File: integrate-data.py

package info (click to toggle)
python-pyvista 0.44.1-11
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 159,804 kB
  • sloc: python: 72,164; sh: 118; makefile: 68
file content (93 lines) | stat: -rw-r--r-- 3,051 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
"""
.. _integrate_example:

Integrate Data
~~~~~~~~~~~~~~

Integrate data over a surface using the
:func:`pyvista.DataSetFilters.integrate_data` filter.

"""

from __future__ import annotations

import pyvista
from pyvista import examples

# %%
# This example calculates the total flow rate and average velocity inside a
# blood vessel.  The boundary object is only used for plotting the shape of
# the dataset geometry.  The inlet surface is generated by slicing the domain.
# Fluid flowing into the domain is in the negative z-direction, so
# a new array, ``normal_velocity``, is created.

dataset = examples.download_blood_vessels()
boundary = dataset.decimate_boundary().extract_all_edges()
inlet_surface = dataset.slice('z', origin=(0, 0, 182))
inlet_surface["normal_velocity"] = -1 * inlet_surface["velocity"][:, 2]

# %%
# The velocity in the inlet is shown.

plotter = pyvista.Plotter()
plotter.add_mesh(boundary, color="grey", opacity=0.25)
plotter.add_mesh(
    inlet_surface,
    scalars="normal_velocity",
    component=2,
    scalar_bar_args=dict(vertical=True, title_font_size=16),
    lighting=False,
)
plotter.add_axes()
plotter.camera_position = [(10, 9.5, -43), (87.0, 73.5, 123.0), (-0.5, -0.7, 0.5)]
plotter.show()

# %%
# The total flow rate is calculated using the
# :func:`pyvista.DataSetFilters.integrate_data` filter.  Note that the data
# is a :class:`pyvista.UnstructuredGrid` object with only 1 point and 1 cell.
integrated_data = inlet_surface.integrate_data()
integrated_data

# %%
# Each array in ``integrated_data`` stores the integrated data.
integrated_data["normal_velocity"]

# %%
# An additional ``Area`` or ``Volume`` array is added.
print(f"Original arrays: {inlet_surface.array_names}")
new_arrays = [name for name in integrated_data.array_names if name not in inlet_surface.array_names]
print(f"New arrays      : {new_arrays}")

# %%
# Display the total flow rate, area of inlet surface, and average velocity.
total_flow_rate = integrated_data["normal_velocity"][0]
area = integrated_data["Area"][0]
average_velocity = total_flow_rate / area
print(f"Total flow rate : {total_flow_rate:.1f}")
print(f"Area            : {area:.0f}")
print(f"Average velocity: {average_velocity:.3f}")


# %%
# Volume Integration
# ~~~~~~~~~~~~~~~~~~
# You can also integrate over a volume. Here, we effectively sum the cell and
# point data across the entire volume. You can use this to compute mean values
# by dividing by the volume of the dataset.
#
# Note that the calculated volume is the same as :attr:`pyvista.DataSet.volume`.
#
# Also note that the center of the dataset is the "point" of the integrated
# volume.

integrated_volume = dataset.integrate_data()
center = integrated_volume.points[0]
volume = integrated_volume['Volume'][0]
mean_density = integrated_volume['density'][0] / volume
mean_velocity = integrated_volume['velocity'][0] / volume

print(f"Center          : {center}")
print(f"Volume          : {volume:.0f}")
print(f"Mean density    : {mean_density:.4f}")
print(f"Mean velocity   : {mean_velocity}")