CDF for nearest neighbour (#63)

* Updat ebounds

* fix mistake

* add plot script

* fix which sims

* Add Poisson

* Just docs

* Hide things to __main__

* Rename paths

* Move old script

* Remove radpos

* Paths renaming

* Paths renaming

* Remove trunk stuff

* Add import

* Add nearest neighbour search

* Add Quijote fiducial indices

* Add final snapshot matching

* Add fiducial observer selection

* add boxsizes

* Add reading functions

* Little stuff

* Bring back the fiducial observer

* Add arguments

* Add quijote paths

* Add notes

* Get this running

* Add yaml

* Remove Poisson stuff

* Get the 2PCF script running

* Add not finished htings

* Remove comment

* Verbosity only on 0th rank!

* Update plotting style

* Add nearest neighbour CDF

* Save radial distance too

* Add centres

* Add basic plotting

scripts_plots/plot_knn.py

@@ -0,0 +1,103 @@
+# Copyright (C) 2023 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.
+
+from os.path import join
+
+import matplotlib.pyplot as plt
+import numpy
+
+import scienceplots  # noqa
+import utils
+
+try:
+    import csiborgtools
+except ModuleNotFoundError:
+    import sys
+    sys.path.append("../")
+    import csiborgtools
+
+
+###############################################################################
+#                Probability of matching a reference simulation halo          #
+###############################################################################
+
+
+def plot_knn(runname):
+    print(f"Plotting kNN CDF for {runname}.")
+    cols = plt.rcParams["axes.prop_cycle"].by_key()["color"]
+    paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
+    reader = csiborgtools.read.kNNCDFReader(paths)
+
+    with plt.style.context(utils.mplstyle):
+        plt.figure()
+
+        # Quijote kNN
+        rs, cdf, ndensity = reader.read("quijote", runname, kind="auto")
+        pk = reader.prob_k(cdf)
+        pk_poisson = reader.poisson_prob_k(rs, numpy.arange(pk.shape[1]),
+                                           ndensity)
+
+        for k in range(3):
+            mu = numpy.mean(pk[:, k, :], axis=0)
+            std = numpy.std(pk[:, k, :], axis=0)
+            plt.plot(rs, mu, label=r"$k = {}$, Quijote".format(k + 1),
+                     c=cols[k % len(cols)])
+            # plt.fill_between(rs, mu - std, mu + std, alpha=0.15,
+            #                  color=cols[k % len(cols)], zorder=0)
+
+            mu = numpy.mean(pk_poisson[:, k, :], axis=0)
+            std = numpy.std(pk_poisson[:, k, :], axis=0)
+            plt.plot(rs, mu, c=cols[k % len(cols)], ls="dashed",
+                     label=r"$k = {}$, Poisson analytical".format(k + 1))
+            # plt.fill_between(rs, mu - std, mu + std, alpha=0.15,
+            #                  color=cols[k % len(cols)], zorder=0, hatch="\\")
+
+        # Quijote poisson kNN
+        rs, cdf, ndensity = reader.read("quijote", "mass003_poisson",
+                                        kind="auto")
+        pk = reader.prob_k(cdf)
+
+        for k in range(3):
+            mu = numpy.mean(pk[:, k, :], axis=0)
+            std = numpy.std(pk[:, k, :], axis=0)
+            plt.plot(rs, mu, label=r"$k = {}$, Poisson Quijote".format(k + 1),
+                     c=cols[k % len(cols)], ls="dotted")
+            # plt.fill_between(rs, mu - std, mu + std, alpha=0.15,
+            #                  color=cols[k % len(cols)], zorder=0)
+
+#         # CSiBORG kNN
+#         rs, cdf, ndensity = reader.read("csiborg", runname, kind="auto")
+#         pk = reader.mean_prob_k(cdf)
+#         for k in range(2):
+#             mu = pk[k, :, 0]
+#             std = pk[k, :, 1]
+#             plt.plot(rs, mu, ls="--", c=cols[k % len(cols)])
+#             plt.fill_between(rs, mu - std, mu + std, alpha=0.15, hatch="\\",
+#                              color=cols[k % len(cols)], zorder=0)
+
+        plt.legend()
+        plt.xlabel(r"$r~[\mathrm{Mpc}]$")
+        plt.ylabel(r"$P(k | V = 4 \pi r^3 / 3)$")
+
+        for ext in ["png"]:
+            fout = join(utils.fout, f"knn_{runname}.{ext}")
+            print("Saving to `{fout}`.".format(fout=fout))
+            plt.savefig(fout, dpi=utils.dpi, bbox_inches="tight")
+        plt.close()
+
+
+if __name__ == "__main__":
+
+    plot_knn("mass003")

scripts_plots/plot_nearest.py

@@ -0,0 +1,91 @@
+# Copyright (C) 2023 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.
+
+from argparse import ArgumentParser
+
+import matplotlib.pyplot as plt
+import numpy
+import scienceplots  # noqa
+from cache_to_disk import cache_to_disk, delete_disk_caches_for_function
+
+import utils
+
+try:
+    import csiborgtools
+except ModuleNotFoundError:
+    import sys
+    sys.path.append("../")
+    import csiborgtools
+
+
+@cache_to_disk(7)
+def read_cdf(simname, run, kwargs):
+    paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
+    reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
+    return reader.build_cdf(simname, run, verbose=True)
+
+
+def plot_cdf(kwargs):
+    print("Plotting the CDFs.", flush=True)
+    paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
+    reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
+    x = reader.bin_centres("neighbour")
+
+    y_quijote = read_cdf("quijote", "mass003", kwargs)
+    y_csiborg = read_cdf("csiborg", "mass003", kwargs)
+    ncdf = y_quijote.shape[0]
+
+    with plt.style.context(utils.mplstyle):
+        plt.figure()
+        for i in range(ncdf):
+            if i == 0:
+                label1 = "Quijote"
+                label2 = "CSiBORG"
+            else:
+                label1 = None
+                label2 = None
+            plt.plot(x, y_quijote[i], c="C0", label=label1)
+            plt.plot(x, y_csiborg[i], c="C1", label=label2)
+        plt.xlim(0, 75)
+        plt.ylim(0, 1)
+        plt.xlabel(r"$r_{\rm neighbour}~[\mathrm{Mpc}]$")
+        plt.ylabel(r"$\mathrm{CDF}(r_{\rm neighbour})$")
+        plt.legend()
+
+        plt.tight_layout()
+        plt.savefig("../plots/nearest_neighbour_cdf.png", dpi=450,
+                    bbox_inches="tight")
+        plt.close()
+
+
+if __name__ == "__main__":
+    parser = ArgumentParser()
+    parser.add_argument('-c', '--clean', action='store_true')
+    args = parser.parse_args()
+
+    kwargs = {"rmax_radial": 155 / 0.705,
+              "nbins_radial": 20,
+              "rmax_neighbour": 100.,
+              "nbins_neighbour": 150,
+              "paths_kind": csiborgtools.paths_glamdring}
+
+    cached_funcs = ["read_cdf"]
+    if args.clean:
+        for func in cached_funcs:
+            print(f"Cleaning cache for function {func}.")
+            delete_disk_caches_for_function(func)
+
+
+    plot_cdf(kwargs)

scripts_plots/utils.py

@@ -15,4 +15,4 @@
 
 dpi = 450
 fout = "../plots/"
-mplstyle = ["notebook"]
+mplstyle = ["science", "notebook"]