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Features/54 distributed random numbers #362
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…reefry function (32bit)
…uted-random-numbers
…ub.com/helmholtz-analytics/heat into features/54-distributed-random-numbers
Codecov Report
@@ Coverage Diff @@
## master #362 +/- ##
==========================================
+ Coverage 97.14% 97.23% +0.09%
==========================================
Files 53 53
Lines 9659 10093 +434
==========================================
+ Hits 9383 9814 +431
- Misses 276 279 +3
Continue to review full report at Codecov.
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matplotlib just simply needs to go still |
What is the state regarding the 32-bit Threefry? Have you tried the upper bit removal? |
I tried to use the 64-Bit logic for the random numbers and cut off the upper 32-Bit but this resulted in a similar probability for equal values compared to the threefry-32 algorithm. (Around 10 per 10k values) |
Right, so let's do the following, lets use the regular threefry32 and just live with the fact that there is repetition. As for your unit tests, just set a slightly higher upper bound for the number of allowed repetitions than 1, e.g. 10? |
Description
Target issue #54.
This builds on @Markus-Goetz implementation of the
threefry64
algorithm. The__counter_sequenze
function was completed which returns initial values for the "random" number calculation. It is currently only tested fortorch.int64
because thethreefry32
is not implemented yet.