Space.build(data=self.dir_ + "mat3.dm",
cols=self.dir_ + "CORE_SS.mat3.cols",
format="dm")
s2 = Space.build(data=self.dir_ + "CORE_SS.mat3.dm",
rows=self.dir_ + "CORE_SS.mat3.rows",
cols=self.dir_ + "CORE_SS.mat3.cols",
format="dm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat3.pkl", Space)
self._test_equal_spaces_dense(s1, s2)
s3.to_dense()
self._test_equal_spaces_dense(s1, s3)
bcs.main([
"build_core_space.py", "-i", self.dir_ + "mat3", "-o", self.dir_,
"--input_format", "dm", "--output_format", "dm"
])
s1 = Space.build(data=self.dir_ + "CORE_SS.mat3.dm",
cols=self.dir_ + "CORE_SS.mat3.cols",
format="dm")
s3 = io_utils.load(self.dir_ + "CORE_SS.mat3.pkl", Space)
s3.to_dense()
self._test_equal_spaces_dense(s1, s3)
def setUp(self):
self.dir_ = data_dir + "pipelines_test_resources/"
#use as a conversion tool, creates the files we want
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "N_mat",
"-o", self.dir_,
"--input_format", "dm"
])
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "AN_mat",
"-o", self.dir_,
"--input_format", "dm"
])
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "A_mat",
"-o", self.dir_,
"--input_format", "dm"
])
tc.main(["train_composition.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "an_train_data.txt",
"-o", self.dir_,
"-m", "lexical_func",
"-p", self.dir_ + "CORE_SS.AN_mat.pkl",
"-a", self.dir_ + "CORE_SS.N_mat.pkl",
"-r", "lstsq",
"--intercept", "False",
"--export_params", "True"
])
def test_simple_ops(self):
#x = matrix([[ -2.19426495e+00, 3.16751379e+00, -3.89945798e-01],
#x = np.mat([[1,2,3],[2,4,6],[4,675,43]])
us = np.mat([[2.19272110e+00, 3.03174768e+00],
[4.38544220e+00, 6.06349536e+00],
[6.76369708e+02, -4.91431927e-02]])
us2 = np.mat([[2.19426495e+00, 3.16751379e+00],
[4.38703714e+00, 6.14112794e+00],
[6.76380808e+02, -5.01074549e-02]])
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "mat3", "-w", "raw", "-s",
"top_sum_3,top_length_3,top_sum_4", "-r", "svd_2,svd_1", "-n",
"none,all,row", "-o", self.dir_, "--input_format", "dm",
"--output_format", "dm"
])
s1 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_3.svd_2.dm",
format="dm")
s2 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_3.svd_1.dm",
format="dm")
s3 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_length_3.svd_2.dm",
format="dm")
s4 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_length_3.svd_1.dm",
format="dm")
s5 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_4.svd_2.dm",
format="dm")
s6 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_4.svd_1.dm",
format="dm")
s7 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_4.svd_1.all.dm",
format="dm")
s8 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_4.svd_1.row.dm",
format="dm")
s9 = s6.apply(Normalization())
s10 = s6.apply(RowNormalization())
self._test_equal_spaces_dense(s1, s3)
self._test_equal_spaces_dense(s2, s4)
self._test_equal_spaces_dense(s7, s9)
self._test_equal_spaces_dense(s8, s10)
np.testing.assert_array_almost_equal(abs(s1.cooccurrence_matrix.mat),
abs(us), 2)
np.testing.assert_array_almost_equal(abs(s2.cooccurrence_matrix.mat),
abs(us[:, 0:1]), 2)
np.testing.assert_array_almost_equal(abs(s5.cooccurrence_matrix.mat),
abs(us2), 2)
np.testing.assert_array_almost_equal(abs(s6.cooccurrence_matrix.mat),
abs(us2[:, 0:1]), 2)
self._test_equal_spaces_structs(s3, s5)
self._test_equal_spaces_structs(s2, s6)
bcs.main([
"build_core_space.py", "-l", self.dir_ + "log1.txt", "-i",
self.dir_ + "mat3", "--weighting", "raw", "--selection",
"top_sum_3,top_length_3,top_sum_4", "--reduction", "svd_2,svd_1",
"-o", self.dir_, "--input_format", "sm", "--output_format", "dm"
])
s1 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_3.svd_2.dm",
format="dm")
s2 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_3.svd_1.dm",
format="dm")
s3 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_length_3.svd_2.dm",
format="dm")
s4 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_length_3.svd_1.dm",
format="dm")
s5 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_4.svd_2.dm",
format="dm")
s6 = Space.build(data=self.dir_ +
"CORE_SS.mat3.raw.top_sum_4.svd_1.dm",
format="dm")
self._test_equal_spaces_dense(s1, s3)
self._test_equal_spaces_dense(s2, s4)
np.testing.assert_array_almost_equal(abs(s1.cooccurrence_matrix.mat),
abs(us), 2)
np.testing.assert_array_almost_equal(abs(s2.cooccurrence_matrix.mat),
abs(us[:, 0:1]), 2)
np.testing.assert_array_almost_equal(abs(s5.cooccurrence_matrix.mat),
abs(us2), 2)
np.testing.assert_array_almost_equal(abs(s6.cooccurrence_matrix.mat),
abs(us2[:, 0:1]), 2)
self._test_equal_spaces_structs(s3, s5)
self._test_equal_spaces_structs(s2, s6)
def test_simple_ops(self):
#x = matrix([[ -2.19426495e+00, 3.16751379e+00, -3.89945798e-01],
#x = np.mat([[1,2,3],[2,4,6],[4,675,43]])
us = np.mat([[ 2.19272110e+00, 3.03174768e+00],
[ 4.38544220e+00, 6.06349536e+00],
[ 6.76369708e+02, -4.91431927e-02]])
us2 = np.mat([[ 2.19426495e+00, 3.16751379e+00],
[ 4.38703714e+00, 6.14112794e+00],
[ 6.76380808e+02, -5.01074549e-02]])
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat3",
"-w", "raw",
"-s", "top_sum_3,top_length_3,top_sum_4",
"-r", "svd_2,svd_1",
"-n", "none,all,row",
"-o", self.dir_,
"--input_format", "dm",
"--output_format", "dm"
])
s1 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_3.svd_2.dm", format="dm")
s2 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_3.svd_1.dm", format="dm")
s3 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_length_3.svd_2.dm", format="dm")
s4 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_length_3.svd_1.dm", format="dm")
s5 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_4.svd_2.dm", format="dm")
s6 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_4.svd_1.dm", format="dm")
s7 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_4.svd_1.all.dm", format="dm")
s8 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_4.svd_1.row.dm", format="dm")
s9 = s6.apply(Normalization())
s10 = s6.apply(RowNormalization())
self._test_equal_spaces_dense(s1, s3)
self._test_equal_spaces_dense(s2, s4)
self._test_equal_spaces_dense(s7, s9)
self._test_equal_spaces_dense(s8, s10)
np.testing.assert_array_almost_equal(abs(s1.cooccurrence_matrix.mat), abs(us), 2)
np.testing.assert_array_almost_equal(abs(s2.cooccurrence_matrix.mat), abs(us[:,0:1]), 2)
np.testing.assert_array_almost_equal(abs(s5.cooccurrence_matrix.mat), abs(us2), 2)
np.testing.assert_array_almost_equal(abs(s6.cooccurrence_matrix.mat), abs(us2[:,0:1]), 2)
self._test_equal_spaces_structs(s3, s5)
self._test_equal_spaces_structs(s2, s6)
bcs.main(["build_core_space.py",
"-l", self.dir_ + "log1.txt",
"-i", self.dir_ + "mat3",
"--weighting", "raw",
"--selection", "top_sum_3,top_length_3,top_sum_4",
"--reduction", "svd_2,svd_1",
"-o", self.dir_,
"--input_format", "sm",
"--output_format", "dm"
])
s1 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_3.svd_2.dm", format="dm")
s2 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_3.svd_1.dm", format="dm")
s3 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_length_3.svd_2.dm", format="dm")
s4 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_length_3.svd_1.dm", format="dm")
s5 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_4.svd_2.dm", format="dm")
s6 = Space.build(data = self.dir_ + "CORE_SS.mat3.raw.top_sum_4.svd_1.dm", format="dm")
self._test_equal_spaces_dense(s1, s3)
self._test_equal_spaces_dense(s2, s4)
np.testing.assert_array_almost_equal(abs(s1.cooccurrence_matrix.mat), abs(us), 2)
np.testing.assert_array_almost_equal(abs(s2.cooccurrence_matrix.mat), abs(us[:,0:1]), 2)
np.testing.assert_array_almost_equal(abs(s5.cooccurrence_matrix.mat), abs(us2), 2)
np.testing.assert_array_almost_equal(abs(s6.cooccurrence_matrix.mat), abs(us2[:,0:1]), 2)
self._test_equal_spaces_structs(s3, s5)
self._test_equal_spaces_structs(s2, s6)
