[Pandora] Error Function Treasure Trove - ERF/ERFI/Sigmoids+PRAISE:
At this time, I have to graciously thank the wonderful minds behind the new "Pine Profiler Mode" (PPM). Directly prior to this release, it allowed me to ascertain script performance even more. While I usually write mostly in highly optimized Pine code, PPM visually identified a few bottlenecks that would otherwise be hard to identify. Anyone who contributed to PPMs creation and testing before release... BRAVO!!! I commend all of those who assisted in it's state-of-the-art engineering and inception, well done!
BACKSTORY:
This script is specifically being released in defense of another member, an exceptionally unique PhD. It was brought to my attention that a script-mod-event occurred, regarding the publishing of a measly antiquated error function (ERF) calculation within his script. This sadly resulted in the now former member jumping ship after receiving unmannerly responses amidst his curious inquiries as to why his erf() was modded. To forbid rusty and rudimentary formulations because a mod-on-duty is temporally offended by a non-nefarious release of code, is in MY opinion an injustice to principles of perpetuating open-source code intended to benefit thousands to millions of community members. While Pine is the heart and soul of TV, the mathematical concepts contributed from the minds of members is the inspirational fuel of curiosity that powers it's pertinent reason to exist and evolve.
It is an indisputable fact that most members are not greatly skilled Pine Poets. Many members may be incapable of innovating robust function code in Pine, even if they have one or more PhDs. We ALL come from various disciplines of mathematical comprehension and education. Some mathematicians are not greatly skilled at coding, while some coders are not exceptional at math. So... what am I to do to attempt to resolve this circumstantial challenge??? Those who know me best are aware that I will always side with "the right side of history" in order to accomplish my primary self-defined missions I choose to accept. Serving as an algorithmic advocate, I felt compelled to intercede by compiling numerous error functions into elegant code of very high caliber that any and every TV member may choose to employ, so this ERROR never happens again.
After weeks of contemplation into algorithms I knew little about, I prioritized myself to resolve an unanticipated matter by creating advanced formulas of exquisitely crafted error functions refined to the best of my current abilities. My aversion for unresolved problems motivated me to eviscerate error function insufficiencies with many more rigid formulations beyond what is thought to exist. ERF needed a proper algorithmic exorcism anyways. In my furiosity, I contemplated an array of madMAXimum diplomatic demolition methods, choosing the chain saw massacre technique to slaughter dysfunctionalities I encountered on a battered ERF roadway. This resulted in prolific solutions that should assuredly endure the test of time. Poetically, as you will come to see, I am ripping the lid off of Pandora's box of error functions in this case to correct wrongs into a splendid bundle of rights for members.
INTENTION:
Error function (ERF) enthusiasts... PREPARE FOR GLORY!! The specific purpose of this script is to deprecate classic error functions with the creation of a fierce and formidable army of superior formulations, each having varying attributes of computational complexity with differing absolute error ranges in their results for multiple compute scenarios. This is NOT an indicator... It is intended to allow members to embark on endeavors to advance the profound knowledge base of this growing worldwide community of 60+ million inquisitive minds. For those of you who believe computational mathematics and statistics is near completion at its finest; I am here to inform you, this is ridiculous to ponder. We are no where near statistical excellence that can and will exist eventually. At this time, metaphorically speaking, we are merely scratching microns off of the surface of the skin of a statistical apple Isaac Newton once pondered.
THIS RELEASE:
Following weeks of pondering methodical experiments beyond the ordinary, I am liberating these wild notions of my error function explorations to the entire globe as copyleft code, not just Pine. This Pandora's basket of ERFs is being openly disclosed for the sake of the sanctity of mathematics, empirical science (not the garbage we are told by CONTROLocrats to blindly trust), revolutionary cutting edge engineering, cosmology, physics, information technology, artificial intelligence, and EVERY other mathematical branch of human knowledge being discovered over centuries. I do believe James Glaisher would favor my aims concerning ERF aspirations embracing the "Power of Pine".
The included functions are intended for TV members to use in any way they see fit. This is a gift to ALL members to foster future innovative excellence on this platform. Any attempt to moderate this code without notification of "self-evident clear and just cause" will be considered an irrevocable egregious action. The original foundational PURPOSE of establishing script moderation (I clearly remember) was primarily to maintain active vigilance over a growing community against intentional nefarious actions and/or behaviors in blatant disrespect to other author's works AND also thwart rampant copypasting bandit operations, all while accommodating balanced principles of fairness for an educational community cause via open source publishing that should support future algorithmic inventions well beyond my lifespan.
APPLICATIONS:
The related error functions are used in probability theory, statistics, and numerous and engineering scientific disciplines. Its key characteristics and applications are innumerable in computational realms. Its versatility and significance make it a fundamental tool in arenas of quantitative analysis and scientific research...
Probability Theory - Is widely used in probability theory to calculate probabilities and quantiles of the normal distribution.
Statistics - It's related to the Gaussian integral and plays a crucial role in statistics, especially in hypothesis testing and confidence interval calculations.
Physics - In physics, it arises in the study of diffusion equations, quantum mechanics, and heat conduction problems.
Engineering - Applications exist in engineering disciplines such as signal processing, control theory, and telecommunications.
Error Analysis - It's employed in error analysis and uncertainty quantification.
Numeric Approximations - Due to its lack of a closed-form expression, numerical methods are often employed to approximate erf/erfi().
AI, LLMs, & MACHINE LEARNING:
The error function (ERF) is indispensable to various AI applications, particularly due to its relation to Gaussian distributions and error analysis. It is used in Gaussian processes for regression and classification, probabilistic inference for Bayesian networks, soft margin computation in SVMs, neural networks involving Gaussian activation functions or noise, and clustering algorithms like Gaussian Mixture Models. Improved ERF approximations can enhance precision in these applications, reduce computational complexity, handle outliers and noise better, and improve optimization and convergence, possibly leading to more accurate, efficient, and robust AI systems.
BONUS ALGORITHMS:
While ERFs are versatile, its opposite also exists in the form of inverse error functions (ERFIs). I have also included a modified form of the inverse fisher transform along side MY sigmoid (sigmyod). I am uncertain what sigmyod() may be used for, but it's a culmination of my examinations deep into "sigmoid domains", something I am fascinated by. Whatever implications it may possess, I am unveiling it along with it's cousin functions. For curious minds, this quality of composition seen here is ideally what underlies what I would term "Pandora functionality" that empowers my Pandora indication. I go through hordes of formulations, testing, and inspection to find what appears to be the most beneficial logical/mathematical equation to apply...
SCRIPT OPERATION:
To showcase the characteristics and performance of my ERF/ERFI formulations, I devised a multi-modal script. By using bar_index , I generated a broad sequence of numeric values to input into the first ERF/ERFI parameter. These sequences allow you to inspect the contours of the error function's outputs for both ERF and ERFI. When combined with compute-intensive precision functions (CIPFs), the polynomial function output values can be subtracted from my CIPFs to obtain results of absolute error, displaying the accuracy of the many polynomial estimation functions I tuned in testing for Pine's float environment.
A host of numeric input settings are wildly adjustable to inspect values/curvatures across the range of numeric input sequences. Very large numbers, such as Divisor:100,000,100/Offset:200,000,000 for ERF modes or... Divisor:100,000,100/Offset:100,000,000 for ERFI modes, will display miniscule output values calculated from input values in close proximity to 0.0 for the various estimates, similar to a microscope. ERFI approximations very near in proximity to +/-1.0 will always yield large deviations of absolute error. Dragging/zooming your chart or using the Offset input will aid with visually clipping off those ERFI extremes where float precision functions cannot suffice.
NOTICE:
perf() and perfi() are intended for precision computation (as good as it basically gets) in a float environment. However, they are CPU intensive (especially perfi). I wouldn't recommend these being used in ANY Pine script unless it's an "absolute necessity" to do so to accomplish your goal. I only built them to obtain "absolute error curvatures" of the error functions for the polynomial approximations. These are visible in the accuracy modes in the indicator Settings.
Error
LogLibrary "Log"
- Log methods that return input value for code readbility and cleaness.
method str(input)
str
Namespace types: series float, simple float, input float, const float
Parameters:
input (float)
method str(input)
str
Namespace types: series int, simple int, input int, const int
Parameters:
input (int)
method str(input)
str
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
input (bool)
method str(input)
str
Namespace types: series string, simple string, input string, const string
Parameters:
input (string)
method str(input)
str
Namespace types: series linefill
Parameters:
input (linefill)
method str(input)
str
Namespace types: series line
Parameters:
input (line)
method str(input)
str
Namespace types: series box
Parameters:
input (box)
method str(input)
str
Namespace types: series label
Parameters:
input (label)
method str(input)
str
Namespace types: chart.point
Parameters:
input (chart.point)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: array
Parameters:
input (array)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
str
Namespace types: matrix
Parameters:
input (matrix)
method str(input)
Namespace types: matrix
Parameters:
input (matrix)
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: chart.point
Parameters:
input (chart.point) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series float, simple float, input float, const float
Parameters:
input (float) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series int, simple int, input int, const int
Parameters:
input (int) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
input (bool) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series string, simple string, input string, const string
Parameters:
input (string) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series linefill
Parameters:
input (linefill) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series line
Parameters:
input (line) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input value with the 'info' log level.
Namespace types: series box
Parameters:
input (box) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: series label
Parameters:
input (label) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input array with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: array
Parameters:
input (array) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Logs the input matrix with the 'info' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method info(input, msg)
Namespace types: matrix
Parameters:
input (matrix)
msg (string)
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: chart.point
Parameters:
input (chart.point) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series float, simple float, input float, const float
Parameters:
input (float) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series int, simple int, input int, const int
Parameters:
input (int) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
input (bool) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series string, simple string, input string, const string
Parameters:
input (string) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series linefill
Parameters:
input (linefill) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series line
Parameters:
input (line) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input value with the 'warning' log level.
Namespace types: series box
Parameters:
input (box) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: series label
Parameters:
input (label) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input array with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: array
Parameters:
input (array) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Logs the input matrix with the 'warning' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method warn(input, msg)
Namespace types: matrix
Parameters:
input (matrix)
msg (string)
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: chart.point
Parameters:
input (chart.point) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series float, simple float, input float, const float
Parameters:
input (float) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series int, simple int, input int, const int
Parameters:
input (int) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
input (bool) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series string, simple string, input string, const string
Parameters:
input (string) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series linefill
Parameters:
input (linefill) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series line
Parameters:
input (line) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input value with the 'error' log level.
Namespace types: series box
Parameters:
input (box) : The input value to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input value.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: series label
Parameters:
input (label) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input array with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input array.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: array
Parameters:
input (array) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Logs the input matrix with the 'error' log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
Returns: The input matrix.
method error(input, msg)
Namespace types: matrix
Parameters:
input (matrix)
msg (string)
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: chart.point
Parameters:
input (chart.point) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series float, simple float, input float, const float
Parameters:
input (float) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series int, simple int, input int, const int
Parameters:
input (int) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
input (bool) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series string, simple string, input string, const string
Parameters:
input (string) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series linefill
Parameters:
input (linefill) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series line
Parameters:
input (line) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input value with the specified log level.
Namespace types: series box
Parameters:
input (box) : The input value to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input value.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: series label
Parameters:
input (label) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input array with the specified log level.
Namespace types: array
Parameters:
input (array) : The input array to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input array.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: array
Parameters:
input (array) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Logs the input matrix with the specified log level.
Namespace types: matrix
Parameters:
input (matrix) : The input matrix to log.
msg (string) : The message to log. Default is an empty string.
level (int) : The log level (1 - info, 2 - warning, 3 - error). Default is 1.
Returns: The input matrix.
method log(input, msg, level)
Namespace types: matrix
Parameters:
input (matrix)
msg (string)
level (int)
Root mean squared error range (RMSER)Similarly to Bollinger bands, the RMSER gives a support and resistance areas for the trading price. Unlike bollinger bands, which use standard deviation, this support and resistance is calculated with 2 * the root mean squared error away from the moving average. This works very well with indices, like $SPX, and prices only fall outside the range during black swan events like the 2020 crash.
Ehlers Average Error Filter [CC]The Average Error Filter was created by John Ehlers and this is a variation of a Zero Lag Exponential Moving Average that uses a Super Smoother to filter out the noise and then uses a second Super Smoother of the difference between the current price and the filtered data. This works well as a trendline and does give out a few false signals like all indicators inevitably do but most signals do a good job of keeping up with the trend and providing clear entries and exits when the trend changes. I have included strong buy and sell signals in addition to normal ones so like always darker colors are strong signals and lighter colors are normal ones. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Ehlers Error Correcting Exponential Moving Average [CC]The Error Correcting Exponential Moving Average was created by John Ehlers and Ric Way (Stocks & Commodities V. 28:11 (30-35)) and this is an excellent moving average that accurately identifies the trend and sticks with the price during trends or choppy periods pretty well. It looks back to find the best gain setting for each day that returns the smallest difference between the current price and the ema based on the gain setting and uses that day's info in it's total calculations and if there is a zero gain for the day then it is just a classic ema. I have included strong buy and sell signals in addition to normal ones so lighter colors are normal and darker colors are strong. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
Barssince Context TestThis is just published for visibility as a public service until the Pine devs are able to fix or document this behavior. The barssince() function returns different values when inside a conditional context. As long as it can be documented (and relied upon), this could be a pretty cool feature, but right now this is now how I read the help documentation to describe the function's intended behavior.
Anyway, in the script you'll see that test and test2 agree on red bars, but on green bars test gets a much lower value, which was pretty shocking to me until I traced down this particular cause within my larger script.
Return Error With Reference & Constant Value Enforcer FunctionsI found MichelT 's work thanks to LucF . One of its cool concepts that touched me was his error's function. Whenever something unexpected takes place, it returns an error's message right on the chart, one nobody can't say they can't see lol. I told him it would be cool if we could get specific messages related to specific cases, he said "there is a task for such feature". On the meantime I wanted to enrich his feature by making the function printing any number the user wants.
Another really cool thing I have been in love with are "Pine Coding Conventions", I can't express enough how thankful I am to the amazing team behind it. Just recently they introduced me to a new rule, one seeming very popular across the board, using all capital letters to define a constant value.
On this script I combined both error's printing message with a constant check functions that enforce the value must remain unchanged ever. I hope you like this work, I really enjoy seeing brilliant people coming up with some awesome ideas. Let's together make "Pine" a more cooler language.
Dual Thrust Trading Algorithm (ps4)This is an PS4 update to the popular Dual Thrust trading algorithm posted by me some time ago (). It has been commonly used in futures, Forex and equity markets. The idea of Dual Thrust is similar to a typical breakout system, however dual thrust uses the historical price to construct update the look back period - theoretically making it more stable in any given period.
See: www.quantconnect.com
[RS]Function - Minkowski_distancecopy pasted description..
Minkowski distance is a metric in a normed vector space. Minkowski distance is used for distance similarity of vector. Given two or more vectors, find distance similarity of these vectors.
