def load_reports(config_file):
cfg = ConfigDict.from_json(config_file)
reports = []
for report_name, report in cfg.reports.items():
if report['module'] not in ['membrane_report', 'multimeter_report']:
continue
report_file = report[
'file_name'] if 'file_name' in report else '{}.h5'.format(
report_name)
report_file = report_file if os.path.isabs(
report_file) else os.path.join(cfg.output_dir, report_file)
reports.append(CompartmentReport(report_file, 'r'))
return reports
def test_compartment_reader2():
report = CompartmentReport(output_file, 'r', default_population='v1')
assert (len(report.populations) == 2)
assert ('v1' in report.populations)
assert (np.all(np.sort(report.node_ids()) == np.arange(5)))
assert (report.tstart() == 0.0)
assert (report.tstop() == 100.0)
assert (report.dt() == 0.1)
assert (report.units() == 'mV')
assert (report.n_elements() == 361)
assert (report.element_pos().size == 361)
assert (report.element_ids().size == 361)
assert (report.data().shape == (1000, 361))
assert (report.data(0).shape == (1000, 10))
assert (report.data(0, time_window=(0.0, 50.0)).shape == (500, 10))
assert (np.all(np.unique(report.data(0)) == [0.0]))
assert (report.data(1).shape == (1000, 50))
assert (np.all(np.unique(report.data(1)) == [1.0]))
assert (report.data(2).shape == (1000, 100))
assert (np.all(np.unique(report.data(2)) == [2.0]))
assert (report.data(3).shape == (1000, 1))
assert (np.all(np.unique(report.data(3)) == [3.0]))
assert (report.data(4).shape == (1000, 200))
assert (np.all(np.unique(report.data(4)) == [4.0]))
# Check v2 population
assert ('v2' in report.populations)
assert (np.all(np.sort(report.node_ids(population='v2')) == np.arange(2)))
assert (report.tstart(population='v2') == 0.0)
assert (report.tstop(population='v2') == 100.0)
assert (report.dt(population='v2') == 0.1)
assert (report.units(population='v2') == 'mV')
assert (report.n_elements(population='v2') == 150)
assert (report.element_pos(population='v2').size == 150)
assert (report.element_ids(population='v2').size == 150)
assert (report.data(population='v2').shape == (1000, 150))
assert (report.data(0, population='v2').shape == (1000, 100))
assert (report.data(0, population='v2',
time_window=(0.0, 50.0)).shape == (500, 100))
assert (np.all(np.unique(report.data(0, population='v2')) == [0.0]))
assert (report.data(1, population='v2').shape == (1000, 50))
assert (np.all(np.unique(report.data(1, population='v2')) == [1.0]))
def test_block_record():
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')
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 node_id, n_elements in rank_cells:
cr.record_cell_block(node_id,
np.full((1000, n_elements),
fill_value=node_id + 1),
beg_step=0,
end_step=1000)
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 test_custom_columns():
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')
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),
synapses=[node_id * 2] * 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 ('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]))
assert ('synapses' in mapping_grp.keys())
assert (mapping_grp['synapses'][()].size == total_elements)
os.remove(output_file)
barrier()
def get_var_recorder(node_recording_df):
if self._var_recorder is None:
self._var_recorder = CompartmentReport(
self._file_name,
mode='w',
variable=self._variable_name[0],
default_population=self._population,
tstart=node_recording_df['time'].min(),
tstop=node_recording_df['time'].max(),
dt=self._interval,
n_steps=len(node_recording_df),
mpi_size=1)
if self._to_h5 and MPI_RANK == 0:
for gid in self._gids:
self._var_recorder.add_cell(
gid,
element_ids=[0],
element_pos=[0.0],
population=self._population)
self._var_recorder.initialize()
return self._var_recorder
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)