@@ -22,5 +22,6 @@ I added the straight_average algorithm to custom_algo.py. This implements the id
Also added was Eric's [trust_weighted_histogram algorithm](Dan's-proposal-for-trust-weighted-histograms). This algorithm requires an additional input, the number of bins, so a `misc_input` field was added to `AlgorithmInput` to include this easily. We will discuss this algorithm a little more below since it brings up some ideas worthy of review.
The next algorithm added was `straight_average_intermediate` which is very similar to `straight_average` but uses `intermediate_results` to allow for correctly sending results to the next level up. In essence the `intermediate_results` are just the Sapienza trust-modified probabilities of every source in the sub-group to be analyzed. The sub-group in this case is a node and its direct descendants (children). The average of the group is calculated and the list of probabilities (modified by trust) become the results for the next level. Two examples of a multi-level tree were created manually to test this concept (just run custom_algo.py). In real life transferring results between nodes will be handled by the server code, so this is really just an experiment to see that things are conceptually ok.
