math_utils.py		math_utils.py
	# -*- coding: utf-8 -*-		# -*- coding: utf-8 -*-
	import numpy as np		import numpy as np
	import math		import math
			from scipy import special
	# Mandatory TAU = 6.283185307179586...		# Mandatory TAU = 6.283185307179586...
	math.tau = 2 * math.pi		math.tau = 2 * math.pi
	def merge_where_nan(target, filler):		def merge_where_nan(target, filler):
	"""		"""
	Procedurally mutates target by replacing its nan values by values from filler.		Procedurally mutates target by replacing its nan values by values from filler.
	This is a very simple polyfill for numpy.copyto (for numpy < 1.7).		This is a very simple polyfill for numpy.copyto (for numpy < 1.7).
	"""		"""
	try:		#try:
			# np.copyto(target, filler, where=np.isnan(target))
			#except AttributeError:
			# isnan = np.isnan(target)
			# target[isnan] = filler[isnan]
			if target.size == filler.size:
	np.copyto(target, filler, where=np.isnan(target))		np.copyto(target, filler, where=np.isnan(target))
	except AttributeError:		else:
	isnan = np.isnan(target)		try:
	target[isnan] = filler[isnan]		for k in target.names:
			if k in filler.names:
			target[k] = np.where(np.isnan(target[k]), filler[k], ta
			rget[k])
			except ValueError:
			raise ValueError(" merge failed ")
	def safe_exp(x):		def safe_exp(x):
	"""		"""
	Should not throw during Underflows (and return 0) and Overflows (and re turn inf).		Should not throw during Underflows (and return 0) and Overflows (and re turn inf).
	This code is a hack, and may be cause of future bugs.		This code is a hack, and may be cause of future bugs.
	Oddly enough, it passes a few basic tests in `math_utils_test.py`.		Oddly enough, it passes a few basic tests in `math_utils_test.py`.
	"""		"""
	try:		try:
	a = math.exp(x)		a = math.exp(x)
	except OverflowError:		except OverflowError:
	skipping to change at line 99		skipping to change at line 109
	median = np.median(data)		median = np.median(data)
	sigma = np.std(data)		sigma = np.std(data)
	return median, sigma, iteration		return median, sigma, iteration
	def flux_gaussian(radius, rhwhm):		def flux_gaussian(radius, rhwhm):
	"""		"""
	Disk Gaussian profile with Gaussian thickness		Disk Gaussian profile with Gaussian thickness
	"""		"""
	energy = np.exp(-radius ** 2 / 2. / (2. * rhwhm / 2.35) ** 2) #* np		#energy = np.exp(-radius ** 2 / 2. / (2. * rhwhm / 2.35) ** 2) #* n
	.exp(-nz ** 2 / 2. / hz ** 2)		p.exp(-nz ** 2 / 2. / hz ** 2)
	return energy #DizkModel.flux_sersic(radius, size, 0.5)		return flux_sersic(radius, rhwhm, 0.5)
	def flux_sersic(radius, size, index):		def flux_sersic(radius, size, index, normalize=False):
	"""		"""
	Sersic profile with Gaussian thickness		Sersic profile with Gaussian thickness
	See http://en.wikipedia.org/wiki/Sersic_profile		See http://en.wikipedia.org/wiki/Sersic_profile
	"""		"""
	beta = 1.9992 * index - 0.3271		beta = 1.9992 * index - 0.3271
	energy = np.exp(-beta * (radius / size) ** (1. / index))		energy = np.exp(-beta * ((radius / size) ** (1. / index) -1) )
			if normalize:
			#Graham Driver 2005
			Norm = size**2 * 2 * np.pi * index * np.exp(beta) / beta**(2*in
			dex)
			energy = energy / Norm
	#energy = np.exp(-beta * (radius / size) ** (1. / index)) * np.exp( -nz ** 2 / 2. / hz ** 2)		#energy = np.exp(-beta * (radius / size) ** (1. / index)) * np.exp( -nz ** 2 / 2. / hz ** 2)
	#energy = np.exp(-beta * (radius / size) ** (1. / index)) * np.exp( -np.sqrt(nz ** 2) / hz ) #exponential z-profile		#energy = np.exp(-beta * (radius / size) ** (1. / index)) * np.exp( -np.sqrt(nz ** 2) / hz ) #exponential z-profile
	#energy = np.exp(-beta * (radius / size) ** (1. / index)) * np.cosh (-nz / hz )**(-2.) #sech^2 z-profile		#energy = np.exp(-beta * (radius / size) ** (1. / index)) * np.cosh (-nz / hz )**(-2.) #sech^2 z-profile
	return energy		return energy
	def flux_exponential(radius, size):		def flux_exponential(radius, size):
	"""		"""
	Disk exponential profile with Gaussian thickness		Disk exponential profile with Gaussian thickness
	This is merely a Sérsic profile with index = 1		This is merely a Sérsic profile with index = 1
	"""		"""
	return flux_sersic(radius, size, 1.)		return flux_sersic(radius, size, 1.)
	def flux_de_vaucouleurs(radius, size):		def flux_de_vaucouleurs(radius, size):
	"""		"""
	De Vaucouleurs profile with Gaussian thickness		De Vaucouleurs profile with Gaussian thickness
	See http://en.wikipedia.org/wiki/De_Vaucouleurs%27_law		See http://en.wikipedia.org/wiki/De_Vaucouleurs%27_law
	This is merely a Sérsic profile with index = 4		This is merely a Sérsic profile with index = 4
	"""		"""
	return flux_sersic(radius, size, 4.)		return flux_sersic(radius, size, 4.)
			def Phi_ppf(q, loc=0, scale=1.):
			"""
			normal ppf
			:param q:
			:param loc:
			:param scale:
			:return:
			"""
			#https://stackoverflow.com/questions/38754423/drawing-gaussian-random-v
			ariables-using-scipy-erfinv
			return loc+2**0.5*scale*special.erfinv(2*q-1)
End of changes. 7 change blocks.
	9 lines changed or deleted		26 lines changed or added
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