code: def test_figarch_no_phi_beta(setup):
      figarch = FIGARCH(p=0, q=0, power=0.7)
  
      sv = figarch.starting_values(setup.resids)
      assert_equal(sv.shape[0], figarch.num_params)
  
      backcast = figarch.backcast(setup.resids)
      assert_allclose(
          np.sqrt(backcast) ** 0.7, figarch.backcast_transform(backcast)
      )
  
      bounds = figarch.bounds(setup.resids)
      assert_equal(
          bounds[0], (0.0, 10.0 * np.mean(np.abs(setup.resids) ** 0.7))
      )
      assert_allclose(
          np.array(bounds[1]), np.array([0.0, 1 - EPS_HALF])
      )
      assert len(bounds) == figarch.num_params
  
      a, b = figarch.constraints()
      a_target = np.zeros((3, 2))
      a_target[0, 0] = 1
      a_target[1, 1] = 1
      a_target[2, 1] = -1
      b_target = np.array([0.0, 0.0, -1.0])
      assert_array_equal(a, a_target)
      assert_array_equal(b, b_target)
  
imports: import types
  from typing import NamedTuple
  import warnings
  import numpy
  from numpy.random import RandomState
  from numpy.testing import assert_allclose, assert_almost_equal, assert_array_equal, assert_equal
  import pytest
  from scipy.special import gamma, gammaln
  from arch.univariate import ZeroMean
  from arch.univariate.distribution import Normal, SkewStudent, StudentsT
  import arch.univariate.recursions_python
  from arch.univariate.volatility import APARCH, ARCH, EGARCH, FIGARCH, GARCH, HARCH, ConstantVariance, EWMAVariance, FixedVariance, MIDASHyperbolic, RiskMetrics2006
  from arch.utility.exceptions import InitialValueWarning
label_desc: Use image node_id 29 for calling a global function with example usage: test_figarch_no_phi_beta(setup) without return types