prefactor | Tool for writing Python refactorings | Parser library

 by   banga Python Version: Current License: No License

kandi X-RAY | prefactor Summary

kandi X-RAY | prefactor Summary

prefactor is a Python library typically used in Utilities, Parser applications. prefactor has no bugs, it has no vulnerabilities and it has low support. However prefactor build file is not available. You can download it from GitHub.

A tool for writing AST-based refactorings for large Python codebases. It uses lib2to3 to convert source code to an AST, run a visitor over it that modifies the tree, and convert the tree back into source code.
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            kandi-support Support

              prefactor has a low active ecosystem.
              It has 8 star(s) with 1 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              prefactor has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of prefactor is current.

            kandi-Quality Quality

              prefactor has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              prefactor does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              prefactor releases are not available. You will need to build from source code and install.
              prefactor 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 prefactor and discovered the below as its top functions. This is intended to give you an instant insight into prefactor implemented functionality, and help decide if they suit your requirements.
            • Remove parentheses around operator
            • Return True if power_node is multiline
            • Visit the node
            • Return the name of a node
            • Parse a file or directory
            • Parse a file
            • Parse a directory
            • Parse source
            • Return a JSON representation of a node
            • Remove imports
            • Remove import from node
            • Visit an import node
            • Visit import_as_as_names node
            • Render a source
            • Parse python code
            • Visit dictsetmaker
            • Visitor for dot
            • Visit the dotted name node
            Get all kandi verified functions for this library.

            prefactor Key Features

            No Key Features are available at this moment for prefactor.

            prefactor Examples and Code Snippets

            No Code Snippets are available at this moment for prefactor.

            Community Discussions

            QUESTION

            Do loop to run batch analysis of .dat
            Asked 2021-Jan-18 at 18:54

            I'm trying to edit a current Mathematica script, to allow for batch processing. This involves importing a series of files of different names (i.e. different numerical suffixes), and in the end writing different .dat for exporting results. I've tried implementing a Do loop for this (in the example code below, it's set up for files with 980 & 998 suffixes), but somehow Mathematica doesn't recognise the Do loop variable. Would someone be able to help? Or perhaps suggest a way of going about this? Thanks!

            ...

            ANSWER

            Answered 2021-Jan-18 at 18:54

            The problem is that StringForm is not a String. Use StringJoin instead. Make sure this works and then add the rest of your code.

            Source https://stackoverflow.com/questions/65779020

            QUESTION

            How to called special functions in the cmath library in C++?
            Asked 2020-Jun-28 at 16:20

            I am trying to define a function that requires me to make use of something called an "Associated Laguerre Polynomial". It's listed here under the library. In visual studio code, intellisense predicts "assoc_laguerre()" as a function so it clearly exists!

            Yet, when building the code, it highlights the assoc_laguerre() function with the message: "Identifier not found".

            Any help would be very appreciated! Thanks!

            Code:

            ...

            ANSWER

            Answered 2020-Jun-28 at 16:20

            You're not compiling with the C++ 2017 version of the language standard enabled. Enable it, and this should be available. Your code compiles with GCC 10.1 and -std=c++17; but not if we use -std=c++14 instead.

            GodBolt

            Source https://stackoverflow.com/questions/62625150

            QUESTION

            Most efficient way to numerically integrate a multivariate trig function with scipy?
            Asked 2020-Apr-22 at 20:38

            Edit: this question is essentially identical to this one and I encourage viewers to go there for more information. To add to that answer: because my function lacks narrow bumps, singularities, etc; has limited integration bounds; and is known to have a small integer solution (I only need 1-2 sigfigs), it is a near-ideal choice for a Monte Carlo algorithm. In the end 1e6 points were more than enough to solve it.

            I have a pretty complicated trig function of five variables x1, x2, x3, y1, z1 I'm trying to integrate over (-pi,pi) (once for every variable). I know the solution is an integer, so I'm only asking for one digit of precision during my numerical integration with scipy.integrate.nquad(); but it still ran for 74.5 hours on my laptop with no result before I stopped it. I also had no idea what my progress was by that point.

            My actual code (and the function):

            ...

            ANSWER

            Answered 2020-Apr-20 at 16:51

            Looks like a case for a monte carlo integration.

            Source https://stackoverflow.com/questions/61309624

            QUESTION

            How to map a 2D lookup table to array (python)?
            Asked 2020-Feb-20 at 14:18

            I have three 2D-arrays of same shape, lets call them theta, phi and A. Let theta and phi be angles to the normal vector seen from different distances on a surface:

            ...

            ANSWER

            Answered 2020-Feb-20 at 14:18

            You can do, e.g., a bilinear interpolation:

            Source https://stackoverflow.com/questions/60298076

            QUESTION

            Python calculation of LennardJones 2D interaction pair correlation distribution function in Grand Canonical Ensemble
            Asked 2019-Dec-10 at 11:00

            Edit I believe there is a problem with the normalization of the histogram, since one must divide with the radius of each element.

            I am trying trying to calculate the fluctuations of particle number and the radial distribution function of a 2d LennardJones(LJ) system using python3. Although I believe the particle fluctuations come out right, the pair correlation g(r) come right for small distances but then blow up ( the calculation uses numpy's histogram method).

            The thing is, I can' t find out why such a behavior emerges- perhaps of some misunderstanding of a method? As it is, I am posting the relevant code right below, and if needed, I could also upload other parts of the code or the entire script.

            Note first, that since we are working with the Grand-Canonical Ensemble, as the number of particles changes, so is the array that stores the particles- and perhaps that's another point where a mistake in implementation could exist.

            Particle removal or insertion

            ...

            ANSWER

            Answered 2019-Dec-08 at 22:52

            Your g(r) is not correctly normalised. You need to divide the number of pairs found in each bin by the average density of the system times the area of the annulus associated to that bin, where the latter is just 2 pi r dr, with r being the bin's midpoint and dr the bin size. As far as I can tell, your prefactor does not contain the "r" bit. There is also something else that is missing, but it's hard to tell without knowing what all the other constants contain.

            EDIT: here is a link that will guide you the implementation of a routine to compute the radial distribution function in 2D and 3D

            Source https://stackoverflow.com/questions/59236066

            QUESTION

            Prefactors computing PSD of a signal with numpy.fft VS. scipy.signal.welch
            Asked 2019-Sep-10 at 19:47

            The power spectral density St of a signal u may be computed as the product of the FFT of the signal, u_fft with its complex conjugate u_fft_c. In Python, this would be written as:

            ...

            ANSWER

            Answered 2019-Sep-10 at 19:47

            The definition of the paramater scale of scipy.signal.welch suggests that the appropriate scaling is performed by the function:

            scaling : { ‘density’, ‘spectrum’ }, optional Selects between computing the power spectral density (‘density’) where Pxx has units of V^2/Hz and computing the power spectrum (‘spectrum’) where Pxx has units of V^2, if x is measured in V and fs is measured in Hz. Defaults to ‘density’

            The correct sampling frequency is to be provided as argumentfs to retreive the correct frequencies and an accurate power spectral density. To recover a power spectrum similar to that computed using np.multiply(u_fft, np.conj(u_fft)), the length of the fft frame and the applied window must respectively be provided as the length of the frame and boxcar (equivalent to no window at all). The fact that scipy.signal.welch applies the correct scaling can be checked by testing a sine wave:

            Source https://stackoverflow.com/questions/57828899

            QUESTION

            RSpec model validation test error in Proc
            Asked 2018-Mar-05 at 09:57

            I'm running into an error with RSpec and I cannot figure out why it's givin the error. I use FactoryBot to create a sweep with sets a value for fsp_name. This value is somehow not recognized in the validations when trying to validate the first_order.

            The error that I'm getting is

            ...

            ANSWER

            Answered 2018-Mar-05 at 09:57

            I ran into an issue with shoulda-matchers when testing uniqueness of and this thread helped. Rspec validates_uniqueness_of test failing with additional validation errors

            I'm guessing that the test is checking the subject, which you haven't set, so it's creating a sweep object on its own. This object wouldn't be generated from factory bot and thus that field would be nil instead of [].

            Try adding this inside the describe Sweep: subject { FactoryBot.create(:sweep, simulation: @simulation) }

            Source https://stackoverflow.com/questions/49107047

            QUESTION

            Taking a sum in python over vectors scaling a variable to graph
            Asked 2017-Aug-01 at 13:48

            I am trying to plot a log-likelihood function in python for the Berthe-Blocke equation and I keep getting a nonsensical plot. Currently I am taking doing

            ...

            ANSWER

            Answered 2017-Aug-01 at 13:48

            Turns out the variables were being passed as an integer, and needed to be forced to be used as floats using float(l)

            Source https://stackoverflow.com/questions/42356989

            QUESTION

            Creating a normal distribution with rejection method yields wrong prefactor
            Asked 2017-Jan-20 at 08:38

            I'm trying to create normal distribution out of evenly distributed values in Fortran with the rejection method. It actually works more or less well, but I don't get exactly the result that I want.

            I generate the normal distribution with this segment of code

            ...

            ANSWER

            Answered 2017-Jan-03 at 10:54

            I just used your routine to generate 1000 points between -2 and 2 and obtained a gaussian distribution.

            How do you generate your histogram? The un-normalized histogram can be plotted with the function N exp(-x**2)/sqrt(pi) * dx where N is the number of points and dx is the binning interval.

            Source https://stackoverflow.com/questions/41425891

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

            Vulnerabilities

            No vulnerabilities reported

            Install prefactor

            You can download it from GitHub.
            You can use prefactor 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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            https://github.com/banga/prefactor.git

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            gh repo clone banga/prefactor

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            git@github.com:banga/prefactor.git

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