Kyle Barbary kbarbary

## simd-vmv.c
// Doing the operation:
//
//                         | a a a a |  | y |
// x * A * y = [ x x x x ] | a a a a |  | y |
//                         | a a a a |  | y |
//                         | a a a a |  | y |
//
// with SIMD intrinics (specifically AVX).
//
// adapted from https://gist.github.com/rygorous/4172889

## split_jwst_miri_bands.py
# Split MIRI transmissions into separate files. Original file was
# http://ircamera.as.arizona.edu/MIRI/ImPCE_TN-00072-ATC-Iss2.xlsx
# saved as CSV.
import numpy as np

data = np.loadtxt("ImPCE_TN-00072-ATC-Iss2.csv", skiprows=2)

bands = ("F560W F770W F1000W F1280W F1130W F1500W F1800W F2100W F2550W"
         .lower().split())

## cpptest.pyx
"""example of converting a numpy array to a C++ valarray and back in cython
using copies.

Compile with `python setup.py build_ext --inplace`

Example
-------
>>> import cpptest, numpy as np

>>> x = np.array([0., 1., 2.])

## deepnn.py
"""A minimal implementation of a dense neural net with an arbitrary
number of layers, backpropagation, and a few different activation functions."""

import numpy as np

# Activation and cost functions (with gradients)
def sigmoid(x):
    y = 1.0 / (1.0 + np.exp(-x))
    return y, y * (1.0 - y)

## dm15source.py
"""sncosmo Source implementing the "dm15" model from Sako et al (2008).

Example::

    >>> import sncosmo
    >>> import dm15source
    >>> model = sncosmo.Model(source='dm15')
    >>> model.set(z=0.5, t0=55000., amplitude=1e-10, dm15=0.9)
    >>> model.bandmag('sdssi', 'ab', 55011.5)
    24.661108429127694

## animate_source.py
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Animate one or more sncosmo Source spectral time series."""

from __future__ import division

import math

import numpy as np
from astropy.utils.misc import isiterable
from astropy.extern import six

## sample-and-plot.ipynb

      
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                kbarbary
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              Created
              December 9, 2013 22:15
            
              
                sncosmo lightcurve MCMC example
              
          
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## new-models-demo.ipynb

      
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              December 27, 2015 17:39
            
          
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## simulation.py
"""Tools for simulation of transients."""

import sys
import math
from copy import deepcopy

import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline as Spline1d
from astropy.table import Table
from astropy import cosmology

## sncosmo-introduction
{
 "metadata": {
  "name": "Introduction"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
	// Doing the operation:
	//
	// \| a a a a \| \| y \|
	// x * A * y = [ x x x x ] \| a a a a \| \| y \|
	// \| a a a a \| \| y \|
	// \| a a a a \| \| y \|
	//
	// with SIMD intrinics (specifically AVX).
	//
	// adapted from https://gist.github.com/rygorous/4172889
	# Split MIRI transmissions into separate files. Original file was
	# http://ircamera.as.arizona.edu/MIRI/ImPCE_TN-00072-ATC-Iss2.xlsx
	# saved as CSV.
	import numpy as np

	data = np.loadtxt("ImPCE_TN-00072-ATC-Iss2.csv", skiprows=2)

	bands = ("F560W F770W F1000W F1280W F1130W F1500W F1800W F2100W F2550W"
	.lower().split())
	"""example of converting a numpy array to a C++ valarray and back in cython
	using copies.

	Compile with `python setup.py build_ext --inplace`

	Example
	-------
	>>> import cpptest, numpy as np

	>>> x = np.array([0., 1., 2.])
	"""A minimal implementation of a dense neural net with an arbitrary
	number of layers, backpropagation, and a few different activation functions."""

	import numpy as np

	# Activation and cost functions (with gradients)
	def sigmoid(x):
	y = 1.0 / (1.0 + np.exp(-x))
	return y, y * (1.0 - y)
	"""sncosmo Source implementing the "dm15" model from Sako et al (2008).

	Example::

	>>> import sncosmo
	>>> import dm15source
	>>> model = sncosmo.Model(source='dm15')
	>>> model.set(z=0.5, t0=55000., amplitude=1e-10, dm15=0.9)
	>>> model.bandmag('sdssi', 'ab', 55011.5)
	24.661108429127694
	# Licensed under a 3-clause BSD style license - see LICENSE.rst
	"""Animate one or more sncosmo Source spectral time series."""

	from __future__ import division

	import math

	import numpy as np
	from astropy.utils.misc import isiterable
	from astropy.extern import six
	"""Tools for simulation of transients."""

	import sys
	import math
	from copy import deepcopy

	import numpy as np
	from scipy.interpolate import InterpolatedUnivariateSpline as Spline1d
	from astropy.table import Table
	from astropy import cosmology
	{
	"metadata": {
	"name": "Introduction"
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	{