class_docstr: A Formula is a model for a mean in a regression model.
  
  It is often given by a sequence of sympy expressions, with the mean
  model being the sum of each term multiplied by a linear regression
  coefficient.
  
  The expressions may depend on additional Symbol instances, giving a
  non-linear regression model.
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docstr: Parameters
  ----------
  seq : sequence of ``sympy.Basic``
  char : str, optional
      character for regression coefficient
docstr_tok: ["Parameters","--","--","--","--","--","seq",":","sequence","of","``","sympy.Basic","``","char",":","str",",","optional","character","for","regression","coefficient"]
code: def __init__(self, seq, char="b"):
      """
      Parameters
      ----------
      seq : sequence of ``sympy.Basic``
      char : str, optional
          character for regression coefficient
      """
      self._terms = np.asarray(seq)
      self._counter = 0
      self.char = char
  
imports: import itertools
  import warnings
  from string import ascii_letters, digits
  import numpy
  import sympy
  from scipy.linalg import pinv
  from sympy import Dummy, default_sort_key
  from sympy.utilities.lambdify import implemented_function, lambdify
  from nipy.algorithms.utils.matrices import full_rank, matrix_rank
  from nipy.utils import VisibleDeprecationWarning, _NoValue
label_desc: Use image node_id 1 to create a new Formula object  with example: obj = Formula(seq, char)