# Copyright (C) 2020 - 2026 ANSYS, Inc. and/or its affiliates. # SPDX-License-Identifier: MIT # # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # _order: 4 """ .. _ref_tutorials_plot_graph: Plot a graph using matplotlib ============================== This tutorial explains how to plot a graph with data from DPF using `matplotlib `_. The current :class:`DpfPlotter` module does not support graph plots. Instead, use the `matplotlib `_ library to plot graphs with PyDPF-Core. There is a large range of graphs you can plot. Here, we showcase: - :ref:`A graph of a result along a path ` - :ref:`A graph of transient data ` """ ############################################################################### # .. _ref_graph_result_space: # # Result along a path # -------------------- # # In this section, we plot the norm of the displacement along a custom path # represented by a # :class:`Line`. We first get the data of interest, # create a custom ``Line`` geometry for the path, map the result on the path, and # finally create a 2D graph. # # Extract the data # ^^^^^^^^^^^^^^^^^ # # First, extract the data from a result file. # For this tutorial we use a case available in the # :mod:`examples` module. import matplotlib.pyplot as plt import ansys.dpf.core as dpf from ansys.dpf.core import examples, geometry as geo, operators as ops result_file_path_1 = examples.find_static_rst() model_1 = dpf.Model(data_sources=result_file_path_1) ############################################################################### # Extract the result of interest — the norm of the displacement field at the # last step. disp_results_1 = model_1.results.displacement.eval() norm_disp = ops.math.norm_fc(fields_container=disp_results_1).eval() ############################################################################### # Define the path # ^^^^^^^^^^^^^^^^ # # Create a path as a # :class:`Line` passing through the diagonal of # the mesh. line_1 = geo.Line(coordinates=[[0.0, 0.06, 0.0], [0.03, 0.03, 0.03]], n_points=50) line_1.plot(mesh=model_1.metadata.meshed_region) ############################################################################### # Map the data on the path # ^^^^^^^^^^^^^^^^^^^^^^^^^ # # Map the displacement norm field to the path using the # :class:`on_coordinates` # mapping operator. This operator interpolates field values at given node coordinates, # using element shape functions. # # It takes a :class:`FieldsContainer` # of data, a 3D vector :class:`Field` of coordinates to # interpolate at, and an optional # :class:`MeshedRegion` to use for element # shape functions if the first field in the data does not have an associated meshed # support. disp_norm_on_path_fc: dpf.FieldsContainer = ops.mapping.on_coordinates( fields_container=norm_disp, coordinates=line_1.mesh.nodes.coordinates_field, ).eval() disp_norm_on_path: dpf.Field = disp_norm_on_path_fc[0] print(disp_norm_on_path) ############################################################################### # Plot the graph # ^^^^^^^^^^^^^^ # # Plot the norm of the displacement field along the path using matplotlib. # # Use the # :py:attr:`Line.path` property to get the # parametric coordinates of the nodes along the line for the X-axis. # The values in the displacement norm field are in the same order as the parametric # coordinates because the mapping operator orders output data the same as the input # coordinates. line_coordinates = line_1.path plt.plot(line_coordinates, disp_norm_on_path.data) plt.xlabel("Position on path") plt.ylabel("Displacement norm") plt.title("Displacement norm along the path") plt.show() ############################################################################### # .. _ref_graph_result_time: # # Transient data # --------------- # # In this section, we plot the minimum and maximum displacement norm over time for a # transient analysis. For more information about using PyDPF-Core with a transient # analysis, see the :ref:`static_transient_examples` examples. # # We create data for the Y-axis, format the time information for the X-axis, and # create a 2D graph using both. # # Prepare data # ^^^^^^^^^^^^^ # # Load a transient case from the # :mod:`examples` module. result_file_path_2 = examples.download_transient_result() model_2 = dpf.Model(data_sources=result_file_path_2) # Check the model is transient via its TimeFreqSupport print(model_2.metadata.time_freq_support) ############################################################################### # Extract the displacement field for every time step. disp_results_2: dpf.FieldsContainer = model_2.results.displacement.on_all_time_freqs.eval() ############################################################################### # Get the minimum and maximum of the norm of the displacement at each time step # using the # :class:`min_max_fc` operator. min_max_op = ops.min_max.min_max_fc(fields_container=ops.math.norm_fc(disp_results_2)) max_disp: dpf.Field = min_max_op.outputs.field_max() print(max_disp) min_disp: dpf.Field = min_max_op.outputs.field_min() print(min_disp) ############################################################################### # Prepare time values # ^^^^^^^^^^^^^^^^^^^^ # # The time or frequency information associated to DPF objects is stored in # :class:`TimeFreqSupport` objects. # # Use the ``TimeFreqSupport`` of a ``Field`` with location ``time_freq`` to retrieve # the time or frequency values associated to the entities in its scoping. time_steps_1: dpf.Field = disp_results_2.time_freq_support.time_frequencies print(time_steps_1) # Extract the data of the Field as a plain array time_data = time_steps_1.data print(time_data) ############################################################################### # Plot the graph # ^^^^^^^^^^^^^^ # # Use the ``unit`` property of the fields to properly label the axes. plt.plot(time_data, max_disp.data, "r", label="Max") plt.plot(time_data, min_disp.data, "b", label="Min") plt.xlabel(f"Time ({time_steps_1.unit})") plt.ylabel(f"Displacement ({max_disp.unit})") plt.legend() plt.show()