formatting (black)

Author: evamariie

AURORA/tutorial.ipynb

@@ -27,7 +27,7 @@
    },
    "outputs": [],
    "source": [
-    "#Installations \n",
+    "# Installations\n",
     "!pip install brainles_aurora matplotlib > /dev/null\n",
     "\n",
     "%load_ext autoreload\n",
@@ -80,26 +80,27 @@
    "source": [
     "import sys\n",
     "\n",
-    "#Check if we are in google colab currently\n",
+    "# Check if we are in google colab currently\n",
     "try:\n",
     "    import google.colab\n",
+    "\n",
     "    colabFlag = True\n",
     "except ImportError as r:\n",
     "    colabFlag = False\n",
     "\n",
-    "#Execute certain steps only if we are in a colab environment\n",
+    "# Execute certain steps only if we are in a colab environment\n",
     "if colabFlag:\n",
     "    # Create a folder in your Google Drive\n",
     "    from google.colab import drive\n",
-    "    drive.mount('/content/drive')\n",
-    "    #clone repository and set path\n",
+    "\n",
+    "    drive.mount(\"/content/drive\")\n",
+    "    # clone repository and set path\n",
     "    !git clone https://github.com/BrainLesion/tutorials.git /content/drive/MyDrive/tutorials\n",
     "    COLAB_BASE_PATH = \"/content/drive/MyDrive/tutorials/AURORA/\"\n",
     "    sys.path.insert(0, BASE_PATH)\n",
-    "    \n",
-    "else: # normal jupyter notebook environment\n",
-    "    BASE_PATH = \"./\" #current working directory would be BraTs-Toolkit anyways if you are not in colab\n",
-    "    "
+    "\n",
+    "else:  # normal jupyter notebook environment\n",
+    "    BASE_PATH = \"./\"  # current working directory would be BraTs-Toolkit anyways if you are not in colab"
    ]
   },
   {
@@ -128,7 +129,7 @@
     "import nibabel as nib\n",
     "import numpy as np\n",
     "import torch\n",
-    "import utils # local file\n"
+    "import utils  # local file"
    ]
   },
   {
@@ -301,32 +302,34 @@
     }
    ],
    "source": [
-    "# We first need to create an instance of the AuroraInfererConfig class, \n",
-    "# which will hold the configuration for the inferer. \n",
+    "# We first need to create an instance of the AuroraInfererConfig class,\n",
+    "# which will hold the configuration for the inferer.\n",
     "# We can then create an instance of the AuroraInferer class, which will be used to perform the inference.\n",
     "\n",
     "config = AuroraInfererConfig(\n",
-    "    tta=False,  \n",
+    "    tta=False,\n",
     "    # we disable test time augmentations for a quick demo\n",
     "    # should be set to True for better results\n",
-    "    sliding_window_batch_size=4,  \n",
+    "    sliding_window_batch_size=4,\n",
     "    # The batch size used for the sliding window inference\n",
-    "    # decrease if you run out of memory \n",
+    "    # decrease if you run out of memory\n",
     "    # warning: too small batches might lead to unstable results\n",
     "    cuda_devices=\"0\",  # optional, if you have multiple GPUs you can specify which one to use\n",
-    "    device = \"cpu\" #uncomment this line to force-use CPU\n",
+    "    device=\"cpu\",  # uncomment this line to force-use CPU\n",
     ")\n",
     "\n",
     "\n",
     "# Now that we have the configuration we can create an instance of the AuroraInferer class.\n",
     "# This class will be used to perform the inference. We can then call the infer method to perform the inference.\n",
-    "inferer = AuroraInferer( config=config )\n",
+    "inferer = AuroraInferer(config=config)\n",
     "\n",
-    "if(torch.cuda.is_available() == False and colabFlag==True):\n",
-    "    raise RuntimeWarning(\"You are not using any GPU in Colab! Go to 'Runtime'->'Change Runtime type' to select GPU usage!\")\n",
+    "if torch.cuda.is_available() == False and colabFlag == True:\n",
+    "    raise RuntimeWarning(\n",
+    "        \"You are not using any GPU in Colab! Go to 'Runtime'->'Change Runtime type' to select GPU usage!\"\n",
+    "    )\n",
     "\n",
-    "# The infer method takes the path to the T1c MRI file and the path to the output segmentation file as arguments. \n",
-    "# The output segmentation file will be created by the infer method and \n",
+    "# The infer method takes the path to the T1c MRI file and the path to the output segmentation file as arguments.\n",
+    "# The output segmentation file will be created by the infer method and\n",
     "# will contain the segmentation of the input T1c MRI.\n",
     "\n",
     "# The example below shows how to perform the inference using a T1c MRI file:\n",
@@ -336,7 +339,7 @@
     ")\n",
     "\n",
     "# IMPORTANT: If this cell produces an OutOfMemoryError, you might not have enough VRAM (minimum 8GB).\n",
-    "# Try using the CPU instead by setting \"useGPU\" to False above\n"
+    "# Try using the CPU instead by setting \"useGPU\" to False above"
    ]
   },
   {
@@ -534,14 +537,14 @@
    "source": [
     "config = AuroraInfererConfig()  # Use default config\n",
     "\n",
-    "inferer = AuroraInferer( config=config )\n",
-    "    \n",
+    "inferer = AuroraInferer(config=config)\n",
+    "\n",
     "# Use all four input modalities,we also create other outputs and a custom log file\n",
     "_ = inferer.infer(\n",
-    "    t1=f\"{BASE_PATH}/data/t1.nii.gz\", \n",
+    "    t1=f\"{BASE_PATH}/data/t1.nii.gz\",\n",
     "    t1c=f\"{BASE_PATH}/data/t1c.nii.gz\",\n",
-    "    t2=f\"{BASE_PATH}/data/t2.nii.gz\", \n",
-    "    fla=f\"{BASE_PATH}/data/flair.nii.gz\", \n",
+    "    t2=f\"{BASE_PATH}/data/t2.nii.gz\",\n",
+    "    fla=f\"{BASE_PATH}/data/flair.nii.gz\",\n",
     "    segmentation_file=f\"{BASE_PATH}/output/multi-modal_segmentation.nii.gz\",\n",
     "    # The unbinarized network outputs for the whole tumor channel (edema + enhancing tumor core + necrosis) channel\n",
     "    whole_tumor_unbinarized_floats_file=f\"{BASE_PATH}/output/whole_tumor_unbinarized_floats.nii.gz\",\n",
@@ -692,7 +695,7 @@
    "source": [
     "config = AuroraInfererConfig()\n",
     "\n",
-    "# AuroraInferer(config=config) \n",
+    "# AuroraInferer(config=config)\n",
     "# If you do not have a GPU that supports CUDA use the CPU version (uncomment the line above, comment the GPU inferer)\n",
     "inferer = AuroraInferer(config=config)\n",
     "\n",