JohannesBuchner

import warnings
import sys
import astropy.io.fits as pyfits
from astropy.table import Table

print("opening FITS file ...")
f = pyfits.open(sys.argv[1])

print("extensions: ", [e.name for e in f])

JohannesBuchner

from getdist.mcsamples import MCSamples
import getdist.chains

def highest_density_interval_from_samples(xsamples, xlo=None, xhi=None, probability_level=0.68):
    """
    Compute the highest density interval (HDI) from posterior samples.

    Parameters
    ----------
    xsamples : array_like

JohannesBuchner

while true
do 
  rsync -avz ./ user@host:remote/directory/
  inotifywait -r ./
done

JohannesBuchner

def sbpl(x, norm, lam1, lam2, x0, xbrk, Lambda):
    """Smoothly bending powerlaw

    Parameterization from Ryde99
    https://ui.adsabs.harvard.edu/abs/1999ApL%26C..39..281R/abstract

    Parameters
    ----------
    x: array of independent variable
    xmax: only consider x values up to this value

JohannesBuchner

# Help create a pyproject.toml from a setup.py file
# 
# USAGE:
#   1)
#     replace "from [a-z.]* import setup" in your setup.py 
#     with "from convert_setup_py_to_pyproject_toml import setup"
#   2)
#     run the resulting script with python, with this script in the PYTHONPATH
#   
#   The above can be achieved on Linux, for example, with:

JohannesBuchner

"""
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

import matplotlib as mpl
import matplotlib.pyplot as plt

# make a colormap that can be used to look up colors
norm = mpl.colors.Normalize(vmin=0, vmax=3)
zcmap = plt.cm.ScalarMappable(norm=norm, cmap=plt.cm.viridis)

# use it to plot stuff
plt.errorbar(
    x=1, xerr=0.1, y=2, yerr=0.2,

JohannesBuchner

#!/usr/bin/env python3
# 
# SYNOPSIS: stripgif.py input.odp output.odp
# 
# 

import os
import sys
import zipfile
import lxml.etree as ET

JohannesBuchner

import sys, os
import joblib
import subprocess

mem = joblib.Memory('.', verbose=False)
@mem.cache
def run_cmd(args, env):
	process = subprocess.run(args, capture_output=True, text=True)
	return process.stdout, process.stderr, process.returncode

JohannesBuchner

#!/usr/bin/env python3
"""
Manage a group of processes, keeping only N running at a time.

Usage:
  procmanage.py N STRING

Arguments:
  N            An integer representing the number of processes to send the CONT signal to.
  STRING       A string representing the full name to match against.