code: def from_matrix_vector(matrix, vector):
      """Combine a matrix and vector into a homogeneous transform.
  
      Combine a rotation matrix and translation vector into a transform
      in homogeneous coordinates.
  
      Parameters
      ----------
      matrix : numpy.ndarray
          An (N, N) array representing the rotation matrix.
  
      vector : numpy.ndarray
          A (1, N) array representing the translation.
  
      Returns
      -------
      xform: numpy.ndarray
          An (N+1, N+1) transform matrix.
  
      See Also
      --------
      nilearn.resampling.to_matrix_vector
  
      """
      nin, nout = matrix.shape
      t = np.zeros((nin + 1, nout + 1), matrix.dtype)
      t[0:nin, 0:nout] = matrix
      t[nin, nout] = 1.0
      t[0:nin, nout] = vector
      return t
  
file_path: nilearn/nilearn/image/resampling.py
imports: import numbers
  import warnings
  import numpy
  from scipy import linalg
  from scipy.ndimage import affine_transform, find_objects
  from ..None import _utils
  from .._utils import stringify_path
  from .._utils.niimg import _get_data
  from .image import copy_img, crop_img
label_desc: Use image node_id 2 for calling a global function with example usage: from_matrix_vector(matrix, vector) and returns: t