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csiborgtools/notebooks/flow/process_PV.ipynb
Richard Stiskalek 779f2e76ac
Calculate upglade redshifts (#128) 
* Update redshift reading

* Add helio to CMB redshift

* Update imports

* Update nb

* Run for Quijote

* Add script

* Update

* Update .gitignore

* Update imports

* Add Peery estimator

* Add bulk flow scripts

* Update typs

* Add comment

* Add blank space

* Update submission script

* Update description

* Add barriers

* Update nb

* Update nb

* Rename script

* Move to old

* Update imports

* Add nb

* Update script

* Fix catalogue key

* Update script

* Update submit

* Update comment

* Update .gitignore

* Update nb

* Update for stationary obsrevers

* Update submission

* Add nb

* Add better verbose control

* Update nb

* Update submit

* Update nb

* Add SN errors

* Add draft of the script

* Update verbosity flags

* Add submission script

* Debug script

* Quickfix

* Remove comment

* Update nb

* Update submission

* Update nb

* Processed UPGLADE
2024-06-20 14:33:00 +01:00

41 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 [ ]: