wga | Wrapper for generator and async/await to enable them use | Runtime Evironment library
kandi X-RAY | wga Summary
kandi X-RAY | wga Summary
Wrapper for generator and async/await to enable them use in Express or restify
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Top functions reviewed by kandi - BETA
- Wraps fn .
- Wraps a function in a promise .
- Checks if obj is a generator function .
- Check if obj is a generator .
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QUESTION
ANSWER
Answered 2022-Jan-30 at 16:17Hi Muhammad Abdul Faheem,
Try to update podfile by command pod update and delete derived data by following these steps:
1.Open your project,Go to files -> Workspace Settings
Then you will find a derived data location with an arrow:-
Just click on that arrow,after that you will find a folder named derived data, delete all the files inside derived data folder. Then it will working fine.
QUESTION
I have .dat file with this type of text
Example: АqMA ЅA Ђ‰ї HB HB MA @ЅA Е€ї HB HB ЂXLA ЂЅA U‡ї HB HB АFA U5ЅA Е€ї HB HB @ю@A ЅA ё€ї HB HB [VA ЅA ±“‡ї HB HB @3MA ЅA U=‰ї HB HB А KA «JЅA Ђ‰ї HB HB ЂdJA ;1ЅA р‡ї HB HB АZA «jЅA `†ї HB HB АFA ±ЅA Uе†ї HB HB А¬XA ЅA bЗ€ї HB HB АHA OlЅA «2€ї HB HB А5WA UЅA vB‰ї HB HB АN>A ЅA Uu€ї HB HB >FA UuЅA Ы†ї HB HB А^A ±ЅA «2€ї HB HB А”\A UuЅA OL€ї HB HB ЂГOA OlЅA р‡ї HB HB @аEA UЅA Ђ‰ї HB HB @QHA OlЅA р‡ї HB HB АeOA ЅA vB‰ї HB HB цQA ЕNЅA Ђ‰ї HB HB @QHA ЂЅA Ђ‰ї HB HB ,IA ЂЅA Ђ‰ї HB HB @эUA «*ЅA Ђ‰ї HB HB DEA ЕNЅA Ђ‰ї HB HB ЂҐTA ЂЅA Ђ‰ї HB HB АоMA ЂЅA «ъ€ї HB HB @ TA ЂЅA Ђ‰ї HB HB А0CA ЂЅA Ђ‰ї HB HB @KIA ЂЅA Ђ‰ї HB HB ЂXA ЂЅA Ђ‰ї HB HB АYQA «jЅA Ђ‰ї HB HB @жDA ;1ЅA Ђ‰ї HB HB IYA ЂЅA Ђ‰ї HB HB @oCA ЂЅA Ђ‰ї HB HB ЂFOA ЂЅA Ђ‰ї HB HB ТWA Щ ЅA Ђ‰ї HB HB OA UuЅA Ђ‰ї HB HB @WGA etc...
It should be matrix (..., 10) with correct float numbers, but idk how to do it. I tried to find what kind of record it is, but i couldn't find anything same :(
Pls help
ps
in matlab it magicaly works fine, but i really can't do the same in Python
...ANSWER
Answered 2022-Jan-13 at 05:22The data is simply a bunch of floats represented by their actual binary data rather than text. Numpy is probably the fastest and easiest by using:
numpy.fromfile(filepath, dtype=float).reshape([-1,10])
It may be a good exercise to learn how binary data is represented by using the struct
library. Here's a quick example to try and read through:
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