Ivan Debono

A notebook of science, thoughts and reason

Category: Python

The APC cluster (3): Montepython with Euclid likelihoods

The latest public release of Montepython includes Euclid likelihoods for the redshift survey (euclid_pk) and the cosmic shear survey (euclid_lensing).

The __init__.py  file needs to be edited because of Python syntax issues. If you try to use it as provided, you will get two errors messages.

File "/home/[APClogin]/montepython/montepython/likelihoods/euclid_pk/__init__.py", line 224, in loglkl
k_sigma = np.zeros(2.*self.nbin+1, 'float64')
TypeError: 'float' object cannot be interpreted as an index

The problem here is the decimal point after the 2, which makes it a float, when it is being used to create an index, which must be an integer.

Correction:
k_sigma = np.zeros(2*self.nbin+1, 'float64')

The second error is caused once again by an unnecessary decimal point in the index:
File "/home/[APClogin]/montepython/montepython/likelihoods/euclid_pk/__init__.py", line 330, in integrand
return self.k_fid[:]**2/(2.*pi)**2*((self.tilde_P_th[:,index_z,index_mu] - self.tilde_P_fid[:,index_z,index_mu])**2/((2./self.V_survey[index_z])*(self.tilde_P_th[:,index_z,index_mu] + self.P_shot[index_z])**2 + (self.alpha[:,2.*index_z+1,index_mu]*self.tilde_P_th[:,index_z,index_mu])**2
*self.k_fid[:]**3/2./pi**2
*self.nbin*log(self.kmax/self.kmin)))
IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indice

Correction:
return self.k_fid[:]**2/(2.*pi)**2*((self.tilde_P_th[:,index_z,index_mu] - self.tilde_P_fid[:,index_z,index_mu])**2/((2/self.V_survey[index_z])*
(self.tilde_P_th[:,index_z,index_mu] + self.P_shot[index_z])**2 + (self.alpha[:,2*index_z+1,index_mu]*self.tilde_P_th[:,index_z,index_mu])**2
*self.k_fid[:]**3/2./pi**2*
self.nbin*log(self.kmax/self.kmin)))

The Champernowne and Copeland-Erdős constants in Python

Python is a great tool. One of the best things about it, as anyone who’s used it will tell you, is the vast collection of useful libraries.

The mathematics libraries include a bewildering array of functions, but they were missing two important ones: the Champernowne constant, and the  Copeland-Erdős constant. So I did my bit for the community and wrote two modules to output these numbers to any desired digit.

David Gawen Champernowne (1912-2000)

Paul Erdős (1913-1996)

Arthur Herbert Copeland (1898-1970)

The modules are included in a package called idmaths, which is available on Github.

Here’s some sample code.

Forecasting an election result

In the run-up to the French presidential election in mid-2017, G. Elliott Morris at The Crosstab published some interesting forecasts using simulated Dirichlet draws. The post in question is no longer online. It was previously available on http://www.thecrosstab.com/2017/02/14/france-2017-methodology .

The method itself is fairly well-known (see e.g. Rigdon et al. 2009, A Bayesian Prediction Model for the U.S. Presidential Election ).

I thought it would be interesting to apply the technique when the poll samples and voter base are both tiny. So I did it for Malta, which held a snap election in June 2017. The main problem here is the inconsistency of the polls. For the last few data points, I used a series of voluntary online surveys carried out by a Facebook group calling themselves MaltaSurvey. In hindsight, the survey results appear to have been biased, but at the time there was no way of knowing how to model this bias.

So, without further ado, here is the link to the code on Github.

 

 

 

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