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# A Ruby implementation of | |
# the Viterbi algorithm based on the hidden Markov model (HMM) | |
# | |
# An original Python code: a Wikipedia page "Viterbi algorithm" at | |
# http://en.wikipedia.org/wiki/Viterbi_algorithm | |
# | |
# Author: MISHIMA, Hiroyuki | |
# | |
require 'pp' |
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iupac = { | |
"A" => ["A"], # Adenine | |
"C" => ["C"], # Cytosine | |
"G" => ["G"], # Guanine | |
"T" => ["T"], # Thymine | |
"R" => ["A", "G"], # puRine | |
"Y" => ["C", "T"], # pYrimidine | |
"S" => ["G", "C"], # Strong | |
"W" => ["A", "T"], # Weak | |
"K" => ["G", "T"], # Keto |
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#!/usr/bin/env ruby | |
# License: the MIT lincense. | |
# Copyright: MISHIMA, Hiroyuki hmishima at nagasaki-u.ac.jp, 2015 | |
require 'rexml/document' | |
class Qstat2 | |
JOBNAME_WIDTH = 65 | |
def initialize |
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#!/bin/bash | |
sel=$(byobu ls | peco | cut -d ":" -f 1) | |
if [ ! -z "${sel}" ] ; then | |
byobu a -t ${sel} | |
fi |
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Sub PhysPosGrouping() | |
Dim oRange As Range | |
Dim lRorB As Long | |
Dim lColR As Long | |
Dim gcount As Long | |
Set oRange = ActiveSheet.UsedRange | |
lRowB = oRange.Row + oRange.Rows.Count - 1 | |
lColR = oRange.Column + oRange.Columns.Count - 1 | |
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#!/usr/bin/env ruby | |
# | |
# Blink all locate LEDs of an SAS-enclosure binded to a block device | |
# Hiroyuki Mishima ([email protected]) | |
# | |
require 'optparse' | |
class BlinkEnclosure | |
PARALLEL = "parallel -j1" |
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#!/usr/bin/env ruby | |
# $ ./klass.rb --hoge=fuga --hoge=puyo --foo=bar | |
# {:h=>false, :hoge=>["fuga", "puyo"] :foo=>["bar"]} | |
require 'optparse' | |
class Klass | |
attr_reader :opts | |
def initialize(opts) |
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#!/usr/bin/env ruby | |
require 'optparse' | |
require 'fileutils' | |
require 'rubyXL' | |
require 'rubyXL/convenience_methods/cell' | |
require 'rubyXL/convenience_methods/color' | |
require 'rubyXL/convenience_methods/font' | |
require 'rubyXL/convenience_methods/workbook' | |
require 'rubyXL/convenience_methods/worksheet' |
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require 'statistics2' | |
def chisq_test(a, b, c, d) | |
total = a + b + c + d | |
row1_total = a + b | |
row2_total = c + d | |
col1_total = a + c | |
col2_total = b + d | |
e_a = (row1_total * col1_total).to_f / total | |
e_b = (row1_total * col2_total).to_f / total |
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##INFO=<ID=BaseQRankSum,Number=1,Type=Float,Description="."> | |
##INFO=<ID=InbreedingCoeff,Number=1,Type=Float,Description="."> | |
##INFO=<ID=ReadPosRankSum,Number=1,Type=Float,Description="."> | |
##INFO=<ID=NEGATIVE_TRAIN_SITE,Number=0,Type=Flag,Description="."> | |
##INFO=<ID=POSITIVE_TRAIN_SITE,Number=0,Type=Flag,Description="."> | |
##INFO=<ID=TOMMO_POSSIBLE_PLATFORM_BIAS_SITE,Number=0,Type=Flag,Description="."> | |
##INFO=<ID=CLNREVSTAT,Number=A,Type=String,Description="."> | |
##INFO=<ID=CLNSIGCONF,Number=A,Type=String,Description="."> | |
##INFO=<ID=CLNDISDBINCL,Number=A,Type=String,Description="."> | |
##INFO=<ID=CLNSIGINCL,Number=A,Type=String,Description="."> |
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