fix negf

freude · May 29, 2020 · 1ff3e69 · 1ff3e69
1 parent 9e36c53
commit 1ff3e69
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Showing 4 changed files with 17 additions and 19 deletions.
diff --git a/nanonet/negf/cfr.py b/nanonet/negf/cfr.py
@@ -49,11 +49,10 @@ def gen_poles_and_residues(self, cutoff=50):
         self.cutoff = cutoff
 
         b_mat = [1 / (2.0 * np.sqrt((2 * (j + 1) - 1) * (2 * (j + 1) + 1))) for j in range(0, cutoff - 1)]
-        b_mat = np.matrix(np.diag(b_mat, -1)) + np.matrix(np.diag(b_mat, 1))
+        b_mat = np.diag(b_mat, -1) + np.diag(b_mat, 1)
 
         poles, residues = eig(b_mat)
 
-        residues = np.array(np.matrix(residues))
         residues = 0.25 * np.array([np.abs(residues[0, j]) ** 2 / (poles[j] ** 2) for j in range(residues.shape[0])])
 
         self.fd_poles_coords = poles

diff --git a/nanonet/negf/continued_fraction_representation.py b/nanonet/negf/continued_fraction_representation.py
@@ -34,11 +34,10 @@ def approximant_diff(energy, poles, residues):
 def poles_and_residues(cutoff=2):
 
     b_mat = [1 / (2.0 * np.sqrt((2*(j+1) - 1)*(2*(j+1) + 1))) for j in range(0, cutoff-1)]
-    b_mat = np.matrix(np.diag(b_mat, -1)) + np.matrix(np.diag(b_mat, 1))
+    b_mat = np.diag(b_mat, -1) + np.diag(b_mat, 1)
 
     poles, residues = eig(b_mat)
 
-    residues = np.array(np.matrix(residues))
     # arg = np.argmax(np.abs(residues), axis=0)
 
     residues = 0.25 * np.array([np.abs(residues[0, j])**2 / (poles[j] ** 2) for j in range(residues.shape[0])])

diff --git a/nanonet/negf/field.py b/nanonet/negf/field.py
@@ -106,17 +106,17 @@ def rotate(self, axis, theta):
         :return:
         """
         if axis == 'x':
-            rot_mat = np.matrix([[1.0, 0.0, 0.0],
-                                 [0.0, np.cos(theta), -np.sin(theta)],
-                                 [0.0, np.sin(theta), np.cos(theta)]])
+            rot_mat = np.array([[1.0, 0.0, 0.0],
+                                [0.0, np.cos(theta), -np.sin(theta)],
+                                [0.0, np.sin(theta), np.cos(theta)]])
         elif axis == 'y':
-            rot_mat = np.matrix([[np.cos(theta), 0.0, np.sin(theta)],
-                                 [0.0, 1.0, 0.0],
-                                 [-np.sin(theta), 0.0, np.cos(theta)]])
+            rot_mat = np.array([[np.cos(theta), 0.0, np.sin(theta)],
+                                [0.0, 1.0, 0.0],
+                                [-np.sin(theta), 0.0, np.cos(theta)]])
         elif axis == 'z':
-            rot_mat = np.matrix([[np.cos(theta), -np.sin(theta), 0.0],
-                                 [np.sin(theta), np.cos(theta), 0.0],
-                                 [0.0, 0.0, 1.0]])
+            rot_mat = np.array([[np.cos(theta), -np.sin(theta), 0.0],
+                                [np.sin(theta), np.cos(theta), 0.0],
+                                [0.0, 0.0, 1.0]])
         else:
             raise ValueError('Wrong axis')
 
@@ -144,7 +144,7 @@ def _transform(self, coords1, translate):
 
             if len(self._rot_mat) > 0:
                 for item in self._rot_mat:
-                    coords[j] = np.array(np.matrix(item) * np.matrix(coords[j]).T).T[0]
+                    coords[j] = np.dot(item * coords[j].T).T[0]
 
         return coords
 
@@ -159,7 +159,7 @@ def _inv_transform(self, coords1, translate):
 
             if len(self._rot_mat) > 0:
                 for item in reversed(self._rot_mat):
-                    coords[j] = np.array(np.linalg.inv(np.matrix(item)) * np.matrix(coords[j]).T).T[0]
+                    coords[j] = np.dot(np.linalg.inv(item), coords[j].T).T[0]
 
             if isinstance(translate, np.ndarray):
                 coords[j] = coords[j] + np.squeeze(translate)
@@ -208,9 +208,9 @@ def add_screening(self, eps, mol_y_length, spacing):
         vec[eps[0]] = 1.0
         vec = np.array(vec)
 
-        rot_mat = np.matrix(np.identity(3))
+        rot_mat = np.identity(3)
         # rot_mat[:2, :2] = np.matrix(np.sqrt(1.0 - self._rot_mat[0][1:, 1:]**2))
-        rot_mat[:2, :2] = np.matrix(self._rot_mat[0][1:, 1:])
+        rot_mat[:2, :2] = self._rot_mat[0][1:, 1:]
         rot_mat[0, 1] = -rot_mat[0, 1]
         rot_mat[1, 0] = -rot_mat[1, 0]
         # rot_mat = np.linalg.inv(rot_mat)
@@ -219,7 +219,7 @@ def add_screening(self, eps, mol_y_length, spacing):
         # rot_mat[0, 0] = -rot_mat[0, 0]
         # rot_mat[1, 1] = -rot_mat[1, 1]
 
-        vec = np.array(rot_mat * np.matrix(vec).T).T[0]
+        vec = np.dot(rot_mat, vec.T).T[0]
 
         dist = X[0] * vec[0] + X[1] * vec[1] + X[2] * vec[2] + eps[1] + \
                0.5 * mol_y_length * (1.0 - np.sin(1.13446)) + \

diff --git a/nanonet/negf/recursive_greens_functions.py b/nanonet/negf/recursive_greens_functions.py
@@ -17,7 +17,7 @@ def mat_mul(list_of_matrices):
     unity = np.eye(list_of_matrices[num_of_mat - 1].shape[0])
 
     for j, item in enumerate(list_of_matrices):
-        list_of_matrices[j] = np.matrix(item)
+        list_of_matrices[j] = item
 
     for j in range(9, -1, -1):
         unity = list_of_matrices[j] * unity