--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sparse_random_autoassociator/parameters.py	Mon Jul 07 01:54:46 2008 -0400
@@ -0,0 +1,28 @@
+"""
+Parameters (weights) used by the L{Model}.
+"""
+
+import numpy
+import globals
+
+class Parameters:
+    """
+    Parameters used by the L{Model}.
+    """
+    def __init__(self, input_dimension=globals.INPUT_DIMENSION, hidden_dimension=globals.HIDDEN_DIMENSION, randomly_initialize=False, seed=globals.SEED):
+        """
+        Initialize L{Model} parameters.
+        @param randomly_initialize: If True, then randomly initialize
+        according to the given seed. If False, then just use zeroes.
+        """
+        if randomly_initialize:
+            numpy.random.seed(seed)
+            self.w1 = (numpy.random.rand(input_dimension, hidden_dimension)-0.5)/input_dimension
+            self.w2 = (numpy.random.rand(hidden_dimension, input_dimension)-0.5)/hidden_dimension
+            self.b1 = numpy.zeros(hidden_dimension)
+            self.b2 = numpy.zeros(input_dimension)
+        else:
+            self.w1 = numpy.zeros((input_dimension, hidden_dimension))
+            self.w2 = numpy.zeros((hidden_dimension, input_dimension))
+            self.b1 = numpy.zeros(hidden_dimension)
+            self.b2 = numpy.zeros(input_dimension)