tvunitLibrary "tvunit"
method assert(this, description, passed, bar)
Adds a test result to the test suite.
Namespace types: TestSuite
Parameters:
this (TestSuite) : The (TestSuite) instance.
description (string) : A description of the test.
passed (bool) : Whether the test passed or result.
bar (int) : The bar index at which the test was run.
Returns: Whether the assertion passed or result.
method assertWindow(this, runTests, description, bars, passed, stopOnFirstFailure)
Adds a test result to the test suite.
Namespace types: TestSuite
Parameters:
this (TestSuite) : The (TestSuite) instance.
runTests (bool) : Whether to run the tests.
description (string) : A description of the test.
bars (int) : The number of bars to test.
passed (bool) : A series of boolean values indicating whether each bar passed.
stopOnFirstFailure (bool) : Whether to stop on the first test failure.
Returns: Whether the assertion ran or not
method totalTests(this)
Returns the total number of tests in the test suite.
Namespace types: TestSuite
Parameters:
this (TestSuite) : The (TestSuite) instance.
Returns: The total number of tests.
method totalTests(this)
Returns the total number of tests in the test suite.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSuite) instance.
Returns: The total number of tests.
method passedTests(this)
Returns the total number of passed tests in the test suite.
Namespace types: TestSuite
Parameters:
this (TestSuite) : The (TestSuite) instance.
Returns: The total number of passed tests.
method passedTests(this)
Returns the total number of passed tests in the test suite.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSuite) instance.
Returns: The total number of passed tests.
method failedTests(this)
Returns the total number of result tests in the test suite.
Namespace types: TestSuite
Parameters:
this (TestSuite) : The (TestSuite) instance.
Returns: The total number of result tests.
method failedTests(this)
Returns the total number of result tests in the test suite.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSuite) instance.
Returns: The total number of result tests.
newTestSession()
Creates a new test session instance.
Returns: A new (TestSession) instance.
method addNewTestSuite(this, name, description)
Creates a new test suite instance.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSession) instance.
name (string) : The name of the test suite.
description (string) : (optional) A description of the test suite.
Returns: A new (TestSuite) instance.
method add(this, suite)
Creates a new test suite instance.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSession) instance.
suite (TestSuite) : The (TestSuite) instance to add.
Returns: The (TestSession) instance.
method totalSuites(this)
Returns the total number of sessions in the test session.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSession) instance.
Returns: The total number of sessions.
method report(this, show, showOnlyFailedTest)
Generates a report of the test session summary that is suitable for logging.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSession) instance.
show (bool) : Optional: Whether to show the report or not. default: true
showOnlyFailedTest (bool) : Optional: Whether to show only result tests or not. default: false
Returns: A formatted string report of the test suite summary.
method reportGui(this, show, pages, pageSize)
Generates a report of the test suite summary for the GUI.
Namespace types: TestSession
Parameters:
this (TestSession) : The (TestSession) instance.
show (bool) : Optional: Whether to show the report or not. default: true
pages (int) : Optional: The number of pages to show (columns). default: 4
pageSize (int) : Optional: The number of results to show per page (rows), excluding the header. default: 5
approxEqual(a, b, tolerance)
Checks if two floating-point numbers are approximately equal within a specified tolerance.
Parameters:
a (float) : The first floating-point number.
b (float) : The second floating-point number.
tolerance (float) : The tolerance within which the two numbers are considered equal. Default is 1e-6.
Returns: True if the numbers are approximately equal, false otherwise. If both are na, returns true.
TestResult
Fields:
description (series string)
passed (series bool)
bar (series int)
TestSuite
Fields:
isEnabled (series bool)
name (series string)
description (series string)
tests (array)
TestSession
Fields:
suites (array)
Test
FunctionADFLibrary "FunctionADF"
Augmented Dickey-Fuller test (ADF), The ADF test is a statistical method used to assess whether a time series is stationary – meaning its statistical properties (like mean and variance) do not change over time. A time series with a unit root is considered non-stationary and often exhibits non-mean-reverting behavior, which is a key concept in technical analysis.
Reference:
-
- rtmath.net
- en.wikipedia.org
adftest(data, n_lag, conf)
: Augmented Dickey-Fuller test for stationarity.
Parameters:
data (array) : Data series.
n_lag (int) : Maximum lag.
conf (string) : Confidence Probability level used to test for critical value, (`90%`, `95%`, `99%`).
Returns: `adf` The test statistic. \
`crit` Critical value for the test statistic at the 10 % levels. \
`nobs` Number of observations used for the ADF regression and calculation of the critical values.
PineUnitPineUnit by Guardian667
A comprehensive testing framework for Pine Script on TradingView. Built with well-known testing paradigms like Assertions, Units and Suites. It offers the ability to log test results in TradingView's built-in Pine Protocol view, as well as displaying them in a compact table directly on your chart, ensuring your scripts are both robust and reliable.
Unit testing Pine Script indicators, libraries, and strategies becomes seamless, ensuring the precision and dependability of your TradingView scripts. Beyond standard function testing based on predefined input values, PineUnit supports series value testing. This means a test can run on every bar, taking into account its specific values. Moreover, you can specify the exact conditions under which a test should execute, allowing for series-based testing only on bars fitting a designated scenario.
Detailed Guide & Source Code
Quick Start
To get started swiftly with PineUnit, follow this minimalistic example.
import Guardian667/PineUnit/1 as PineUnit
var testSession = PineUnit.createTestSession()
var trueTest = testSession.createSimpleTest("True is always True")
trueTest.assertTrue(true)
testSession.report()
After running your script, you'll notice a table on your chart displaying the test results. For a detailed log output, you can also utilize the Pine Protocol view in TradingView.
--------------------------------------------------------------
T E S T S
--------------------------------------------------------------
Running Default Unit
Tests run: 1, Failures: 0, Not executed: 0, Skipped: 0
To further illustrate, let's introduce a test that's destined to fail:
var bullTest = testSession.createSeriesTest("It's allways Bull Market")
bullTest.assertTrue(close > open, "Uhoh... it's not always bullish")
After executing, the test results will reflect this intentional discrepancy:
--------------------------------------------------------------
T E S T S
--------------------------------------------------------------
Running Default Unit
Tests run: 2, Failures: 1, Not executed: 0, Skipped: 0 <<< FAILURE! - in
It's allways Bull Market
Uhoh... it's not always bullish ==> expected: , but was
This shows how PineUnit efficiently captures and reports discrepancies in test expectations.
It's important to recognise the difference between `createSimpleTest()` and `createSeriesTest()`. In contrast to a simple test, a series-based test is executed on each bar, making assertions on series values.
License
This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
@ Guardian667
A Personal Note
As a software developer experienced in OO-based languages, diving into Pine Script is a unique journey. While many aspects of it are smooth and efficient, there are also notable gaps, particularly in the realm of testing. We've all been there: using `plotchar()` for debugging, trying to pinpoint those elusive issues in our scripts. I've come to appreciate the value of writing tests, which often obviates the need for such debugging. My hope is that this Testing Framework serves you well and saves you a significant amount of time, more that I invested into developing this "baby."
MathSpecialFunctionsTestFunctionsLibrary "MathSpecialFunctionsTestFunctions"
Methods for test functions.
rosenbrock(input_x, input_y) Valley-shaped Rosenbrock function for 2 dimensions: (x,y) -> (1-x)^2 + 100*(y-x^2)^2.
Parameters:
input_x : float, common range within (-5.0, 10.0) or (-2.048, 2.048).
input_y : float, common range within (-5.0, 10.0) or (-2.048, 2.048).
Returns: float
rosenbrock_mdim(samples) Valley-shaped Rosenbrock function for 2 or more dimensions.
Parameters:
samples : float array, common range within (-5.0, 10.0) or (-2.048, 2.048).
Returns: float
himmelblau(input_x, input_y) Himmelblau, a multi-modal function: (x,y) -> (x^2+y-11)^2 + (x+y^2-7)^2
Parameters:
input_x : float, common range within (-6.0, 6.0 ).
input_y : float, common range within (-6.0, 6.0 ).
Returns: float
rastrigin(samples) Rastrigin, a highly multi-modal function with many local minima.
Parameters:
samples : float array, common range within (-5.12, 5.12 ).
Returns: float
drop_wave(input_x, input_y) Drop-Wave, a multi-modal and highly complex function with many local minima.
Parameters:
input_x : float, common range within (-5.12, 5.12 ).
input_y : float, common range within (-5.12, 5.12 ).
Returns: float
ackley(input_x) Ackley, a function with many local minima. It is nearly flat in outer regions but has a large hole at the center.
Parameters:
input_x : float array, common range within (-32.768, 32.768 ).
Returns: float
bohachevsky1(input_x, input_y) Bowl-shaped first Bohachevsky function.
Parameters:
input_x : float, common range within (-100.0, 100.0 ).
input_y : float, common range within (-100.0, 100.0 ).
Returns: float
matyas(input_x, input_y) Plate-shaped Matyas function.
Parameters:
input_x : float, common range within (-10.0, 10.0 ).
input_y : float, common range within (-10.0, 10.0 ).
Returns: float
six_hump_camel(input_x, input_y) Valley-shaped six-hump camel back function.
Parameters:
input_x : float, common range within (-3.0, 3.0 ).
input_y : float, common range within (-2.0, 2.0 ).
Returns: float
