Update readthedocs

Author: Atika-Syeda

.readthedocs.yml

@@ -21,5 +21,9 @@ python:
    version: 3.8
    install:
       - requirements: docs/requirements.txt
-
+      #- method: pip
+        #path: .
+        #extra_requirements:
+        #  - docs
+        #  - gui
 

docs/environment.yml

@@ -1,24 +1,13 @@
 {
   "cells": [
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {
-        "colab_type": "text",
-        "id": "view-in-github"
-      },
-      "source": [
-        "<a href=\"https://colab.research.google.com/github/MouseLand/facemap/blob/dev/notebooks/process_keypoints.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-      ]
-    },
     {
       "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "aNJBMgPY5xR8"
       },
       "source": [
-        "# **Facemap 1.0 Keypoints Prediction in colab with a GPU**\n",
+        "# Facemap 1.0 Keypoints Prediction in colab with a GPU\n",
         "\n",
         "Framework for predicting neural activity from mouse orofacial movements tracked using a pose estimation model. Package also includes singular value decomposition (SVD) of behavioral videos.\n",
         "\n",
@@ -31,6 +20,17 @@
         "This tutorials shows how to process keypoints using Facemap. For more information on the Pose class see [here](https://github.com/MouseLand/facemap/blob/main/facemap/pose/pose.py)"
       ]
     },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "view-in-github"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/MouseLand/facemap/blob/dev/notebooks/process_keypoints.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
     {
       "attachments": {},
       "cell_type": "markdown",
@@ -402,7 +402,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {
         "cellView": "form",
         "id": "IKmjuZerAf9J"
@@ -439,7 +439,7 @@
         "id": "DZPn2mG6lti7"
       },
       "source": [
-        "See `load_visualize_keypoints.ipynb` to load and visualize the saved keypoints in a notebook. Alternatively, use the [Facemap GUI](https://github.com/MouseLand/facemap/blob/main/docs/pose_tracking_gui_tutorial.md#visualize-keypoints) to view keypoints tracking on video."
+        "Next, use the [Facemap GUI](https://github.com/MouseLand/facemap/blob/main/docs/pose_tracking_gui_tutorial.md#visualize-keypoints) to view keypoints tracking on video. "
       ]
     }
   ],
@@ -462,7 +462,15 @@
       "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": "3.9.7"
     }
   },

docs/notebooks/process_keypoints.ipynb

@@ -1,24 +1,13 @@
 {
   "cells": [
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {
-        "colab_type": "text",
-        "id": "view-in-github"
-      },
-      "source": [
-        "<a href=\"https://colab.research.google.com/github/MouseLand/facemap/blob/dev/notebooks/refine_keypoints_model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-      ]
-    },
     {
       "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "aNJBMgPY5xR8"
       },
       "source": [
-        "# **Facemap 1.0 - Keypoints model refinement in colab using a GPU**\n",
+        "# Facemap 1.0 - Keypoints model refinement in colab using a GPU\n",
         "\n",
         "Facemap is a framework for predicting neural activity from mouse orofacial movements tracked using a pose estimation model. Package also includes singular value decomposition (SVD) of behavioral videos.\n",
         "\n",
@@ -31,6 +20,17 @@
         "This tutorials shows how to refine keypoints and finetune model using Facemap. For more information on the Pose class see [here](https://github.com/MouseLand/facemap/blob/main/facemap/pose/pose.py)"
       ]
     },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "view-in-github"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/MouseLand/facemap/blob/dev/notebooks/refine_keypoints_model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
     {
       "attachments": {},
       "cell_type": "markdown",

docs/notebooks/refine_keypoints_model.ipynb

@@ -91,7 +91,7 @@ Keypoints processing
 ~~~~~~~~~~~~~~~~~~~~
 
 Keypoints processing saves two outputs: a \*.h5 and a \*metadata.pkl file. 
-   - \*.h5 file contains: Keypoints stored as a 3D array of shape (3, number of bodyparts, number of frames). The first dimension of size 3 is in the order: (x, y, likelihood). For more details on using/loading the \*.h5 file in python see this `tutorial <https://github.com/MouseLand/facemap/blob/main/notebooks/load_visualize_keypoints.ipynb>`__.
+   - \*.h5 file contains: Keypoints stored as a 3D array of shape (3, number of bodyparts, number of frames). The first dimension of size 3 is in the order: (x, y, likelihood). For more details on using/loading the \*.h5 file in python see this `tutorial <https://github.com/MouseLand/facemap/blob/main/docs/notebooks/load_visualize_keypoints.ipynb>`__.
    - \*metadata.pkl file: contains a dictionary consisting of the following variables:
         -  batch_size: batch size used for inference
         -  image_size: frame size

docs/outputs.rst

@@ -121,4 +121,4 @@ proc = np.load('cam1_proc.npy', allow_pickle=True).item()
 
 The `_proc.npy` files can be loaded into the GUI (and will automatically be loaded after processing). The checkboxes in the lower left allow you to view different traces from the processed video(s).
 
-For example usage, see [notebook](https://github.com/MouseLand/facemap/blob/dev/notebooks/process.ipynb).
+For example usage, see [notebook](https://github.com/MouseLand/facemap/blob/main/docs/notebooks/process_svd.ipynb).