C# Nmath to Python SciPy

Hello everyone!

I need to port some functions from C# to Python, but i can't implement next code right:

[SqlFunction(IsDeterministic = true, DataAccess = DataAccessKind.None)]
public static SqlDouble LogNormDist(double probability, double mean, double stddev)
{
    LognormalDistribution lnd = new LognormalDistribution(mean,stddev);
    return (SqlDouble)lnd.CDF(probability);
}

This code uses CenterSpace Nmath library.

Anyone can help me to write a right function in python, which will be similar to this code?

Sorry for my English.

UPD Actually, i don't understand which scipy.stats.lognorm.cdf attrs are simillar to C# probability, mean, stddev

If just copy existing order to python, like in answer below, i get wrong number.

From stackoverflow

• Maybe you can use Python.NET (this is NOT IronPython), it allows to access .NET components and services:

  http://pythonnet.sourceforge.net/

  Josip : I use Python.NET with Python 2.6 (had to build it myself). It's somewhat unstable, lacks .NET 3.0, and it seems the project is inactive for quite some time. I would not recommend it for production code, but it's quite nice to have .NET components handy from Python.

• Scipy has a bunch of distributions defined in the scipy.stats package

  import scipy.stats
  
  def LogNormDist(prob, mean=0, stddev=1):
      return scipy.stats.lognorm.cdf(prob,stddev,mean)
  

  Update

  Okay, it looks like Scipy's stat definitions are a little nonstandard. Here's the end of the docstring for scipy.stats.lognormal

  Lognormal distribution

  lognorm.pdf(x,s) = 1/(s*x*sqrt(2*pi)) * exp(-1/2*(log(x)/s)**2) for x > 0, s > 0.

  If log x is normally distributed with mean mu and variance sigma**2, then x is log-normally distributed with shape paramter sigma and scale parameter exp(mu).

  So maybe try

  return scipy.stats.lognorm.cdf(prob,stddev,scipy.exp(mean))
  

  If that still doesn't work, try getting a few sample points and I'll see if I can find a working relationship.

  Udpate 2

  Oops, I didn't realize that the scale param is a keyword. This one should now work:

  import scipy.stats
  
  def LogNormDist(prob, mean=0, stddev=1):
      return scipy.stats.lognorm.cdf(prob,stddev,scale=scipy.exp(mean))
  

  Cheers and good luck with your project!

  Ivan : Thank you, this is very helpful!

  Ivan : Thanks, but that still doesn't work, so i've run C# code with different attributes and this is what i have: prob | stddev | mean | result 0.3 | 1.0 | 3.2 | 5,31431365968782E-06 0.8 | 2.3 | 7.0 | 0,000843306609677019 0.1 | 0.2 | 0.3 | 0 1 | 4.1 | 6.8 | 0,0486046047161232

  Ivan : Thanks a lot!!!

• The Python docs describe a method random.lognormvariate(mu, sigma):

  http://docs.python.org/library/random.html

  Maybe that's what you want.