Use of Healpix, camb, CLASS, cosmomc, compilers, etc.
Albin Nilsson
Posts: 13
Joined: October 05 2016
Affiliation: NCBJ, Warsaw

I'm trying to do a generic run to reproduce some standard plots and results. I have not defined any new parameters or changed the code anywhere.
I keep getting the error message: "parameter ranges not found: param1", although I haven't defined param1 at all.
Does anyone have any ideas? See below for my params.ini file:

Code: Select allp>

#Sample parameters for cosmomc used as a generic sampler
#Write your likelihood function in calclike.f90

generic_mcmc=T
parameterization=generic

#Folder where files &#40;chains, checkpoints, etc.&#41; are stored
root_dir = chains/tut/

#Root name for files produced
file_root = tut

#action = 0, to MCMC, action=1, postprocess .data file
action = 0

#You can either use numbered parameters, or, usually better, define a parameter name file as below
num_theory_params = 6
param&#91;omegabh2&#93; = 0.0221 0.005 0.1 0.0001 0.0001
param&#91;omegach2&#93; = 0.12 0.001 0.99 0.001 0.0005
param&#91;theta&#93; = 1.0411 0.5 10 0.0004 0.0002
param&#91;tau&#93; = 0.09 0.01 0.8 0.01 0.005

neutrino_hierarchy = degenerate
num_massive_neutrinos=1
param&#91;mnu&#93; = 0.06
param&#91;meffsterile&#93; = 0

#alternative using parameter names from your generic_example.paramnames file

#Planck 2015 + BAO
#—-highl temp + pol——-#
DEFAULT&#40;batch2/plik_dx11dr2_HM_v18_TTTEEE.ini&#41;
#—-lowl temp + pol——–#
DEFAULT&#40;batch2/lowTEB.ini&#41;
#———BAO—————#
DEFAULT&#40;batch2/BAO.ini&#41;

#General settings
DEFAULT&#40;batch2/common.ini&#41;

#Max samples to get
samples = 100000

#Use vanilla MCMC here since no speed hierarchy defined
sampling_method = 7
use_fast_slow = F

estimate_propose_matrix = F
delta_loglike = 2

propose_scale = 2.4

#Temperature at which to Monte-Carlo
temperature = 1

#Feedback level &#40; 2=lots,1=chatty,0=less,−1=minimal&#41;
feedback = 1

#Can re-start from the last line of previous run &#40;.txt file&#41;
continue_from =

#Increase to oversample fast parameters,e.g. if space is odd shape
oversample_fast = 1

#Can use covariance matrix for proposal density, otherwise use settings below
#Covariance matrix can be produced using "getdist" prorgram.
propose_matrix =

#If action = 1
redo_likelihoods = T
redo_theory = F
redo_cls = F
redo_pk = F
redo_skip = 0
redo_outroot =
redo_thin = 1
#If large difference in log likelihoods may need to offset to give sensible weights
#for exp&#40;difference in likelihoods&#41;
redo_likeoffset =  0

#Number of distinct points to sample
#Every accepted point is included

#number of steps between independent samples
#if non-zero all info is dumped to file file_root.data
#if you change this probably have to change output routines in code too
indep_sample = 0

#number of samples to disgard at start
#May prefer to set to zero and remove later
burn_in = 0

#If zero set automatically

#MPI mode multi-chain options &#40;recommended&#41;
#MPI_Converge_Stop is a &#40;variance of chain means&#41;/&#40;mean of variances&#41; parameter that can be used to stop the chains
#Set to a negative number not to use this feature. Does not guarantee good accuracy of confidence limits.
MPI_Converge_Stop = 0.01
#if MPI_LearnPropose = T, the proposal density is continally updated from the covariance of samples so far &#40;since burn in&#41;
MPI_LearnPropose = T
#Can optionally also check for convergence of confidence limits &#40;after MPI_Converge_Stop  reached&#41;
MPI_Check_Limit_Converge = T

#if MPI_Check_Limit_Converge = T, give tail fraction to check &#40;checks both tails&#41;&#58;
MPI_Limit_Converge = 0.025
#And the permitted percentil chain variance in units of the standard deviation &#40;small values v slow&#41;&#58;
MPI_Limit_Converge_Err = 0.1
#which parameter's tails to check. If zero, check all parameters&#58;
MPI_Limit_Param = 0

#If have covmat, R to reach before updating proposal density &#40;increase if covmat likely to be poor&#41;
#Only used if not varying new parameters that are fixed in covmat
MPI_Max_R_ProposeUpdate = 2
#As above, but used if varying new parameters that were fixed in covmat
MPI_Max_R_ProposeUpdateNew = 30

#if blank this is set from system clock
rand_seed =



Jason Dossett
Posts: 97
Joined: March 19 2010
Affiliation: The University of Texas at Dallas
Contact:

You should not be doing a generic run if you want to reproduce the standard plots.

A generic run will not invoke camb or any of the standard likelihoods at all.

Albin Nilsson
Posts: 13
Joined: October 05 2016
Affiliation: NCBJ, Warsaw

Hi, and thank for replying. By generic run, I mean a standard one. I haven't changed anything, just trying to reproduce some standard results.
Any ideas as to what the problem might be?

Antony Lewis
Posts: 1354
Joined: September 23 2004
Affiliation: University of Sussex
Contact:

### Re: trouble with standard run: \\\"paramranges not foun

Albin Nilsson wrote:Hi, and thank for replying. By generic run, I mean a standard one. I haven't changed anything, just trying to reproduce some standard results.
Any ideas as to what the problem might be?
You have

generic_mcmc=T
parameterization=generic

that are not in the supplied test_planck.ini (which is probably the best starting point for non-grid single Planck-like runs).