mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-22 17:38:02 +00:00
32e36afdc3
* Add submit script * Add support for gadget2 * Add OMP * Lower resolution * Update resolution again * Add selection on galactic latitude * Update name * Update nb * Update nb * Add CLONES params * Add import * Add CLONES path * Add CLONES reader * Quick fix * Add CLONES * Update slice nb * Update nb * Update nb * Tiny updates * Update nb * Add name * Add CLONES support * Add CF4 field * Add CLONES * Update script * Update nb * Update nb
344 lines
13 KiB
Python
344 lines
13 KiB
Python
# Copyright (C) 2024 Richard Stiskalek
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 3 of the License, or (at your
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# option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
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# Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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"""Script to help with plots in `flow_calibration.ipynb`."""
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from copy import copy, deepcopy
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import numpy as np
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from jax import numpy as jnp
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from getdist import MCSamples
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from h5py import File
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import csiborgtools
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###############################################################################
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# Convert between coordinate systems #
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###############################################################################
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def cartesian_to_radec(x, y, z):
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d = (x**2 + y**2 + z**2)**0.5
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dec = np.arcsin(z / d)
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ra = np.arctan2(y, x)
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ra[ra < 0] += 2 * np.pi
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ra *= 180 / np.pi
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dec *= 180 / np.pi
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return d, ra, dec
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###############################################################################
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# Convert names to LaTeX #
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###############################################################################
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def names_to_latex(names, for_corner=False):
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"""Convert the names of the parameters to LaTeX."""
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ltx = {"alpha": "\\alpha",
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"beta": "\\beta",
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"Vmag": "V_{\\rm ext} ~ [\\mathrm{km} / \\mathrm{s}]",
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"Vx": "V_x ~ [\\mathrm{km} / \\mathrm{s}]",
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"Vy": "V_y ~ [\\mathrm{km} / \\mathrm{s}]",
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"Vz": "V_z ~ [\\mathrm{km} / \\mathrm{s}]",
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"sigma_v": "\\sigma_v ~ [\\mathrm{km} / \\mathrm{s}]",
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"alpha_cal": "\\mathcal{A}",
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"beta_cal": "\\mathcal{B}",
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"mag_cal": "\\mathcal{M}",
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"l": "\\ell ~ [\\mathrm{deg}]",
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"b": "b ~ [\\mathrm{deg}]",
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}
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ltx_corner = {"alpha": r"$\alpha$",
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"beta": r"$\beta$",
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"Vmag": r"$V_{\rm ext}$",
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"l": r"$\ell$",
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"b": r"$b$",
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"sigma_v": r"$\sigma_v$",
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"alpha_cal": r"$\mathcal{A}$",
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"beta_cal": r"$\mathcal{B}$",
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"mag_cal": r"$\mathcal{M}$",
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}
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names = copy(names)
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for i, name in enumerate(names):
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if "SFI_gals" in name:
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names[i] = names[i].replace("SFI_gals", "SFI")
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if "CF4_GroupAll" in name:
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names[i] = names[i].replace("CF4_GroupAll", "CF4Group")
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if "CF4_TFR_i" in name:
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names[i] = names[i].replace("CF4_TFR_i", "CF4,TFR")
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for cat in ["2MTF", "SFI", "CF4,TFR"]:
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ltx[f"a_{cat}"] = f"a_{{\\rm TF}}^{{\\rm {cat}}}"
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ltx[f"b_{cat}"] = f"b_{{\\rm TF}}^{{\\rm {cat}}}"
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ltx[f"c_{cat}"] = f"c_{{\\rm TF}}^{{\\rm {cat}}}"
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ltx[f"corr_mag_eta_{cat}"] = f"\\rho_{{m,\\eta}}^{{\\rm {cat}}}"
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ltx[f"eta_mean_{cat}"] = f"\\widehat{{\\eta}}^{{\\rm {cat}}}"
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ltx[f"eta_std_{cat}"] = f"\\widehat{{\\sigma}}_\\eta^{{\\rm {cat}}}"
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ltx[f"mag_mean_{cat}"] = f"\\widehat{{m}}^{{\\rm {cat}}}"
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ltx[f"mag_std_{cat}"] = f"\\widehat{{\\sigma}}_m^{{\\rm {cat}}}"
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ltx_corner[f"a_{cat}"] = rf"$a_{{\rm TF}}^{{\rm {cat}}}$"
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ltx_corner[f"b_{cat}"] = rf"$b_{{\rm TF}}^{{\rm {cat}}}$"
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ltx_corner[f"c_{cat}"] = rf"$c_{{\rm TF}}^{{\rm {cat}}}$"
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ltx_corner[f"corr_mag_eta_{cat}"] = rf"$\rho_{{m,\eta}}^{{\rm {cat}}}$"
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ltx_corner[f"eta_mean_{cat}"] = rf"$\widehat{{\eta}}^{{\rm {cat}}}$"
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ltx_corner[f"eta_std_{cat}"] = rf"$\widehat{{\sigma}}_\eta^{{\rm {cat}}}$" # noqa
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ltx_corner[f"mag_mean_{cat}"] = rf"$\widehat{{m}}^{{\rm {cat}}}$"
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ltx_corner[f"mag_std_{cat}"] = rf"$\widehat{{\sigma}}_m^{{\rm {cat}}}$"
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for cat in ["2MTF", "SFI", "Foundation", "LOSS", "CF4Group", "CF4,TFR"]:
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ltx[f"alpha_{cat}"] = f"\\alpha^{{\\rm {cat}}}"
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ltx[f"e_mu_{cat}"] = f"\\sigma_{{\\mu}}^{{\\rm {cat}}}"
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ltx[f"a_dipole_mag_{cat}"] = f"\\epsilon_{{\\rm mag}}^{{\\rm {cat}}}"
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ltx[f"a_dipole_l_{cat}"] = f"\\epsilon_{{\\ell}}^{{\\rm {cat}}} ~ [\\mathrm{{deg}}]" # noqa
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ltx[f"a_dipole_b_{cat}"] = f"\\epsilon_{{b}}^{{\\rm {cat}}} ~ [\\mathrm{{deg}}]" # noqa
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ltx["a_dipole_mag"] = "\\epsilon_{{\\rm mag}}"
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ltx["a_dipole_l"] = "\\epsilon_{{\\ell}} ~ [\\mathrm{{deg}}]"
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ltx["a_dipole_b"] = "\\epsilon_{{b}} ~ [\\mathrm{{deg}}]"
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ltx_corner[f"alpha_{cat}"] = rf"$\alpha^{{\rm {cat}}}$"
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ltx_corner[f"e_mu_{cat}"] = rf"$\sigma_{{\mu}}^{{\rm {cat}}}$"
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ltx_corner[f"a_dipole_mag_{cat}"] = rf"$\epsilon_{{\rm mag}}^{{\rm {cat}}}$" # noqa
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ltx_corner[f"a_dipole_l_{cat}"] = rf"$\epsilon_{{\ell}}^{{\rm {cat}}}$"
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ltx_corner[f"a_dipole_b_{cat}"] = rf"$\epsilon_{{b}}^{{\rm {cat}}}$"
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for cat in ["Foundation", "LOSS"]:
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ltx[f"alpha_cal_{cat}"] = f"\\mathcal{{A}}^{{\\rm {cat}}}"
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ltx[f"beta_cal_{cat}"] = f"\\mathcal{{B}}^{{\\rm {cat}}}"
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ltx[f"mag_cal_{cat}"] = f"\\mathcal{{M}}^{{\\rm {cat}}}"
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ltx_corner[f"alpha_cal_{cat}"] = rf"$\mathcal{{A}}^{{\rm {cat}}}$"
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ltx_corner[f"beta_cal_{cat}"] = rf"$\mathcal{{B}}^{{\rm {cat}}}$"
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ltx_corner[f"mag_cal_{cat}"] = rf"$\mathcal{{M}}^{{\rm {cat}}}$"
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for cat in ["CF4Group"]:
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ltx[f"dmu_{cat}"] = f"\\Delta\\mu^{{\\rm {cat}}}"
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ltx[f"dmu_dipole_mag_{cat}"] = f"\\epsilon_\\mu_{{\\rm mag}}^{{\\rm {cat}}}" # noqa
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ltx[f"dmu_dipole_l_{cat}"] = f"\\epsilon_\\mu_{{\\ell}}^{{\\rm {cat}}} ~ [\\mathrm{{deg}}]" # noqa
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ltx[f"dmu_dipole_b_{cat}"] = f"\\epsilon_\\mu_{{b}}^{{\\rm {cat}}} ~ [\\mathrm{{deg}}]" # noqa
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ltx_corner[f"dmu_{cat}"] = rf"$\Delta\mu_{{0}}^{{\rm {cat}}}$"
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ltx_corner[f"dmu_dipole_mag_{cat}"] = rf"$\epsilon_{{\rm mag}}^{{\rm {cat}}}$" # noqa
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ltx_corner[f"dmu_dipole_l_{cat}"] = rf"$\epsilon_{{\ell}}^{{\rm {cat}}}$" # noqa
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ltx_corner[f"dmu_dipole_b_{cat}"] = rf"$\epsilon_{{b}}^{{\rm {cat}}}$" # noqa
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labels = copy(names)
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for i, label in enumerate(names):
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if for_corner:
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labels[i] = ltx_corner[label] if label in ltx_corner else label
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else:
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labels[i] = ltx[label] if label in ltx else label
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return labels
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def simname_to_pretty(simname):
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ltx = {"Carrick2015": "Carrick+15",
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"Lilow2024": "Lilow+24",
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"csiborg1": "CB1",
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"csiborg2_main": "CB2",
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"csiborg2X": "Manticore",
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"CF4": "Courtois+23",
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"CF4gp": "CF4group",
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"CLONES": "Sorce+2018",
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}
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if isinstance(simname, list):
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names = [ltx[s] if s in ltx else s for s in simname]
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return "".join([f"{n}, " for n in names]).rstrip(", ")
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return ltx[simname] if simname in ltx else simname
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def catalogue_to_pretty(catalogue):
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ltx = {"SFI_gals": "SFI",
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"CF4_TFR_not2MTForSFI_i": r"CF4 $i$-band",
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"CF4_TFR_i": r"CF4 TFR $i$",
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"CF4_TFR_w1": r"CF4 TFR W1",
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}
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if isinstance(catalogue, list):
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names = [ltx[s] if s in ltx else s for s in catalogue]
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return "".join([f"{n}, " for n in names]).rstrip(", ")
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return ltx[catalogue] if catalogue in ltx else catalogue
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###############################################################################
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# Read in goodness-of-fit #
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###############################################################################
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def get_gof(kind, fname):
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"""Read in the goodness-of-fit statistics `kind`."""
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if kind not in ["BIC", "AIC", "neg_lnZ_harmonic"]:
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raise ValueError("`kind` must be one of 'BIC', 'AIC', 'neg_lnZ_harmonic'.") # noqa
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with File(fname, 'r') as f:
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return f[f"gof/{kind}"][()]
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###############################################################################
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# Read in samples #
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###############################################################################
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def get_samples(fname, convert_Vext_to_galactic=True):
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"""Read in the samples from the HDF5 file."""
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samples = {}
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with File(fname, 'r') as f:
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grp = f["samples"]
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for key in grp.keys():
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samples[key] = grp[key][...]
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if convert_Vext_to_galactic:
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Vext = samples.pop("Vext")
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samples["Vmag"] = np.linalg.norm(Vext, axis=1)
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Vext = csiborgtools.cartesian_to_radec(Vext)
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samples["l"], samples["b"] = csiborgtools.radec_to_galactic(
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Vext[:, 1], Vext[:, 2])
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else:
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Vext = samples.pop("Vext")
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samples["Vx"] = Vext[:, 0]
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samples["Vy"] = Vext[:, 1]
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samples["Vz"] = Vext[:, 2]
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keys = list(samples.keys())
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for key in keys:
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if "dmu_dipole_" in key:
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dmu = samples.pop(key)
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dmu = csiborgtools.cartesian_to_radec(dmu)
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dmu_mag = dmu[:, 0]
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l, b = csiborgtools.radec_to_galactic(dmu[:, 1], dmu[:, 2])
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samples[key.replace("dmu_dipole_", "dmu_dipole_mag_")] = dmu_mag
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samples[key.replace("dmu_dipole_", "dmu_dipole_l_")] = l
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samples[key.replace("dmu_dipole_", "dmu_dipole_b_")] = b
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if "a_dipole" in key:
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adipole = samples.pop(key)
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adipole = csiborgtools.cartesian_to_radec(adipole)
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adipole_mag = adipole[:, 0]
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l, b = csiborgtools.radec_to_galactic(adipole[:, 1], adipole[:, 2])
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samples[key.replace("a_dipole", "a_dipole_mag")] = adipole_mag
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samples[key.replace("a_dipole", "a_dipole_l")] = l
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samples[key.replace("a_dipole", "a_dipole_b")] = b
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return samples
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###############################################################################
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# Bulk flow plotting #
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###############################################################################
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def get_bulkflow_simulation(simname, convert_to_galactic=True):
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f = np.load(f"/mnt/extraspace/rstiskalek/csiborg_postprocessing/field_shells/enclosed_mass_{simname}.npz") # noqa
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r, B = f["distances"], f["cumulative_velocity"]
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if convert_to_galactic:
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Bmag, Bl, Bb = cartesian_to_radec(B[..., 0], B[..., 1], B[..., 2])
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Bl, Bb = csiborgtools.radec_to_galactic(Bl, Bb)
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B = np.stack([Bmag, Bl, Bb], axis=-1)
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return r, B
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def get_bulkflow(fname, simname, convert_to_galactic=True, downsample=1,
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Rmax=125):
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# Read in the samples
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with File(fname, "r") as f:
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Vext = f["samples/Vext"][...]
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try:
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beta = f["samples/beta"][...]
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except KeyError:
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beta = jnp.ones(len(Vext))
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# Read in the bulk flow
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f = np.load(f"/mnt/extraspace/rstiskalek/csiborg_postprocessing/field_shells/enclosed_mass_{simname}.npz") # noqa
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r = f["distances"]
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# Shape of B_i is (nsims, nradial)
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Bx, By, Bz = (f["cumulative_velocity"][..., i] for i in range(3))
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# Mask out the unconstrained large scales
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Rmax = Rmax # Mpc/h
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mask = r < Rmax
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r = r[mask]
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Bx = Bx[:, mask]
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By = By[:, mask]
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Bz = Bz[:, mask]
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Vext = Vext[::downsample]
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beta = beta[::downsample]
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# Multiply the simulation velocities by beta.
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Bx = Bx[..., None] * beta
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By = By[..., None] * beta
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Bz = Bz[..., None] * beta
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# Add V_ext, shape of B_i is `(nsims, nradial, nsamples)``
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Bx = Bx + Vext[:, 0]
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By = By + Vext[:, 1]
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Bz = Bz + Vext[:, 2]
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if convert_to_galactic:
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Bmag, Bl, Bb = cartesian_to_radec(Bx, By, Bz)
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Bl, Bb = csiborgtools.radec_to_galactic(Bl, Bb)
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B = np.stack([Bmag, Bl, Bb], axis=-1)
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else:
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B = np.stack([Bx, By, Bz], axis=-1)
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# Stack over the simulations
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B = np.hstack([B[i] for i in range(len(B))])
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return r, B
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###############################################################################
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# Prepare samples for plotting #
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###############################################################################
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def samples_for_corner(samples):
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samples = deepcopy(samples)
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# Remove the true parameters of each galaxy.
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keys = list(samples.keys())
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for key in keys:
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# Generally don't want to plot the true latent parameters..
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if "x_TFR" in key or "_true_" in key:
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samples.pop(key)
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keys = list(samples.keys())
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if any(x.ndim > 1 for x in samples.values()):
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raise ValueError("All samples must be 1D arrays.")
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data = np.vstack([x for x in samples.values()]).T
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labels = names_to_latex(list(samples.keys()), for_corner=True)
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return data, labels, keys
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def samples_to_getdist(samples, label):
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data, __, keys = samples_for_corner(samples)
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return MCSamples(
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samples=data, names=keys,
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labels=names_to_latex(keys, for_corner=False),
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label=label)
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