taldcroft

import numpy as np
import pywcs
import pyfits

class EventFile(object):
    def __init__(self, filename, hdu=1):
        self.filename= filename
        hdus = pyfits.open(filename)
        self.header = hdus[hdu].header
        self.hdus = hdus

taldcroft

import scipy.spatial
from astropy.table import Table

dat = Table.read('sources_ra_dec_z.fits')

ok = ((dat['z'] > 0)
      & (dat['ra'] > 150.0) & (dat['ra'] < 151.0)
      & (dat['dec'] > 2.0) & (dat['dec'] < 3.0))
datok = dat[ok]

taldcroft

# -*- coding: utf-8 -*-
#
# Eng archive documentation build configuration file, created by
# sphinx-quickstart on Mon Nov 23 22:45:31 2009.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#

taldcroft

"""
Version numbering for this module. The `major`, `minor`, and `bugfix` variables
hold the respective parts of the version number (bugfix is '0' if absent). The
`release` variable is True if this is a release, and False if this is a
development version.

NOTE: this code copied from astropy.version and simplified.  Any license restrictions
therein are applicable.
"""

taldcroft

def get_options():
    parser = argparse.ArgumentParser()
    parser.add_argument("filename",
                      help="Model file")
    parser.add_argument("--days",
                      type=float,
                      default=15,
                      help="Number of days in fit interval (default=90")
    parser.add_argument("--stop",
                      help="Stop time of fit interval (default=model values)")

taldcroft

import asciitable

def structured_array(arr, colnames):
    """Select and possibly re-order columns from a structured array.

    :param arr: numpy structured array
    :param colnames: column names to include
    """
    dtypes = [(x, arr[x].dtype, arr[x].shape[1:]) for x in colnames]
    dat = np.ndarray(len(arr), dtype=dtypes)

taldcroft

"""Provide examples of defining asciitable inconsistent_handler routines to
deal with tables that have rows that are inconsistent with the header
definition.
"""
import asciitable

DEBUG = True


def skip_bad_lines(self, str_vals, ncols):

taldcroft

import numpy as np
import xija
from Chandra.Time import DateTime
from Ska.Matplotlib import plot_cxctime
import Ska.DBI
import Ska.engarchive.fetch_sci as fetch
import matplotlib.pyplot as plt

db = Ska.DBI.DBI(server='sybase', dbi='sybase', user='aca_read')

taldcroft

Main

blah balh

Section

blah blah blah

taldcroft

import numpy as np
from numpy import pi, sin, cos, exp
from scipy.interpolate import interp1d
from multiprocessing import Pool

RAD2ARCSEC = 180. * 3600. / pi  # convert to arcsec for better scale


class CalcScatter(object):