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import time
import multiprocessing as mp
import gc
#From https://gist.github.com/astrofrog/1453933
import numpy as np
import matplotlib.pyplot as plt
@iancze
iancze / frame.html
Last active August 29, 2015 14:01
Bokeh Embedding
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Test plot</title>
</head>
<body>
<div id="9fe4daf9-51ec-4a04-a625-d9d6c84217a9">
<script
src="static/js/9fe4daf9-51ec-4a04-a625-d9d6c84217a9.js"
@iancze
iancze / arrays.py
Last active August 29, 2015 14:07
Accessing numpy arrays
import numpy as np
rr = np.linspace(0, 20, num=50) #50 elements linearly spaced from 0 to 20
a = 3.0
b = 7.5
w = 2.0
#The functional way
#this np.vectorize decorator is sort of python magic, but allows you
@iancze
iancze / yo.py
Created October 23, 2014 03:11
YOCODEDONE
#!/usr/bin/env python
import yopy #Install with pip install yopy
username = "IANCZE" #Your personal yo account
token = <REDACTED> #Developer API key
yo = yopy.Yo(token=token,user="YOCODEDONE") #(optionally) create a separate account on your DEV page to send the Yo's
yo.yo(username) #send a yo at me, yo
#Usage
#$ python mcmc.py ; ./yo.py
@iancze
iancze / index.jade
Created May 31, 2015 18:33
ERES source
extends ../reveal
block cssstyle
style.
.reveal img.noborder {
border:none;
box-shadow:none;
background:none;
@iancze
iancze / Starfish likelihood function
Created June 1, 2015 18:46
Starfish likelihood function
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Spectroscopic Likelihood Function\n",
"\n",
"by Ian Czekala (`iczekala@cfa.harvard.edu`)\n",
"\n",
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\documentclass{aastex61}
% \documentclass[modern]{aastex61}
\shorttitle{Test AAS Document}
\shortauthors{Czekala et al.}
\begin{document}
\title{Testing}
# based off of DFM's notebook here: https://gist.github.com/dfm/3f746476ac61e142b340ad74c7a1bc75
# imports come from PSOAP, celerite
term1 = terms.Matern32Term(log_sigma=-4.0, log_rho=-22)
term2 = terms.Matern32Term(log_sigma=-6.0, log_rho=-22)
gp1 = celerite.GP(term1)
gp2 = celerite.GP(term2)
@iancze
iancze / stuff_visibilities.py
Created October 11, 2018 17:33
Putting model and residual visibilities back into a CASA measurement set
# presume that we have been modeling some table of visibilities exported by UVPLOT
# : https://github.com/mtazzari/uvplot/blob/master/uvplot/io.py
# we want to put the model and residual visibilties into the CASA MS format so we can CLEAN them to make an image.
# load the model visibilities produced by galario
# assemble them into the right form to go into CASA
# (following UVHDF5: https://github.com/AstroChem/UVHDF5/blob/master/UVHDF5_to_MS.py)
# these would probably be columns of a text file in your case
uu = fid["uu"][:,:] # [kilolam]