From 9e5c9ce8e60b3f1d127c96e4c80829147f6923f9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jo=C3=A3o=20Carvalho?= <joao.carvalho@ua.pt>
Date: Tue, 1 Mar 2022 15:56:11 +0000
Subject: [PATCH] first complete version

added readme, sample data script and renamed some files
---
 README.md                            | 59 ++++++++++++++++++++++++++++
 classification/classify_from_nrcs.py |  5 +--
 download_and_test_sample.sh          | 15 +++++++
 main.py => fcmclassifier.py          |  0
 4 files changed, 76 insertions(+), 3 deletions(-)
 create mode 100644 README.md
 create mode 100644 download_and_test_sample.sh
 rename main.py => fcmclassifier.py (100%)

diff --git a/README.md b/README.md
new file mode 100644
index 0000000..6654d28
--- /dev/null
+++ b/README.md
@@ -0,0 +1,59 @@
+## Classification of 1D-signals using Extended-Alphabet Finite-Context models
+
+This package provides an easy to use solution to perform classification on uni-dimensional signals, using an approach that relies on Extended-Alphabet Finite-Context Models. The code was developed from scratch by myself for research purposes, but feel free to reproduce it for whatever you like. Just make sure to cite the papers mentioned on the [citations](#CITATION) section.
+
+The code was developed with the Linux system in mind and should work out of the box in either Ubuntu machines or WSL (Windows Subsystem for Linux) -- either WSL1 or WSL2.
+
+
+
+
+## INSTALLATION
+To install the package, all you need to do is run these commands on a Linux terminal (or WSL):
+```bash
+# Download repo
+git clone https://github.com/joaomrcarvalho/fcmclassifier.git
+
+# Enter repo
+cd fcmclassifier
+
+# Install requirements
+python -m pip install -r requirements.txt
+```
+All dependencies will be automatically installed.
+
+
+## USAGE
+The program was developed using the "click" package, so you can use the command
+
+```bash
+python fcmclassifier.py --help
+```
+
+to get information about the parameters expected.
+
+## EXAMPLE
+A simple example is provided in download_and_test_sample.sh. This script will make sure you have the zip package, download a sample database, unzip it and attempt to run the classifier on its' data (folder "sample_data"), producing a folder named "quantized_data" with the quantized data, as well as the file "results_nrc.csv" with the computer NRC values. 
+
+To run this script, navigate to the main directory of the proect and type the following command:
+```bash
+sh download_and_test_sample.sh
+```
+
+
+## CITATION
+This is part of the research I have done during my PhD and there are a couple of papers related with the subject. Please cite the following two papers if you use this project:
+
+* João M. Carvalho, Susana Brás, Diogo Pratas, Jacqueline Ferreira, Sandra C. Soares and Armando J. Pinho. "**Extended-Alphabet Finite-Context Models**", Pattern Recognition Letters Volume 112, 1 September 2018, pp. 49-55. doi: [10.1016/J.PATREC.2018.05.026](https://www.sciencedirect.com/science/article/abs/pii/S0167865518302095?via%3Dihub)
+
+
+*    João M. Carvalho, Susana Brás and Armando J. Pinho. "**Compression-Based Classification of ECG Using First-Order Derivatives**" on Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer International Publishing. 2019 pp. 27--36
+doi: [10.1007/978-3-030-16447-8_3](https://link.springer.com/chapter/10.1007/978-3-030-16447-8_3)
+
+
+## ISSUES
+Please let me know if you find any issue, at https://github.com/joaomrcarvalho/fcmclassifier/issues
+
+## LICENSE
+GPL v3.
+
+For more information, please visit http://www.gnu.org/licenses/gpl-3.0.html
diff --git a/classification/classify_from_nrcs.py b/classification/classify_from_nrcs.py
index 2ff86f5..f807d19 100644
--- a/classification/classify_from_nrcs.py
+++ b/classification/classify_from_nrcs.py
@@ -6,10 +6,9 @@ def classify(nrc_csv):
 
     df_nrc = pd.read_csv(nrc_csv)
     print(df_nrc)
-
-    classes = df_nrc.columns[1:-2]
+    print()
 
     y_true = df_nrc['Target']
     y_pred = df_nrc['Guess']
-
+    
     compute_and_print_metrics(y_true, y_pred)
diff --git a/download_and_test_sample.sh b/download_and_test_sample.sh
new file mode 100644
index 0000000..29aa54c
--- /dev/null
+++ b/download_and_test_sample.sh
@@ -0,0 +1,15 @@
+# make sure the zip package is installed
+# it isn't, by default, on WSL
+# this will ask you for your sudo password
+# if you're not an admin on the computer you're using, delete this line
+sudo apt install zip
+
+# download the sample data
+wget https://joaomrcarvalho.github.io/datasets/fcmclassifier_sample_data.zip
+
+# unzip it to sample_data folder
+unzip fcmclassifier_sample_data.zip
+
+# output quantization files for "quantized_data" folder
+# and attempt to perform classification
+python fcmclassifier.py sample_data quantized_data -a 17 -k 25 -d 3
\ No newline at end of file
diff --git a/main.py b/fcmclassifier.py
similarity index 100%
rename from main.py
rename to fcmclassifier.py