diff --git a/docs/tutorial/basic_concepts.ipynb b/docs/tutorial/basic_concepts.ipynb
index d68c6dc8c..2afae5e70 100644
--- a/docs/tutorial/basic_concepts.ipynb
+++ b/docs/tutorial/basic_concepts.ipynb
@@ -6,6 +6,29 @@
    "source": [
     "# Basic pathpyG Concepts\n",
     "\n",
+    "## Prerequisites\n",
+    "\n",
+    "First, we need to set up our Python environment that has PyTorch, PyTorch Geometric and PathpyG installed. Depending on where you are executing this notebook, this might already be (partially) done. E.g. Google Colab has PyTorch installed by default so we only need to install the remaining dependencies. The DevContainer that is part of our GitHub Repository on the other hand already has all of the necessary dependencies installed. \n",
+    "\n",
+    "In the following, we install the packages for usage in Google Colab using Jupyter magic commands. For other environments comment in or out the commands as necessary. For more details on how to install `pathpyG` especially if you want to install it with GPU-support, we refer to our [documentation](https://www.pathpy.net/dev/getting_started/). Note that `%%capture` discards the full output of the cell to not clutter this tutorial with unnecessary installation details. If you want to print the output, you can comment `%%capture` out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "# !pip install torch\n",
+    "!pip install torch_geometric\n",
+    "!pip install git+https://github.com/pathpy/pathpyG.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Motivation and Learning Objectives\n",
     "\n",
     "This first step of our multi-stage introductory tutorial introduces the key concepts of `pathpyG`. While `pathpyG` targets GPU-accelerated analysis and learning in time series data on temporal graphs, it is also a great tool to represent, analyze and visualize static graphs. For this, it provides a `Graph` class that is implemented based on the `torch_geometric.data.Data` object, which has the advantage that we can directly apply `pyG` transforms and use the underlying data for graph learning tasks.\n",
@@ -17,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -627,7 +650,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -636,7 +659,7 @@
        "Data(edge_index=[2, 3], num_nodes=3)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/docs/tutorial/dbgnn.ipynb b/docs/tutorial/dbgnn.ipynb
index 777097cc0..f712042f2 100644
--- a/docs/tutorial/dbgnn.ipynb
+++ b/docs/tutorial/dbgnn.ipynb
@@ -6,6 +6,29 @@
    "source": [
     "# Causality-Aware Graph Neural Networks\n",
     "\n",
+    "## Prerequisites\n",
+    "\n",
+    "First, we need to set up our Python environment that has PyTorch, PyTorch Geometric and PathpyG installed. Depending on where you are executing this notebook, this might already be (partially) done. E.g. Google Colab has PyTorch installed by default so we only need to install the remaining dependencies. The DevContainer that is part of our GitHub Repository on the other hand already has all of the necessary dependencies installed. \n",
+    "\n",
+    "In the following, we install the packages for usage in Google Colab using Jupyter magic commands. For other environments comment in or out the commands as necessary. For more details on how to install `pathpyG` especially if you want to install it with GPU-support, we refer to our [documentation](https://www.pathpy.net/dev/getting_started/). Note that `%%capture` discards the full output of the cell to not clutter this tutorial with unnecessary installation details. If you want to print the output, you can comment `%%capture` out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "# !pip install torch\n",
+    "!pip install torch_geometric\n",
+    "!pip install git+https://github.com/pathpy/pathpyG.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Motivation and Learning Objectives\n",
     "\n",
     "In previous tutorials, we have introduced causal paths in temporal graphs, and how we can use them to generate higher-order De Bruijn graph models that capture temporal-topological patterns in time series data. In this tutorial, we will show how we can use De Bruijn Graph Neural Networks, a causality-aware deep learning architecture for temporal graph data. The details of this approach are introduced [in this paper](https://proceedings.mlr.press/v198/qarkaxhija22a.html). The architecture is implemented in pathpyG and can be readily applied to temporal graph data. \n",
diff --git a/docs/tutorial/netzschleuder.ipynb b/docs/tutorial/netzschleuder.ipynb
index d8ea4cb36..cb51cab6e 100644
--- a/docs/tutorial/netzschleuder.ipynb
+++ b/docs/tutorial/netzschleuder.ipynb
@@ -6,6 +6,29 @@
    "source": [
     "# Accessing the Netzschleuder Repository\n",
     "\n",
+    "## Prerequisites\n",
+    "\n",
+    "First, we need to set up our Python environment that has PyTorch, PyTorch Geometric and PathpyG installed. Depending on where you are executing this notebook, this might already be (partially) done. E.g. Google Colab has PyTorch installed by default so we only need to install the remaining dependencies. The DevContainer that is part of our GitHub Repository on the other hand already has all of the necessary dependencies installed. \n",
+    "\n",
+    "In the following, we install the packages for usage in Google Colab using Jupyter magic commands. For other environments comment in or out the commands as necessary. For more details on how to install `pathpyG` especially if you want to install it with GPU-support, we refer to our [documentation](https://www.pathpy.net/dev/getting_started/). Note that `%%capture` discards the full output of the cell to not clutter this tutorial with unnecessary installation details. If you want to print the output, you can comment `%%capture` out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "# !pip install torch\n",
+    "!pip install torch_geometric\n",
+    "!pip install git+https://github.com/pathpy/pathpyG.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Motivation and Learning Objectives\n",
     "\n",
     "Access to a large number of graphs with different topological characteristics and from different domains is crucial for the development and evaluation of graph learning methods. Tousands of graph data sets are available scattered throughout the web, possibly using different data formats and with missing information on their actual origin. Addressing this issue the [Netschleuder Online Repository](https://networks.skewed.de/) by Tiago Peixoto provides a single repository of graphs in a single format, including descriptions, citations, and node-/edge- or graph-level meta-data. To facilitate the development of graph learning techniques, pathpyG provides a feature that allows to directly read networks from the netzschleuder repository via an API.\n",
@@ -17,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -52,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -94,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -111,6 +134,9 @@
       "Graph attributes\n",
       "\tnum_nodes\t\t<class 'int'>\n",
       "\ttags\t\t<class 'list'>\n",
+      "\turl\t\t<class 'str'>\n",
+      "\tname\t\t<class 'str'>\n",
+      "\tnum_nodes\t\t<class 'int'>\n",
       "\tcitation\t\t<class 'str'>\n",
       "\tname\t\t<class 'str'>\n",
       "\turl\t\t<class 'str'>\n",
@@ -126,7 +152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -422,7 +448,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -446,7 +472,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -734,7 +760,7 @@
        "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fab2bf61720>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -752,7 +778,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -843,7 +869,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/docs/tutorial/paths_higher_order.ipynb b/docs/tutorial/paths_higher_order.ipynb
index 2b77c1cc0..15d5e0e73 100644
--- a/docs/tutorial/paths_higher_order.ipynb
+++ b/docs/tutorial/paths_higher_order.ipynb
@@ -6,6 +6,29 @@
    "source": [
     "# Paths and Higher-Order De Bruijn Graph Models\n",
     "\n",
+    "## Prerequisites\n",
+    "\n",
+    "First, we need to set up our Python environment that has PyTorch, PyTorch Geometric and PathpyG installed. Depending on where you are executing this notebook, this might already be (partially) done. E.g. Google Colab has PyTorch installed by default so we only need to install the remaining dependencies. The DevContainer that is part of our GitHub Repository on the other hand already has all of the necessary dependencies installed. \n",
+    "\n",
+    "In the following, we install the packages for usage in Google Colab using Jupyter magic commands. For other environments comment in or out the commands as necessary. For more details on how to install `pathpyG` especially if you want to install it with GPU-support, we refer to our [documentation](https://www.pathpy.net/dev/getting_started/). Note that `%%capture` discards the full output of the cell to not clutter this tutorial with unnecessary installation details. If you want to print the output, you can comment `%%capture` out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "# !pip install torch\n",
+    "!pip install torch_geometric\n",
+    "!pip install git+https://github.com/pathpy/pathpyG.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Motivation and Learning Objective\n",
     "\n",
     "While `pathpyG` is useful to handle and visualize static graphs - as the name suggests - its main advantage is that it facilitates the analysis of time series data that can be used to calculate **paths** in a graph. As we shall see in the following tutorial, there are various situations in which naturally have access to data on paths, including data on (random) walks or trajectories, traces of dynamical processes giving rise to node sequences or directed acyclic graphs, or temporal graph data with time-stamped edges. ``pathpyG` ca nbe used to model patterns in such data based on higher-order De Bruijn graph models, a modelling framework that captures patterns in time series data on graphs.\n",
@@ -17,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1446,7 +1469,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
diff --git a/docs/tutorial/temporal_graphs.ipynb b/docs/tutorial/temporal_graphs.ipynb
index 7aa598b00..dbc24db31 100644
--- a/docs/tutorial/temporal_graphs.ipynb
+++ b/docs/tutorial/temporal_graphs.ipynb
@@ -6,9 +6,11 @@
    "source": [
     "# Temporal Graphs and Path Data\n",
     "\n",
-    "## Motivation and Learning Objectives\n",
+    "## Prerequisites\n",
+    "\n",
+    "First, we need to set up our Python environment that has PyTorch, PyTorch Geometric and PathpyG installed. Depending on where you are executing this notebook, this might already be (partially) done. E.g. Google Colab has PyTorch installed by default so we only need to install the remaining dependencies. The DevContainer that is part of our GitHub Repository on the other hand already has all of the necessary dependencies installed. \n",
     "\n",
-    "In this tutorial we will introduce the representation of temporal graph data in the `Temporal Graph` class and how such data can be used to calculate time respecting paths.\n"
+    "In the following, we install the packages for usage in Google Colab using Jupyter magic commands. For other environments comment in or out the commands as necessary. For more details on how to install `pathpyG` especially if you want to install it with GPU-support, we refer to our [documentation](https://www.pathpy.net/dev/getting_started/). Note that `%%capture` discards the full output of the cell to not clutter this tutorial with unnecessary installation details. If you want to print the output, you can comment `%%capture` out."
    ]
   },
   {
@@ -16,6 +18,27 @@
    "execution_count": 1,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "%%capture\n",
+    "# !pip install torch\n",
+    "!pip install torch_geometric\n",
+    "!pip install git+https://github.com/pathpy/pathpyG.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Motivation and Learning Objectives\n",
+    "\n",
+    "In this tutorial we will introduce the representation of temporal graph data in the `Temporal Graph` class and how such data can be used to calculate time respecting paths."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import torch\n",
     "from torch_geometric.data import TemporalData\n",
@@ -28,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -53,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -70,7 +93,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -91,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -100,7 +123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -136,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -159,7 +182,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -184,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -281,7 +304,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -312,7 +335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -734,7 +757,7 @@
        "<pathpyG.visualisations.network_plots.TemporalNetworkPlot at 0x7f7492c0aa10>"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -753,7 +776,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -762,7 +785,7 @@
        "TemporalData(src=[7], dst=[7], t=[7])"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -773,7 +796,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -797,7 +820,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -821,7 +844,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -852,7 +875,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
diff --git a/docs/tutorial/visualisation.ipynb b/docs/tutorial/visualisation.ipynb
index 7b6231187..ce5992f0d 100644
--- a/docs/tutorial/visualisation.ipynb
+++ b/docs/tutorial/visualisation.ipynb
@@ -6,6 +6,29 @@
    "source": [
     "# Interactiv Graph Visualization\n",
     "\n",
+    "## Prerequisites\n",
+    "\n",
+    "First, we need to set up our Python environment that has PyTorch, PyTorch Geometric and PathpyG installed. Depending on where you are executing this notebook, this might already be (partially) done. E.g. Google Colab has PyTorch installed by default so we only need to install the remaining dependencies. The DevContainer that is part of our GitHub Repository on the other hand already has all of the necessary dependencies installed. \n",
+    "\n",
+    "In the following, we install the packages for usage in Google Colab using Jupyter magic commands. For other environments comment in or out the commands as necessary. For more details on how to install `pathpyG` especially if you want to install it with GPU-support, we refer to our [documentation](https://www.pathpy.net/dev/getting_started/). Note that `%%capture` discards the full output of the cell to not clutter this tutorial with unnecessary installation details. If you want to print the output, you can comment `%%capture` out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "# !pip install torch\n",
+    "!pip install torch_geometric\n",
+    "!pip install git+https://github.com/pathpy/pathpyG.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Motivation\n",
     "\n",
     "This tutorial is specifically designed to guide you through the process of visualizing your data using `pathpyG`, an advanced data visualization tool. Data visualization is a crucial aspect of data analysis and interpretation, allowing for the transformation of complex datasets into visually appealing and easy-to-understand formats. pathpyG excels in this area by providing a range of functionalities that cater to both beginners and advanced users. Throughout this tutorial, you will be introduced to the basic and advanced features of pathpyG, empowering you to effectively visualize your data. This will not only enhance your understanding of your data but also enable you to communicate your findings more effectively to others.\n",
@@ -31,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -57,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 3,
    "metadata": {
     "scrolled": true
    },
@@ -93,7 +116,7 @@
        "\n",
        "</style>\n",
        "\n",
-       "<div id = \"xa2bdc9f454344ca5930aa933c9938269\"> </div>\n",
+       "<div id = \"x27730b31e4684e9c97987b6b990e46ba\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -126,7 +149,7 @@
        "};\n",
        "require(['d3'], function(d3){ //START\n",
        "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"color\": \"gray\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"label\": \"a\"}, {\"uid\": \"b\", \"label\": \"b\"}, {\"uid\": \"c\", \"label\": \"c\"}]}\n",
-       "const config = {\"node_label\": [\"a\", \"b\", \"c\"], \"edge_color\": \"gray\", \"directed\": true, \"curved\": true, \"selector\": \"#xa2bdc9f454344ca5930aa933c9938269\"}\n",
+       "const config = {\"node_label\": [\"a\", \"b\", \"c\"], \"edge_color\": \"gray\", \"directed\": true, \"curved\": true, \"selector\": \"#x27730b31e4684e9c97987b6b990e46ba\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -344,10 +367,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fc3d3c35840>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9c5ad5b190>"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -368,7 +391,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -377,7 +400,7 @@
        "'Our graph has 3 nodes and 2 edges.'"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -397,7 +420,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -407,23 +430,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
+       "}\n",
+       "\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
        "\n",
-       ".buttonText {\n",
-       "  color: #4e4d4d;\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
        "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"x1d7b978920384c4a9a27a2e3db0a8c6e\"> </div>\n",
+       "<div id = \"x5f9d102ad0574bf8a653a16aab944bbf\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -444,7 +475,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -455,8 +486,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"weight\": 1}, {\"uid\": \"b-a\", \"source\": \"b\", \"target\": \"a\", \"weight\": 1}, {\"uid\": \"b-c\", \"source\": \"b\", \"target\": \"c\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"x\": 0.7828295701678004, \"y\": 0.8967297344309817}, {\"uid\": \"b\", \"x\": 0.07285572206061308, \"y\": 0.4922263514824733}, {\"uid\": \"c\", \"x\": 0.8161077739882794, \"y\": 0.12851051414183867}]}\n",
-       "const config = {\"selector\": \"#x1d7b978920384c4a9a27a2e3db0a8c6e\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\"}, {\"uid\": \"b\"}, {\"uid\": \"c\"}]}\n",
+       "const config = {\"directed\": true, \"curved\": true, \"selector\": \"#x5f9d102ad0574bf8a653a16aab944bbf\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -465,8 +496,13 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
+       "const charge_distance = config.charge_distance || 400;\n",
+       "const charge_force = config.charge_force || -3000;\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
+       "// const weight = false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "var svg = d3.select(selector)\n",
@@ -489,16 +525,42 @@
        "var nodes = data.nodes\n",
        "var links = data.edges\n",
        "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Link creation template */\n",
        "var link = container.append(\"g\").attr(\"class\", \"links\")\n",
        "    .selectAll(\".link\")\n",
        "    .data(links)\n",
        "    .enter()\n",
-       "    .append(\"line\")\n",
+       "    .append(\"path\")\n",
        "    .attr(\"class\", \"link\")\n",
        "    .style(\"stroke\", function(d) { return d.color; })\n",
        "    .style(\"stroke-opacity\", function(d) { return d.opacity; })\n",
-       "    .style(\"stroke-width\", function(d){  return d.size });\n",
+       "    .style(\"stroke-width\", function(d){  return d.size })\n",
+       "    .style(\"fill\",\"none\")\n",
+       "    .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
+       "\n",
+       "    //.attr(\"marker-end\", function (d) { return marker(d.color); });\n",
+       "    //.attr(\"marker-end\", \"url(#arrow)\");\n",
        "\n",
        "/*Node creation template */\n",
        "var node = container.append(\"g\").attr(\"class\", \"nodes\")\n",
@@ -512,38 +574,98 @@
        "    .style(\"fill\", function(d) { return d.color; })\n",
        "    .style(\"opacity\", function(d) { return d.opacity; });\n",
        "\n",
+       "/*Label creation template */\n",
+       "var text = container.append(\"g\").attr(\"class\",\"labels\")\n",
+       "    .selectAll(\"g\")\n",
+       "    .data(nodes)\n",
+       "    .enter().append(\"g\")\n",
+       "\n",
+       "text.append(\"text\")\n",
+       "    .attr(\"class\", \"label-text\")\n",
+       "    .attr(\"x\", function(d) {\n",
+       "        var r = (d.size === undefined) ? 15 : d.size;\n",
+       "        return 5 + r; })\n",
+       "    .attr(\"dy\", \".31em\")\n",
+       "    .text(function(d) { return d.label; });\n",
+       "\n",
+       "/*Scale weight for d3js */\n",
+       "var weightScale = d3.scaleLinear()\n",
+       "    .domain(d3.extent(links, function (d) { return d.weight }))\n",
+       "    .range([.1, 1]);\n",
        "\n",
        "/*Simulation of the forces*/\n",
        "var simulation = d3.forceSimulation(nodes)\n",
-       "    .force(\"charge\", d3.forceManyBody().strength(-3000))\n",
-       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
-       "    .force(\"x\", d3.forceX(width / 2).strength(1))\n",
-       "    .force(\"y\", d3.forceY(height / 2).strength(1))\n",
        "    .force(\"links\", d3.forceLink(links)\n",
        "           .id(function(d) {return d.uid; })\n",
-       "           .distance(50).strength(function(d){return d.weight;}))\n",
+       "           .distance(50)\n",
+       "           .strength(function(d){return weightScale(d.weight);})\n",
+       "          )\n",
+       "    .force(\"charge\", d3.forceManyBody()\n",
+       "           .strength(charge_force)\n",
+       "           .distanceMax(charge_distance)\n",
+       "          )\n",
+       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
        "    .on(\"tick\", ticked);\n",
        "\n",
        "/*Update of the node and edge objects*/\n",
        "function ticked() {\n",
        "    node.call(updateNode);\n",
        "    link.call(updateLink);\n",
+       "    text.call(updateText);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateLink(link) {\n",
-       "    link\n",
-       "        .attr(\"x1\", function(d) { return d.source.x; })\n",
-       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
-       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
-       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "    // link\n",
+       "    //     .attr(\"x1\", function(d) { return d.source.x; })\n",
+       "    //     .attr(\"y1\", function(d) { return d.source.y; })\n",
+       "    //     .attr(\"x2\", function(d) { return d.target.x; })\n",
+       "    //     .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "\n",
+       "\n",
+       "    link.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    link.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
+       "\n",
        "/*Update node positions */\n",
        "function updateNode(node) {\n",
        "    node.attr(\"transform\", function(d) {\n",
        "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
        "    });\n",
+       "    // node\n",
+       "    //     .attr(\"cx\", function(d) { return d.x; })\n",
+       "    //     .attr(\"cy\", function(d) { return d.y; });\n",
+       "};\n",
+       "\n",
+       "/*Update text positions */\n",
+       "function updateText(text) {\n",
+       "    text.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -583,10 +705,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe1b9347670>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9c5ad5aa10>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -625,12 +747,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -656,14 +778,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -674,10 +796,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192eaf9d0>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5d344610>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -695,12 +817,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -711,10 +833,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe2986ee440>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9c5ad5a1a0>"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -737,7 +859,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -747,23 +869,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
        "}\n",
        "\n",
-       ".buttonText {\n",
-       "  color: #4e4d4d;\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
+       "}\n",
+       "\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
        "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"x3248201c5d704bf68b87e67bb35b1963\"> </div>\n",
+       "<div id = \"x6ea62538d21841459e8651f39367eccf\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -784,7 +914,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -795,8 +925,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"green\", \"weight\": 1}, {\"uid\": \"b-a\", \"source\": \"b\", \"target\": \"a\", \"color\": \"green\", \"weight\": 1}, {\"uid\": \"b-c\", \"source\": \"b\", \"target\": \"c\", \"color\": \"green\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"color\": \"green\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"color\": \"#ff01ff\", \"x\": 0.7032860747241524, \"y\": 0.7935163649564502}, {\"uid\": \"b\", \"color\": \"#ff01ff\", \"x\": 0.950769991012186, \"y\": 0.9882562713573045}, {\"uid\": \"c\", \"color\": \"#ff01ff\", \"x\": 0.005192524845727187, \"y\": 0.04765898068070129}]}\n",
-       "const config = {\"node_color\": [255, 1, 255], \"edge_color\": \"green\", \"selector\": \"#x3248201c5d704bf68b87e67bb35b1963\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"green\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"color\": \"green\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"color\": \"#ff01ff\"}, {\"uid\": \"b\", \"color\": \"#ff01ff\"}, {\"uid\": \"c\", \"color\": \"#ff01ff\"}]}\n",
+       "const config = {\"node_color\": [255, 1, 255], \"edge_color\": \"green\", \"directed\": true, \"curved\": true, \"selector\": \"#x6ea62538d21841459e8651f39367eccf\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -805,8 +935,13 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
+       "const charge_distance = config.charge_distance || 400;\n",
+       "const charge_force = config.charge_force || -3000;\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
+       "// const weight = false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "var svg = d3.select(selector)\n",
@@ -829,16 +964,42 @@
        "var nodes = data.nodes\n",
        "var links = data.edges\n",
        "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Link creation template */\n",
        "var link = container.append(\"g\").attr(\"class\", \"links\")\n",
        "    .selectAll(\".link\")\n",
        "    .data(links)\n",
        "    .enter()\n",
-       "    .append(\"line\")\n",
+       "    .append(\"path\")\n",
        "    .attr(\"class\", \"link\")\n",
        "    .style(\"stroke\", function(d) { return d.color; })\n",
        "    .style(\"stroke-opacity\", function(d) { return d.opacity; })\n",
-       "    .style(\"stroke-width\", function(d){  return d.size });\n",
+       "    .style(\"stroke-width\", function(d){  return d.size })\n",
+       "    .style(\"fill\",\"none\")\n",
+       "    .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
+       "\n",
+       "    //.attr(\"marker-end\", function (d) { return marker(d.color); });\n",
+       "    //.attr(\"marker-end\", \"url(#arrow)\");\n",
        "\n",
        "/*Node creation template */\n",
        "var node = container.append(\"g\").attr(\"class\", \"nodes\")\n",
@@ -852,50 +1013,110 @@
        "    .style(\"fill\", function(d) { return d.color; })\n",
        "    .style(\"opacity\", function(d) { return d.opacity; });\n",
        "\n",
+       "/*Label creation template */\n",
+       "var text = container.append(\"g\").attr(\"class\",\"labels\")\n",
+       "    .selectAll(\"g\")\n",
+       "    .data(nodes)\n",
+       "    .enter().append(\"g\")\n",
+       "\n",
+       "text.append(\"text\")\n",
+       "    .attr(\"class\", \"label-text\")\n",
+       "    .attr(\"x\", function(d) {\n",
+       "        var r = (d.size === undefined) ? 15 : d.size;\n",
+       "        return 5 + r; })\n",
+       "    .attr(\"dy\", \".31em\")\n",
+       "    .text(function(d) { return d.label; });\n",
+       "\n",
+       "/*Scale weight for d3js */\n",
+       "var weightScale = d3.scaleLinear()\n",
+       "    .domain(d3.extent(links, function (d) { return d.weight }))\n",
+       "    .range([.1, 1]);\n",
        "\n",
        "/*Simulation of the forces*/\n",
        "var simulation = d3.forceSimulation(nodes)\n",
-       "    .force(\"charge\", d3.forceManyBody().strength(-3000))\n",
-       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
-       "    .force(\"x\", d3.forceX(width / 2).strength(1))\n",
-       "    .force(\"y\", d3.forceY(height / 2).strength(1))\n",
        "    .force(\"links\", d3.forceLink(links)\n",
        "           .id(function(d) {return d.uid; })\n",
-       "           .distance(50).strength(function(d){return d.weight;}))\n",
+       "           .distance(50)\n",
+       "           .strength(function(d){return weightScale(d.weight);})\n",
+       "          )\n",
+       "    .force(\"charge\", d3.forceManyBody()\n",
+       "           .strength(charge_force)\n",
+       "           .distanceMax(charge_distance)\n",
+       "          )\n",
+       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
        "    .on(\"tick\", ticked);\n",
        "\n",
        "/*Update of the node and edge objects*/\n",
        "function ticked() {\n",
        "    node.call(updateNode);\n",
        "    link.call(updateLink);\n",
+       "    text.call(updateText);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateLink(link) {\n",
-       "    link\n",
-       "        .attr(\"x1\", function(d) { return d.source.x; })\n",
-       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
-       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
-       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
-       "};\n",
-       "\n",
-       "/*Update node positions */\n",
-       "function updateNode(node) {\n",
-       "    node.attr(\"transform\", function(d) {\n",
-       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
-       "    });\n",
-       "};\n",
+       "    // link\n",
+       "    //     .attr(\"x1\", function(d) { return d.source.x; })\n",
+       "    //     .attr(\"y1\", function(d) { return d.source.y; })\n",
+       "    //     .attr(\"x2\", function(d) { return d.target.x; })\n",
+       "    //     .attr(\"y2\", function(d) { return d.target.y; });\n",
        "\n",
-       "/*Add drag functionality to the node objects*/\n",
-       "node.call(\n",
-       "    d3.drag()\n",
-       "        .on(\"start\", dragstarted)\n",
-       "        .on(\"drag\", dragged)\n",
-       "        .on(\"end\", dragended)\n",
-       ");\n",
        "\n",
-       "function dragstarted(d) {\n",
-       "    d3.event.sourceEvent.stopPropagation();\n",
+       "    link.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    link.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
+       "};\n",
+       "\n",
+       "\n",
+       "/*Update node positions */\n",
+       "function updateNode(node) {\n",
+       "    node.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
+       "    // node\n",
+       "    //     .attr(\"cx\", function(d) { return d.x; })\n",
+       "    //     .attr(\"cy\", function(d) { return d.y; });\n",
+       "};\n",
+       "\n",
+       "/*Update text positions */\n",
+       "function updateText(text) {\n",
+       "    text.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
+       "};\n",
+       "\n",
+       "/*Add drag functionality to the node objects*/\n",
+       "node.call(\n",
+       "    d3.drag()\n",
+       "        .on(\"start\", dragstarted)\n",
+       "        .on(\"drag\", dragged)\n",
+       "        .on(\"end\", dragended)\n",
+       ");\n",
+       "\n",
+       "function dragstarted(d) {\n",
+       "    d3.event.sourceEvent.stopPropagation();\n",
        "    if (!d3.event.active) simulation.alphaTarget(0.3).restart();\n",
        "    d.fx = d.x;\n",
        "    d.fy = d.y;\n",
@@ -923,10 +1144,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192f482b0>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5d17ca90>"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -949,7 +1170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -959,23 +1180,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
+       "}\n",
+       "\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
        "\n",
-       ".buttonText {\n",
-       "  color: #4e4d4d;\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
        "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"xf2ad507554b94dd09277fd52eb011d3b\"> </div>\n",
+       "<div id = \"x421675ea69c14cceb127bcd3ae375827\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -996,7 +1225,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -1007,8 +1236,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"orange\", \"weight\": 1}, {\"uid\": \"b-a\", \"source\": \"b\", \"target\": \"a\", \"color\": \"#00FF00\", \"weight\": 1}, {\"uid\": \"b-c\", \"source\": \"b\", \"target\": \"c\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"color\": \"red\", \"size\": 40, \"x\": 0.13747628276170443, \"y\": 0.779590602281368}, {\"uid\": \"b\", \"color\": \"green\", \"size\": 10, \"opacity\": 0.5, \"x\": 0.34712978594315425, \"y\": 0.755114969330337}, {\"uid\": \"c\", \"color\": \"blue\", \"size\": 25, \"opacity\": 0.3, \"x\": 0.4549181099718945, \"y\": 0.5707710290430372}]}\n",
-       "const config = {\"node_color\": [\"red\", \"green\", \"blue\"], \"node_size\": {\"a\": 40, \"b\": 10, \"c\": 25}, \"node_opacity\": {\"b\": 0.5, \"c\": 0.3}, \"edge_color\": [\"orange\", \"#00FF00\"], \"selector\": \"#xf2ad507554b94dd09277fd52eb011d3b\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"orange\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"color\": \"#00FF00\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"size\": 40, \"color\": \"red\"}, {\"uid\": \"b\", \"size\": 10, \"color\": \"green\", \"opacity\": 0.5}, {\"uid\": \"c\", \"size\": 25, \"color\": \"blue\", \"opacity\": 0.3}]}\n",
+       "const config = {\"node_color\": [\"red\", \"green\", \"blue\"], \"node_size\": {\"a\": 40, \"b\": 10, \"c\": 25}, \"node_opacity\": {\"b\": 0.5, \"c\": 0.3}, \"edge_color\": [\"orange\", \"#00FF00\"], \"directed\": true, \"curved\": true, \"selector\": \"#x421675ea69c14cceb127bcd3ae375827\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -1017,8 +1246,13 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
+       "const charge_distance = config.charge_distance || 400;\n",
+       "const charge_force = config.charge_force || -3000;\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
+       "// const weight = false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "var svg = d3.select(selector)\n",
@@ -1041,16 +1275,42 @@
        "var nodes = data.nodes\n",
        "var links = data.edges\n",
        "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Link creation template */\n",
        "var link = container.append(\"g\").attr(\"class\", \"links\")\n",
        "    .selectAll(\".link\")\n",
        "    .data(links)\n",
        "    .enter()\n",
-       "    .append(\"line\")\n",
+       "    .append(\"path\")\n",
        "    .attr(\"class\", \"link\")\n",
        "    .style(\"stroke\", function(d) { return d.color; })\n",
        "    .style(\"stroke-opacity\", function(d) { return d.opacity; })\n",
-       "    .style(\"stroke-width\", function(d){  return d.size });\n",
+       "    .style(\"stroke-width\", function(d){  return d.size })\n",
+       "    .style(\"fill\",\"none\")\n",
+       "    .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
+       "\n",
+       "    //.attr(\"marker-end\", function (d) { return marker(d.color); });\n",
+       "    //.attr(\"marker-end\", \"url(#arrow)\");\n",
        "\n",
        "/*Node creation template */\n",
        "var node = container.append(\"g\").attr(\"class\", \"nodes\")\n",
@@ -1064,38 +1324,98 @@
        "    .style(\"fill\", function(d) { return d.color; })\n",
        "    .style(\"opacity\", function(d) { return d.opacity; });\n",
        "\n",
+       "/*Label creation template */\n",
+       "var text = container.append(\"g\").attr(\"class\",\"labels\")\n",
+       "    .selectAll(\"g\")\n",
+       "    .data(nodes)\n",
+       "    .enter().append(\"g\")\n",
+       "\n",
+       "text.append(\"text\")\n",
+       "    .attr(\"class\", \"label-text\")\n",
+       "    .attr(\"x\", function(d) {\n",
+       "        var r = (d.size === undefined) ? 15 : d.size;\n",
+       "        return 5 + r; })\n",
+       "    .attr(\"dy\", \".31em\")\n",
+       "    .text(function(d) { return d.label; });\n",
+       "\n",
+       "/*Scale weight for d3js */\n",
+       "var weightScale = d3.scaleLinear()\n",
+       "    .domain(d3.extent(links, function (d) { return d.weight }))\n",
+       "    .range([.1, 1]);\n",
        "\n",
        "/*Simulation of the forces*/\n",
        "var simulation = d3.forceSimulation(nodes)\n",
-       "    .force(\"charge\", d3.forceManyBody().strength(-3000))\n",
-       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
-       "    .force(\"x\", d3.forceX(width / 2).strength(1))\n",
-       "    .force(\"y\", d3.forceY(height / 2).strength(1))\n",
        "    .force(\"links\", d3.forceLink(links)\n",
        "           .id(function(d) {return d.uid; })\n",
-       "           .distance(50).strength(function(d){return d.weight;}))\n",
+       "           .distance(50)\n",
+       "           .strength(function(d){return weightScale(d.weight);})\n",
+       "          )\n",
+       "    .force(\"charge\", d3.forceManyBody()\n",
+       "           .strength(charge_force)\n",
+       "           .distanceMax(charge_distance)\n",
+       "          )\n",
+       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
        "    .on(\"tick\", ticked);\n",
        "\n",
        "/*Update of the node and edge objects*/\n",
        "function ticked() {\n",
        "    node.call(updateNode);\n",
        "    link.call(updateLink);\n",
+       "    text.call(updateText);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateLink(link) {\n",
-       "    link\n",
-       "        .attr(\"x1\", function(d) { return d.source.x; })\n",
-       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
-       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
-       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "    // link\n",
+       "    //     .attr(\"x1\", function(d) { return d.source.x; })\n",
+       "    //     .attr(\"y1\", function(d) { return d.source.y; })\n",
+       "    //     .attr(\"x2\", function(d) { return d.target.x; })\n",
+       "    //     .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "\n",
+       "\n",
+       "    link.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    link.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
+       "\n",
        "/*Update node positions */\n",
        "function updateNode(node) {\n",
        "    node.attr(\"transform\", function(d) {\n",
        "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
        "    });\n",
+       "    // node\n",
+       "    //     .attr(\"cx\", function(d) { return d.x; })\n",
+       "    //     .attr(\"cy\", function(d) { return d.y; });\n",
+       "};\n",
+       "\n",
+       "/*Update text positions */\n",
+       "function updateText(text) {\n",
+       "    text.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -1135,10 +1455,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192f48430>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5d1a7f40>"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1163,20 +1483,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/html": [
-       "<div style=\"vertical-align: middle;\"><strong>viridis</strong> </div><div class=\"cmap\"><img alt=\"viridis colormap\" title=\"viridis\" style=\"border: 1px solid #555;\" src=\"data:image/png;base64,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\"></div><div style=\"vertical-align: middle; max-width: 514px; display: flex; justify-content: space-between;\"><div style=\"float: left;\"><div title=\"#440154ff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #440154ff;\"></div> under</div><div style=\"margin: 0 auto; display: inline-block;\">bad <div title=\"#00000000\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #00000000;\"></div></div><div style=\"float: right;\">over <div title=\"#fde725ff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #fde725ff;\"></div></div>"
+       "<div style=\"vertical-align: middle;\"><strong>viridis</strong> </div><div class=\"cmap\"><img alt=\"viridis colormap\" title=\"viridis\" style=\"border: 1px solid #555;\" src=\"data:image/png;base64,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\"></div><div style=\"vertical-align: middle; max-width: 514px; display: flex; justify-content: space-between;\"><div style=\"float: left;\"><div title=\"#440154ff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #440154ff;\"></div> under</div><div style=\"margin: 0 auto; display: inline-block;\">bad <div title=\"#00000000\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #00000000;\"></div></div><div style=\"float: right;\">over <div title=\"#fde725ff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #fde725ff;\"></div></div>"
       ],
       "text/plain": [
-       "<matplotlib.colors.ListedColormap at 0x7fe192f48e80>"
+       "<matplotlib.colors.ListedColormap at 0x7f9b5d29e680>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1189,7 +1509,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -1199,23 +1519,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
+       "}\n",
+       "\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
        "\n",
-       ".buttonText {\n",
-       "  color: #4e4d4d;\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
        "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"x11c44f6b1bd6445a9b1d2910d5e547e2\"> </div>\n",
+       "<div id = \"x800e9347da254d3a87da3f58147986f1\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -1236,7 +1564,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -1247,8 +1575,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"#00ff00\", \"weight\": 1}, {\"uid\": \"b-a\", \"source\": \"b\", \"target\": \"a\", \"color\": \"#ff0000\", \"weight\": 1}, {\"uid\": \"b-c\", \"source\": \"b\", \"target\": \"c\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"color\": \"#440154\", \"x\": 0.7724663863365322, \"y\": 0.20441592398371877}, {\"uid\": \"b\", \"color\": \"#fde724\", \"x\": 0.9194290271035113, \"y\": 0.30879847029447516}, {\"uid\": \"c\", \"color\": \"#440154\", \"x\": 0.9425318935101207, \"y\": 0.7825613274204651}]}\n",
-       "const config = {\"edge_color\": [1, 9], \"node_color\": {\"a\": 0.0, \"b\": 1.0, \"c\": 0.0}, \"selector\": \"#x11c44f6b1bd6445a9b1d2910d5e547e2\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"a-b\", \"source\": \"a\", \"target\": \"b\", \"color\": \"#00ff00\", \"weight\": 1}, {\"uid\": \"c-b\", \"source\": \"c\", \"target\": \"b\", \"color\": \"#ff0000\", \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"color\": \"#440154\"}, {\"uid\": \"b\", \"color\": \"#440154\"}, {\"uid\": \"c\", \"color\": \"#440154\"}]}\n",
+       "const config = {\"edge_color\": [1, 9], \"node_color\": {\"a\": 0.0, \"b\": 0.0, \"c\": 0.0}, \"directed\": true, \"curved\": true, \"selector\": \"#x800e9347da254d3a87da3f58147986f1\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -1257,8 +1585,13 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
+       "const charge_distance = config.charge_distance || 400;\n",
+       "const charge_force = config.charge_force || -3000;\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
+       "// const weight = false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "var svg = d3.select(selector)\n",
@@ -1281,16 +1614,42 @@
        "var nodes = data.nodes\n",
        "var links = data.edges\n",
        "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Link creation template */\n",
        "var link = container.append(\"g\").attr(\"class\", \"links\")\n",
        "    .selectAll(\".link\")\n",
        "    .data(links)\n",
        "    .enter()\n",
-       "    .append(\"line\")\n",
+       "    .append(\"path\")\n",
        "    .attr(\"class\", \"link\")\n",
        "    .style(\"stroke\", function(d) { return d.color; })\n",
        "    .style(\"stroke-opacity\", function(d) { return d.opacity; })\n",
-       "    .style(\"stroke-width\", function(d){  return d.size });\n",
+       "    .style(\"stroke-width\", function(d){  return d.size })\n",
+       "    .style(\"fill\",\"none\")\n",
+       "    .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
+       "\n",
+       "    //.attr(\"marker-end\", function (d) { return marker(d.color); });\n",
+       "    //.attr(\"marker-end\", \"url(#arrow)\");\n",
        "\n",
        "/*Node creation template */\n",
        "var node = container.append(\"g\").attr(\"class\", \"nodes\")\n",
@@ -1304,38 +1663,98 @@
        "    .style(\"fill\", function(d) { return d.color; })\n",
        "    .style(\"opacity\", function(d) { return d.opacity; });\n",
        "\n",
+       "/*Label creation template */\n",
+       "var text = container.append(\"g\").attr(\"class\",\"labels\")\n",
+       "    .selectAll(\"g\")\n",
+       "    .data(nodes)\n",
+       "    .enter().append(\"g\")\n",
+       "\n",
+       "text.append(\"text\")\n",
+       "    .attr(\"class\", \"label-text\")\n",
+       "    .attr(\"x\", function(d) {\n",
+       "        var r = (d.size === undefined) ? 15 : d.size;\n",
+       "        return 5 + r; })\n",
+       "    .attr(\"dy\", \".31em\")\n",
+       "    .text(function(d) { return d.label; });\n",
+       "\n",
+       "/*Scale weight for d3js */\n",
+       "var weightScale = d3.scaleLinear()\n",
+       "    .domain(d3.extent(links, function (d) { return d.weight }))\n",
+       "    .range([.1, 1]);\n",
        "\n",
        "/*Simulation of the forces*/\n",
        "var simulation = d3.forceSimulation(nodes)\n",
-       "    .force(\"charge\", d3.forceManyBody().strength(-3000))\n",
-       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
-       "    .force(\"x\", d3.forceX(width / 2).strength(1))\n",
-       "    .force(\"y\", d3.forceY(height / 2).strength(1))\n",
        "    .force(\"links\", d3.forceLink(links)\n",
        "           .id(function(d) {return d.uid; })\n",
-       "           .distance(50).strength(function(d){return d.weight;}))\n",
+       "           .distance(50)\n",
+       "           .strength(function(d){return weightScale(d.weight);})\n",
+       "          )\n",
+       "    .force(\"charge\", d3.forceManyBody()\n",
+       "           .strength(charge_force)\n",
+       "           .distanceMax(charge_distance)\n",
+       "          )\n",
+       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
        "    .on(\"tick\", ticked);\n",
        "\n",
        "/*Update of the node and edge objects*/\n",
        "function ticked() {\n",
        "    node.call(updateNode);\n",
        "    link.call(updateLink);\n",
+       "    text.call(updateText);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateLink(link) {\n",
-       "    link\n",
-       "        .attr(\"x1\", function(d) { return d.source.x; })\n",
-       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
-       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
-       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "    // link\n",
+       "    //     .attr(\"x1\", function(d) { return d.source.x; })\n",
+       "    //     .attr(\"y1\", function(d) { return d.source.y; })\n",
+       "    //     .attr(\"x2\", function(d) { return d.target.x; })\n",
+       "    //     .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "\n",
+       "\n",
+       "    link.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    link.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
+       "\n",
        "/*Update node positions */\n",
        "function updateNode(node) {\n",
        "    node.attr(\"transform\", function(d) {\n",
        "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
        "    });\n",
+       "    // node\n",
+       "    //     .attr(\"cx\", function(d) { return d.x; })\n",
+       "    //     .attr(\"cy\", function(d) { return d.y; });\n",
+       "};\n",
+       "\n",
+       "/*Update text positions */\n",
+       "function updateText(text) {\n",
+       "    text.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -1375,10 +1794,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192f4b940>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5e745780>"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1403,16 +1822,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192f4bb80>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5d142ef0>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1432,7 +1851,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1441,17 +1860,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/opt/conda/lib/python3.10/site-packages/torch_geometric/data/storage.py:327: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'node_groups', 'name', 'node_id', 'node_name', 'node__pos', 'tags', 'description', 'citation', 'edge_index', 'url'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
-      "  warnings.warn(\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -1459,23 +1870,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
        "}\n",
        "\n",
-       ".buttonText {\n",
-       "  color: #4e4d4d;\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
+       "\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
+       "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"x49f7b9acb652479d8b9b44c97e107628\"> </div>\n",
+       "<div id = \"x496dd068455242fca7dd20de3f0df590\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -1496,7 +1915,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -1507,8 +1926,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"0-1\", \"source\": \"0\", \"target\": \"1\", \"weight\": 1}, {\"uid\": \"0-2\", \"source\": \"0\", \"target\": \"2\", \"weight\": 1}, {\"uid\": \"0-3\", \"source\": \"0\", \"target\": \"3\", \"weight\": 1}, {\"uid\": \"0-4\", \"source\": \"0\", \"target\": \"4\", \"weight\": 1}, {\"uid\": \"0-5\", \"source\": \"0\", \"target\": \"5\", \"weight\": 1}, {\"uid\": \"0-6\", \"source\": \"0\", \"target\": \"6\", \"weight\": 1}, {\"uid\": \"0-7\", \"source\": \"0\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"0-8\", \"source\": \"0\", \"target\": \"8\", \"weight\": 1}, {\"uid\": \"0-10\", \"source\": \"0\", \"target\": \"10\", \"weight\": 1}, {\"uid\": \"0-11\", \"source\": \"0\", \"target\": \"11\", \"weight\": 1}, {\"uid\": \"0-12\", \"source\": \"0\", \"target\": \"12\", \"weight\": 1}, {\"uid\": \"0-13\", \"source\": \"0\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"0-17\", \"source\": \"0\", \"target\": \"17\", \"weight\": 1}, {\"uid\": \"0-19\", \"source\": \"0\", \"target\": \"19\", \"weight\": 1}, {\"uid\": \"0-21\", \"source\": \"0\", \"target\": \"21\", \"weight\": 1}, {\"uid\": \"0-31\", \"source\": \"0\", \"target\": \"31\", \"weight\": 1}, {\"uid\": \"1-2\", \"source\": \"1\", \"target\": \"2\", \"weight\": 1}, {\"uid\": \"1-3\", \"source\": \"1\", \"target\": \"3\", \"weight\": 1}, {\"uid\": \"1-7\", \"source\": \"1\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"1-13\", \"source\": \"1\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"1-17\", \"source\": \"1\", \"target\": \"17\", \"weight\": 1}, {\"uid\": \"1-19\", \"source\": \"1\", \"target\": \"19\", \"weight\": 1}, {\"uid\": \"1-21\", \"source\": \"1\", \"target\": \"21\", \"weight\": 1}, {\"uid\": \"1-30\", \"source\": \"1\", \"target\": \"30\", \"weight\": 1}, {\"uid\": \"2-3\", \"source\": \"2\", \"target\": \"3\", \"weight\": 1}, {\"uid\": \"2-7\", \"source\": \"2\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"2-8\", \"source\": \"2\", \"target\": \"8\", \"weight\": 1}, {\"uid\": \"2-9\", \"source\": \"2\", \"target\": \"9\", \"weight\": 1}, {\"uid\": \"2-13\", \"source\": \"2\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"2-27\", \"source\": \"2\", \"target\": \"27\", \"weight\": 1}, {\"uid\": \"2-28\", \"source\": \"2\", \"target\": \"28\", \"weight\": 1}, {\"uid\": \"2-32\", \"source\": \"2\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"3-7\", \"source\": \"3\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"3-12\", \"source\": \"3\", \"target\": \"12\", \"weight\": 1}, {\"uid\": \"3-13\", \"source\": \"3\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"4-6\", \"source\": \"4\", \"target\": \"6\", \"weight\": 1}, {\"uid\": \"4-10\", \"source\": \"4\", \"target\": \"10\", \"weight\": 1}, {\"uid\": \"5-6\", \"source\": \"5\", \"target\": \"6\", \"weight\": 1}, {\"uid\": \"5-10\", \"source\": \"5\", \"target\": \"10\", \"weight\": 1}, {\"uid\": \"5-16\", \"source\": \"5\", \"target\": \"16\", \"weight\": 1}, {\"uid\": \"6-16\", \"source\": \"6\", \"target\": \"16\", \"weight\": 1}, {\"uid\": \"8-30\", \"source\": \"8\", \"target\": \"30\", \"weight\": 1}, {\"uid\": \"8-32\", \"source\": \"8\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"8-33\", \"source\": \"8\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"9-33\", \"source\": \"9\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"13-33\", \"source\": \"13\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"19-33\", \"source\": \"19\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"23-25\", \"source\": \"23\", \"target\": \"25\", \"weight\": 1}, {\"uid\": \"23-29\", \"source\": \"23\", \"target\": \"29\", \"weight\": 1}, {\"uid\": \"25-24\", \"source\": \"25\", \"target\": \"24\", \"weight\": 1}, {\"uid\": \"27-23\", \"source\": \"27\", \"target\": \"23\", \"weight\": 1}, {\"uid\": \"27-24\", \"source\": \"27\", \"target\": \"24\", \"weight\": 1}, {\"uid\": \"27-33\", \"source\": \"27\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"28-33\", \"source\": \"28\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"29-26\", \"source\": \"29\", \"target\": \"26\", \"weight\": 1}, {\"uid\": \"30-32\", \"source\": \"30\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"30-33\", \"source\": \"30\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"31-24\", \"source\": \"31\", \"target\": \"24\", \"weight\": 1}, {\"uid\": \"31-25\", \"source\": \"31\", \"target\": \"25\", \"weight\": 1}, {\"uid\": \"31-28\", \"source\": \"31\", \"target\": \"28\", \"weight\": 1}, {\"uid\": \"31-32\", \"source\": \"31\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"31-33\", \"source\": \"31\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"32-14\", \"source\": \"32\", \"target\": \"14\", \"weight\": 1}, {\"uid\": \"32-15\", \"source\": \"32\", \"target\": \"15\", \"weight\": 1}, {\"uid\": \"32-18\", \"source\": \"32\", \"target\": \"18\", \"weight\": 1}, {\"uid\": \"32-20\", \"source\": \"32\", \"target\": \"20\", \"weight\": 1}, {\"uid\": \"32-22\", \"source\": \"32\", \"target\": \"22\", \"weight\": 1}, {\"uid\": \"32-23\", \"source\": \"32\", \"target\": \"23\", \"weight\": 1}, {\"uid\": \"32-29\", \"source\": \"32\", \"target\": \"29\", \"weight\": 1}, {\"uid\": \"32-33\", \"source\": \"32\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"33-14\", \"source\": \"33\", \"target\": \"14\", \"weight\": 1}, {\"uid\": \"33-15\", \"source\": \"33\", \"target\": \"15\", \"weight\": 1}, {\"uid\": \"33-18\", \"source\": \"33\", \"target\": \"18\", \"weight\": 1}, {\"uid\": \"33-20\", \"source\": \"33\", \"target\": \"20\", \"weight\": 1}, {\"uid\": \"33-23\", \"source\": \"33\", \"target\": \"23\", \"weight\": 1}, {\"uid\": \"33-26\", \"source\": \"33\", \"target\": \"26\", \"weight\": 1}, {\"uid\": \"33-29\", \"source\": \"33\", \"target\": \"29\", \"weight\": 1}], \"nodes\": [{\"uid\": \"0\", \"x\": 0.8964918119802723, \"y\": 0.9318428822367382}, {\"uid\": \"1\", \"x\": 0.7299901567847716, \"y\": 0.7736782802591167}, {\"uid\": \"2\", \"x\": 0.69511574126669, \"y\": 0.577542293210213}, {\"uid\": \"3\", \"x\": 0.8404500077914804, \"y\": 0.7157754691625263}, {\"uid\": \"4\", \"x\": 0.553924478090228, \"y\": 0.03325034568263241}, {\"uid\": \"5\", \"x\": 0.137320854612617, \"y\": 0.5806234987064328}, {\"uid\": \"6\", \"x\": 0.8998529760046461, \"y\": 0.3564391328136246}, {\"uid\": \"7\", \"x\": 0.1592745626507498, \"y\": 0.3471562402092825}, {\"uid\": \"8\", \"x\": 0.11753964612393164, \"y\": 0.9536265847269503}, {\"uid\": \"9\", \"x\": 0.3673363748362293, \"y\": 0.4558914349791342}, {\"uid\": \"10\", \"x\": 0.19119140854832184, \"y\": 0.23425510644840286}, {\"uid\": \"11\", \"x\": 0.9045243595073555, \"y\": 0.12220271271988203}, {\"uid\": \"12\", \"x\": 0.5455942088261964, \"y\": 0.6805649642834745}, {\"uid\": \"13\", \"x\": 0.7758083950458972, \"y\": 0.8523418502727979}, {\"uid\": \"14\", \"x\": 0.8465495773236784, \"y\": 0.8309059575979989}, {\"uid\": \"15\", \"x\": 0.16080235785608732, \"y\": 0.20726424877300753}, {\"uid\": \"16\", \"x\": 0.7674788869022915, \"y\": 0.719470336961589}, {\"uid\": \"17\", \"x\": 0.8434132174292602, \"y\": 0.12461952078712923}, {\"uid\": \"18\", \"x\": 0.448504328805176, \"y\": 0.9869751834666647}, {\"uid\": \"19\", \"x\": 0.8349898998341647, \"y\": 0.47608875944196904}, {\"uid\": \"20\", \"x\": 0.5985735376551901, \"y\": 0.21615573759898277}, {\"uid\": \"21\", \"x\": 0.22407042304428582, \"y\": 0.10659289343834966}, {\"uid\": \"22\", \"x\": 0.41486131398384685, \"y\": 0.0926665993053909}, {\"uid\": \"23\", \"x\": 0.9678448627964713, \"y\": 0.16486478595895804}, {\"uid\": \"24\", \"x\": 0.46561787880912375, \"y\": 0.5757087103520798}, {\"uid\": \"25\", \"x\": 0.8445117025876915, \"y\": 0.6095442168230067}, {\"uid\": \"26\", \"x\": 0.2545774078948001, \"y\": 0.9793274333137758}, {\"uid\": \"27\", \"x\": 0.4015335481391499, \"y\": 0.05984709917949316}, {\"uid\": \"28\", \"x\": 0.11755756847592036, \"y\": 0.9637263963594733}, {\"uid\": \"29\", \"x\": 0.8496510091107978, \"y\": 0.15390666353622406}, {\"uid\": \"30\", \"x\": 0.5412296602616111, \"y\": 0.8776880119990804}, {\"uid\": \"31\", \"x\": 0.08536818836818039, \"y\": 0.1430362520966666}, {\"uid\": \"32\", \"x\": 0.2723877785669123, \"y\": 0.39580407350475566}, {\"uid\": \"33\", \"x\": 0.5734711344526062, \"y\": 0.1286092739787238}]}\n",
-       "const config = {\"selector\": \"#x49f7b9acb652479d8b9b44c97e107628\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"0-2\", \"source\": \"0\", \"target\": \"2\", \"weight\": 1}, {\"uid\": \"0-1\", \"source\": \"0\", \"target\": \"1\", \"weight\": 1}, {\"uid\": \"0-31\", \"source\": \"0\", \"target\": \"31\", \"weight\": 1}, {\"uid\": \"0-21\", \"source\": \"0\", \"target\": \"21\", \"weight\": 1}, {\"uid\": \"0-19\", \"source\": \"0\", \"target\": \"19\", \"weight\": 1}, {\"uid\": \"0-17\", \"source\": \"0\", \"target\": \"17\", \"weight\": 1}, {\"uid\": \"0-13\", \"source\": \"0\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"0-12\", \"source\": \"0\", \"target\": \"12\", \"weight\": 1}, {\"uid\": \"0-11\", \"source\": \"0\", \"target\": \"11\", \"weight\": 1}, {\"uid\": \"0-8\", \"source\": \"0\", \"target\": \"8\", \"weight\": 1}, {\"uid\": \"0-7\", \"source\": \"0\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"0-6\", \"source\": \"0\", \"target\": \"6\", \"weight\": 1}, {\"uid\": \"0-5\", \"source\": \"0\", \"target\": \"5\", \"weight\": 1}, {\"uid\": \"0-4\", \"source\": \"0\", \"target\": \"4\", \"weight\": 1}, {\"uid\": \"0-3\", \"source\": \"0\", \"target\": \"3\", \"weight\": 1}, {\"uid\": \"0-10\", \"source\": \"0\", \"target\": \"10\", \"weight\": 1}, {\"uid\": \"1-7\", \"source\": \"1\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"1-30\", \"source\": \"1\", \"target\": \"30\", \"weight\": 1}, {\"uid\": \"1-21\", \"source\": \"1\", \"target\": \"21\", \"weight\": 1}, {\"uid\": \"1-19\", \"source\": \"1\", \"target\": \"19\", \"weight\": 1}, {\"uid\": \"1-17\", \"source\": \"1\", \"target\": \"17\", \"weight\": 1}, {\"uid\": \"1-13\", \"source\": \"1\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"1-3\", \"source\": \"1\", \"target\": \"3\", \"weight\": 1}, {\"uid\": \"1-2\", \"source\": \"1\", \"target\": \"2\", \"weight\": 1}, {\"uid\": \"2-3\", \"source\": \"2\", \"target\": \"3\", \"weight\": 1}, {\"uid\": \"2-32\", \"source\": \"2\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"2-28\", \"source\": \"2\", \"target\": \"28\", \"weight\": 1}, {\"uid\": \"2-27\", \"source\": \"2\", \"target\": \"27\", \"weight\": 1}, {\"uid\": \"2-13\", \"source\": \"2\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"2-9\", \"source\": \"2\", \"target\": \"9\", \"weight\": 1}, {\"uid\": \"2-8\", \"source\": \"2\", \"target\": \"8\", \"weight\": 1}, {\"uid\": \"2-7\", \"source\": \"2\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"3-7\", \"source\": \"3\", \"target\": \"7\", \"weight\": 1}, {\"uid\": \"3-12\", \"source\": \"3\", \"target\": \"12\", \"weight\": 1}, {\"uid\": \"3-13\", \"source\": \"3\", \"target\": \"13\", \"weight\": 1}, {\"uid\": \"4-6\", \"source\": \"4\", \"target\": \"6\", \"weight\": 1}, {\"uid\": \"4-10\", \"source\": \"4\", \"target\": \"10\", \"weight\": 1}, {\"uid\": \"5-16\", \"source\": \"5\", \"target\": \"16\", \"weight\": 1}, {\"uid\": \"5-10\", \"source\": \"5\", \"target\": \"10\", \"weight\": 1}, {\"uid\": \"5-6\", \"source\": \"5\", \"target\": \"6\", \"weight\": 1}, {\"uid\": \"6-16\", \"source\": \"6\", \"target\": \"16\", \"weight\": 1}, {\"uid\": \"8-30\", \"source\": \"8\", \"target\": \"30\", \"weight\": 1}, {\"uid\": \"8-32\", \"source\": \"8\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"8-33\", \"source\": \"8\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"9-33\", \"source\": \"9\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"13-33\", \"source\": \"13\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"19-33\", \"source\": \"19\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"23-25\", \"source\": \"23\", \"target\": \"25\", \"weight\": 1}, {\"uid\": \"23-29\", \"source\": \"23\", \"target\": \"29\", \"weight\": 1}, {\"uid\": \"25-24\", \"source\": \"25\", \"target\": \"24\", \"weight\": 1}, {\"uid\": \"27-23\", \"source\": \"27\", \"target\": \"23\", \"weight\": 1}, {\"uid\": \"27-24\", \"source\": \"27\", \"target\": \"24\", \"weight\": 1}, {\"uid\": \"27-33\", \"source\": \"27\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"28-33\", \"source\": \"28\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"29-26\", \"source\": \"29\", \"target\": \"26\", \"weight\": 1}, {\"uid\": \"30-32\", \"source\": \"30\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"30-33\", \"source\": \"30\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"31-33\", \"source\": \"31\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"31-25\", \"source\": \"31\", \"target\": \"25\", \"weight\": 1}, {\"uid\": \"31-32\", \"source\": \"31\", \"target\": \"32\", \"weight\": 1}, {\"uid\": \"31-24\", \"source\": \"31\", \"target\": \"24\", \"weight\": 1}, {\"uid\": \"31-28\", \"source\": \"31\", \"target\": \"28\", \"weight\": 1}, {\"uid\": \"32-29\", \"source\": \"32\", \"target\": \"29\", \"weight\": 1}, {\"uid\": \"32-33\", \"source\": \"32\", \"target\": \"33\", \"weight\": 1}, {\"uid\": \"32-23\", \"source\": \"32\", \"target\": \"23\", \"weight\": 1}, {\"uid\": \"32-22\", \"source\": \"32\", \"target\": \"22\", \"weight\": 1}, {\"uid\": \"32-20\", \"source\": \"32\", \"target\": \"20\", \"weight\": 1}, {\"uid\": \"32-18\", \"source\": \"32\", \"target\": \"18\", \"weight\": 1}, {\"uid\": \"32-15\", \"source\": \"32\", \"target\": \"15\", \"weight\": 1}, {\"uid\": \"32-14\", \"source\": \"32\", \"target\": \"14\", \"weight\": 1}, {\"uid\": \"33-14\", \"source\": \"33\", \"target\": \"14\", \"weight\": 1}, {\"uid\": \"33-15\", \"source\": \"33\", \"target\": \"15\", \"weight\": 1}, {\"uid\": \"33-18\", \"source\": \"33\", \"target\": \"18\", \"weight\": 1}, {\"uid\": \"33-20\", \"source\": \"33\", \"target\": \"20\", \"weight\": 1}, {\"uid\": \"33-23\", \"source\": \"33\", \"target\": \"23\", \"weight\": 1}, {\"uid\": \"33-26\", \"source\": \"33\", \"target\": \"26\", \"weight\": 1}, {\"uid\": \"33-29\", \"source\": \"33\", \"target\": \"29\", \"weight\": 1}], \"nodes\": [{\"uid\": \"0\"}, {\"uid\": \"1\"}, {\"uid\": \"2\"}, {\"uid\": \"3\"}, {\"uid\": \"4\"}, {\"uid\": \"5\"}, {\"uid\": \"6\"}, {\"uid\": \"7\"}, {\"uid\": \"8\"}, {\"uid\": \"9\"}, {\"uid\": \"10\"}, {\"uid\": \"11\"}, {\"uid\": \"12\"}, {\"uid\": \"13\"}, {\"uid\": \"14\"}, {\"uid\": \"15\"}, {\"uid\": \"16\"}, {\"uid\": \"17\"}, {\"uid\": \"18\"}, {\"uid\": \"19\"}, {\"uid\": \"20\"}, {\"uid\": \"21\"}, {\"uid\": \"22\"}, {\"uid\": \"23\"}, {\"uid\": \"24\"}, {\"uid\": \"25\"}, {\"uid\": \"26\"}, {\"uid\": \"27\"}, {\"uid\": \"28\"}, {\"uid\": \"29\"}, {\"uid\": \"30\"}, {\"uid\": \"31\"}, {\"uid\": \"32\"}, {\"uid\": \"33\"}]}\n",
+       "const config = {\"directed\": true, \"curved\": true, \"selector\": \"#x496dd068455242fca7dd20de3f0df590\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -1517,8 +1936,13 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
+       "const charge_distance = config.charge_distance || 400;\n",
+       "const charge_force = config.charge_force || -3000;\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
+       "// const weight = false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "var svg = d3.select(selector)\n",
@@ -1541,16 +1965,42 @@
        "var nodes = data.nodes\n",
        "var links = data.edges\n",
        "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Link creation template */\n",
        "var link = container.append(\"g\").attr(\"class\", \"links\")\n",
        "    .selectAll(\".link\")\n",
        "    .data(links)\n",
        "    .enter()\n",
-       "    .append(\"line\")\n",
+       "    .append(\"path\")\n",
        "    .attr(\"class\", \"link\")\n",
        "    .style(\"stroke\", function(d) { return d.color; })\n",
        "    .style(\"stroke-opacity\", function(d) { return d.opacity; })\n",
-       "    .style(\"stroke-width\", function(d){  return d.size });\n",
+       "    .style(\"stroke-width\", function(d){  return d.size })\n",
+       "    .style(\"fill\",\"none\")\n",
+       "    .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
+       "\n",
+       "    //.attr(\"marker-end\", function (d) { return marker(d.color); });\n",
+       "    //.attr(\"marker-end\", \"url(#arrow)\");\n",
        "\n",
        "/*Node creation template */\n",
        "var node = container.append(\"g\").attr(\"class\", \"nodes\")\n",
@@ -1564,38 +2014,98 @@
        "    .style(\"fill\", function(d) { return d.color; })\n",
        "    .style(\"opacity\", function(d) { return d.opacity; });\n",
        "\n",
+       "/*Label creation template */\n",
+       "var text = container.append(\"g\").attr(\"class\",\"labels\")\n",
+       "    .selectAll(\"g\")\n",
+       "    .data(nodes)\n",
+       "    .enter().append(\"g\")\n",
+       "\n",
+       "text.append(\"text\")\n",
+       "    .attr(\"class\", \"label-text\")\n",
+       "    .attr(\"x\", function(d) {\n",
+       "        var r = (d.size === undefined) ? 15 : d.size;\n",
+       "        return 5 + r; })\n",
+       "    .attr(\"dy\", \".31em\")\n",
+       "    .text(function(d) { return d.label; });\n",
+       "\n",
+       "/*Scale weight for d3js */\n",
+       "var weightScale = d3.scaleLinear()\n",
+       "    .domain(d3.extent(links, function (d) { return d.weight }))\n",
+       "    .range([.1, 1]);\n",
        "\n",
        "/*Simulation of the forces*/\n",
        "var simulation = d3.forceSimulation(nodes)\n",
-       "    .force(\"charge\", d3.forceManyBody().strength(-3000))\n",
-       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
-       "    .force(\"x\", d3.forceX(width / 2).strength(1))\n",
-       "    .force(\"y\", d3.forceY(height / 2).strength(1))\n",
        "    .force(\"links\", d3.forceLink(links)\n",
        "           .id(function(d) {return d.uid; })\n",
-       "           .distance(50).strength(function(d){return d.weight;}))\n",
+       "           .distance(50)\n",
+       "           .strength(function(d){return weightScale(d.weight);})\n",
+       "          )\n",
+       "    .force(\"charge\", d3.forceManyBody()\n",
+       "           .strength(charge_force)\n",
+       "           .distanceMax(charge_distance)\n",
+       "          )\n",
+       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
        "    .on(\"tick\", ticked);\n",
        "\n",
        "/*Update of the node and edge objects*/\n",
        "function ticked() {\n",
        "    node.call(updateNode);\n",
        "    link.call(updateLink);\n",
+       "    text.call(updateText);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateLink(link) {\n",
-       "    link\n",
-       "        .attr(\"x1\", function(d) { return d.source.x; })\n",
-       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
-       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
-       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "    // link\n",
+       "    //     .attr(\"x1\", function(d) { return d.source.x; })\n",
+       "    //     .attr(\"y1\", function(d) { return d.source.y; })\n",
+       "    //     .attr(\"x2\", function(d) { return d.target.x; })\n",
+       "    //     .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "\n",
+       "\n",
+       "    link.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    link.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
+       "\n",
        "/*Update node positions */\n",
        "function updateNode(node) {\n",
        "    node.attr(\"transform\", function(d) {\n",
        "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
        "    });\n",
+       "    // node\n",
+       "    //     .attr(\"cx\", function(d) { return d.x; })\n",
+       "    //     .attr(\"cy\", function(d) { return d.y; });\n",
+       "};\n",
+       "\n",
+       "/*Update text positions */\n",
+       "function updateText(text) {\n",
+       "    text.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -1635,10 +2145,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192f4ac50>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5d143670>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1649,7 +2159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1659,23 +2169,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
        "}\n",
        "\n",
-       ".buttonText {\n",
-       "  color: #4e4d4d;\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
+       "\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
+       "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"x6e0902f33bce4095887b94341c28a296\"> </div>\n",
+       "<div id = \"xca95b4a5b37e4ab0a8263ea734b2c792\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -1696,7 +2214,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -1707,8 +2225,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"0-1\", \"source\": \"0\", \"target\": \"1\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-2\", \"source\": \"0\", \"target\": \"2\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-3\", \"source\": \"0\", \"target\": \"3\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-4\", \"source\": \"0\", \"target\": \"4\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-5\", \"source\": \"0\", \"target\": \"5\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-6\", \"source\": \"0\", \"target\": \"6\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-7\", \"source\": \"0\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-8\", \"source\": \"0\", \"target\": \"8\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-10\", \"source\": \"0\", \"target\": \"10\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-11\", \"source\": \"0\", \"target\": \"11\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-12\", \"source\": \"0\", \"target\": \"12\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-13\", \"source\": \"0\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-17\", \"source\": \"0\", \"target\": \"17\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-19\", \"source\": \"0\", \"target\": \"19\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-21\", \"source\": \"0\", \"target\": \"21\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-31\", \"source\": \"0\", \"target\": \"31\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-2\", \"source\": \"1\", \"target\": \"2\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-3\", \"source\": \"1\", \"target\": \"3\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-7\", \"source\": \"1\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-13\", \"source\": \"1\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-17\", \"source\": \"1\", \"target\": \"17\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-19\", \"source\": \"1\", \"target\": \"19\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-21\", \"source\": \"1\", \"target\": \"21\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-30\", \"source\": \"1\", \"target\": \"30\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-3\", \"source\": \"2\", \"target\": \"3\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-7\", \"source\": \"2\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-8\", \"source\": \"2\", \"target\": \"8\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-9\", \"source\": \"2\", \"target\": \"9\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-13\", \"source\": \"2\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-27\", \"source\": \"2\", \"target\": \"27\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-28\", \"source\": \"2\", \"target\": \"28\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-32\", \"source\": \"2\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"3-7\", \"source\": \"3\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"3-12\", \"source\": \"3\", \"target\": \"12\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"3-13\", \"source\": \"3\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"4-6\", \"source\": \"4\", \"target\": \"6\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"4-10\", \"source\": \"4\", \"target\": \"10\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"5-6\", \"source\": \"5\", \"target\": \"6\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"5-10\", \"source\": \"5\", \"target\": \"10\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"5-16\", \"source\": \"5\", \"target\": \"16\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"6-16\", \"source\": \"6\", \"target\": \"16\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"8-30\", \"source\": \"8\", \"target\": \"30\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"8-32\", \"source\": \"8\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"8-33\", \"source\": \"8\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"9-33\", \"source\": \"9\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"13-33\", \"source\": \"13\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"19-33\", \"source\": \"19\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"23-25\", \"source\": \"23\", \"target\": \"25\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"23-29\", \"source\": \"23\", \"target\": \"29\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"25-24\", \"source\": \"25\", \"target\": \"24\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"27-23\", \"source\": \"27\", \"target\": \"23\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"27-24\", \"source\": \"27\", \"target\": \"24\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"27-33\", \"source\": \"27\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"28-33\", \"source\": \"28\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"29-26\", \"source\": \"29\", \"target\": \"26\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"30-32\", \"source\": \"30\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"30-33\", \"source\": \"30\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-24\", \"source\": \"31\", \"target\": \"24\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-25\", \"source\": \"31\", \"target\": \"25\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-28\", \"source\": \"31\", \"target\": \"28\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-32\", \"source\": \"31\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-33\", \"source\": \"31\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-14\", \"source\": \"32\", \"target\": \"14\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-15\", \"source\": \"32\", \"target\": \"15\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-18\", \"source\": \"32\", \"target\": \"18\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-20\", \"source\": \"32\", \"target\": \"20\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-22\", \"source\": \"32\", \"target\": \"22\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-23\", \"source\": \"32\", \"target\": \"23\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-29\", \"source\": \"32\", \"target\": \"29\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-33\", \"source\": \"32\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-14\", \"source\": \"33\", \"target\": \"14\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-15\", \"source\": \"33\", \"target\": \"15\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-18\", \"source\": \"33\", \"target\": \"18\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-20\", \"source\": \"33\", \"target\": \"20\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-23\", \"source\": \"33\", \"target\": \"23\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-26\", \"source\": \"33\", \"target\": \"26\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-29\", \"source\": \"33\", \"target\": \"29\", \"color\": \"gray\", \"weight\": 1}], \"nodes\": [{\"uid\": \"0\", \"color\": \"#00ff00\", \"x\": 0.44299438467996566, \"y\": 0.511128428372227}, {\"uid\": \"1\", \"color\": \"#00ff00\", \"x\": 0.3820773275500381, \"y\": 0.5527052613183674}, {\"uid\": \"2\", \"color\": \"#00ff00\", \"x\": 0.2955994837302057, \"y\": 0.77115650383607}, {\"uid\": \"3\", \"color\": \"#00ff00\", \"x\": 0.7521742152645982, \"y\": 0.3312286554677759}, {\"uid\": \"4\", \"color\": \"#00ff00\", \"x\": 0.840270717549149, \"y\": 0.9099800009326984}, {\"uid\": \"5\", \"color\": \"#00ff00\", \"x\": 0.4749228048249067, \"y\": 0.6056044482434825}, {\"uid\": \"6\", \"color\": \"#00ff00\", \"x\": 0.641944433713229, \"y\": 0.5630131565334746}, {\"uid\": \"7\", \"color\": \"#00ff00\", \"x\": 0.696377803759266, \"y\": 0.639585512067289}, {\"uid\": \"8\", \"color\": \"#00ff00\", \"x\": 0.1588945187910349, \"y\": 0.5927920013424256}, {\"uid\": \"9\", \"color\": \"#ff0000\", \"x\": 0.6155751822721448, \"y\": 0.5247726217118983}, {\"uid\": \"10\", \"color\": \"#00ff00\", \"x\": 0.6578781924748942, \"y\": 0.5911268935582356}, {\"uid\": \"11\", \"color\": \"#00ff00\", \"x\": 0.6415267644382175, \"y\": 0.9057917436644242}, {\"uid\": \"12\", \"color\": \"#00ff00\", \"x\": 0.21343309123801812, \"y\": 0.974152221225963}, {\"uid\": \"13\", \"color\": \"#00ff00\", \"x\": 0.3123012159530263, \"y\": 0.1500584975078798}, {\"uid\": \"14\", \"color\": \"#ff0000\", \"x\": 0.04098964657795323, \"y\": 0.8464782233906714}, {\"uid\": \"15\", \"color\": \"#ff0000\", \"x\": 0.053653059041677054, \"y\": 0.42059659912623637}, {\"uid\": \"16\", \"color\": \"#00ff00\", \"x\": 0.6591882823771819, \"y\": 0.03272402728879609}, {\"uid\": \"17\", \"color\": \"#00ff00\", \"x\": 0.7914113659347299, \"y\": 0.040504153677774046}, {\"uid\": \"18\", \"color\": \"#ff0000\", \"x\": 0.04713525495538062, \"y\": 0.6802059374276778}, {\"uid\": \"19\", \"color\": \"#00ff00\", \"x\": 0.725841412289243, \"y\": 0.230095878754205}, {\"uid\": \"20\", \"color\": \"#ff0000\", \"x\": 0.2957872931176354, \"y\": 0.4022857800369979}, {\"uid\": \"21\", \"color\": \"#00ff00\", \"x\": 0.0711875817353188, \"y\": 0.6817231659436757}, {\"uid\": \"22\", \"color\": \"#ff0000\", \"x\": 0.5799154232335122, \"y\": 0.8859672661774974}, {\"uid\": \"23\", \"color\": \"#ff0000\", \"x\": 0.4535729936197018, \"y\": 0.6795821629534011}, {\"uid\": \"24\", \"color\": \"#ff0000\", \"x\": 0.9306199523591718, \"y\": 0.2307754237507601}, {\"uid\": \"25\", \"color\": \"#ff0000\", \"x\": 0.24472979199756117, \"y\": 0.2612107269031243}, {\"uid\": \"26\", \"color\": \"#ff0000\", \"x\": 0.650620045593157, \"y\": 0.37378363296110395}, {\"uid\": \"27\", \"color\": \"#ff0000\", \"x\": 0.5301589169637992, \"y\": 0.9740296318834606}, {\"uid\": \"28\", \"color\": \"#ff0000\", \"x\": 0.13242470310847587, \"y\": 0.6238463430852181}, {\"uid\": \"29\", \"color\": \"#ff0000\", \"x\": 0.4544316852763701, \"y\": 0.5246922085980148}, {\"uid\": \"30\", \"color\": \"#ff0000\", \"x\": 0.23545219677341434, \"y\": 0.16916699479511355}, {\"uid\": \"31\", \"color\": \"#ff0000\", \"x\": 0.6909254637713599, \"y\": 0.9656032022541213}, {\"uid\": \"32\", \"color\": \"#ff0000\", \"x\": 0.24034658686211174, \"y\": 0.9690585049252692}, {\"uid\": \"33\", \"color\": \"#ff0000\", \"x\": 0.1511573048159729, \"y\": 0.5936876504001527}]}\n",
-       "const config = {\"edge_color\": \"gray\", \"node_color\": [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], \"selector\": \"#x6e0902f33bce4095887b94341c28a296\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"0-2\", \"source\": \"0\", \"target\": \"2\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-1\", \"source\": \"0\", \"target\": \"1\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-31\", \"source\": \"0\", \"target\": \"31\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-21\", \"source\": \"0\", \"target\": \"21\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-19\", \"source\": \"0\", \"target\": \"19\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-17\", \"source\": \"0\", \"target\": \"17\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-13\", \"source\": \"0\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-12\", \"source\": \"0\", \"target\": \"12\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-11\", \"source\": \"0\", \"target\": \"11\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-8\", \"source\": \"0\", \"target\": \"8\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-7\", \"source\": \"0\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-6\", \"source\": \"0\", \"target\": \"6\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-5\", \"source\": \"0\", \"target\": \"5\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-4\", \"source\": \"0\", \"target\": \"4\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-3\", \"source\": \"0\", \"target\": \"3\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"0-10\", \"source\": \"0\", \"target\": \"10\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-7\", \"source\": \"1\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-30\", \"source\": \"1\", \"target\": \"30\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-21\", \"source\": \"1\", \"target\": \"21\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-19\", \"source\": \"1\", \"target\": \"19\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-17\", \"source\": \"1\", \"target\": \"17\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-13\", \"source\": \"1\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-3\", \"source\": \"1\", \"target\": \"3\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"1-2\", \"source\": \"1\", \"target\": \"2\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-3\", \"source\": \"2\", \"target\": \"3\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-32\", \"source\": \"2\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-28\", \"source\": \"2\", \"target\": \"28\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-27\", \"source\": \"2\", \"target\": \"27\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-13\", \"source\": \"2\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-9\", \"source\": \"2\", \"target\": \"9\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-8\", \"source\": \"2\", \"target\": \"8\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"2-7\", \"source\": \"2\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"3-7\", \"source\": \"3\", \"target\": \"7\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"3-12\", \"source\": \"3\", \"target\": \"12\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"3-13\", \"source\": \"3\", \"target\": \"13\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"4-6\", \"source\": \"4\", \"target\": \"6\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"4-10\", \"source\": \"4\", \"target\": \"10\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"5-16\", \"source\": \"5\", \"target\": \"16\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"5-10\", \"source\": \"5\", \"target\": \"10\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"5-6\", \"source\": \"5\", \"target\": \"6\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"6-16\", \"source\": \"6\", \"target\": \"16\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"8-30\", \"source\": \"8\", \"target\": \"30\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"8-32\", \"source\": \"8\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"8-33\", \"source\": \"8\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"9-33\", \"source\": \"9\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"13-33\", \"source\": \"13\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"19-33\", \"source\": \"19\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"23-25\", \"source\": \"23\", \"target\": \"25\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"23-29\", \"source\": \"23\", \"target\": \"29\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"25-24\", \"source\": \"25\", \"target\": \"24\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"27-23\", \"source\": \"27\", \"target\": \"23\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"27-24\", \"source\": \"27\", \"target\": \"24\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"27-33\", \"source\": \"27\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"28-33\", \"source\": \"28\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"29-26\", \"source\": \"29\", \"target\": \"26\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"30-32\", \"source\": \"30\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"30-33\", \"source\": \"30\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-33\", \"source\": \"31\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-25\", \"source\": \"31\", \"target\": \"25\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-32\", \"source\": \"31\", \"target\": \"32\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-24\", \"source\": \"31\", \"target\": \"24\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"31-28\", \"source\": \"31\", \"target\": \"28\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-29\", \"source\": \"32\", \"target\": \"29\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-33\", \"source\": \"32\", \"target\": \"33\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-23\", \"source\": \"32\", \"target\": \"23\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-22\", \"source\": \"32\", \"target\": \"22\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-20\", \"source\": \"32\", \"target\": \"20\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-18\", \"source\": \"32\", \"target\": \"18\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-15\", \"source\": \"32\", \"target\": \"15\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"32-14\", \"source\": \"32\", \"target\": \"14\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-14\", \"source\": \"33\", \"target\": \"14\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-15\", \"source\": \"33\", \"target\": \"15\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-18\", \"source\": \"33\", \"target\": \"18\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-20\", \"source\": \"33\", \"target\": \"20\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-23\", \"source\": \"33\", \"target\": \"23\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-26\", \"source\": \"33\", \"target\": \"26\", \"color\": \"gray\", \"weight\": 1}, {\"uid\": \"33-29\", \"source\": \"33\", \"target\": \"29\", \"color\": \"gray\", \"weight\": 1}], \"nodes\": [{\"uid\": \"0\", \"color\": \"#00ff00\"}, {\"uid\": \"1\", \"color\": \"#00ff00\"}, {\"uid\": \"2\", \"color\": \"#00ff00\"}, {\"uid\": \"3\", \"color\": \"#00ff00\"}, {\"uid\": \"4\", \"color\": \"#00ff00\"}, {\"uid\": \"5\", \"color\": \"#00ff00\"}, {\"uid\": \"6\", \"color\": \"#00ff00\"}, {\"uid\": \"7\", \"color\": \"#00ff00\"}, {\"uid\": \"8\", \"color\": \"#00ff00\"}, {\"uid\": \"9\", \"color\": \"#ff0000\"}, {\"uid\": \"10\", \"color\": \"#00ff00\"}, {\"uid\": \"11\", \"color\": \"#00ff00\"}, {\"uid\": \"12\", \"color\": \"#00ff00\"}, {\"uid\": \"13\", \"color\": \"#00ff00\"}, {\"uid\": \"14\", \"color\": \"#ff0000\"}, {\"uid\": \"15\", \"color\": \"#ff0000\"}, {\"uid\": \"16\", \"color\": \"#00ff00\"}, {\"uid\": \"17\", \"color\": \"#00ff00\"}, {\"uid\": \"18\", \"color\": \"#ff0000\"}, {\"uid\": \"19\", \"color\": \"#00ff00\"}, {\"uid\": \"20\", \"color\": \"#ff0000\"}, {\"uid\": \"21\", \"color\": \"#00ff00\"}, {\"uid\": \"22\", \"color\": \"#ff0000\"}, {\"uid\": \"23\", \"color\": \"#ff0000\"}, {\"uid\": \"24\", \"color\": \"#ff0000\"}, {\"uid\": \"25\", \"color\": \"#ff0000\"}, {\"uid\": \"26\", \"color\": \"#ff0000\"}, {\"uid\": \"27\", \"color\": \"#ff0000\"}, {\"uid\": \"28\", \"color\": \"#ff0000\"}, {\"uid\": \"29\", \"color\": \"#ff0000\"}, {\"uid\": \"30\", \"color\": \"#ff0000\"}, {\"uid\": \"31\", \"color\": \"#ff0000\"}, {\"uid\": \"32\", \"color\": \"#ff0000\"}, {\"uid\": \"33\", \"color\": \"#ff0000\"}]}\n",
+       "const config = {\"edge_color\": \"gray\", \"node_color\": [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], \"directed\": true, \"curved\": true, \"selector\": \"#xca95b4a5b37e4ab0a8263ea734b2c792\"}\n",
        "console.log(\"Static Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -1717,8 +2235,13 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
+       "const charge_distance = config.charge_distance || 400;\n",
+       "const charge_force = config.charge_force || -3000;\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
+       "// const weight = false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "var svg = d3.select(selector)\n",
@@ -1741,16 +2264,42 @@
        "var nodes = data.nodes\n",
        "var links = data.edges\n",
        "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Link creation template */\n",
        "var link = container.append(\"g\").attr(\"class\", \"links\")\n",
        "    .selectAll(\".link\")\n",
        "    .data(links)\n",
        "    .enter()\n",
-       "    .append(\"line\")\n",
+       "    .append(\"path\")\n",
        "    .attr(\"class\", \"link\")\n",
        "    .style(\"stroke\", function(d) { return d.color; })\n",
        "    .style(\"stroke-opacity\", function(d) { return d.opacity; })\n",
-       "    .style(\"stroke-width\", function(d){  return d.size });\n",
+       "    .style(\"stroke-width\", function(d){  return d.size })\n",
+       "    .style(\"fill\",\"none\")\n",
+       "    .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
+       "\n",
+       "    //.attr(\"marker-end\", function (d) { return marker(d.color); });\n",
+       "    //.attr(\"marker-end\", \"url(#arrow)\");\n",
        "\n",
        "/*Node creation template */\n",
        "var node = container.append(\"g\").attr(\"class\", \"nodes\")\n",
@@ -1764,38 +2313,98 @@
        "    .style(\"fill\", function(d) { return d.color; })\n",
        "    .style(\"opacity\", function(d) { return d.opacity; });\n",
        "\n",
+       "/*Label creation template */\n",
+       "var text = container.append(\"g\").attr(\"class\",\"labels\")\n",
+       "    .selectAll(\"g\")\n",
+       "    .data(nodes)\n",
+       "    .enter().append(\"g\")\n",
+       "\n",
+       "text.append(\"text\")\n",
+       "    .attr(\"class\", \"label-text\")\n",
+       "    .attr(\"x\", function(d) {\n",
+       "        var r = (d.size === undefined) ? 15 : d.size;\n",
+       "        return 5 + r; })\n",
+       "    .attr(\"dy\", \".31em\")\n",
+       "    .text(function(d) { return d.label; });\n",
+       "\n",
+       "/*Scale weight for d3js */\n",
+       "var weightScale = d3.scaleLinear()\n",
+       "    .domain(d3.extent(links, function (d) { return d.weight }))\n",
+       "    .range([.1, 1]);\n",
        "\n",
        "/*Simulation of the forces*/\n",
        "var simulation = d3.forceSimulation(nodes)\n",
-       "    .force(\"charge\", d3.forceManyBody().strength(-3000))\n",
-       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
-       "    .force(\"x\", d3.forceX(width / 2).strength(1))\n",
-       "    .force(\"y\", d3.forceY(height / 2).strength(1))\n",
        "    .force(\"links\", d3.forceLink(links)\n",
        "           .id(function(d) {return d.uid; })\n",
-       "           .distance(50).strength(function(d){return d.weight;}))\n",
+       "           .distance(50)\n",
+       "           .strength(function(d){return weightScale(d.weight);})\n",
+       "          )\n",
+       "    .force(\"charge\", d3.forceManyBody()\n",
+       "           .strength(charge_force)\n",
+       "           .distanceMax(charge_distance)\n",
+       "          )\n",
+       "    .force(\"center\", d3.forceCenter(width / 2, height / 2))\n",
        "    .on(\"tick\", ticked);\n",
        "\n",
        "/*Update of the node and edge objects*/\n",
        "function ticked() {\n",
        "    node.call(updateNode);\n",
        "    link.call(updateLink);\n",
+       "    text.call(updateText);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateLink(link) {\n",
-       "    link\n",
-       "        .attr(\"x1\", function(d) { return d.source.x; })\n",
-       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
-       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
-       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "    // link\n",
+       "    //     .attr(\"x1\", function(d) { return d.source.x; })\n",
+       "    //     .attr(\"y1\", function(d) { return d.source.y; })\n",
+       "    //     .attr(\"x2\", function(d) { return d.target.x; })\n",
+       "    //     .attr(\"y2\", function(d) { return d.target.y; });\n",
+       "\n",
+       "\n",
+       "    link.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    link.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
+       "\n",
        "/*Update node positions */\n",
        "function updateNode(node) {\n",
        "    node.attr(\"transform\", function(d) {\n",
        "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
        "    });\n",
+       "    // node\n",
+       "    //     .attr(\"cx\", function(d) { return d.x; })\n",
+       "    //     .attr(\"cy\", function(d) { return d.y; });\n",
+       "};\n",
+       "\n",
+       "/*Update text positions */\n",
+       "function updateText(text) {\n",
+       "    text.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -1835,10 +2444,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7fe192f49900>"
+       "<pathpyG.visualisations.network_plots.StaticNetworkPlot at 0x7f9b5d140880>"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1859,7 +2468,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1877,7 +2486,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1887,23 +2496,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
+       "}\n",
+       "\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
        "\n",
-       ".labelText {\n",
-       "  fill: #4e4d4d;\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
        "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"x0e565812260d439b9d279546aade0908\"> </div>\n",
+       "<div id = \"xad4df62641e244ea8ec8c63f244c985d\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -1924,7 +2541,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -1935,8 +2552,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"a-b-1\", \"source\": \"a\", \"target\": \"b\", \"start\": 1, \"end\": 2, \"weight\": 1}, {\"uid\": \"b-c-5\", \"source\": \"b\", \"target\": \"c\", \"start\": 5, \"end\": 6, \"weight\": 1}, {\"uid\": \"c-d-9\", \"source\": \"c\", \"target\": \"d\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"d-a-9\", \"source\": \"d\", \"target\": \"a\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"a-b-10\", \"source\": \"a\", \"target\": \"b\", \"start\": 10, \"end\": 11, \"weight\": 1}, {\"uid\": \"b-c-10\", \"source\": \"b\", \"target\": \"c\", \"start\": 10, \"end\": 11, \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"start\": 0, \"end\": 11, \"x\": 0.906967507567079, \"y\": 0.6268052634965343}, {\"uid\": \"b\", \"start\": 0, \"end\": 11, \"x\": 0.1644599361908876, \"y\": 0.6942465825204079}, {\"uid\": \"c\", \"start\": 0, \"end\": 11, \"x\": 0.6872480127194887, \"y\": 0.5748514831037128}, {\"uid\": \"d\", \"start\": 0, \"end\": 11, \"x\": 0.18865650928412359, \"y\": 0.09722359575147}]}\n",
-       "const config = {\"end\": 11, \"start\": 0, \"selector\": \"#x0e565812260d439b9d279546aade0908\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"a-b-1.0\", \"source\": \"a\", \"target\": \"b\", \"start\": 1, \"end\": 2, \"weight\": 1}, {\"uid\": \"b-c-5.0\", \"source\": \"b\", \"target\": \"c\", \"start\": 5, \"end\": 6, \"weight\": 1}, {\"uid\": \"c-d-9.0\", \"source\": \"c\", \"target\": \"d\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"d-a-9.0\", \"source\": \"d\", \"target\": \"a\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"a-b-10.0\", \"source\": \"a\", \"target\": \"b\", \"start\": 10, \"end\": 11, \"weight\": 1}, {\"uid\": \"b-c-10.0\", \"source\": \"b\", \"target\": \"c\", \"start\": 10, \"end\": 11, \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"start\": 0, \"end\": 11}, {\"uid\": \"b\", \"start\": 0, \"end\": 11}, {\"uid\": \"c\", \"start\": 0, \"end\": 11}, {\"uid\": \"d\", \"start\": 0, \"end\": 11}]}\n",
+       "const config = {\"end\": 11, \"start\": 0, \"directed\": true, \"curved\": true, \"selector\": \"#xad4df62641e244ea8ec8c63f244c985d\"}\n",
        "console.log(\"Temporal Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -1948,8 +2565,8 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
        "const delta = config.delta || 300;\n",
        "\n",
        "// variables for the temporal components\n",
@@ -1958,6 +2575,9 @@
        "const targetValue = config.intervals || 300;\n",
        "const duration = config.delta || 300;  \n",
        "\n",
+       "// variables for the edge components\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "let svg = d3.select(selector)\n",
@@ -1976,32 +2596,58 @@
        "let nodes = container.append(\"g\").attr(\"class\", \"nodes\")\n",
        "    .selectAll(\"circle.node\");\n",
        "\n",
+       "/*Label creation template */\n",
+       "let labels = container.append(\"g\").attr(\"class\", \"labels\")\n",
+       "    .selectAll(\".label\");\n",
+       "\n",
        "/*Time counter */\n",
        "let text = svg.append(\"text\")\n",
        "    .text(\"T=\"+startTime)\n",
        "    .attr(\"x\", 20)\n",
-       "    .attr(\"y\", 20)\n",
-       "    .attr(\"class\", \"labelText\");\n",
+       "    .attr(\"y\", 20);\n",
        "\n",
        "let bttn = svg.append(\"text\")\n",
        "    .attr(\"x\",70)\n",
        "    .attr(\"y\", 20)\n",
-       "    .text(\"Play\")\n",
-       "    .attr(\"class\", \"labelText\");\n",
+       "    .text(\"Play\");\n",
        "\n",
        "/*Assign data to variable*/\n",
        "let network = data\n",
        "\n",
+       "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Render function to show dynamic networks*/\n",
        "function render(){\n",
        "\n",
        "    // get network data\n",
        "    let nodeData = network.nodes;\n",
        "    let edgeData = network.edges;\n",
+       "    // let labelData = network.nodes;\n",
        "\n",
        "    // render network objects\n",
        "    renderNodes(nodeData);\n",
        "    renderEdges(edgeData);\n",
+       "    renderLabels(nodeData);\n",
        "\n",
        "    // run simulation\n",
        "    simulation.nodes(nodeData);\n",
@@ -2017,36 +2663,57 @@
        "\n",
        "    let new_nodes = nodes.enter().append(\"circle\")\n",
        "        .attr(\"class\", \"node\")\n",
-       "        .style(\"r\", d => d.size)\n",
+       "        .style(\"r\", function(d){  return d.size+\"px\"; })\n",
        "        .style(\"fill\", d => d.color)\n",
        "        .style(\"opacity\", d => d.opacity)\n",
        "        .call(drag);\n",
-       "\n",
+       "    \n",
        "    nodes.exit()\n",
        "        .transition() // transition to shrink node\n",
        "        .duration(delta)\n",
        "        .style(\"r\", \"0px\")\n",
        "        .remove();\n",
-       "\n",
+       "    \n",
        "    nodes = nodes.merge(new_nodes);\n",
        "\n",
        "    nodes.transition() // transition to change size and color\n",
        "        .duration(delta)\n",
-       "        .style(\"r\", d => d.size)\n",
+       "        .style(\"r\", function(d){  return d.size+\"px\"; })\n",
        "        .style(\"fill\", d => d.color)\n",
        "        .style(\"opacity\", d => d.opacity);\n",
        "};\n",
        "\n",
+       "/*Render label objects*/\n",
+       "function renderLabels(data){\n",
+       "    // console.log(\"render Nodes\")\n",
+       "    \n",
+       "    labels = container.select('.nodes').selectAll('.label-text').data(data, d=> d.uid);\n",
+       "\n",
+       "    let new_labels = labels.enter().append(\"text\")\n",
+       "        .attr(\"class\", \"label-text\")\n",
+       "        .attr(\"x\", function(d) {\n",
+       "            var r = (d.size === undefined) ? 15 : d.size;\n",
+       "            return 5 + r; })\n",
+       "        .attr(\"dy\", \".32em\")\n",
+       "        .text(d=>d.label);\n",
+       "    \n",
+       "    labels.exit().remove();\n",
+       "\n",
+       "    labels = labels.merge(new_labels);\n",
+       "};\n",
+       "\n",
        "/*Render edge objects*/\n",
        "function renderEdges(data){\n",
        "    // console.log(\"render Edges\")\n",
        "    edges = container.select(\".edges\").selectAll(\".link\").data(data, d=> d.uid);\n",
        "\n",
-       "    let new_edges =  edges.enter().append(\"line\")\n",
+       "    let new_edges =  edges.enter().append(\"path\")\n",
        "        .attr(\"class\", \"link\")\n",
        "        .style(\"stroke\", d => d.color)\n",
        "        .style(\"stroke-opacity\", d => d.opacity)\n",
-       "        .style(\"stroke-width\", d => d.size);\n",
+       "        .style(\"stroke-width\", d => d.size)\n",
+       "        .style(\"fill\",\"none\")\n",
+       "        .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
        "\n",
        "    edges.exit().remove();\n",
        "\n",
@@ -2083,22 +2750,60 @@
        "function ticked() {\n",
        "    nodes.call(updateNodePositions);\n",
        "    edges.call(updateEdgePositions);\n",
+       "    labels.call(updateLabelPositions);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateEdgePositions(edges) {\n",
-       "    edges\n",
-       "        .attr(\"x1\", d => d.source.x)\n",
-       "        .attr(\"y1\", d => d.source.y)\n",
-       "        .attr(\"x2\", d => d.target.x)\n",
-       "        .attr(\"y2\", d => d.target.y);\n",
+       "    // edges\n",
+       "    //     .attr(\"x1\", d => d.source.x)\n",
+       "    //     .attr(\"y1\", d => d.source.y)\n",
+       "    //     .attr(\"x2\", d => d.target.x)\n",
+       "    //     .attr(\"y2\", d => d.target.y);\n",
+       "\n",
+       "    edges.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    edges.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Update node positions */\n",
        "function updateNodePositions(nodes) {\n",
-       "    nodes\n",
-       "        .attr(\"cx\", d => d.x)\n",
-       "        .attr(\"cy\", d => d.y);\n",
+       "    nodes.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
+       "    // nodes\n",
+       "    //     .attr(\"cx\", d => d.x)\n",
+       "    //     .attr(\"cy\", d => d.y);\n",
+       "};\n",
+       "\n",
+       "\n",
+       "/*Update node positions */\n",
+       "function updateLabelPositions(labels) {\n",
+       "    labels.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -2200,10 +2905,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.TemporalNetworkPlot at 0x7fe192f4aa70>"
+       "<pathpyG.visualisations.network_plots.TemporalNetworkPlot at 0x7f9b5d143550>"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2221,7 +2926,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 19,
    "metadata": {
     "scrolled": true
    },
@@ -2233,23 +2938,31 @@
        "svg circle.node {\n",
        "  fill: #3b5998;\n",
        "  stroke: #1b3978;\n",
-       "  stroke-width: 5.5px;\n",
+       "  stroke-width: 2.5px;\n",
        "  r: 15px;\n",
        "  opacity: 1;\n",
        "}\n",
        "\n",
        ".link {\n",
-       "  stroke: #4e4d4d;\n",
-       "  stroke-opacity: .6;\n",
-       "  stroke-width: 4px;\n",
+       "  stroke: #969595;\n",
+       "  stroke-opacity: .75;\n",
+       "  stroke-width: 2.5px;\n",
+       "}\n",
+       "\n",
+       ".arrow {\n",
+       "  fill: #969595;\n",
        "}\n",
        "\n",
-       ".labelText {\n",
-       "  fill: #4e4d4d;\n",
+       "\n",
+       ".label-text {\n",
+       "    fill: #969595;\n",
+       "    font-size: 16px;\n",
+       "    font-family: sans-serif;\n",
        "}\n",
+       "\n",
        "</style>\n",
        "\n",
-       "<div id = \"xa47215df978048f6a1727e2df5375e60\"> </div>\n",
+       "<div id = \"x83b1fdb7db744d0ea4adb9033bab16b5\"> </div>\n",
        "<script charset=\"utf-8\" src=\"https://d3js.org/d3.v5.min.js\"></script>\n",
        "<script charset=\"utf-8\">\n",
        "// Load via requireJS if available (jupyter notebook environment)\n",
@@ -2270,7 +2983,7 @@
        "\n",
        "        // Helper function that waits for d3js to be loaded\n",
        "        require = function require(symbols, callback) {\n",
-       "            var ms = 5;\n",
+       "            var ms = 10;\n",
        "            window.setTimeout(function(t) {\n",
        "                if (window[symbols[0]])\n",
        "                    callback(window[symbols[0]]);\n",
@@ -2281,8 +2994,8 @@
        "    }\n",
        "};\n",
        "require(['d3'], function(d3){ //START\n",
-       "const data = {\"edges\": [{\"uid\": \"a-b-1\", \"source\": \"a\", \"target\": \"b\", \"start\": 1, \"end\": 2, \"weight\": 1}, {\"uid\": \"b-c-5\", \"source\": \"b\", \"target\": \"c\", \"start\": 5, \"end\": 6, \"weight\": 1}, {\"uid\": \"c-d-9\", \"source\": \"c\", \"target\": \"d\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"d-a-9\", \"source\": \"d\", \"target\": \"a\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"a-b-10\", \"source\": \"a\", \"target\": \"b\", \"start\": 10, \"end\": 11, \"weight\": 1}, {\"uid\": \"b-c-10\", \"source\": \"b\", \"target\": \"c\", \"start\": 10, \"end\": 11, \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"start\": 0, \"end\": 11, \"color\": \"blue\", \"x\": 0.29014880808206867, \"y\": 0.9132228481802602}, {\"uid\": \"b\", \"start\": 0, \"end\": 11, \"color\": \"red\", \"x\": 0.34930717374489373, \"y\": 0.21186580802088928}, {\"uid\": \"c\", \"start\": 0, \"end\": 11, \"color\": \"green\", \"x\": 0.9923568567207832, \"y\": 0.8699045589222012}, {\"uid\": \"d\", \"start\": 0, \"end\": 11, \"color\": \"yellow\", \"x\": 0.6440859442417113, \"y\": 0.05013964071658106}]}\n",
-       "const config = {\"node_color\": {\"a\": \"blue\", \"b\": \"red\", \"c\": \"green\", \"d\": \"yellow\"}, \"start\": -1, \"end\": 25, \"delta\": 1000, \"selector\": \"#xa47215df978048f6a1727e2df5375e60\"}\n",
+       "const data = {\"edges\": [{\"uid\": \"a-b-1.0\", \"source\": \"a\", \"target\": \"b\", \"start\": 1, \"end\": 2, \"weight\": 1}, {\"uid\": \"b-c-5.0\", \"source\": \"b\", \"target\": \"c\", \"start\": 5, \"end\": 6, \"weight\": 1}, {\"uid\": \"c-d-9.0\", \"source\": \"c\", \"target\": \"d\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"d-a-9.0\", \"source\": \"d\", \"target\": \"a\", \"start\": 9, \"end\": 10, \"weight\": 1}, {\"uid\": \"a-b-10.0\", \"source\": \"a\", \"target\": \"b\", \"start\": 10, \"end\": 11, \"weight\": 1}, {\"uid\": \"b-c-10.0\", \"source\": \"b\", \"target\": \"c\", \"start\": 10, \"end\": 11, \"weight\": 1}], \"nodes\": [{\"uid\": \"a\", \"start\": 0, \"end\": 11, \"color\": \"blue\"}, {\"uid\": \"b\", \"start\": 0, \"end\": 11, \"color\": \"red\"}, {\"uid\": \"c\", \"start\": 0, \"end\": 11, \"color\": \"green\"}, {\"uid\": \"d\", \"start\": 0, \"end\": 11, \"color\": \"yellow\"}]}\n",
+       "const config = {\"node_color\": {\"a\": \"blue\", \"b\": \"red\", \"c\": \"green\", \"d\": \"yellow\"}, \"start\": -1, \"end\": 25, \"delta\": 1000, \"directed\": true, \"curved\": true, \"selector\": \"#x83b1fdb7db744d0ea4adb9033bab16b5\"}\n",
        "console.log(\"Temporal Network Template\");\n",
        "/* Resources\n",
        "   https://bl.ocks.org/mapio/53fed7d84cd1812d6a6639ed7aa83868\n",
@@ -2294,8 +3007,8 @@
        "\n",
        "// variables from the config file\n",
        "const selector = config.selector;\n",
-       "const width = config.width || 400;\n",
-       "const height = config.height || 400;\n",
+       "const width = config.width || 800;\n",
+       "const height = config.height || 600;\n",
        "const delta = config.delta || 300;\n",
        "\n",
        "// variables for the temporal components\n",
@@ -2304,6 +3017,9 @@
        "const targetValue = config.intervals || 300;\n",
        "const duration = config.delta || 300;  \n",
        "\n",
+       "// variables for the edge components\n",
+       "const curved = config.curved || false;\n",
+       "const directed = config.directed || false;\n",
        "\n",
        "/* Create a svg element to display the network */\n",
        "let svg = d3.select(selector)\n",
@@ -2322,32 +3038,58 @@
        "let nodes = container.append(\"g\").attr(\"class\", \"nodes\")\n",
        "    .selectAll(\"circle.node\");\n",
        "\n",
+       "/*Label creation template */\n",
+       "let labels = container.append(\"g\").attr(\"class\", \"labels\")\n",
+       "    .selectAll(\".label\");\n",
+       "\n",
        "/*Time counter */\n",
        "let text = svg.append(\"text\")\n",
        "    .text(\"T=\"+startTime)\n",
        "    .attr(\"x\", 20)\n",
-       "    .attr(\"y\", 20)\n",
-       "    .attr(\"class\", \"labelText\");\n",
+       "    .attr(\"y\", 20);\n",
        "\n",
        "let bttn = svg.append(\"text\")\n",
        "    .attr(\"x\",70)\n",
        "    .attr(\"y\", 20)\n",
-       "    .text(\"Play\")\n",
-       "    .attr(\"class\", \"labelText\");\n",
+       "    .text(\"Play\");\n",
        "\n",
        "/*Assign data to variable*/\n",
        "let network = data\n",
        "\n",
+       "\n",
+       "/*Create arrow head with same color as the edge */\n",
+       "function marker (color) {\n",
+       "       var reference;\n",
+       "       svg.append(\"svg:defs\").selectAll(\"marker\")\n",
+       "          .data([reference])\n",
+       "          .enter().append(\"svg:marker\")\n",
+       "          .attr(\"id\", \"arrow\"+color)\n",
+       "          .attr(\"viewBox\", \"0 -5 10 10\")\n",
+       "          .attr(\"refX\", 10)\n",
+       "          .attr(\"refY\", -0)\n",
+       "          .attr(\"markerWidth\", 6)\n",
+       "          .attr(\"markerHeight\", 6)\n",
+       "          .attr(\"orient\", \"auto\")\n",
+       "          .append(\"svg:path\")\n",
+       "          .attr('class','.arrow')\n",
+       "          .attr(\"d\", \"M0,-5L10,0L0,5\")\n",
+       "          .style('opacity',1)\n",
+       "          .style(\"fill\", color);\n",
+       "       return \"url(#\" + \"arrow\"+color + \")\";\n",
+       "     };\n",
+       "\n",
        "/*Render function to show dynamic networks*/\n",
        "function render(){\n",
        "\n",
        "    // get network data\n",
        "    let nodeData = network.nodes;\n",
        "    let edgeData = network.edges;\n",
+       "    // let labelData = network.nodes;\n",
        "\n",
        "    // render network objects\n",
        "    renderNodes(nodeData);\n",
        "    renderEdges(edgeData);\n",
+       "    renderLabels(nodeData);\n",
        "\n",
        "    // run simulation\n",
        "    simulation.nodes(nodeData);\n",
@@ -2363,36 +3105,57 @@
        "\n",
        "    let new_nodes = nodes.enter().append(\"circle\")\n",
        "        .attr(\"class\", \"node\")\n",
-       "        .style(\"r\", d => d.size)\n",
+       "        .style(\"r\", function(d){  return d.size+\"px\"; })\n",
        "        .style(\"fill\", d => d.color)\n",
        "        .style(\"opacity\", d => d.opacity)\n",
        "        .call(drag);\n",
-       "\n",
+       "    \n",
        "    nodes.exit()\n",
        "        .transition() // transition to shrink node\n",
        "        .duration(delta)\n",
        "        .style(\"r\", \"0px\")\n",
        "        .remove();\n",
-       "\n",
+       "    \n",
        "    nodes = nodes.merge(new_nodes);\n",
        "\n",
        "    nodes.transition() // transition to change size and color\n",
        "        .duration(delta)\n",
-       "        .style(\"r\", d => d.size)\n",
+       "        .style(\"r\", function(d){  return d.size+\"px\"; })\n",
        "        .style(\"fill\", d => d.color)\n",
        "        .style(\"opacity\", d => d.opacity);\n",
        "};\n",
        "\n",
+       "/*Render label objects*/\n",
+       "function renderLabels(data){\n",
+       "    // console.log(\"render Nodes\")\n",
+       "    \n",
+       "    labels = container.select('.nodes').selectAll('.label-text').data(data, d=> d.uid);\n",
+       "\n",
+       "    let new_labels = labels.enter().append(\"text\")\n",
+       "        .attr(\"class\", \"label-text\")\n",
+       "        .attr(\"x\", function(d) {\n",
+       "            var r = (d.size === undefined) ? 15 : d.size;\n",
+       "            return 5 + r; })\n",
+       "        .attr(\"dy\", \".32em\")\n",
+       "        .text(d=>d.label);\n",
+       "    \n",
+       "    labels.exit().remove();\n",
+       "\n",
+       "    labels = labels.merge(new_labels);\n",
+       "};\n",
+       "\n",
        "/*Render edge objects*/\n",
        "function renderEdges(data){\n",
        "    // console.log(\"render Edges\")\n",
        "    edges = container.select(\".edges\").selectAll(\".link\").data(data, d=> d.uid);\n",
        "\n",
-       "    let new_edges =  edges.enter().append(\"line\")\n",
+       "    let new_edges =  edges.enter().append(\"path\")\n",
        "        .attr(\"class\", \"link\")\n",
        "        .style(\"stroke\", d => d.color)\n",
        "        .style(\"stroke-opacity\", d => d.opacity)\n",
-       "        .style(\"stroke-width\", d => d.size);\n",
+       "        .style(\"stroke-width\", d => d.size)\n",
+       "        .style(\"fill\",\"none\")\n",
+       "        .attr(\"marker-end\", function (d) {if(directed){return marker(d.color)}else{return null}; });\n",
        "\n",
        "    edges.exit().remove();\n",
        "\n",
@@ -2429,22 +3192,60 @@
        "function ticked() {\n",
        "    nodes.call(updateNodePositions);\n",
        "    edges.call(updateEdgePositions);\n",
+       "    labels.call(updateLabelPositions);\n",
        "};\n",
        "\n",
        "/*Update link positions */\n",
        "function updateEdgePositions(edges) {\n",
-       "    edges\n",
-       "        .attr(\"x1\", d => d.source.x)\n",
-       "        .attr(\"y1\", d => d.source.y)\n",
-       "        .attr(\"x2\", d => d.target.x)\n",
-       "        .attr(\"y2\", d => d.target.y);\n",
+       "    // edges\n",
+       "    //     .attr(\"x1\", d => d.source.x)\n",
+       "    //     .attr(\"y1\", d => d.source.y)\n",
+       "    //     .attr(\"x2\", d => d.target.x)\n",
+       "    //     .attr(\"y2\", d => d.target.y);\n",
+       "\n",
+       "    edges.attr(\"d\", function(d) {\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        return \"M\" +\n",
+       "            d.source.x + \",\" +\n",
+       "            d.source.y + \"A\" +\n",
+       "            dr + \",\" + dr + \" 0 0,1 \" +\n",
+       "            d.target.x + \",\" +\n",
+       "            d.target.y;\n",
+       "    });\n",
+       "\n",
+       "    // recalculate and back off the distance\n",
+       "    edges.attr(\"d\", function (d, i) {\n",
+       "        var pl = this.getTotalLength();\n",
+       "        var r = (d.target.size === undefined) ? 15 : d.target.size;\n",
+       "        var m = this.getPointAtLength(pl - r);\n",
+       "        var dx = d.target.x - d.source.x,\n",
+       "            dy = d.target.y - d.source.y,\n",
+       "            dr = Math.sqrt(dx * dx + dy * dy);\n",
+       "        if(!curved)dr=0;\n",
+       "        var result = \"M\" + d.source.x + \",\" + d.source.y + \"A\" + dr + \",\" + dr + \" 0 0,1 \" + m.x + \",\" + m.y;\n",
+       "        return result;\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Update node positions */\n",
        "function updateNodePositions(nodes) {\n",
-       "    nodes\n",
-       "        .attr(\"cx\", d => d.x)\n",
-       "        .attr(\"cy\", d => d.y);\n",
+       "    nodes.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
+       "    // nodes\n",
+       "    //     .attr(\"cx\", d => d.x)\n",
+       "    //     .attr(\"cy\", d => d.y);\n",
+       "};\n",
+       "\n",
+       "\n",
+       "/*Update node positions */\n",
+       "function updateLabelPositions(labels) {\n",
+       "    labels.attr(\"transform\", function(d) {\n",
+       "        return \"translate(\" + d.x + \",\" + d.y + \")\";\n",
+       "    });\n",
        "};\n",
        "\n",
        "/*Add drag functionality to the node objects*/\n",
@@ -2546,10 +3347,10 @@
     {
      "data": {
       "text/plain": [
-       "<pathpyG.visualisations.network_plots.TemporalNetworkPlot at 0x7fe192f49b10>"
+       "<pathpyG.visualisations.network_plots.TemporalNetworkPlot at 0x7f9b5d1415d0>"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }