def test_1(dismod, capsys, assert_correct=True):
"""
Parent rate and subgroup random effect densities must be something other than uniform for this problem to solve.
With gaussian priors, there seems to be a scaling problem in dismod (see the initial objective function),
and dismod does not converge well.
"""
prior['parent_density'] = 'gaussian'
prior['parent_std'] = 100
prior['subgroup_density'] = 'gaussian'
prior['subgroup_std'] = 100
db_kwds.update({'prior': prior})
db = example_db.example_db(file_name, **db_kwds)
run_dismod(db.path, 'set option print_level_fixed 0')
success, db = dismod_tests.run_test(file_name, config, truth)
if not success:
msg = 'ERROR: Dismod_AT succeeded, but there is unresolvable ambiguity between the rate and group rate mulcov.'
var = ((sum(
(db.fit_var.fit_var_value - db.truth_var.truth_var_value)[:4]**2))
**.5 < 1e-7)
fit = ((sum(db.fit_data_subset.weighted_residual**2))**.5 < 1e-7)
if not var:
msg += '\n The fit_var values do not match the truth.'
if not fit:
msg += '\n Data weighted residual errors are too large.'
if not (var and fit):
msg += '\n Dismod may be scaling this problem improperly.'
if not (var and fit):
with capsys.disabled():
print('\n' + msg)
def test_0(dismod, capsys, assert_correct=True):
"""
Parent rate and subgroup random effect densities must be something other than uniform for this problem to solve.
With gaussian priors, there seems to be a scaling problem in dismod (see the initial objective function),
and dismod does not converge well.
"""
prior['parent_density'] = 'gaussian'
prior['parent_std'] = 100
prior['subgroup_density'] = 'gaussian'
prior['subgroup_std'] = 100
db_kwds.update({'prior': prior})
db = example_db.example_db(file_name, **db_kwds)
run_dismod(db.path, 'init')
info = run_dismod(db.path, 'fit both')
print(info.stdout)
global stdout
stdout = info.stdout
lines = stdout.splitlines()
for i, line in enumerate(lines):
if 'iter' in line and 'objective' in line:
break
col_index = lines[i].split().index('objective')
objective = float(lines[i + 1].split()[col_index])
if not (objective > -1e-10):
with capsys.disabled():
print(
f"\nERROR: Dismod scaled this fit both problem incorrectly, objective was {objective}."
)
def __call__(self, index: int):
self.index = index
index_db = self.index_file_pattern.format(index=index)
copy2(src=str(self.main_db), dst=str(index_db))
# Set the seed to null so each process will have a unique random sequence
run_dismod(str(index_db), "set option random_seed ''")
return self._process(db=index_db)
def test_run_dismod_fit_predict(dismod, ihme):
run = run_dismod(dm_file='temp.db', command='init')
if run.exit_status:
print(run.stderr)
assert run.exit_status == 0
run = run_dismod(dm_file='temp.db', command='fit fixed')
if run.exit_status:
print(run.stderr)
assert run.exit_status == 0
run = run_dismod(dm_file='temp.db', command='predict fit_var')
if run.exit_status:
print(run.stderr)
assert run.exit_status == 0
def test_default_init_with_null_weight_id(default_fill, weight_list):
data_df = two_input_data_df.copy()
data_df['weight_id'] = weight_list
try:
default_fill.data = data_df
run = run_dismod(dm_file=str(default_fill.path), command='init')
if run.exit_status:
print(run.stdout)
print(run.stderr)
assert run.exit_status == 0
except Exception:
raise
finally:
default_fill.data = default_data_df
def test_default_init_with_null_mulstd(default_fill, mulstd_value_prior_id):
prior_smooth_df = default_fill.smooth.copy()
smooth_df = default_fill.smooth.copy()
smooth_df['mulstd_value_prior_id'] = mulstd_value_prior_id
try:
default_fill.smooth = smooth_df
run = run_dismod(dm_file=str(default_fill.path), command='init')
if run.exit_status:
print(run.stdout)
print(run.stderr)
assert run.exit_status == 0
except Exception:
raise
finally:
default_fill.smooth = prior_smooth_df
def system(args):
# run_dismod assumes that the execitable name is dmdismod
# To make this code work with the dismod_at executable, make an executable simlink: dmdismod -> dismod_at
program = args[0]
db = args[1]
cmd = ' '.join(args[2:])
info = run_dismod(db, cmd)
if info.stdout or info.stderr: print ('-'*30)
if info.stdout: print (info.stdout)
if info.stderr: print (info.stderr)
# if info.stderr:
# raise Exception(f'ERROR: {info.stderr}')
if ' step ' in info.stdout and ' f ' in info.stdout and ' grad ' in info.stdout:
raise Exception (f'GRADIENT ERROR')
if 'error' in info.stderr.lower() or info.exit_status:
raise Exception(f'ERROR: {info.stderr}')
if ' invalid number ' in info.stderr.lower():
raise Exception(f'ERROR: {info.stderr}')
def run_dmdismod(file, dm_commands: List[str]) -> None:
"""
Runs commands on a dismod file.
Parameters
----------
file
Filepath to a database
dm_commands
List of commands that dismod_at understands
"""
for c in dm_commands:
process = run_dismod(dm_file=file, command=c)
if process.exit_status:
LOG.error(f"{c} failed with exit_status {process.exit_status}:")
LOG.error(f"{process.stderr}")
raise
else:
print(process.stdout)
print(process.stderr)
def test_dmdismod_init(dm):
run = run_dismod(dm_file=str(dm.path), command='init')
if run.exit_status:
print(run.stdout)
print(run.stderr)
assert run.exit_status == 0
