from typing import Union
import numpy as np
import plotly.graph_objs as go
from .plot_resp_base import PlotResponseBase
from .plot_utils import (
_plot_points_cmap,
_plot_lines,
_plot_lines_cmap,
_plot_all_mesh,
_get_line_cells,
_get_unstru_cells,
_get_plotly_dim_scene
)
from ...post import loadODB
from ...utils import gram_schmidt, CONSTANTS
PKG_NAME = CONSTANTS.get_pkg_name()
class PlotTrussResponse(PlotResponseBase):
def __init__(self, model_info_steps, truss_resp_step, model_update):
super().__init__(model_info_steps, truss_resp_step, model_update)
def _get_truss_data(self, step):
return self._get_model_data("TrussData", step)
def _plot_all_mesh(self, plotter, color="#738595", step=0):
pos = self._get_node_data(step).to_numpy()
line_cells, _ = _get_line_cells(self._get_line_data(step))
_, unstru_cell_types, unstru_cells = _get_unstru_cells(
self._get_unstru_data(step)
)
(
face_points,
face_line_points,
face_mid_points,
veci,
vecj,
veck,
) = self._get_plotly_unstru_data(
pos, unstru_cell_types, unstru_cells, scalars=None
)
line_points, line_mid_points = self._get_plotly_line_data(
pos, line_cells, scalars=None
)
_plot_all_mesh(plotter, line_points, face_line_points, color=color, width=1.5)
def _set_resp_type(self, resp_type: str):
if resp_type.lower() in ["axialforce", "force"]:
resp_type = "axialForce"
elif resp_type.lower() in ["axialdefo", "axialdeformation", "deformation"]:
resp_type = "axialDefo"
elif resp_type.lower() in ["stress", "axialstress"]:
resp_type = "Stress"
elif resp_type.lower() in ["strain", "axialstrain"]:
resp_type = "Strain"
else:
raise ValueError(
f"Not supported response type {resp_type}! "
"Valid options are: axialForce, axialDefo, Stress, Strain."
)
self.resp_type = resp_type
def _make_truss_info(self, ele_tags, step):
pos = self._get_node_data(step).to_numpy()
truss_data = self._get_truss_data(step)
if ele_tags is None:
truss_tags = truss_data.coords["eleTags"].values
truss_cells = truss_data.to_numpy().astype(int)
else:
truss_tags = np.atleast_1d(ele_tags)
truss_cells = truss_data.sel(eleTags=truss_tags).to_numpy().astype(int)
truss_node_coords = []
truss_cells_new = []
for i, cell in enumerate(truss_cells):
nodei, nodej = cell[1:]
truss_node_coords.append(pos[nodei])
truss_node_coords.append(pos[nodej])
truss_cells_new.append([2, 2 * i, 2 * i + 1])
truss_node_coords = np.array(truss_node_coords)
return truss_tags, truss_node_coords, truss_cells_new
def refactor_resp_step(self, resp_type: str, ele_tags):
self._set_resp_type(resp_type)
resps = []
if self.ModelUpdate or ele_tags is not None:
for i in range(self.num_steps):
truss_tags, _, _ = self._make_truss_info(ele_tags, i)
da = self._get_resp_data(i, self.resp_type)
da = da.sel(eleTags=truss_tags)
resps.append(da)
else:
for i in range(self.num_steps):
da = self._get_resp_data(i, self.resp_type)
resps.append(da)
self.resp_step = resps # update
def _get_resp_peak(self, idx="absMax"):
if isinstance(idx, str):
if idx.lower() == "absmax":
resp = [np.max(np.abs(data)) for data in self.resp_step]
step = np.argmax(resp)
elif idx.lower() == "max":
resp = [np.max(data) for data in self.resp_step]
step = np.argmax(resp)
elif idx.lower() == "absmin":
resp = [np.min(np.abs(data)) for data in self.resp_step]
step = np.argmin(resp)
elif idx.lower() == "min":
resp = [np.min(data) for data in self.resp_step]
step = np.argmin(resp)
else:
raise ValueError("Invalid argument, one of [absMax, absMin, Max, Min]")
else:
step = int(idx)
resp = self.resp_step[step]
maxv = np.amax(np.abs(resp))
if maxv == 0:
alpha_ = 0.0
else:
alpha_ = self.max_bound_size * self.pargs.scale_factor / maxv
cmin, cmax = self._get_truss_resp_clim()
return step, (cmin, cmax), float(alpha_)
def _get_truss_resp_clim(self):
maxv = [np.max(data) for data in self.resp_step]
minv = [np.min(data) for data in self.resp_step]
cmin, cmax = np.min(minv), np.max(maxv)
return cmin, cmax
def _create_mesh(
self,
plotter,
value,
ele_tags=None,
show_values=True,
plot_all_mesh=True,
clim=None,
coloraxis="coloraxis",
alpha=1.0,
line_width=1.5,
):
step = int(round(value))
truss_tags, truss_coords, truss_cells = self._make_truss_info(ele_tags, step)
resps = self.resp_step[step].to_numpy()
resp_points, resp_cells = [], []
scalars = []
for cell, resp in zip(truss_cells, resps):
coord1 = truss_coords[cell[1]]
coord2 = truss_coords[cell[2]]
xaxis = coord2 - coord1
length = np.linalg.norm(xaxis)
xaxis = xaxis / length
cos_theta = np.dot(xaxis, [0, 0, 1])
if 1 - cos_theta**2 < 1e-4:
axis_up = [1, 0, 0]
elif self.show_zaxis:
axis_up = [0, 0, 1]
else:
axis_up = [0, 1, 0]
_, plot_axis, _ = gram_schmidt(xaxis, axis_up)
coord3 = coord1 + alpha * resp * plot_axis
coord4 = coord2 + alpha * resp * plot_axis
coord_upper = [coord3 + length / 12 * i * xaxis for i in range(13)] + [
coord4
]
coord_lower = [coord1 + length / 12 * i * xaxis for i in range(13)] + [
coord3
]
for i in range(len(coord_upper)):
resp_cells.append([2, len(resp_points), len(resp_points) + 1])
resp_points.extend([coord_lower[i], coord_upper[i]])
scalars.extend([resp, resp])
resp_points = np.array(resp_points)
scalars = np.array(scalars)
# ---------------------------------
if plot_all_mesh:
self._plot_all_mesh(plotter, step=step)
line_points, line_mid_points = self._get_plotly_line_data(
truss_coords, truss_cells, scalars=None
)
_plot_lines(
plotter,
pos=line_points,
width=self.pargs.line_width,
color=self.pargs.color_truss,
name="Truss",
hoverinfo="skip",
)
line_points, line_mid_points, line_scalars = self._get_plotly_line_data(
resp_points, resp_cells, scalars
)
_plot_lines_cmap(
plotter,
line_points,
scalars=line_scalars,
coloraxis=coloraxis,
clim=clim,
width=line_width,
)
if show_values:
_plot_points_cmap(
plotter,
resp_points,
scalars=scalars,
clim=clim,
coloraxis=coloraxis,
name=self.resp_type,
size=self.pargs.point_size,
)
def _make_txt(self, step):
resp = self.resp_step[step].to_numpy()
maxv = np.max(resp)
minv = np.min(resp)
t_ = self.time[step]
title = f'<span style="font-weight:bold; font-size:{self.pargs.title_font_size}">{PKG_NAME}'
title += " :: Truss Responses 3D Viewer</span><br><br><br>"
title += f"<b>{self.resp_type.capitalize()}</b><br>"
# comp = (
# self.component
# if isinstance(self.component, str)
# else " ".join(self.component)
# )
# title += f"<b>{comp}</b><br>"
maxv = self._set_txt_props(f"{maxv:.3E}")
minv = self._set_txt_props(f"{minv:.3E}")
title += f"<b>Max.:</b> {maxv}<br><b>Min.:</b> {minv}"
step_txt = self._set_txt_props(f"{step}")
title += f"<br><b>step:</b> {step_txt}; "
t_txt = self._set_txt_props(f"{t_:.3f}")
title += f"<b>time</b>: {t_txt}"
txt = dict(
font=dict(size=self.pargs.font_size),
text=title,
)
return txt
def plot_slide(
self,
ele_tags=None,
show_values=True,
alpha=1.0,
line_width=1.5,
):
plot_all_mesh = True if ele_tags is None else False
_, clim, alpha_ = self._get_resp_peak()
n_data = None
for i in range(self.num_steps):
plotter = []
self._create_mesh(
plotter,
i,
alpha=alpha_ * alpha,
ele_tags=ele_tags,
clim=clim,
coloraxis=f"coloraxis{i + 1}",
show_values=show_values,
plot_all_mesh=plot_all_mesh,
line_width=line_width,
)
self.FIGURE.add_traces(plotter)
if i == 0:
n_data = len(self.FIGURE.data)
for i in range(0, len(self.FIGURE.data) - n_data):
self.FIGURE.data[i].visible = False
# Create and add slider
steps = []
for i in range(self.num_steps):
txt = self._make_txt(i)
step = dict(
method="update",
args=[
{"visible": [False] * len(self.FIGURE.data)},
{"title": txt},
], # layout attribute
label=str(i),
)
step["args"][0]["visible"][n_data * i : n_data * (i + 1)] = [True] * n_data
# Toggle i'th trace to "visible"
steps.append(step)
sliders = [
dict(
active=self.num_steps,
currentvalue={"prefix": "Step: "},
pad={"t": 50},
steps=steps,
)
]
coloraxiss = {}
for i in range(self.num_steps):
coloraxiss[f"coloraxis{i + 1}"] = dict(
colorscale=self.pargs.cmap,
cmin=clim[0],
cmax=clim[1],
showscale=True,
colorbar=dict(tickfont=dict(size=15)),
)
self.FIGURE.update_layout(
sliders=sliders,
**coloraxiss,
)
def plot_peak_step(
self,
ele_tags=None,
step="absMax",
show_values=True,
alpha=1.0,
line_width=1.5,
):
plot_all_mesh = True if ele_tags is None else False
max_step, clim, alpha_ = self._get_resp_peak(idx=step)
plotter = []
self._create_mesh(
plotter=plotter,
value=max_step,
ele_tags=ele_tags,
alpha=alpha_ * alpha,
clim=clim,
coloraxis="coloraxis",
show_values=show_values,
plot_all_mesh=plot_all_mesh,
line_width=line_width,
)
self.FIGURE.add_traces(plotter)
txt = self._make_txt(max_step)
self.FIGURE.update_layout(
coloraxis=dict(
colorscale=self.pargs.cmap,
cmin=clim[0],
cmax=clim[1],
colorbar=dict(tickfont=dict(size=self.pargs.font_size - 2)),
),
title=txt,
)
def plot_anim(
self,
ele_tags=None,
show_values=True,
alpha=1.0,
framerate: int = None,
line_width=1.5,
):
if framerate is None:
framerate = np.ceil(self.num_steps / 10)
plot_all_mesh = True if ele_tags is None else False
_, clim, alpha_ = self._get_resp_peak()
nb_frames = self.num_steps
times = int(nb_frames / framerate)
# -----------------------------------------------------------------------------
# start plot
frames = []
for i in range(nb_frames):
plotter = []
self._create_mesh(
plotter=plotter,
value=i,
ele_tags=ele_tags,
alpha=alpha_ * alpha,
clim=clim,
coloraxis="coloraxis",
show_values=show_values,
plot_all_mesh=plot_all_mesh,
line_width=line_width,
)
frames.append(go.Frame(data=plotter, name="step:" + str(i)))
self.FIGURE = go.Figure(frames=frames)
# Add data to be displayed before animation starts
plotter0 = []
self._create_mesh(
plotter0,
0,
alpha=alpha_,
ele_tags=ele_tags,
coloraxis="coloraxis",
clim=clim,
show_values=show_values,
plot_all_mesh=plot_all_mesh,
line_width=line_width,
)
self.FIGURE.add_traces(plotter0)
def frame_args(duration):
return {
"frame": {"duration": duration},
"mode": "immediate",
"fromcurrent": True,
"transition": {"duration": duration, "easing": "linear"},
}
sliders = [
{
"pad": {"b": 10, "t": 60},
"len": 0.9,
"x": 0.1,
"y": 0,
"steps": [
{
"args": [[f.name], frame_args(0)],
"label": "step:" + str(k),
"method": "animate",
}
for k, f in enumerate(self.FIGURE.frames)
],
}
]
# Layout
for i in range(len(self.FIGURE.frames)):
txt = self._make_txt(i)
self.FIGURE.frames[i]["layout"].update(title=txt)
self.FIGURE.update_layout(
coloraxis=dict(
colorscale=self.pargs.cmap,
cmin=clim[0],
cmax=clim[1],
colorbar=dict(tickfont=dict(size=15)),
),
updatemenus=[
{
"buttons": [
{
"args": [None, frame_args(times)],
"label": "▶", # play symbol
"method": "animate",
},
{
"args": [[None], frame_args(0)],
"label": "◼", # pause symbol
"method": "animate",
},
],
"direction": "left",
"pad": {"r": 10, "t": 70},
"type": "buttons",
"x": 0.1,
"y": 0,
}
],
sliders=sliders,
)
def update_fig(self, show_outline: bool = False):
if not self.show_zaxis:
scene = _get_plotly_dim_scene(mode="2d", show_outline=show_outline)
else:
scene = _get_plotly_dim_scene(mode="3d", show_outline=show_outline)
self.FIGURE.update_layout(
template=self.pargs.theme,
autosize=True,
showlegend=False,
scene=scene,
# title=title,
font=dict(family=self.pargs.font_family),
)
return self.FIGURE
[docs]
def plot_truss_responses(
odb_tag: Union[int, str] = 1,
ele_tags: Union[int, list] = None,
slides: bool = False,
step: Union[int, str] = "absMax",
show_values: bool = True,
resp_type: str = "axialForce",
alpha: float = 1.0,
show_outline: bool = False,
line_width: float = 1.5,
):
"""Visualizing Truss Response.
Parameters
----------
odb_tag: Union[int, str], default: 1
Tag of output databases (ODB) to be visualized.
ele_tags: Union[int, list], default: None
The tags of truss elements to be visualized. If None, all truss elements are selected.
slides: bool, default: False
Display the response for each step in the form of a slideshow.
Otherwise, show the step with the following ``step`` parameter.
step: Union[int, str], default: "absMax"
If slides = False, this parameter will be used as the step to plot.
If str, Optional: [absMax, absMin, Max, Min].
If int, this step will be demonstrated (counting from 0).
show_values: bool, default: True
Whether to display the response value.
resp_type: str, default: "axialForce"
Response type, optional, one of ["axialForce", "axialDefo", "Stress", "Strain"].
alpha: float, default: 1.0
Scale the size of the response graph.
.. Note::
You can adjust the scale to make the response graph more visible.
A negative number will reverse the direction.
show_outline: bool, default: False
Whether to display the outline of the model.
line_width: float, default: 1.5.
Line width of the response graph.
Returns
-------
fig: `plotly.graph_objects.Figure <https://plotly.com/python-api-reference/generated/plotly.graph_objects.Figure.html>`_
You can use `fig.show()` to display,
You can also use `fig.write_html("path/to/file.html")` to save as an HTML file, see
`Interactive HTML Export in Python <https://plotly.com/python/interactive-html-export/>`_
"""
model_info_steps, model_update, truss_resp_step = loadODB(
odb_tag, resp_type="Truss"
)
plotbase = PlotTrussResponse(model_info_steps, truss_resp_step, model_update)
plotbase.refactor_resp_step(resp_type=resp_type, ele_tags=ele_tags)
if slides:
plotbase.plot_slide(
ele_tags=ele_tags,
show_values=show_values,
alpha=alpha,
line_width=line_width,
)
else:
plotbase.plot_peak_step(
step=step,
show_values=show_values,
alpha=alpha,
line_width=line_width,
)
return plotbase.update_fig(show_outline=show_outline)
[docs]
def plot_truss_responses_animation(
odb_tag: Union[int, str] = 1,
ele_tags: Union[int, list] = None,
framerate: int = None,
show_values: bool = False,
resp_type: str = "axialForce",
alpha: float = 1.0,
show_outline: bool = False,
line_width: float = 1.5,
):
"""Truss response animation.
Parameters
----------
odb_tag: Union[int, str], default: 1
Tag of output databases (ODB) to be visualized.
ele_tags: Union[int, list], default: None
The tags of truss elements to be visualized. If None, all truss elements are selected.
framerate: int, default: None
Framerate for the display, i.e., the number of frames per second.
show_values: bool, default: False
Whether to display the response value.
resp_type: str, default: "axialForce"
Response type, optional, one of ["axialForce", "axialDefo", "Stress", "Strain"].
alpha: float, default: 1.0
Scale the size of the response graph.
.. Note::
You can adjust the scale to make the response graph more visible.
A negative number will reverse the direction.
show_outline: bool, default: False
Whether to display the outline of the model.
line_width: float, default: 1.5.
Line width of the response graph.
Returns
-------
fig: `plotly.graph_objects.Figure <https://plotly.com/python-api-reference/generated/plotly.graph_objects.Figure.html>`_
You can use `fig.show()` to display,
You can also use `fig.write_html("path/to/file.html")` to save as an HTML file, see
`Interactive HTML Export in Python <https://plotly.com/python/interactive-html-export/>`_
"""
model_info_steps, model_update, truss_resp_step = loadODB(
odb_tag, resp_type="Truss"
)
plotbase = PlotTrussResponse(model_info_steps, truss_resp_step, model_update)
plotbase.refactor_resp_step(resp_type=resp_type, ele_tags=ele_tags)
plotbase.plot_anim(
ele_tags=ele_tags,
show_values=show_values,
alpha=alpha,
framerate=framerate,
line_width=line_width,
)
return plotbase.update_fig(show_outline=show_outline)