Visualization based on plotly

Tip

Due to the interactivity of plotly, the image rendering speed is relatively slow. If you have many analysis steps, such as earthquake response time history analysis, you should use the pyvista engine.

Display OpenSeesPy Model

First load the necessary classes and functions, where GetFEMdata is used to get the model data from the current domain of OpenSeesPy, and OpsVisPlotly is used to visualize the model.

import openseespy.opensees as ops
from opstool.vis import GetFEMdata, OpsVisPlotly
from opstool import load_ops_examples

Load the 3D Arch Bridge finite element model. Function load_ops_examples() is used to load predefined examples from opstool.

load_ops_examples("ArchBridge")

Get the model data from the current domain. Of course, you can also run your own model code before instantiating GetFEMdata. Parameter results_dir is used to specify the directory where the output file is saved.

ModelData = GetFEMdata(results_dir="opstool_output")
ModelData.get_model_data(save_file="ModelData.hdf5")

Model data saved in opstool_output/ModelData.hdf5 !

Instantiating visualization class OpsVisPlotly.

opsv = OpsVisPlotly(point_size=2, line_width=3, colors_dict=None, theme="plotly",
                    color_map="jet", on_notebook=True, results_dir="opstool_output")

Display the geometric information of the model, Input parameter explanation see class method model_vis().

Tip

When show_node_label and show_ele_label True, rendering speed is relatively slow. Therefore, it is recommended not to use them, but to use mouse hover to display related information.

opsv.model_vis(input_file="ModelData.hdf5",
               show_node_label=False, show_ele_label=False,
               show_local_crd=True, label_size=8,
               show_outline=True,
               opacity=1.0,
               save_html=None)

Display Eigen Analysis

Note

Before performing the eigenvalue analysis, you need to ensure that the OpenSeesPy model is correct and that the mass is set.

Obtain the first 15 orders of modal data.

ModelData.get_eigen_data(mode_tag=15, solver="-genBandArpack",
                         save_file='EigenData.hdf5')

Eigen data saved in opstool_output/EigenData.hdf5 !

Visualize eigenvalue modes. When you set a two-element list for the argument mode_tags and subplots is False, the method eigen_vis() returns a slide-style plot.

opsv.eigen_vis(input_file='EigenData.hdf5',
               mode_tags=[1, 9], subplots=False,
               alpha=None, show_outline=False,
               show_origin=False, opacity=1.0,
               show_face_line=False, save_html=None)

Of course, subplots set to True will return a multi-sub plot.

opsv.eigen_vis(input_file='EigenData.hdf5',
               mode_tags=[2, 11], subplots=True,
               alpha=None, show_outline=False,
               show_origin=False, opacity=1.0,
               show_face_line=False, save_html=None)

You can also create an html animation by eigen_anim().

opsv.eigen_anim(input_file='EigenData.hdf5',
                mode_tag=5, alpha=None, show_outline=False,
                opacity=1, framerate=3,
                show_face_line=True,
                save_html=None)

Display Node Deformation

First we use the function gen_grav_load() to generate the gravity load.

from opstool.preprocessing import gen_grav_load
gen_grav_load(ts_tag=1, pattern_tag=1,
              factor=-9.81, direction="Z")

Next, we save the node response data in each analysis step. I chose to do this to strip the visualization from the analysis, and you are free to tweak the analysis parameters, which is very helpful for debugging the convergence of the model!

Note that you must enter parameters analysis_tag and num_steps, the former to identify the different analysis types and the latter to tell get_node_resp_step() how many steps to output the data after. In addition, it is also used get_frame_resp_step() here to obtain the response data of the frame elements.

If you cannot determine num_steps (eg adaptive step analysis), you can also use parameter total_time, which is the final time of the analysis. You can specify one of the parameters num_steps and total_time. If both are used, it depends on which one arrives first.

Nsteps = 10
ops.wipeAnalysis()
ops.system('BandGeneral')
ops.constraints('Transformation')
ops.numberer('RCM')
ops.test('NormDispIncr', 1.0e-12, 10, 3)
ops.algorithm('Newton')
ops.integrator('LoadControl', 1 / Nsteps)
ops.analysis('Static')

# Important!!!! to clear step data in previous analysis case!
ModelData.reset_steps_state()
# start analysis loop
for i in range(Nsteps):
    ok = ops.analyze(1)
    ModelData.get_node_resp_step(num_steps=Nsteps,
                                 total_time=10000000000,
                                 stop_cond=False,
                                 save_file="NodeRespStepData-1.hdf5",
                                 model_update=False)
    ModelData.get_frame_resp_step(num_steps=Nsteps,
                                  total_time=10000000000,
                                  stop_cond=False,
                                  save_file="BeamRespStepData-1.hdf5")

Node response data saved in opstool_output/NodeRespStepData-1.hdf5!
Frame elements response data saved in opstool_output/BeamRespStepData-1.hdf5!

Visualize node displacement by method deform_vis(). Of course, velocity and acceleration are also optional, just change response to “vel” or “accel”.

opsv.deform_vis(input_file="NodeRespStepData-1.hdf5",
                slider=True,
                response="disp", alpha=None,
                show_outline=False, show_origin=True,
                show_face_line=False, opacity=1,
                save_html=None,
                model_update=False)

Create an html animation by deform_anim().

opsv.deform_anim(input_file="NodeRespStepData-1.hdf5",
                 response="disp", alpha=None,
                 show_outline=False,
                 show_face_line=False, opacity=1,
                 save_html=None,
                 model_update=False)

Display Frame Element Response

When saving the node response data, we also save the response of the frame elemengts by method get_frame_resp_step(), which you can visualize in the following way.

opsv.frame_resp_vis(input_file="BeamRespStepData-1.hdf5",
                    ele_tags=None,
                    slider=True,
                    response="My",
                    show_values=False,
                    alpha=None,
                    opacity=1,
                    save_html=None)