[update] dockerfile, notebook and readme

Dockerfile

@@ -38,6 +38,7 @@ RUN pip install -e .
 WORKDIR /app
 
 COPY Tutorial.ipynb /app
+COPY Explore_Data.ipynb /app
 COPY *.py /app/
 
 EXPOSE 8989 5000

Explore_Data.ipynb

@@ -0,0 +1,94 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "250ef129-c335-4f6c-97ea-afc865ca2fda",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "860bbfe3-fe43-4a7a-b937-e801b3fd437e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data=np.load('data3.npz')\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5cf68811-44dc-4bb4-8ff7-03275a167ff7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "actual_data=data['data']\n",
+    "metadata=data['lon_lat']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3e6f6b65-5cb4-4515-b163-67229880b966",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cmap_instance = plt.get_cmap(\"inferno\")\n",
+    "lat_min=metadata[0][0]\n",
+    "lat_max=metadata[0][1]\n",
+    "lon_min=metadata[1][0]\n",
+    "lon_max=metadata[1][1]\n",
+    "fig, axs = plt.subplots(1, 1, figsize=(10, 8))\n",
+    "axs.set_xlim(lat_min, lat_max)\n",
+    "axs.set_ylim(lon_min, lon_max)\n",
+    "axs.set_title(\"Selected Sub-Region Of Interest\")\n",
+    "axs.set_xlabel(\"Longitude (Degrees)\")\n",
+    "axs.set_ylabel(\"Latitude (Degrees)\")\n",
+    "data_fig = axs.imshow(\n",
+    "    actual_data,\n",
+    "    cmap=cmap_instance,\n",
+    "    origin=\"lower\",\n",
+    "    vmin=30,\n",
+    "    vmax=1999,\n",
+    "    extent=(lat_min, lat_max, lon_min, lon_max),\n",
+    ")\n",
+    "\n",
+    "cbar = fig.colorbar(\n",
+    "    data_fig,\n",
+    "    fraction=0.046 * actual_data.shape[0] / actual_data.shape[1],\n",
+    "    pad=0.04,\n",
+    ")\n",
+    "cbar_ticks = np.linspace(30, 1999, 8)\n",
+    "cbar.set_ticks(cbar_ticks)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

README.md

@@ -46,10 +46,12 @@ This tutorial follows the steps in Figure 1.
 
 ## Prerequisites
 
+> :bulb: **Note:** To follow this tutorial you must have a computer with minimum **8 GB of RAM** and **5 GB of free disk** 
+
 Before starting this tutorial, ensure you have installed Git and Docker Desktop on your computer.
 
 * **To install Git**: Follow the [installation instructions](https://github.com/git-guides/install-git) for your operating system (Linux, Windows, or Mac).
-* **To install Docker Desktop**: Follow the [installation instructions](https://docs.docker.com/engine/install/) for your operating system (Linux, Windows, or Mac).
+* **To install Docker Desktop**: Follow the [installation instructions](https://docs.docker.com/engine/install/) for your operating system (Linux, Windows, or Mac). ***Be sure you are running the most recent version of Docker! Previous versions to 4.15.10 may not work.***
 
 After installation, confirm that both tools are correctly set up by executing the following commands in your terminal.
 
@@ -84,13 +86,15 @@ Server:
   Stopped: 120
  Images: 48
 ```
-> :bulb: **Note**: The specific numbers in the output might vary based on your installation details and additional information may also appear.
+> :bulb: **Note:** The specific numbers in the output might vary based on your installation details and additional information may also appear.
 
 ## Running the Tutorial with Docker
 
-To run this tutorial, we have prepared a Docker container named [`globalcomputinglab/somospie_openvisus`](https://hub.docker.com/repository/docker/globalcomputinglab/somospie_openvisus/general) that includes all necessary software. Ensure you have installed Docker Desktop as outlined in the [Prerequisites](#prerequisites) and have it open on your computer.
+To run this tutorial, we have prepared a Docker container named [`globalcomputinglab/somospie_openvisus`](https://hub.docker.com/repository/docker/globalcomputinglab/somospie_openvisus/general) that includes all necessary software. Ensure you have installed Docker Desktop as outlined in the [Prerequisites](#prerequisites).
+
+**:bulb: Note: Before following the next steps, make sure to open the Docker Desktop Application.**
 
-Follow these steps in your terminal to use the Docker container for the tutorial:
+Now open the terminal and follow the next steps to deploy the tutorial in the Docker container:
 ```
 # Clone the tutorial repository:
 git clone https://github.com/nsdf-fabric/Openvisus_Tutorial.git
@@ -215,12 +219,16 @@ NSDF Resources:
 - **Slack workspace**: [nsdf-workspace](https://nsdf-workspace.slack.com/).
 - **Github Discussions**: [issues](https://github.com/nsdf-fabric/catalog-comparison-tool/issues): Discussions and Q&A.
 - **Mailing list**: [https://groups.google.com/g/nsdf](https://groups.google.com/g/nsdf) - [email protected]
-- **Twitter**: [@FabricNsdf](https://twitter.com/FabricNsdf).
+- **Twitter**: [@FabricNsdf](https://twitter.com/FabricNsdf)
+
+OpenVisus Resources:
+- **Github:** [Open Source distribution of the ViSUS capabilities](https://github.com/sci-visus/openvisus)
+- **Webpage:** [VISUS - High performance Big Data Analysis and Visualization Solutions](https://visus.org/)
 
 SOMOSPIE Resources:
 - **GitHub:** [SOMOSPIE software](https://github.com/TauferLab/SOMOSPIE)
 - **Webpage:** [SOMOSPIE overview](https://globalcomputing.group/somospie)
-- **Questions:** Michela Taufer [[email protected]](email:[email protected]). 
+- **Questions:** Michela Taufer [[email protected]](email:[email protected]) 
 
 ## Related Publications
 
@@ -230,6 +238,12 @@ SOMOSPIE Resources:
 
 [3] D. Rorabaugh, M. Guevara, R. Llamas, J. Kitson, R. Vargas, and M. Taufer. SOMOSPIE: A modular SOil MOisture SPatial Inference Engine based on data-driven decisions. In Proceedings of the 2019 15th International Conference on eScience (eScience) (2019). [link](https://ieeexplore.ieee.org/document/9041768)
 
+[4] V. Pascucci and R. J. Frank, "Global Static Indexing for Real-Time Exploration of Very Large Regular Grids," SC '01: Proceedings of the 2001 ACM/IEEE Conference on Supercomputing, Denver, CO, USA, 2001, pp. 45-45, [link](http://doi.org/10.1145/582034.582036)
+
+[5] Pascucci, Valerio, et al. "The ViSUS visualization framework." High Performance Visualization. Chapman and Hall/CRC, 2012. 439-452. [link](https://www.taylorfrancis.com/chapters/edit/10.1201/b12985-32/visus-visualization-frame[…]a-gyulassy-cameron-christensen-sujin-philip-sidharth-kumar)
+
+[6] Brian Summa, Giorgio Scorzelli, Ming Jiang, Peer-Timo Bremer, and Valerio Pascucci. 2011. Interactive editing of massive imagery made simple: Turning Atlanta into Atlantis. ACM Trans. Graph. 30, 2, Article 7 (April 2011), 13 pages. [link](https://doi.org/10.1145/1944846.1944847)
+
 ## Copyright and License
 
 Copyright (c) 2024, Global Computing Lab