APM QA refactoring: render stream support, echo path simulation, new export engine

webrtc/modules/audio_processing/test/py_quality_assessment/README.md

 # APM Quality Assessment tool
 
 Python wrapper of `audioproc_f` with which quality assessment can be
 automatized. The tool allows to simulate different noise conditions, input
 signals, APM configurations and it computes different scores.
 Once the scores are computed, the results can be easily exported to an HTML page
 which allows to listen to the APM input and output signals and also the
 reference one used for evaluation.
 
 ## Dependencies
 
  - OS: Linux
  - Python 2.7
- - Python libraries: numpy, scipy, pydub (0.17.0+)
+ - Python libraries: numpy, scipy, pydub (0.17.0+), pandas (0.20.1+)
  - It is recommended that a dedicated Python environment is used
    - install `virtualenv`
    - `$ sudo apt-get install python-virtualenv`
    - setup a new Python environment (e.g., `my_env`)
    - `$ cd ~ && virtualenv my_env`
    - activate the new Python environment
    - `$ source ~/my_env/bin/activate`
    - add dependcies via `pip`
-   - `(my_env)$ pip install numpy pydub scipy`
+   - `(my_env)$ pip install numpy pydub scipy pandas`
  - PolqaOem64 (see http://www.polqa.info/)
     - Tested with POLQA Library v1.180 / P863 v2.400
  - Aachen Impulse Response (AIR) Database
     - Download https://www2.iks.rwth-aachen.de/air/air_database_release_1_4.zip
  - Input probing signals and noise tracks (you can make your own dataset - *1)
 
 ## Build
 
  - Compile WebRTC
  - Go to `out/Default/py_quality_assessment` and check that
@@ skipping 27 matching lines @@
  - Run `apm_quality_assessment.sh`
  - The script will end by opening the browser and showing ALL the computed
    scores
 
 ## Usage (export reports)
 
 Showing all the results at once can be confusing. You therefore may want to
 export separate reports. In this case, you can use the
 `apm_quality_assessment_export.py` script as follows:
 
- - Set --output_dir to the same value used in `apm_quality_assessment.sh`
+ - Set `--output_dir, -o` to the same value used in `apm_quality_assessment.sh`
  - Use regular expressions to select/filter out scores by
     - APM configurations: `--config_names, -c`
-    - probing signals: `--input_names, -i`
+    - capture signals: `--capture_names, -i`
+    - render signals: `--render_names, -r`
+    - echo simulator: `--echo_simulator_names, -e`
     - test data generators: `--test_data_generators, -t`
-    - scores: `--eval_scores, -e`
+    - scores: `--eval_scores, -s`
  - Assign a suffix to the report name using `-f <suffix>`
 
 For instance:
 
 ```
 $ ./apm_quality_assessment-export.py \
-  -o ~/data/apm_quality_assessment \
-  -e \(polqa\) \
-  -n \(echo\) \
+  -o output/ \
   -c "(^default$)|(.*AE.*)" \
+  -t \(white_noise\) \
+  -s \(polqa\) \
   -f echo
 ```
 
 ## Troubleshooting
 
 The input wav file must be:
   - sampled at a sample rate that is a multiple of 100 (required by POLQA)
   - in the 16 bit format (required by `audioproc_f`)
-  -  encoded in the Microsoft WAV signed 16 bit PCM format (Audacity default
-     when exporting)
+  - encoded in the Microsoft WAV signed 16 bit PCM format (Audacity default
+    when exporting)
 
 Depending on the license, the POLQA tool may take “breaks” as a way to limit the
 throughput. When this happens, the APM Quality Assessment tool is slowed down.
 For more details about this limitation, check Section 10.9.1 in the POLQA manual
 v.1.18.
 
 In case of issues with the POLQA score computation, check
 `py_quality_assessment/eval_scores.py` and adapt
 `PolqaScore._parse_output_file()`.
 The code can be also fixed directly into the build directory (namely,
 `out/Default/py_quality_assessment/eval_scores.py`).