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import lineax as lx
import jax.numpy as jnp
import jax
from jaxtyping import Float, Array


class CubicSpline:
    x_grid: Float[Array, str("batch")]  # input x data
    y_grid: Float[Array, str("n")]  # input y data

iphysresearch

gist - Manage your gist like a pro

All your notes, scripts, config files and snippets deserve version control and tagging!
gist is a simple bash script for gist management. It is lightweight(~700LOC) and dependency-free! Helps you to boost coding workflow.

• Getting Started
• Dependencies
• Basic Commands
• Update and clone gists from Github

iphysresearch

How to organize your Python data science project

Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.

Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.

Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!

Disclaimer 3: I found the Cookiecutter Data Science page after finishing this blog post. Many ideas overlap here, though some directories are irrelevant in my work -- which is to

iphysresearch

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O  输入训练数据
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)  # 字符数目和单词数目