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#Results from heasarc_fermilpsc: Fermi LAT 4-Year Point Source Catalog
#Coordinate system:  Galactic
|name              |_Lii    |_Bii    |flux_1_100_gev|flux_1_100_gev_error|spectral_index|spectral_index_error|detection_significance|assoc_name_1              |lii     |bii     |semi_major_axis_68|semi_minor_axis_68|position_angle_68|semi_major_axis_95|semi_minor_axis_95|position_angle_95|pivot_energy|flux_density|flux_density_error|energy_flux|energy_flux_error|curve_significance|spectrum_type   |beta  |beta_error|cutoff  |cutoff_error|exp_index|exp_index_error|powerlaw_index|flux_30_100_mev|flux_30_100_mev_pos_err|flux_30_100_mev_neg_err|nufnu_30_100_mev|sqrt_ts_30_100_mev|flux_100_300_mev|flux_100_300_mev_pos_err|flux_100_300_mev_neg_err|nufnu_100_300_mev|sqrt_ts_100_300_mev|flux_0p3_1_gev|flux_0p3_1_gev_pos_err|flux_0p3_1_gev_neg_err|nufnu_0p3_1_gev|sqrt_ts_0p3_1_gev|flux_1_3_gev|flux_1_3_gev_pos_err|flux_1_3_gev_neg_err|nufnu_1_3_gev|sqrt_ts_1_3_gev|flux_3_10_gev|flux_3_10_gev_pos_err|flux_3_10_gev_neg_er

smsharma

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#!/usr/bin/env bash

# rmate
# Copyright (C) 2011-2015 by Harald Lapp <[email protected]>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#

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###############################################################################
# run_11bin.py
###############################################################################
#
# Perform scan to obtain best-fit disk and bulge PS population parameters
#
# Here using the 4D efficiency function and the new 11 binning
# 
###############################################################################

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import numpy as np
from astropy.cosmology import Planck15

from units import *

import sys, os
if os.environ['DIFF']: # Whether to use Theano version of lensing gradients
    from profiles_theano import *
else:
    from profiles import *

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import numpy as np
import sys
sys.path.append("../Lensing-PowerSpectra/Simulations/")
from units import *
import theano.tensor as tt

def deflection_sis(x, y, x0=0, y0=0, b=1.5):
    """ Deflection for singular isothermal ellipsoid, from astro-ph/0102341
    """ 
    # Go into shifted coordinats of the potential

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%%cython

import cython
cimport cython

import numpy as np
cimport numpy as np

import warnings

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# define a theano Op for our likelihood function
class LogLikeWithGrad(tt.Op):

    itypes = [tt.dvector] # expects a vector of parameter values when called
    otypes = [tt.dscalar] # outputs a single scalar value (the log likelihood)

    def __init__(self, loglike):
        """
        Initialise with various things that the function requires. Below
        are the things that are needed in this particular example.

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jupyter nbconvert --to rst examples/*.ipynb
rm -r docs/Example*
mv examples/*rst examples/*_files docs/
cd docs/
perl -pi -w -e 's/.. code:: ipython3/.. code:: python/g;' *.rst