Metropolis | A modern , geometric typeface | User Interface library

 by   chrismsimpson Python Version: r11 License: Unlicense

kandi X-RAY | Metropolis Summary

kandi X-RAY | Metropolis Summary

Metropolis is a Python library typically used in User Interface applications. Metropolis has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However Metropolis build file is not available. You can download it from GitHub.

A modern, geometric typeface. Influenced by other popular geometric, minimalist sans-serif typefaces of the new millenium. Designed for optimal readability at small point sizes while beautiful at large point sizes.
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              Metropolis has a medium active ecosystem.
              It has 1731 star(s) with 88 fork(s). There are 52 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 10 open issues and 25 have been closed. On average issues are closed in 404 days. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Metropolis is r11

            kandi-Quality Quality

              Metropolis has no bugs reported.

            kandi-Security Security

              Metropolis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              Metropolis is licensed under the Unlicense License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Metropolis releases are available to install and integrate.
              Metropolis has no build file. You will be need to create the build yourself to build the component from source.

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            Metropolis Key Features

            No Key Features are available at this moment for Metropolis.

            Metropolis Examples and Code Snippets

            Metropolis-Hastings GAN (MHGAN),Notes
            Pythondot img1Lines of Code : 23dot img1License : Permissive (MIT)
            copy iconCopy
            gan = WGAN(
                Generator(
                  input_shape=noise_dimensions,
                  output_shape=real_dimensions
                ),
                Discriminator()
            )
            gan.train(
                sess,
                data_sampler,
                noise_sampler,
                batch_size=32,
                n_epochs=100,
                n_accumulate=1
            )
            
            mhgan   
            Metropolis-Hastings GAN (MHGAN),Notes
            Pythondot img2Lines of Code : 23dot img2License : Permissive (MIT)
            copy iconCopy
            gan = WGAN(
                Generator(
                  input_shape=noise_dimensions,
                  output_shape=real_dimensions
                ),
                Discriminator()
            )
            gan.train(
                sess,
                data_sampler,
                noise_sampler,
                batch_size=32,
                n_epochs=100,
                n_accumulate=1
            )
            
            mhgan   
            Metropolis,Example,Define Worker task
            Pythondot img3Lines of Code : 15dot img3License : Permissive (MIT)
            copy iconCopy
            from metropolis import Worker
            
            
            worker = Worker(nats='nats://localhost:4222')
            
            
            @worker.task(subject='foo.bar', queue='worker')
            def mytask(data, *args, **kwargs):
                """Simple task which returns reverse string
                """
            
                return data[0][::-1]
            
            
            wor  

            Community Discussions

            QUESTION

            drop_duplicates even more for a specific column with latest value?
            Asked 2022-Apr-15 at 22:30

            Is there a way to customize drop_duplicates so that it drops the "kind of" duplicates?

            Example: pandas df

            Year Name ID City 2011 Superman 101 Metropolis 2011 Batman 102 Gotham 2012 The Batman 102 Gotham 2011 Noobmaster69 103 Online 2011 Noobmaster69 103 Online

            I tried using drop_duplicates so I got this

            Year Name ID City 2011 Superman 101 Metropolis 2011 Batman 102 Gotham 2012 The Batman 102 Gotham 2011 Noobmaster69 103 Online

            I actually want to squeeze it even more, as I want only "102" row with "The Batman" which is newer info (2012>2011) to be on the data frame. Expecting something like this

            Year Name ID City 2011 Superman 101 Metropolis 2012 The Batman 102 Gotham 2011 Noobmaster69 103 Online ...

            ANSWER

            Answered 2022-Apr-15 at 22:30

            Try this, duplicates can be easily delete with ID column.

            Source https://stackoverflow.com/questions/71879993

            QUESTION

            R beamer numbering in default theme
            Asked 2022-Mar-21 at 17:09

            I am looking for a solution on how to force slides numbering in R's beamer_presentation with theme set at "default".

            So far, I have found a solution but under them "metropolis". If I just type "default" instead of "metropolis", there is an error.

            ...

            ANSWER

            Answered 2022-Mar-21 at 17:09

            Beamer actually has a very handy macro to add frame numbers: \setbeamertemplate{footline}[frame numbers] to the footline

            Source https://stackoverflow.com/questions/70853716

            QUESTION

            How do I remove the
            Asked 2022-Mar-11 at 16:53

            So, right now, what I'm trying to do is that I'm trying to scrape a table from rottentomatoes.com and but every time I run the code, I'm facing an issue that it just prints

            This is my code so far:

            ...

            QUESTION

            Ising model metropolis algorithm
            Asked 2022-Mar-09 at 21:34

            I am trying to use the metropolis algorithm to simulate the Ising model. The problem that I am having is that the code will not settle all the time. For high beta values, the energy preference should be that the spins are all in the same direction, however in my code, even though it works most of the time, occasionally there will be horizontal or vertical bands of spin up and then spin down in the grid (grid2). This then makes the average spin count settle at a value which is not 1 or -1 which it should be for high beta. I have some idea where the problem lies - my delta energy at the boundary when this occurs is 4 and so at high beta this makes it really unlikely that the spin will flip and so it ends up being stuck. I was thinking that maybe I am not running it long enough but looking at the average_spin_count on the variable explorer it seems to settle after maximum 200 turns. I was also thinking maybe using diagonals but other codes and simulations of this don't seem to use this idea and so I was hoping someone could point out where I am going wrong. (You have to run the code multiple times until you get a case where there are not all spin up/down). Thanks

            ...

            ANSWER

            Answered 2022-Mar-09 at 21:34

            If you plot the final grid of such a case, you will see what happens, use matplotlib for example, see below:

            Source https://stackoverflow.com/questions/71415396

            QUESTION

            Implementation of the Metropolis-Hasting algorithm for solving gaussian integrals
            Asked 2022-Feb-02 at 20:28

            I am currently having issue with the implementation of the Metropolis-Hastings algorithm.

            I am trying to use the algorithm to calculate integrals of the form

            In using this algorithm, we can obtain a long chain of configurations ( in this case, each configuration is just a single numbers) such that in the tail-end of the chain the probability of having a particular configuration follows (or rather tends to) a gaussian distribution.

            My code seems to be messing up with obtaining the said gaussian distributions. There is a strange dependence on the transition probablity (the probablity of picking a new candidate configuration depending on the previous configuration in the chain). However, if this transition probability is symmetric, there should be no dependence on this function at all (it only affects speed at which phase space [space of potential configurations] is explored and how quickly the chain converges to the desired distribution)!

            In my case I am using a normal distribution transition function (which satisfies the need to be symmetric), with width d. For each d I use I do indeed get a gaussian distribution however the standard deviation, sigma, depends on my choice of d. The resulting gaussian should have a sigma of roughly 0.701 but I find that the value I actually get depends on the parameter d, when it shouldn't.

            I am not sure where the error in this code is, any help would be greatly appreciated!

            ...

            ANSWER

            Answered 2022-Feb-02 at 20:28

            You need to save x even when it doesn't change. Otherwise the center values are under-counted, and more so as d increases, which increases the variance.

            Source https://stackoverflow.com/questions/70958350

            QUESTION

            invalid value encountered in log in Python
            Asked 2022-Jan-24 at 13:10

            I am trying to impement the random walk metropolis hastings algorithm which my code is :

            ...

            ANSWER

            Answered 2022-Jan-24 at 13:10

            When you call the function with this variables. The result of 1+omega*(data-mucan)**2 has a lot of negative number and when calculate np.log(1+omega*(data-mucan)**2) code calculate np.log(negative number) and this is invalid value encountered in log. negative number for log is out of the range

            Source https://stackoverflow.com/questions/70834135

            QUESTION

            MCMC for estimating negative binomial distribution
            Asked 2022-Jan-19 at 21:25

            I want to estimate parameters of negative binomial distribution using MCMC Metropolis-Hastings algorithm. In other words, I have sample:

            ...

            ANSWER

            Answered 2022-Jan-19 at 21:25

            Change dnorm in loglikelihood to dnbinom and fix the proposal for prob so it doesn't go outside (0,1):

            Source https://stackoverflow.com/questions/70777597

            QUESTION

            Operator= slowing down simulation
            Asked 2022-Jan-14 at 02:09

            I am running a Monte Carlo simulation of a polymer. The entire configuration of the current state of the system is given by the object called Grid. This is my definition of Grid:

            ...

            ANSWER

            Answered 2022-Jan-14 at 02:09

            One thing that you can certainly do to improve performance is to force moving _G rather than coping it to G:

            Source https://stackoverflow.com/questions/70661636

            QUESTION

            How to dynamically change the size of icon in
            Asked 2021-Dec-08 at 02:34

            currently, to style my icons under the 'react-icons' library, I am using the 'IconContext.Provider' tag. However, is there a solution for me to change the size of the icon dynamically based on the size of my media ?

            Is the only solution to go about doing this only with the global stylesheet? I am avoiding it as I have only just started using NextJs and I do not want my style to have a possible clash with other style. Hence, I am separating them into modules.

            Thank you.

            NavBar.Module.Css

            ...

            ANSWER

            Answered 2021-Dec-08 at 02:34

            I did "npm i react-responsive" and import the following in my code

            Source https://stackoverflow.com/questions/70215794

            QUESTION

            Change representation (background-color & frame) of chunks in RMarkdown (with Beamer-Presentations)
            Asked 2021-Oct-21 at 20:02

            Background: I'm using the metropolis theme which slides background colour is the same as the default background colour of the displayed code in chunks in beamer.

            Problem: I want to change the representation of the chunks output. There should be a different type of representation for source-code & results to distinguish them. The source-codes background should be in a slightly darker grey than the metropolis slides background and the results should be surrounded by a black line as a frame.

            What I already tried: This threat answers my question for HTML-outputs (YAML: output: html_document), but I didn't figured out how to get it working in beamer_presentation.

            This is my "minimal" working example:

            ...

            ANSWER

            Answered 2021-Oct-21 at 20:02
            • you can change the colour of the code with \definecolor{shadecolor}{RGB}{148,248,248} (choose whatever colour you like)

            • adding a frame around the output is a bit more hacky. rmarkdown automatically loads all kinds of packages to format verbatim code, like the fancyverb package, but then it goes ahead and ignores them and uses the normal latex verbatim endvironment for the output. Makes no sense at all, but you can use this dirty hack to redefine the environment like this to use the fancyverb package which provides an option to add a frame:

            Source https://stackoverflow.com/questions/69667762

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

            Vulnerabilities

            No vulnerabilities reported

            Install Metropolis

            You can download it from GitHub.
            You can use Metropolis 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

            Reachable via chris.m.simpson [at] icloud.com or tweet @ChrisMSimpson.
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