def test_loadmat():
"""
Tests :meth:`bet.sampling.basicSampling.loadmat`
"""
np.random.seed(1)
mdat1 = {
'samples': np.random.random((5, 1)),
'data': np.random.random((5, 1)),
'num_samples': 5
}
mdat2 = {'samples': np.random.random((6, 1)), 'num_samples': 6}
model = "this is not a model"
sio.savemat(os.path.join(local_path, 'testfile1'), mdat1)
sio.savemat(os.path.join(local_path, 'testfile2'), mdat2)
(loaded_sampler1, samples1,
data1) = bsam.loadmat(os.path.join(local_path, 'testfile1'))
nptest.assert_array_equal(samples1, mdat1['samples'])
nptest.assert_array_equal(data1, mdat1['data'])
assert loaded_sampler1.num_samples == 5
assert loaded_sampler1.lb_model == None
(loaded_sampler2, samples2,
data2) = bsam.loadmat(os.path.join(local_path, 'testfile2'), model)
nptest.assert_array_equal(samples2, mdat2['samples'])
nptest.assert_array_equal(data2, None)
assert loaded_sampler2.num_samples == 6
assert loaded_sampler2.lb_model == model
if os.path.exists(os.path.join(local_path, 'testfile1.mat')):
os.remove(os.path.join(local_path, 'testfile1.mat'))
if os.path.exists(os.path.join(local_path, 'testfile2.mat')):
os.remove(os.path.join(local_path, 'testfile2.mat'))
def test_loadmat():
"""
Tests :meth:`bet.sampling.basicSampling.loadmat`
"""
np.random.seed(1)
mdat1 = {'samples':np.random.random((5,1)),
'data':np.random.random((5,1)), 'num_samples':5}
mdat2 = {'samples':np.random.random((6,1)), 'num_samples':6}
model = "this is not a model"
sio.savemat(os.path.join(local_path, 'testfile1'), mdat1)
sio.savemat(os.path.join(local_path, 'testfile2'), mdat2)
(loaded_sampler1, samples1, data1) = bsam.loadmat(os.path.join(local_path,
'testfile1'))
nptest.assert_array_equal(samples1, mdat1['samples'])
nptest.assert_array_equal(data1, mdat1['data'])
assert loaded_sampler1.num_samples == 5
assert loaded_sampler1.lb_model == None
(loaded_sampler2, samples2, data2) = bsam.loadmat(os.path.join(local_path,
'testfile2'), model)
nptest.assert_array_equal(samples2, mdat2['samples'])
nptest.assert_array_equal(data2, None)
assert loaded_sampler2.num_samples == 6
assert loaded_sampler2.lb_model == model
if os.path.exists(os.path.join(local_path, 'testfile1.mat')):
os.remove(os.path.join(local_path, 'testfile1.mat'))
if os.path.exists(os.path.join(local_path, 'testfile2.mat')):
os.remove(os.path.join(local_path, 'testfile2.mat'))
def test_loadmat():
"""
Tests :meth:`bet.sampling.basicSampling.loadmat`
"""
np.random.seed(1)
mdat1 = {'num_samples': 5}
mdat2 = {'num_samples': 6}
model = "this is not a model"
my_input1 = sample_set(1)
my_input1.set_values(np.random.random((5, 1)))
my_output = sample_set(1)
my_output.set_values(np.random.random((5, 1)))
my_input2 = sample_set(1)
my_input2.set_values(np.random.random((6, 1)))
sio.savemat(os.path.join(local_path, 'testfile1'), mdat1)
sio.savemat(os.path.join(local_path, 'testfile2'), mdat2)
bet.sample.save_discretization(disc(my_input1, my_output),
(os.path.join(local_path, 'testfile1')),
globalize=True)
bet.sample.save_discretization(disc(my_input2, None),
os.path.join(local_path, 'testfile2'),
"NAME",
globalize=True)
(loaded_sampler1,
discretization1) = bsam.loadmat(os.path.join(local_path, 'testfile1'))
nptest.assert_array_equal(discretization1._input_sample_set.get_values(),
my_input1.get_values())
nptest.assert_array_equal(discretization1._output_sample_set.get_values(),
my_output.get_values())
assert loaded_sampler1.num_samples == 5
assert loaded_sampler1.lb_model is None
(loaded_sampler2,
discretization2) = bsam.loadmat(os.path.join(local_path, 'testfile2'),
disc_name="NAME",
model=model)
nptest.assert_array_equal(discretization2._input_sample_set.get_values(),
my_input2.get_values())
assert discretization2._output_sample_set is None
assert loaded_sampler2.num_samples == 6
assert loaded_sampler2.lb_model == model
if os.path.exists(os.path.join(local_path, 'testfile1.mat')):
os.remove(os.path.join(local_path, 'testfile1.mat'))
if os.path.exists(os.path.join(local_path, 'testfile2.mat')):
os.remove(os.path.join(local_path, 'testfile2.mat'))
def test_loadmat():
"""
Tests :meth:`bet.sampling.basicSampling.loadmat`
"""
np.random.seed(1)
mdat1 = {'num_samples':5}
mdat2 = {'num_samples':6}
model = "this is not a model"
my_input1 = sample_set(1)
my_input1.set_values(np.random.random((5,1)))
my_output = sample_set(1)
my_output.set_values(np.random.random((5,1)))
my_input2 = sample_set(1)
my_input2.set_values(np.random.random((6,1)))
sio.savemat(os.path.join(local_path, 'testfile1'), mdat1)
sio.savemat(os.path.join(local_path, 'testfile2'), mdat2)
bet.sample.save_discretization(disc(my_input1, my_output),
(os.path.join(local_path, 'testfile1')), globalize=True)
bet.sample.save_discretization(disc(my_input2, None),
os.path.join(local_path, 'testfile2'), "NAME", globalize=True)
(loaded_sampler1, discretization1) = bsam.loadmat(os.path.join(local_path,
'testfile1'))
nptest.assert_array_equal(discretization1._input_sample_set.get_values(),
my_input1.get_values())
nptest.assert_array_equal(discretization1._output_sample_set.get_values(),
my_output.get_values())
assert loaded_sampler1.num_samples == 5
assert loaded_sampler1.lb_model is None
(loaded_sampler2, discretization2) = bsam.loadmat(os.path.join(local_path,
'testfile2'), disc_name="NAME", model=model)
nptest.assert_array_equal(discretization2._input_sample_set.get_values(),
my_input2.get_values())
assert discretization2._output_sample_set is None
assert loaded_sampler2.num_samples == 6
assert loaded_sampler2.lb_model == model
if os.path.exists(os.path.join(local_path, 'testfile1.mat')):
os.remove(os.path.join(local_path, 'testfile1.mat'))
if os.path.exists(os.path.join(local_path, 'testfile2.mat')):
os.remove(os.path.join(local_path, 'testfile2.mat'))
def test_loadmat_parallel():
"""
Tests :class:`bet.sampling.basicSampling.sampler.loadmat`.
"""
np.random.seed(1)
mdat1 = {'num_samples':10}
mdat2 = {'num_samples':20}
model = "this is not a model"
my_input1 = sample_set(1)
my_input1.set_values_local(np.array_split(np.random.random((10,1)),
comm.size)[comm.rank])
my_output1 = sample_set(1)
my_output1.set_values_local(np.array_split(np.random.random((10,1)),
comm.size)[comm.rank])
my_input2 = sample_set(1)
my_input2.set_values_local(np.array_split(np.random.random((20,1)),
comm.size)[comm.rank])
my_output2 = sample_set(1)
my_output2.set_values_local(np.array_split(np.random.random((20,1)),
comm.size)[comm.rank])
file_name1 = 'testfile1.mat'
file_name2 = 'testfile2.mat'
if comm.size > 1:
local_file_name1 = os.path.os.path.join(os.path.dirname(file_name1),
"proc{}_{}".format(comm.rank, os.path.basename(file_name1)))
local_file_name2 = os.path.os.path.join(os.path.dirname(file_name2),
"proc{}_{}".format(comm.rank, os.path.basename(file_name2)))
else:
local_file_name1 = file_name1
local_file_name2 = file_name2
sio.savemat(local_file_name1, mdat1)
sio.savemat(local_file_name2, mdat2)
comm.barrier()
bet.sample.save_discretization(disc(my_input1, my_output1),
file_name1, globalize=False)
bet.sample.save_discretization(disc(my_input2, my_output2),
file_name2, "NAME", globalize=False)
(loaded_sampler1, discretization1) = bsam.loadmat(file_name1)
nptest.assert_array_equal(discretization1._input_sample_set.get_values(),
my_input1.get_values())
nptest.assert_array_equal(discretization1._output_sample_set.get_values(),
my_output1.get_values())
assert loaded_sampler1.num_samples == 10
assert loaded_sampler1.lb_model is None
(loaded_sampler2, discretization2) = bsam.loadmat(file_name2,
disc_name="NAME", model=model)
nptest.assert_array_equal(discretization2._input_sample_set.get_values(),
my_input2.get_values())
nptest.assert_array_equal(discretization2._output_sample_set.get_values(),
my_output2.get_values())
assert loaded_sampler2.num_samples == 20
assert loaded_sampler2.lb_model == model
if comm.size == 1:
os.remove(file_name1)
os.remove(file_name2)
else:
os.remove(local_file_name1)
os.remove(local_file_name2)
def test_loadmat_parallel():
"""
Tests :class:`bet.sampling.basicSampling.sampler.loadmat`.
"""
np.random.seed(1)
mdat1 = {'num_samples': 10}
mdat2 = {'num_samples': 20}
model = "this is not a model"
my_input1 = sample_set(1)
my_input1.set_values_local(
np.array_split(np.random.random((10, 1)), comm.size)[comm.rank])
my_output1 = sample_set(1)
my_output1.set_values_local(
np.array_split(np.random.random((10, 1)), comm.size)[comm.rank])
my_input2 = sample_set(1)
my_input2.set_values_local(
np.array_split(np.random.random((20, 1)), comm.size)[comm.rank])
my_output2 = sample_set(1)
my_output2.set_values_local(
np.array_split(np.random.random((20, 1)), comm.size)[comm.rank])
file_name1 = 'testfile1.mat'
file_name2 = 'testfile2.mat'
if comm.size > 1:
local_file_name1 = os.path.os.path.join(
os.path.dirname(file_name1),
"proc{}_{}".format(comm.rank, os.path.basename(file_name1)))
local_file_name2 = os.path.os.path.join(
os.path.dirname(file_name2),
"proc{}_{}".format(comm.rank, os.path.basename(file_name2)))
else:
local_file_name1 = file_name1
local_file_name2 = file_name2
sio.savemat(local_file_name1, mdat1)
sio.savemat(local_file_name2, mdat2)
comm.barrier()
bet.sample.save_discretization(disc(my_input1, my_output1),
file_name1,
globalize=False)
bet.sample.save_discretization(disc(my_input2, my_output2),
file_name2,
"NAME",
globalize=False)
(loaded_sampler1, discretization1) = bsam.loadmat(file_name1)
nptest.assert_array_equal(discretization1._input_sample_set.get_values(),
my_input1.get_values())
nptest.assert_array_equal(discretization1._output_sample_set.get_values(),
my_output1.get_values())
assert loaded_sampler1.num_samples == 10
assert loaded_sampler1.lb_model is None
(loaded_sampler2, discretization2) = bsam.loadmat(file_name2,
disc_name="NAME",
model=model)
nptest.assert_array_equal(discretization2._input_sample_set.get_values(),
my_input2.get_values())
nptest.assert_array_equal(discretization2._output_sample_set.get_values(),
my_output2.get_values())
assert loaded_sampler2.num_samples == 20
assert loaded_sampler2.lb_model == model
if comm.size == 1:
os.remove(file_name1)
os.remove(file_name2)
else:
os.remove(local_file_name1)
os.remove(local_file_name2)