code: def noisy_scale_coords(
      coords, random_state, max_coord=10.0, noise=0.0001
  ):
      expansion = max_coord / np.abs(coords).max()
      coords = (coords * expansion).astype(np.float32)
      return coords + random_state.normal(
          scale=noise, size=coords.shape
      ).astype(np.float32)
  
imports: from __future__ import print_function
  import locale
  from warnings import warn
  import time
  from scipy.optimize import curve_fit
  from sklearn.base import BaseEstimator
  from sklearn.utils import check_random_state, check_array
  from sklearn.utils.validation import check_is_fitted
  from sklearn.metrics import pairwise_distances
  from sklearn.preprocessing import normalize
  from sklearn.neighbors import KDTree
  from sklearn.decomposition import PCA, TruncatedSVD
  import numpy
  import scipy.sparse
  from scipy.sparse import tril, triu
  import scipy.sparse.csgraph
  import numba
  import umap.distances
  import umap.sparse
  from umap.utils import submatrix, ts, csr_unique, fast_knn_indices
  from umap.spectral import spectral_layout, tswspectral_layout
  from umap.layouts import optimize_layout_euclidean, optimize_layout_generic, optimize_layout_inverse
  from pynndescent import NNDescent
  from pynndescent.distances import named_distances
  from pynndescent.sparse import sparse_named_distances
label_desc: Use image node_id 18 for calling a global function with example usage: noisy_scale_coords(coords, random_state, max_coord, noise) and returns: unknown