Yasir Demirtaş tyasird

local .ssh/config contents

Host juwels
    HostName juwels.fz-juelich.de
    User salaj1
    IdentityFile ~/.ssh/id_rsa_juwels.pub

To connect simply ssh juwels.

juwels

Simulate a scanned PDF with ImageMagick

Download and install Ghostscript and ImageMagick + Convert Module
Execute the following command in the console (change the filename)

$ convert -density 200 INPUT.pdf -rotate 0.3 +noise Multiplicative -format pdf  -quality 85 -compress JPEG -colorspace gray OUTPUT.pdf

Description of the options

-density: set the input DPI to 200
-rotate: set Page rotation to 0.3 degrees

A poker hand consists of 5 cards dealt at random without replacement from a standard deck of 52 cards of which 26 are red and the rest black. A poker hand is dealt. Find the chance that the hand contains three red cards and two black cards.

To achieve it, we use the [hypergeometric][1] probability mass function. We want 3 cards from the set of 26 red cards and 2 from the set of 26. So the parameters for the hypergeometric function are:

M = 52  # Total number of cards
n = 26  # Number of Type I cards (e.g. red cards) 
N = 5   # Number of draws (5 cards dealt in one poker hand)
k = 3   # Number of Type I cards we want in one hand

	// ==UserScript==
	// @name ChatGPT CSS fixes
	// @version 2025-04-24
	// @updateURL https://gist.github.com/alexchexes/d2ff0b9137aa3ac9de8b0448138125ce/raw/chatgpt_ui_fix.user.js
	// @downloadURL https://gist.github.com/alexchexes/d2ff0b9137aa3ac9de8b0448138125ce/raw/chatgpt_ui_fix.user.js
	// @namespace http://tampermonkey.net/
	// @description Adjusts width of side bar and messages of the ChatGPT web interface
	// @author alexchexes
	// @match https://chat.openai.com/*
	// @match https://chatgpt.com/*

	#Rscript normalize_featurecounts.R counts_table.txt tpm ;
	#Rscript normalize_featurecounts.R counts_table.txt rpkm ;

	#Sample table###

	#GeneID<TAB>sample1<TAB>sample2<TAB>sample3<TAB>Length
	#Gene1<TAB>10<TAB>4<TAB>5<TAB>1500
	#Gene2<TAB>20<TAB>43<TAB>60<TAB>4300

	import GEOparse
	import pandas as pd
	import matplotlib.pyplot as plt
	import numpy
	from matplotlib.backends.backend_pdf import PdfPages

	#gseNums = ['GSE14860']
	#gseNums = ['GSE49278', 'GSE19750', 'GSE10846']
	gseNums = ['GSE19417', 'GSE49278', 'GSE19750', 'GSE10846', 'GSE39582', 'GSE35158', 'GSE19422', 'GSE19987', 'GSE32894', 'GSE35158', 'GSE27155', 'GSE33630', 'GSE56303', 'GSE29695', 'GSE10141', 'GSE9843', 'GSE25097', 'GSE32225', 'GSE26566', 'GSE65858', 'GSE39366', 'GSE22138', 'GSE46517', 'GSE71729', 'GSE8607', 'GSE4573', 'GSE29354', 'GSE71118', 'GSE19949', 'GSE15641', 'GSE26253', 'GSE15460', 'GSE21034', 'GSE9891', 'GSE32062', 'GSE72094', 'GSE26939', 'GSE29174', 'GSE31448', 'GSE45725', 'GSE40435', 'GSE14860']

	library(data.table)
	library(foreach)

	args <- commandArgs(TRUE)

	#### Input files ####
	# Series Matrix File
	SERIES_FILE <- args[1]
	# Platform data table obtained from GEO.
	PLATFORM_FILE <- args[2]