astrofrog

$ make html
sphinx-build-2.7 -b html -d _build/doctrees   . _build/html
Making output directory...
Running Sphinx v1.1.2
loading pickled environment... not yet created
loading intersphinx inventory from http://docs.python.org/objects.inv...
loading intersphinx inventory from http://docs.scipy.org/doc/scipy/reference/objects.inv...
loading intersphinx inventory from http://docs.scipy.org/doc/numpy/objects.inv...
loading intersphinx inventory from http://matplotlib.sourceforge.net/objects.inv...
[autosummary] generating autosummary for: ascii/ascii_api.rst, ascii/base_classes.rst, ascii/fixed_width_gallery.rst, ascii/index.rst, ascii/read.rst, ascii/write.rst, configs.rst, development/building_packaging.rst, development/codeguide.rst, development/codeguide_emacs.rst, ..., wcs/api.rst, wcs/api_distortion.rst, wcs/api_sip.rst, wcs/api_units.rst, wcs/api_wcs.rst, wcs/api_wcsprm.rst, wcs/examples.rst, wcs/history.rst, wcs/index.rst, wcs/relax.rst

astrofrog

from astropy.config import messaging

print '=' * 78
print "By default, only messages with level INFO and above are shown:"
print '-' * 78

messaging.debug("Nothing much here")
messaging.info("For information")
messaging.warn("Be careful")
messaging.error("Big time problem!")

astrofrog

import warnings

from astropy.config import logger

print '=' * 78
print "By default, only messages with level INFO and above are shown:"
print '-' * 78

logger.debug("Nothing much here")
logger.info("For information")

astrofrog

import matplotlib.pyplot as plt

import numpy as np

values = np.random.poisson(10., 100)

s = plt.cm.ScalarMappable()
s.set_clim(0., 20.)
s.set_cmap(plt.cm.RdBu)
s.set_array(values)

astrofrog

from scipy.optimize import curve_fit

import numpy as np

# Define images
image1 = np.random.random((100, 200))
image2 = np.random.random((100, 200))
image3 = np.random.random((100, 200))

# Combine into a 3D cube

astrofrog

import numpy as np

def merge_structured_arrays(array1, array2):
    n1 = len(array1)
    n2 = len(array2)
    array_out = array1.copy()
    array_out.resize(n1 + n2)
    array_out[n1:] = array2
    return array_out

astrofrog

# How to interpolate values from scattered points onto a grid

import numpy as np
from scipy.interpolate import Rbf

np.random.seed(2)

# Generate fake data (replace with real data)
N = 10
x = np.random.random(N) * 2. - 1.

astrofrog

import numpy as np

def distance(ra1, dec1, ra2, dec2):
    return np.degrees(np.arccos(np.sin(np.radians(dec1))
                              * np.sin(np.radians(dec2))
                              + np.cos(np.radians(dec1))
                              * np.cos(np.radians(dec2))
                              * np.cos(np.radians(ra1) - np.radians(ra2))))
          
def distance_approx(ra1, dec1, ra2, dec2):

astrofrog

import time
import numpy as np
import photutils
from collections import OrderedDict


c = OrderedDict()

name = "Small data, single small aperture"
c[name] = {}

astrofrog

import cookielib,urllib2,urllib,htmllib,formatter,os,sys
import pyfits
from math import cos,radians
import multiprocessing as mp
import time

class LinksExtractor(htmllib.HTMLParser): # derive new HTML parser

    def __init__(self, formatter) :        # class constructor
        htmllib.HTMLParser.__init__(self, formatter)  # base class constructor