[estimate] add bounds. Hopefully fixes #81

smcpp/commands/command.py

@@ -84,6 +84,12 @@ def add_common_estimation_args(parser):
                            default=smcpp.defaults.xtol,
                            help=r"x tolerance for optimizer. "
                            "optimizer will stop when |x' - x|_\infty < xtol")
+    optimizer.add_argument('--Nmax', type=float,
+            default=smcpp.defaults.maximum_population_size,
+            help="upper bound on scaled effective population size")
+    optimizer.add_argument('--Nmin', type=float,
+            default=smcpp.defaults.minimum_population_size,
+            help="lower bound on scaled effective population size")
     optimizer.add_argument('--regularization-penalty', '-rp',
                            type=float, help="regularization penalty",
                            default=smcpp.defaults.regularization_penalty)

smcpp/defaults.py

@@ -8,7 +8,9 @@
 maximum = 1e4
 t1 = None
 tK = None
-regularization_degree = 1
+regularization_degree = 2
 spline = "piecewise"
 cores = None
 perplexity_threshold = .5
+minimum_population_size = 1e-3
+maximum_population_size = 1e3

smcpp/model.py

@@ -187,7 +187,11 @@ def f(x):
         self[:] = res.x
 
     def stepwise_values(self):
-        return self(np.cumsum(self.s))
+        ret = np.clip(self(np.cumsum(self.s)),
+                smcpp.defaults.minimum_population_size,
+                smcpp.defaults.maximum_population_size)
+        # logger.debug("self[:]: %s\ns: %s\nstep(): %s", self[:], self.s, ret)
+        return ret
 
     def reset(self):
         self[:] = 0.