gamma

I have created a class for word2vec vectorisation which is working fine. But when I create a model pickle file and use that pickle file in a Flask App, I am getting an error like:

AttributeError: module '__main__' has no attribute 'GensimWord2VecVectorizer'

I am creating the model on Google Colab.

Code in Jupyter Notebook:

I am using the functions defined here: Extreme value analysis and user defined probability functions in Stan for modeling the data with a generalized pareto distribution, but my problem is that my model is in a for-loop and expects three real valued arguments, whereas, the gpd functions assume a vector, real, real argument.

I’m not so sure that my model chunk is so amenable to being vectorized, and so I was thinking I would need to have the gpd functions take in real valued arguments (but maybe I’m wrong).

I’d appreciate any help with switching the code around to achieve this. Here is my stan code

I have a dataset that contains information about patients. It includes several variables and their clinical status (0 if they are healthy, 1 if they are sick). I have tried to implement an SVM model to predict patient status based on these variables.

I've been working on python to make a program which need to handle complex problem from list of dict. The thing is I need to transform this data into dictionary and sort it. The input for this function is come from trees. The code I share here is working, but takes a long time to run. In here I wanna ask is there any idea to make this function run more faster in python? I use python 3.7.3 if you ask. The reason I wanna improve this code is because when I tried to make input data for this function need around 3-4 hours, but to run this function need time around 21-22 hours (this really shock me).

here is the structure of data that I input on below:

I'm having trouble understanding an error message I'm getting from my GEKKO model.

For context, this model is supposed to optimize the gas spring force and dimension parameters of a gas-spring assisted door to minimize the operator force required to close the door. My intent is to calculate the required force at a series of angles between 0 and 90 degrees, then sum the absolute value of the force at all angles and minimize that value. There is also a constraint on the gas spring length so the optimization doesn't come up with unrealistic dimension parameters. I've defined the force and other values that need to be computed at each angle as lists of Intermediate variables.

The error appears to be related to one of these lists of Intermediate variables, but I don't know how to interpret "Position: 2" in the error message, let alone "Error in syntax of function string". I've searched in some other answers on here, but I haven't found a clear answer on how to use this position information to troubleshoot the model. What is the message trying to tell me?

I am new to stackoverflow and also quite new to Python. So, I hope to ask my question in an appropriate manner. I am running a Python code similar to this minimal example with an example function that is a product of a lorentzian with a cosinus that I want to numerically integrate:

Ownership Tree

Hi,

I was trying to understand ownership concepts in Rust and came across this image (attached in this post) in "Programming Rust" book.

In particular am concerned about the "Borrowing a shared reference" part. In the book, the author says

Values borrowed by shared references are read-only. Across the lifetime of a shared reference, neither its referent, nor anything reachable from that referent, can be changed by anything. There exist no live mutable references to anything in that structure, its owner is held read-only, and so on. It’s really frozen

In the image, he goes on to highlight the path along the ownership tree that becomes immutable once a shared reference is taken to a particular section of the ownership tree. But what confused me is that the author also mentions that certain other parts of the ownership tree are not read only.

So I tried to test out with this code:

I couldn't find a question similar to the one that I have here. I have a very large named list of named vectors that match column names in a dataframe. I would like to use the list of named vectors to replace values in the dataframe columns that match each list element's name. That is, the name of the vector in the list matches the name of the dataframe column and the key-value pair in each vector element will be used to recode the column.

Reprex below:

I have a joint probability density f(x,y,z) and I wish to find the conditional distribution X|Y=y,Z=z, which is equivalent to treating x as data and y and z as parameters (constants).

For example, if I have X|Y=y,Z=z being the pdf of a N(1-2y,3z^2+2), the function would be: