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user_warm_start.py¶
View page sourceContinuing a Fit Using Ipopt Warm Start¶
Option Table¶
In the option table defined below,
max_num_iter_fixed = 5 .
This fit will terminate when
the maximum number of iterations is reached.
The corresponding warning is suppressed by setting
warn_on_stderr = false .
The second fit will start where the first left off.
To see this, set print_level_fixed = 5 (in the option table) and
run this example .
Fixed Trace Table¶
This example uses the trace_fixed_table to check the number of iterations used.
Source Code¶
# values used to simulate data
iota_true = 0.01
# ------------------------------------------------------------------------
import sys
import os
import copy
test_program = 'example/user/warm_start.py'
check_program = sys.argv[0].replace('\\', '/')
if check_program != test_program or len(sys.argv) != 1 :
usage = 'python3 ' + test_program + '\n'
usage += 'where python3 is the python 3 program on your system\n'
usage += 'and working directory is the dismod_at distribution directory\n'
sys.exit(usage)
print(test_program)
#
# import dismod_at
local_dir = os.getcwd() + '/python'
if( os.path.isdir( local_dir + '/dismod_at' ) ) :
sys.path.insert(0, local_dir)
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')
# ------------------------------------------------------------------------
# Note that the a, t values are not used for this example
def example_db (file_name) :
# note that the a, t values are not used for this case
def fun_iota(a, t) :
return ('prior_iota', None, None)
def fun_chi(a, t) :
return (chi_true, None, None)
# ----------------------------------------------------------------------
# age table:
age_list = [ 0.0, 5.0, 15.0, 35.0, 50.0, 75.0, 90.0, 100.0 ]
#
# time table:
time_list = [ 1990.0, 2000.0, 2010.0, 2200.0 ]
#
# integrand table:
integrand_table = [
{ 'name':'Sincidence' }
]
#
# node table:
node_table = [ { 'name':'world', 'parent':'' } ]
#
# weight table:
weight_table = list()
#
# covariate table:
covariate_table = list()
#
# mulcov table:
mulcov_table = list()
#
# avgint table: empty
avgint_table = list()
#
# nslist_dict:
nslist_dict = dict()
# ----------------------------------------------------------------------
# data table:
data_table = list()
# values that are the same for all data rows
row = {
'integrand': 'Sincidence',
'meas_value': iota_true,
'density': 'gaussian',
'meas_std': iota_true / 10.,
'weight': '',
'hold_out': False,
'age_lower': 50.0,
'age_upper': 50.0,
'time_lower': 2000.,
'time_upper': 2000.,
'node': 'world',
'subgroup': 'world',
}
data_table.append( copy.copy(row) )
#
# ----------------------------------------------------------------------
# prior_table
prior_table = [
{ # prior_iota
'name': 'prior_iota',
'density': 'uniform',
'lower': iota_true / 10.,
'upper': iota_true * 10.,
'mean': iota_true * 2.0,
}
]
# ----------------------------------------------------------------------
# smooth table
name = 'smooth_iota'
fun = fun_iota
smooth_table = [
{ 'name':name,
'age_id':[0],
'time_id':[0],
'fun':fun
}
]
# ----------------------------------------------------------------------
# rate table:
rate_table = [
{ 'name': 'iota',
'parent_smooth': 'smooth_iota',
}
]
# ----------------------------------------------------------------------
# option_table
option_table = [
{ 'name':'rate_case', 'value':'iota_pos_rho_zero' },
{ 'name':'parent_node_name', 'value':'world' },
{ 'name':'warn_on_stderr', 'value':'false' },
{ 'name':'quasi_fixed', 'value':'false' },
{ 'name':'max_num_iter_fixed', 'value':'5' },
{ 'name':'print_level_fixed', 'value':'0' },
{ 'name':'tolerance_fixed', 'value':'1e-8' },
{ 'name':'max_num_iter_random', 'value':'50' },
{ 'name':'print_level_random', 'value':'0' },
{ 'name':'tolerance_random', 'value':'1e-10' }
]
# ----------------------------------------------------------------------
# subgroup_table
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_dict,
rate_table,
mulcov_table,
option_table
)
# ----------------------------------------------------------------------
return
# ===========================================================================
# Create database
file_name = 'example.db'
example_db(file_name)
#
# first fit command
program = '../../devel/dismod_at'
dismod_at.system_command_prc([ program, file_name, 'init' ])
dismod_at.system_command_prc([ program, file_name, 'fit', 'fixed' ])
#
# trace_fixed table
connection = dismod_at.create_connection(
file_name, new = False, readonly = True
)
trace_fixed_table = dismod_at.get_table_dict(connection, 'trace_fixed')
connection.close()
# trace includes iteration zero
assert( len(trace_fixed_table) == 6 )
#
# warm start second fit
dismod_at.system_command_prc(
[ program, file_name, 'fit', 'fixed', 'warm_start'
])
# -----------------------------------------------------------------------
# read database
connection = dismod_at.create_connection(
file_name, new = False, readonly = True
)
var_table = dismod_at.get_table_dict(connection, 'var')
rate_table = dismod_at.get_table_dict(connection, 'rate')
fit_var_table = dismod_at.get_table_dict(connection, 'fit_var')
log_table = dismod_at.get_table_dict(connection, 'log' )
trace_fixed_table = dismod_at.get_table_dict(connection, 'trace_fixed')
connection.close()
#
# second fit should converge in 2 iterations
assert( len(trace_fixed_table) <= 3 )
#
# check that we a warning (maximum number iterations during first fit)
warning_count = 0
for row in log_table :
if row['message_type'] == 'warning' :
warning_count += 1
assert warning_count in [ 1, 2]
#
assert len(var_table) == 1
fit_value = fit_var_table[0]['fit_var_value']
var_row = var_table[0]
rate_id = var_row['rate_id']
rate_name = rate_table[rate_id]['rate_name']
assert rate_name == 'iota'
rel_err = fit_value / iota_true - 1.0
if abs( rel_err ) > 1e-6 :
print( "iota rel_err = ", rel_err)
# -----------------------------------------------------------------------------
print('warm_start.py: OK')
# -----------------------------------------------------------------------------