def compile(self, col, mkr_list, attr_list, withtest=False):
"""
Compiles data given into flags for a single run of 'mmSolver'.
:param self: The solver to compile
:type self: Solver
:param col: The collection to compile.
:type col: Collection
:param mkr_list: Markers to measure
:type mkr_list: list of Marker
:param attr_list: Attributes to solve for
:type attr_list: list of Attribute
:return:
Yields a tuple of two Actions at each iteration. First
action is the solver action, second action is for
validation of the solve.
:rtype: (Action, Action)
"""
assert isinstance(self, solverbase.SolverBase)
assert isinstance(mkr_list, list)
assert isinstance(attr_list, list)
func = 'maya.cmds.mmSolverAffects'
args = []
kwargs = dict()
kwargs['camera'] = []
kwargs['marker'] = []
kwargs['attr'] = []
kwargs['mode'] = 'addAttrsToMarkers'
# Get precomputed data to reduce re-querying Maya for data.
precomputed_data = self.get_precomputed_data()
mkr_state_values = precomputed_data.get(
solverbase.MARKER_STATIC_VALUES_KEY)
attr_state_values = precomputed_data.get(
solverbase.ATTR_STATIC_VALUES_KEY)
# Get Markers and Cameras
markers, cameras = api_compile.markersAndCameras_compile_flags(
mkr_list, mkr_static_values=mkr_state_values)
if len(markers) == 0 and len(cameras) == 0:
LOG.warning('No Markers or Cameras found!')
return
elif len(markers) == 0:
LOG.warning('No Markers found!')
return
elif len(cameras) == 0:
LOG.warning('No Cameras found!')
return
# Get Attributes
#
# NOTE: time is not a factor for the calculation of 'affects'
# relationships, therefore use_animated and use_static are
# True, to ensure all attributes (that are not locked) are
# calculated.
use_animated = True
use_static = True
attrs = api_compile.attributes_compile_flags(
col,
attr_list,
use_animated,
use_static,
attr_static_values=attr_state_values)
if len(attrs) == 0:
LOG.warning('No Attributes found!')
return
kwargs['marker'] = markers
kwargs['camera'] = cameras
kwargs['attr'] = attrs
action = api_action.Action(func=func, args=args, kwargs=kwargs)
yield action, action
# Query and set 'used solver object' values on nodes.
func = _runAndSetUsedSolveObjects
args = [col.get_node()]
action = api_action.Action(func=func, args=args, kwargs=kwargs)
yield action, action
def compile(self, mkr_list, attr_list, withtest=False):
"""
Compiles data given into flags for a single run of 'mmSolver'.
:param self: The solver to compile
:type self: Solver
:param mkr_list: Markers to measure
:type mkr_list: list of Marker
:param attr_list: Attributes to solve for
:type attr_list: list of Attribute
:return: List of SolverActions to be performed one after the other.
:rtype: [SolverAction, ..]
"""
assert isinstance(self, solverbase.SolverBase)
assert isinstance(mkr_list, list)
assert isinstance(attr_list, list)
assert self.get_frame_list_length() > 0
func = 'maya.cmds.mmSolver'
args = []
kwargs = dict()
kwargs['camera'] = []
kwargs['marker'] = []
kwargs['attr'] = []
kwargs['frame'] = []
# Get Markers and Cameras
markers, cameras = api_compile.markersAndCameras_compile_flags(mkr_list)
if len(markers) == 0 and len(cameras) == 0:
LOG.warning('No Markers or Cameras found!')
return
elif len(markers) == 0:
LOG.warning('No Markers found!')
return
elif len(cameras) == 0:
LOG.warning('No Cameras found!')
return
# Get Attributes
use_animated = self.get_attributes_use_animated()
use_static = self.get_attributes_use_static()
attrs = api_compile.attributes_compile_flags(attr_list,
use_animated,
use_static)
if len(attrs) == 0:
LOG.warning('No Attributes found!')
return
# Get Frames
frm_list = self.get_frame_list()
frame_use_tags = self.get_frames_use_tags()
frames = api_compile.frames_compile_flags(frm_list, frame_use_tags)
if len(frames) == 0:
LOG.warning('No Frames found!')
return
kwargs['marker'] = markers
kwargs['camera'] = cameras
kwargs['attr'] = attrs
kwargs['frame'] = frames
solver_type = self.get_solver_type()
if solver_type is not None:
kwargs['solverType'] = solver_type
iterations = self.get_max_iterations()
if iterations is not None:
kwargs['iterations'] = iterations
verbose = self.get_verbose()
if verbose is not None:
kwargs['verbose'] = verbose
delta_factor = self.get_delta_factor()
if delta_factor is not None:
kwargs['delta'] = delta_factor
auto_diff_type = self.get_auto_diff_type()
if auto_diff_type is not None:
kwargs['autoDiffType'] = auto_diff_type
tau_factor = self.get_tau_factor()
if tau_factor is not None:
kwargs['tauFactor'] = tau_factor
gradient_error_factor = self.get_gradient_error_factor()
if gradient_error_factor is not None:
kwargs['epsilon1'] = gradient_error_factor
parameter_error_factor = self.get_parameter_error_factor()
if parameter_error_factor is not None:
kwargs['epsilon2'] = parameter_error_factor
error_factor = self.get_error_factor()
if error_factor is not None:
kwargs['epsilon3'] = error_factor
kwargs['robustLossType'] = const.ROBUST_LOSS_TYPE_TRIVIAL_VALUE
kwargs['robustLossScale'] = 1.0
# TODO: Add 'robustLossType' flag.
# TODO: Add 'robustLossScale' flag.
# TODO: Add 'autoParamScaling' flag.
# TODO: Add 'debugFile' flag.
# # Add a debug file flag to the mmSolver command, only
# # triggered during debug mode.
# # TODO: Wrap this in another function.
# if logging.DEBUG >= LOG.getEffectiveLevel():
# debug_file = maya.cmds.file(query=True, sceneName=True)
# debug_file = os.path.basename(debug_file)
# debug_file, ext = os.path.splitext(debug_file)
# debug_file_path = os.path.join(
# os.path.expandvars('${TEMP}'),
# debug_file + '_' + str(i).zfill(6) + '.log'
# )
# if len(debug_file) > 0 and debug_file_path is not None:
# kwargs['debugFile'] = debug_file_path
action = api_action.Action(
func=func,
args=args,
kwargs=kwargs
)
# Check the inputs and outputs are valid.
vaction = None
if withtest is True:
assert api_action.action_func_is_mmSolver(action) is True
vfunc = func
vargs = list(args)
vkwargs = kwargs.copy()
remove_keys = ['debugFile', 'verbose']
for key in remove_keys:
if key in vkwargs:
del vkwargs[key]
vkwargs['printStatistics'] = ['inputs']
vaction = api_action.Action(
func=vfunc,
args=vargs,
kwargs=vkwargs
)
yield action, vaction
def compile(self, col, mkr_list, attr_list, withtest=False):
"""
Compiles data given into flags for a single run of 'mmSolver'.
:param self: The solver to compile
:type self: Solver
:param col: The collection to compile.
:type col: Collection
:param mkr_list: Markers to measure
:type mkr_list: list of Marker
:param attr_list: Attributes to solve for
:type attr_list: list of Attribute
:return:
Yields a tuple of two Actions at each iteration. First
action is the solver action, second action is for
validation of the solve.
:rtype: (Action, Action)
"""
assert isinstance(self, solverbase.SolverBase)
assert isinstance(mkr_list, list)
assert isinstance(attr_list, list)
assert self.get_frame_list_length() > 0
func = 'maya.cmds.mmSolver'
args = []
kwargs = dict()
kwargs['camera'] = []
kwargs['marker'] = []
kwargs['attr'] = []
kwargs['frame'] = []
# Get precomputed data to reduce re-querying Maya for data.
precomputed_data = self.get_precomputed_data()
mkr_state_values = precomputed_data.get(
solverbase.MARKER_STATIC_VALUES_KEY)
attr_state_values = precomputed_data.get(
solverbase.ATTR_STATIC_VALUES_KEY)
attr_stiff_state_values = precomputed_data.get(
solverbase.ATTR_STIFFNESS_STATIC_VALUES_KEY)
attr_smooth_state_values = precomputed_data.get(
solverbase.ATTR_SMOOTHNESS_STATIC_VALUES_KEY)
# Get Markers and Cameras
markers, cameras = api_compile.markersAndCameras_compile_flags(
mkr_list, mkr_static_values=mkr_state_values)
if len(markers) == 0 and len(cameras) == 0:
LOG.warning('No Markers or Cameras found!')
return
elif len(markers) == 0:
LOG.warning('No Markers found!')
return
elif len(cameras) == 0:
LOG.warning('No Cameras found!')
return
# Get Attributes
use_animated = self.get_attributes_use_animated()
use_static = self.get_attributes_use_static()
attrs = api_compile.attributes_compile_flags(
col,
attr_list,
use_animated,
use_static,
attr_static_values=attr_state_values)
if len(attrs) == 0:
LOG.warning('No Attributes found!')
return
# Stiffness Attribute Flags
stiff_flags = None
use_stiffness = self.get_use_stiffness()
if use_stiffness is True:
stiff_flags = api_compile.attr_stiffness_compile_flags(
col,
attr_list,
attr_static_values=attr_state_values,
attr_stiff_static_values=attr_stiff_state_values,
)
# Smoothness Attribute Flags
smooth_flags = None
use_smoothness = self.get_use_smoothness()
if use_smoothness is True:
smooth_flags = api_compile.attr_smoothness_compile_flags(
col,
attr_list,
attr_static_values=attr_state_values,
attr_smooth_static_values=attr_smooth_state_values,
)
# Get Frames
frm_list = self.get_frame_list()
frame_use_tags = self.get_frames_use_tags()
frames = api_compile.frames_compile_flags(frm_list, frame_use_tags)
if len(frames) == 0:
LOG.warning('No Frames found!')
return
kwargs['marker'] = markers
kwargs['camera'] = cameras
kwargs['attr'] = attrs
kwargs['frame'] = frames
if stiff_flags:
kwargs['attrStiffness'] = stiff_flags
if smooth_flags:
kwargs['attrSmoothness'] = smooth_flags
solver_type = self.get_solver_type()
if solver_type is not None:
kwargs['solverType'] = solver_type
iterations = self.get_max_iterations()
if iterations is not None:
kwargs['iterations'] = iterations
verbose = self.get_verbose()
if verbose is not None:
kwargs['verbose'] = verbose
delta_factor = self.get_delta_factor()
if delta_factor is not None:
kwargs['delta'] = delta_factor
auto_diff_type = self.get_auto_diff_type()
if auto_diff_type is not None:
kwargs['autoDiffType'] = auto_diff_type
tau_factor = self.get_tau_factor()
if tau_factor is not None:
kwargs['tauFactor'] = tau_factor
gradient_error_factor = self.get_gradient_error_factor()
if gradient_error_factor is not None:
kwargs['epsilon1'] = gradient_error_factor
parameter_error_factor = self.get_parameter_error_factor()
if parameter_error_factor is not None:
kwargs['epsilon2'] = parameter_error_factor
error_factor = self.get_error_factor()
if error_factor is not None:
kwargs['epsilon3'] = error_factor
kwargs['robustLossType'] = const.ROBUST_LOSS_TYPE_TRIVIAL_VALUE
kwargs['robustLossScale'] = 1.0
kwargs['timeEvalMode'] = self.get_time_eval_mode()
value = self.get_remove_unused_markers()
if value is not None:
kwargs['removeUnusedMarkers'] = value
value = self.get_remove_unused_attributes()
if value is not None:
kwargs['removeUnusedAttributes'] = value
# TODO: Add 'robustLossType' flag.
# TODO: Add 'robustLossScale' flag.
# TODO: Add 'autoParamScaling' flag.
# TODO: Add 'debugFile' flag.
# # Add a debug file flag to the mmSolver command, only
# # triggered during debug mode.
# # TODO: Wrap this in another function.
# if logging.DEBUG >= LOG.getEffectiveLevel():
# debug_file = maya.cmds.file(query=True, sceneName=True)
# debug_file = os.path.basename(debug_file)
# debug_file, ext = os.path.splitext(debug_file)
# debug_file_path = os.path.join(
# os.path.expandvars('${TEMP}'),
# debug_file + '_' + str(i).zfill(6) + '.log'
# )
# if len(debug_file) > 0 and debug_file_path is not None:
# kwargs['debugFile'] = debug_file_path
action = api_action.Action(func=func, args=args, kwargs=kwargs)
# Check the inputs and outputs are valid.
vaction = None
if withtest is True:
assert api_action.action_func_is_mmSolver(action) is True
vfunc = func
vargs = list(args)
vkwargs = kwargs.copy()
remove_keys = ['debugFile', 'verbose']
for key in remove_keys:
if key in vkwargs:
del vkwargs[key]
vkwargs['printStatistics'] = ['inputs']
vaction = api_action.Action(func=vfunc, args=vargs, kwargs=vkwargs)
yield action, vaction