csiborgtools/notebooks/test_mmain.ipynb at 39b3498621038d05364a12741254a2f3654763d6

mirror of https://github.com/Richard-Sti/csiborgtools_public.git synced 2025-07-12 00:53:02 +00:00

Richard Stiskalek fdb0df8d4c

Add mmain and other major updates (#44 )

* Move paths to a separate file

* Add mmain reader

* Add a verbosity flag

* Fix imports

* Fix bug

* Rename files

* Return ultimate parents

* Add script to generate mmain

* Remove mmain path

* edit path

* Add mmain path

* Change function name

* Rename function

* Turn off verbose

* Fix list requirement

* Edit init match paths

* Fix init pathing

* Edit paths docs

* Edit dumpdir name

* Rename path

* Fix split paths

* Remove unused import

* Add comment

* Update readme

* remove read mmain

* Rename haloatalogue

* Fix minor bugs

* Update nbs

* Add create directory option

* Move split jobs

* Move spliot jobs

* Remove splitting

* Add import

* Edit script

* Deeper split folder

* Fix paths bug

* Rename catalogue

* Rename Catalogue

* Add new clumpread

* Edit paths

* add knn paths

* Update commenting

* Update imports

* Add more conversions

* Update temp file

* Add a note

* Add catalogue

* Cooment

* Update TODO

* Update script

* add nb

* Update

* pep8

* edit paths & pep8

* Fix knn auto paths

* add paths docs

* Add auto and cross knn paths

* Add new paths

* Simplify tpcf reading

* pep8 patch

* update readme

* Update progress

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* Pep 8 and restructure

* add lambda spin

* add clump and halo

* add checks

* Edit halo profile fit

* Update gitignore

* backup script

2023-04-18 11:02:36 +02:00

6 KiB

Raw Blame History

In [1]:

import numpy as np
import matplotlib.pyplot as plt
from h5py import File
from scipy.stats import spearmanr

import csiborgtools

%matplotlib inline
%load_ext autoreload
%autoreload 2

In [2]:

paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)

# d = np.load(paths.field_interpolated("SDSS", "csiborg2_main", 16817, "density", "SPH", 1024))

In [33]:

survey = csiborgtools.SDSS()(apply_selection=False)
# survey = csiborgtools.SDSSxALFALFA()(apply_selection=False)

In [35]:

for kind in ["main", "random"]:
    x, smooth = csiborgtools.summary.read_interpolated_field(survey, f"csiborg2_{kind}", "density", "SPH", 1024, paths)
    np .savez(f"../data/{survey.name}_{kind}_density_SPH_1024.npz", val=x, smooth_scales=smooth)

Reading fields:   0%|          | 0/20 [00:00<?, ?it/s]Reading fields: 100%|██████████| 20/20 [00:11<00:00,  1.80it/s]
Reading fields: 100%|██████████| 20/20 [00:10<00:00,  1.86it/s]

In [37]:

Out[37]:

(20, 641409, 5)

In [24]:

np.load("../data/SDSS_main_density_SPH_1024.npz")["val"]

Out[24]:

array([[[nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        ...,
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan]],

       [[nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        ...,
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan]],

       [[nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        ...,
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan]],

       ...,

       [[nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        ...,
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan]],

       [[nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        ...,
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan]],

       [[nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        ...,
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan],
        [nan, nan, nan, nan, nan]]], dtype=float32)

In [ ]:

6 KiB Raw Blame History

6 KiB

Raw Blame History