Added slice sampler to test_step

Author: Christopher Fonnesbeck

pymc/sample.py

@@ -17,7 +17,6 @@ def sample(draws, step, start=None, trace=None, track_progress=True, model=None)
     Parameters
     ----------
 
-    model : Model (optional if in `with` context)
     draws : int
         The number of samples to draw
     step : function
@@ -26,8 +25,9 @@ def sample(draws, step, start=None, trace=None, track_progress=True, model=None)
         Starting point in parameter space (Defaults to trace.point(-1))
     trace : NpTrace
         A trace of past values (defaults to None)
-    track : list of vars
-        The variables to follow
+    track_progress : bool
+        Flag for progress bar
+    model : Model (optional if in `with` context)
 
     Examples
     --------

pymc/tests/models.py

@@ -1,14 +1,7 @@
 from pymc import Model, Normal, Metropolis
-import numpy as np 
+import numpy as np
 import pymc as pm
 
-def simple_init(): 
-    start, model, moments = simple_model()
-
-    step = Metropolis(model.vars, np.diag([1.]), model = model)
-    return model, start, step, moments
-
-
 def simple_model():
     mu = -2.1
     tau = 1.3
@@ -17,6 +10,12 @@ def simple_model():
 
     return model.test_point, model, (mu, tau**-1)
 
+def simple_init():
+    start, model, moments = simple_model()
+
+    step = Metropolis(model.vars, np.diag([1.]), model = model)
+    return model, start, step, moments
+
 def simple_2model():
     mu = -2.1
     tau = 1.3
@@ -34,7 +33,7 @@ def mv_simple():
         [.05 , .1,  0],
         [1. ,-0.05,5.5]])
 
-    tau = np.dot(p,p.T) 
+    tau = np.dot(p,p.T)
 
 
     with pm.Model() as model:

pymc/tests/test_step.py

@@ -1,5 +1,5 @@
-from checks import *
-from models import simple_model, mv_simple
+from .checks import *
+from .models import simple_model, mv_simple
 from theano.tensor import constant
 from scipy.stats.mstats import moment
 
@@ -11,8 +11,8 @@ def check_stat(name, trace, var, stat, value, bound):
 def test_step_continuous():
     start, model, (mu, C) = mv_simple()
 
-    hmc = pm.HamiltonianMC(model.vars,  C, is_cov = True, model = model)
-    mh = pm.Metropolis(model.vars , C, is_cov = True, scaling = 2, model = model)
+    hmc = pm.HamiltonianMC(model.vars,  C, is_cov=True, model=model)
+    mh = pm.Metropolis(model.vars, model=model)
     slicer = pm.Slice(model.vars, model=model)
     compound = pm.CompoundStep([hmc, mh])
 
@@ -25,9 +25,9 @@ def test_step_continuous():
 
     for st in steps:
         np.random.seed(1)
-        h = sample(8000, st, start, track_progress=False, model = model)
+        h = sample(8000, st, start, model=model)
         for (var, stat, val, bound) in check:
             np.random.seed(1)
-            h = sample(8000, st, start, track_progess=False, model = model)
+            h = sample(8000, st, start, model=model)
 
             yield check_stat,repr(st), h, var, stat, val, bound