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

notebooks/flow/flow_bulk.py

@@ -0,0 +1,65 @@
+# Copyright (C) 2024 Richard Stiskalek
+# This program is free software; you can redistribute it and/or modify it
+# under the terms of the GNU General Public License as published by the
+# Free Software Foundation; either version 3 of the License, or (at your
+# option) any later version.
+#
+# This program is distributed in the hope that it will be useful, but
+# WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General
+# Public License for more details.
+#
+# You should have received a copy of the GNU General Public License along
+# with this program; if not, write to the Free Software Foundation, Inc.,
+# 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+"""Script to help with plots in `flow_calibration.ipynb`."""
+from os.path import exists, join
+
+import csiborgtools
+import numpy as np
+from astropy import units as u
+from astropy.cosmology import FlatLambdaCDM
+
+FDIR = "/mnt/extraspace/rstiskalek/csiborg_postprocessing/field_shells"
+
+
+def read_enclosed_density(simname):
+    fname = join(FDIR, f"enclosed_mass_{simname}.npz")
+
+    if exists(fname):
+        data = np.load(fname)
+    else:
+        raise FileNotFoundError(f"File `{fname}` not found.")
+
+    Om0 = csiborgtools.simname2Omega_m(simname)
+    cosmo = FlatLambdaCDM(H0=100, Om0=Om0)
+    rho_matter = Om0 * cosmo.critical_density(0).to(u.M_sun / u.Mpc**3).value
+
+    r = data["distances"]
+    volume = 4 * np.pi / 3 * r**3
+
+    overdensity = data["enclosed_mass"] / volume / rho_matter - 1
+
+    return r, overdensity
+
+
+def read_enclosed_flow(simname):
+    fname = join(FDIR, f"enclosed_mass_{simname}.npz")
+
+    if exists(fname):
+        data = np.load(fname)
+    else:
+        raise FileNotFoundError(f"File {fname} not found.")
+
+    r = data["distances"]
+    V = data["cumulative_velocity"]
+    nsim, nbin = V.shape[:2]
+    Vmag = np.linalg.norm(V, axis=-1)
+    l = np.empty((nsim, nbin), dtype=V.dtype)  # noqa
+    b = np.empty_like(l)
+
+    for n in range(nsim):
+        V_n = csiborgtools.cartesian_to_radec(V[n])
+        l[n], b[n] = csiborgtools.radec_to_galactic(V_n[:, 1], V_n[:, 2])
+
+    return r, Vmag, l, b

notebooks/flow/flow_calibration.py

@@ -0,0 +1,193 @@
+# Copyright (C) 2024 Richard Stiskalek
+# This program is free software; you can redistribute it and/or modify it
+# under the terms of the GNU General Public License as published by the
+# Free Software Foundation; either version 3 of the License, or (at your
+# option) any later version.
+#
+# This program is distributed in the hope that it will be useful, but
+# WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General
+# Public License for more details.
+#
+# You should have received a copy of the GNU General Public License along
+# with this program; if not, write to the Free Software Foundation, Inc.,
+# 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+"""Script to help with plots in `flow_calibration.ipynb`."""
+from copy import copy
+from os.path import join, exists
+
+import numpy as np
+from getdist import MCSamples
+from h5py import File
+
+import csiborgtools
+
+
+def read_samples(catalogue, simname, ksmooth, include_calibration=False,
+                 return_MCsamples=False, subtract_LG_velocity=-1):
+    print(f"\nReading {catalogue} fitted to {simname} with ksmooth = {ksmooth}.", flush=True)  # noqa
+    paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
+    nsims = paths.get_ics(simname)
+
+    # The last simulation was used to draw the mocks.
+    if catalogue in ["CB2_small", "CB2_large"]:
+        nsims = nsims[:-5]
+
+    FDIR_LG = "/mnt/extraspace/rstiskalek/csiborg_postprocessing/peculiar_velocity/observer"  # noqa
+
+    Vx, Vy, Vz, beta, sigma_v, alpha = [], [], [], [], [], []
+    BIC, AIC, logZ, chi2 = [], [], [], []
+
+    if catalogue in ["LOSS", "Foundation", "Pantheon+"]:
+        alpha_cal, beta_cal, mag_cal, e_mu_intrinsic = [], [], [], []
+    elif catalogue in ["2MTF", "SFI_gals", "SFI_gals_masked"]:
+        a, b, e_mu_intrinsic = [], [], []
+    elif catalogue == "SFI_groups":
+        h = []
+    elif catalogue in ["CB2_small", "CB2_large"]:
+        pass
+    else:
+        raise ValueError(f"Catalogue {catalogue} not recognized.")
+
+    fname = f"/mnt/extraspace/rstiskalek/csiborg_postprocessing/peculiar_velocity/flow_samples_{catalogue}_{simname}_smooth_{ksmooth}.hdf5"  # noqa
+    with File(fname, 'r') as f:
+        for i, nsim in enumerate(nsims):
+            Vx.append(f[f"sim_{nsim}/Vext_x"][:])
+            Vy.append(f[f"sim_{nsim}/Vext_y"][:])
+            Vz.append(f[f"sim_{nsim}/Vext_z"][:])
+
+            alpha.append(f[f"sim_{nsim}/alpha"][:])
+            beta.append(f[f"sim_{nsim}/beta"][:])
+            sigma_v.append(f[f"sim_{nsim}/sigma_v"][:])
+
+            if subtract_LG_velocity >= 0:
+                fname = join(FDIR_LG, f"{simname}_{nsim}_observer_velocity.npz")  # noqa
+                if not exists(fname):
+                    raise FileNotFoundError(f"File {fname} not found.")
+                d = np.load(fname)
+                R = d["smooth_scales"][subtract_LG_velocity]
+                if i == 0:
+                    print(f"Subtracting LG velocity with kernel {R} Mpc / h.", flush=True)  # noqa
+                Vx_LG, Vy_LG, Vz_LG = d["vobs"][subtract_LG_velocity]
+                if simname == "Carrick2015":
+                    Vx[-1] += beta[-1] * Vx_LG
+                    Vy[-1] += beta[-1] * Vy_LG
+                    Vz[-1] += beta[-1] * Vz_LG
+                else:
+                    Vx[-1] += Vx_LG
+                    Vy[-1] += Vy_LG
+                    Vz[-1] += Vz_LG
+
+            BIC.append(f[f"sim_{nsim}/BIC"][...])
+            AIC.append(f[f"sim_{nsim}/AIC"][...])
+            logZ.append(f[f"sim_{nsim}/logZ"][...])
+            try:
+                chi2.append(f[f"sim_{nsim}/chi2"][...])
+            except KeyError:
+                chi2.append([0.])
+
+            if catalogue in ["LOSS", "Foundation", "Pantheon+"]:
+                alpha_cal.append(f[f"sim_{nsim}/alpha_cal"][:])
+                beta_cal.append(f[f"sim_{nsim}/beta_cal"][:])
+                mag_cal.append(f[f"sim_{nsim}/mag_cal"][:])
+                e_mu_intrinsic.append(f[f"sim_{nsim}/e_mu_intrinsic"][:])
+            elif catalogue in ["2MTF", "SFI_gals"]:
+                a.append(f[f"sim_{nsim}/a"][:])
+                b.append(f[f"sim_{nsim}/b"][:])
+                e_mu_intrinsic.append(f[f"sim_{nsim}/e_mu_intrinsic"][:])
+            elif catalogue == "SFI_groups":
+                h.append(f[f"sim_{nsim}/h"][:])
+            elif catalogue in ["CB2_small", "CB2_large"]:
+                pass
+            else:
+                raise ValueError(f"Catalogue {catalogue} not recognized.")
+
+    Vx, Vy, Vz, alpha, beta, sigma_v = np.hstack(Vx), np.hstack(Vy), np.hstack(Vz), np.hstack(alpha), np.hstack(beta), np.hstack(sigma_v)  # noqa
+
+    gof = np.hstack(BIC), np.hstack(AIC), np.hstack(logZ), np.hstack(chi2)
+
+    if catalogue in ["LOSS", "Foundation", "Pantheon+"]:
+        alpha_cal, beta_cal, mag_cal, e_mu_intrinsic = np.hstack(alpha_cal), np.hstack(beta_cal), np.hstack(mag_cal), np.hstack(e_mu_intrinsic)  # noqa
+    elif catalogue in ["2MTF", "SFI_gals", "SFI_gals_masked"]:
+        a, b, e_mu_intrinsic = np.hstack(a), np.hstack(b), np.hstack(e_mu_intrinsic)  # noqa
+    elif catalogue == "SFI_groups":
+        h = np.hstack(h)
+    elif catalogue in ["CB2_small", "CB2_large"]:
+        pass
+    else:
+        raise ValueError(f"Catalogue {catalogue} not recognized.")
+
+    # Calculate magnitude of V_ext
+    Vmag = np.sqrt(Vx**2 + Vy**2 + Vz**2)
+    # Calculate direction in galactic coordinates of V_ext
+    V = np.vstack([Vx, Vy, Vz]).T
+    V = csiborgtools.cartesian_to_radec(V)
+    l, b = csiborgtools.radec_to_galactic(V[:, 1], V[:, 2])
+
+    data = [alpha, beta, Vmag, l, b, sigma_v]
+    names = ["alpha", "beta", "Vmag", "l", "b", "sigma_v"]
+
+    if include_calibration:
+        if catalogue in ["LOSS", "Foundation", "Pantheon+"]:
+            data += [alpha_cal, beta_cal, mag_cal, e_mu_intrinsic]
+            names += ["alpha_cal", "beta_cal", "mag_cal", "e_mu_intrinsic"]
+        elif catalogue in ["2MTF", "SFI_gals", "SFI_gals_masked"]:
+            data += [a, b, e_mu_intrinsic]
+            names += ["a", "b", "e_mu_intrinsic"]
+        elif catalogue == "SFI_groups":
+            data += [h]
+            names += ["h"]
+        else:
+            raise ValueError(f"Catalogue {catalogue} not recognized.")
+
+    print("BIC  = {:4f} +- {:4f}".format(np.mean(gof[0]), np.std(gof[0])))
+    print("AIC  = {:4f} +- {:4f}".format(np.mean(gof[1]), np.std(gof[1])))
+    print("logZ = {:4f} +- {:4f}".format(np.mean(gof[2]), np.std(gof[2])))
+    print("chi2 = {:4f} +- {:4f}".format(np.mean(gof[3]), np.std(gof[3])))
+
+    data = np.vstack(data).T
+
+    if return_MCsamples:
+        simname = simname_to_pretty(simname)
+        if ksmooth == 1:
+            simname = fr"{simname} (2)"
+
+        if subtract_LG_velocity >= 0:
+            simname += " (LG)"
+
+        label = fr"{catalogue}, {simname}, $\log \mathcal{{Z}} = {np.mean(gof[2]):.1f}$"                 # noqa
+
+        return MCSamples(samples=data, names=names,
+                         labels=names_to_latex(names), label=label)
+
+    return data, names, gof
+
+
+def simname_to_pretty(simname):
+    ltx = {"Carrick2015": "C+15",
+           "csiborg1": "CB1",
+           "csiborg2_main": "CB2",
+           }
+    return ltx[simname] if simname in ltx else simname
+
+
+def names_to_latex(names, for_corner=False):
+    ltx = {"alpha": "\\alpha",
+           "beta": "\\beta",
+           "Vmag": "V_{\\rm ext} ~ [\\mathrm{km} / \\mathrm{s}]",
+           "sigma_v": "\\sigma_v ~ [\\mathrm{km} / \\mathrm{s}]",
+           }
+
+    ltx_corner = {"alpha": r"$\alpha$",
+                  "beta": r"$\beta$",
+                  "Vmag": r"$V_{\rm ext}$",
+                  "sigma_v": r"$\sigma_v$",
+                  "h": r"$h$",
+                  }
+
+    labels = copy(names)
+    for i, label in enumerate(names):
+        if label in ltx:
+            labels[i] = ltx_corner[label] if for_corner else ltx[label]
+
+    return labels