| # |
| # Copyright 2022 Google LLC |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| import numpy as np |
| |
| import lc3 |
| import tables as T, appendix_c as C |
| |
| ### ------------------------------------------------------------------------ ### |
| |
| class EnergyBand: |
| |
| def __init__(self, dt, sr): |
| |
| self.dt = dt |
| self.I = T.I[dt][sr] |
| |
| def compute(self, x): |
| |
| e = [ np.mean(np.square(x[self.I[i]:self.I[i+1]])) |
| for i in range(len(self.I)-1) ] |
| |
| e_lo = np.sum(e[:len(e) - [2, 3, 4, 2][self.dt]]) |
| e_hi = np.sum(e[len(e) - [2, 3, 4, 2][self.dt]:]) |
| |
| return e, (e_hi > 30*e_lo) |
| |
| ### ------------------------------------------------------------------------ ### |
| |
| def check_unit(rng, dt, sr): |
| |
| ns = T.NS[dt][sr] |
| ok = True |
| |
| nrg = EnergyBand(dt, sr) |
| |
| x = (2 * rng.random(T.NS[dt][sr])) - 1 |
| |
| (e , nn ) = nrg.compute(x) |
| (e_c, nn_c) = lc3.energy_compute(dt, sr, x) |
| ok = ok and np.amax(np.abs(e_c - e)) < 1e-5 and nn_c == nn |
| |
| x[15*ns//16:] *= 1e2 |
| |
| (e , nn ) = nrg.compute(x) |
| (e_c, nn_c) = lc3.energy_compute(dt, sr, x) |
| ok = ok and np.amax(np.abs(e_c - e)) < 1e-3 and nn_c == nn |
| |
| return ok |
| |
| def check_appendix_c(dt): |
| |
| i0 = dt - T.DT_7M5 |
| sr = T.SRATE_16K |
| |
| ok = True |
| |
| e = lc3.energy_compute(dt, sr, C.X[i0][0])[0] |
| ok = ok and np.amax(np.abs(1 - e/C.E_B[i0][0])) < 1e-6 |
| |
| e = lc3.energy_compute(dt, sr, C.X[i0][1])[0] |
| ok = ok and np.amax(np.abs(1 - e/C.E_B[i0][1])) < 1e-6 |
| |
| return ok |
| |
| def check(): |
| |
| rng = np.random.default_rng(1234) |
| |
| ok = True |
| |
| for dt in range(T.NUM_DT): |
| for sr in range(T.SRATE_8K, T.SRATE_48K + 1): |
| ok = ok and check_unit(rng, dt, sr) |
| |
| for dt in ( T.DT_2M5, T.DT_5M, T.DT_10M ): |
| for sr in ( T.SRATE_48K_HR, T.SRATE_96K_HR ): |
| ok = ok and check_unit(rng, dt, sr) |
| |
| for dt in ( T.DT_7M5, T.DT_10M ): |
| ok = ok and check_appendix_c(dt) |
| |
| return ok |
| |
| ### ------------------------------------------------------------------------ ### |