103     def compute_lpc_coeffs(self, bw, f, x):  argument
110         e = [ sum(x[S[s]:S[s+1]] ** 2) for s in range(3) ]
113             c = [ np.dot(x[S[s]:S[s+1]-k], x[S[s]+k:S[s+1]])
163     def filtering(self, st, x, rc_order, rc):  argument
165         y = np.empty(len(x))
167         for i in range(len(x)):
169             xi = x[i]
183     def run(self, x, bw, nn_flag, nbytes):  argument
186         y = x.copy()
195             (pred_gain, a) = self.compute_lpc_coeffs(bw, f, x)
217                     fstate, x[i0:i1], rc_order, rc_q)
242     def filtering(self, st, x, rc_order, rc):  argument
244         y = x.copy()
246         for i in range(len(x)):
248             xi = x[i] - rc[rc_order-1] * st[rc_order-1]
280     def run(self, x, bw):  argument
283         y = x.copy()
295                     fstate, x[i0:i1], rc_order, rc)
310         x = rng.random(T.NE[dt][bw]) * 1e2
311         x = pow(x, .5 + i/5)
316                 y = analysis.run(x, bw, nn_flag, nbytes)
317                 (y_c, data_c) = lc3.tns_analyze(dt, bw, nn_flag, nbytes, x)
340         x = rng.random(T.NE[dt][bw]) * 1e2
346         y = synthesis.run(x, bw)
347         y_c = lc3.tns_synthesize(dt, bw, synthesis.get_data(), x)
377         (x, side) = lc3.tns_analyze(dt, sr, False, C.NBYTES[dt], C.X_S[dt][i])
382         ok = ok and np.amax(np.abs(x - C.X_F[dt][i])) < 1e-3
401         x = C.X_HAT_Q[dt][i] * (10 ** (g_int / 28))
403         x = lc3.tns_synthesize(dt, sr, side, x)
404         ok = ok and np.amax(np.abs(x - C.X_HAT_TNS[dt][i])) < 1e-3
418     x = C.X_HAT_F_48K_10M
419     x = lc3.tns_synthesize(dt, sr, side, x)
420     ok = ok and np.amax(np.abs(x - C.X_HAT_TNS_48K_10M)) < 1e-3