Zhaozhou Li syrte

## sersic_lum.py
from numpy import pi, exp
from scipy.special import gamma, gammaincinv, gammainc

# Normalisation constant
def b(n):
    return gammaincinv(2*n, 0.5)

# Total luminosity of a 2D Sérsic profile
def sersic_total_lum(Ie, re, n):
    bn = b(n)

## apj_short_prop.bst
%%This is often best used in a latex file in two-column mode.  To do that, do:
%%
%%\usepackage{multicol}  % before \begin{document}
%% ... document ...
%%\begin{multicols}{2}
%%\bibliography{filename}{}
%%\bibliographystyle{apj_short_prop}
%%\end{multicols}


## gpy_kernel_cheatsheet.py
%pylab inline
import numpy as np
import pylab as plt
import GPy
import re

def get_equation(kern):
    match = re.search(r'(math::)(\r\n|\r|\n)*(?P<equation>.*)(\r\n|\r|\n)*', kern.__doc__)
    return '' if match is None else match.group('equation').strip()

## weighted_kde.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                syrte
                / weighted_kde.ipynb
            
            
              Created
              May 9, 2019 12:12
                — forked from tillahoffmann/weighted_kde.ipynb
            
              
                Weighted kernel density estimation based on `scipy.stats.gaussian_kde`.
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
	from numpy import pi, exp
	from scipy.special import gamma, gammaincinv, gammainc

	# Normalisation constant
	def b(n):
	return gammaincinv(2*n, 0.5)

	# Total luminosity of a 2D Sérsic profile
	def sersic_total_lum(Ie, re, n):
	bn = b(n)
	%%This is often best used in a latex file in two-column mode. To do that, do:
	%%
	%%\usepackage{multicol} % before \begin{document}
	%% ... document ...
	%%\begin{multicols}{2}
	%%\bibliography{filename}{}
	%%\bibliographystyle{apj_short_prop}
	%%\end{multicols}
	%pylab inline
	import numpy as np
	import pylab as plt
	import GPy
	import re

	def get_equation(kern):
	match = re.search(r'(math::)(\r\n\|\r\|\n)(?P<equation>.)(\r\n\|\r\|\n)*', kern.__doc__)
	return '' if match is None else match.group('equation').strip()