pca update

Class_Mod/PCA_.py

-from Packages import *
-from Class_Mod.DATA_HANDLING import *
-
+from sklearn.decomposition import PCA
 
 class LinearPCA:
     def __init__(self, X, Ncomp=10):
@@ -57,12 +55,15 @@ class LinearPCA:
             Hat = ti @ np.linalg.pinv(np.transpose(ti) @ ti) @ np.transpose(ti)
             self.lev[self._r.columns[i]] = ti.ravel()
         self.leverage = pd.DataFrame(self.lev)
-        ## Hotelling t2
-        #self.eigvals = M.singular_values_**2
-        #self.Lambda = np.diag(self.eigvals)
-
-        #self.T2 = self.__t @ np.linalg.inv(self.Lambda) @self.__t.T
 
+        ## Hotelling t2
+        
+        self.eigvals = M.singular_values_**2
+        self.Lambda = np.diag(self.eigvals)
+        self.T2 = pd.DataFrame()
+        tt = self._r.to_numpy()
+        for i in range(self._t.shape[1]):
+           self.T2[self.__pcnames[i]] = np.diag(self.__t[:,i].reshape((-1,1)) @ np.linalg.inv(np.array(self.Lambda[i,i]).reshape((1,1))) @ np.transpose(self.__t[:,i].reshape((-1,1))))
         
 
     @property
@@ -79,4 +80,8 @@ class LinearPCA:
     
     @property
     def residuals(self):
-        return self.res
\ No newline at end of file
+        return self.res
+    @property
+    def hotelling(self):
+        #return pd.DataFrame(self.T2)
+        return self.T2
\ No newline at end of file