This function works okay for numbers divisible by 3 or 5. However, there is a slight issue with numbers that are divisible by both. Even though you know this, go ahead and start a new chat thread. Then, prompt ChatGPT to write doctest test for the function: You: Write doctest tests ...
stris now written likenumpy.str_instead ofnumpy.bytes_. Complex numbers where the real or imaginary part arenanbut the other part are not are now read correctly as opposed to setting both parts tonan. Fixed bugs in string conversions on Python 2 resulting fromstr.decode()andunicode.encode()...
You can also use it to round numbers: \usepackage{siunitx}%---\sisetup{ round-mode = places, round-precision = 3 }%You can also round numbers, for example\num{1.23456}. Finally, it can help you better align numbers in a table: ...
In both solutions, we achieve the same result of creating a dictionary with the elements fromnumbersas keys and the elements fromlettersas values. However, the example withzip()is more concise and efficient. Most importantly, the solution with the loop is very error-prone. If the two listsnu...
The data type used for image pixel values, stored as a signed 32-bit integer in bytes 13 through 16, is designated by one of the code numbers in the following table. Data TypeNumpy TypeDescription 0NPY_UINT81-byte unsigned integer
Write two numpy arrays to a multi-series TIFF file: Read the second image series from the TIFF file: Successively write the frames of one contiguous series to a TIFF file: >>> data=numpy.random.randint(0,255, (30,301,219),'uint8') >>>withTiffWriter('temp.tif')astif: ...forframe...