Anton Kratz antonkratz

You might run into a situation where git log, man man display absolutely nothing. This could be b/c bash forgot the PAGER variable. How this is possible is beyond me. You must reset the PAGER variable and then it will work again:

export PAGER=less

Cytoscape 3.7.1

the layout is too dense and I want to expand the layout

Layout --> Node layout Tools --> Scale:

when I zoom out, the text on the label dissappears

Delete all lines in the file myfile that contain the string foobar:

sed -i '/foobar/d' myfile

file1: A list of keys, one key one line

file2: A table, the keys are in column 1

what this does: pull out the lines from the table which match a key from a list

time awk -F'      ' 'NR==FNR{c[$1]++;next};c[$1] > 0' file1 file2 > output.txt

conda adds an uncalled for (base) before my PS1 prompt. Most solutions suggest to edit the .condarc file. This did not work for me. Instead:

conda config --set auto_activate_base False

https://askubuntu.com/questions/1026383/why-does-base-appear-in-front-of-my-terminal-prompt

	# author: Anton Kratz
	# created: Mon Dec 17 19:08:48 PST 2018

	# Based on original code by Mike Yu which is at [1]. However [1] has various NDEX and other
	# code intermingled which is not necessary in this context. Also, I am building a similarity
	# table for DNA repair on the fly.

	# [1] https://github.com/michaelkyu/ddot/blob/master/examples/Process_the_Gene_Ontology.ipynb

	import requests

	Select All
	`Object > Clipping mask > Release`
	`Object > Path > Clean up`

	Clipping masks. Deleting an object deletes random objects scattered throughout b.c they are connected thru the clipping mask. I do not want this.

	import pubchempy as pcp
	import pandas as pd
	import numpy as np
	from collections import OrderedDict

	drugs_df = pd.read_csv('oli_drugs.csv')

	def queryPubChem(compounds,batchlist = None,match='name'):
	"""
	This function queries the PubChem database to retrieve both the isomeric smile and CID of a compound.

	x = c(0.8846, 1.1554, 0.9317, 0.9703, 0.9053, 0.9454, 1.0146, 0.9012, 0.9055, 1.3307)
	y = c(0.9828, 1.0329, 0.931, 1.3794, 0.9273, 0.9605, 1.0259, 0.9542, 0.9717, 0.9357)
	ShortSci = c("MotAlb", "PruMod", "EriRub", "LusMeg", "PhoOch", "PhoPho",
	"SaxRub", "TurMer", "TurPil", "TurPhi")
	df <- data.frame(x = x, y = y, z = ShortSci)

	library(ggplot2)
	library(ggrepel)
	p1 <- ggplot(data = df, aes(x = x, y = y)) + theme_bw() +
	geom_text_repel(aes(label = z),

	#' symlog transformation
	#'
	#' `symlog_trans()` transforms data using `log(x)` for `abs(x) > thr`, where
	#' `thr` is a tuneable threshold, but leaves the data linear for `abs(x) < thr`.
	#' (credit for base code to https://stackoverflow.com/users/1320535/julius-vainora)
	#'
	#'
	#' @param base base of logarithm
	#' @param thr numeric threshold for transitioning from log to linear
	#' @param scale numeric scaling factor for data