def optimal_random_effect(fixed_effect):
#
# set start_var value for the fixed effects
var_id = node_name2var_id['world']
sql_cmd = 'UPDATE start_var SET start_var_value = ' + str(fixed_effect)
sql_cmd += ' WHERE start_var_id == ' + str(var_id)
new = False
connection = dismod_at.create_connection(file_name, new)
dismod_at.sql_command(connection, sql_cmd)
connection.close()
#
# optimize the random effects
dismod_at.system_command_prc([program, file_name, 'fit', 'random'])
#
# retrieve the optimal random effects
new = False
connection = dismod_at.create_connection(file_name, new)
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
#
var_id = node_name2var_id['child_0']
uhat_0 = fit_var_table[var_id]['fit_var_value']
#
var_id = node_name2var_id['child_1']
uhat_1 = fit_var_table[var_id]['fit_var_value']
#
uhat = numpy.array([uhat_0, uhat_1])
return uhat
else:
assert False
#
row_list.append([value])
dismod_at.create_table(connection, tbl_name, col_name, col_type, row_list)
connection.close()
return
# ===========================================================================
# Run the init command to create the var table
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
# -----------------------------------------------------------------------
# create truth_var table
create_truth_var_table()
# -----------------------------------------------------------------------------
# create predict table
dismod_at.system_command_prc([program, file_name, 'predict', 'truth_var'])
# -----------------------------------------------------------------------------
# add data to data table
new = False
connection = dismod_at.create_connection(file_name, new)
predict_table = dismod_at.get_table_dict(connection, 'predict')
avgint_table = dismod_at.get_table_dict(connection, 'avgint')
density_table = dismod_at.get_table_dict(connection, 'density')
#
# get column names and types for data table
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ---------------------------------------------------------------------------
# Fit Both
# ---------------------------------------------------------------------------
#
# create the database
file_name = 'example.db'
example_db(file_name)
#
# initialize the database
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
#
# fit both the fixed and random effects
dismod_at.system_command_prc([program, file_name, 'fit', 'both'])
# ---------------------------------------------------------------------------
# Compare Fit and Truth
# ---------------------------------------------------------------------------
#
# read var table and supporting information including the fit
new = False
connection = dismod_at.create_connection(file_name, new)
subgroup_table = dismod_at.get_table_dict(connection, 'subgroup')
node_table = dismod_at.get_table_dict(connection, 'node')
age_table = dismod_at.get_table_dict(connection, 'age')
var_table = dismod_at.get_table_dict(connection, 'var')
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
# create database
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
return
# ===========================================================================
# create the database
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
dismod_at.system_command_prc(
[program, file_name, 'set', 'option', 'max_num_iter_fixed', '1'])
dismod_at.system_command_prc([program, file_name, 'fit', 'both'])
dismod_at.system_command_prc(
[program, file_name, 'set', 'scale_var', 'fit_var'])
dismod_at.system_command_prc(
[program, file_name, 'set', 'option', 'max_num_iter_fixed', '30'])
dismod_at.system_command_prc(
[program, file_name, 'set', 'option', 'warn_on_stderr', 'true'])
dismod_at.system_command_prc([program, file_name, 'fit', 'both'])
# -----------------------------------------------------------------------
# connect to database
new = False
connection = dismod_at.create_connection(file_name, new)
#
data_table,
prior_table,
smooth_table,
nslist_table,
rate_table,
mulcov_table,
option_table
)
# ----------------------------------------------------------------------
n_smooth = len( smooth_table )
# ===========================================================================
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([ program, file_name, 'init' ])
dismod_at.system_command_prc([ program, file_name, 'fit', 'both' ])
dismod_at.system_command_prc(
[ program, file_name, 'sample', 'asymptotic', 'both', '20' ]
)
# --------------------------------------------------------------------------
# BEGIN call plot_rate_fit
database = file_name
rate_set = { 'iota', 'chi' }
pdf_file = 'example.pdf'
plot_title = 'Example Rate Plot'
plot_set = dismod_at.plot_rate_fit(database, pdf_file, plot_title, rate_set)
assert plot_set == rate_set
# END call plot_rate_fit
# -----------------------------------------------------------------------
# connect to database
smooth_table, nslist_table, rate_table, mulcov_table, option_table ) # ---------------------------------------------------------------------- return # =========================================================================== # Create database file_name = 'example.db' example_db(file_name) program = '../../devel/dismod_at' # # fit fixed dismod_at.system_command_prc([ program, file_name, 'init' ]) dismod_at.system_command_prc([ program, file_name, 'set', 'truth_var', 'prior_mean' ]) dismod_at.system_command_prc([ program, file_name, 'predict', 'truth_var' ]) # # new = False connection = dismod_at.create_connection(file_name, new) data_table = dismod_at.get_table_dict(connection, 'data') avgint_table = dismod_at.get_table_dict(connection, 'avgint') predict_table = dismod_at.get_table_dict(connection, 'predict') # n_data = len(data_table) assert len(avgint_table) == n_data assert len(predict_table) == n_data
subgroup_table = [{'subgroup': 'world', 'group': 'world'}]
# ----------------------------------------------------------------------
# create database
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ===========================================================================
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
dismod_at.system_command_prc([program, file_name, 'fit', 'both'])
dismod_at.system_command_prc(
[program, file_name, 'sample', 'asymptotic', 'both',
str(number_sample)])
# -----------------------------------------------------------------------
# get tables
new = False
connection = dismod_at.create_connection(file_name, new)
var_table = dismod_at.get_table_dict(connection, 'var')
node_table = dismod_at.get_table_dict(connection, 'node')
rate_table = dismod_at.get_table_dict(connection, 'rate')
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
sample_table = dismod_at.get_table_dict(connection, 'sample')
hes_random_table = dismod_at.get_table_dict(connection, 'hes_random')
connection.close()
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Create database and run init, start, fit with just fixed effects
file_name = 'example.db'
example_db(file_name)
program = '../../devel/dismod_at'
#
# init
dismod_at.system_command_prc([program, file_name, 'init'])
#
# set
dismod_at.system_command_prc(
[program, file_name, 'set', 'truth_var', 'prior_mean'])
#
# simulate
dismod_at.system_command_prc(
[program, file_name, 'simulate',
str(number_sample)])
#
# sample simulate
dismod_at.system_command_prc(
[program, file_name, 'sample', 'simulate', 'both',
str(number_sample)])
# -----------------------------------------------------------------------
prior_table, smooth_table, nslist_table, rate_table, mulcov_table, option_table ) # --------------------------------------------------------------------------- # Step 1: Create fit_n1.db # --------------------------------------------------------------------------- file_name = 'fit_n1.db' example_db(file_name) # # init program = '../../devel/dismod_at' dismod_at.system_command_prc( [ program, file_name, 'init' ] ) # ----------------------------------------------------------------------------- # Step 2: Fit With n1 As Parent # ----------------------------------------------------------------------------- dismod_at.system_command_prc( [ program, file_name, 'fit', 'both' ] ) # # check e1 new = False connection = dismod_at.create_connection(file_name, new) rate_table = dismod_at.get_table_dict(connection, 'rate') node_table = dismod_at.get_table_dict(connection, 'node') age_table = dismod_at.get_table_dict(connection, 'age') var_table = dismod_at.get_table_dict(connection, 'var') fit_var_table = dismod_at.get_table_dict(connection, 'fit_var') covariate_table = dismod_at.get_table_dict(connection, 'covariate') n_var = len(var_table)
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Create database
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
dismod_at.system_command_prc(
[program, file_name, 'bnd_mulcov',
str(max_abs_effect), 'income'])
dismod_at.system_command_prc([program, file_name, 'fit', 'fixed'])
# -----------------------------------------------------------------------
# read database
new = False
connection = dismod_at.create_connection(file_name, new)
var_table = dismod_at.get_table_dict(connection, 'var')
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
bnd_mulcov_table = dismod_at.get_table_dict(connection, 'bnd_mulcov')
mulcov_table = dismod_at.get_table_dict(connection, 'mulcov')
covariate_table = dismod_at.get_table_dict(connection, 'covariate')
connection.close()
#
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
return
# ===========================================================================
# create the database
file_name = 'example.db'
example_db(file_name)
#
# fit data
program_cpp = '../../devel/dismod_at'
program_py = '../../../bin/dismodat.py'
dismod_at.system_command_prc([program_cpp, file_name, 'init'])
dismod_at.system_command_prc([program_cpp, file_name, 'fit', 'fixed'])
dismod_at.system_command_prc([program_py, file_name, 'db2csv'])
#
# weighted residuals
file_in = 'data.csv'
file_in = open(file_in, 'r')
reader = csv.DictReader(file_in)
time_r = list()
residual = list()
for row in reader:
assert row['integrand'] == 'mtspecific'
assert row['time_lo'] == row['time_up']
time_r.append(float(row['time_lo']))
residual.append(float(row['residual']))
residual_max = numpy.max(residual)
avgint_table, data_table, prior_table, smooth_table, nslist_table, rate_table, mulcov_table, option_table ) # =========================================================================== file_name = 'example.db' example_db(file_name) # program = '../../devel/dismod_at' ns_string = str(number_sample) dismod_at.system_command_prc([ program, file_name, 'init' ]) # # Tables that are the same for both types of sampling new = False connection = dismod_at.create_connection(file_name, new) var_table = dismod_at.get_table_dict(connection, 'var') node_table = dismod_at.get_table_dict(connection, 'node') rate_table = dismod_at.get_table_dict(connection, 'rate') connection.close() assert len(var_table) == 3 # # map from node name to variable id node_name2var_id = dict() for var_id in range(len(var_table) ) : row = var_table[var_id] assert row['var_type'] == 'rate'
#
# import get_started_db example
sys.path.append(os.getcwd() + '/example/get_started')
import get_started_db
#
# change into the build/example/get_started directory
distutils.dir_util.mkpath('build/example/get_started')
os.chdir('build/example/get_started')
# ---------------------------------------------------------------------------
# create get_started.db
get_started_db.get_started_db()
# -----------------------------------------------------------------------
# create the var table
program = '../../devel/dismod_at'
file_name = 'get_started.db'
dismod_at.system_command_prc([program, file_name, 'init'])
# -----------------------------------------------------------------------
# connect to database
new = False
connection = dismod_at.create_connection(file_name, new)
# -----------------------------------------------------------------------
# get the variable information
var_table = dismod_at.get_table_dict(connection, 'var')
# -----------------------------------------------------------------------
# create a truth_var table with variables values to use during simulation
tbl_name = 'truth_var'
col_name = ['truth_var_value']
col_type = ['real']
row_list = list()
omega_world = 2e-2
income_multiplier = -1e-3
import dismod_at
#
# change into the build/example/user directory
if not os.path.exists('build/example/user'):
os.makedirs('build/example/user')
os.chdir('build/example/user')
#
# command
command = ['echo', 'system_command_prc: Test Output']
#
# result is stdout
result = dismod_at.system_command_prc(
command,
print_command=False,
return_stdout=True,
return_stderr=False,
file_stdout=None,
file_stderr=None,
write_command=False,
)
assert result == command[1] + '\n'
#
# result is None
result = dismod_at.system_command_prc(
command,
print_command=False,
return_stdout=False,
return_stderr=False,
file_stdout=None,
file_stderr=None,
write_command=False,
data_table, prior_table, smooth_table, nslist_table, rate_table, mulcov_table, option_table ) # ---------------------------------------------------------------------- # =========================================================================== # Create database and run init, start, fit with just fixed effects file_name = 'example.db' example_db(file_name) # program = '../../devel/dismod_at' dismod_at.system_command_prc([ program, file_name, 'init' ]) dismod_at.system_command_prc([ program, file_name, 'fit', 'fixed' ]) # # set start_var table equal to fit_var table dismod_at.system_command_prc( [ program, file_name, 'set', 'start_var', 'fit_var' ] ) # # change the density from gaussian to students integrand_name = 'Sincidence' density_name = 'students' eta_str = 'null' nu_str = str(nu) dismod_at.system_command_prc([ program, file_name, 'data_density', integrand_name, density_name, eta_str, nu_str
#
# Drop group_id column from mulcov table
sql_cmd = 'ALTER TABLE mulcov RENAME COLUMN group_id TO not_used_one'
dismod_at.sql_command(connection, sql_cmd)
#
# Drop subgroup_smooth_id column from mulcov table
sql_cmd = 'ALTER TABLE mulcov RENAME COLUMN subgroup_smooth_id TO not_used_two'
dismod_at.sql_command(connection, sql_cmd)
#
# Rename group_smooth_id column to smooth_id in mulcov table
sql_cmd = 'ALTER TABLE mulcov RENAME COLUMN group_smooth_id TO smooth_id'
dismod_at.sql_command(connection, sql_cmd)
#
# close the database
connection.close()
#
# use old2new_command to restore the database
program = '../../devel/dismod_at'
file_name = 'get_started.db'
command = 'old2new'
dismod_at.system_command_prc( [ program, file_name, command ] )
#
# check that restore worked by running init command
command = 'init'
dismod_at.system_command_prc( [ program, file_name, command ] )
#
# -----------------------------------------------------------------------
print('old2new_command: OK')
sys.exit(0)
# END PYTHON
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Run the init command to create the var table
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
# -----------------------------------------------------------------------
# read database
new = False
connection = dismod_at.create_connection(file_name, new)
var_table = dismod_at.get_table_dict(connection, 'var')
rate_table = dismod_at.get_table_dict(connection, 'rate')
integrand_table = dismod_at.get_table_dict(connection, 'integrand')
covariate_table = dismod_at.get_table_dict(connection, 'covariate')
node_table = dismod_at.get_table_dict(connection, 'node')
# -----------------------------------------------------------------------
# truth table:
tbl_name = 'truth_var'
col_name = ['truth_var_value']
col_type = ['real']
row_list = list()
# ----------------------------------------------------------------------
# create database
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ===========================================================================
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
na_string = str(number_sample)
dismod_at.system_command_prc([program, file_name, 'init'])
#
# -----------------------------------------------------------------------
# create truth_table
# -----------------------------------------------------------------------
# truth table:
new = False
connection = dismod_at.create_connection(file_name, new)
var_table = dismod_at.get_table_dict(connection, 'var')
rate_table = dismod_at.get_table_dict(connection, 'rate')
node_table = dismod_at.get_table_dict(connection, 'node')
assert len(var_table) == 3
#
tbl_name = 'truth_var'
col_name = ['truth_var_value']
col_type = ['real']
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# create database
database = 'example.db'
example_db(database)
#
# init
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, database, 'init'])
#
# fit fixed
dismod_at.system_command_prc([program, database, 'fit', 'fixed'])
# -----------------------------------------------------------------------------
# read tables
#
new = False
connection = dismod_at.create_connection(database, new)
#
name_list = [
'fit_var',
'data',
]
table_list = dict()
for table_name in name_list:
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Create database
file_name = 'example.db'
example_db(file_name)
#
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
#
integrand = 'Sincidence'
#
# hold out all the data (as a test of putting it back in)
max_fit = "0"
dismod_at.system_command_prc(
[program, file_name, 'hold_out', integrand, max_fit])
#
# hold out half of the data
max_fit = len_data_table / 2
dismod_at.system_command_prc(
[program, file_name, 'hold_out', integrand,
str(max_fit)])
# -----------------------------------------------------------------------
# read database
prior_table, smooth_table, nslist_table, rate_table, mulcov_table, option_table ) # ---------------------------------------------------------------------- return # =========================================================================== # Run the init command to create the var table file_name = 'example.db' example_db(file_name) # program = '../../devel/dismod_at' dismod_at.system_command_prc([ program, file_name, 'init' ]) # ----------------------------------------------------------------------- # read database new = False connection = dismod_at.create_connection(file_name, new) var_table = dismod_at.get_table_dict(connection, 'var') rate_table = dismod_at.get_table_dict(connection, 'rate') covariate_table= dismod_at.get_table_dict(connection, 'covariate') # ----------------------------------------------------------------------- # truth table: tbl_name = 'truth_var' col_name = [ 'truth_var_value' ] col_type = [ 'real' ] row_list = list() var_id2true = list() for var_id in range( len(var_table) ) :
def exec_shell_cmd(cmd):
program = '../../devel/dismod_at'
command = [program, database] + cmd.split()
dismod_at.system_command_prc(command)
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
# ===========================================================================
# Create database and run init, start, fit with zero sum for random effects
file_name = 'example.db'
example_db(file_name)
#
from dismod_at import system_command_prc
program = '../../devel/dismod_at'
system_command_prc([program, file_name, 'init'])
system_command_prc([program, file_name, 'fit', 'fixed'])
system_command_prc([program, file_name, 'fit', 'both'])
# -----------------------------------------------------------------------
# connect to database
new = False
connection = dismod_at.create_connection(file_name, new)
# -----------------------------------------------------------------------
# check the zero random effects solution
#
# get variable and fit_var tables
var_table = dismod_at.get_table_dict(connection, 'var')
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
rate_table = dismod_at.get_table_dict(connection, 'rate')
node_table = dismod_at.get_table_dict(connection, 'node')
time_table = dismod_at.get_table_dict(connection, 'time')
get_started_db.get_started_db()
# -----------------------------------------------------------------------
# change into distribution directory to run sandbox version of dismodat.py
# return to test_dir when done.
os.chdir(dist_dir)
print(os.getcwd())
program = 'bin/dismodat.py'
file_name = test_dir + '/get_started.db'
command = 'modify'
table_name = 'data' # table we are modifiying
column_name = 'density_id' # column we are modifying
row_expression = 'data_id==0' # row we are modifiying
value_expression = '6' # value we are placeing in that row, column
system_cmd = [
program, file_name, command, table_name, column_name, row_expression,
value_expression
]
dismod_at.system_command_prc(system_cmd)
# -----------------------------------------------------------------------
# get data table
new = False
connection = dismod_at.create_connection(file_name, new)
data_table = dismod_at.get_table_dict(connection, 'data')
connection.close()
data_id = 0
column_name = 'density_id'
assert data_table[data_id][column_name] == 6
# -----------------------------------------------------------------------
print('modify_command.py: OK')
# END PYTHON
prior_table, smooth_table, nslist_table, rate_table, mulcov_table, option_table ) # ---------------------------------------------------------------------- return # =========================================================================== # Create database and run init, start, fit with just fixed effects file_name = 'example.db' example_db(file_name) # program = '../../devel/dismod_at' dismod_at.system_command_prc([ program, file_name, 'init' ]) dismod_at.system_command_prc([ program, file_name, 'fit', 'fixed' ]) # ----------------------------------------------------------------------- # connect to database new = False connection = dismod_at.create_connection(file_name, new) # ----------------------------------------------------------------------- # check the zero random effects solution # # get variable and fit_var tables var_table = dismod_at.get_table_dict(connection, 'var') fit_var_table = dismod_at.get_table_dict(connection, 'fit_var') rate_table = dismod_at.get_table_dict(connection, 'rate') node_table = dismod_at.get_table_dict(connection, 'node') # # one age and two times for each of north_america, canada, unites_states
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Create database
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
stdout = dismod_at.system_command_prc([program, file_name, 'fit', 'both'])
# -----------------------------------------------------------------------
# Check trace_init_fit_model results
check = 'Begin dismod_at: fit_model constructor\n'
check += 'Begin cppad_mixed::initialize\n'
check += 'init_ran_like_done_\n'
check += 'init_ran_jac_done_\n'
check += 'init_ran_hes_done_\n'
check += 'init_ldlt_ran_hes_done_\n'
check += 'init_hes_cross_done_\n'
check += 'init_fix_like_done_\n'
check += 'init_fix_con_done_\n'
check += 'End cppad_mixed::initialize\n'
check += 'End dismod_at: fit_model constructor\n'
check += 'Begin cppad_mixed::init_laplace_obj\n'
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Create database and run init, start, fit with just fixed effects
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
dismod_at.system_command_prc([program, file_name, 'fit', 'random'])
# -----------------------------------------------------------------------
# connect to database
new = False
connection = dismod_at.create_connection(file_name, new)
# -----------------------------------------------------------------------
# check the zero random effects solution
#
# get variable and fit_var tables
var_table = dismod_at.get_table_dict(connection, 'var')
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
rate_table = dismod_at.get_table_dict(connection, 'rate')
node_table = dismod_at.get_table_dict(connection, 'node')
#
# one age and two times for each of north_america, canada, unites_states
import dismod_at # # import get_started_db example sys.path.append(os.getcwd() + '/example/get_started') import get_started_db # # change into the build/example/get_started directory distutils.dir_util.mkpath(test_dir) os.chdir(test_dir) # --------------------------------------------------------------------------- # create get_started.db get_started_db.get_started_db() # ----------------------------------------------------------------------- program = '../../devel/dismod_at' file_name = 'get_started.db' dismod_at.system_command_prc([program, file_name, 'init']) dismod_at.system_command_prc([program, file_name, 'fit', 'both']) # # change into distribution directory to run sandbox version of dismodat.py # return to test_dir when done. os.chdir(dist_dir) print(os.getcwd()) program = 'bin/dismodat.py' file_name = test_dir + '/get_started.db' dismod_at.system_command_prc([program, file_name, 'db2csv']) os.chdir(test_dir) # --------------------------------------------------------------------------- # get_table def get_table(name):
subgroup_table = [{'subgroup': 'world', 'group': 'world'}]
# ----------------------------------------------------------------------
# create database
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ===========================================================================
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
dismod_at.system_command_prc([program, file_name, 'fit', 'both'])
dismod_at.system_command_prc([program, file_name, 'predict', 'fit_var'])
# -----------------------------------------------------------------------
# connect to database
new = False
connection = dismod_at.create_connection(file_name, new)
predict_table = dismod_at.get_table_dict(connection, 'predict')
avgint_table = dismod_at.get_table_dict(connection, 'avgint')
node_table = dismod_at.get_table_dict(connection, 'node')
#
# check that all the avgint_table values were predicted (no subsetting)
assert len(predict_table) == 3
#
# S(a) = exp( - iota * a )
iota_canada = math.exp(canada_effect) * iota_north_america
dismod_at.create_database(file_name, age_list, time_list, integrand_table,
node_table, subgroup_table, weight_table,
covariate_table, avgint_table, data_table,
prior_table, smooth_table, nslist_table,
rate_table, mulcov_table, option_table)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Run the init command to create the var table
file_name = 'example.db'
example_db(file_name)
#
program = '../../devel/dismod_at'
dismod_at.system_command_prc([program, file_name, 'init'])
# -----------------------------------------------------------------------
# read database
new = False
connection = dismod_at.create_connection(file_name, new)
var_table = dismod_at.get_table_dict(connection, 'var')
rate_table = dismod_at.get_table_dict(connection, 'rate')
covariate_table = dismod_at.get_table_dict(connection, 'covariate')
# -----------------------------------------------------------------------
# truth table:
tbl_name = 'truth_var'
col_name = ['truth_var_value']
col_type = ['real']
row_list = list()
var_id2true = list()
for var_id in range(len(var_table)):
