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csiborgtools/notebooks/diagnostic/powerspectrum_H0.ipynb
Richard Stiskalek ee222cd010
Fix overlap runs (#125) 
* Update nb

* Update script

* Update script

* Rename

* Update script

* Update script

* Remove warning

* Ignore minors when extracting MAH

* Fix paths bug

* Move notebooks

* Move files

* Rename and delete things

* Rename file

* Move file

* Rename things

* Remove old print statement

* Add basic MAH plot

* Add random MAH path

* Output snapshot numbers

* Add MAH random extraction

* Fix redshift bug

* Edit script

* Add extracting random MAH

* Little updates

* Add CB2 redshift

* Add some caching

* Add diagnostic plots

* Add caching

* Minor updates

* Update nb

* Update notebook

* Update script

* Add Sorce randoms

* Add CB2 varysmall

* Update nb

* Update nb

* Update nb

* Use catalogue HMF

* Move definition of radec2galactic

* Update nb

* Update import

* Update import

* Add galatic coords to catalogues

* Update nb
2024-04-08 11:23:21 +02:00

55 KiB
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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 [ ]: