PINE LIBRARY

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AGbayLIB

Library "AGbayLIB"
Changes the timeframe period to the given period and returns the data matrix[cyear, cmonth, cday, chour, cminute_, csecond, cfulltime, copen, cclose, chigh, clow, cvolume] and sets the timeframe to the active time period

getTimeFrameValues(active_period_, period_, max_bars_)
: add function description here
Parameters:
active_period_ (string): Current time frame period to be set after getting period_ data
period_ (string): Target time period for returning data
max_bars_ (int): The historical bar count to be get
Returns: An array of data_row type with size of max_bars_ which includes rows of data: [year, month, day, hour, minute_, second, fulltime, open, close, high, clow, volume]

data_row
Fields:
year (series__integer)
month (series__integer)
day (series__integer)
hour (series__integer)
minute (series__integer)
second (series__integer)
fulltime (series__string)
open (series__float)
close (series__float)
high (series__float)
low (series__float)
volume (series__float)

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Unused import removed

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v3

Added:
data_set
Fields:
symbol (series__string)
time_period (series__string)
count (series__integer)
records (array__|data_row|#OBJ)

Updated:
getTimeFrameValues(symbol, period, max_bars, opens, closes, highs, lows, volumes, times)
: Creates an data_set typed object, copies open,close,high,low,volume,time data into records and also calculates trends of records
Parameters:
symbol (string): Symbol
period (string): Target time period for returning data
max_bars (int): The historical bar count to be get
opens (float): The historical bars of open data
closes (float): The historical bars of open data
highs (float): The historical bars of open data
lows (float): The historical bars of open data
volumes (float): The historical bars of open data
times (int): The historical bars of open data
Returns: An data_set object which contains array of data_row type which includes [timestamp, year, month, day, hour, minute, second, fulltime, open, close, high, clow, volume, trend]

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v11

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v12

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v13

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v14

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v15

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v16

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v17

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v18

Updated:
data_row
Contains candle values
Fields:
timestamp (series int): Time value of the candle
year (series int): Extracted year value from time
month (series int): Extracted month value from time
day (series int): Extracted day value from time
hour (series int): Extracted hour value from time
minute (series int): Extracted minute value from time
second (series int): Extracted second value from time
fulltime (series string)
open (series float): Open value of candle
close (series float): Close value of candle
high (series float): High value of candle
low (series float): Low value of candle
volume (series float): Volume value of candle
trend (series int): Calculated trend value of candle
trend_count (series int): Calculated trending candle count of active candle

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v19

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v20

Added:
agSetting
Fields:
symbol (series__string)
period (series__string)
iperiod (series__integer)
max_bar_count (series__integer)
min_trend_count (series__integer)
tenkansen_count (series__integer)
kijunsen_count (series__integer)

agCandle
Contains candle values
Fields:
timestamp (series int): Time value of the candle
year (series int): Extracted year value from time
month (series int): Extracted month value from time
day (series int): Extracted day value from time
dayofweek (series int)
hour (series int): Extracted hour value from time
minute (series int): Extracted minute value from time
second (series int): Extracted second value from time
fulltime (series string)
barindex (series int)
open (series float): Open value of candle
close (series float): Close value of candle
high (series float): High value of candle
low (series float): Low value of candle
volume (series float): Volume value of candle
resistantance (series bool)
supply (series bool)
trend (series int): Calculated trend value of candle
trend_count (series int): Calculated trending candle count of active candle

agZigZagNode
Fields:
candle (|agCandle|#OBJ)
candle_index (series__integer)
trend (series__integer)
pinnedCandle (|agCandle|#OBJ)
pinned_candle_index (series__integer)

agSymbolCandles
Fields:
setting (|agSetting|#OBJ)
count (series__integer)
candles (array__|agCandle|#OBJ)
zigzag_nodes (array__|agZigZagNode|#OBJ)

Updated:
getTimeFrameValues(setting, opens, closes, highs, lows, volumes, times, bar_indexes)
: Creates an data_set typed object, copies open,close,high,low,volume,time data into records and also calculates trends of records
Parameters:
setting (agSetting)
opens (float): The historical bars of open data
closes (float): The historical bars of open data
highs (float): The historical bars of open data
lows (float): The historical bars of open data
volumes (float): The historical bars of open data
times (int): The historical bars of open data
bar_indexes (int)
Returns: An agSymbolCandles object which contains array of agCandles type which includes [timestamp, year, month, day, hour, minute, second, fulltime, open, close, high, clow, volume, trend]

Removed:
data_row
Contains candle values

data_set

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v22

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v24

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v38

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v39

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v40

Added:
isBearishBullish(setting, copen, cclose, clow, chigh)
: Searches bearish and bullish order blocks
Parameters:
setting (agSetting): setting parameters for calculation
copen (float)
cclose (float)
clow (float)
chigh (float)
Returns: [bullishOB, bearishOB, OB_bull, OB_bull_chigh, OB_bull_clow, OB_bull_avg, OB_bear, OB_bear_chigh, OB_bear_clow,OB_bear_avg] Tuple

Updated:
agCandle
Contains candle values
Fields:
timestamp (series int): Time value of the candle
year (series int): Extracted year value from time
month (series int): Extracted month value from time
day (series int): Extracted day value from time
dayofweek (series int)
hour (series int): Extracted hour value from time
minute (series int): Extracted minute value from time
second (series int): Extracted second value from time
fulltime (series string)
barindex (series int)
open (series float): Open value of candle
close (series float): Close value of candle
high (series float): High value of candle
low (series float): Low value of candle
volume (series float): Volume value of candle
resistantance (series bool)
supply (series bool)
trend (series int): Calculated trend value of candle
trend_count (series int): Calculated trending candle count of active candle
is_order (series bool)
is_white (series bool)
is_bullish (series bool)

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agbay

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