Merge branch 'docfixes' into 'docker'

[doc] clariefied session's Algorythms-Unsynchronized Operation documentation

See merge request !216

doc/user/algorithms/guide.rst

@@ -28,7 +28,7 @@
 ============
 
 Graphically represented, :ref:`toolchains` look like a set of interconnected
-blocks. As illustrated in the figure below, each block can accomodate one
+blocks. As illustrated in the figure below, each block can accommodate one
 *Algorithm*, along with the necessary input and output interfaces. We also
 refer to the inputs and outputs collectively as *endpoints*.
 
@@ -212,7 +212,7 @@ The example below illustrates how such an algorithm could be implemented:
            if inputs['in2'].isDataUnitDone():
                out = magical_processing(self.objs)
                outputs['out'].write({'value': out})
-               self.images = [] #reset accumulator for next label
+               self.objs = [] #reset accumulator for next label
 
            return True
 
@@ -229,19 +229,20 @@ Unsynchronized Operation
 ------------------------
 
 Not all inputs for a block need to be synchronized together. In the diagram
-shown below, the block is synchronized with the input ``in`` (as indicated by
-the green circle which matches the color of the input line connecting ``in``).
-The output ``out`` is synchronized with the block. The input ``in2`` is not
-synchronized with the endpoint ``in`` and with the block. A processing block
+shown below, the block is synchronized with the inputs ``in`` and ``in2`` (as indicated by
+the green circle which matches the colour of the input lines connecting ``in`` and ``in2``).
+The output ``out`` is synchronized with the block (and as one can notice locking at the code
+below, outputs signal after every ``in`` input). The input ``in3`` is not
+synchronized with the endpoints ``in``, ``in2`` and with the block. A processing block
 which receives a previously calculated model and must score test samples is a
 good example for this condition. In this case, the user is responsible for
-reading out the contents of ``in2`` explicitly.
+reading out the contents of ``in3`` explicitly.
 
 .. image:: img/case-study-4.*
 
 
 In this case the algorithm will include an explicit loop to read the
-unsynchronized input (``in2``).
+unsynchronized input (``in3``).
 
 .. code-block:: python
    :linenos:
@@ -260,12 +261,15 @@ unsynchronized input (``in2``).
            # Loads the "model" data at the beginning, once
            if self.models is None:
                self.models = []
-               while inputs['in2'].hasMoreData():
-                   inputs['in2'].next()
-                   self.models.append(inputs['in2'].data.value)
+               while inputs['in3'].hasMoreData():
+                   inputs['in3'].next()
+                   self.models.append(inputs['in3'].data.value)
 
-           # Processes the current input in `in', apply the model/models
-           out = magical_processing(inputs['in'].data.value, self.models)
+           # Processes the current input in `in' and `in2', apply the 
+           # model/models
+           out = magical_processing(inputs['in'].data.value,
+                                    inputs['in2'].data.value,
+                                    self.models)
 
            # Writes the output
            outputs.write({'value': out})
@@ -289,18 +293,20 @@ it is safer to treat inputs using their *group*. For example:
 
 
        def process(self, inputs, outputs):
-           # N.B.: this will be called for every unit in `in'
+           # N.B.: this will be called for every unit in `in':
 
            # Loads the "model" data at the beginning, once
            if self.models is None:
                self.models = []
-               group = inputs.groupOf('in2')
+               group = inputs.groupOf('in3')
                while group.hasMoreData():
                    group.next() #synchronously advances the data
-                   self.models.append(group['in2'].data.value)
+                   self.models.append(group['in3'].data.value)
 
-           # Processes the current input in `in', apply the model/models
-           out = magical_processing(inputs['in'].data.value, self.models)
+           # Processes the current input in `in' and `in2', apply the model/models
+           out = magical_processing(inputs['in'].data.value,
+                                    inputs['in2'].data.value,
+                                    self.models)
 
            # Writes the output
            outputs.write({'value': out})

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