readme and styleguide (#308)

* Update README.md

* style

* imports within classes

Author: Pwhsky

README.md

@@ -85,11 +85,11 @@ Here you find a series of notebooks that give you an overview of the core featur
 
 These are examples of how DeepTrack2 can be used on real datasets:
 
-- DTEx201 **[MNIST](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx201_MNIST.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx201_MNIST.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+- DTEx211 **[MNIST](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx201_MNIST.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/2-examples/DTEx201_MNIST.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
   Training a fully connected neural network to identify handwritten digits using MNIST dataset.
 
-- DTEx202 **Single Particle Tracking**
+- DTEx212 **Single Particle Tracking**
 
   Tracks experimental videos of a single particle. (Requires opencv-python compiled with ffmpeg)
 
@@ -114,7 +114,7 @@ These are examples of how DeepTrack2 can be used on real datasets:
   </p>
   <!-- GH_ONLY_END -->
 
-- DTEx203 **Multi-Particle tracking**
+- DTEx213 **Multi-Particle tracking**
 - 
   Detecting quantum dots in a low SNR image.
 
@@ -138,19 +138,19 @@ These are examples of how DeepTrack2 can be used on real datasets:
   </p>
   <!-- GH_ONLY_END -->
 
-- DTEx204 **Particle Feature Extraction**
+- DTEx214 **Particle Feature Extraction**
 - 
   Extracting the radius and refractive index of particles.
 
-- DTEx205 **Cell Counting**
+- DTEx215 **Cell Counting**
 
   Counting the number of cells in fluorescence images.
 
-- DTEx206 **3D Multi-Particle tracking**
+- DTEx216 **3D Multi-Particle tracking**
 
   Tracking multiple particles in 3D for holography.
 
-- DTEx207 **GAN image generation**
+- DTEx217 **GAN image generation**
 
   Using a GAN to create cell image from masks.
 

tutorials/4-developers/DTDV411_style.ipynb

@@ -71,7 +71,7 @@
     "\n",
     "Use absolute imports for all imports, unless the target is at the same level in the hierarchy inside a `__init__.py`.\n",
     "\n",
-    "### Absolute imports\n",
+    "### Absolute Imports\n",
     "\n",
     "For example, in `deeptrack/features/optics.py`:\n",
     "```python\n",
@@ -92,6 +92,27 @@
     "from .sources import *  # Correct: sources is a directory.\n",
     "from .optics import GaussianApodization, Aberration  # Correct: importing explicitly from a file.\n",
     "from .optics import *  # Incorrect: wildcard imports from files should be avoided.\n",
+    "```\n",
+    "\n",
+    "### Imports within Classes or Functions \n",
+    "\n",
+    "Not all imports need to be placed at the beginning of the module.\n",
+    "You can import libraries within classes given it will only be used within that scope and not outside the class.\n",
+    "\n",
+    "For example, in `deeptrack/features.py`:\n",
+    "```python\n",
+    "def _check_non_overlapping(\n",
+    "        self: NonOverlapping, \n",
+    "        list_of_volumes: list[np.ndarray],\n",
+    "    ) -> bool:\n",
+    "    \"\"\"\n",
+    "    ...\n",
+    "\n",
+    "    \"\"\"\n",
+    "        # Imports used locally within the function.\n",
+    "        from skimage.morphology import isotropic_erosion, isotropic_dilation\n",
+    "        from deeptrack.augmentations import CropTight, Pad\n",
+    "        from deeptrack.optics import _get_position\n",
     "```"
    ]
   },
@@ -117,12 +138,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from __future__ import annotations\n",
     "\n",
+    "\n",
     "def my_function(\n",
     "    param1: int | float,\n",
     "    param2: str,\n",
@@ -170,10 +192,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
+    "from __future__ import annotations\n",
+    "\n",
+    "\n",
     "class MyClass:\n",
     "    \"\"\"A one-line descriptioon of the class.\n",
     "\n",
@@ -228,8 +253,9 @@
     "    attribute_1: int\n",
     "    attribute_2: str\n",
     "\n",
+    "    #\n",
     "    def __init__(\n",
-    "        self: 'MyClass',\n",
+    "        self: MyClass,\n",
     "        parameter_1: int,\n",
     "        parameter_2: str,\n",
     "    ):\n",
@@ -243,29 +269,29 @@
     "        self.attribute_2 = parameter_2\n",
     "\n",
     "    def get_1(\n",
-    "        self: 'MyClass',\n",
+    "        self: MyClass,\n",
     "    ) -> int:\n",
     "        \"\"\"...\"\"\"\n",
     "        \n",
     "        return self.attribute_1\n",
     "\n",
     "    def get_2(\n",
-    "        self: 'MyClass',\n",
+    "        self: MyClass,\n",
     "    ) -> str:\n",
     "        \"\"\"...\"\"\"\n",
     "        \n",
     "        return self.attribute_2\n",
     "\n",
     "    def set_1(\n",
-    "        self: 'MyClass',\n",
+    "        self: MyClass,\n",
     "        new_value: int,\n",
     "    ) -> None:\n",
     "        \"\"\"...\"\"\"\n",
     "        \n",
     "        self.attribute_1 = new_value\n",
     "\n",
     "    def set_2(\n",
-    "        self: 'MyClass',\n",
+    "        self: MyClass,\n",
     "        new_value: str,\n",
     "    ) -> None:\n",
     "        \"\"\"...\"\"\"\n",
@@ -282,20 +308,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Ellipsis"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\"\"\"Docstring for the example.py module.\n",
     "\n",