How to plot contour of plotly 3D Mesh?

📊 Plotly Python
6

Hey @numam,

Here’s an updated version that should be more consistent. Instead of transforming back into 3D space via a neural network, we can simply take the indices of the detected edge, and use those indices to obtain the points in 3D space.

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image1145×1150 105 KB
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image819×1041 54.3 KB

Let me know how it goes for you! Here’s the code:

import plotly.graph_objs as go
import numpy as np
import pandas as pd
from sklearn.decomposition import PCA
import alphashape


def generate_contour_sample(x, y, z, alpha=0.0, n_components=2, plot=True):
    X = np.array([x, y, z]).T

    # do PCA to make 3D data planar
    pca = PCA(n_components=n_components)
    pca.fit(X)
    X_transformed = pca.transform(X)

    # generate boundary points in PCA space
    alpha_shape = alphashape.alphashape(X_transformed, alpha)
    alpha_shape_points = alpha_shape.boundary.coords
    x_boundary = np.array(alpha_shape_points.xy[0])
    y_boundary = np.array(alpha_shape_points.xy[1])
    bound_mat = np.array([x_boundary, y_boundary]).T

    # get the indices for the boundary
    inds = []
    for coord in bound_mat:
        # return index where the values are close
        ind_match = np.where(np.all(np.isclose(coord, X_transformed, atol=1e-3), axis=1))
        if ind_match:
            inds.append(ind_match)
    inds = np.array(inds).flatten()

    if plot:
        fig = go.Figure(
            data=[
                go.Scatter3d(x=x, y=y, z=z, name='Input Data', mode='markers'),
                go.Scatter3d(x=X_transformed[:, 0], y=X_transformed[:, 1], z=50 + np.zeros(len(X_transformed[:, 0])),
                             name='Points in 2-component PCA'),
                go.Scatter3d(x=x_boundary, y=y_boundary, z=75 + np.zeros(len(x_boundary)), name='Edge in PCA space'),
                go.Scatter3d(x=x[inds], y=y[inds], z=z[inds],
                             name='Reconstructed Edge')

            ],
            layout=go.Layout(
                scene=dict(
                    aspectmode='data',
                ),
                template='plotly_dark'
            )
        )

        fig.show()

    return np.array([x[inds], y[inds], z[inds]]).T


if __name__ == '__main__':
    data = pd.read_csv('ROIvertices.csv', header=None)

    contour_pts = generate_contour_sample(data.iloc[:, 0], data.iloc[:, 1], data.iloc[:, 2], alpha=0.7, plot=True)