PEP8 Updates

Author: bjedwards

pymc/examples/discrete_find_MAP.py

@@ -40,7 +40,7 @@
 
 with model:
     for i in range(n+1):
-        s = {'p':0.5, 'surv_sim':i}
+        s = {'p': 0.5, 'surv_sim': i}
         map_est = mc.find_MAP(start=s, vars=model.vars,
                               fmin=mc.starting.optimize.fmin_bfgs)
         print('surv_sim: %i->%i, p: %f->%f, LogP:%f'%(s['surv_sim'],
@@ -58,7 +58,7 @@
 
 with model:
     for i in range(n+1):
-        s = {'p':0.5, 'surv_sim':i}
+        s = {'p': 0.5, 'surv_sim': i}
         map_est = mc.find_MAP(start=s, vars=model.vars)
         print('surv_sim: %i->%i, p: %f->%f, LogP:%f'%(s['surv_sim'],
                                                       map_est['surv_sim'],
@@ -74,14 +74,15 @@
 # near found minimums. Because it has a slightly different interface to other
 # minimization schemes we have to define a wrapper function.
 
-def bh(*args,**kwargs):
+
+def bh(*args, **kwargs):
     result = mc.starting.optimize.basinhopping(*args, **kwargs)
     # A `Result` object is returned, the argmin value can be in `x`
     return result['x']
 
 with model:
     for i in range(n+1):
-        s = {'p':0.5, 'surv_sim':i}
+        s = {'p': 0.5, 'surv_sim': i}
         map_est = mc.find_MAP(start=s, vars=model.vars, fmin=bh)
         print('surv_sim: %i->%i, p: %f->%f, LogP:%f'%(s['surv_sim'],
                                                       map_est['surv_sim'],
@@ -95,7 +96,7 @@ def bh(*args,**kwargs):
 
 with model:
     for i in range(n+1):
-        s = {'p':0.5, 'surv_sim':i}
+        s = {'p': 0.5, 'surv_sim': i}
         map_est = mc.find_MAP(start=s, vars=model.vars,
                               fmin=bh, minimizer_kwargs={"method": "Powell"})
         print('surv_sim: %i->%i, p: %f->%f, LogP:%f'%(s['surv_sim'],
@@ -112,6 +113,6 @@ def bh(*args,**kwargs):
     step2 = mc.step_methods.Metropolis(vars=[surv_sim])
 
 with model:
-    trace = mc.sample(25000,[step1,step2],start=map_est)
+    trace = mc.sample(25000, [step1, step2], start=map_est)
 
 mc.traceplot(trace);

pymc/tests/test_tuning.py

@@ -31,10 +31,10 @@ def test_find_MAP_discrete():
     yes = 15
 
     with Model() as model:
-        p = Beta('p',alpha,beta)
+        p = Beta('p', alpha, beta)
         ss = Binomial('ss', n=n, p=p)
         s = Binomial('s', n=n, p=p, observed=yes)
-        
+
         map_est1 = starting.find_MAP()
         map_est2 = starting.find_MAP(vars=model.vars)
 

pymc/tuning/starting.py

@@ -45,7 +45,7 @@ def find_MAP(start=None, vars=None, fmin=None, return_raw=False,
 
     if vars is None:
         vars = model.cont_vars
- 
+
     disc_vars = list(typefilter(vars, discrete_types))
 
     if disc_vars and disp: