Merge pull request #698 from apdavison/improve-warnings

Move warnings about missing features to the point where they are used

pyNN/connectors.py

@@ -939,10 +939,8 @@ def __init__(self, cset, safe=True, callback=None):
             """
             Connector.__init__(self, safe=safe, callback=callback)
             self.cset = cset
-            if csa.arity(cset) == 0:
-                pass
-            else:
-                assert csa.arity(cset) == 2, 'must specify mask or connection-set with arity 2'
+            arity = csa.arity(cset)
+            assert arity in (0, 2), 'must specify mask or connection-set with arity 0 or 2'
     else:
         def __init__(self, cset, safe=True, callback=None):
             raise RuntimeError("CSAConnector not available---couldn't import csa module")

pyNN/nest/__init__.py

@@ -47,11 +47,6 @@
 
 logger = logging.getLogger("PyNN")
 
-try:
-    nest.Install('pynn_extensions')
-except nest.kernel.NESTError as err:
-    warnings.warn("Unable to install NEST extensions. Certain models may not be available.")
-
 
 # ==============================================================================
 #   Utility functions

pyNN/nest/connectors.py

@@ -7,6 +7,7 @@
 """
 
 import logging
+from warnings import warn
 import nest
 try:
     import csa
@@ -28,70 +29,56 @@
                              FromFileConnector,
                              CloneConnector,
                              ArrayConnector,
-                             FixedTotalNumberConnector)
+                             FixedTotalNumberConnector,
+                             CSAConnector as DefaultCSAConnector)
 
 from .random import NativeRNG, NEST_RDEV_TYPES
 
 
 logger = logging.getLogger("PyNN")
 
 
-if not nest.ll_api.sli_func("statusdict/have_libneurosim ::"):
+class CSAConnector(DefaultCSAConnector):
+    """
+    Use the Connection-Set Algebra (Djurfeldt, 2012) to connect
+    cells. This is an optimized variant of CSAConnector, which
+    iterates the connection-set on the C++ level in NEST.
 
-    print(("CSAConnector: libneurosim support not available in NEST.\n" +
-           "Falling back on PyNN's default CSAConnector.\n" +
-           "Please re-compile NEST using --with-libneurosim=PATH"))
+    See Djurfeldt et al. (2014) doi:10.3389/fninf.2014.00043 for
+    more details about the new interface and a comparison between
+    this and PyNN's native CSAConnector.
 
-    from pyNN.connectors import CSAConnector
+    Takes any of the standard :class:`Connector` optional
+    arguments and, in addition:
 
-else:
+        `cset`:
+            a connection set object.
+    """
 
-    class CSAConnector(Connector):
-        """
-        Use the Connection-Set Algebra (Djurfeldt, 2012) to connect
-        cells. This is an optimized variant of CSAConnector, which
-        iterates the connection-set on the C++ level in NEST.
-
-        See Djurfeldt et al. (2014) doi:10.3389/fninf.2014.00043 for
-        more details about the new interface and a comparison between
-        this and PyNN's native CSAConnector.
-
-        Takes any of the standard :class:`Connector` optional
-        arguments and, in addition:
-
-            `cset`:
-                a connection set object.
-        """
-        parameter_names = ('cset',)
-
-        if haveCSA:
-            def __init__(self, cset, safe=True, callback=None):
-                """
-                """
-                Connector.__init__(self, safe=safe, callback=callback)
-                self.cset = cset
-                arity = csa.arity(cset)
-                assert arity in (0, 2), 'must specify mask or connection-set with arity 0 or 2'
+    def connect(self, projection):
+        if nest.ll_api.sli_func("statusdict/have_libneurosim ::"):
+            return self.cg_connect(projection)
         else:
-            def __init__(self, cset, safe=True, callback=None):
-                raise RuntimeError("CSAConnector not available---couldn't import csa module")
+            warn("Note: using the default CSAConnector. To use the accelerated version for NEST,\n"
+                    "Please re-compile NEST using --with-libneurosim=PATH")
+            return super(CSAConnector, self).connect(projection)
 
-        def connect(self, projection):
-            """Connect-up a Projection."""
+    def cg_connect(self, projection):
+        """Connect-up a Projection using the Connection Generator interface"""
 
-            presynaptic_cells = projection.pre.all_cells.astype('int64')
-            postsynaptic_cells = projection.post.all_cells.astype('int64')
+        presynaptic_cells = projection.pre.all_cells.astype('int64')
+        postsynaptic_cells = projection.post.all_cells.astype('int64')
 
-            if csa.arity(self.cset) == 2:
-                param_map = {'weight': 0, 'delay': 1}
-                nest.CGConnect(presynaptic_cells, postsynaptic_cells, self.cset,
-                               param_map, projection.nest_synapse_model)
-            else:
-                nest.CGConnect(presynaptic_cells, postsynaptic_cells, self.cset,
-                               model=projection.nest_synapse_model)
+        if csa.arity(self.cset) == 2:
+            param_map = {'weight': 0, 'delay': 1}
+            nest.CGConnect(presynaptic_cells, postsynaptic_cells, self.cset,
+                            param_map, projection.nest_synapse_model)
+        else:
+            nest.CGConnect(presynaptic_cells, postsynaptic_cells, self.cset,
+                            model=projection.nest_synapse_model)
 
-            projection._connections = None  # reset the caching of the connection list, since this will have to be recalculated
-            projection._sources.extend(presynaptic_cells)
+        projection._connections = None  # reset the caching of the connection list, since this will have to be recalculated
+        projection._sources.extend(presynaptic_cells)
 
 
 class NESTConnectorMixin(object):

pyNN/nest/simulator.py

@@ -53,6 +53,11 @@ class _State(common.control.BaseState):
 
     def __init__(self):
         super(_State, self).__init__()
+        try:
+            nest.Install('pynn_extensions')
+            self.extensions_loaded = True
+        except nest.kernel.NESTError as err:
+            self.extensions_loaded = False
         self.initialized = False
         self.optimize = False
         self.spike_precision = "off_grid"

pyNN/nest/standardmodels/synapses.py

@@ -27,13 +27,13 @@ class StaticSynapse(synapses.StaticSynapse, NESTSynapseMixin):
 
 class STDPMechanism(synapses.STDPMechanism, NESTSynapseMixin):
     """Specification of STDP models."""
-    
+
     base_translations = build_translations(
         ('weight', 'weight', 1000.0),  # nA->pA, uS->nS
         ('delay', 'delay'),
         ('dendritic_delay_fraction', 'dendritic_delay_fraction')
     )  # will be extended by translations from timing_dependence, etc.
-    
+
     def __init__(self, timing_dependence=None, weight_dependence=None,
                  voltage_dependence=None, dendritic_delay_fraction=1.0,
                  weight=0.0, delay=None):

pyNN/nest/synapses.py

@@ -8,6 +8,7 @@
 import nest
 
 from pyNN.models import BaseSynapseType
+from pyNN.errors import NoModelAvailableError
 from .simulator import state
 from .conversion import make_pynn_compatible, make_sli_compatible
 
@@ -40,7 +41,15 @@ def _get_nest_synapse_model(self):
                 synapse_defaults[name] = value.evaluate(simplify=True)
         synapse_defaults = make_sli_compatible(synapse_defaults)
         synapse_defaults.pop("tau_minus", None)
-        nest.SetDefaults(self.nest_name + '_lbl', synapse_defaults)
+        try:
+            nest.SetDefaults(self.nest_name + '_lbl', synapse_defaults)
+        except nest.lib.hl_api_exceptions.NESTError as err:
+            if not state.extensions_loaded:
+                raise NoModelAvailableError(
+                    "{self.__class__.__name__} is not available."
+                    "There was a problem loading NEST extensions".format(self=self)
+                )
+            raise
         return self.nest_name + '_lbl'
 
     def _get_minimum_delay(self):