From 77fa2728642f2e58efd08ec59fda10a7813d907e Mon Sep 17 00:00:00 2001
From: Karim Mache <k.mache@fz-juelich.de>
Date: Sat, 29 Mar 2025 00:45:26 +0100
Subject: [PATCH] creat requirements file
---
.history/README_20250329004405.md | 35 +++++++++++++++++++++++++++++++
.history/README_20250329004519.md | 35 +++++++++++++++++++++++++++++++
README.md | 23 ++++++++++----------
TOAR-classifier_v2.ipynb | 2 +-
4 files changed, 82 insertions(+), 13 deletions(-)
create mode 100644 .history/README_20250329004405.md
create mode 100644 .history/README_20250329004519.md
diff --git a/.history/README_20250329004405.md b/.history/README_20250329004405.md
new file mode 100644
index 0000000..ece6864
--- /dev/null
+++ b/.history/README_20250329004405.md
@@ -0,0 +1,35 @@
+## TOAR-classifier v2: A data-driven classification tool for global air quality stations
+This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments.
+<img src="./figures/toar_classifier_v2.png" alt="My image" with=100>
+
+### Files
+- `data` is the folder containing all the data used in this work, including the predictions of station categories from the Machine Learning (ML) model.
+- `figures` contains all the figures.
+- `TOAR-classifier_v2.ipynb` is the notebook containing the code.
+- `requirements.txt` contains all the necessary packages.
+
+### Run the Code
+
+**Note:** This has been tested on Ubuntu 24.04.
+
+1. Install Python 3 if not already installed (most Linux systems have Python pre-installed).
+2. Install Jupyter Notebook:
+ - `pip install notebook` (for Jupyter Notebook) or
+ - `pip install jupyterlab` (for JupyterLab).
+
+clone the project by running the following
+`git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git`
+
+change directory to ml_toar_station_classification, `cd ml_toar_station_classification`
+
+creat virtual environment `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient
+
+activate the created venv `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"`
+
+#### Install required package
+open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2`
+
+Install all the required packages for the project by uncommenting the first cell in the notebook and running the cell
+
+Run the code cell by cell.
+
diff --git a/.history/README_20250329004519.md b/.history/README_20250329004519.md
new file mode 100644
index 0000000..1566ce9
--- /dev/null
+++ b/.history/README_20250329004519.md
@@ -0,0 +1,35 @@
+## TOAR-classifier v2: A data-driven classification tool for global air quality stations
+This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments.
+<img src="./figures/toar_classifier_v2.png" alt="My image" with=100>
+
+### Files
+- `data` is the folder containing all the data used in this work, including the predictions of station categories from the Machine Learning (ML) model.
+- `figures` contains all the figures.
+- `TOAR-classifier_v2.ipynb` is the notebook containing the code.
+- `requirements.txt` contains all the necessary packages.
+
+### Run the Code
+
+**Note:** This has been tested on Ubuntu 24.04.
+
+1. Install Python 3 if not already installed (most Linux systems have Python pre-installed).
+2. Install Jupyter Notebook:
+ - `pip install notebook` (for Jupyter Notebook) or
+ - `pip install jupyterlab` (for JupyterLab).
+
+3. clone the project by running the following
+`git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git`
+
+change directory to ml_toar_station_classification, `cd ml_toar_station_classification`
+
+creat virtual environment `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient
+
+activate the created venv `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"`
+
+#### Install required package
+open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2`
+
+Install all the required packages for the project by uncommenting the first cell in the notebook and running the cell
+
+Run the code cell by cell.
+
diff --git a/README.md b/README.md
index a18dd29..1566ce9 100644
--- a/README.md
+++ b/README.md
@@ -3,22 +3,21 @@ This study develops a machine learning approach to classify 23,974 air quality m
<img src="./figures/toar_classifier_v2.png" alt="My image" with=100>
### Files
-`data` is the folder contening all data use in this work, including the predictions of station cotegories form Machine Learning (ML) model.
+- `data` is the folder containing all the data used in this work, including the predictions of station categories from the Machine Learning (ML) model.
+- `figures` contains all the figures.
+- `TOAR-classifier_v2.ipynb` is the notebook containing the code.
+- `requirements.txt` contains all the necessary packages.
-`figures` contains all figures
+### Run the Code
-`TOAR-classifier_v2.ipynb` is the notebook contening the code
+**Note:** This has been tested on Ubuntu 24.04.
-`requirements.txt` contains all neccessary packages.
+1. Install Python 3 if not already installed (most Linux systems have Python pre-installed).
+2. Install Jupyter Notebook:
+ - `pip install notebook` (for Jupyter Notebook) or
+ - `pip install jupyterlab` (for JupyterLab).
-### Run code
-NB: This has been test on Ubuntu 24.04
-
-Install if needed python3, most Linux system already have python install
-
-Install jupyter notebook `pip install notebook` or jupyter lab `pip install jupyterlab`
-
-clone the project by running the following
+3. clone the project by running the following
`git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git`
change directory to ml_toar_station_classification, `cd ml_toar_station_classification`
diff --git a/TOAR-classifier_v2.ipynb b/TOAR-classifier_v2.ipynb
index 9341b97..fc6b9bd 100755
--- a/TOAR-classifier_v2.ipynb
+++ b/TOAR-classifier_v2.ipynb
@@ -24,7 +24,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 58,
"id": "8666a040",
"metadata": {
"tags": []
--
GitLab