clintval

$ffmpeg -i in.mov -pix_fmt rgb8 -r 10 output.gif && gifsicle -O3 output.gif -o output.gif

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from typing import Any, Callable, Optional

class wait_callable_true(object):
    """Wait until a callable evaluates to a truthy statement, then continue.
    
    This object can be used as a function or as a context manager.

    Args:
        callable: A function which should eventually return a truthy value.
        call_rate: The rate at which to test the callable, optional.

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import numpy as np
import scipy.stats as stats

__all__ = [
    'gaussian_1d_mixture',
    'gaussian_2d_mixture']


def gaussian_1d_mixture(arr, cov_factor=0.2):
    """A Gaussian kernel density estimation with a tuneable covariance factor.

clintval

from itertools import combinations, product

def hamming_circle(word, n, alphabet):
    """Create all words of hamming distance `n` in a given alphabet from a
    target word.

    Examples
    ---
    >>> sorted(hamming_circle('abc', 0, 'abc'))
    ['abc']

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from cyvcf2 import VCFReader

from snv_spectrum import Snv

reader = VCFReader(str(root / 'all.ann.vcf'))
samples = reader.samples

for variant in reader:
    for sample, depth, alt_depth, gt_base in zip(
        samples,

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#!/bin/bash
#
# drawHelix.sh <input.fa> 
#
# Reads a fasta input file and stream a B-Form DNA
# helix with the sequence to STDOUT
#
##    __     __   __           ___
###  |__) | /  \ /__` \ / |\ |  |   /\  \_/ 
#### |__) | \__/ .__/  |  | \|  |  /~~\ / \ 

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import sys
import threading
import time

# Really though just use a library for this:
#    https://github.com/ManrajGrover/halo
#
class Spinner:
    """https://stackoverflow.com/a/39504463/3727678"""
    busy = False

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# Pipe in the karyotype chromosomes
# Prefix each chromosome name with `chr` if necessary
# Slice the contigs from the source indexed FASTA with samtools
# Output to file

build="${build}"

echo {1..20} X Y M \
  | xargs printf -- 'chr%s ' \
  | xargs samtools faidx "${build}".fa \

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from Bio.Seq import Seq
from Bio.Seq import reverse_complement

dna_bases = ('A', 'C', 'G', 'T')
purines = ('A', 'G')
pyrimidines = ('C', 'T')

transitions = ('A>T', 'C>G', 'G>C', 'T>A')
transversions = ('A>C', 'A>G', 'C>A', 'C>T', 'G>A', 'G>T', 'T>C', 'T>G')

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import re
import csv
import textwrap
import matplotlib.pyplot as plt

from collections import Counter

class ReadError(LookupError):
    """Raise this when a property of a read is called for and no data exists"""
    pass