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@JohannesBuchner
JohannesBuchner / rsync_on_change.sh
Created Dec 15, 2015
rsync loop that updates remote directory when local directory changes (using inotify)
View rsync_on_change.sh
while true
do
rsync -avz ./ user@host:remote/directory/
inotifywait -r ./
done
@JohannesBuchner
JohannesBuchner / rsyncprogress.py
Last active Mar 7, 2019
Progress bar for rsync
View rsyncprogress.py
"""
Progress bar for rsync
========================
Shows file progress and total progress as a progress bar.
Usage
---------
Run rsync with -P and pipe into this program. Example::
@JohannesBuchner
JohannesBuchner / photo-panning-video.diascope
Created Oct 18, 2015
Diascope file to create Ken Burns effects (zoom&pan) and transitions across 5 nice photos.
View photo-panning-video.diascope
format pal quality=1 aspect=4:3 mpeg2sound=ac3 mpeg2=3,192
# later: quality=1 interlaced
set dur=sec
set resize=resize
set title_offset=20%,80% title_area=15%
# http://computoser.com/track/722
# http://computoser.com/track/6340
audio spacy.mp3
#set label=green
@JohannesBuchner
JohannesBuchner / methodchoice.rst
Last active Aug 29, 2015
Method decision tree for parameter estimation and model comparison
View methodchoice.rst

Method decision tree

  • Write down your problem mathematically/statistically; stripping out astronomy-specific details from your model (e.g. pre-compute redshifts, weights, etc.)
  • Ideally, shorten and simplify it down to primitives of math and statistics, which can be implemented in any language.

For the following decision tree, keep in mind that typically, one first thinks

  • I just want to quickly find the best fit on this.
View enumerate-list-demo.rst

Enumerated List Bug Demo

First

  1. foo (should be 1.)
  2. bar (should be 2.)

Second

@JohannesBuchner
JohannesBuchner / statistics-minimal.rst
Last active Jul 31, 2016
ArXiV minimal statistics checklist
View statistics-minimal.rst

ArXiV minimal statistics checklist

This checklist help you identify and fix common errors/misinterpretation in your analysis, or of a paper you are refereeing.

  1. If you use p-values (from a KS test, Pearson correlation, etc.).
  1. What do you think a low p-value says?
  1. You have absolutely disproved the null hypothesis (e.g. "no correlation" is ruled out, the data are not sampled from this model, there is no difference between the population means).
@JohannesBuchner
JohannesBuchner / console-progress.py
Last active Aug 29, 2015
Console progress bar -- takes stdin from arbitrary commands and plots a progress bar
View console-progress.py
"""
SYNOPSIS: ./myprog | python console-progress.py
example for myprog:
#!/bin/bash
echo 100
for i in $(seq 1 100)
do
sleep 1
@JohannesBuchner
JohannesBuchner / pvalue.py
Created Jun 20, 2015
p-value reliability
View pvalue.py
import matplotlib.pyplot as plt
import numpy
import scipy.stats
# http://www.medpagetoday.com/Blogs/TheMethodsMan/52171
def calc_reliability(p, power=0.8, frac_true=0.1):
"""
Given this p-value, power of the test and fraction of hypotheses that
are actually true.
@JohannesBuchner
JohannesBuchner / overlapgauss.py
Created Jun 20, 2015
Probability that two measurements actually have the same value
View overlapgauss.py
import numpy
import matplotlib.pyplot as plt
import scipy.stats
# two gaussian uncertainties with width sigma
# at distance delta
# what is the probability that they actually have the same value?
def compute_bayes(delta, border=5):
a = scipy.stats.norm()
@JohannesBuchner
JohannesBuchner / codememoize.py
Last active Aug 29, 2015
For tests/builds that should only re-run when code or data files have changed (memoized tests)
View codememoize.py
"""
Memoizes a given function, given its code dependencies (loaded modules and
additional data files)
Example::
import douglasadams
def costlyfunction():
# compute answer to the universe and everything
return douglasadams.compute_answer() == 42
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