def _debug_bcg(self):
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._X,
self._B, self._tol,
self._maxiter)
self._final_X, self._final_R, self._residual_hist = bcg_solver_obj.bcg_variant_one_run(
0)
print(self._residual_hist)
def _db_bcg_least_square (self):
""" """
m = 32
self._BB_m = np.random.random( ( self._mat.shape[0],m) )
self._BX_m = np.ones ( (self._mat.shape[1],m) )
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_m, self._BB_m, self._tol, self._maxiter)
self._final_X_bcg, self._final_R_bcg, self._residual_hist_bcg = bcg_solver_obj.bcg_variant_one_run(0)
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._BX_m, self._BB_m, self._tol, self._maxiter)
self._final_X_bcg_lstsq, self._final_R_bcg_lstsq, self._residual_hist_bcg_lstsq = bcg_solver_obj.bcg_variant_lstsq_run(0)
plot_worker = Presenter()
residual_list = [self._residual_hist_bcg, self._residual_hist_bcg_lstsq]
legend_list = ["bcg","bcg_lstsq"]
color_list = ["r","k"]
plot_worker.instant_plot_y_log10(residual_list, "test", "#iteration", "$\\mathbf{log_{10}\\frac{||x_1||}{||b_1||}}$", legend_list, color_list)
def _debug_bcg(self):
bcg_solver_obj = NativeBlockConjugateGradient(self._mat, self._X, self._B, self._tol, self._maxiter)
self._final_X, self._final_R, self._residual_hist = bcg_solver_obj.bcg_variant_one_run(0)
print(self._residual_hist)