Stephen J Newhouse snewhouse

## Install MSOffice on Ubuntu.md

      
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                snewhouse
                / Install MSOffice on Ubuntu.md
            
            
              Created
              June 28, 2021 12:48
                — forked from raelgc/Install MSOffice on Ubuntu.md
            
              
                Install MSOffice on Ubuntu
              
          
    Install Microsoft Office 2010 on Ubuntu

Requirements

We'll install MSOffice using the PlayOnLinux wizard. Additionally, MSOffice requires samba and winbind to properly work.
So, if not installed, install them:
sudo apt-get install playonlinux samba winbind


## transform_to_supervised.py
import pandas as pd

def transform_to_supervised(df,
                            previous_steps=1,
                            forecast_steps=1,
                            dropnan=True):

    """
    Transforms a DataFrame containing time series data into a DataFrame
    containing data suitable for use as a supervised learning problem.

## Makefile
# Hello, and welcome to makefile basics.
#
# You will learn why `make` is so great, and why, despite its "weird" syntax,
# it is actually a highly expressive, efficient, and powerful way to build
# programs.
#
# Once you're done here, go to
# http://www.gnu.org/software/make/manual/make.html
# to learn SOOOO much more.

## gist:f852a52d9f311ed07d0f323071db3015

      
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                snewhouse
                / gist:f852a52d9f311ed07d0f323071db3015
            
            
              Created
              May 1, 2017 07:00
                — forked from rxaviers/gist:7360908
            
              
                Complete list of github markdown emoji markup
              
          
    People


 :bowtie:
😄 :smile:
😆 :laughing:


😊 :blush:
😃 :smiley:
☺️ :relaxed:


😏 :smirk:
😍 :heart_eyes:
😘 :kissing_heart:


😚 :kissing_closed_eyes:
😳 :flushed:
😌 :relieved:


😆 :satisfied:
😁 :grin:
😉 :wink:


😜 :stuck_out_tongue_winking_eye:
😝 :stuck_out_tongue_closed_eyes:
😀 :grinning:


😗 :kissing:
😙 :kissing_smiling_eyes:
😛 :stuck_out_tongue:


## bamfilter_oneliners.md

      
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                snewhouse
                / bamfilter_oneliners.md
            
            
              Created
              November 20, 2016 11:11
                — forked from davfre/bamfilter_oneliners.md
            
              
                SAM and BAM filtering oneliners
              
          
    SAM and BAM filtering one-liners
@author: David Fredman, david.fredmanAAAAAA@gmail.com (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)

  
## deinterleave_fastq.sh
#!/bin/bash
# Usage: deinterleave_fastq.sh < interleaved.fastq f.fastq r.fastq [compress]
#
# Deinterleaves a FASTQ file of paired reads into two FASTQ
# files specified on the command line. Optionally GZip compresses the output
# FASTQ files using pigz if the 3rd command line argument is the word "compress"
#
# Can deinterleave 100 million paired reads (200 million total
# reads; a 43Gbyte file), in memory (/dev/shm), in 4m15s (255s)
#

## kmeans.py
import tensorflow as tf
import numpy as np
import time

N=10000
K=4
MAX_ITERS = 1000

start = time.time()
	import pandas as pd

	def transform_to_supervised(df,
	previous_steps=1,
	forecast_steps=1,
	dropnan=True):

	"""
	Transforms a DataFrame containing time series data into a DataFrame
	containing data suitable for use as a supervised learning problem.
	# Hello, and welcome to makefile basics.
	#
	# You will learn why `make` is so great, and why, despite its "weird" syntax,
	# it is actually a highly expressive, efficient, and powerful way to build
	# programs.
	#
	# Once you're done here, go to
	# http://www.gnu.org/software/make/manual/make.html
	# to learn SOOOO much more.
`:bowtie:`	😄 `:smile:`	😆 `:laughing:`
😊 `:blush:`	😃 `:smiley:`	☺️ `:relaxed:`
😏 `:smirk:`	😍 `:heart_eyes:`	😘 `:kissing_heart:`
😚 `:kissing_closed_eyes:`	😳 `:flushed:`	😌 `:relieved:`
😆 `:satisfied:`	😁 `:grin:`	😉 `:wink:`
😜 `:stuck_out_tongue_winking_eye:`	😝 `:stuck_out_tongue_closed_eyes:`	😀 `:grinning:`
😗 `:kissing:`	😙 `:kissing_smiling_eyes:`	😛 `:stuck_out_tongue:`
	#!/bin/bash
	# Usage: deinterleave_fastq.sh < interleaved.fastq f.fastq r.fastq [compress]
	#
	# Deinterleaves a FASTQ file of paired reads into two FASTQ
	# files specified on the command line. Optionally GZip compresses the output
	# FASTQ files using pigz if the 3rd command line argument is the word "compress"
	#
	# Can deinterleave 100 million paired reads (200 million total
	# reads; a 43Gbyte file), in memory (/dev/shm), in 4m15s (255s)
	#
	import tensorflow as tf
	import numpy as np
	import time

	N=10000
	K=4
	MAX_ITERS = 1000

	start = time.time()