def setUp(self):
# Specify output locations
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'files_POD_DELETE_ME'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.vec_path = join(self.test_dir, 'vec_%03d.pkl')
self.mode_path = join(self.test_dir, 'mode_%03d.pkl')
# Specify data dimensions
self.num_states = 30
self.num_vecs = 10
# Generate random data and write to disk using handles
self.vecs_array = (
parallel.call_and_bcast(
np.random.random, (self.num_states, self.num_vecs)) +
1j * parallel.call_and_bcast(
np.random.random, (self.num_states, self.num_vecs)))
self.vec_handles = [
VecHandlePickle(self.vec_path % i) for i in range(self.num_vecs)]
for idx, hdl in enumerate(self.vec_handles):
hdl.put(self.vecs_array[:, idx])
parallel.barrier()
def setUp(self):
# Specify output locations
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'files_BPOD_DELETE_ME'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.direct_vec_path = join(self.test_dir, 'direct_vec_%03d.pkl')
self.adjoint_vec_path = join(self.test_dir, 'adjoint_vec_%03d.pkl')
self.direct_mode_path = join(self.test_dir, 'direct_mode_%03d.pkl')
self.adjoint_mode_path = join(self.test_dir, 'adjoint_mode_%03d.pkl')
# Specify system dimensions. Test single inputs/outputs as well as
# multiple inputs/outputs. Also allow for more inputs/outputs than
# states.
self.num_states = 10
self.num_inputs_list = [
1,
parallel.call_and_bcast(np.random.randint, 2, self.num_states + 2)]
self.num_outputs_list = [
1,
parallel.call_and_bcast(np.random.randint, 2, self.num_states + 2)]
# Specify how long to run impulse responses
self.num_steps = self.num_states + 1
parallel.barrier()
def setUp(self):
# Specify output locations
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'files_POD_DELETE_ME'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.vec_path = join(self.test_dir, 'vec_%03d.pkl')
self.mode_path = join(self.test_dir, 'mode_%03d.pkl')
# Specify data dimensions
self.num_states = 30
self.num_vecs = 10
# Generate random data and write to disk using handles
self.vecs_array = (
parallel.call_and_bcast(np.random.random,
(self.num_states, self.num_vecs)) +
1j * parallel.call_and_bcast(np.random.random,
(self.num_states, self.num_vecs)))
self.vec_handles = [
VecHandlePickle(self.vec_path % i) for i in range(self.num_vecs)
]
for idx, hdl in enumerate(self.vec_handles):
hdl.put(self.vecs_array[:, idx])
parallel.barrier()
def setUp(self):
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'files_vectorspace_DELETE_ME'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.max_vecs_per_proc = 10
self.total_num_vecs_in_mem = (parallel.get_num_procs() *
self.max_vecs_per_proc)
self.vec_space = vspc.VectorSpaceHandles(inner_product=np.vdot,
verbosity=0)
self.vec_space.max_vecs_per_proc = self.max_vecs_per_proc
# Default data members; set verbosity to 0 even though default is 1
# so messages won't print during tests
self.default_data_members = {
'inner_product':
np.vdot,
'max_vecs_per_node':
10000,
'max_vecs_per_proc':
(10000 * parallel.get_num_nodes() // parallel.get_num_procs()),
'verbosity':
0,
'print_interval':
10,
'prev_print_time':
0.
}
parallel.barrier()
def setUp(self):
# Specify output locations
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'files_BPOD_DELETE_ME'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.direct_vec_path = join(self.test_dir, 'direct_vec_%03d.pkl')
self.adjoint_vec_path = join(self.test_dir, 'adjoint_vec_%03d.pkl')
self.direct_mode_path = join(self.test_dir, 'direct_mode_%03d.pkl')
self.adjoint_mode_path = join(self.test_dir, 'adjoint_mode_%03d.pkl')
# Specify system dimensions. Test single inputs/outputs as well as
# multiple inputs/outputs. Also allow for more inputs/outputs than
# states.
self.num_states = 10
self.num_inputs_list = [
1,
parallel.call_and_bcast(np.random.randint, 2, self.num_states + 2)
]
self.num_outputs_list = [
1,
parallel.call_and_bcast(np.random.randint, 2, self.num_states + 2)
]
# Specify how long to run impulse responses
self.num_steps = self.num_states + 1
parallel.barrier()
def test_puts_gets(self):
test_dir = 'DELETE_ME_test_files_pod'
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
if not os.path.isdir(test_dir):
parallel.call_from_rank_zero(os.mkdir, test_dir)
num_vecs = 10
num_states = 30
correlation_mat_true = parallel.call_and_bcast(np.random.random,
((num_vecs, num_vecs)))
eigvals_true = parallel.call_and_bcast(np.random.random, num_vecs)
eigvecs_true = parallel.call_and_bcast(np.random.random,
((num_states, num_vecs)))
my_POD = PODHandles(None, verbosity=0)
my_POD.correlation_mat = correlation_mat_true
my_POD.eigvals = eigvals_true
my_POD.eigvecs = eigvecs_true
eigvecs_path = join(test_dir, 'eigvecs.txt')
eigvals_path = join(test_dir, 'eigvals.txt')
correlation_mat_path = join(test_dir, 'correlation.txt')
my_POD.put_decomp(eigvals_path, eigvecs_path)
my_POD.put_correlation_mat(correlation_mat_path)
parallel.barrier()
POD_load = PODHandles(None, verbosity=0)
POD_load.get_decomp(eigvals_path, eigvecs_path)
correlation_mat_loaded = util.load_array_text(correlation_mat_path)
np.testing.assert_allclose(correlation_mat_loaded,
correlation_mat_true)
np.testing.assert_allclose(POD_load.eigvals, eigvals_true)
np.testing.assert_allclose(POD_load.eigvecs, eigvecs_true)
def setUp(self):
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'files_vectorspace_DELETE_ME'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.max_vecs_per_proc = 10
self.total_num_vecs_in_mem = (
parallel.get_num_procs() * self.max_vecs_per_proc)
self.vec_space = vspc.VectorSpaceHandles(
inner_product=np.vdot, verbosity=0)
self.vec_space.max_vecs_per_proc = self.max_vecs_per_proc
# Default data members; set verbosity to 0 even though default is 1
# so messages won't print during tests
self.default_data_members = {
'inner_product': np.vdot, 'max_vecs_per_node': 10000,
'max_vecs_per_proc': (
10000 * parallel.get_num_nodes() // parallel.get_num_procs()),
'verbosity': 0, 'print_interval': 10, 'prev_print_time': 0.}
parallel.barrier()
def tearDown(self):
parallel.barrier()
parallel.call_from_rank_zero(rmtree, self.test_dir, ignore_errors=True)
parallel.barrier()
def tearDown(self):
parallel.barrier()
parallel.call_from_rank_zero(rmtree, self.test_dir, ignore_errors=True)
parallel.barrier()
def setUp(self):
if not os.access('.', os.W_OK):
raise RuntimeError('Cannot write to current directory')
self.test_dir = 'DELETE_ME_test_files_bpod'
if not os.path.isdir(self.test_dir):
parallel.call_from_rank_zero(os.mkdir, self.test_dir)
self.mode_nums = [2, 3, 0]
self.num_direct_vecs = 10
self.num_adjoint_vecs = 12
self.num_inputs = 1
self.num_outputs = 1
self.num_states = 20
#A = np.mat(np.random.random((self.num_states, self.num_states)))
A = np.mat(
parallel.call_and_bcast(util.drss, self.num_states, 1, 1)[0])
B = np.mat(
parallel.call_and_bcast(np.random.random,
(self.num_states, self.num_inputs)))
C = np.mat(
parallel.call_and_bcast(np.random.random,
(self.num_outputs, self.num_states)))
self.direct_vecs = [B]
A_powers = np.identity(A.shape[0])
for t in range(self.num_direct_vecs - 1):
A_powers = A_powers.dot(A)
self.direct_vecs.append(A_powers.dot(B))
self.direct_vec_array = np.array(self.direct_vecs).squeeze().T
A_adjoint = A.H
C_adjoint = C.H
A_adjoint_powers = np.identity(A_adjoint.shape[0])
self.adjoint_vecs = [C_adjoint]
for t in range(self.num_adjoint_vecs - 1):
A_adjoint_powers = A_adjoint_powers.dot(A_adjoint)
self.adjoint_vecs.append(A_adjoint_powers.dot(C_adjoint))
self.adjoint_vec_array = np.array(self.adjoint_vecs).squeeze().T
self.direct_vec_path = join(self.test_dir, 'direct_vec_%03d.txt')
self.adjoint_vec_path = join(self.test_dir, 'adjoint_vec_%03d.txt')
self.direct_vec_handles = [
V.VecHandleArrayText(self.direct_vec_path % i)
for i in range(self.num_direct_vecs)
]
self.adjoint_vec_handles = [
V.VecHandleArrayText(self.adjoint_vec_path % i)
for i in range(self.num_adjoint_vecs)
]
if parallel.is_rank_zero():
for i, handle in enumerate(self.direct_vec_handles):
handle.put(self.direct_vecs[i])
for i, handle in enumerate(self.adjoint_vec_handles):
handle.put(self.adjoint_vecs[i])
self.Hankel_mat_true = np.dot(self.adjoint_vec_array.T,
self.direct_vec_array)
self.L_sing_vecs_true, self.sing_vals_true, self.R_sing_vecs_true = \
parallel.call_and_bcast(util.svd, self.Hankel_mat_true, atol=1e-10)
self.direct_mode_array = self.direct_vec_array * \
np.mat(self.R_sing_vecs_true) * \
np.mat(np.diag(self.sing_vals_true ** -0.5))
self.adjoint_mode_array = self.adjoint_vec_array * \
np.mat(self.L_sing_vecs_true) *\
np.mat(np.diag(self.sing_vals_true ** -0.5))
self.my_BPOD = BPODHandles(np.vdot, verbosity=0)
parallel.barrier()