mpMath | WeChat official account formula editing plug-in | Document Editor library

 by   ciaochaos JavaScript Version: v0.1.8 License: MIT

kandi X-RAY | mpMath Summary

kandi X-RAY | mpMath Summary

mpMath is a JavaScript library typically used in Editor, Document Editor, Latex applications. mpMath has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

WeChat official account formula editing plug-in

            kandi-support Support

              mpMath has a low active ecosystem.
              It has 109 star(s) with 18 fork(s). There are 4 watchers for this library.
              It had no major release in the last 12 months.
              mpMath has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of mpMath is v0.1.8

            kandi-Quality Quality

              mpMath has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

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

            kandi-Reuse Reuse

              mpMath releases are available to install and integrate.
              It has 81 lines of code, 0 functions and 7 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            mpMath Key Features

            No Key Features are available at this moment for mpMath.

            mpMath Examples and Code Snippets

            No Code Snippets are available at this moment for mpMath.

            Community Discussions


            Handling rounding errors in matrix multiplication in numpy
            Asked 2022-Apr-09 at 14:53

            TL;DR: Matrix multiplication for state transition matrix should be norm preserving, but np.matmul does not conserve norm. How can I fix this? Is there a better python module to do so?

            I have a right state transition matrix, A, i.e., s(t)A(tau)=s(t+tau)

            where s(t) is a column matrix which sums to 1. Also, we know that each row of A adds upto 1 as well.

            We know that A^n is also a right state transition matrix for any n in natural numbers.

            One way to find the steady state distribution is to compute A^n as n goes to infinity. The following snippet calculates A^(2^n):



            Answered 2022-Apr-09 at 14:29

            The problem comes from the fact that the operation is not numerically stable. As a result it quickly diverge (exponentially) to 0 or infinity even with relatively-small values of n like 70. You can use a diagonalization method based on eigenvalues (see here for more informations) which is far more numerically stable.



            No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/rtree/lib'
            Asked 2022-Mar-13 at 16:13

            I am trying to build an app from a python file (Mac OS) using the py2app extension. I have a folder with the python file and the "" file.

            • I first tested the app by running python py2app -A in the terminal and the dist and build folder are successfully created and the app works when launched.
            • Now when I try to build it non-locally by running the command python py2app in the terminal, there are various "WARNING: ImportERROR" messages while building and finally a error: [Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/rtree/lib' error.

              How can I fix this? I've tried to delete anaconda fully as I don't use it but it seems to still want to run through it. Additionally, I have tried to run the build command using a virtual environment but I end up having even more import errors.
              *I Left out a lot of the "skipping" and "warning" lines using "..." for space


            Answered 2022-Mar-13 at 16:13

            The error error: [Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/rtree/lib' was caused by py2app trying to build the program bundle using a non-existent interpreter. This means that even if you try to uninstall a manager like Anaconda, it still has option logs somewhere on your mac.

            The fix:

            1. Open the terminal and type the command type -a python.
            • You will see similar lines



            Hexadecimal notation of square roots in Python - Sha-512
            Asked 2022-Mar-08 at 21:38

            I am going over the description of Sha-512. It is mentioned that the initial hash value consists of the sequence of 64-bit words that are obtained by taking the fractional part of the first eight primes. I am trying to replicate these values in Python, but I am not getting the same results. To include more digits, I am using the mpmath library.



            Answered 2022-Mar-08 at 21:38

            As a comment already explained, you're actually only using 53 bits in your calculations (native CPython float precision).

            Here's an easy way to reproduce the result you're apparently after:



            jupyter contrib nbextension install gives Jupyter command `jupyter-contrib` not found
            Asked 2022-Mar-01 at 17:47

            Trying to (re)install Jupyter's nbextension via the following steps in terminal

            1. pip install jupyter_contrib_nbextensions
            2. jupyter contrib nbextension install --user
            3. install --user jupyter nbextension enable varInspector/main

            Step 1 = runs and i am able to launch notebooks via "jupyter notebook" in terminal just fine.

            Step 2 = fails with



            Answered 2022-Mar-01 at 17:47

            So in case anyone comes across similar for any reason with me encountering this probably due getting a new machine and IT doing their voodoo magic transferring my old stuff to this new machine.

            Anyhow, there were a bunch of things I still needed to install after I got my new machine and i am not able to exactly pin point what caused issues from my question but in the end I was able to resolve. Follow me there below ...

            Checking out my python.exe files I found 2 paths. First one added as environment variable

            1. C:\Users-----\AppData\Local\Programs\Python\Python310
            2. C:\Users----\AppData\Roaming\Python\Python310\

            Second one not added. Adding roaming version to path variables did not solve the issue and gave additional errors instead: Fatal error in launcher: Unable to create process using '"C:\Program Files\Python310\python.exe"


            1. I uninstalled python (done that before didnt help doing just that alone)

            2. Deleted all environment variables pointing to python (here is what environment variables are just in case -

            3. Uninstalled python extension from VS code (

            4. Deleted Python folders mentioned in the two paths above

            5. Then reinstalled python (clicked add to path during installation)

            6. Reinstalled VS code python extension

            7. Everything works now.

            Best of luck



            Fourier approximation only works in range 0.0–1.0
            Asked 2022-Feb-03 at 14:16

            Im attempting to recreate a fourier approximation for a python function with a given numerical output (without using external libraries), however my function only works in the range of numbers from 0.0 to 1.0. Ive considered simply multiplying any given input larger than 1.0 to a negative power of ten, and then multiplying by the positive power once the result has been held.

            However, as I am limiting myself to not use external libraries (ie something like Decimal or mpmath), I feel as though this solution would not work well given python's limited floating-point precision. I feel as though there's a much less 'hacky' solution to this problem, however I am unable to figure out what such may be.



            Answered 2022-Feb-03 at 14:16

            This code is computing a nice triangular wave (which is in no way restricted to the interval [0, 1]). I limited the number of terms to 5 then to 50 to make the Runge phenomenon clearly visible.

            By the way, the computation is perfectly accurate.



            Why are my decimal places not counting correctly?
            Asked 2022-Jan-27 at 02:06

            I am trying to print pi with a specific number of decimal places based on an input. When I enter 99 decimal places, it prints out 99. When I enter 100 decimal places, it only prints out 99. When I enter 101 decimal places it prints out 101. I want to be able to limit it to 100 decimal places. I am new to python and trying to work an exercise. Here is my code:



            Answered 2022-Jan-27 at 02:06

            The issue is that a value ending in a 0 at the end of the decimals won't print that 0. Compare mp.dps values 32, 33 and 34 (where a 0 occurs naturally in pi). At the position where you're looking at, the value would end in a 9, but since the next digit is >= 5, it rounds to a 0 and doesn't print.

            However, see this:



            HuggingFace - 'optimum' ModuleNotFoundError
            Asked 2022-Jan-11 at 12:49

            I want to run the 3 code snippets from this webpage.

            I've made all 3 one post, as I am assuming it all stems from the same problem of optimum not having been imported correctly?

            Kernel: conda_pytorch_p36




            Answered 2022-Jan-11 at 12:49

            Pointed out by a Contributor of HuggingFace, on this Git Issue,

            The library previously named LPOT has been renamed to Intel Neural Compressor (INC), which resulted in a change in the name of our subpackage from lpot to neural_compressor. The correct way to import would now be from import IncQuantizerForSequenceClassification Concerning the graphcore subpackage, you need to install it first with pip install optimum[graphcore] Furthermore you'll need to have access to an IPU in order to use it.




            ZeroDivisionError: matrix is numerically singular
            Asked 2022-Jan-07 at 12:43

            I'm trying to solve 5 equations with 5 unknowns.



            Answered 2022-Jan-07 at 12:43

            As suggested here, the error got resolved by adding:



            UnsatisfiableError on importing environment pywin32==300 (Requested package -> Available versions)
            Asked 2021-Dec-03 at 14:58

            Good day

            I am getting an error while importing my environment:



            Answered 2021-Dec-03 at 09:22

            Build tags in you environment.yml are quite strict requirements to satisfy and most often not needed. In your case, changing the yml file to



            python interval arithmetic library
            Asked 2021-Nov-09 at 21:19

            I would like to know if there exists a python interval arithmetic library with the following features:

            If x and y are both intervals, eg: [1.2,2.1], [3.8,9.9], then their sum/product/ratio is an interval, and in particular, any real number in the first interval plus/times/over the a real number in the second interval, will be contained in the resulting interval.

            In particular, I would like to know of such a library that does this and accounts for floating point error so that the results can be used in mathematical proofs. I have found some libraries such as this one: that account for error on real numbers, however they don't do so in this stricter sense that I require.

            Thanks to TimPeters for suggesting this library:

            I think this should be the correct tool to use.



            Answered 2021-Nov-09 at 21:19

            As suggested in comments, the OP appeared to be happy with the basic interval arithmetic facilities (binary floating point, with user-settable precision, emulated in software) supplied by the widely used mpmath extension library.


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            You can download it from GitHub.


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