170 lines
5.0 KiB
Lua
170 lines
5.0 KiB
Lua
local private, public = {}, {}
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Aux.stat_average = public
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private.PUSH_INTERVAL = 3
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private.NEW_RECORD = '0:0:0:0:0:0:0:0'
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function private.load_data()
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local dataset = Aux.persistence.load_dataset()
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dataset.stat_average_data = dataset.stat_average_data or { next_push = time() + private.PUSH_INTERVAL, item_data = {} }
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return dataset.stat_average_data
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end
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function public.read_record(item_key)
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local data = private.load_data()
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return Aux.util.map(Aux.persistence.deserialize(data.item_data[item_key] or private.NEW_RECORD, ':'), function(value)
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return tonumber(value)
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end)
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end
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function private.write_record(item_key, record)
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local data = private.load_data()
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data.item_data[item_key] = Aux.persistence.serialize(record, ':')
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end
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function public.process_auction(auction_info)
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if auction_info.buyout_price == 0 then
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return
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end
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local data = private.load_data()
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if data.next_push < time() then
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private.push_data()
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end
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local buyout = auction_info.buyout_price / auction_info.aux_quantity
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local item_record = public.read_record(auction_info.item_key)
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item_record[1] = item_record[1] + 1 -- auction count
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item_record[2] = item_record[2] + 1 -- daily auction count
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item_record[3] = item_record[3] + buyout -- daily accumulated buyout
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private.write_record(auction_info.item_key, item_record)
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end
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function public.get_price_data(item_key)
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local auction_count, daily_auction_count, daily_accumulated_buyout, seen_days, EMA3, EMA7, EMA14 = unpack(public.read_record(item_key))
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local daily_average = daily_accumulated_buyout / daily_auction_count
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return auction_count, seen_days, daily_average, EMA3, EMA7, EMA14
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end
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function public.get_mean(item_key)
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local _, daily_auction_count, daily_accumulated_buyout, seen_days, EMA3, EMA7, EMA14 = unpack(public.read_record(item_key))
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local mean = 0
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local daily_average = daily_accumulated_buyout / daily_auction_count
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if seen_days == 0 then
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if daily_auction_count > 0 then
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mean = daily_average
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end
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elseif seen_days <= 3 then -- No EMAs before day 4
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mean = EMA3
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if daily_auction_count > 0 then
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mean = (mean * seen_days + daily_average) / (seen_days + 1)
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end
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else
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-- we have 4 or more days of data, potentially enough to perform mean and stddev calculations
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local count = 0
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local valueset, weightset = {}, {}
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-- include daily data if available
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if daily_auction_count > 0 then
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count = 1
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valueset[count] = daily_average
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weightset[count] = 1
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end
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-- EMA3: standard weight 3, reduced if seenDays < 6, reduced if there was daily data, but never less than 1
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local weight = 3 - count
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if seen_days < 6 then
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weight = seen_days - 3
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if weight > 1 then
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weight = weight - count
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end
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end
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count = count + 1
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valueset[count] = EMA3
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weightset[count] = weight
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-- EMA7: standard weight 4, reduced if seenDays < 10
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if seen_days > 6 then
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count = count + 1
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valueset[count] = EMA7
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if seen_days < 10 then
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weightset[count] = seen_days - 6
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else
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weightset[count] = 4
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end
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end
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-- EMA14: standard weight 7, reduced if seenDays < 17
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if seen_days > 10 then
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count = count + 1
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valueset[count] = EMA14
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if seen_days < 17 then
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weightset[count] = seen_days - 10
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else
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weightset[count] = 7
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end
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end
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-- we will use a weighted incremental algorithm, based on sample code by West and Knuth http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
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local sumWeight, sumSquares = 0, 0 -- actually "sum of squares of differences from the (current) mean", but that's rather long for a variable name.
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for i=1,count do
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local value, weight = valueset[i], weightset[i]
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local nextweight = weight + sumWeight
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local valuediff = value - mean
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local meanadjust = valuediff * weight / nextweight
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mean = mean + meanadjust
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sumSquares = sumSquares + sumWeight * valuediff * meanadjust
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sumWeight = nextweight
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end
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-- stddev = sqrt(sumSquares / sumWeight * count / (count - 1))
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end
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return mean
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end
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function private.push_data()
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local data = private.load_data()
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local item_data = data.item_data
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for item_key, _ in pairs(item_data) do
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local item_record = public.read_record(item_key)
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local _, daily_auction_count, daily_accumulated_buyout, seen_days, EMA3, EMA7, EMA14 = unpack(item_record)
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if daily_auction_count > 0 then
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local daily_average = daily_accumulated_buyout / daily_auction_count
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if seen_days < 3 then
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-- for first 3 days perform plain average instead of EMAs
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EMA3 = (EMA3 * seen_days + daily_average) / (seen_days + 1)
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EMA7 = EMA3
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EMA14 = EMA3
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else
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-- do normal EMA calculations
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EMA3 = (EMA3 * 2 + daily_average) / 3
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EMA7 = (EMA7 * 6 + daily_average) / 7
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EMA14 = (EMA14 * 13 + daily_average) / 14
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end
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item_record[2] = 0 -- daily auction count
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item_record[3] = 0 -- daily accumulated buyout
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item_record[4] = seen_days + 1 -- seen days
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item_record[5] = EMA3 -- EMA3
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item_record[6] = EMA7 -- EMA7
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item_record[7] = EMA14 -- EMA14
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private.write_record(item_key, item_record)
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end
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end
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data.next_push = time() + private.PUSH_INTERVAL
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end |