README
¶
Financial Analysis UDA: Candler - converts raw price data to Candles for technical analysis
This module aggregates time series data into candles using the marketstore UDA interface.
The interesting functions can be called from SQL
Example:
$ mkts -rootDir /data/market-data/mktsdb/
» select candlecandler('12Min',Open,High,Low,Close,Avg::Volume,Sum::Volume) from `TSLA/1Min/OHLCV` where Epoch > '2017-01-01' limit 10;
============================= ========== ========== ========== ========== ========== ==========
Epoch Open High Low Close Volume_SUM Volume_AVG
============================= ========== ========== ========== ========== ========== ==========
2017-01-03 14:24:00 +0000 UTC 214.86 215.3 210.96 212.5378 342337 57056.168
2017-01-03 14:36:00 +0000 UTC 212.555 216.143 211.4 215.82 501743 41811.918
2017-01-03 14:48:00 +0000 UTC 215.82 218.39 215.39 217.775 520423 43368.582
2017-01-03 15:00:00 +0000 UTC 217.82 220.33 217.56 220.255 667460 55621.668
2017-01-03 15:12:00 +0000 UTC 220.29 220.29 218.77 219.65 255877 21323.084
2017-01-03 15:24:00 +0000 UTC 219.63 220 218.9 219.59 210390 17532.5
2017-01-03 15:36:00 +0000 UTC 219.55 219.87 219.0444 219.1 140869 11739.083
2017-01-03 15:48:00 +0000 UTC 219.18 219.25 217.46 217.71 203272 16939.334
2017-01-03 16:00:00 +0000 UTC 217.72 218.25 216.59 217.87 122625 10218.75
2017-01-03 16:12:00 +0000 UTC 218.04 218.317 216.61 216.68 87799 7316.5835
============================= ========== ========== ========== ========== ========== ==========
Elapsed query time: 63.754 ms
Notice that the parameters of the candlecandler() function in some cases have a notation like "AVG:Volume" - those are dynamic tags used by the function to take a variable number of inputs which are used by the candlecandler().
/*
Accum() sends new data to the aggregate
*/
func (ca *CandleCandler) Accum(cols io.ColumnInterface) error {
if cols.Len() == 0 {
return fmt.Errorf("Empty input to Accum")
}
/*
Get the input column for "Price"
*/
openCols := ca.ArgMap.GetMappedColumns(requiredColumns[0].Name)
highCols := ca.ArgMap.GetMappedColumns(requiredColumns[1].Name)
lowCols := ca.ArgMap.GetMappedColumns(requiredColumns[2].Name)
closeCols := ca.ArgMap.GetMappedColumns(requiredColumns[3].Name)
open, err := candler.GetAverageColumnFloat32(cols, openCols)
if err != nil {
return err
}
high, err := candler.GetAverageColumnFloat32(cols, highCols)
if err != nil {
return err
}
Documentation
¶
Index ¶
- func GetAverageColumnFloat32(cols io.ColumnInterface, srcCols []io.DataShape) (avgCol []float32, err error)
- type Candle
- type CandleMap
- type Candler
- func (ca *Candler) Accum(cols io.ColumnInterface) error
- func (ca *Candler) GetCandle(t time.Time, cndl ...*Candle) *Candle
- func (ca *Candler) GetInitArgs() []io.DataShape
- func (ca *Candler) GetOptionalArgs() []io.DataShape
- func (ca *Candler) GetRequiredArgs() []io.DataShape
- func (ca *Candler) Init(args ...interface{}) error
- func (c Candler) New() (ca *Candler, am *functions.ArgumentMap)
- func (ca *Candler) Output() *io.ColumnSeries
- func (ca *Candler) Reset()
- type EOHLCStruct
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func GetAverageColumnFloat32 ¶
func GetAverageColumnFloat32(cols io.ColumnInterface, srcCols []io.DataShape) (avgCol []float32, err error)
Utility Functions
Types ¶
type Candle ¶
type Candle struct {
StartTime time.Time
Duration *utils.CandleDuration
/*
Every candle has OHLC
*/
EOHLC EOHLCStruct
OpenTime, CloseTime time.Time // The time at which the Open and Close prices happened
/*
Some candles optionally sum quantities like "Volume" from the
input columns
*/
SumMap map[string]float64 // One sum per mapped column
Count int64 // Counts the elements incorporated in the Sums
/*
Does this candle have complete data? Sometimes we can tell...
*/
Complete bool
}
func (*Candle) SerializeToRowData ¶
type Candler ¶
type Candler struct {
uda.AggInterface
// Input arguments mapping
ArgMap *functions.ArgumentMap
/*
Manages one timeframe, creates candles in that timeframe from
input and outputs them on demand.
*/
MyCD *utils.CandleDuration
CMap CandleMap
/*
We need to keep an ordered list of sum and avg names to ensure ordered output
*/
SumNames, AvgNames []string // A cache of the column names that are summed and averaged in the candles
AccumSumNames []string // Consolidated list of names either summed or averaged
}
func NewCandler ¶
CONCRETE - these may be suitable methods for general usage
func (*Candler) Accum ¶
func (ca *Candler) Accum(cols io.ColumnInterface) error
OVERRIDES - these methods should be overridden in a concrete implementation of this class
OVERRIDE THIS METHOD Accum() sends new data to the aggregate
func (*Candler) GetInitArgs ¶
func (*Candler) GetOptionalArgs ¶
func (*Candler) GetRequiredArgs ¶
func (Candler) New ¶
func (c Candler) New() (ca *Candler, am *functions.ArgumentMap)
OVERRIDE THIS METHOD Creates a new candler using the arguments of the specific implementation for inputColumns and optionalInputColumns
func (*Candler) Output ¶
func (ca *Candler) Output() *io.ColumnSeries
Output() returns the currently valid output of this aggregate
type EOHLCStruct ¶
*********************************** Candle ******************************************* - Represents quantities within an interval of time - Always has Open, High, Low, Close prices defined within - Optionally has averaged and summed quantities inside - Has a starting time representing the candle, it begins the interval *********************************** Candle *******************************************
Source Files
Directories