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
def updateMeasNoiseDensity(self, density_name: str, params: Dict[str,
Any]):
connection = dismod_at.create_connection(self.path, False)
density_table = dismod_at.get_table_dict(connection, 'density')
command = 'UPDATE data SET density_id = ' \
+ str(self.density_dict[density_name])
print(command)
dismod_at.sql_command(connection, command)
for k, v in params.items():
command = 'UPDATE data SET ' + k + ' = ' + str(v)
dismod_at.sql_command(connection, command)
print(command)
connection.close()
file_name = 'get_started.db'
connection = dismod_at.create_connection(file_name, new)
option_table = dismod_at.get_table_dict(connection, 'option')
node_table = dismod_at.get_table_dict(connection, 'node')
parent_node_id = None
for row in option_table:
if row['option_name'] == 'parent_node_name':
name = row['option_value']
for node_id in range(len(node_table)):
if node_table[node_id]['node_name'] == name:
assert parent_node_id == None
parent_node_id = str(node_id)
assert parent_node_id != None
cmd = "INSERT INTO option ('option_name', 'option_value')"
cmd += " VALUES('parent_node_id', '" + parent_node_id + "')"
dismod_at.sql_command(connection, cmd)
connection.close()
# -----------------------------------------------------------------------
program = '../../devel/dismod_at'
for command in ['init', 'fit']:
cmd = [program, file_name, command]
if command == 'fit':
variables = 'both'
cmd.append(variables)
print(' '.join(cmd))
flag = subprocess.call(cmd)
if flag != 0:
sys.exit('The dismod_at ' + command + ' command failed')
# -----------------------------------------------------------------------
# connect to database
new = False
def sql_count_rows(connection, table_name) : sqlcmd = 'SELECT COUNT(*) FROM ' + table_name result = dismod_at.sql_command(connection, sqlcmd) n_row = result[0][0] return n_row
predict_array[sample_index, avgint_id] = value predict_found[avgint_id] = True predict_mean = numpy.mean(predict_array, axis=0) predict_std = numpy.std(predict_array, axis=0, ddof = 1) # ----------------------------------------------------------------------------- # Step 6: Priors for n11 as Parent # ----------------------------------------------------------------------------- # create fit_n11.db starting from fit_n1.db shutil.copyfile(file_name, 'fit_n11.db') file_name = 'fit_n11.db' connection.close() connection = dismod_at.create_connection(file_name, new) # # get last id from certain tables sqlcmd = 'SELECT COUNT(prior_id) FROM prior' result = dismod_at.sql_command(connection, sqlcmd) prior_id = sql_count_rows(connection, 'prior') - 1 smooth_id = sql_count_rows(connection, 'smooth') - 1 smooth_grid_id = sql_count_rows(connection, 'smooth_grid') - 1 # sqlcmd = 'SELECT density_id FROM density WHERE density_name=="uniform"' result = dismod_at.sql_command(connection, sqlcmd) uniform_id = result[0][0] # sqlcmd = 'SELECT density_id FROM density WHERE density_name=="gaussian"' result = dismod_at.sql_command(connection, sqlcmd) gaussian_id = result[0][0] # # add smooth_iota_n11 smooth_name = 'smooth_iota_n11' n_age = len( age_table )
assert( covariate_name == 'one' ) # truth_var_value = gamma_true(meas_noise_effect) else : assert( var_type == 'rate' ) rate_id = var_info['rate_id'] rate_name = rate_table[rate_id]['rate_name'] node_id = var_info['node_id'] node_name = node_table[node_id]['node_name'] assert node_name == 'world' # truth_var_value = iota_true # var_id2true.append( truth_var_value ) row_list.append( [ truth_var_value ] ) dismod_at.sql_command(connection, 'DROP TABLE IF EXISTS truth_var') dismod_at.create_table(connection, tbl_name, col_name, col_type, row_list) # ------------------------------------------------------------------------- # create and check the data_sim table dismod_at.system_command_prc([ program, file_name, 'simulate', '1' ]) # # check results in data_sim table new = False connection = dismod_at.create_connection(file_name, new) density_table = dismod_at.get_table_dict(connection, 'density') data_table = dismod_at.get_table_dict(connection, 'data') data_subset_table = dismod_at.get_table_dict(connection, 'data_subset') data_sim_table = dismod_at.get_table_dict(connection, 'data_sim') # # check that all the data_id appear in the data_subset table for data_subset_id in range(len(data_subset_table)) :
