algorithms-in-python | Implementing testing some algorithms in python | Learning library

 by   AnthonyDiGirolamo Python Version: Current License: MIT

kandi X-RAY | algorithms-in-python Summary

kandi X-RAY | algorithms-in-python Summary

algorithms-in-python is a Python library typically used in Tutorial, Learning, Example Codes applications. algorithms-in-python has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However algorithms-in-python build file is not available. You can download it from GitHub.

Implementing and testing some algorithms in python (and ruby).
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              algorithms-in-python has a low active ecosystem.
              It has 8 star(s) with 2 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              algorithms-in-python has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of algorithms-in-python is current.

            kandi-Quality Quality

              algorithms-in-python has no bugs reported.

            kandi-Security Security

              algorithms-in-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              algorithms-in-python is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              algorithms-in-python releases are not available. You will need to build from source code and install.
              algorithms-in-python has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed algorithms-in-python and discovered the below as its top functions. This is intended to give you an instant insight into algorithms-in-python implemented functionality, and help decide if they suit your requirements.
            • Heaps sort
            • Sift down - down
            • Remove count elements from an array
            • Top - level merge algorithm
            • Top - down merge
            • Performs the top - down merge
            Get all kandi verified functions for this library.

            algorithms-in-python Key Features

            No Key Features are available at this moment for algorithms-in-python.

            algorithms-in-python Examples and Code Snippets

            No Code Snippets are available at this moment for algorithms-in-python.

            Community Discussions

            Trending Discussions on algorithms-in-python

            QUESTION

            Lossy conversion from float64 to uint8
            Asked 2020-Mar-20 at 06:16

            ANSWER

            Answered 2019-Nov-16 at 22:46

            The warning is self explanatory: color.convert_colorspace(in_hsv_h, 'HSV', 'RGB') is of type float64, and imsave, convert elements to uint8.

            The pixels of PNG image, are stored as one byte per component (one byte for red, one for green and one for blue).
            Each component is an integer value in range [0, 255] (type uint8).

            The output of color.convert_colorspace is of float64, each color component is in range [0, 1] of type float64 (stored as 64 bits in memory, and much more accurate than uint8).

            The conversion from float64 range [0, 1] to uint8 range [0, 255] is performed like: uint8_val = round(float64_val*255).
            The rounding operation loose some data (for example: in case float64_val*255 = 132.658, the result is rounded to 133).

            Convert image to uint8 prior to saving to suppress this warning

            Tells you to convert the image elements to uint8 prior to saving.

            Solution is simple.
            Multiply by 255, and add .astype(np.uint8).

            Source https://stackoverflow.com/questions/58893860

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

            Vulnerabilities

            No vulnerabilities reported

            Install algorithms-in-python

            You can download it from GitHub.
            You can use algorithms-in-python like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            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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