Step 6.2 Visualization ABM model
0. Initialization
0.1. Importing all necessary libraries
import os
import topogenesis as tg
import pyvista as pv
import trimesh as tm
import pandas as pd
import numpy as np
import networkx as nx
from sklearn.cluster import KMeans
import scipy as sp
import pickle
import matplotlib.pyplot as plt
from matplotlib import cm
np.random.seed(0)
0.2. Specifying the inputs
agn_num = 22
n_frames = 800
0.3. Load the high resolution envelope lattice and preferences
lattice_path = os.path.relpath('../Data/dynamic output/voxelized_envelope_cut.csv')
avail_lattice = tg.lattice_from_csv(lattice_path)
init_avail_lattice = tg.to_lattice(np.copy(avail_lattice), avail_lattice)
agn_prefs = pd.read_csv("../Data/raw data/Programme_pref.csv")
agn_prefs
0.4. Load the animation frames/lattices
frames = []
for i in range(n_frames):
csv_path = os.path.relpath('../Data/dynamic output/abm_animation/abm_f_'+ f'{i:03}' + '.csv')
frames.append(tg.lattice_from_csv(csv_path))
1. Visualization
1.1. Visusalize a specific agent
agn = 13
p = pv.Plotter(notebook=True)
base_lattice = frames[0]
# Set the grid dimensions: shape + 1 because we want to inject our values on the CELL data
grid = pv.UniformGrid()
grid.dimensions = np.array(base_lattice.shape) + 1
# The bottom left corner of the data set
grid.origin = base_lattice.minbound - base_lattice.unit * 0.5
# These are the cell sizes along each axis
grid.spacing = base_lattice.unit
# adding the boundingbox wireframe
#p.add_mesh(grid.outline(), color="grey", label="Domain")
# adding the availability lattice
init_avail_lattice.fast_vis(p)
# adding axes
p.add_axes()
p.show_bounds(grid="back", location="back", color="#aaaaaa")
def create_mesh(value):
f = int(value)
lattice = frames[f]
# Add the data values to the cell data
grid.cell_arrays["Agents"] = lattice.flatten(order="F").astype(int) # Flatten the array!
# filtering the voxels
threshed = grid.threshold([agn-0.1, agn+0.9])
# adding the voxels
p.add_mesh(threshed, name='sphere', show_edges=True, opacity=1.0, show_scalar_bar=False)
return
p.add_slider_widget(create_mesh, [0, n_frames], title='Time', value=0, event_type="always", style="classic")
p.show(use_ipyvtk=True)
1.2. Visualize all agents
p = pv.Plotter(notebook=True)
base_lattice = frames[0]
# Set the grid dimensions: shape + 1 because we want to inject our values on the CELL data
grid = pv.UniformGrid()
grid.dimensions = np.array(base_lattice.shape) + 1
# The bottom left corner of the data set
grid.origin = base_lattice.minbound - base_lattice.unit * 0.5
# These are the cell sizes along each axis
grid.spacing = base_lattice.unit
# adding the boundingbox wireframe
p.add_mesh(grid.outline(), color="grey", label="Domain")
# adding the availability lattice
#init_avail_lattice.fast_vis(p)
# adding axes
#p.add_axes()
#p.show_bounds(grid="back", location="back", color="#aaaaaa")
# making space list with index for the sargs
space_list = agn_prefs.get('space_name')
# formatting for the sarg annotation
space_list = space_list.to_dict()
sargs = dict(
shadow = True,
n_labels = 0,
italic = False,
fmt=" %.0f",
font_family="arial",
height = 0.6,
vertical = True,
position_x = 1,
position_y = 0.75)
def create_mesh(value):
f = int(value)
lattice = frames[f]
# Add the data values to the cell data
grid.cell_arrays["Agents"] = lattice.flatten(order="F").astype(int) # Flatten the array!
# filtering the voxels
threshed = grid.threshold([-0.1, agn_num - 0.9])
# adding the voxels
p.add_mesh(threshed, name='sphere', show_edges=True, opacity=1.0, show_scalar_bar=True, annotations = space_list, scalar_bar_args=sargs, cmap= "tab20")
return
p.add_slider_widget(create_mesh, [0, n_frames], title='Time', value=0, event_type="always", style="classic")
#for i in range(160):
# create_mesh(i * 5)
# p.screenshot("growth_" + str(i * 5), transparent_background=True)
p.show(use_ipyvtk=True)