Issue docstring harmonic (#541)

* Remove tracking of project settings

* Fix docstring for HarmonicOscillator

* black

* Fix bar ParameterError

.gitignore

@@ -118,6 +118,9 @@ venv.bak/
 .spyderproject
 .spyproject
 
+# VSCode project settings
+.vscode/
+
 # Rope project settings
 .ropeproject
 

pymbar/other_estimators.py

@@ -242,7 +242,7 @@ def bar(
         DeltaF_initial = DeltaF
 
     if method not in ["self-consistent-iteration", "false-position", "bisection"]:
-        raise ParameterError("method {:d} is not defined for bar".format(method))
+        raise ParameterError("method {} is not defined for bar".format(method))
 
     if uncertainty_method not in ["BAR", "MBAR"]:
         raise ParameterError(

pymbar/testsystems/harmonic_oscillators.py

@@ -10,7 +10,7 @@ class HarmonicOscillatorsTestCase(object):
     Generate energy samples with default parameters.
 
     >>> testcase = HarmonicOscillatorsTestCase()
-    >>> x_kn, u_kln, N_k, s_n = testcase.sample()
+    >>> x_n, u_kn, N_k, s_n = testcase.sample()
 
     Retrieve analytical properties.
 
@@ -22,12 +22,12 @@ class HarmonicOscillatorsTestCase(object):
 
     Generate energy samples with default parameters in one line.
 
-    >>> x_kn, u_kln, N_k, s_n = HarmonicOscillatorsTestCase().sample()
+    >>> x_n, u_kn, N_k, s_n = HarmonicOscillatorsTestCase().sample()
 
     Generate energy samples with specified parameters.
 
     >>> testcase = HarmonicOscillatorsTestCase(O_k=[0, 1, 2, 3, 4], K_k=[1, 2, 4, 8, 16])
-    >>> x_kn, u_kln, N_k, s_n = testcase.sample(N_k=[10, 20, 30, 40, 50])
+    >>> x_n, u_kn, N_k, s_n = testcase.sample(N_k=[10, 20, 30, 40, 50])
 
     Test sampling in different output modes.
 
@@ -131,9 +131,11 @@ def sample(self, N_k=(10, 20, 30, 40, 50), mode="u_kn", seed=None):
         s_n : np.ndarray, shape=(n_samples), dtype='int'
             s_n is the state of origin of x_n
 
+        if mode == 'u_kln':
+
         x_kn : np.ndarray, shape=(n_states, n_samples), dtype=float
             1D harmonic oscillator positions
-        u_kln : np.ndarray, shape=(n_states, n_states, n_samples), dytpe=float, only if mode='u_kln'
+        u_kln : np.ndarray, shape=(n_states, n_states, n_samples), dytpe=float
            u_kln[k,l,n] is reduced potential of sample n from state k evaluated at state l.
         N_k : np.ndarray, shape=(n_states), dtype=int32
            N_k[k] is the number of samples generated from state k