Minimal formitting

.gitignore

@@ -133,3 +133,4 @@ dmypy.json
 
 #VScode
 .vscode 
+.DS_Store

LotkaVolterraModel.py

@@ -37,9 +37,9 @@ def dX_dt(X, a=1.0, b=0.1, c=1.5, d=0.75):
     >>> dX_dt(np.zeros(2),1,0.1,1.5,.75)        # zero is a fixpoint
     array([0., 0.])
     """
-    if np.size(X)>2:
+    if np.size(X) > 2:
         raise ValueError("X has only two dimensions!")
-    
+
     return np.array([a * X[0] - b * X[0] * X[1], -c * X[1] + d * b * X[0] * X[1]])
 
 

README.md

@@ -17,6 +17,7 @@ If you are a new user, we recommend checking out the detailed Github Guides.
 - numpy
 - scipy 
 - matplotlib
+- sklearn 
 
 Specifially, I'm sharing a requirements file (req.txt)
 

test_LVM.py

@@ -16,12 +16,15 @@ def test_dX_dt():
         - np.array([0.9, -1.425])
     ).all
 
+
 def test_dX_dt_wronginput():
     """ testing for wrong dimensions (ValueError) """
     import pytest
+
     with pytest.raises(ValueError):
         LotkaVolterraModel.dX_dt(np.ones(3), 1, 0.1, 1.5, 0.75)
 
+
 def test_growth():
     state = np.array([13.0, 12.0])
     growth = LotkaVolterraModel.dX_dt(state, a=1.0, b=0.3, c=1.5, d=0.1)