Added EOS2021 theory line

Added functionality to plot the AllGalaxies (EOS2021) model from Munoz+2021 (2110.13919).

The code in process_munoz_2021.py reads the data in the theory folder, both for the standard (EOS) and optimistic (OPT) parameters. Same structure as other theory dictionaries

eor_limits/plot_eor_limits.py

@@ -17,6 +17,12 @@
 from eor_limits.data import DATA_PATH
 
 default_theory_params = {
+    "munoz_2021_AllGalaxies_z8.5": {
+        "paper": "munoz_2021",
+        "model": "EOS",
+        "redshift": 8.5,
+        "linewidth": 3,
+    },
     "mesinger_2016_faint_nf0.8": {
         "paper": "mesinger_2016",
         "model": "faint",
@@ -39,7 +45,7 @@
         "paper": "mesinger_2016",
         "model": "bright",
         "nf": 0.5,
-        "linewidth": 3,
+        "linewidth": 2,
     },
     "pagano_beta1_z8.5": {"paper": "pagano_liu_2020", "beta": 1, "redshift": 8.5},
     "pagano_beta-1_z8.5": {"paper": "pagano_liu_2020", "beta": -1, "redshift": 8.5},
@@ -238,6 +244,12 @@ def make_plot(
                 dict_use = copy.deepcopy(theory)
                 dict_use.pop("paper")
                 paper_dict = get_pagano_2020_line(**dict_use)
+            elif theory["paper"] == "munoz_2021":
+                from eor_limits.process_munoz_2021 import get_munoz_2021_line
+
+                dict_use = copy.deepcopy(theory)
+                dict_use.pop("paper")
+                paper_dict = get_munoz_2021_line(**dict_use)
             else:
                 raise ValueError(
                     "Theory paper " + theory["paper"] + " is not a yaml in the "

eor_limits/process_munoz_2021.py

@@ -0,0 +1,81 @@
+#! /usr/bin/env python
+# -*- mode: python; coding: utf-8 -*
+# Copyright (c) 2019 Nichole Barry, Bryna Hazelton
+# Licensed under the 2-clause BSD License
+# (Slightly) modified by Julian Munoz in 2021
+"""Process Munoz et al. 2021 spectra for plotting."""
+
+import os
+
+import numpy as np
+
+from eor_limits.data import DATA_PATH
+
+
+
+def get_munoz_2021_line(model="EOS", redshift=None, linewidth=1.0):
+    """
+    Get the AllGalaxies model
+
+    Parameters
+    ----------
+    model : str
+        Which model to use. Options are 'EOS' for standard EOS2021 (AllGalaxies) or OPT for 'optimistic' (More PopIII stars)
+    redshift :  float
+        Which redshift to get a model for (the closest match).
+
+    """
+
+    if model not in ["EOS", "OPT"]:
+        raise ValueError("Model must be either 'EOS' or 'OPT'.")
+
+    paper_dict = {
+        "author": "Mu\~noz",
+        "year": 2021,
+        "model": " ",
+        "doi": "arXiv: 2110.13919",
+        "type": "line",
+        "marker": ".",
+        "linewidth": linewidth,
+    }
+
+    if model == "EOS":
+        munoz_file_k = os.path.join(DATA_PATH, "theory", "munoz_2021_allgalaxies/1pt5Gpc_EOS_coeval_pow_kbins.bin")
+        munoz_file_z = os.path.join(DATA_PATH, "theory", "munoz_2021_allgalaxies/1pt5Gpc_EOS_coeval_pow_zlist.bin")
+        munoz_file_P21 = os.path.join(DATA_PATH, "theory", "munoz_2021_allgalaxies/1pt5Gpc_EOS_coeval_pow_P21.bin")
+        #munoz_file_errP21 = os.path.join(DATA_PATH, "theory", "munoz_2021_allgalaxies/1pt5Gpc_EOS_coeval_pow_errP21.bin")
+        paper_dict["linestyle"] = "solid"
+        paper_dict["model"] = "AllGalaxies"
+    else: ## model == "OPT"
+        munoz_file_k = os.path.join(DATA_PATH, "theory", "munoz_2021_optimistic/600Mpc_pt0_coeval_pow_kbins.bin")
+        munoz_file_z = os.path.join(DATA_PATH, "theory", "munoz_2021_optimistic/600Mpc_pt0_coeval_pow_zlist.bin")
+        munoz_file_P21 = os.path.join(DATA_PATH, "theory", "munoz_2021_optimistic/600Mpc_pt0_coeval_pow_P21.bin")
+        #munoz_file_errP21 = os.path.join(DATA_PATH, "theory", "munoz_2021_allgalaxies/600Mpc_pt0_coeval_pow_errP21.bin")
+        paper_dict["linestyle"] = "dashdotted"
+        paper_dict["model"] = "AllGalaxies (OPT)"
+
+
+
+
+
+
+
+    redshifts = np.fromfile(munoz_file_z)
+    k_arr = np.fromfile(munoz_file_k)
+    delta_squared_arr = np.fromfile(munoz_file_P21).reshape((redshifts.size, k_arr.size))
+
+
+
+    # Sort in order of ascending redshift
+    order = np.argsort(redshifts)
+    redshifts = redshifts[order]
+    delta_squared_arr = delta_squared_arr[order]
+
+    redshift_ind = np.argmin(np.abs(redshifts - redshift))
+
+    paper_dict["k"] = k_arr.tolist()
+    # redshift is the 1st index, k is the 2nd
+    paper_dict["delta_squared"] = delta_squared_arr[redshift_ind, :]
+    paper_dict["redshift"] = np.asarray(redshifts)[redshift_ind].tolist()
+
+    return paper_dict