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Add animate_transient and refactor FieldsContainer.animate() to use it #904

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Add animate_transient and refactor FieldsContainer.animate() to use it #904

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116 changes: 115 additions & 1 deletion src/ansys/dpf/core/animation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,14 +20,17 @@ def animate_mode(

Parameters
----------
field_container :
fields_container :
Field container containing the modal results.
mode_number : int, optional
Mode number of the results to animation. The default is ``1``.
type_mode : int, optional
Whether it is 0 or 1. Default to 0.
If 0, the norm of the displacements will be scaled from 1 to -1 to 1.
If 1, the norm of the displacements will be scaled between -1 and 1.
frame_number: int, optional
Number of frames to create for the animation.
Defaults to 41 when type_mode=0, or 21 when type_mode=1
save_as : Path of file to save the animation to. Defaults to None. Can be of any format
supported by pyvista.Plotter.write_frame (.gif, .mp4, ...).
deform_scale_factor : float, optional
Expand Down Expand Up @@ -108,3 +111,114 @@ def animate_mode(
clim=[0, max_data],
**kwargs,
)


def animate_transient(
fields_container, save_as=None, deform_by=None, deform_scale_factor=1.0, **kwargs
):
"""Creates an animation based on the Fields contained in the FieldsContainer.

This method creates a movie or a gif based on the time ids of a FieldsContainer.
For kwargs see pyvista.Plotter.open_movie/add_text/show.

Parameters
----------
fields_container: FieldsContainer
Field container containing the results to animate.
save_as :
Path of file to save the animation to. Defaults to None. Can be of any format
supported by pyvista.Plotter.write_frame (.gif, .mp4, ...).
deform_by : FieldsContainer, Result, Operator, optional
Used to deform the plotted mesh. Must return a FieldsContainer of the same length as
fields_container, containing 3D vector Fields of distances.
Defaults to None, which takes fields_container if possible.
Set as False to force static animation.
deform_scale_factor : float, list, optional
Scale factor to apply when warping the mesh. Defaults to 1.0. Can be a list to make
scaling frequency-dependent.
"""
from ansys.dpf.core.animator import Animator

# Create a workflow defining the result to render at each step of the animation
wf = dpf.Workflow()
# First define the workflow index input
forward_index = dpf.operators.utility.forward()
wf.set_input_name("loop_over", forward_index.inputs.any)
# Define the field extraction using the fields_container and indices
extract_field_op = dpf.operators.utility.extract_field(fields_container)
to_render = extract_field_op.outputs.field
n_components = fields_container[0].component_count
if n_components > 1:
norm_op = dpf.operators.math.norm(extract_field_op.outputs.field)
to_render = norm_op.outputs.field

loop_over = fields_container.get_time_scoping()
frequencies = fields_container.time_freq_support.time_frequencies
if frequencies is None:
raise ValueError("The fields_container has no time_frequencies.")

# TODO /!\ We should be using a mechanical::time_selector, however it is not wrapped.

wf.set_input_name("indices", extract_field_op.inputs.indices) # Have to do it this way
wf.connect("indices", forward_index) # Otherwise not accepted
# Add the operators to the workflow
wf.add_operators([extract_field_op, forward_index])

deform = True
# Define whether to deform and what with
if deform_by is not False:
if deform_by is None or isinstance(deform_by, bool):
# By default, set deform_by as fields_container if nodal 3D vector field
if fields_container[0].location == dpf.common.locations.nodal and n_components == 3:
deform_by = fields_container
else:
deform = False
if deform_by and not isinstance(deform_by, dpf.FieldsContainer):
deform_by = deform_by.eval()
if len(deform_by) != len(fields_container):
raise ValueError(
"'deform_by' argument must result in a FieldsContainer "
"of same length as the animated one "
f"(len(deform_by.eval())={len(deform_by)} "
f"!= len(fields_container)={len(fields_container)})."
)
else:
deform = False

if deform:
scale_factor_fc = dpf.animator.scale_factor_to_fc(deform_scale_factor, deform_by)
scale_factor_invert = dpf.operators.math.invert_fc(scale_factor_fc)
# Extraction of the field of interest based on index
# time_selector = dpf.Operator("mechanical::time_selector")
extract_field_op_2 = dpf.operators.utility.extract_field(deform_by)
wf.set_input_name("indices", extract_field_op_2.inputs.indices)
wf.connect("indices", forward_index) # Otherwise not accepted
# Scaling of the field based on scale_factor and index
extract_scale_factor_op = dpf.operators.utility.extract_field(scale_factor_invert)
wf.set_input_name("indices", extract_scale_factor_op.inputs.indices)
wf.connect("indices", forward_index) # Otherwise not accepted

divide_op = dpf.operators.math.component_wise_divide(
extract_field_op_2.outputs.field, extract_scale_factor_op.outputs.field
)
wf.set_output_name("deform_by", divide_op.outputs.field)
else:
deform_scale_factor = None
wf.set_output_name("to_render", to_render)
wf.progress_bar = False

loop_over_field = dpf.fields_factory.field_from_array(frequencies.data[loop_over.ids - 1])
loop_over_field.scoping.ids = loop_over.ids
loop_over_field.unit = frequencies.unit

# Initiate the Animator
anim = Animator(workflow=wf, **kwargs)

kwargs.setdefault("freq_kwargs", {"font_size": 12, "fmt": ".3e"})

return anim.animate(
loop_over=loop_over_field,
save_as=save_as,
scale_factor=deform_scale_factor,
**kwargs,
)
90 changes: 6 additions & 84 deletions src/ansys/dpf/core/fields_container.py
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Original file line number Diff line number Diff line change
Expand Up @@ -497,92 +497,14 @@ def animate(self, save_as=None, deform_by=None, scale_factor=1.0, **kwargs):
Scale factor to apply when warping the mesh. Defaults to 1.0. Can be a list to make
scaling frequency-dependent.
"""
from ansys.dpf.core.animator import Animator

# Create a workflow defining the result to render at each step of the animation
wf = dpf.core.Workflow()
# First define the workflow index input
forward_index = dpf.core.operators.utility.forward()
wf.set_input_name("loop_over", forward_index.inputs.any)
# Define the field extraction using the fields_container and indices
extract_field_op = dpf.core.operators.utility.extract_field(self)
to_render = extract_field_op.outputs.field
n_components = self[0].component_count
if n_components > 1:
norm_op = dpf.core.operators.math.norm(extract_field_op.outputs.field)
to_render = norm_op.outputs.field

loop_over = self.get_time_scoping()
frequencies = self.time_freq_support.time_frequencies
if frequencies is None:
raise ValueError("The fields_container has no time_frequencies.")

# TODO /!\ We should be using a mechanical::time_selector, however it is not wrapped.

wf.set_input_name("indices", extract_field_op.inputs.indices) # Have to do it this way
wf.connect("indices", forward_index) # Otherwise not accepted
# Add the operators to the workflow
wf.add_operators([extract_field_op, forward_index])

deform = True
# Define whether to deform and what with
if deform_by is not False:
if deform_by is None or isinstance(deform_by, bool):
# By default, set deform_by as self if nodal 3D vector field
if self[0].location == dpf.core.common.locations.nodal and n_components == 3:
deform_by = self
else:
deform = False
if deform_by and not isinstance(deform_by, dpf.core.FieldsContainer):
deform_by = deform_by.eval()
if len(deform_by) != len(self):
raise ValueError(
"'deform_by' argument must result in a FieldsContainer "
"of same length as the animated one "
f"(len(deform_by.eval())={len(deform_by)} "
f"!= len(self)={len(self)})."
)
else:
deform = False

if deform:
scale_factor_fc = dpf.core.animator.scale_factor_to_fc(scale_factor, deform_by)
scale_factor_invert = dpf.core.operators.math.invert_fc(scale_factor_fc)
# Extraction of the field of interest based on index
# time_selector = dpf.core.Operator("mechanical::time_selector")
extract_field_op_2 = dpf.core.operators.utility.extract_field(deform_by)
wf.set_input_name("indices", extract_field_op_2.inputs.indices)
wf.connect("indices", forward_index) # Otherwise not accepted
# Scaling of the field based on scale_factor and index
extract_scale_factor_op = dpf.core.operators.utility.extract_field(scale_factor_invert)
wf.set_input_name("indices", extract_scale_factor_op.inputs.indices)
wf.connect("indices", forward_index) # Otherwise not accepted

divide_op = dpf.core.operators.math.component_wise_divide(
extract_field_op_2.outputs.field, extract_scale_factor_op.outputs.field
)
wf.set_output_name("deform_by", divide_op.outputs.field)
else:
scale_factor = None
wf.set_output_name("to_render", to_render)
wf.progress_bar = False

loop_over_field = dpf.core.fields_factory.field_from_array(
frequencies.data[loop_over.ids - 1]
)
loop_over_field.scoping.ids = loop_over.ids
loop_over_field.unit = frequencies.unit

# Initiate the Animator
anim = Animator(workflow=wf, **kwargs)

kwargs.setdefault("freq_kwargs", {"font_size": 12, "fmt": ".3e"})
from ansys.dpf.core.animation import animate_transient

return anim.animate(
loop_over=loop_over_field,
return animate_transient(
fields_container=self,
save_as=save_as,
scale_factor=scale_factor,
**kwargs,
deform_by=deform_by,
deform_scale_factor=scale_factor,
**kwargs
)

def __add__(self, fields_b):
Expand Down