create custom functions

(create-custom-fns [{:keys :bench.stats.lag :bench.stats.time :sample 10 :aggregate :max}] {:order :desc :key :start}) => (contains {:bench.stats.lag fn? :bench.stats.time fn?})

creates a merge function

(def merge-fn (create-merge-fn {:sample 9} {:key identity :order :asc}))

(long (merge-fn (range 90))) => 44

creates a map merge function

(map-merge-fn {:time {:aggregate :first} :default {:sample 4} :custom [{:keys :bench.stats.lag :sample 10 :aggregate :max} {:keys :bench.stats.time :sample 4 :aggregate :mean}]} {:order :desc :key :start}) => fn?

parses the transform expr

prepares the merge functions and options

(prep-merge {:sample [0 :1m :range]} {:unit :ms}) => (contains-in [fn? {:size {:type :to, :start :array 0, :end :time 60000}, :strategy :range}])

processes time series

processes the indicator stage

(->> (process-compute {:start 0 :bench.stats.lag 0.7 :bench.stats.time 0.3} {:start 2 :bench.stats.lag 0.3 :bench.stats.time 0.5} {:start 3 :bench.stats.lag 0.4 :bench.stats.time 0.3} {:start 4 :bench.stats.lag 0.5 :bench.stats.time 0.3} {:compute {:lag :s/norm :bench.stats.lag :time :s/norm :bench.stats.time}}) (map (juxt :lag :time))) => [1.0 0.6 0.4285714285714286 1.0 0.5714285714285715 0.6 0.7142857142857143 0.6]

processes the transform stage

creates a merge function for time

transform array based on resolution