fit_one_job¶

Run One Job¶

Prototype¶

# at_cascade.fit_one_job
def fit_one_job(
   job_table               ,
   run_job_id              ,
   all_node_database       ,
   node_table              ,
   fit_integrand           ,
   fit_type                ,
   first_fit               ,
   trace_file_obj   = None ,
) :
   assert type(job_table) == list
   assert type(run_job_id) == int
   assert type(all_node_database) == str
   assert type(node_table) == list
   assert type(fit_integrand) == set
   assert fit_type in [ 'both', 'fixed' ]
   assert type(first_fit) == bool
   if trace_file_obj is not None :
      assert isinstance(trace_file_obj, io.TextIOBase)

Default Value¶

The only argument that can be None is trace_file_obj.

job_table¶

This is a job_table containing the jobs necessary to fit the fit_goal_set.

run_job_id¶

This is the job_id for the job that is run.

all_node_database¶

is a python string specifying the location of the all_node_db relative to the current working directory.

node_table¶

is a list of dict containing the node table for this cascade.

fit_integrand¶

is a set of integrand_id values that occur in the data table; see get_fit_integrand.

fit_type¶

is a str equal to ‘both’ or ‘fixed’ and specifies the type of fit that dismod_at will do.

first_fit¶

If first_fit is True, this is assumed to be an input_node_database. Otherwise, it is assumed that this routine has previously been called with first_fit equal to True.

trace_file_obj¶

If this argument is not None, it is a io.TextIOBase object corresponding to a file that is opened for writing the tracing output for this job.

fit_database¶

The fit_database for this fit is fit_node_dir/dismod.db where fit_node_dir is the database_dir returned by get_database_dir for the fit node and split_reference_id corresponding to run_job_id.

Upon Input¶

On input, fit_database is an input_node_database.

fit_var¶

Upon return, the fit_var table correspond to the posterior mean for the model variables for the fit_node.

sample¶

Upon return, the sample table contains the corresponding samples from the posterior distribution for the model variables for the fit_node.

log¶

The log table is initialized as empty when fit_one_job starts. Upon return or abort due to an exception, the log table contains a summary of the operations preformed by dismod. In addition, the following entries will be added to the log table if the corresponding event occurs:

:header-rows:1¶
message_type	message	event
at_cascade	no data: abort	abort fit because all the data is held out
at_cascade	fit: OK	the maximum likelihood problem was solved
at_cascade	sample: OK	the posterior samples were computed
at_cascade	children: OK	the child databases with priors were created

Note that the events depend on each other in the following way:

If children: OK is present, then sample: OK is present.
If sample: OK is present, then fit: OK is present.
If fit: OK is present, then no data: abort is not present.

Exception¶

If there is no data from this fit, this routine will raise an exception with a message that starts with: no data: abort ; i.e., the same as the message it puts in the log.