FunctionSMCMCLibrary "FunctionSMCMC"
Methods to implement Markov Chain Monte Carlo Simulation (MCMC)
markov_chain(weights, actions, target_path, position, last_value) a basic implementation of the markov chain algorithm
Parameters:
weights : float array, weights of the Markov Chain.
actions : float array, actions of the Markov Chain.
target_path : float array, target path array.
position : int, index of the path.
last_value : float, base value to increment.
Returns: void, updates target array
mcmc(weights, actions, start_value, n_iterations) uses a monte carlo algorithm to simulate a markov chain at each step.
Parameters:
weights : float array, weights of the Markov Chain.
actions : float array, actions of the Markov Chain.
start_value : float, base value to start simulation.
n_iterations : integer, number of iterations to run.
Returns: float array with path.
MATH
LibraryPrivateUsage001This is a public library that include the functions explained below. The libraries are considered public domain code and permission is not required from the author if you reuse these functions in your open-source scripts
LibraryCheckNthBarLibrary "LibraryCheckNthBar"
TODO: add library description here
canwestart(UTC, prd) this function can be used if current bar is in last Nth bar
Parameters:
UTC : is UTC of the chart
prd : is the length of last Nth bar
Returns: true if the current bar is in N bar
FunctionDecisionTreeLibrary "FunctionDecisionTree"
Method to generate decision tree based on weights.
decision_tree(weights, depth) Method to generate decision tree based on weights.
Parameters:
weights : float array, weights for decision consideration.
depth : int, depth of the tree.
Returns: int array
FunctionDaysInMonthLibrary "FunctionDaysInMonth"
Method to find the number of days in a given month of year.
days_in_month(year, month) Method to find the number of days in a given month of year.
Parameters:
year : int, year of month, so we know if year is a leap year or not.
month : int, month number.
Returns: int
FunctionForecastLinearLibrary "FunctionForecastLinear"
Method for linear Forecast, same as found in excel and other sheet packages.
forecast(sample_x, sample_y, target_x) linear forecast method.
Parameters:
sample_x : float array, sample data X value.
sample_y : float array, sample data Y value.
target_x : float, target X to get Y forecast value.
Returns: float
FunctionBoxCoxTransformLibrary "FunctionBoxCoxTransform"
Methods to compute the Box-Cox Transformer.
regular(sample, lambda) Regular transform.
Parameters:
sample : float array, sample data values.
lambda : float, scaling factor.
Returns: float array.
inverse(sample, lambda) Regular transform.
Parameters:
sample : float array, sample data values.
lambda : float, scaling factor.
Returns: float array.
FunctionPolynomialRegressionLibrary "FunctionPolynomialRegression"
TODO:
polyreg(sample_x, sample_y) Method to return a polynomial regression channel using (X,Y) sample points.
Parameters:
sample_x : float array, sample data X points.
sample_y : float array, sample data Y points.
Returns: tuple with:
_predictions: Array with adjusted Y values.
_max_dev: Max deviation from the mean.
_min_dev: Min deviation from the mean.
_stdev/_sizeX: Average deviation from the mean.
draw(sample_x, sample_y, extend, mid_color, mid_style, mid_width, std_color, std_style, std_width, max_color, max_style, max_width) Method for drawing the Polynomial Regression into chart.
Parameters:
sample_x : float array, sample point X value.
sample_y : float array, sample point Y value.
extend : string, default=extend.none, extend lines.
mid_color : color, default=color.blue, middle line color.
mid_style : string, default=line.style_solid, middle line style.
mid_width : int, default=2, middle line width.
std_color : color, default=color.aqua, standard deviation line color.
std_style : string, default=line.style_dashed, standard deviation line style.
std_width : int, default=1, standard deviation line width.
max_color : color, default=color.purple, max range line color.
max_style : string, default=line.style_dotted, max line style.
max_width : int, default=1, max line width.
Returns: line array.
FunctionLinearRegressionLibrary "FunctionLinearRegression"
Method for Linear Regression using array sample points.
linreg(sample_x, sample_y) Performs Linear Regression over the provided sample points.
Parameters:
sample_x : float array, sample points X value.
sample_y : float array, sample points Y value.
Returns: tuple with:
_predictions: Array with adjusted Y values.
_max_dev: Max deviation from the mean.
_min_dev: Min deviation from the mean.
_stdev/_sizeX: Average deviation from the mean.
draw(sample_x, sample_y, extend, mid_color, mid_style, mid_width, std_color, std_style, std_width, max_color, max_style, max_width) Method for drawing the Linear Regression into chart.
Parameters:
sample_x : float array, sample point X value.
sample_y : float array, sample point Y value.
extend : string, default=extend.none, extend lines.
mid_color : color, default=color.blue, middle line color.
mid_style : string, default=line.style_solid, middle line style.
mid_width : int, default=2, middle line width.
std_color : color, default=color.aqua, standard deviation line color.
std_style : string, default=line.style_dashed, standard deviation line style.
std_width : int, default=1, standard deviation line width.
max_color : color, default=color.purple, max range line color.
max_style : string, default=line.style_dotted, max line style.
max_width : int, default=1, max line width.
Returns: line array.
MathSpecialFunctionsDiscreteFourierTransformLibrary "MathSpecialFunctionsDiscreteFourierTransform"
Method for Complex Discrete Fourier Transform (DFT).
dft(inputs, inverse) Complex Discrete Fourier Transform (DFT).
Parameters:
inputs : float array, pseudo complex array of paired values .
inverse : bool, invert the transformation.
Returns: float array, pseudo complex array of paired values .
MathComplexEvaluateLibrary "MathComplexEvaluate"
TODO: add library description here
is_op(char) Check if char is a operator.
Parameters:
char : string, 1 character string.
Returns: bool.
operator(op, left, right) operation between left and right values.
Parameters:
op : string, operator string character.
left : float, left value of operation.
right : float, right value of operation.
operator_precedence(op) level of precedence of operator.
Parameters:
op : string, operator 1 char string.
Returns: int.
eval() evaluate a string with references to a array of arguments.
| @param tokens string, arithmetic operations with references to indices in arguments, ex:"0+1*0+2*2+3" arguments
| @param arguments float array, arguments.
| @returns float, solution.
MathComplexTrignometryLibrary "MathComplexTrignometry"
Methods for complex number trignometry operations.
sinh(complex) Hyperbolic Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
cosh(complex) Hyperbolic cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
tanh(complex) Hyperbolic tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
coth(complex) Hyperbolic cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
sech(complex) Hyperbolic Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
csch(complex) Hyperbolic Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
sin(complex) Trigonometric Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
cos(complex) Trigonometric cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
tan(complex) Trigonometric tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
cot(complex) Trigonometric cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
sec(complex) Trigonometric Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
csc(complex) Trigonometric Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asin(complex) Trigonometric Arc Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acos(complex) Trigonometric Arc Cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
atan(complex) Trigonometric Arc Tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acot(complex) Trigonometric Arc Cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asec(complex) Trigonometric Arc Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acsc(complex) Trigonometric Arc Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asinh(complex) Hyperbolic Arc Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acosh(complex) Hyperbolic Arc Cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
atanh(complex) Hyperbolic Arc Tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acoth(complex) Hyperbolic Arc Cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asech(complex) Hyperbolic Arc Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acsch(complex) Hyperbolic Arc Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
MathComplexExtensionLibrary "MathComplexExtension"
A set of utility functions to handle complex numbers.
get_phase(complex_number, in_radians) The phase value of complex number complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
in_radians : boolean, value for the type of angle value, default=true, options=(true: radians, false: degrees)
Returns: float value with phase.
natural_logarithm(complex_number) Natural logarithm of complex number (base E).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, complex number.
common_logarithm(complex_number) Common logarithm of complex number (base 10).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, complex number.
logarithm(complex_number, base) Common logarithm of complex number (custom base).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
base : float, base value.
Returns: float array, complex number.
power(complex_number, complex_exponent) Raise complex_number with complex_exponent.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
complex_exponent : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
root(complex_number, complex_exponent) Raise complex_number with inverse of complex_exponent.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
complex_exponent : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
square(complex_number) Square of complex_number (power 2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
square_root(complex_number) Square root of complex_number (power 1/2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
square_roots(complex_number) Square root of complex_number (power 1/2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: tuple with 2 complex numbers.
cubic_roots(complex_number) Square root of complex_number (power 1/2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: tuple with 2 complex numbers.
to_polar_form(complex_number, in_radians) The polar form value of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
in_radians : boolean, value for the type of angle value, default=true, options=(true: radians, false: degrees)
Returns: float array, pseudo complex number in the form of a array
** returns a array
MathComplexOperatorLibrary "MathComplexOperator"
A set of utility functions to handle complex numbers.
conjugate(complex_number) Computes the conjugate of complex_number by reversing the sign of the imaginary part.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
add(complex_number_a, complex_number_b) Adds complex number complex_number_b to complex_number_a, in the form:
.
Parameters:
complex_number_a : pseudo complex number in the form of a array .
complex_number_b : pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
subtract(complex_number_a, complex_number_b) Subtract complex_number_b from complex_number_a, in the form:
.
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
multiply(complex_number_a, complex_number_b) Multiply complex_number_a with complex_number_b, in the form:
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
divide(complex_number_a, complex_number_b) Divide complex_number _a with _b, in the form:
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
reciprocal(complex_number) Computes the reciprocal or inverse of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
negative(complex_number) Negative of complex_number, in the form:
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
inverse(complex_number) Inverse of complex_number, in the form:
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
exponential(complex_number) Exponential of complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
ceil(complex_number, digits) Ceils complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
digits : int, digits to use as ceiling.
Returns: _complex: pseudo complex number in the form of a array
radius(complex_number) Radius(magnitude) of complex_number, in the form:
This is defined as its distance from the origin (0,0) of the complex plane.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float value with radius.
magnitude(complex_number) magnitude(absolute value) of complex_number, should be the same as the radius.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float.
magnitude_squared(complex_number) magnitude(absolute value) of complex_number, should be the same as the radius.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float.
sign(complex_number) Unity of complex numbers.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, complex number.
MathComplexArrayLibrary "MathComplexArray"
Array methods to handle complex number arrays.
new(size, initial_complex) Prototype to initialize a array of complex numbers.
Parameters:
size : size of the array.
initial_complex : Complex number to be used as default value, in the form of array .
Returns: float array, pseudo complex Array in the form of a array
get(id, index) Get the complex number in a array, in the form of a array
Parameters:
id : float array, ID of the array.
index : int, Index of the complex number.
Returns: float array, pseudo complex number in the form of a array
set(id, index, complex_number) Sets the values complex number in a array.
Parameters:
id : float array, ID of the array.
index : int, Index of the complex number.
complex_number : float array, Complex number, in the form: .
Returns: Void, updates array id.
push(id, complex_number) Push the values into a complex number array.
Parameters:
id : float array, ID of the array.
complex_number : float array, Complex number, in the form: .
Returns: Void, updates array id.
pop(id, complex_number) Pop the values from a complex number array.
Parameters:
id : float array, ID of the array.
complex_number : float array, Complex number, in the form: .
Returns: Void, updates array id.
to_string(id, format) Reads a array of complex numbers into a string, of the form: " [ , ... ]""
Parameters:
id : float array, ID of the array.
format : string, format of the number conversion, default='#.##########'.
Returns: string, translated complex array into string.
MathComplexCoreLibrary "MathComplexCore"
Core functions to handle complex numbers.
set_real(complex_number, real) Set the real part of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
real : float, value to replace real value of complex_number.
Returns: Void, Modifies complex_number.
set_imaginary(complex_number, imaginary) Set the imaginary part of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
imaginary : float, value to replace imaginary value of complex_number.
Returns: Void, Modifies complex_number.
new(real, imaginary) Creates a prototype array to handle complex numbers.
Parameters:
real : float, real value of the complex number. default=0.
imaginary : float, imaginary number of the complex number. default=0.
@return float array, pseudo complex number in the form of a array .
zero() complex number "0+0i".
@return float array, pseudo complex number in the form of a array .
one() complex number "1+0i".
@return float array, pseudo complex number in the form of a array .
imaginary_one() complex number "0+1i".
@return float array, pseudo complex number in the form of a array .
nan() complex number "0+1i".
@return float array, pseudo complex number in the form of a array .
from_polar_coordinates(magnitude, phase) Create a complex number from a point's polar coordinates.
Parameters:
magnitude : float, default=0.0, The magnitude, which is the distance from the origin (the intersection of the x-axis and the y-axis) to the number.
phase : float, default=0.0, The phase, which is the angle from the line to the horizontal axis, measured in radians.
@return float array, pseudo complex number in the form of a array .
get_real(complex_number) Get the real part of complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: float, Real part of the complex_number.
get_imaginary(complex_number) Get the imaginary part of complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: float, Imaginary part of the complex number.
is_complex(complex_number) Checks that its a valid complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_nan(complex_number) Checks that its empty "na" complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_real(complex_number) Checks that the complex_number is real.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_real_non_negative(complex_number) Checks that the complex_number is real and not negative.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_zero(complex_number) Checks that the complex_number is zero.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
equals(complex_number_a, complex_number_b) Compares two complex numbers:
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: boolean value representing the equality.
to_string(complex, format) Converts complex_number to a string format, in the form: "a+bi"
Parameters:
complex : pseudo complex number in the form of a array .
format : string, formating to apply.
Returns: a string in "a+bi" format
ArrayStatisticsLibrary "ArrayStatistics"
Statistic Functions using arrays.
rms(sample) Root Mean Squared
Parameters:
sample : float array, data sample points.
Returns: float
skewness_pearson1(sample) Pearson's 1st Coefficient of Skewness.
Parameters:
sample : float array, data sample.
Returns: float
skewness_pearson2(sample) Pearson's 2nd Coefficient of Skewness.
Parameters:
sample : float array, data sample.
Returns: float
pearsonr(sample_a, sample_b) Pearson correlation coefficient measures the linear relationship between two datasets.
Parameters:
sample_a : float array, sample with data.
sample_b : float array, sample with data.
Returns: float p
kurtosis(sample) Kurtosis of distribution.
Parameters:
sample : float array, data sample.
Returns: float
range_int(sample, percent) Get range around median containing specified percentage of values.
Parameters:
sample : int array, Histogram array.
percent : float, Values percentage around median.
Returns: tuple with , Returns the range which containes specifies percentage of values.
BinaryDecimalConversionLibrary "BinaryDecimalConversion"
Converts decimal to and from binary.
to_binary(number) convert integer to binary string
Parameters:
number : int, value to convert.
Returns: string
to_decimal(binary) Converts a binary in a string to decimal.
Parameters:
binary : string, binary number in a string.
Returns: int
StringEvaluationLibrary "StringEvaluation"
Methods to handle evaluation of strings.
is_comma(char) Check if char is a comma ".".
Parameters:
char : string, 1 character string.
Returns: bool.
is_op(char) Check if char is a operator.
Parameters:
char : string, 1 character string.
Returns: bool.
number(char) convert a single char string into valid number.
Parameters:
char : string, 1 character string.
Returns: float.
operator(op, left, right) operation between left and right values.
Parameters:
op : string, operator string character.
left : float, left value of operation.
right : float, right value of operation.
operator_precedence(op) level of precedence of operator.
Parameters:
op : string, operator 1 char string.
Returns: int.
cleanup(_str) Evaluate a string to clean up and retrieve only used chars
Parameters:
_str : string, arithmetic operations in a string.
Returns: string array, evaluated array.
generate_rpn(tokens) uses Shunting-Yard algorithm to generate a RPN (Reverse Polish notation)
array of strings from a array of strings containing arithmetic notation.
ex:.. ' ' --> ' '
Parameters:
tokens : string array, array with arithmetic notation.
Returns:
parse_rpn() evaluate a RPN (Reverse Polish notation) array of strings.
ex:.. 3 4 2 * 1 5 - 2 3 ^ ^ / +
| @param tokens string array, RPN ordered tokens, ex( ).
| @returns float, solution.
eval() evaluate a string with references to a array of arguments.
| @param tokens string, arithmetic operations with references to indices in arguments, ex:"0+1*0+2*2+3" arguments
| @param arguments float array, arguments.
| @returns float, solution.
SignificantFiguresLibrary "SignificantFigures"
sigFig(float _float, int _figures)
@description Takes a floating-point number - one that can, but doesn't have to, include a decimal point - and converts it to a floating-point number with only a certain number of digits left. For example, say you want to display a variable from your script to the user and it comes out to something like 45.366666666666666666666667 or whatever. That looks awful when you, for example, print it in a label. Now you could round it up to the nearest integer easily using a built-in function, or even to a certain number of decimal places using a reasonably simple custom function. But that's a bit arbitrary. Suppose you don't know what asset the script will be used on, and so you can't predict what the price is, and what the value will turn out to be. It could be 0.00045366666666666666666666667 instead. Now if you round it up to 3 decimal places it comes out as 0.000, which is useless. My function will round that number to 0.0004536 instead, if told to do it to 4 significant digits.
I think this is more friendly.
@function Converts float with arbitrary number of digits to one with a specified number of significant figures.
@param float _float is the floating-point number to manipulate.
@param int _figures is the number of significant figures you want.
@returns Returns a float with the specified number of significant figures
MathSpecialFunctionsGammaLibrary "MathSpecialFunctionsGamma"
Gamma Functions.
GammaQ(index) Enumeration of the polynomial coefficients for the "GammaLn" approximation.
Parameters:
index : int, 0 => index => 10, index of coeficient.
Returns: float
GammaLn(z) Computes the logarithm of the Gamma function.
Parameters:
z : The argument of the gamma function.
Returns: The logarithm of the gamma function.
Gamma(z) Computes the Gamma function.
Parameters:
z : The argument of the gamma function.
Returns: float, The logarithm of the gamma function.
GammaLowerRegularized(a, x)
Parameters:
a : float, The argument for the gamma function.
x : float, The upper integral limit.
Returns: float, The lower incomplete gamma function.
GammaUpperRegularized(a, x) Returns the upper incomplete regularized gamma function
Parameters:
a : float, The argument for the gamma function.
x : float, The lower integral limit.
Returns: float, The upper incomplete regularized gamma function.
GammaUpperIncomplete(a, x) Returns the upper incomplete gamma function.
Parameters:
a : float, The argument for the gamma function.
x : float, The lower integral limit.
Returns: float, The upper incomplete gamma function.
GammaLowerIncomplete(a, x)
Parameters:
a : float, The argument for the gamma function.
x : float, The upper integral limit.
Returns: float, The lower incomplete gamma function.
ProbabilityLibrary "Probability"
erf(value) Complementary error function
Parameters:
value : float, value to test.
Returns: float
ierf_mcgiles(value) Computes the inverse error function using the Mc Giles method, sacrifices accuracy for speed.
Parameters:
value : float, -1.0 >= _value >= 1.0 range, value to test.
Returns: float
ierf_double(value) computes the inverse error function using the Newton method with double refinement.
Parameters:
value : float, -1. > _value > 1. range, _value to test.
Returns: float
ierf(value) computes the inverse error function using the Newton method.
Parameters:
value : float, -1. > _value > 1. range, _value to test.
Returns: float
complement(probability) probability that the event will not occur.
Parameters:
probability : float, 0 >=_p >= 1, probability of event.
Returns: float
entropy_gini_impurity_single(probability) Gini Inbalance or Gini index for a given probability.
Parameters:
probability : float, 0>=x>=1, probability of event.
Returns: float
entropy_gini_impurity(events) Gini Inbalance or Gini index for a series of events.
Parameters:
events : float , 0>=x>=1, array with event probability's.
Returns: float
entropy_shannon_single(probability) Entropy information value of the probability of a single event.
Parameters:
probability : float, 0>=x>=1, probability value.
Returns: float, value as bits of information.
entropy_shannon(events) Entropy information value of a distribution of events.
Parameters:
events : float , 0>=x>=1, array with probability's.
Returns: float
inequality_chebyshev(n_stdeviations) Calculates Chebyshev Inequality.
Parameters:
n_stdeviations : float, positive over or equal to 1.0
Returns: float
inequality_chebyshev_distribution(mean, std) Calculates Chebyshev Inequality.
Parameters:
mean : float, mean of a distribution
std : float, standard deviation of a distribution
Returns: float
inequality_chebyshev_sample(data_sample) Calculates Chebyshev Inequality for a array of values.
Parameters:
data_sample : float , array of numbers.
Returns: float
intersection_of_independent_events(events) Probability that all arguments will happen when neither outcome
is affected by the other (accepts 1 or more arguments)
Parameters:
events : float , 0 >= _p >= 1, list of event probabilities.
Returns: float
union_of_independent_events(events) Probability that either one of the arguments will happen when neither outcome
is affected by the other (accepts 1 or more arguments)
Parameters:
events : float , 0 >= _p >= 1, list of event probabilities.
Returns: float
mass_function(sample, n_bins) Probabilities for each bin in the range of sample.
Parameters:
sample : float , samples to pool probabilities.
n_bins : int, number of bins to split the range
@return float
cumulative_distribution_function(mean, stdev, value) Use the CDF to determine the probability that a random observation
that is taken from the population will be less than or equal to a certain value.
Or returns the area of probability for a known value in a normal distribution.
Parameters:
mean : float, samples to pool probabilities.
stdev : float, number of bins to split the range
value : float, limit at which to stop.
Returns: float
transition_matrix(distribution) Transition matrix for the suplied distribution.
Parameters:
distribution : float , array with probability distribution. ex:.
Returns: float
diffusion_matrix(transition_matrix, dimension, target_step) Probability of reaching target_state at target_step after starting from start_state
Parameters:
transition_matrix : float , "pseudo2d" probability transition matrix.
dimension : int, size of the matrix dimension.
target_step : number of steps to find probability.
Returns: float
state_at_time(transition_matrix, dimension, start_state, target_state, target_step) Probability of reaching target_state at target_step after starting from start_state
Parameters:
transition_matrix : float , "pseudo2d" probability transition matrix.
dimension : int, size of the matrix dimension.
start_state : state at which to start.
target_state : state to find probability.
target_step : number of steps to find probability.
MathStatisticsKernelDensityEstimationLibrary "MathStatisticsKernelDensityEstimation"
(KDE) Method for Kernel Density Estimation
kde(observations, kernel, bandwidth, nsteps)
Parameters:
observations : float array, sample data.
kernel : string, the kernel to use, default='gaussian', options='uniform', 'triangle', 'epanechnikov', 'quartic', 'triweight', 'gaussian', 'cosine', 'logistic', 'sigmoid'.
bandwidth : float, bandwidth to use in kernel, default=0.5, range=(0, +inf), less will smooth the data.
nsteps : int, number of steps in range of distribution, default=20, this value is connected to how many line objects you can display per script.
Returns: tuple with signature: (float array, float array)
draw_horizontal(distribution_x, distribution_y, distribution_lines, graph_lines, graph_labels) Draw a horizontal distribution at current location on chart.
Parameters:
distribution_x : float array, distribution points x value.
distribution_y : float array, distribution points y value.
distribution_lines : line array, array to append the distribution curve lines.
graph_lines : line array, array to append the graph lines.
graph_labels : label array, array to append the graph labels.
Returns: void, updates arrays: distribution_lines, graph_lines, graph_labels.
draw_vertical(distribution_x, distribution_y, distribution_lines, graph_lines, graph_labels) Draw a vertical distribution at current location on chart.
Parameters:
distribution_x : float array, distribution points x value.
distribution_y : float array, distribution points y value.
distribution_lines : line array, array to append the distribution curve lines.
graph_lines : line array, array to append the graph lines.
graph_labels : label array, array to append the graph labels.
Returns: void, updates arrays: distribution_lines, graph_lines, graph_labels.
style_distribution(lines, horizontal, to_histogram, line_color, line_style, linewidth) Style the distribution lines.
Parameters:
lines : line array, distribution lines to style.
horizontal : bool, default=true, if the display is horizontal(true) or vertical(false).
to_histogram : bool, default=false, if graph style should be switched to histogram.
line_color : color, default=na, if defined will change the color of the lines.
line_style : string, defaul=na, if defined will change the line style, options=('na', line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_right, line.style_arrow_left, line.style_arrow_both)
linewidth : int, default=na, if defined will change the line width.
Returns: void.
style_graph(lines, lines, horizontal, line_color, line_style, linewidth) Style the graph lines and labels
Parameters:
lines : line array, graph lines to style.
lines : labels array, graph labels to style.
horizontal : bool, default=true, if the display is horizontal(true) or vertical(false).
line_color : color, default=na, if defined will change the color of the lines.
line_style : string, defaul=na, if defined will change the line style, options=('na', line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_right, line.style_arrow_left, line.style_arrow_both)
linewidth : int, default=na, if defined will change the line width.
Returns: void.