Using the NS noise estimate for the IE

webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer_unittest.cc

 /*
  *  Copyright (c) 2015 The WebRTC project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */
 
@@ skipping 81 matching lines @@
     enh_.reset(new IntelligibilityEnhancer(config_));
   }
 
   bool CheckUpdate(VarianceArray::StepType step_type) {
     config_.sample_rate_hz = kSampleRate;
     config_.var_type = step_type;
     enh_.reset(new IntelligibilityEnhancer(config_));
     float* clear_cursor = &clear_data_[0];
     float* noise_cursor = &noise_data_[0];
     for (int i = 0; i < kSamples; i += kFragmentSize) {
-      enh_->AnalyzeCaptureAudio(&noise_cursor, kSampleRate, kNumChannels);
       enh_->ProcessRenderAudio(&clear_cursor, kSampleRate, kNumChannels);
       clear_cursor += kFragmentSize;
       noise_cursor += kFragmentSize;
     }
     for (int i = 0; i < kSamples; i++) {
       if (std::fabs(clear_data_[i] - orig_data_[i]) > kMaxTestError) {
         return true;
       }
     }
     return false;
@@ skipping 34 matching lines @@
   }
 }
 
 // Tests ERB bank creation, comparing against matlab output.
 TEST_F(IntelligibilityEnhancerTest, TestErbCreation) {
   ASSERT_EQ(arraysize(kTestCenterFreqs), enh_->bank_size_);
   for (size_t i = 0; i < enh_->bank_size_; ++i) {
     EXPECT_NEAR(kTestCenterFreqs[i], enh_->center_freqs_[i], kMaxTestError);
     ASSERT_EQ(arraysize(kTestFilterBank[0]), enh_->freqs_);
     for (size_t j = 0; j < enh_->freqs_; ++j) {
-      EXPECT_NEAR(kTestFilterBank[i][j], enh_->filter_bank_[i][j],
+      EXPECT_NEAR(kTestFilterBank[i][j], enh_->render_filter_bank_[i][j],
                   kMaxTestError);
     }
   }
 }
 
 // Tests analytic solution for optimal gains, comparing
 // against matlab output.
 TEST_F(IntelligibilityEnhancerTest, TestSolveForGains) {
   ASSERT_EQ(kTestStartFreq, enh_->start_freq_);
   vector<float> sols(enh_->bank_size_);
@@ skipping 16 matching lines @@
     EXPECT_NEAR(kTestNonZeroVarLambdaTop[i], sols[i], kMaxTestError);
   }
   lambda = -1.0;
   enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]);
   for (size_t i = 0; i < enh_->bank_size_; i++) {
     EXPECT_NEAR(kTestZeroVar[i], sols[i], kMaxTestError);
   }
 }
 
 }  // namespace webrtc