From eb2f0f18182f21fb74cc08bec340c187e5442723 Mon Sep 17 00:00:00 2001
From: JHKru <jhkr@web.de>
Date: Mon, 19 Feb 2024 19:16:52 +0100
Subject: [PATCH] Style changes

---
 src/springcraft/nma.py | 14 ++++++--------
 tests/test_anm.py      | 18 +++++++-----------
 2 files changed, 13 insertions(+), 19 deletions(-)

diff --git a/src/springcraft/nma.py b/src/springcraft/nma.py
index 9c0311d..fa15ea3 100644
--- a/src/springcraft/nma.py
+++ b/src/springcraft/nma.py
@@ -288,8 +288,8 @@ def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
     for 'mode_subset' and 'memory_efficient' are passed to the function.
     """
     
-    from springcraft import GNM
-    from springcraft import ANM
+    from .gnm import GNM
+    from .anm import ANM
     
     eig_values, eig_vectors = enm.eigen()
     n_nodes = len(enm._coord)
@@ -327,9 +327,8 @@ def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
     elif all_modes:
         # 3N x 3N -> N x 3 x N x 3 -> N x N x 3 x 3
         cov = enm.covariance
-        reshaped = cov.reshape(
-                            cov.shape[0]//3, 3, -1, 3
-                        ).swapaxes(1,2)
+        reshaped = cov.reshape(cov.shape[0]//3, 3, cov.shape[0]//3, 3
+                               ).swapaxes(1,2)
         # Accept array of any dimension 
         # -> Sum over diagonals in last two dims
         # -> Return any shape (in this case NxN)
@@ -341,9 +340,8 @@ def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
 
         # Reshape array of eigenvectors
         # (k,3n) -> (k,n,3) for ANMs; (k,n) -> (k,n,1) for GNMs
-        modes_reshaped = np.reshape(
-                            eig_vectors, (len(mode_subset), -1, num_dim)
-                            )
+        modes_reshaped = np.reshape(eig_vectors, (len(mode_subset), -1, num_dim)
+                                    )
         dcc = np.zeros((n_nodes, n_nodes))
         for ev, evec in zip(eig_values, modes_reshaped):
             dcc += (evec @ evec.T) / ev
diff --git a/tests/test_anm.py b/tests/test_anm.py
index 79b91e7..09b4a0a 100644
--- a/tests/test_anm.py
+++ b/tests/test_anm.py
@@ -189,10 +189,9 @@ def test_frequency_fluctuation_dcc(ff_name):
             # no temperature weighting
             tem_scaling = 1
             tem = 1
-            reference_fluc = np.genfromtxt(
-                    join(data_dir(), ref_fluc),
-                    skip_header=1, delimiter=","
-                )
+            reference_fluc = np.genfromtxt(join(data_dir(), ref_fluc),
+                                            skip_header=1, delimiter=","
+                                        )
 
         # Bio3d -> Mass- and temperature weighting
         else:
@@ -211,14 +210,11 @@ def test_frequency_fluctuation_dcc(ff_name):
             reference_masses = np.array(enm_nma_bio3d.rx2["mass"])
             reference_freq = np.array(enm_nma_bio3d.rx2["frequencies"])
             reference_fluc = np.array(enm_nma_bio3d.rx2["fluctuations"])
-            reference_fluc_subset = np.array(
-                                        bio3d.fluct_nma(enm_nma_bio3d, 
-                                                        mode_inds=r_seq(12,33)
-                                        ))
+            reference_fluc_subset = np.array(bio3d.fluct_nma(
+                                            enm_nma_bio3d, mode_inds=r_seq(12,33)
+                                            ))
             reference_dcc = np.array(bio3d.dccm(enm_nma_bio3d))
-            reference_dcc_subset = np.array(
-                                        bio3d.dccm(enm_nma_bio3d, nmodes=30)
-                                    )
+            reference_dcc_subset = np.array(bio3d.dccm(enm_nma_bio3d, nmodes=30))
 
             tem_scaling = K_B*N_A
             test_nomw = springcraft.ANM(ca, ff)