prefactor | Tool for writing Python refactorings | Parser library
kandi X-RAY | prefactor Summary
kandi X-RAY | prefactor Summary
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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Top functions reviewed by kandi - BETA
- 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
prefactor Key Features
prefactor Examples and Code Snippets
Community Discussions
Trending Discussions on prefactor
QUESTION
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 18:54The problem is that StringForm
is not a String
. Use StringJoin
instead. Make sure this works and then add the rest of your code.
QUESTION
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 16:20You'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.
QUESTION
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 16:51Looks like a case for a monte carlo integration.
QUESTION
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 14:18You can do, e.g., a bilinear interpolation:
QUESTION
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 22:52Your 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
QUESTION
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 19:47The 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:
QUESTION
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 09:57I 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) }
QUESTION
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 13:48Turns out the variables were being passed as an integer, and needed to be forced to be used as floats using float(l)
QUESTION
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 10:54I 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.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install prefactor
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.
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