[arXiv]
Authors: Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke
We revisit the benchmark after simple traditional algorithms beat deep learning methods in conformation generation.
Data
[arXiv]
Authors: Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke
We revisit the benchmark after simple traditional algorithms beat deep learning methods in conformation generation.
Data
| import numpy as np | |
| import pandas as pd | |
| from matplotlib.figure import Figure | |
| data_url = "https://cdn.jsdelivr.net/gh/holoviz/panel@master/examples/assets/occupancy.csv" | |
| data = pd.read_csv(data_url, parse_dates=["date"]).set_index("date") | |
| primary_color = "#0072B5" | |
| secondary_color = "#94EA84" |
| import ast | |
| import requests | |
| url = 'http://localhost:5006/rest/post_data' | |
| def post(value): | |
| data = {'data': value} | |
| response = requests.post(url, data = data) | |
| if response.status_code==200: | |
| print(ast.literal_eval(response.text)) |
| import pandas as pd | |
| import hvplot.pandas | |
| import panel as pn | |
| pn.extension(sizing_mode="stretch_width") | |
| PALETTE = [ | |
| "#ff6f69", | |
| "#ffcc5c", | |
| "#88d8b0", |
| # From https://stackoverflow.com/a/68876046/1319998, which is itself inspired by https://stackoverflow.com/a/68814418/1319998 | |
| from contextlib import contextmanager | |
| from collections import namedtuple | |
| from ctypes import cdll, byref, string_at, c_char_p, c_int, c_double, c_int64, c_void_p | |
| from ctypes.util import find_library | |
| from sys import platform | |
| def query(db_file, sql, params=()): |
| # WARNING : This gist in the current form is a collection of command examples. Please exercise caution where mentioned. | |
| # Docker | |
| sudo apt-get update | |
| sudo apt-get remove docker docker-engine docker.io | |
| sudo apt install docker.io | |
| sudo systemctl start docker | |
| sudo systemctl enable docker | |
| docker --version |
This is an early draft of this guide, which currently does not include any screenshots. I may be making a lot of assumptions about what you do or do not know in this guide and so I welcome any constructive criticism to help make it more useful. Please feel free to fork this guide and annotate it where it does not work, I would welcome any pull requests to improve this documentation.