reordered documentation of raw_randomstreams

doc/library/tensor/raw_random.txt

@@ -6,7 +6,6 @@
 =============================================
 
 .. module:: raw_random
-   :platform: Unix, Windows
    :synopsis: symbolic random variables
 .. moduleauthor:: LISA
 
@@ -17,6 +16,80 @@ the friendlier :class:`RandomStreams` interface.
 Reference
 =========
 
+.. class:: RandomStreamsBase(object)
+    
+    This is the interface for the
+    :class:`theano.tensor.shared_randomstreams.RandomStreams` subclass and the
+    :class:`theano.tensor.randomstreams.RandomStreams` subclass.
+
+    .. method:: binomial(self, size=(), n=1, prob=0.5, ndim=None):
+
+        Sample n times with probability of success prob for each trial, return the number of
+        successes.
+
+        If the size argument is ambiguous on the number of dimensions, the first argument may be a
+        plain integer to supplement the missing information.
+
+    .. method:: uniform(self,  size=(), low=0.0, high=1.0, ndim=None):
+
+        Sample a tensor of given size whose element from a uniform distribution between low and high.
+
+        If the size argument is ambiguous on the number of
+        dimensions, the first argument may be a plain integer
+        to supplement the missing information.
+
+    .. method:: normal(self, size=(), avg=0.0, std=1.0, ndim=None):
+
+        Usage: normal(random_state, size,
+        Sample from a normal distribution centered on avg with
+        the specified standard deviation (std)
+
+        If the size argument is ambiguous on the number of
+        dimensions, the first argument may be a plain integer
+        to supplement the missing information.
+
+    .. method:: random_integers(self, size=(), low=0, high=1, ndim=None):
+
+        Usage: random_integers(random_state, size, low=0, high=1)
+        Sample a random integer between low and high, both inclusive.
+
+        If the size argument is ambiguous on the number of
+        dimensions, the first argument may be a plain integer
+        to supplement the missing information.
+
+    .. method:: permutation(self, size=(), n=1, ndim=None):
+
+        Returns permutations of the integers between 0 and n-1, as many times
+        as required by size. For instance, if size=(p,q), p*q permutations
+        will be generated, and the output shape will be (p,q,n), because each
+        permutation is of size n.
+
+        Theano tries to infer the number of dimensions from the length of the size argument, but you
+        may always specify it with the `ndim` parameter.
+
+        .. note:: 
+            Note that the output will then be of dimension ndim+1.
+
+    .. method:: multinomial(self, size=(), n=1, pvals=[0.5, 0.5], ndim=None):
+
+        Sample n times from a multinomial distribution defined by probabilities pvals,
+        as many times as required by size. For instance, if size=(p,q), p*q
+        samples will be drawn, and the output shape will be (p,q,len(pvals)).
+
+        Theano tries to infer the number of dimensions from the length of the size argument, but you
+        may always specify it with the `ndim` parameter.
+
+        .. note:: 
+            Note that the output will then be of dimension ndim+1.
+
+    .. method:: shuffle_row_elements(self, input):
+        
+        Return a variable with every row (rightmost index) shuffled.
+        
+        This uses permutation random variable internally, available via the ``.permutation``
+        attribute of the return value.
+    
+
 .. class:: RandomStateType(gof.Type)
 
     A `Type` for variables that will take ``numpy.random.RandomState`` values.
@@ -96,72 +169,3 @@ Reference
 
     :returns: :class:`RandomVariable`, NewRandomState
 
-.. class:: RandomStreamsBase(object)
-
-    .. method:: binomial(self, size=(), n=1, prob=0.5, ndim=None):
-
-        Sample n times with probability of success prob for each trial, return the number of
-        successes.
-
-        If the size argument is ambiguous on the number of dimensions, the first argument may be a
-        plain integer to supplement the missing information.
-
-    .. method:: uniform(self,  size=(), low=0.0, high=1.0, ndim=None):
-
-        Sample a tensor of given size whose element from a uniform distribution between low and high.
-
-        If the size argument is ambiguous on the number of
-        dimensions, the first argument may be a plain integer
-        to supplement the missing information.
-
-    .. method:: normal(self, size=(), avg=0.0, std=1.0, ndim=None):
-
-        Usage: normal(random_state, size,
-        Sample from a normal distribution centered on avg with
-        the specified standard deviation (std)
-
-        If the size argument is ambiguous on the number of
-        dimensions, the first argument may be a plain integer
-        to supplement the missing information.
-
-    .. method:: random_integers(self, size=(), low=0, high=1, ndim=None):
-
-        Usage: random_integers(random_state, size, low=0, high=1)
-        Sample a random integer between low and high, both inclusive.
-
-        If the size argument is ambiguous on the number of
-        dimensions, the first argument may be a plain integer
-        to supplement the missing information.
-
-    .. method:: permutation(self, size=(), n=1, ndim=None):
-
-        Returns permutations of the integers between 0 and n-1, as many times
-        as required by size. For instance, if size=(p,q), p*q permutations
-        will be generated, and the output shape will be (p,q,n), because each
-        permutation is of size n.
-
-        Theano tries to infer the number of dimensions from the length of the size argument, but you
-        may always specify it with the `ndim` parameter.
-
-        .. note:: 
-            Note that the output will then be of dimension ndim+1.
-
-    .. method:: multinomial(self, size=(), n=1, pvals=[0.5, 0.5], ndim=None):
-
-        Sample n times from a multinomial distribution defined by probabilities pvals,
-        as many times as required by size. For instance, if size=(p,q), p*q
-        samples will be drawn, and the output shape will be (p,q,len(pvals)).
-
-        Theano tries to infer the number of dimensions from the length of the size argument, but you
-        may always specify it with the `ndim` parameter.
-
-        .. note:: 
-            Note that the output will then be of dimension ndim+1.
-
-    .. method:: shuffle_row_elements(self, input):
-        
-        Return a variable with every row (rightmost index) shuffled.
-        
-        This uses permutation random variable internally, available via the ``.permutation``
-        attribute of the return value.
-