code: def make_canvas(icon_batch, coordinates, grid_size):
      """Given a list of images and their coordinates, places them on a white canvas."""
  
      grid_shape = (grid_size, grid_size)
      icon_shape = icon_batch[0].shape
      canvas = np.ones((*grid_shape, *icon_shape))
  
      for icon, (x, y) in zip(icon_batch, coordinates):
          canvas[x, y] = icon
  
      return np.hstack(np.hstack(canvas))
  
file_path: lucid/lucid/recipes/activation_atlas/main.py
imports: from enum import Enum, auto
  import numpy
  from lucid.modelzoo.aligned_activations import push_activations, NUMBER_OF_AVAILABLE_SAMPLES, layer_inverse_covariance
  from lucid.recipes.activation_atlas.layout import aligned_umap
  from lucid.recipes.activation_atlas.render import render_icons
  from more_itertools import chunked
label_desc: Use image node_id 5 for calling a global function with example usage: make_canvas(icon_batch, coordinates, grid_size) and returns: np