def test_one_compartment_report():
population = 'p1'
output_file = tempfile.mkstemp(suffix='h5')[1]
cr = CompartmentReport(output_file,
mode='w',
default_population=population,
tstart=0.0,
tstop=100.0,
dt=0.1)
cr.add_cell(node_id=0, element_ids=[0], element_pos=[0.0])
for i in range(1000):
cr.record_cell(0, [i / 100.0], tstep=i)
cr.close()
report_h5 = h5py.File(output_file, 'r')
report_grp = report_h5['/report/{}'.format(population)]
assert ('data' in report_grp)
data_ds = report_grp['data'][()]
assert (report_grp['data'].size == 1000)
assert (np.isreal(data_ds.dtype))
assert (data_ds[0] == 0.00)
assert (data_ds[-1] == 9.99)
assert ('mapping' in report_grp)
mapping_grp = report_grp['mapping']
assert (all(mapping_grp['element_ids'][()] == [0]))
assert (mapping_grp['element_pos'][()] == [0.0])
assert (mapping_grp['index_pointer'][()].size == 2)
assert (mapping_grp['node_ids'][()] == [0])
assert (np.allclose(mapping_grp['time'][()], [0.0, 100.0, 0.1]))
os.remove(output_file)
def test_multi_population_report():
cells = [(0, 10, 'v1'), (1, 50, 'v1'), (2, 100, 'v1'), (3, 1, 'v1'),
(4, 200, 'v1'), (0, 100, 'v2'), (1, 50, 'v2')]
rank_cells = [c for c in cells[rank::nhosts]]
output_file = os.path.join(cpath, 'output/multi_population_report.h5')
cr = CompartmentReport(output_file,
mode='w',
tstart=0.0,
tstop=100.0,
dt=0.1,
variable='Vm',
units='mV')
for node_id, n_elements, pop in rank_cells:
cr.add_cell(node_id=node_id,
population=pop,
element_ids=np.arange(n_elements),
element_pos=np.zeros(n_elements))
for i in range(1000):
for node_id, n_elements, pop in rank_cells:
cr.record_cell(node_id,
population=pop,
vals=[node_id + i / 1000.0] * n_elements,
tstep=i)
cr.close()
if rank == 0:
report_h5 = h5py.File(output_file, 'r')
report_grp = report_h5['/report/{}'.format('v1')]
assert ('data' in report_grp)
data_ds = report_grp['data'][()]
assert (report_grp['data'].shape == (1000, 361))
assert (np.isreal(data_ds.dtype))
assert ('mapping' in report_grp)
mapping_grp = report_grp['mapping']
assert (mapping_grp['element_ids'].size == 361)
assert (mapping_grp['element_pos'].size == 361)
assert (mapping_grp['index_pointer'].size == 6)
assert (np.all(np.sort(mapping_grp['node_ids'][()]) == np.arange(5)))
assert (np.allclose(mapping_grp['time'][()], [0.0, 100.0, 0.1]))
report_grp = report_h5['/report/{}'.format('v2')]
assert ('data' in report_grp)
data_ds = report_grp['data'][()]
assert (report_grp['data'].shape == (1000, 150))
assert (np.isreal(data_ds.dtype))
assert ('mapping' in report_grp)
mapping_grp = report_grp['mapping']
assert (mapping_grp['element_ids'].size == 150)
assert (mapping_grp['element_pos'].size == 150)
assert (mapping_grp['index_pointer'].size == 3)
assert (np.all(np.sort(mapping_grp['node_ids'][()]) == [0, 1]))
assert (np.allclose(mapping_grp['time'][()], [0.0, 100.0, 0.1]))
os.remove(output_file)
barrier()
def test_multi_cell_report(buffer_size=0):
cells = [(0, 10), (1, 50), (2, 100), (3, 1), (4, 200)]
total_elements = sum(n_elements for _, n_elements in cells)
rank_cells = [c for c in cells[rank::nhosts]]
output_file = os.path.join(cpath, 'output/multi_compartment_report.h5')
population = 'cortical'
cr = CompartmentReport(output_file,
mode='w',
default_population=population,
tstart=0.0,
tstop=100.0,
dt=0.1,
variable='mebrane_potential',
units='mV',
buffer_size=buffer_size)
for node_id, n_elements in rank_cells:
cr.add_cell(node_id=node_id,
element_ids=np.arange(n_elements),
element_pos=np.zeros(n_elements))
for i in range(1000):
for node_id, n_elements in rank_cells:
cr.record_cell(node_id, [node_id + i / 1000.0] * n_elements,
tstep=i)
cr.close()
if rank == 0:
report_h5 = h5py.File(output_file, 'r')
report_grp = report_h5['/report/{}'.format(population)]
assert ('data' in report_grp)
data_ds = report_grp['data'][()]
assert (report_grp['data'].shape == (1000, total_elements))
assert (np.isreal(data_ds.dtype))
assert ('mapping' in report_grp)
mapping_grp = report_grp['mapping']
assert (mapping_grp['element_ids'].size == total_elements)
assert (mapping_grp['element_pos'].size == total_elements)
assert (mapping_grp['index_pointer'].size == 6)
assert (np.all(np.sort(mapping_grp['node_ids'][()]) == np.arange(5)))
assert (np.allclose(mapping_grp['time'][()], [0.0, 100.0, 0.1]))
os.remove(output_file)
barrier()
def build_file():
rank_cells = [(0, 10, 'v1'), (1, 50, 'v1'), (2, 100, 'v1'), (3, 1, 'v1'),
(4, 200, 'v1'), (0, 100, 'v2'), (1, 50, 'v2')]
cr = CompartmentReport(output_file,
mode='w',
tstart=0.0,
tstop=100.0,
dt=0.1,
variable='Vm',
units='mV')
for node_id, n_elements, pop in rank_cells:
cr.add_cell(node_id=node_id,
population=pop,
element_ids=np.arange(n_elements),
element_pos=np.zeros(n_elements))
for i in range(1000):
for node_id, n_elements, pop in rank_cells:
cr.record_cell(node_id,
population=pop,
vals=[node_id] * n_elements,
tstep=i)
cr.close()
def test_multi_compartment_report():
population = 'cortical'
output_file = tempfile.mkstemp(suffix='h5')[1]
n_elements = 50
cr = CompartmentReport(output_file,
mode='w',
default_population=population,
tstart=0.0,
tstop=100.0,
dt=0.1)
cr.add_cell(node_id=0,
element_ids=np.arange(n_elements),
element_pos=[0.5] * n_elements)
cr.initialize()
for i in range(1000):
cr.record_cell(0, [i + j for j in range(n_elements)], tstep=i)
cr.close()
report_h5 = h5py.File(output_file, 'r')
report_grp = report_h5['/report/{}'.format(population)]
assert ('data' in report_grp)
data_ds = report_grp['data'][()]
assert (report_grp['data'].shape == (1000, n_elements))
assert (np.isreal(data_ds.dtype))
assert (data_ds[0, 0] == 0.0)
assert (data_ds[999, n_elements - 1] == 999.0 + n_elements - 1)
assert ('mapping' in report_grp)
mapping_grp = report_grp['mapping']
assert (np.allclose(mapping_grp['element_ids'][()], np.arange(n_elements)))
assert (np.allclose(mapping_grp['element_pos'][()], [0.5] * n_elements))
assert (mapping_grp['index_pointer'][()].size == 2)
assert (mapping_grp['node_ids'][()] == [0])
assert (np.allclose(mapping_grp['time'][()], [0.0, 100.0, 0.1]))
os.remove(output_file)
