Migrate dashboard

FANS_Dashboard/FANS_Dashboard.ipynb

@@ -51,10 +51,10 @@
    "outputs": [],
    "source": [
     "import numpy as np\n",
-    "from fans_dashboard.core.utils import *\n",
-    "from fans_dashboard.core.postprocessing import compute_rank2tensor_measures\n",
+    "from MSUtils.fans_dashboard.utils import *\n",
+    "from MSUtils.fans_dashboard.postprocessing import compute_rank2tensor_measures\n",
     "from MSUtils.general.h52xdmf import write_xdmf\n",
-    "from fans_dashboard.plotting.plotting import plot_subplots"
+    "from MSUtils.fans_dashboard.plotting import plot_subplots"
    ]
   },
   {

FANS_Dashboard/README.md

@@ -1,5 +1,5 @@
 # FANS Dashboard
 
-The FANS Dashboard is a comprehensive tool designed to streamline the post-processing, interpretation, and visualization of results generated by the FANS solver. This jupyter notebook provides a user-friendly environment to work with complex simulation data stored in HDF5 format, offering a step-by-step workflow that covers data extraction, postprocessing, visualization, and preparation for 3D visualization in tools like ParaView.
+The FANS Dashboard is a comprehensive tool designed to streamline the post-processing, interpretation, and visualization of results generated by the FANS solver. It uses helper functions from [MSUtils](https://github.com/DataAnalyticsEngineering/MSUtils) to facilitate various tasks. This jupyter notebook provides an exemplary pipeline and a user-friendly environment to work with complex simulation data stored in HDF5 format, offering a step-by-step workflow that covers data extraction, postprocessing, visualization, and preparation for 3D visualization in tools like ParaView.
 
 For further details follow along [`FANS_Dashboard.ipynb`](FANS_Dashboard.ipynb)