Logan Whitehouse Lswhiteh

## gist:929045944cf217b06973420af4c49aba
#!/usr/bin/python3
# Takes input from MEA-tools output, sorts into channels by 10 second bins

import os
import numpy as np
import pandas as pd
from collections import Counter

def organizeSpikes(file):
    raw_data = pd.read_csv(file)

## sunbeamlibraryerror.txt
2018-11-27 18:53:57 UTC [     info] Starting Sunbeam installation...
2018-11-27 18:53:57 UTC [     info]     Conda path:   /N/u/lswhiteh/Carbonate/miniconda3
2018-11-27 18:53:57 UTC [     info]     Sunbeam src:  /N/dc2/scratch/lswhiteh/sunbeam-stable
2018-11-27 18:53:57 UTC [     info]     Sunbeam env:  'sunbeam'
2018-11-27 18:54:24 UTC [  warning] Found pre-existing Conda installation in /N/soft/rhel7/anaconda/python3.6/4.3.1.
2018-11-27 18:54:24 UTC [  warning] Ignoring specified Conda path in favor of existing Conda install.
2018-11-27 18:54:24 UTC [     info] Conda already installed.
2018-11-27 18:54:24 UTC [     info] Specified environment already exists (use '--update env' to update)
2018-11-27 18:54:24 UTC [     info] Installing Sunbeam library...
  The scripts sunbeam, sunbeam_init and sunbeam_mod_config are installed in '/N/u/lswhiteh/Carbonate/.local/bin' which is not on PATH.

## final_report.html
<!DOCTYPE html>

<html xmlns="http://www.w3.org/1999/xhtml">

<head>

<meta charset="utf-8" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />

## sunbeampermerror.txt
[lswhiteh@h1 sunbeam-stable]$ mkdir ~/tmp
[lswhiteh@h1 sunbeam-stable]$ TMPDIR=$HOME/tmp ./install.sh -e testsunbeam
2018-11-27 21:04:00 UTC [     info] Starting Sunbeam installation...
2018-11-27 21:04:00 UTC [     info]     Conda path:   /N/u/lswhiteh/Carbonate/miniconda3
2018-11-27 21:04:00 UTC [     info]     Sunbeam src:  /N/dc2/scratch/lswhiteh/sunbeam-stable
2018-11-27 21:04:00 UTC [     info]     Sunbeam env:  'testsunbeam'
2018-11-27 21:04:32 UTC [  warning] Found pre-existing Conda installation in /N/soft/rhel7/anaconda/python3.6/4.3.1.
2018-11-27 21:04:32 UTC [  warning] Ignoring specified Conda path in favor of existing Conda install.
2018-11-27 21:04:32 UTC [     info] Conda already installed.
2018-11-27 21:04:32 UTC [     info] Creating Sunbeam environment...

## Longleaf.txt
*** This is a MUST READ for MASS STORAGE USERS ***


TLDR Version:

·   The hardware underlying Mass Storage (/ms) is being replaced with a new system

·   Data is being migrated from the old to new system

## A simple example: Confusion Matrix with Keras flow_from_directory.py
import numpy as np
from keras import backend as K
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.preprocessing.image import ImageDataGenerator
from sklearn.metrics import classification_report, confusion_matrix

#Start
train_data_path = 'F://data//Train'

## history_saver.sh
#Make a repo called "history_saver", clone it to home dir
#Put this on a crontab job or something (or just manually invoke the script)
#Check your bash settings to make sure history allocation is long enough, sometimes it's truncated
cd ~/history_saver
month_date=$(date +'%Y/%m')
mkdir -p $month_date
today_date=$(date +'%d')
history >> ${month_date}/${today_date}.txt
git add . -A
git commit -m "Updating history for ${month_date}/${today_date}.txt"

## vcf_to_ms.py
from argparse import ArgumentParser
from glob import glob

import allel


def get_ua():
    agp = ArgumentParser(
        description="Utility to convert VCFs to ms-style outputs. Output will be placed in the same location with identical filename as VCF with the `.msOut` suffix."
    )
	#!/usr/bin/python3
	# Takes input from MEA-tools output, sorts into channels by 10 second bins

	import os
	import numpy as np
	import pandas as pd
	from collections import Counter

	def organizeSpikes(file):
	raw_data = pd.read_csv(file)
	2018-11-27 18:53:57 UTC [ info] Starting Sunbeam installation...
	2018-11-27 18:53:57 UTC [ info] Conda path: /N/u/lswhiteh/Carbonate/miniconda3
	2018-11-27 18:53:57 UTC [ info] Sunbeam src: /N/dc2/scratch/lswhiteh/sunbeam-stable
	2018-11-27 18:53:57 UTC [ info] Sunbeam env: 'sunbeam'
	2018-11-27 18:54:24 UTC [ warning] Found pre-existing Conda installation in /N/soft/rhel7/anaconda/python3.6/4.3.1.
	2018-11-27 18:54:24 UTC [ warning] Ignoring specified Conda path in favor of existing Conda install.
	2018-11-27 18:54:24 UTC [ info] Conda already installed.
	2018-11-27 18:54:24 UTC [ info] Specified environment already exists (use '--update env' to update)
	2018-11-27 18:54:24 UTC [ info] Installing Sunbeam library...
	The scripts sunbeam, sunbeam_init and sunbeam_mod_config are installed in '/N/u/lswhiteh/Carbonate/.local/bin' which is not on PATH.
	<!DOCTYPE html>

	<html xmlns="http://www.w3.org/1999/xhtml">

	<head>

	<meta charset="utf-8" />
	<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
	<meta name="generator" content="pandoc" />
	[lswhiteh@h1 sunbeam-stable]$ mkdir ~/tmp
	[lswhiteh@h1 sunbeam-stable]$ TMPDIR=$HOME/tmp ./install.sh -e testsunbeam
	2018-11-27 21:04:00 UTC [ info] Starting Sunbeam installation...
	2018-11-27 21:04:00 UTC [ info] Conda path: /N/u/lswhiteh/Carbonate/miniconda3
	2018-11-27 21:04:00 UTC [ info] Sunbeam src: /N/dc2/scratch/lswhiteh/sunbeam-stable
	2018-11-27 21:04:00 UTC [ info] Sunbeam env: 'testsunbeam'
	2018-11-27 21:04:32 UTC [ warning] Found pre-existing Conda installation in /N/soft/rhel7/anaconda/python3.6/4.3.1.
	2018-11-27 21:04:32 UTC [ warning] Ignoring specified Conda path in favor of existing Conda install.
	2018-11-27 21:04:32 UTC [ info] Conda already installed.
	2018-11-27 21:04:32 UTC [ info] Creating Sunbeam environment...
	* This is a MUST READ for MASS STORAGE USERS *



	TLDR Version:

	· The hardware underlying Mass Storage (/ms) is being replaced with a new system

	· Data is being migrated from the old to new system
	import numpy as np
	from keras import backend as K
	from keras.models import Sequential
	from keras.layers.core import Dense, Dropout, Activation, Flatten
	from keras.layers.convolutional import Convolution2D, MaxPooling2D
	from keras.preprocessing.image import ImageDataGenerator
	from sklearn.metrics import classification_report, confusion_matrix

	#Start
	train_data_path = 'F://data//Train'
	#Make a repo called "history_saver", clone it to home dir
	#Put this on a crontab job or something (or just manually invoke the script)
	#Check your bash settings to make sure history allocation is long enough, sometimes it's truncated
	cd ~/history_saver
	month_date=$(date +'%Y/%m')
	mkdir -p $month_date
	today_date=$(date +'%d')
	history >> ${month_date}/${today_date}.txt
	git add . -A
	git commit -m "Updating history for ${month_date}/${today_date}.txt"
	from argparse import ArgumentParser
	from glob import glob

	import allel


	def get_ua():
	agp = ArgumentParser(
	description="Utility to convert VCFs to ms-style outputs. Output will be placed in the same location with identical filename as VCF with the `.msOut` suffix."
	)