quickstart guide updated

pni-lab · Nov 7, 2023 · 83d13ca · 83d13ca
1 parent add99c4
commit 83d13ca
Showing 1 changed file with 35 additions and 19 deletions.
diff --git a/docs/04-package.ipynb b/docs/04-package.ipynb
@@ -10,12 +10,35 @@
     "\n",
     "***for Connectivity-based Hopfield Neural Networks (CHNNs)***\n",
     "\n",
-    "## Installation\n",
+    "### Installation\n",
     "\n",
+    ":::{hint}\n",
+    "\n",
+    "The package 'connattractor' will be soon available on PyPI.\n",
+    "\n",
+    "Afterwards the preferred way to install it will be:\n",
     "```bash\n",
     "pip install connattractor\n",
     "```\n",
     "\n",
+    "For now, the best way to try out the package may be the docker container:\n",
+    "  - install [docker](https://www.docker.com/)\n",
+    "  - clone the repo and start your notebook in a docker container\n",
+    "    ```bash\n",
+    "    git clone https://github.com/pni-lab/connattractor.git\n",
+    "    cd connattractor\n",
+    "    docker run -it -v $PWD:/mounted/connattractor -p 8080:8080 -p 8888:8888 pnilab/connattractor:latest jupyter notebook\n",
+    "    ```\n",
+    "  - copy paste the last link in your browser to start the notebook\n",
+    "\n",
+    "You can also clone and run the github repository and set up your own Python environment, of course.\n",
+    "\n",
+    "See: [https://github.com/pni-lab/connattractor](https://github.com/pni-lab/connattractor)\n",
+    ":::\n",
+    "\n",
+    "## QuickStart Guide\n",
+    "### Contents\n",
+    "\n",
     "- **Part 1**: The quickest way to plot and analyze your data on the CHNN projection\n",
     "- **Part 2**: Build your own CHNN projection"
    ]
@@ -76,7 +99,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Load the example task data, scrub it and seperate it into task and rest:"
+    "#### Load the example task data, scrub it and seperate it into task and rest"
    ]
   },
   {
@@ -166,7 +189,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Plotting data in the projection plane"
+    "#### Plot the data in the projection plane"
    ]
   },
   {
@@ -241,7 +264,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Statistical analysis"
+    "#### Statistical analysis"
    ]
   },
   {
@@ -352,7 +375,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Obtain functional connectivity matrix\n",
+    "#### Obtain functional connectivity matrix\n",
     "\n",
     "Should be a partial correlation matrix, square and symmetric.\n",
     "\n",
@@ -361,7 +384,7 @@
     "\n",
     "Users are, nevertheless, encouraged to use dataset-specific connectomes.\n",
     "\n",
-    "#### Let's load in the example connectome"
+    "##### Let's load in the example connectome"
    ]
   },
   {
@@ -759,7 +782,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Now we construct a CHNN and plot the weights"
+    "#### Construct your fcHNN"
    ]
   },
   {
@@ -797,7 +820,7 @@
     }
    },
    "source": [
-    "#### Now we run the stochastic relaxation procedure to obtain simulated states\n",
+    "#### Run the stochastic relaxation procedure to obtain simulated states\n",
     "It may take a few seconds..."
    ]
   },
@@ -836,7 +859,7 @@
     }
    },
    "source": [
-    "#### We create a Hopfield Embedding\n",
+    "#### Create your Hopfield Embedding\n",
     "Again, a few seconds..."
    ]
   },
@@ -868,7 +891,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### and plot the state space in it"
+    "#### Plot the state space"
    ]
   },
   {
@@ -902,19 +925,12 @@
     "ax.set_yticks([])\n",
     "ax.grid(False)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "hide_input": false,
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -928,7 +944,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.8"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,