Wednesday, December 8, 2010

Trimming Reconstruction

When looking over my xi and wps matrices used in the reconstruction, Alexia noticed that some fo the numbers were all over the place. She suggested changing the range of the correlation functions I use to those which have enough data to have reasonable number. So I spent yesterday creating the following code to "trim" the matrices to whatever ranges the user wants. Here is how it works:

The wpsMat is a concatenation of all the wps(r,theta) correlation functions at the different redshift (r) bins. However, sometimes there aren't enough objects at certain redshift bins, so the values in wps for that bin are nonsensical. Likewise there might angles (theta) that are too big or small. The followincg code allows you to decide how many of the r and theta bins to skip from the start and end of the data set:

skipStartR = 2 # number of r bins to skip at start
skipEndR = 1 # number of r bins to skip at end
skipR = skipStartR + skipEndR #total r bins skiped
skipStartT = 0 # number of theta bins to skip at start
skipEndT = 0 # number of theta bings to skip at end
#Make matrix with skipping:
makeWPSmatrix4(workingDir,rbins, corrBins, wpsMatrixFile, skipStartR, skipEndR, skipStartT, skipEndT)

Similarly, we can want to skip the same r bins in the xi matrix, and also we can skip bins along the line of sight (l):

#Create a matrix to input the correlation function data
# Write Xi Matrix to file
skipStartL = 0 # number of line of sight bins to skip at start
skipEndL = 0 # number of line of sight bins to skip at end
makeXimatrix4(workingDir,rbins,nxicorr,xiMatrixFile, skipStartR, skipEndR, skipStartL, skipEndL)

This doesn't appear to be helping the reconstruction. Here is reconstruction without trimming:

Reconstruction without trimming

Construction with trimming:

The code to make these plots is here: ../logs/101208log.py

2 comments:

  1. Jess. Why is the truth changing in the middle redshifts, shouldn't the blue curves look kinda the same (minus some points on the ends)?

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  2. The blue is the same data in both, but the histogram binning changes due to there being less reconstruction bins in the trimmed set.

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