Point Cloud Alignment with PCA
Project description
PCA2
Point Cloud Alignment with PCA
Install
Create conda environment (Recommended)
git pull https://github.com/lukemshepherd/PCA_2.git
cd PCA2
conda env create -f environment.yml
conda activate PCA2
Install from PyPi
pip install PCA2
Or: Install from GitHub
cd PCA2
pip install -e .
How to use
Fill me in please! Don't forget code examples:
Set custom filter level (optional)
bone.filter_level = 0.2
Load the data that you want to use
tibia_f2 = bone.from_matlab_path(matlab_file='data/tibia_f2.mat')
tibia_f1 = bone.from_matlab_path(matlab_file='data/phantom_tibia_f1.mat')
Set custom colour for bone (optional)
tibia_f1.default_color = (0.8, 0.3, 0)
Rotate the bone
rotate(tibia_f1, tibia_f2)
0.17458532149354633 no invert
0.5815521223920518 no invert
1.9141791241147516e-16 no invert
Plotting the rotation
Plotting with mayavi is very similar to matplotplib where you build a scene and call it with show()
You can plot bones by calling the .plot() method and then mlab.show()
tibia_f1.plot()
tibia_f2.plot()
mlab.show()
Table of angles
df_angles(tibia_f1, tibia_f2, name='tibia')
0.6019718433476905 no invert
2.6184557666721346e-16 no invert
0.6019718433476903 no invert
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
tibia f2: pc1 | tibia f2: pc2 | tibia f2: pc3 | |
---|---|---|---|
tibia f1: pc1 | 0.601972 | NaN | NaN |
tibia f1: pc2 | NaN | 2.618456e-16 | NaN |
tibia f1: pc3 | NaN | NaN | 0.601972 |
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