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One needs to implement a Statistic class/object for each quantity from kotlin-statisitcs. If the reduction could be done in parallel, one should use ComposableStatistic instead.
Use Mean and Median as a reference.
The text was updated successfully, but these errors were encountered:
I am very happy to hear that. Please do not hesitate to write if you think that there should be some changes in the statistic API. I made it this way so we could do non-blocking streaming processing of large data. But it is not much tested yet.
Port/re-implement methods from https://github.com/thomasnield/kotlin-statistics. Use stream-based reduction and
Buffer
.The API is here: https://github.com/mipt-npm/kmath/blob/dev/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt
Example usage is here: https://github.com/mipt-npm/kmath/blob/dev/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt
One needs to implement a
Statistic
class/object for each quantity from kotlin-statisitcs. If the reduction could be done in parallel, one should useComposableStatistic
instead.Use
Mean
andMedian
as a reference.The text was updated successfully, but these errors were encountered: