Mercury

Below is my query but when I include my CapturedDateTime and IsOutOfSpec columns then it returns multiple rows but I only want one record to be returned that displays the averages of the last 10 records. So it must return the average PartWeight, average SprueWeight and average Bom Weight for a specified stock code.

Been getting this error when running 'ng build' on my Angular 12.0.2 project

I'm working with Python's Enum classes (in Python 3.9), and trying to combine a couple of things from their documentation. The "Planet" example class demonstrates a tuple (mass,radius) as the value of the enum members, and also setting additional member attributes based on that as the values are passed to an overridden __init__() method. However, the "value" of the enum members winds up being that tuple. The AutoName class shows using the enum.auto() helper function and an overridden _generate_next_value_() method to use the member's name as the value. And in general, overriding the __new__() method seems to be the only way to set the value attribute of a member. I'm having trouble combining these three things.

What I'd like is something like Planet, except where the "value" is changed to "name", as in AutoName(), so that Planet.MERCURY is "MERCURY", not the tuple. But in an override of __new__(), there seems to be no way to know what the "name" of the member being created is, so you can't set "value" to it. And with "auto()", there seems to be no way to provide additional values, like the (mass, radius) info from Planet. I'd hoped to do something like this (assuming the existence of the AutoName class):

I am making a tool which calculates your weight on different planets. I dont' know why but my code is not working. I have attached it. The problem is with the javascript. Someone please help me.

I have put my code here : https://www.w3schools.com/code/tryit.asp?filename=GQKHM7XCL3KM

I am trying to get the second last value in each row of a data frame, meaning the first job a person has had. (Job1_latest is the most recent job and people had a different number of jobs in the past and I want to get the first one). I managed to get the last value per row with the code below:

first_job <- function(x) tail(x[!is.na(x)], 1)

first_job <- apply(data, 1, first_job)

When trying to run my tests in a dual client / server repo, I'm getting the following error that I can't seem to get past.

I am doing a time-series sequence classification problem.

I have 80 time-series all length 1002. Each seq corresponds to 1 of 4 categories (copper, cadmium, lead, mercury). I want to use Keras LSTMs to model this. These models require data to be fed in the form [batches, timesteps, features]. As each seq is independent, the most basic setup is for X_train to have shape [80, 1002, 1]. This works fine in an LSTM (with stateful=False)

But, 1002 is quite a long seq length. A smaller size could perform better.

Let's say I split each seq up into 3 parts of 334. I could continue to use a stateless LSTM. But (I think?) it makes sense to have it be stateful for 3 samples and then reset state (since the 3 chunks are related).

How do I implement this in Keras?

First, I transform the data into shape [240, 334, 1] using a simple X_train.reshape(-1, 334, 1) but how do I maintain the state for 3 samples and then reset the state in model.fit()?

I know I need to call model.reset_states() somewhere but couldn't find any sample code out there showing me how to work it. Do I have to subclass a model? Can I do this using for epoch in range(num_epochs) and GradientTape? What are my options? How can I implement this?

Also, if I split the sequences up, what do I do with the labels? Do I multiply them by the number of chunks each seq is split up into (3 in this case)? Is there a way for an LSTM to ingest 3 samples and then spit out one prediction? Or does each sample have to correspond to a prediction?

Finally, if I split my sequences up into 3 subsequences, do I have to have a batch size of 3? Or can I choose any multiple of 3?

Here is the super basic code I used with X_train.shape == [80, 1002, 1].

I use ggeffects::ggemmeans() to get predictions from models, and I don't know whether I found a bug or otherwise doing things wrong. When using a factor variable as a predictor in the model, the output of ggemmeans() gets messed up when releveling the factor.

Below there are two scenarios, a and b, in which I convert a data column to a factor, then fit a model with lm() and finally calculate predictions with ggemmeans().

I heard that NaN errors are when you are trying to pass an object as a number, yet in my HTML, 'productquantity' is set as a number, so why is it giving me this error? These files operate with another HTML file and another JavaScript file to retrieve data and these 2 display the data. 'productquantity is what is my only hurdle and where the NaN error comes up. If you need the other HTML and Javascript file, please let me know. Thanks in advance!