class_docstr: This class is intended for the ResDNN Histology Network model.
class_docstr_tok: ["This","class","is","intended","for","the","ResDNN","Histology","Network","model","."]
docstr: Predict fODF (as SH) from input raw DWI signal (as SH)
  
  Parameters
  ----------
  x_test : np.ndarray
      Array of size (N, M) where M is
      ``(sh_order + 1) * (sh_order + 2) / 2``.
      N should not be too big as to limit memory usage.
  
  Returns
  -------
  np.ndarray (N, M)
      Predicted fODF (as SH)
docstr_tok: ["Predict","fODF","(","as","SH",")","from","input","raw","DWI","signal","(","as","SH",")","Parameters","--","--","--","--","--","x_test",":","np.ndarray","Array","of","size","(","N",",","M",")","where","M","is","``","(","sh_order","+","1",")","*","(","sh_order","+","2",")","\/","2","``",".","N","should","not","be","too","big","as","to","limit","memory","usage",".","Returns","--","--","--","-","np.ndarray","(","N",",","M",")","Predicted","fODF","(","as","SH",")"]
code: def __predict(self, x_test):
      r"""
      Predict fODF (as SH) from input raw DWI signal (as SH)
  
      Parameters
      ----------
      x_test : np.ndarray
          Array of size (N, M) where M is
          ``(sh_order + 1) * (sh_order + 2) / 2``.
          N should not be too big as to limit memory usage.
  
      Returns
      -------
      np.ndarray (N, M)
          Predicted fODF (as SH)
      """
  
      if x_test.shape[-1] != self.sh_size:
          raise ValueError(
              "Expected input for the provided model weights "
              "do not match the declared model ({})".format(
                  self.sh_size
              )
          )
  
      return self.model.predict(x_test)
  
file_path: dipy/dipy/nn/histo_resdnn.py
imports: import logging
  import numpy
  from dipy.core.gradients import unique_bvals_magnitude, get_bval_indices
  from dipy.core.sphere import HemiSphere
  from dipy.data import get_sphere, get_fnames
  from dipy.reconst.shm import sf_to_sh, sh_to_sf, sph_harm_ind_list
  from dipy.testing.decorators import doctest_skip_parser
  from dipy.utils.optpkg import optional_package
  from dipy.nn.utils import set_logger_level
label_desc: Use image node_id 4 for calling the HistoResDNN obj's underlying member method code with example usage: obj.__predict(x_test) and returns: self