def initialize(self,
M_c,
M_r,
T,
initialization='from_the_prior',
n_chains=1):
"""Sample a latent state from prior
:param M_c: The column metadata
:type M_c: dict
:param M_r: The row metadata
:type M_r: dict
:param T: The data table in mapped representation (all floats, generated
by data_utils.read_data_objects)
:type T: list of lists
:returns: X_L, X_D -- the latent state
"""
output_path = self.output_path
input_filename = self.input_filename
table_data_filename = self.table_data_filename
intialize_args_dict_filename = self.command_dict_filename
xu.assert_vpn_is_connected()
#
table_data = dict(M_c=M_c, M_r=M_r, T=T)
initialize_args_dict = dict(command='initialize',
initialization=initialization)
xu.write_initialization_files(input_filename, table_data,
table_data_filename,
initialize_args_dict,
intialize_args_dict_filename, n_chains)
os.system('cp %s initialize_input' % input_filename)
self.send_hadoop_command(n_tasks=n_chains)
was_successful = self.get_hadoop_results()
hadoop_output = None
if was_successful:
hu.copy_hadoop_output(output_path, 'initialize_output')
X_L_list, X_D_list = hu.read_hadoop_output(output_path)
hadoop_output = X_L_list, X_D_list
return hadoop_output
def initialize(self, M_c, M_r, T, initialization='from_the_prior',
n_chains=1):
"""Sample a latent state from prior
:param M_c: The column metadata
:type M_c: dict
:param M_r: The row metadata
:type M_r: dict
:param T: The data table in mapped representation (all floats, generated
by data_utils.read_data_objects)
:type T: list of lists
:returns: X_L, X_D -- the latent state
"""
output_path = self.output_path
input_filename = self.input_filename
table_data_filename = self.table_data_filename
intialize_args_dict_filename = self.command_dict_filename
xu.assert_vpn_is_connected()
#
table_data = dict(M_c=M_c, M_r=M_r, T=T)
initialize_args_dict = dict(command='initialize',
initialization=initialization)
xu.write_initialization_files(input_filename,
table_data, table_data_filename,
initialize_args_dict,
intialize_args_dict_filename,
n_chains)
os.system('cp %s initialize_input' % input_filename)
self.send_hadoop_command(n_tasks=n_chains)
was_successful = self.get_hadoop_results()
hadoop_output = None
if was_successful:
hu.copy_hadoop_output(output_path, 'initialize_output')
X_L_list, X_D_list = hu.read_hadoop_output(output_path)
hadoop_output = X_L_list, X_D_list
return hadoop_output
script_name = 'hadoop_line_processor.py'
#
table_data_filename = hs.default_table_data_filename
initialize_input_filename = 'initialize_input'
initialize_output_filename = 'initialize_output'
initialize_args_dict = hs.default_initialize_args_dict
analyze_input_filename = 'analyze_input'
analyze_output_filename = 'analyze_output'
analyze_args_dict = hs.default_analyze_args_dict
# set up
table_data = xu.read_and_pickle_table_data(filename, table_data_filename)
# create initialize input
xu.write_initialization_files(initialize_input_filename,
initialize_args_dict=initialize_args_dict,
n_chains=n_chains)
# initialize
xu.run_script_local(initialize_input_filename, script_name,
initialize_output_filename)
# read initialization output, write analyze input
analyze_args_dict['n_steps'] = n_steps
analyze_args_dict['max_time'] = 20
xu.link_initialize_to_analyze(initialize_output_filename,
analyze_input_filename, analyze_args_dict)
# analyze
xu.run_script_local(analyze_input_filename, script_name,
analyze_output_filename)
script_name = 'hadoop_line_processor.py'
#
table_data_filename = hs.default_table_data_filename
initialize_input_filename = 'initialize_input'
initialize_output_filename = 'initialize_output'
initialize_args_dict = hs.default_initialize_args_dict
analyze_input_filename = 'analyze_input'
analyze_output_filename = 'analyze_output'
analyze_args_dict = hs.default_analyze_args_dict
# set up
table_data = xu.read_and_pickle_table_data(filename, table_data_filename)
# create initialize input
xu.write_initialization_files(initialize_input_filename,
initialize_args_dict=initialize_args_dict,
n_chains=n_chains)
# initialize
xu.run_script_local(initialize_input_filename, script_name,
initialize_output_filename)
# read initialization output, write analyze input
analyze_args_dict['n_steps'] = n_steps
analyze_args_dict['max_time'] = 20
xu.link_initialize_to_analyze(initialize_output_filename,
analyze_input_filename,
analyze_args_dict)
# analyze
xu.run_script_local(analyze_input_filename, script_name,
