Functions

Kopjes toevoegen

Import ``` python linenums="1" import os import topogenesis as tg import pyvista as pv import trimesh as tm import numpy as np import networkx as nx from scipy.interpolate import RegularGridInterpolator import matplotlib.pyplot as plt

convert mesh to pv_mesh

def tri_to_pv(tri_mesh): faces = np.pad(tri_mesh.faces, ((0, 0),(1,0)), 'constant', constant_values=3) pv_mesh = pv.PolyData(tri_mesh.vertices, faces) return pv_mesh

def visualize(object_to_visualize, title, name_save): # load the context mesh context_path = os.path.relpath('../data/immediate_context.obj') context_mesh = tm.load(context_path)

pv.set_plot_theme("document")

# initiating the plotter
p = pv.Plotter(notebook=True)

# Create the spatial reference
grid = pv.UniformGrid()

# Set the grid dimensions: shape because we want to inject our values
grid.dimensions = object_to_visualize.shape
# The bottom left corner of the data set
grid.origin = object_to_visualize.minbound
# These are the cell sizes along each axis
grid.spacing = object_to_visualize.unit

# Add the data values to the cell data
grid.point_arrays[title] = object_to_visualize.flatten(order="F")  # Flatten the Lattice

# adding the meshes
p.add_mesh(tri_to_pv(context_mesh), opacity=0.1, style='wireframe')

# adding the volume
opacity = np.array([0,0.6,0.6,0.6,0.6,0.6,0.6])
p.add_volume(grid, cmap="coolwarm",opacity=opacity, shade=False)

p.show(screenshot=name_save)

def save_image(object_to_visualize, title, name_save): # load the context mesh context_path = os.path.relpath('../data/immediate_context.obj') context_mesh = tm.load(context_path)

pv.set_plot_theme("document")

# initiating the plotter
p = pv.Plotter(notebook=True)

# Create the spatial reference
grid = pv.UniformGrid()

# Set the grid dimensions: shape because we want to inject our values
grid.dimensions = object_to_visualize.shape
# The bottom left corner of the data set
grid.origin = object_to_visualize.minbound
# These are the cell sizes along each axis
grid.spacing = object_to_visualize.unit

# Add the data values to the cell data
grid.point_arrays[title] = object_to_visualize.flatten(order="F")  # Flatten the Lattice

# adding the meshes
p.add_mesh(tri_to_pv(context_mesh), opacity=0.1, style='wireframe')

# adding the volume
opacity = np.array([0,0.6,0.6,0.6,0.6,0.6,0.6])
p.add_volume(grid, cmap="coolwarm",opacity=opacity, shade=False)

p.screenshot(name_save)

def save_image_lattice(object_to_visualize, title, name_save, program): pv.set_plot_theme("document") p = pv.Plotter(notebook=True)

# Set the grid dimensions: shape + 1 because we want to inject our values on the CELL data
grid = pv.UniformGrid()
grid.dimensions = np.array(object_to_visualize.shape) + 1
# The bottom left corner of the data set
grid.origin = object_to_visualize.minbound - object_to_visualize.unit * 0.5
# These are the cell sizes along each axis
grid.spacing = object_to_visualize.unit

# adding the boundingbox wireframe
p.add_mesh(grid.outline(), color="grey", label="Domain")

# adding axes
p.add_axes()
p.show_bounds(grid="back", location="back", color="#777777")

# Add the data values to the cell data
grid.cell_arrays[title] = object_to_visualize.flatten(order="F").astype(int)  # Flatten the array!
# filtering the voxels
agn_num = len(program)
threshed = grid.threshold([-0.1, agn_num - 0.9])
# adding the voxels
p.add_mesh(threshed, show_edges=True, opacity=1.0, show_scalar_bar=False)

p.screenshot(name_save)
```