Merge pull request #503 from brainpy/doc

[doc] add synapse model documentations

Author: chaoming0625

brainpy/_src/dnn/linear.py

@@ -44,7 +44,7 @@ class Dense(Layer, SupportOnline, SupportOffline, SupportSTDP):
     The number of the input feature. A positive integer.
   num_out: int
     The number of the output features. A positive integer.
-  weight_initializer: optional, Initializer
+  W_initializer: optional, Initializer
     The weight initialization.
   b_initializer: optional, Initializer
     The bias initialization.

brainpy/_src/dyn/projections/plasticity.py

@@ -40,7 +40,8 @@ class STDP_Song2000(Projection):
   where :math:`t_{sp}` denotes the spike time and :math:`A_1` is the increment
   of :math:`A_{pre}`, :math:`A_2` is the increment of :math:`A_{post}` produced by a spike.
 
-  Example::
+  Here is an example of the usage of this class::
+
     import brainpy as bp
     import brainpy.math as bm
 
@@ -138,10 +139,7 @@ def __init__(
       if not post.has_bef_update(self._post_repr):
         syn_cls = syn()
         out_cls = out()
-        if out_label is None:
-          out_name = self.name
-        else:
-          out_name = f'{out_label} // {self.name}'
+        out_name = self.name if out_label is None else f'{out_label} // {self.name}'
         post.add_inp_fun(out_name, out_cls)
         post.add_bef_update(self._post_repr, _AlignPost(syn_cls, out_cls))
       # references
@@ -154,35 +152,29 @@ def __init__(
       # synapse initialization
       self._syn_id = f'Delay({str(delay)}) // {syn.identifier}'
       if not delay_cls.has_bef_update(self._syn_id):
-        # delay
         delay_access = DelayAccess(delay_cls, delay)
-        # synapse
         syn_cls = syn()
-        # add to "after_updates"
         delay_cls.add_bef_update(self._syn_id, _AlignPreMg(delay_access, syn_cls))
-
       # output initialization
-      if out_label is None:
-        out_name = self.name
-      else:
-        out_name = f'{out_label} // {self.name}'
+      out_name = self.name if out_label is None else f'{out_label} // {self.name}'
       post.add_inp_fun(out_name, out)
-
       # references
       self.refs = dict(pre=pre, post=post)  # invisible to `self.nodes()`
       self.refs['delay'] = delay_cls.get_bef_update(self._syn_id)
       self.refs['syn'] = delay_cls.get_bef_update(self._syn_id).syn
       self.refs['out'] = out
 
-    self.refs['pre_trace'] = self.calculate_trace(pre, delay, Expon.desc(pre.num, tau=tau_s))
-    self.refs['post_trace'] = self.calculate_trace(post, None, Expon.desc(post.num, tau=tau_t))
-    # parameters
+    # trace initialization
+    self.refs['pre_trace'] = self._init_trace(pre, delay, Expon.desc(pre.num, tau=tau_s))
+    self.refs['post_trace'] = self._init_trace(post, None, Expon.desc(post.num, tau=tau_t))
+
+    # synapse parameters
     self.tau_s = parameter(tau_s, sizes=self.pre_num)
     self.tau_t = parameter(tau_t, sizes=self.post_num)
     self.A1 = parameter(A1, sizes=self.pre_num)
     self.A2 = parameter(A2, sizes=self.post_num)
 
-  def calculate_trace(
+  def _init_trace(
       self,
       target: DynamicalSystem,
       delay: Union[None, int, float],
@@ -234,5 +226,5 @@ def update(self):
     if issubclass(self.syn.cls, AlignPost):
       self.refs['syn'].add_current(current)  # synapse post current
     else:
-      self.refs['out'].bind_cond(current)
+      self.refs['out'].bind_cond(current)  # align pre
     return current

brainpy/_src/dyn/projections/tests/test_STDP.py

@@ -51,3 +51,4 @@ def run(i, I_pre, I_post):
 
     indices = bm.arange(0, duration, bm.dt)
     bm.for_loop(run, [indices, I_pre, I_post], jit=True)
+    bm.clear_buffer_memory()

brainpy/_src/dynsys.py

@@ -593,6 +593,12 @@ def __repr__(self):
 
 
 class Projection(DynamicalSystem):
+  """Base class to model synaptic projections.
+
+  Args:
+    name: The name of the dynamic system.
+    mode: The computing mode. It should be an instance of :py:class:`~.Mode`.
+  """
 
   def update(self, *args, **kwargs):
     nodes = tuple(self.nodes(level=1, include_self=False).subset(DynamicalSystem).unique().values())
@@ -610,6 +616,10 @@ def reset_state(self, *args, **kwargs):
     else:
       raise ValueError('Do not implement the reset_state() function.')
 
+  def clear_input(self, *args, **kwargs):
+    """Empty function of clearing inputs."""
+    pass
+
 
 class Dynamic(DynamicalSystem):
   """Base class to model dynamics.