Monte-Carlo-Method | "Hit or Miss" MC

 by   Gigi-G TypeScript Version: Current License: GPL-3.0

kandi X-RAY | Monte-Carlo-Method Summary

kandi X-RAY | Monte-Carlo-Method Summary

Monte-Carlo-Method is a TypeScript library. Monte-Carlo-Method has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

"Hit or Miss" MC
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            kandi-support Support

              Monte-Carlo-Method has a low active ecosystem.
              It has 10 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              Monte-Carlo-Method has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Monte-Carlo-Method is current.

            kandi-Quality Quality

              Monte-Carlo-Method has 0 bugs and 0 code smells.

            kandi-Security Security

              Monte-Carlo-Method has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              Monte-Carlo-Method code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              Monte-Carlo-Method is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              Monte-Carlo-Method releases are not available. You will need to build from source code and install.
              Installation instructions are available. Examples and code snippets are not available.
              It has 281 lines of code, 0 functions and 42 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            Monte-Carlo-Method Key Features

            No Key Features are available at this moment for Monte-Carlo-Method.

            Monte-Carlo-Method Examples and Code Snippets

            Estimate the probability of a point in the circle .
            pythondot img1Lines of Code : 28dot img1License : Permissive (MIT License)
            copy iconCopy
            def pi_estimator(iterations: int):
                """
                An implementation of the Monte Carlo method used to find pi.
                1. Draw a 2x2 square centred at (0,0).
                2. Inscribe a circle within the square.
                3. For each iteration, place a dot anywhere in the   
            Calculate the area under a curve estimator .
            pythondot img2Lines of Code : 27dot img2License : Permissive (MIT License)
            copy iconCopy
            def area_under_curve_estimator(
                iterations: int,
                function_to_integrate: Callable[[float], float],
                min_value: float = 0.0,
                max_value: float = 1.0,
            ) -> float:
                """
                An implementation of the Monte Carlo method to find area unde  

            Community Discussions

            Trending Discussions on Monte-Carlo-Method

            QUESTION

            How to calculate error of calculated integral in python?
            Asked 2018-Jun-28 at 15:58

            I am calculating an integral with the Monte-Carlo-Method (for 3 different N's 10, 100, 1000), but I want to calculate the error to the real exact value of the integral (calculated analytically). How to do that? How to calculate the real value of the integral, and plot&print the error value?

            Here is the code I am using now, to calculate the integral with the Monte-Carlo-Method:

            ...

            ANSWER

            Answered 2018-Jun-28 at 15:58

            You could use scipy.integrate, which offers different methods of calculating the integral. e.g.:

            Source https://stackoverflow.com/questions/51086879

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install Monte-Carlo-Method

            Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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          • HTTPS

            https://github.com/Gigi-G/Monte-Carlo-Method.git

          • CLI

            gh repo clone Gigi-G/Monte-Carlo-Method

          • sshUrl

            git@github.com:Gigi-G/Monte-Carlo-Method.git

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