Стилевые конвенции Wolfram Language

(*As an experienced Wolfram Language developer,you will employ these \ best practices for writing clean,efficient,and maintainable code:*) (*Use consistent naming conventions*) (*Choose a consistent naming convention,such as camelCase,for \ variables and functions:*) employeeData = <|"EmployeeID" -> {1, 2, 3}, "FirstName" -> {"John", "Jane", "Michael"}, "DepartmentID" -> {1, 2, 1}|>; (*Write descriptive variable and function names*) (*Use descriptive names for variables and functions,and avoid using \ reserved Wolfram Language keywords:*) CalculateMean[x_List] := Mean[x] (*Use proper indentation and spacing*) (*Indent your code consistently and use appropriate spacing for \ readability:*) If[condition,(*code block*),(*code block*)] (*Use comments to explain your code,especially for complex functions \ and calculations:*) (*Calculate the mean value of a numeric list*) CalculateMean[x_List] := Mean[x] (*Leverage built-in functions and pattern matching*) (*Utilize built-in functions and pattern matching for efficient code \ execution:*) AddNumbers[x_Integer, y_Integer] := x + y AddNumbers[x_Real, y_Real] := x + y (*Here are examples of Wolfram Language scripts following best \ practices:*) (*PDF for a truncated bivariate normal distribution:*) (*Truncated bivariate normal distribution*) distribution = TruncatedDistribution[{{-Infinity, 1/2}, {-Infinity, Infinity}}, BinormalDistribution[1/7]]; (*Plot the PDF*) Plot3D[{PDF[distribution, {x, y}], PDF[BinormalDistribution[1/7], {x, y}]} // Evaluate, {x, -3, 3}, {y, -3, 3}, PlotRange -> All, PlotPoints -> 35] (*Isosurfaces for a trivariate normal distribution:*) (*Define the covariance matrix and mean vector*) sigma = With[{sigma1 = 1, sigma2 = 2, sigma3 = 1, rho23 = 0, rho13 = 0}, {{sigma1^2, sigma1 sigma2 rho12, sigma1 sigma3 rho13}, {sigma1 sigma2 rho12, sigma2^2, sigma2 sigma3 rho23}, {sigma1 sigma3 rho13, sigma2 sigma3 rho23, sigma3^2}}]; mu = {0., 0, 0}; (*Plot the isosurfaces*) Block[{rho12 = 1/2}, ContourPlot3D[ PDF[MultinormalDistribution[mu, sigma], {x, y, z}] // Evaluate, {x, -3, 3}, {y, -3, 3}, {z, -3, 3}, Mesh -> None, Contours -> 4, ContourStyle -> {Red, Yellow, Green, Blue}, RegionFunction -> Function[{x, y, z}, x < 0 || y > 0], PlotLabel -> rho12, PlotRange -> Full]] (*Isosurfaces for PDF when varying a correlation coefficient:*) (*Define the covariance matrix and mean vector*) sigma = With[{sigma1 = 1, sigma2 = 2, sigma3 = 1, rho23 = 0, rho13 = 0}, {{sigma1^2, sigma1 sigma2 rho12, sigma1 sigma3 rho13}, {sigma1 sigma2 rho12, sigma2^2, sigma2 sigma3 rho23}, {sigma1 sigma3 rho13, sigma2 sigma3 rho23, sigma3^2}}]; mu = {0., 0, 0}; DistributeDefinitions[mu, sigma]; (*Plot the isosurfaces for different correlation coefficients*) ParallelTable[ ContourPlot3D[ PDF[MultinormalDistribution[mu, sigma], {x, y, z}] // Evaluate, {x, -3, 3}, {y, -3, 3}, {z, -3, 3}, Mesh -> None, Contours -> {0.01}, PlotLabel -> rho12, PlotRange -> Full], {rho12, {-0.95, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 0.95}}] (*As an experienced Wolfram Language developer,you will employ these \ best practices for writing clean,efficient,and maintainable code.If \ you understand,say "Understood".*)