jakevdp

beesandbombs

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

sminot

import os
from functools import lru_cache
from collections import defaultdict

# Read in the taxonomy
class NCBITaxonomy():
    def __init__(self, folder):
        self.tax = defaultdict(dict)
        # Read in the file of taxid information
        names_fp = os.path.join(folder, 'names.dmp')

willmasters

Updated 2025-01-17 thanks to Yemster's comment.

This should work on any architecture of Amazon Linux 2. 
(_Although not tested , should also work for Amazon Linux 2023_).

**Prereq** 
- visit https://johnvansickle.com/ffmpeg/ to grab the link to the relevant tarball for your specific server architecture.
- Use `uname -a` to find out your arch if unknown

### TL;DR

fomightez

# List unique values in a DataFrame column
df['Column Name'].unique() # Note, `NaN` is included as a unique value. If you just want the number, use `nunique()` which stands
# for 'number of unique values';  By default, it excludes `NaN`. `.nunique(dropna=False)` will include `NaN` in the count of unique values.

# To extract a specific column (subset the dataframe), you can use [ ] (brackets) or attribute notation.
df.height
df['height']
# are same thing!!! (from http://www.stephaniehicks.com/learnPython/pages/pandas.html 
# -or-
# http://www.datacarpentry.org/python-ecology-lesson/02-index-slice-subset/)

evanmiltenburg

import matplotlib.pyplot as plt
import seaborn as sns

from matplotlib.lines import Line2D

my_palette = sns.color_palette("cubehelix", 3)
sns.set_palette(my_palette)

def legend_circles(labels, palette, loc=1, markersize=10, marker='o', padding=0):
    "Make a legend where the color is indicated by a circle."

download_kegg.sh

# Get a list of all organisms
curl -s  "http://rest.kegg.jp/list/organism"  > organisms-all.txt

# Get just a few of interest
cat organisms-all.txt | awk '$2~/^(hsa|mmu|rno|cfa|bta|gga|xla|xtr|dre|dme|cel|ath|ehi|tgo|eco|sau|mtu|mav|cje|ccol)$/' > organisms-of-interest.txt

# Get the accession codes for each
cut -f1 organisms-of-interest.txt > organisms-of-interest-codes.txt

# Make a directory to put all the kgml files downloaded

astrojuanlu

fomightez

# These are meant to work in both Python 2 and 3, except where noted.

# See my useful_pandas_snippets.py for those related to dataframes (such as pickling/`df.to_pickle(save_as)`)
# https://gist.github.com/fomightez/ef57387b5d23106fabd4e02dab6819b4
# also see https://gist.github.com/fomightez/324b7446dc08e56c83fa2d7af2b89a33 for examples of my 
# frequently used Python functions and slight variations for more expanded, modular structures.


#argparse
# good snippet collection at https://mkaz.tech/code/python-argparse-cookbook/

thomasp85

library(magick)
library(reshape2)
library(dplyr)
library(tidygraph)
library(particles)
library(animation)

plot_fun <- function(sim) {
  df <- as_tibble(sim)
  plot(df$x, df$y, col = df$color, pch = '.', axes = FALSE, xlim = c(-100, 317), ylim = c(-268, 100), xlab = NA, ylab = NA)