nmwsharp

Pretty print tables summarizing properties of tensor arrays in numpy, pytorch, jax, etc.

Now on pip! `pip install arrgh` https://github.com/nmwsharp/arrgh

chrisjurich

def eterna_recalculated(row,scale_max=2.3):
    """Helper method that recalculates the Eterna score for an entry from a dataframe. It will then put the score back into the row. Please note that there is not a 1:1 correspondence between the actual and recalculated scores"""
    assert len(row["target_structure"]) == len(row["sequence"])
    # sometimes there is a fingerprint sequence at the end of the sturcutre, If that is the case it needs to be removed
    sequence = re.sub("AAAGAAACAACAACAACAAC$","",row["sequence"])
    # data_len is the number of data points that will be reviewed
    data_len = min(
            len(row["target_structure"]),
            len(row["SHAPE_data"]), # can probably get rid of this one
            len(sequence),

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

davfre

SAM and BAM filtering one-liners

@author: David Fredman, [email protected] (sans poly-A tail)
@dependencies: http://sourceforge.net/projects/bamtools/ and http://samtools.sourceforge.net/

Please extend with additional/faster/better solutions via a pull request!

BWA mapping (using piping for minimal disk I/O)

mwaskom

cbsmith

// -*- compile-command: "clang++ -ggdb -o random_selection -std=c++0x -stdlib=libc++ random_selection.cpp" -*-
//Reference implementation for doing random number selection from a container.
//Kept for posterity and because I made a surprising number of subtle mistakes on my first attempt.
#include <random>
#include <iterator>

template <typename RandomGenerator = std::default_random_engine>
struct random_selector
{
	//On most platforms, you probably want to use std::random_device("/dev/urandom")()

0

abc	1	2	3
def	4	5	6
ga	7	9	10
hij	1	5	99

werediver

import threading


# Based on tornado.ioloop.IOLoop.instance() approach.
# See https://github.com/facebook/tornado
class SingletonMixin(object):
	__singleton_lock = threading.Lock()
	__singleton_instance = None

	@classmethod

aaronwolen

# Code written by brentp in response to BioStars question:
# http://www.biostars.org/post/show/6544/

import random
import sys

def write_random_records(fqa, fqb, N=100000):
    """ get N random headers from a fastq file without reading the
    whole thing into memory"""
    records = sum(1 for _ in open(fqa)) / 4