def list_outputs(self,
explicit=True,
implicit=True,
values=True,
prom_name=False,
residuals=False,
residuals_tol=None,
units=False,
shape=False,
bounds=False,
scaling=False,
desc=False,
hierarchical=True,
print_arrays=False,
tags=None,
includes=None,
excludes=None,
list_autoivcs=False,
out_stream=_DEFAULT_OUT_STREAM):
"""
Return and optionally log a list of output names and other optional information.
Parameters
----------
explicit : bool, optional
include outputs from explicit components. Default is True.
implicit : bool, optional
include outputs from implicit components. Default is True.
values : bool, optional
When True, display/return output values. Default is True.
prom_name : bool, optional
When True, display/return the promoted name of the variable.
Default is False.
residuals : bool, optional
When True, display/return residual values. Default is False.
residuals_tol : float, optional
If set, limits the output of list_outputs to only variables where
the norm of the resids array is greater than the given 'residuals_tol'.
Default is None.
units : bool, optional
When True, display/return units. Default is False.
shape : bool, optional
When True, display/return the shape of the value. Default is False.
bounds : bool, optional
When True, display/return bounds (lower and upper). Default is False.
scaling : bool, optional
When True, display/return scaling (ref, ref0, and res_ref). Default is False.
desc : bool, optional
When True, display/return description. Default is False.
hierarchical : bool, optional
When True, human readable output shows variables in hierarchical format.
print_arrays : bool, optional
When False, in the columnar display, just display norm of any ndarrays with size > 1.
The norm is surrounded by vertical bars to indicate that it is a norm.
When True, also display full values of the ndarray below the row. Format is affected
by the values set with numpy.set_printoptions
Default is False.
tags : str or list of strs
User defined tags that can be used to filter what gets listed. Only outputs with the
given tags will be listed.
Default is None, which means there will be no filtering based on tags.
includes : iter of str or None
Glob patterns for pathnames to include in the check. Default is None, which
includes all.
excludes : iter of str or None
Glob patterns for pathnames to exclude from the check. Default is None, which
excludes nothing.
list_autoivcs : bool
If True, include auto_ivc outputs in the listing. Defaults to False.
out_stream : file-like
Where to send human readable output. Default is sys.stdout.
Set to None to suppress.
Returns
-------
list
list of output names and other optional information about those outputs
"""
meta = self._abs2meta
expl_outputs = []
impl_outputs = []
for var_name in self.outputs.absolute_names():
if not list_autoivcs and var_name.startswith('_auto_ivc.'):
continue
# Filter based on tags
if tags and not (make_set(tags)
& make_set(meta[var_name]['tags'])):
continue
var_name_prom = self._abs2prom['output'][var_name]
if not match_prom_or_abs(var_name, var_name_prom, includes,
excludes):
continue
# check if residuals were recorded, skip if within specifed tolerance
if residuals and self.residuals and var_name in self.residuals.absolute_names(
):
resids = self.residuals[var_name]
if residuals_tol and np.linalg.norm(resids) < residuals_tol:
continue
else:
resids = 'Not Recorded'
val = self.outputs[var_name]
var_meta = {}
if values:
var_meta['value'] = val
if prom_name:
var_meta['prom_name'] = var_name_prom
if residuals:
var_meta['resids'] = resids
if units:
var_meta['units'] = meta[var_name]['units']
if shape:
var_meta['shape'] = val.shape
if bounds:
var_meta['lower'] = meta[var_name]['lower']
var_meta['upper'] = meta[var_name]['upper']
if scaling:
var_meta['ref'] = meta[var_name]['ref']
var_meta['ref0'] = meta[var_name]['ref0']
var_meta['res_ref'] = meta[var_name]['res_ref']
if desc:
var_meta['desc'] = meta[var_name]['desc']
if meta[var_name]['explicit']:
expl_outputs.append((var_name, var_meta))
else:
impl_outputs.append((var_name, var_meta))
if out_stream:
if not self.outputs:
ostream = sys.stdout if out_stream is _DEFAULT_OUT_STREAM else out_stream
ostream.write(
'WARNING: Outputs not recorded. Make sure your recording '
+ 'settings have record_outputs set to True\n')
if explicit:
self._write_table('explicit', expl_outputs, hierarchical,
print_arrays, out_stream)
if implicit:
self._write_table('implicit', impl_outputs, hierarchical,
print_arrays, out_stream)
if explicit and implicit:
return expl_outputs + impl_outputs
elif explicit:
return expl_outputs
elif implicit:
return impl_outputs
else:
raise RuntimeError(
'You have excluded both Explicit and Implicit components.')
def list_inputs(self,
values=True,
prom_name=False,
units=False,
shape=False,
desc=False,
hierarchical=True,
print_arrays=False,
tags=None,
includes=None,
excludes=None,
out_stream=_DEFAULT_OUT_STREAM):
"""
Return and optionally log a list of input names and other optional information.
Parameters
----------
values : bool, optional
When True, display/return input values. Default is True.
prom_name : bool, optional
When True, display/return the promoted name of the variable.
Default is False.
units : bool, optional
When True, display/return units. Default is False.
shape : bool, optional
When True, display/return the shape of the value. Default is False.
desc : bool, optional
When True, display/return description. Default is False.
hierarchical : bool, optional
When True, human readable output shows variables in hierarchical format.
print_arrays : bool, optional
When False, in the columnar display, just display norm of any ndarrays with size > 1.
The norm is surrounded by vertical bars to indicate that it is a norm.
When True, also display full values of the ndarray below the row. Format is affected
by the values set with numpy.set_printoptions
Default is False.
tags : str or list of strs
User defined tags that can be used to filter what gets listed. Only inputs with the
given tags will be listed.
Default is None, which means there will be no filtering based on tags.
includes : iter of str or None
Glob patterns for pathnames to include in the check. Default is None, which
includes all.
excludes : iter of str or None
Glob patterns for pathnames to exclude from the check. Default is None, which
excludes nothing.
out_stream : file-like object
Where to send human readable output. Default is sys.stdout.
Set to None to suppress.
Returns
-------
list
list of input names and other optional information about those inputs
"""
meta = self._abs2meta
inputs = []
if self.inputs is not None:
for var_name in self.inputs.absolute_names():
# Filter based on tags
if tags and not (make_set(tags)
& make_set(meta[var_name]['tags'])):
continue
var_name_prom = self._abs2prom['input'][var_name]
if not match_prom_or_abs(var_name, var_name_prom, includes,
excludes):
continue
val = self.inputs[var_name]
var_meta = {}
if values:
var_meta['value'] = val
if prom_name:
var_meta['prom_name'] = var_name_prom
if units:
var_meta['units'] = meta[var_name]['units']
if shape:
var_meta['shape'] = val.shape
if desc:
var_meta['desc'] = meta[var_name]['desc']
inputs.append((var_name, var_meta))
if out_stream:
if self.inputs:
self._write_table('input', inputs, hierarchical, print_arrays,
out_stream)
else:
ostream = sys.stdout if out_stream is _DEFAULT_OUT_STREAM else out_stream
ostream.write(
'WARNING: Inputs not recorded. Make sure your recording ' +
'settings have record_inputs set to True\n')
return inputs
