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QUESTION
I wish to identify and then create a list in python all stocks (Capitalized Letters) mentioned here..
The problem I have a large text doc with many areas containing 2 3 or 4 Capitalised letters however i only want to get the ones that precede a paragraph ending (stocks-to-watcch are in the following paragraph):
i.e SE, SAM, PYPL, LAD, GLOB .....etc
Not sure if non capturing groups is the way to go or whether I can do look behinds.. if I do non capturing groups to I was thinking something like this would work but it doesn't... any help greatly appreciated
...ANSWER
Answered 2021-Apr-25 at 21:09Extract the substring between two strings:
QUESTION
I am working on a project on Xilinx Vitis that I created a arrayA
with
ANSWER
Answered 2021-Jan-19 at 13:58You can only reinterpret_cast
arrays of char
, signed char
, unsigned char
and std::byte
, and uint8_t
might not be an alias to one of those.
You also need to ensure that the data is properly aligned to treat it as ap_uint<128>
.
QUESTION
I have a table in my database (versions: MariaDB 10.3.17, MySQL 5.7) as follows:
...ANSWER
Answered 2020-Aug-05 at 10:59You need to select elements that have the timestamp value greater than your id timestamp, using a query like this:
QUESTION
I'm trying to run a pytorch script which is using torchaudio on a google TPU. To do this I'm using pytorch xla following this notebook, more specifically I'm using this code cell to load the xla:
...ANSWER
Answered 2020-Mar-30 at 11:01I tested using the notebook below; Getting Started with PyTorch on Cloud TPUs
After changing the cell containing;
FROM:
QUESTION
I have a dictionary file of medical phrases and a corpus of raw texts. I'm trying to use the dictionary file to select the relevant phrases from the text. Phrases, in this case, are 1 to 5-word n-grams. In the end, I would like the selected phrases in a dataframe with two columns: doc_id, phrase
I've been trying to use the quanteda package to do this but haven't been successful. Below is some code to reproduce my latest attempt. I'd appreciate any advice you have...I've tried a variety of methods but keep getting back only single-word matches.
...ANSWER
Answered 2020-Mar-19 at 16:42If you want to match-multi word patterns from a dictionary, you can do so by constructing your dfm
using ngrams.
QUESTION
I have two main scripts for my pyQT5 gui. First the GUI file ("MSCVgui_script") then the run file ("guiRun".py). I when I run my run file the GUI crashes when I modify the variable "self.imageFiles1" in the funciton assingPics.
What I do:
- run "guiRun.py"
- Select "Browse File"
- select folder from the pop up
- Close pop up
- select the check mark blue on the GUI
- Crash-> no error report The photo file paths are"C:\Users.....\Images\photo_Blue.jpg" names are "photo_Blue"
runGui script below
...ANSWER
Answered 2020-Mar-04 at 08:04imag = cv2.imread(imag, 0)
returns a greyscale image so imag.data
will be an ndarray containing height*width
8-bit integers instead of height*width*3
which is what is needed for QtGui.QImage(imag.data, imag.shape[1], imag.shape[0], QtGui.QImage.Format_RGB888)
. To load a color image use imag = cv2.imread(imag, 1)
(or simply imag = cv2.imread(imag)
since flag == 1
is the default).
As an alternative you could just use the file name to initialize the QImage
object instead of constructing an OpenCV
image first.
QUESTION
I have the following code:
...ANSWER
Answered 2020-Feb-05 at 08:25std::tuple
's assignment operators are not constexpr
until c++20. If you avoid assignment operators and construct your tuples in-place then your code compiles:
QUESTION
I am working with multiple files, and multiple training samples in each file. I will use ConcatDataset
as described here:
I need to have negative samples in addition to my true samples, and I need my negative samples to be randomly selected from all the training data files. So, I am wondering, would the returned batch samples just be a random consecutive chuck from a single file, or would be batch span across multiple random indexes across all the datafiles?
If there are more details needed about what I am trying to do exactly, it's because I am trying to train over a TPU with Pytorch XLA.
Normally for negative samples, I would just use a 2nd DataSet
and DataLoader
, however, I am trying to train over TPUs with Pytorch XLA (alpha was just released a few days ago https://github.com/pytorch/xla ), and to do that I need to send my DataLoader
to a torch_xla.distributed.data_parallel.DataParallel
object, like model_parallel(train_loop_fn, train_loader)
which can be seen in these example notebooks
https://github.com/pytorch/xla/blob/master/contrib/colab/resnet18-training-xrt-1-15.ipynb
https://github.com/pytorch/xla/blob/master/contrib/colab/mnist-training-xrt-1-15.ipynb
So, I am now limited to a single DataLoader
, which will need to handle both the true samples, and negative samples that need to be randomly selected from all my files.
ANSWER
Answered 2019-Oct-13 at 20:39ConcatDataset
is a custom class that is subclassed from torch.utils.data.Dataset
. Let's take a look at one example.
QUESTION
My current goal is to display data onto a message box. As this picture shows, the data is all over the place, but if I send it to Excel it looks perfectly fine whereas the message box is just not even.
How can I even out the displayed data on messagebox just to look like the excel?
Here is my code:
...ANSWER
Answered 2019-Oct-08 at 15:22I have good experience using pandas with tabulate and then inserting in Tkinter window with tkinterhtml.
You have "stralign" and "numalign" in tabulate and even "floatfmt" for all sorts of formats and alignment while creating tables.
example for usage:
QUESTION
I'm trying to make a mask from contours.
Here's my full df
Here's a glimpse of first 7 rows
...ANSWER
Answered 2019-Sep-19 at 14:08Solved it, the function I was actually looking for is fillPoly
Replacing this line solves the problem
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