code: def test_PCANoMask_nostandardize(data_dict):
      nimages = data_dict["nimages"]
      ntotal = nimages - 1
      ncomp = 5
      p = pca_image(
          data_dict["fmridata"], ncomp=ncomp, standardize=False
      )
      assert _rank(p) == ntotal
      assert p["basis_vectors over t"].shape == (nimages, ntotal)
      assert p["basis_projections"].shape == data_dict["mask"].shape + (
          ncomp,
      )
      assert p["pcnt_var"].shape == (ntotal,)
      assert_almost_equal(p["pcnt_var"].sum(), 100.0)
      assert p["basis_projections"].axes.coord_names == (
          "i",
          "j",
          "k",
          "PCA components",
      )
      assert_array_equal(
          p["basis_projections"].coordmap.affine,
          data_dict["fmridata"].coordmap.affine,
      )
  
imports: import numpy
  import pytest
  from nibabel.affines import from_matvec
  from numpy.testing import assert_almost_equal, assert_array_equal
  from ....core.api import AffineTransform, Image
  from ....core.api import CoordinateSystem
  from ....core.image.image import rollimg
  from ....core.reference.coordinate_map import AxisError, drop_io_dim
  from ....core.reference.coordinate_map import product
  from ....io.api import load_image
  from ....testing import funcfile
  from ..pca import pca
  from ..pca import pca_image
  from .test_pca import res2pos1
label_desc: Use image node_id 7 for calling a global function with example usage: test_PCANoMask_nostandardize(data_dict) without return types