code: import itertools
  
  import numpy as np
  
  from solvers.grid_solver import GridSolver
  from solvers.math import interpolate_signal, ls_fit
  from solvers.tests.base_test_case import BaseTestCase
  from solvers.tests.correction_models import linear_correction
  
  
  class TestGridSolver(BaseTestCase):
      offset_candidates = np.arange(-3, 3, 0.1)
      slope_candidates = np.arange(-0.03, 0.03, 0.001)
      candidates = np.array(list(itertools.product(slope_candidates, offset_candidates)))
  
      def setUp(self):
          super().setUp()
          self.solver = GridSolver(x=self.x,
                                   pure_components=self.pure_components,
                                   candidates=self.candidates,
                                   correction_model=linear_correction,
                                   fit_function=ls_fit)
  
      def test_no_x_axis_errors_should_pass(self) -> None:
          self.run_test(self.mixture_signal)
  
      def test_offset_error_should_pass(self) -> None:
          x_distorted = self.x + 2
          signal = interpolate_signal(self.mixture_signal, self.x, x_distorted, 0, 0)
          self.run_test(signal)
  
      def test_slope_error_should_pass(self) -> None:
          x_distorted = 1.01 * self.x
          signal = interpolate_signal(self.mixture_signal, self.x, x_distorted, 0, 0)
          self.run_test(signal)
  
      def test_slope_and_offset_error_should_pass(self) -> None:
          x_distorted = 1.01 * self.x - 2
          signal = interpolate_signal(self.mixture_signal, self.x, x_distorted, 0, 0)
          self.run_test(signal)
  
apis: numpy.arange