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========================================================== Skip to step 3 if you don't have a libbitcoin blockchain ========================================================== 1. Generate the raw data needed. It's formatted for direct importing into Python. $ g++ -ggdb collisions.cpp $(pkg-config --cflags --libs libbitcoin) -lgmp $ ./a.out | tee buckets_data.py 2. total_tx_sizes.py will show us the cumulative raw size of all transactions in the blockchain (needs a libbitcoin blockchain - this step can be skipped). $ python total_tx_sizes.py 11719793765 bytes That's around 12 Gb. 3. Display data in a more human friendly format. $ python display_data.py The numbers are the % of colliding txs in a bucket. If 5% of txs share a hash table bucket with another 2 txs then we will see: 3: 5.00 % NOTE: The empty rate and the fill rate for the first bucket seem to match too closely to seem like coincidence. Is this a bug in my code's logic or some underlying property? 4. Generate the data for the graphs. We leave out the empty bucket otherwise it skews the plots too much and makes them difficult to examine. $ python reformat.py Paste this data into graph/graphs.js under the variable called 'datasets'