Changeset 712

Timestamp:

02/16/10 12:33:37 (2 years ago)

Author:

apdavison

Message:

Moved the Space class out of common into its own module

Location:

trunk/src

Files:

• __init__.py (modified) (1 diff)
• brian/__init__.py (modified) (2 diffs)
• common.py (modified) (1 diff)
• connectors.py (modified) (5 diffs)
• connectors2.py (modified) (3 diffs)
• nest/__init__.py (modified) (2 diffs)
• neuron/__init__.py (modified) (2 diffs)
• pcsim/__init__.py (modified) (2 diffs)
• space.py (added)

trunk/src/__init__.py

@@ -67 +67 @@
 
 __version__ = '0.7pre ( $Rev$)'.replace(' $','')
-__all__ = ["common", "random", "nest", "neuron", "pcsim", "brian", "recording", "errors"]
+__all__ = ["common", "random", "nest", "neuron", "pcsim", "brian", "recording", "errors", "space"]
 

trunk/src/brian/__init__.py

@@ -9 +9 @@
 #import brian_no_units_no_warnings
 from pyNN.brian import simulator
-from pyNN import common, recording, __doc__
+from pyNN import common, recording, space, __doc__
 common.simulator = simulator
 recording.simulator = simulator
@@ -172 +172 @@
 
 
-Space = common.Space
+Space = space.Space

trunk/src/common.py

@@ -133 +133 @@
         raise errors.ConnectionError("delay (%s) is out of range [%s,%s]" % (delay, get_min_delay(), get_max_delay()))
     return delay
-
-def distance(src, tgt, mask=None, scale_factor=1.0, offset=0.0,
-             periodic_boundaries=None): # may need to add an offset parameter
-    """
-    Return the Euclidian distance between two cells.
-    `mask` allows only certain dimensions to be considered, e.g.::
-      * to ignore the z-dimension, use `mask=array([0,1])`
-      * to ignore y, `mask=array([0,2])`
-      * to just consider z-distance, `mask=array([2])`
-    `scale_factor` allows for different units in the pre- and post- position
-    (the post-synaptic position is multipied by this quantity).
-    """
-    d = src.position - scale_factor*(tgt.position + offset)
-    
-    if not periodic_boundaries == None:
-        d = numpy.minimum(abs(d), periodic_boundaries-abs(d))
-    if mask is not None:
-        d = d[mask]
-    return numpy.sqrt(numpy.dot(d, d))
-
-
-class Space(object):
-    
-    AXES = {'x' : [0],    'y': [1],    'z': [2],
-            'xy': [0,1], 'yz': [1,2], 'xz': [0,2], 'xyz': range(3), None: range(3)}
-    
-    def __init__(self, axes=None, scale_factor=1.0, offset=0.0,
-                 periodic_boundaries=None):
-        """
-        axes -- if not supplied, then the 3D distance is calculated. If supplied,
-            axes should be a string containing the axes to be used, e.g. 'x', or
-            'yz'. axes='xyz' is the same as axes=None.
-        scale_factor -- it may be that the pre and post populations use
-            different units for position, e.g. degrees and µm. In this case,
-            `scale_factor` can be specified, which is applied to the positions
-            in the post-synaptic population.
-        offset -- if the origins of the coordinate systems of the pre- and post-
-            synaptic populations are different, `offset` can be used to adjust
-            for this difference. The offset is applied before any scaling.
-        periodic_boundaries -- either `None`, or a tuple giving the boundaries
-            for each dimension, e.g. `((x_min, x_max), None, (z_min, z_max))`.
-        """
-        self.periodic_boundaries = periodic_boundaries
-        self.axes = numpy.array(Space.AXES[axes])
-        self.scale_factor = scale_factor
-        self.offset = offset
-        
-    def distances(self, A, B):
-        """
-        Calculate the distance matrix between two sets of coordinates, given
-        the topology of the current space.
-        From http://projects.scipy.org/pipermail/numpy-discussion/2007-April/027203.html
-        """
-        if len(A.shape) == 1:
-            A = A.reshape(3, 1)
-        if len(B.shape) == 1:
-            B = B.reshape(3, 1)
-        B = self.scale_factor*(B + self.offset)
-        d = numpy.zeros((A.shape[1], B.shape[1]), dtype=A.dtype)
-        for axis in self.axes:
-            diff2 = A[axis,:,None] - B[axis,:]
-            if self.periodic_boundaries is not None:
-                boundaries = self.periodic_boundaries[axis]
-                if boundaries is not None:
-                    range = boundaries[1]-boundaries[0]
-                    ad2 = abs(diff2)
-                    diff2 = numpy.minimum(ad2, range-ad2)
-            diff2 **= 2
-            d += diff2
-        numpy.sqrt(d, d)
-        return d
 
 

trunk/src/connectors.py

@@ -21 +21 @@
                   sin, sinh, sqrt, tan, tanh
 from pyNN import random, common, errors
+from pyNN.space import Space
 
 logger = logging.getLogger("PyNN")
@@ -147 +148 @@
     """
     
-    def __init__(self, allow_self_connections=True, weights=0.0, delays=None, space=common.Space()):
+    def __init__(self, allow_self_connections=True, weights=0.0, delays=None, space=Space()):
         """
         Create a new connector.
@@ -455 +456 @@
     """
     
-    def __init__(self, p_connect, allow_self_connections=True, weights=0.0, delays=None, space=common.Space()):
+    def __init__(self, p_connect, allow_self_connections=True, weights=0.0, delays=None, space=Space()):
         """
         Create a new connector.
@@ -500 +501 @@
     
     def __init__(self, d_expression, allow_self_connections=True,
-                 weights=0.0, delays=None, space=common.Space()):
+                 weights=0.0, delays=None, space=Space()):
         """
         Create a new connector.
@@ -524 +525 @@
         assert isinstance(allow_self_connections, bool)
         self.allow_self_connections = allow_self_connections
-        assert isinstance(space, common.Space)
+        assert isinstance(space, Space)
         self.space = space
 

trunk/src/connectors2.py

@@ -1 +1 @@
 import numpy
 from pyNN import common
+from pyNN.space import Space
 from pyNN.random import RandomDistribution
 from numpy import exp
@@ -87 +88 @@
     
     def __init__(self, allow_self_connections=True,
-                 weights=0.0, delays=None, space=common.Space()):
+                 weights=0.0, delays=None, space=Space()):
         """
         Create a new connector.
@@ -133 +134 @@
     
     def __init__(self, p_connect, allow_self_connections=True,
-                 weights=0.0, delays=None, space=common.Space()):
+                 weights=0.0, delays=None, space=Space()):
         """
         Create a new connector.

trunk/src/nest/__init__.py

@@ -7 +7 @@
 import nest
 from pyNN.nest import simulator
-from pyNN import common, recording, errors, __doc__
+from pyNN import common, recording, errors, space, __doc__
 common.simulator = simulator
 recording.simulator = simulator
@@ -433 +433 @@
 
 
-Space = common.Space
-
-# ==============================================================================
+Space = space.Space
+
+# ==============================================================================

trunk/src/neuron/__init__.py

@@ -9 +9 @@
 from pyNN.random import *
 from pyNN.neuron import simulator
-from pyNN import common, recording, __doc__
+from pyNN import common, recording, space, __doc__
 common.simulator = simulator
 recording.simulator = simulator
@@ -285 +285 @@
 
 
-Space = common.Space
-
-# ==============================================================================
+Space = space.Space
+
+# ==============================================================================

trunk/src/pcsim/__init__.py

@@ -15 +15 @@
 
 import pyNN.random
-from pyNN import common, recording, errors, __doc__
+from pyNN import common, recording, errors, space, __doc__
 from pyNN.pcsim import simulator
 common.simulator = simulator
@@ -822 +822 @@
     
 
-Space = common.Space
+Space = space.Space
 
 # ==============================================================================