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docs/tutorials/lesson1.md

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@@ -1188,6 +1188,31 @@ ngc-learn operates and care should be taken to check that your system is evolvin
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in the way that you expect (working with the online functionality of an NGC
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system will be the subject of a future advanced lesson).
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### Setting the Order of Synaptic Adjustments
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Normally, when you set update rules for cables that you would like to evolve
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with time, your `NGCGraph` will determine its own order in which the calculated
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adjustments appear in the `delta` object (returned from `.settle()`) as well as
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the order in which learnable parameters appear in the `.theta` data member.
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If you wanted the order of the cables to appear in a certain way in `.theta`
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(which would affect the order of `delta`), you can use the `.set_learning_order()`
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function before you call the `.compile()` routine for your `NGCGraph`.
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This was actually done earlier in the last section, where you set the order
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of the cable parameters in `.theta` to be cable `b_bmu` followed by cable `a_amu`
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as in the code snippet reproduced from earlier:
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```python
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circuit.set_learning_order([b_bmu, a_amu]) # enforces order - b_bmu then a_amu
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```
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Setting the order of learnable cables directly affects what is returned by
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functions such as `.settle()` and `.step()` since, internally, the `NGCGraph` will
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organize itself to ensure that the order of updates in `delta` exactly match
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the order of learnable parameters stored in `.theta`. (Note: if a cable has a
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synaptic matrix `A` and bias `b`, then always the order will be that cable's
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`A` followed by `b` in `.theta`.)
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### Extracting Signals and Properties: Getter Functions
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Two of the most important "getter" functions you will want to be familiar with

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