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# This is a CamiTK python action
#
# Testing MeshComponent in python: compute the mesh barycenter and use matplotlib
# to show a 3D plots of a sample of the points and the barycenter.
import numpy as np
import camitk
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # Needed to activate 3D projection
from PySide2.QtWidgets import *
def init(self:camitk.Action):
camitk.info("CamiTK version: " + camitk.__version__)
# # camitk.Application.open(camitk.Core.get_test_data_dir() + "/brain.mha")
# camitk.Application.open(camitk.Core.getTestDataDir() + "/sinus_skin.vtk")
# for c in camitk.Application.getTopLevelComponents():
# print(c.getName()) # print will print to CamiTK console without timestamp, level and location in code
def compute_barycenter(self:camitk.Action):
points = self.getTargets()[-1].getPointSetAsNumpy()
barycenter = np.mean(points, axis=0)
self.setParameterValue("Barycenter", "QVector3D(" + str(barycenter[0]) + "," + str(barycenter[1]) + "," + str(barycenter[2]) +")")
return points, barycenter
def targetDefined(self:camitk.Action):
compute_barycenter(self)
def subsample_points(points, max_points=1000):
n = points.shape[0]
if n <= max_points:
return points # nothing to do
indices = np.random.choice(n, size=max_points, replace=False)
return points[indices]
def process(self:camitk.Action):
points, barycenter = compute_barycenter(self)
# 3D matplot is too slow for big mesh, only takes 1 every 100 points
subsampled = subsample_points(points)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.get_current_fig_manager().set_window_title(self.getTargets()[-1].getName())
# Plot all points
ax.scatter(subsampled[:,0], subsampled[:,1], subsampled[:,2], c='blue', marker='o', label='Points')
# Plot barycenter
ax.scatter(barycenter[0], barycenter[1], barycenter[2],
c='red', marker='^', s=100, label='Barycenter')
# Labels
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
# Legend
ax.legend()
# Equal aspect ratio (optional but looks better)
ax.set_box_aspect([np.ptp(subsampled[:,0]), np.ptp(subsampled[:,1]), np.ptp(subsampled[:,2])])
plt.show()
msg = QMessageBox()
msg.setIcon(QMessageBox.Information)
# setting message for Message Box
msg.setText("You can now check the plot...")
# setting Message box window title
msg.setWindowTitle("Plot Information")
# declaring buttons on Message Box
msg.setStandardButtons(QMessageBox.Ok | QMessageBox.Cancel)
msg.exec_()
return
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