# PineJS Utility Functions Custom Study [Constructor](https://charting-library-docs.xstaging.tv/latest/custom_studies/custom-indicator-constructor.md) is able to use utility functions from PineJS object (an argument of [custom_indicators_getter](https://charting-library-docs.xstaging.tv/latest/api/interfaces/Charting_Library.ChartingLibraryWidgetOptions#custom_indicators_getter) function). ## Functions ported from Pine ### `na(x)` Test value if it's a NaN. **Returns** `true` if `x` is not a valid number (`x` is NaN), otherwise `false`. ### `nz(x, y)` Replaces NaN values with zeros (or given value) in a series. **Returns** `x` if it's a valid (not NaN) number, otherwise y ### `and(expr1, expr2)` Logical AND. Applicable to boolean expressions. **Returns** Boolean value, or series of boolean values. ### `or(expr1, expr2)` Logical OR. Applicable to boolean expressions. **Returns** Boolean value, or series of boolean values. ### `not(expr)` Logical negation (NOT). Applicable to boolean expressions. **Returns** Boolean value, or series of boolean values. ### `max(x1, x2, ..., x10)` **Returns** The greatest of multiple values ### `min(x1, x2, ..., x10)` **Returns** The smallest of multiple given values. ### `pow(base, exponent)` Mathematical power function. **Returns** `x` raised to the power of `y`. If `x` is a series, it is calculated elementwise. **Arguments** - **`base` (series[float])** Specify the base to use. - **`exponent` (float)** Specifies the exponent. ### `abs(x)` Absolute value of `x` is `x` if `x >= 0`, or `-x` otherwise. **Returns** The absolute value of x ### `log(x)` Natural logarithm of any `x > 0` is the unique `y` such that `e^y = x` **Returns** The natural logarithm of x. ### `log10(x)` Base 10 logarithm of any `x > 0` is the unique `y` such that `10^y = x` **Returns** The base 10 logarithm of x. ### `sqrt(x)` Square root of any `x >= 0` is the unique `y >= 0` such that `y^2 = x` **Returns** The square root of x. ### `sign(x)` Sign (signum) of `x` is zero if the `x` is zero, `1.0` if the `x` is greater than zero, `-1.0` if the `x` is less than zero. **Returns** The sign of the argument. ### `exp(x)` The exp function of `x` is `e^x`, where `x` is the argument and `e` is Euler's number. **Returns** A number representing e^x. ### `sin(x)` The `sin` function returns the trigonometric sine of an angle. **Returns** The trigonometric sine of an angle. **Arguments** - **`x` (series[float])** Angle, in radians. ### `cos(x)` The cos function returns the trigonometric cosine of an angle. **Returns** The trigonometric cosine of an angle. **Arguments** - **`x` (series[float])** Angle, in radians. ### `tan(x)` The tan function returns the trigonometric tangent of an angle. **Returns** The trigonometric tangent of an angle. **Arguments** - **`x` (series[float])** Angle, in radians. ### `asin(x)` The asin function returns the arcsine (in radians) of number such that `sin(asin(y)) = y` for `y` in range `[-1, 1]`. **Returns** The arcsine of a value; the returned angle is in the range `[-Pi/2, Pi/2]`, or na if y is outside of range `[-1, 1]`. ### `acos(x)` The acos function returns the arccosine (in radians) of number such that `cos(acos(y)) = y` for `y` in range `[-1, 1]`. **Returns** The arc cosine of a value; the returned angle is in the range `[0, Pi]`, or `na` if `y` is outside of range `[-1, 1]`. ### `atan(x)` The atan function returns the arctangent (in radians) of number such that `tan(atan(y)) = y` for any `y`. **Returns** The arc tangent of a value; the returned angle is in the range `[-Pi/2, Pi/2]`. ### `floor(x)` **Returns** The largest integer less than or equal to the given number. ### `ceil(x)` The ceil function returns the smallest (closest to negative infinity) integer that is greater than or equal to the argument. **Returns** The smallest integer greater than or equal to the given number. ### `round(x)` **Returns** The value of `x` rounded to the nearest integer, with ties rounding up. If the precision parameter is used, returns a float value rounded to that number of decimal places. ### `avg(x1, x2, ..., x10)` Calculates average of all given series (elementwise). **Returns** Average. ### `open(context)` Current open price. **Arguments** - **`context`** PineJS execution context. ### `high(context)` Current high price. **Arguments** - **`context`** PineJS execution context. ### `low(context)` Current low price. **Arguments** - **`context`** PineJS execution context. ### `close(context)` Close price of the current bar when it has closed, or last traded price of a yet incomplete, realtime bar. **Arguments** - **`context`** PineJS execution context. ### `hl2(context)` Is a shortcut for `(high + low)/2` **Arguments** - **`context`** PineJS execution context. ### `hlc3(context)` Is a shortcut for (high + low + close)/3 **Arguments** - **`context`** PineJS execution context. ### `ohlc4(context)` Is a shortcut for (open + high + low + close)/4 **Arguments** - **`context`** PineJS execution context. ### `volume(context)` Current bar volume. **Arguments** - **`context`** PineJS execution context. ### `period(context)` Resolution string, e.g. `60` - 60 minutes, `D` - daily, `W` - weekly, `M` - monthly, `5D` - 5 days, `12M` - one year, `3M` - one quarter **Arguments** - **`context`** PineJS execution context. ### `tickerid(context)` **Arguments** - **`context`** PineJS execution context. ### `year(context)` Current bar year in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `month(context)` Current bar month in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `weekofyear(context)` Week number of current bar time in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `dayofmonth(context)` Date of current bar time in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `dayofweek(context)` Day of week for current bar time in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `hour(context)` Current bar hour in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `minute(context)` Current bar minute in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `second(context)` Current bar second in exchange timezone. **Arguments** - **`context`** PineJS execution context. ### `iff(condition, then, _else)` If ... then ... else ... **Remarks** `iff` does exactly the same thing as ternary conditional operator `?:` but in a functional style. Also iff is slightly less efficient than operator `?:` ### `rising(series, length)` Test if the `series` is now rising for `length` bars long. **Returns** `true` if current `x` is greater than any previous `x` for `length` bars back, `false` otherwise. **Arguments** - **`series` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). ### `falling(series, length)` Test if the `series` is now falling for `length` bars long. **Returns** `true` if current `x` is less than any previous `x` for `length` bars back, `false` otherwise. **Arguments** - **`series` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). ### `rsi(upper, lower)` Relative strength index. It is calculated based on rma's of upward and downward change of x. **Returns** Relative strength index. **Arguments** - **`upper` (float)** Series of values to process. - **`lower` (float)** Number of bars (length). ### `sum(source, length, context)` The sum function returns the sliding sum of last y values of x. **Returns** Sum of x for y bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `sma(source, length, context)` The sma function returns the moving average, that is the sum of last `length` values of `source`, divided by `length`. **Returns** Simple moving average of x for y bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `rma(source, length, context)` Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length. **Returns** Exponential moving average of x with alpha = 1 / y. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `fixnan(current, context)` For a given series replaces NaN values with previous nearest non-NaN value. **Returns** Series without `na` gaps. **Arguments** - **`current` (series[float])** Series of values to process. - **`context`** PineJS execution context. ### `tr(handle_nan, context)` **Returns** True range. It is `max(high - low, abs(high - close[1]), abs(low - close[1]))` **Arguments** - **`handle_nan` (bool)** How NaN values are handled. if `true`, and previous day's close is NaN then `tr` would be calculated as current day high-low. Otherwise (if `false`) `tr` would return NaN in such cases. Also note, that atr uses `tr(true)`. - **`context`** PineJS execution context. ### `atr(length, context)` Function atr (average true range) returns the RMA of true range. True range is `max(high - low, abs(high - close[1]), abs(low - close[1]))` **Returns** Average true range. **Arguments** - **`length` (integer)** Length (number of bars back). - **`context`** PineJS execution context. ### `ema(series, length, context)` The ema function returns the exponentially weighted moving average. In ema weighting factors decrease exponentially. It calculates by using a formula: `EMA = alpha * x + (1 - alpha) * EMA[1]`, where `alpha = 2 / (y + 1)` **Returns** Exponential moving average of x with alpha = 2 / (y + 1) **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `wma(source, length, context)` The wma function returns weighted moving average of `source` for `length` bars back. In wma weighting factors decrease in arithmetical progression. **Returns** Weighted moving average of `series` for `length` bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `vwma(source, length, context)` The `vwma` function returns volume-weighted moving average of `source` for `length` bars back. It is the same as: `sma(x * volume, y) / sma(volume, y)` **Returns** Volume-weighted moving average of `source` for `length` bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `swma(source, context)` Symmetrically weighted moving average with fixed length: 4. Weights: `[1/6, 2/6, 2/6, 1/6]`. **Returns** Symmetrically weighted moving average **Arguments** - **`source` (series[float])** Source series. - **`context`** PineJS execution context. ### `lowestbars(source, length, context)` Lowest value offset for a given number of bars back. **Returns** Offset to the lowest bar. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `lowest(source, length, context)` Lowest value for a given number of bars back. **Returns** Lowest value. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `highestbars(source, length, context)` Highest value offset for a given number of bars back. **Returns** Offset to the highest bar. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `highest(source, length, context)` Highest value for a given number of bars back. **Returns** Highest value. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `cum(x, context)` Cumulative (total) sum of `x`. In other words it's a sum of all elements of `x`. **Returns** Total sum series. **Arguments** - **`x` (series[float])** Series of values to process. - **`context`** PineJS execution context. ### `accdist(context)` Accumulation/distribution index. **Arguments** - **`context`** PineJS execution context. ### `correlation(source_a, source_b, length, context)` Correlation coefficient. Describes the degree to which two series tend to deviate from their `sma` values. **Returns** Correlation coefficient. **Arguments** - **`source_a` (series[float])** Source series. - **`source_b` (series[float])** Target series. - **`length` (integer)** Length (number of bars back). - **`context`** PineJS execution context. ### `stoch(source, high, low, length, context)` Stochastic. It is calculated by a formula: `100 * (close - lowest(low, length)) / (highest(high, length) - lowest(low, length))` **Returns** Stochastic. **Arguments** - **`source` (series[float])** Source series. - **`high` (series[float])** Series of high. - **`low` (series[float])** Series of low. - **`length` (integer)** Length (number of bars back). - **`context`** PineJS execution context. ### `tsi(source, short_length, long_length, context)` True strength index. It uses moving averages of the underlying momentum of a financial instrument. **Returns** True strength index. A value in range [-1, 1] **Arguments** - **`source` (series[float])** Source series. - **`short_length` (integer)** Short length. - **`long_length` (integer)** Long length. - **`context`** PineJS execution context. ### `cross(x, y, context)` **Returns** `true` if two series have crossed each other, otherwise `false`. **Arguments** - **`x` (series[float])** First series. - **`y` (series[float])** Second series. - **`context`** PineJS execution context. ### `linreg(source, length, offset)` Linear regression curve. A line that best fits the prices specified over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: `linreg = intercept + slope * (length - 1 - offset)`, where intercept and slope are the values calculated with the least squares method on source series (x argument). **Returns** Linear regression curve. **Arguments** - **`source` (series[float])** Source series. - **`length` (integer)** - **`offset` (integer)** Offset. ### `sar(start, inc, max, context)` Parabolic SAR (parabolic stop and reverse) is a method devised by J. Welles Wilder, Jr., to find potential reversals in the market price direction of traded goods. **Returns** Parabolic SAR. **Arguments** - **`start` (series[float])** Start. - **`inc` (integer)** Increment. - **`max` (integer)** Maximum. - **`context`** PineJS execution context. ### `alma(series, length, offset, sigma)` Arnaud Legoux Moving Average. It uses Gaussian distribution as weights for moving average. **Returns** Arnaud Legoux Moving Average. **Arguments** - **`series` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`offset` (float)** Controls tradeoff between smoothness (closer to 1) and responsiveness (closer to 0). - **`sigma` (float)** Changes the smoothness of ALMA. The larger sigma the smoother ALMA. ### `change(source)` Difference between current value and previous, `x - x[1]`. **Returns** The result of subtraction. **Arguments** - **`source` (series[float])** ### `roc(source, length)` Function roc (rate of change) showing the difference between current value of `source` and the value of `source` that was `length` days ago. It is calculated by the formula: `100 * change(src, length) / src[length]`. **Returns** The rate of change of `source` for `length` bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). ### `dev(source, length, context)` Measure of difference between the series and it's `sma`. **Returns** Deviation of `source` for `length` bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. ### `stdev(source, length, context)` **Returns** Standard deviation. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. **Remarks** This is a biased estimation of standard deviation. ### `variance(source, length, context)` Variance is the expectation of the squared deviation of a series from its mean `sma`, and it informally measures how far a set of numbers are spread out from their mean. **Returns** Variance of `source` for `length` bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). - **`context`** PineJS execution context. **Remarks** This is a biased estimation of sample variance. ### `percentrank(source, length)` Percent rank is the percents of how many previous values was less than or equal to the current value of given series. **Returns** Percent rank of `source` for `length` bars back. **Arguments** - **`source` (series[float])** Series of values to process. - **`length` (integer)** Number of bars (length). ### `dmi(diLength, adxSmoothingLength, context)` Calculates the directional movement values +DI, -DI, DX, ADX, and ADXR. **Returns** An array of the +DI, -DI, DX, ADX, and ADXR values with `diLength` smoothing for the (+/-)DI values and `adxSmoothingLength` for the ADX value. **Arguments** - **`diLength` (integer)** Number of bars (length) used when calculating the +DI and -DI values. - **`adxSmoothingLength` (integer)** Number of bars (length) used when calculating the ADX value. - **`context`** PineJS execution context. ## Functions specific to the library - `isZero(number)` - boolean, shows whether the `number` equals zero or almost zero - `toBool(number)` - boolean, `true` if a number is finite and not equals zero - `eq(arg1, arg2)` - boolean, `true` if argument numbers are equal - `neq(arg1, arg2)` - boolean, `true` if argument numbers are not equal - `ge(arg1, arg2)` - boolean, `true` if first argument number is greater or equal to second - `gt(arg1, arg2)` - boolean, `true` if first argument number is greater than second - `le(arg1, arg2)` - boolean, `true` if first argument number is lesser or equal to second - `lt(arg1, arg2)` - boolean, `true` if first argument is lesser than second - `updatetime(context)` - string, symbol update time - `ticker(context)` - string, symbol name without exchange prefix, e.g. 'MSFT' - `interval(context)` - returns symbol interval string - `isdwm(context)` - boolean, returns `true` if current resolution is a daily or weekly or monthly resolution - `isintraday(context)` - boolean, returns true if current resolution is an intraday (minutes or seconds) resolution - `isdaily(context)` - boolean, returns `true` if current resolution is a daily resolution - `isweekly(context)` - boolean, returns `true` if current resolution is a weekly resolution - `ismonthly(context)` - boolean, returns `true` if current resolution is a monthly resolution - `add_days_considering_dst(timezone, utcTime, daysCount)` - `selectSessionBreaks(context, times)` - select session breaks for intraday resolutions only - `timepart(symbol, field, time)` - `wvap(source, context)` - `createNewSessionCheck(context)` - `error(message)` - returns study error with `message` specified - `time(context, period)` - returns UNIX time of current bar --- ## Sitemap - [All documentation pages](https://charting-library-docs.xstaging.tv/llms.txt) - [Full page map with headings](https://charting-library-docs.xstaging.tv/docs_map.md)