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CDF for nearest neighbour (#63)

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* Updat ebounds

* fix mistake

* add plot script

* fix which sims

* Add Poisson

* Just docs

* Hide things to __main__

* Rename paths

* Move old script

* Remove radpos

* Paths renaming

* Paths renaming

* Remove trunk stuff

* Add import

* Add nearest neighbour search

* Add Quijote fiducial indices

* Add final snapshot matching

* Add fiducial observer selection

* add boxsizes

* Add reading functions

* Little stuff

* Bring back the fiducial observer

* Add arguments

* Add quijote paths

* Add notes

* Get this running

* Add yaml

* Remove Poisson stuff

* Get the 2PCF script running

* Add not finished htings

* Remove comment

* Verbosity only on 0th rank!

* Update plotting style

* Add nearest neighbour CDF

* Save radial distance too

* Add centres

* Add basic plotting
This commit is contained in:
Richard Stiskalek 2023-05-21 22:46:28 +01:00 • committed by GitHub
parent 369438f881
commit 2185846e90
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34 changed files with 1254 additions and 351 deletions
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12
scripts/match_singlematch.py
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@ -45,12 +45,12 @@ def pair_match(nsim0, nsimx, sigma, smoothen, verbose):
catx = HaloCatalogue(nsimx, paths, load_initial=True, bounds=bounds,
with_lagpatch=True, load_clumps_cat=True)
clumpmap0 = read_h5(paths.particles_path(nsim0))["clumpmap"]
parts0 = read_h5(paths.initmatch_path(nsim0, "particles"))["particles"]
clumpmap0 = read_h5(paths.particles(nsim0))["clumpmap"]
parts0 = read_h5(paths.initmatch(nsim0, "particles"))["particles"]
clid2map0 = {clid: i for i, clid in enumerate(clumpmap0[:, 0])}
clumpmapx = read_h5(paths.particles_path(nsimx))["clumpmap"]
partsx = read_h5(paths.initmatch_path(nsimx, "particles"))["particles"]
clumpmapx = read_h5(paths.particles(nsimx))["clumpmap"]
partsx = read_h5(paths.initmatch(nsimx, "particles"))["particles"]
clid2mapx = {clid: i for i, clid in enumerate(clumpmapx[:, 0])}
# We generate the background density fields. Loads halos's particles one by
@ -77,7 +77,7 @@ def pair_match(nsim0, nsimx, sigma, smoothen, verbose):
for j, match in enumerate(matches):
match_hids[i][j] = catx["index"][match]
fout = paths.overlap_path(nsim0, nsimx, smoothed=False)
fout = paths.overlap(nsim0, nsimx, smoothed=False)
numpy.savez(fout, ref_hids=cat0["index"], match_hids=match_hids,
ngp_overlap=ngp_overlap)
if verbose:
@ -99,7 +99,7 @@ def pair_match(nsim0, nsimx, sigma, smoothen, verbose):
match_indxs, smooth_kwargs,
verbose=verbose)
fout = paths.overlap_path(nsim0, nsimx, smoothed=True)
fout = paths.overlap(nsim0, nsimx, smoothed=True)
numpy.savez(fout, smoothed_overlap=smoothed_overlap, sigma=sigma)
if verbose:
print(f"{datetime.now()}: calculated smoothing, saved to {fout}.",