privatization

nifty5/__init__.py

@@ -64,7 +64,7 @@ from .minimization.nonlinear_cg import NonlinearCG
 from .minimization.descent_minimizers import (
     DescentMinimizer, SteepestDescent, VL_BFGS, L_BFGS, RelaxedNewton,
     NewtonCG)
-from .minimization.scipy_minimizer import (ScipyMinimizer, L_BFGS_B, ScipyCG)
+from .minimization.scipy_minimizer import L_BFGS_B
 from .minimization.energy import Energy
 from .minimization.quadratic_energy import QuadraticEnergy
 from .minimization.energy_adapter import EnergyAdapter
@@ -73,7 +73,7 @@ from .minimization.kl_energy import KL_Energy
 from .sugar import *
 from .plot import Plot
 
-from .library.smooth_linear_amplitude import (SLAmplitude, CepstrumOperator)
+from .library.smooth_linear_amplitude import SLAmplitude, CepstrumOperator
 from .library.inverse_gamma_operator import InverseGammaOperator
 from .library.los_response import LOSResponse
 from .library.dynamic_operator import (dynamic_operator,

nifty5/minimization/scipy_minimizer.py

@@ -93,7 +93,7 @@ class _MinHelper(object):
         return _toArray_rw(res)
 
 
-class ScipyMinimizer(Minimizer):
+class _ScipyMinimizer(Minimizer):
     """Scipy-based minimizer
 
     Parameters
@@ -136,19 +136,19 @@ class ScipyMinimizer(Minimizer):
 
 
 def L_BFGS_B(ftol, gtol, maxiter, maxcor=10, disp=False, bounds=None):
-    """Returns a ScipyMinimizer object carrying out the L-BFGS-B algorithm.
+    """Returns a _ScipyMinimizer object carrying out the L-BFGS-B algorithm.
 
     See Also
     --------
-    ScipyMinimizer
+    _ScipyMinimizer
     """
     options = {"ftol": ftol, "gtol": gtol, "maxiter": maxiter,
                "maxcor": maxcor, "disp": disp}
-    return ScipyMinimizer("L-BFGS-B", options, False, bounds)
+    return _ScipyMinimizer("L-BFGS-B", options, False, bounds)
 
 
-class ScipyCG(Minimizer):
-    """Returns a ScipyMinimizer object carrying out the conjugate gradient
+class _ScipyCG(Minimizer):
+    """Returns a _ScipyMinimizer object carrying out the conjugate gradient
     algorithm as implemented by SciPy.
 
     This class is only intended for double-checking NIFTy's own conjugate

test/test_minimizers.py

@@ -41,7 +41,8 @@ minimizers = [
 
 newton_minimizers = ['ift.RelaxedNewton(IC)']
 quadratic_only_minimizers = [
-    'ift.ConjugateGradient(IC)', 'ift.ScipyCG(tol=1e-5, maxiter=300)'
+    'ift.ConjugateGradient(IC)',
+    'ift.minimization.scipy_minimizer._ScipyCG(tol=1e-5, maxiter=300)'
 ]
 slow_minimizers = ['ift.SteepestDescent(IC)']