some cosmetics

bagustris · Aug 22, 2024 · 2c737be · 2c737be
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -475,9 +475,9 @@ Version 0.66.3
 
 Version 0.66.2
 --------------
-* enabled data-pathes with quotes 
+* enabled data-pacthes with quotes 
 * enabled missing category labels
-* used tgdm for progress display
+* used tqdm for progress display
 
 Version 0.66.1
 --------------

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -17,7 +17,7 @@ The preferred way to contribute to nkululeko is to fork the [main repository](ht
 	cd nkululeko
 	```
 
-	-	Using HTTPS&#x3A;
+	-	Using HTTPS:
 
 	```bash
 	git clone https://github.com/YourLogin/nkululeko.git
@@ -64,7 +64,7 @@ The preferred way to contribute to nkululeko is to fork the [main repository](ht
 	git push -u origin my-feature
 	```
 
-9.	Finally, go to the web page of the your nkululeko fork repo, and click 'Pull request' button to send your changes to the maintainers to review.
+9.	Finally, go to the web page of your nkululeko fork repo, and click 'Pull request' button to send your changes to the maintainers to review.
 
 Remarks
 -------
@@ -84,11 +84,11 @@ It is recommended to check that your contribution complies with the following ru
 Filing bugs
 -----------
 
-we use Github issues to track all bugs and feature requests. In the case of coming across a bug, having a question or a feature suggestion etc. please feel free to open an issue. 
+We use Github issues to track all bugs and feature requests. In the case of coming across a bug, having a question or a feature suggestion etc. please feel free to open an issue. 
 
 Please check that your issue complies with the following rules before submitting:
 
--	Verify that your issue is not being currently addressed by other in[issues](https://github.com/felixbur/nkululeko/issues) or [pull requests](https://github.com/felixbur/nkululeko/pulls).
+-	Verify that your issue is not being currently addressed by in other [issues](https://github.com/felixbur/nkululeko/issues) or [pull requests](https://github.com/felixbur/nkululeko/pulls).
 
 -	Please ensure all code snippets and error messages are formatted appropriately. See [Creating and highlighting code blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks).
 

diff --git a/README.md b/README.md
@@ -160,7 +160,7 @@ All of them take *--config <my_config.ini>* as an argument.
   * *configurations*: which experiments to combine
   * *--method* (optional): majority_voting, mean (default), max, sum, uncertainty, uncertainty_weighted, confidence_weighted, performance_weighted  
   * *--threshold*: uncertainty threshold (1.0 means no threshold)
-  * *--weightes*: weights for performance_weighted method (could be from previous UAR, ACC)
+  * *--weights*: weights for performance_weighted method (could be from previous UAR, ACC)
   * *--outfile* (optional): name of CSV file for output (default: ensemble_result.csv)
   * *--no_labels* (optional): indicate that no ground truth is given 
 * **nkululeko.multidb**: do [multiple experiments](http://blog.syntheticspeech.de/2024/01/02/nkululeko-compare-several-databases/), comparing several databases cross and in itself
@@ -176,14 +176,11 @@ All of them take *--config <my_config.ini>* as an argument.
 * **nkululeko.predict**: [predict features](http://blog.syntheticspeech.de/2023/08/16/nkululeko-how-to-predict-labels-for-your-data-from-existing-models-and-check-them/) like SNR, MOS, arousal/valence, age/gender, with DNN models
 * **nkululeko.segment**: [segment a database](http://blog.syntheticspeech.de/2023/07/14/nkululeko-segmenting-a-database/) based on VAD (voice activity detection)
 * **nkululeko.resample**: check on all [sampling rates and change](http://blog.syntheticspeech.de/2023/08/31/how-to-fix-different-sampling-rates-in-a-dataset-with-nkululeko/) to 16kHz 
-* **nkululeko.nkuluflag**: a convenient module to specify configuration parameters on the command-line.
-  * usage: nkuluflag.py [-h] [--config CONFIG] [--data [DATA ...]] [--label [LABEL ...]] [--tuning_params [TUNING_PARAMS ...]] [--layers [LAYERS ...]] [--model MODEL] [--feat FEAT] [--set SET]
-                    [--with_os WITH_OS] [--target TARGET] [--epochs EPOCHS] [--runs RUNS] [--learning_rate LEARNING_RATE] [--drop DROP]
-
-
-
-
+* **nkululeko.nkuluflag**: a convenient module to specify configuration parameters on the command-line. Usage:
 
+  ```bash
+  $ python -m nkululeko.nkuluflag.py [-h] [--config CONFIG] [--data [DATA ...]] [--label [LABEL ...]] [--tuning_params [TUNING_PARAMS ...]] [--layers [LAYERS ...]] [--model MODEL] [--feat FEAT] [--set SET] [--with_os WITH_OS] [--target TARGET] [--epochs EPOCHS] [--runs RUNS] [--learning_rate LEARNING_RATE] [--drop DROP]
+  ```
 
 There's my [blog](http://blog.syntheticspeech.de/?s=nkululeko) with tutorials:
 * [Introduction](http://blog.syntheticspeech.de/2021/08/04/machine-learning-experiment-framework/)

diff --git a/docs/source/how_to.md b/docs/source/how_to.md
@@ -7,28 +7,30 @@ starting without programming experience).
 This post is meant to help you with setting up your first experiment,
 based on the Berlin Emodb.
 
-1) Set up Python
+0) Set up Python
 
 It's written in python, so first you have to set up a Python environment.
 It is recommended to use Linux-based systems for easiness, but it should work on Windows as well.
-The current version of nkululeko is tested with Python 3.8.5.
+Python is pre-installed on most Linux systems, but you might want to install a virtual environment to keep your system clean.
+The current version of nkululeko is tested with Python 3.9.
 
-2) Get a database
-
-Load the Berlin emodb database to some location on you harddrive, as
-discussed in [this post](http://blog.syntheticspeech.de/2021/08/10/get-all-information-from-emodb/). 
-I will refer to the location as "emodb root" from now on. You can also follow [Hello World page](hello_world_aud.md).
-
-3) Install Nkululeko
+1) Install Nkululeko
 
 Inside your virtual environment, run:
 
     pip install nkululeko
 
 This should install nkululeko and all required modules. It takes a long
-time and a lot of space, when done intially.
+time and a lot of space, when done initially.
+
+2) Get a database
+
+Load the Berlin emodb database to some location on you harddrive, as
+discussed in [this post](http://blog.syntheticspeech.de/2021/08/10/get-all-information-from-emodb/). 
+I will refer to the location as "emodb root" from now on. You can also follow [Hello World page](hello_world_aud.md).
+
 
-5) Adapt the INI file
+3) Adapt the INI file
 
 Use your favourite editor, e.g., Visual Studio code and edit the file
 that defines your experiment. You might start with this demo sample. You
@@ -42,13 +44,13 @@ this:
 
 An overview on all nkululeko options is listed in [INI file](ini_file).
 
-6) Run the experiment
+4) Run the experiment
 
 Inside a shell type (or use VSC) and start the process with:
 
     python -m nkululeko.nkululeko --config exp_emodb.ini
 
-7)  Inspect the results
+5)  Inspect the results
 
 If all goes well, the program should start by extracting opensmile
 features, and, if you\'re done, you should be able to inspect the

diff --git a/nkululeko/utils/util.py b/nkululeko/utils/util.py
@@ -175,7 +175,7 @@ def get_exp_dir(self):
         """Get the experiment directory."""
         root = os.path.join(self.config["EXP"]["root"], "")
         name = self.config["EXP"]["name"]
-        dir_name = f"{root}{name}"
+        dir_name = f"{root}/{name}"
         audeer.mkdir(dir_name)
         return dir_name