Fix the stereo support in IntelligibilityEnhancer

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 195 matching lines @@
 
 class IntelligibilityEnhancerTest : public ::testing::Test {
  protected:
   IntelligibilityEnhancerTest()
       : clear_data_(kSamples), noise_data_(kSamples), orig_data_(kSamples) {
     enh_.reset(new IntelligibilityEnhancer(kSampleRate, kNumChannels));
   }
 
   bool CheckUpdate() {
     enh_.reset(new IntelligibilityEnhancer(kSampleRate, kNumChannels));
-    float* clear_cursor = &clear_data_[0];
-    float* noise_cursor = &noise_data_[0];
+    float* clear_cursor = clear_data_.data();
+    float* noise_cursor = noise_data_.data();
     for (int i = 0; i < kSamples; i += kFragmentSize) {
       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;
       }
     }
@@ skipping 38 matching lines @@
 // Tests analytic solution for optimal gains, comparing
 // against matlab output.
 TEST_F(IntelligibilityEnhancerTest, TestSolveForGains) {
   ASSERT_EQ(kTestStartFreq, enh_->start_freq_);
   std::vector<float> sols(enh_->bank_size_);
   float lambda = -0.001f;
   for (size_t i = 0; i < enh_->bank_size_; i++) {
     enh_->filtered_clear_pow_[i] = 0.f;
     enh_->filtered_noise_pow_[i] = 0.f;
   }
-  enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]);
+  enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, sols.data());
   for (size_t i = 0; i < enh_->bank_size_; i++) {
     EXPECT_NEAR(kTestZeroVar, sols[i], kMaxTestError);
   }
   for (size_t i = 0; i < enh_->bank_size_; i++) {
     enh_->filtered_clear_pow_[i] = static_cast<float>(i + 1);
     enh_->filtered_noise_pow_[i] = static_cast<float>(enh_->bank_size_ - i);
   }
-  enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]);
+  enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, sols.data());
   for (size_t i = 0; i < enh_->bank_size_; i++) {
     EXPECT_NEAR(kTestNonZeroVarLambdaTop[i], sols[i], kMaxTestError);
   }
   lambda = -1.f;
-  enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]);
+  enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, sols.data());
   for (size_t i = 0; i < enh_->bank_size_; i++) {
     EXPECT_NEAR(kTestNonZeroVarLambdaTop[i], sols[i], kMaxTestError);
   }
 }
 
 }  // namespace webrtc