Added documentation about ifelse vs switch.

doc/tutorial/conditions.txt

+.. _tutconditions:
+
+==========
+Conditions
+==========
+
+**IfElse vs switch**
+
+- Build condition over symbolic variables.
+- IfElse Op takes a `boolean` condition and two variables to compute as input.
+- Switch take a `tensor` as condition and two variables to compute as input.
+  - Switch is an elemwise operation. It is more general then ifelse.
+- While Switch Op evaluates both 'output' variables, IfElse Op is lazy and only
+  evaluates one variable respect to the condition.
+
+**Example**
+
+.. code-block:: python
+
+  from theano import tensor as T
+  from theano.lazycond import ifelse
+  import theano, time, numpy
+
+  a,b = T.scalars('a','b')
+  x,y = T.matrices('x','y')
+  
+  z_switch = T.switch(T.lt(a,b), T.mean(x), T.mean(y))
+  z_lazy = ifelse(T.lt(a,b), T.mean(x), T.mean(y))
+
+  f_switch = theano.function([a,b,x,y], z_switch, 
+                      mode=theano.Mode(linker='vm'))
+  f_lazyifelse = theano.function([a,b,x,y], z_lazy,
+                      mode=theano.Mode(linker='vm'))
+
+  val1 = 0.
+  val2 = 1.
+  big_mat1 = numpy.ones((10000,1000))
+  big_mat2 = numpy.ones((10000,1000))
+
+  n_times = 10
+
+  tic = time.clock()
+  for i in xrange(n_times):
+      f_switch(val1, val2, big_mat1, big_mat2)
+  print 'time spent evaluating both values %f sec'%(time.clock()-tic)
+
+  tic = time.clock()
+  for i in xrange(n_times):
+      f_lazyifelse(val1, val2, big_mat1, big_mat2)
+  print 'time spent evaluating one value %f sec'%(time.clock()-tic)
+
+In this example, IfElse Op spend less time (about an half) than Switch
+since it computes only one variable instead of both.
+
+.. code-block:: python
+  >>> python ifelse_switch.py
+  time spent evaluating both values 0.6700 sec
+  time spent evaluating one value 0.3500 sec
+
+
+It is actually important to use  ``linker='vm'`` or ``linker='cvm'``,
+otherwise IfElse will compute both variables and take the same computation
+time as the Switch Op. The linker is not currently set by default to 'cvm' but
+it will be in a near future.
+
+There is not an optimization to automatically change a switch with a broadcasted scalar to an ifelse, as this is not always the faster. See this `ticket <http://trac-hg.assembla.com/theano/ticket/764>`_

doc/tutorial/index.txt

@@ -32,6 +32,7 @@ you out.
     symbolic_graphs
     modes
     aliasing
+    conditions
     loop
     using_gpu
     pycuda