Made name() a classmethod. Closes #1399.

MichaelClerx · MichaelClerx · commit 9221e3d8f470 · 2026-02-05T16:50:04.000Z
diff --git a/pints/_abc/__init__.py b/pints/_abc/__init__.py
@@ -16,10 +16,9 @@ class ABCSampler(pints.Loggable, pints.TunableMethod):
     :class:`pints.TunableMethod` interfaces.
     """
 
+    @classmethod
     def name(self):
-        """
-        Returns this method's full name.
-        """
+        """ Returns this method's full name. """
         raise NotImplementedError
 
     def ask(self):
diff --git a/pints/_abc/_abc_rejection.py b/pints/_abc/_abc_rejection.py
@@ -46,6 +46,7 @@ def __init__(self, log_prior):
         self._xs = None
         self._ready_for_tell = False
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.ABCSampler.name()`. """
         return 'Rejection ABC'
diff --git a/pints/_abc/_abc_smc.py b/pints/_abc/_abc_smc.py
@@ -106,6 +106,7 @@ def __init__(self, log_prior, perturbation_kernel=None,
             raise ValueError('Provided perturbation kernel must be an instance'
                   ' of pints.LogPrior')
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.ABCSampler.name()`. """
         return 'ABC-SMC'
diff --git a/pints/_mcmc/__init__.py b/pints/_mcmc/__init__.py
@@ -18,6 +18,7 @@ class MCMCSampler(pints.Loggable, pints.TunableMethod):
     :class:`pints.TunableMethod` interfaces.
     """
 
+    @classmethod
     def name(self):
         """
         Returns this method's full name.
diff --git a/pints/_mcmc/_differential_evolution.py b/pints/_mcmc/_differential_evolution.py
@@ -176,6 +176,7 @@ def n_hyper_parameters(self):
         """ See :meth:`TunableMethod.n_hyper_parameters()`. """
         return 5
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Differential Evolution MCMC'
diff --git a/pints/_mcmc/_dram_ac.py b/pints/_mcmc/_dram_ac.py
@@ -104,6 +104,7 @@ def _generate_proposal(self):
             self._sigma[self._proposal_count])
         return proposed
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Delayed Rejection Adaptive Metropolis (Dram) MCMC'
diff --git a/pints/_mcmc/_dream.py b/pints/_mcmc/_dream.py
@@ -214,6 +214,7 @@ def _log_write(self, logger):
         # logger.log(self._acceptance)
         # TODO
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'DiffeRential Evolution Adaptive Metropolis (DREAM) MCMC'
diff --git a/pints/_mcmc/_emcee_hammer.py b/pints/_mcmc/_emcee_hammer.py
@@ -136,6 +136,7 @@ def _initialise(self):
         # Update sampler state
         self._running = True
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Emcee Hammer MCMC'
diff --git a/pints/_mcmc/_haario_ac.py b/pints/_mcmc/_haario_ac.py
@@ -70,6 +70,7 @@ def _generate_proposal(self):
         return np.random.multivariate_normal(
             self._current, self._sigma * np.exp(self._log_lambda))
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Haario adaptive covariance MCMC'
diff --git a/pints/_mcmc/_haario_bardenet_ac.py b/pints/_mcmc/_haario_bardenet_ac.py
@@ -72,6 +72,7 @@ def _generate_proposal(self):
         return np.random.multivariate_normal(
             self._current, self._sigma * np.exp(self._log_lambda))
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Haario-Bardenet adaptive covariance MCMC'
diff --git a/pints/_mcmc/_hamiltonian.py b/pints/_mcmc/_hamiltonian.py
@@ -185,6 +185,7 @@ def n_hyper_parameters(self):
         """ See :meth:`TunableMethod.n_hyper_parameters()`. """
         return 2
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Hamiltonian Monte Carlo'
diff --git a/pints/_mcmc/_mala.py b/pints/_mcmc/_mala.py
@@ -176,6 +176,7 @@ def _log_write(self, logger):
         """ See :meth:`Loggable._log_write()`. """
         logger.log(self._acceptance)
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Metropolis-Adjusted Langevin Algorithm (MALA)'
diff --git a/pints/_mcmc/_metropolis.py b/pints/_mcmc/_metropolis.py
@@ -100,6 +100,7 @@ def _log_write(self, logger):
         """ See :meth:`Loggable._log_write()`. """
         logger.log(self._acceptance)
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Metropolis random walk MCMC'
diff --git a/pints/_mcmc/_monomial_gamma_hamiltonian.py b/pints/_mcmc/_monomial_gamma_hamiltonian.py
@@ -291,6 +291,7 @@ def mass(self):
         """
         return self._m
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Monomial-Gamma Hamiltonian Monte Carlo'
diff --git a/pints/_mcmc/_nuts.py b/pints/_mcmc/_nuts.py
@@ -659,6 +659,7 @@ def n_hyper_parameters(self):
         """ See :meth:`TunableMethod.n_hyper_parameters()`. """
         return 1
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'No-U-Turn MCMC'
diff --git a/pints/_mcmc/_population.py b/pints/_mcmc/_population.py
@@ -153,6 +153,7 @@ def _log_write(self, logger):
         logger.log(self._j)
         logger.log('yes' if self._have_exchanged else 'no')
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Population MCMC'
diff --git a/pints/_mcmc/_rao_blackwell_ac.py b/pints/_mcmc/_rao_blackwell_ac.py
@@ -78,6 +78,7 @@ def _generate_proposal(self):
         return np.random.multivariate_normal(
             self._current, self._lambda * self._sigma)
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Rao-Blackwell adaptive covariance MCMC'
diff --git a/pints/_mcmc/_relativistic.py b/pints/_mcmc/_relativistic.py
@@ -320,6 +320,7 @@ def n_hyper_parameters(self):
         """ See :meth:`TunableMethod.n_hyper_parameters()`. """
         return 4
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Relativistic MCMC'
diff --git a/pints/_mcmc/_slice_doubling.py b/pints/_mcmc/_slice_doubling.py
@@ -385,6 +385,7 @@ def expansion_steps(self):
         """
         return self._p
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Slice Sampling - Doubling'
diff --git a/pints/_mcmc/_slice_rank_shrinking.py b/pints/_mcmc/_slice_rank_shrinking.py
@@ -151,6 +151,7 @@ def current_slice_height(self):
         """
         return self._current_log_y
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Slice Sampling - Covariance-Adaptive: Rank Shrinking.'
diff --git a/pints/_mcmc/_slice_stepout.py b/pints/_mcmc/_slice_stepout.py
@@ -420,6 +420,7 @@ def prob_overrelaxed(self):
         """
         return self._prob_overrelaxed
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.MCMCSampler.name()`. """
         return 'Slice Sampling - Stepout'
diff --git a/pints/_nested/__init__.py b/pints/_nested/__init__.py
@@ -93,6 +93,7 @@ def n_hyper_parameters(self):
         """ See :meth:`TunableMethod.n_hyper_parameters()`. """
         raise NotImplementedError
 
+    @classmethod
     def name(self):
         """ Name of sampler """
         raise NotImplementedError
diff --git a/pints/_nested/_ellipsoid.py b/pints/_nested/_ellipsoid.py
@@ -340,6 +340,7 @@ def _draw_from_ellipsoid(self, covmat, cent, npts):
 
         return pnts
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.NestedSampler.name()`. """
         return 'Nested ellipsoidal sampler'
diff --git a/pints/_nested/_rejection.py b/pints/_nested/_rejection.py
@@ -102,6 +102,7 @@ def set_hyper_parameters(self, x):
         """
         self.set_n_active_points(x[0])
 
+    @classmethod
     def name(self):
         """ See :meth:`pints.NestedSampler.name()`. """
         return 'Nested rejection sampler'
diff --git a/pints/_optimisers/__init__.py b/pints/_optimisers/__init__.py
@@ -186,10 +186,9 @@ def f_guessed(self):
         """
         return self.f_best()
 
+    @classmethod
     def name(self):
-        """
-        Returns this method's full name.
-        """
+        """ Returns this method's full name. """
         raise NotImplementedError
 
     def needs_sensitivities(self):
diff --git a/pints/_optimisers/_adam.py b/pints/_optimisers/_adam.py
@@ -119,6 +119,7 @@ def _log_write(self, logger):
         logger.log(self._b1t)
         logger.log(self._b2t)
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Adam'
diff --git a/pints/_optimisers/_cmaes.py b/pints/_optimisers/_cmaes.py
@@ -161,6 +161,7 @@ def _initialise(self):
         # Update optimiser state
         self._running = True
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Covariance Matrix Adaptation Evolution Strategy (CMA-ES)'
diff --git a/pints/_optimisers/_cmaes_bare.py b/pints/_optimisers/_cmaes_bare.py
@@ -223,6 +223,7 @@ def _initialise(self):
         # Update optimiser state
         self._running = True
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Bare-bones CMA-ES'
diff --git a/pints/_optimisers/_gradient_descent.py b/pints/_optimisers/_gradient_descent.py
@@ -60,6 +60,7 @@ def learning_rate(self):
         """ Returns this optimiser's learning rate. """
         return self._eta
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Gradient descent'
diff --git a/pints/_optimisers/_irpropmin.py b/pints/_optimisers/_irpropmin.py
@@ -165,6 +165,7 @@ def min_step_size(self):
         """ Returns the minimum step size (or ``None`` if not set). """
         return self._step_min
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'iRprop-'
diff --git a/pints/_optimisers/_nelder_mead.py b/pints/_optimisers/_nelder_mead.py
@@ -218,6 +218,7 @@ def f_best(self):
         """ See: :meth:`pints.Optimiser.f_best()`. """
         return self._fs[0] if self._running else np.inf
 
+    @classmethod
     def name(self):
         """ See: :meth:`pints.Optimiser.name()`. """
         return 'Nelder-Mead'
diff --git a/pints/_optimisers/_pso.py b/pints/_optimisers/_pso.py
@@ -172,6 +172,7 @@ def _log_write(self, logger):
         for f in self._fl:
             logger.log(f)
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Particle Swarm Optimisation (PSO)'
diff --git a/pints/_optimisers/_snes.py b/pints/_optimisers/_snes.py
@@ -120,6 +120,7 @@ def _initialise(self):
         # Update optimiser state
         self._running = True
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Seperable Natural Evolution Strategy (SNES)'
diff --git a/pints/_optimisers/_xnes.py b/pints/_optimisers/_xnes.py
@@ -131,6 +131,7 @@ def _initialise(self):
         # Update optimiser state
         self._running = True
 
+    @classmethod
     def name(self):
         """ See :meth:`Optimiser.name()`. """
         return 'Exponential Natural Evolution Strategy (xNES)'
diff --git a/pints/tests/test_opt_controller.py b/pints/tests/test_opt_controller.py
@@ -46,6 +46,7 @@ def __init__(self, x0, sigma0=None, boundaries=None):
     def ask(self):
         return np.array(self.xs[self._i: self._i + self.np])
 
+    @classmethod
     def name(self):
         return 'List1D'
 
