Merge pull request #57 from MahdiAll99/dev

Dev

MEDimage/learning/Stats.py

@@ -2,7 +2,7 @@
 
 import os
 from pathlib import Path
-from typing import List
+from typing import List, Tuple
 import warnings
 
 import numpy as np
@@ -224,7 +224,7 @@ def __compute_midrank(self, x: np.array) -> np.array:
         T2[J] = T + 1
         return T2
 
-    def __fast_delong(self, predictions_sorted_transposed: np.array, label_1_count: int) -> tuple[float, float]:
+    def __fast_delong(self, predictions_sorted_transposed: np.array, label_1_count: int) -> Tuple[float, float]:
         """
         Computes the empricial AUC and its covariance using the fast version of DeLong's method.
 
@@ -273,7 +273,7 @@ def __fast_delong(self, predictions_sorted_transposed: np.array, label_1_count:
 
         return aucs, delongcov
 
-    def __compute_ground_truth_statistics(self, ground_truth: np.array) -> tuple[np.array, int]:
+    def __compute_ground_truth_statistics(self, ground_truth: np.array) -> Tuple[np.array, int]:
         """
         Computes the order of the ground truth and the number of positive examples.
 

requirements.txt

@@ -1,32 +1,32 @@
-numpy==1.22.4
-isort==5.10.1
-ipykernel==6.15.1
-ipywidgets==8.0.1
-jupyter==1.0.0
-matplotlib==3.7.0
-networkx==2.8.5
-neuroCombat==0.2.12
-nibabel==3.2.2
-nilearn==0.10.1
-numpyencoder==0.3.0
-pandas==1.5.3
-Pillow==9.2.0
-protobuf==3.20.*
-pycaret==3.0.4
-pydicom==1.2.2
-PyWavelets==1.1.1
-ray==2.5.1
-scikit_image==0.18.2
-scipy==1.7.0
-setuptools==62.2.0
-SimpleITK==2.1.1.2
-scikit_learn==1.2.2
-seaborn==0.13.2
-Sphinx==7.2.6
+numpy
+isort
+ipykernel
+ipywidgets
+jupyter
+matplotlib
+networkx
+neuroCombat
+nibabel
+nilearn
+numpyencoder
+pandas
+Pillow
+protobuf
+pycaret
+pydicom
+PyWavelets
+ray
+scikit_image
+scipy
+setuptools
+SimpleITK
+scikit_learn
+seaborn
+Sphinx
 sphinx-carousel==1.2.0
 sphinx-jsonschema==1.19.1
 sphinx-rtd-dark-mode==1.2.4
-tqdm==4.65.0
-wget==3.2
-tabulate==0.9.0
-xgboost==1.7.6
+tqdm
+wget
+tabulate
+xgboost