Merge pull request #54 from TUDelft-CITG/feature/openclsim-core-update

Replace core objects with openclsim

.github/workflows/azure-static-web-apps-happy-bush-0c5d10603.yml

@@ -32,7 +32,8 @@ jobs:
         run: |
           python -m pip install --upgrade pip setuptools==57.5
           # install gdal separate
-          pip install wheel gdal==3.0.4
+          pip install wheel gdal==$(gdal-config --version)
+          pip install -e .
           pip install -e .[testing]
       - name: Copy examples and build the book
         run: |

Dockerfile

@@ -1,12 +1,17 @@
 # Start with pyramid app image
 FROM continuumio/miniconda3
+ENV DEBIAN_FRONTEND noninteractive
+RUN apt update
+RUN apt install -y build-essential python3-dev
 
 # Install conda stuff first
 # install gdal library
-RUN conda install nomkl pyproj
-RUN conda install -c conda-forge gdal nomkl
+RUN conda install -c conda-forge mamba nomkl
+RUN mamba install -c conda-forge pyproj
+RUN mamba install -c conda-forge gdal
 
 WORKDIR /OpenTNSim
+ENV PROJ_DATA=/opt/conda/share/proj
 ADD . /OpenTNSim
 RUN pip install --upgrade pip
 # Install the application

README.md

@@ -31,7 +31,6 @@ To also install the extra dependencies used for testing you can use:
 pip install opentnsim[testing]
 ```
 
-
 This is the preferred method to install OpenTNSim, as it will always install the most recent stable release.
 
 If you don not have [pip](https://pip.pypa.io) installed, this [Python installation guide](http://docs.python-guide.org/en/latest/starting/installation/) can guide you through the process.
@@ -72,3 +71,5 @@ Based on the examples and docs a book can be generated using the commands `make
 Code quality is checked using sonarcloud. You can see results on the [sonarcloud](https://sonarcloud.io/project/overview?id=TUDelft-CITG_OpenTNSim) website. For now we have disabled coverage and duplication checks. These can be enabled when we include coverage measurements and reduce duplication by optimizing the tests.
 
 
+## OpenCLSim 
+OpenTNSim makes use of the [OpenCLSim](https://github.com/TUDelft-CITG/OpenCLSim) code. Both packages are maintained by the same team of developers. There are some differences between packages (e.g. in logging approaches), but you can use them together. We are working towards further integrating these two software packages.

environment.yml

@@ -15,7 +15,7 @@ dependencies:
   - requests=2
   - scipy=1
   - setuptools
-  - shapely=1.7
+  - shapely>=2
   - geos=3
   - tqdm=4
   - jupyter=1

notebooks/Example 01 - Defining a basic graph.ipynb

@@ -153,7 +153,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -200,7 +200,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -214,7 +214,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.6"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,

notebooks/Example 02 - Defining a basic vessel.ipynb

@@ -111,16 +111,18 @@
     {
      "data": {
       "text/plain": [
-       "{'env': None,\n",
-       " 'log': {'Message': [], 'Timestamp': [], 'Value': [], 'Geometry': []},\n",
+       "{'v': None,\n",
+       " 'env': None,\n",
+       " 'logbook': [],\n",
        " 'route': None,\n",
+       " 'position_on_route': 0,\n",
        " 'complete_path': None,\n",
-       " 'geometry': <shapely.geometry.point.Point at 0x1635ca5d220>,\n",
+       " 'geometry': <POINT (0 0)>,\n",
        " 'node': None,\n",
-       " 'v': None,\n",
-       " 'edge_functions': [],\n",
+       " 'wgs84': Geod(ellps='WGS84'),\n",
+       " 'on_pass_edge_functions': [],\n",
        " 'name': 'Vessel 1',\n",
-       " 'id': '1551cc85-bf57-11ec-bf5f-8c04ba0c9d8f'}"
+       " 'id': '1ec24ec6-bbda-4f94-b445-849ff7eaed49'}"
       ]
      },
      "execution_count": 5,
@@ -182,7 +184,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -196,7 +198,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.6"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,