[ENH] Updated to latest codes in the paper

3Phases/1d-pdf.py

@@ -0,0 +1,215 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Aug  8 18:21:48 2023
+
+@author: Alankar
+"""
+import numpy as np
+import h5py
+import sys
+sys.path.append("..")
+import matplotlib
+import matplotlib.pyplot as plt
+from misc.coolLambda import cooling_approx
+from scipy.integrate import simpson, trapezoid
+import pickle
+
+## Plot Styling
+matplotlib.rcParams["xtick.direction"] = "in"
+matplotlib.rcParams["ytick.direction"] = "in"
+matplotlib.rcParams["xtick.top"] = True
+matplotlib.rcParams["ytick.right"] = True
+matplotlib.rcParams["xtick.minor.visible"] = True
+matplotlib.rcParams["ytick.minor.visible"] = True
+matplotlib.rcParams["axes.grid"] = True
+matplotlib.rcParams["lines.dash_capstyle"] = "round"
+matplotlib.rcParams["lines.solid_capstyle"] = "round"
+matplotlib.rcParams["legend.handletextpad"] = 0.4
+matplotlib.rcParams["axes.linewidth"] = 0.8
+matplotlib.rcParams["lines.linewidth"] = 3.0
+matplotlib.rcParams["ytick.major.width"] = 0.6
+matplotlib.rcParams["xtick.major.width"] = 0.6
+matplotlib.rcParams["ytick.minor.width"] = 0.45
+matplotlib.rcParams["xtick.minor.width"] = 0.45
+matplotlib.rcParams["ytick.major.size"] = 4.0
+matplotlib.rcParams["xtick.major.size"] = 4.0
+matplotlib.rcParams["ytick.minor.size"] = 2.0
+matplotlib.rcParams["xtick.minor.size"] = 2.0
+matplotlib.rcParams["xtick.major.pad"] = 6.0
+matplotlib.rcParams["xtick.minor.pad"] = 6.0
+matplotlib.rcParams["ytick.major.pad"] = 6.0
+matplotlib.rcParams["ytick.minor.pad"] = 6.0
+matplotlib.rcParams["xtick.labelsize"] = 24.0
+matplotlib.rcParams["ytick.labelsize"] = 24.0
+matplotlib.rcParams["axes.titlesize"] = 24.0
+matplotlib.rcParams["axes.labelsize"] = 28.0
+plt.rcParams["font.size"] = 28
+matplotlib.rcParams["legend.handlelength"] = 2
+#matplotlib.rcParams["figure.dpi"] = 200
+matplotlib.rcParams["axes.axisbelow"] = True
+plt.figure(figsize=(13, 10))
+
+tng50 = np.loadtxt("./Illustris-TNG50-1/tng50-pdf-data.txt")
+
+plt.plot(
+    10.0 ** tng50[:, 0],
+    tng50[:, 1],
+    color="darkgoldenrod",
+    linewidth=4,
+    linestyle="--",
+)
+plt.plot(
+    10.0 ** tng50[:, 0],
+    tng50[:, 2] ,
+    color="yellowgreen",
+    linewidth=4,
+    linestyle="--",
+)
+plt.plot(
+    10.0 ** tng50[:, 0],
+    tng50[:, 3] ,
+    color="slateblue",
+    linewidth=4,
+    linestyle="--",
+)
+
+def probT(y, params):
+    fv    = params["fv"]
+    sig   = params["sig"]
+    ymed  = params["median_T"]
+    A,B,C = params["factors"]
+
+    prob = np.array([(fv[i]/(2*sig[i,0]*sig[i,1])) / \
+                     np.sqrt(np.pi*A[i]) * \
+                     np.exp( -(y-ymed[i])**2/(4.*A[i]*(sig[i,0]*sig[i,1])**2.) )
+            for i in range(fv.shape[0])])  
+    return prob
+
+def mass_PDF(y, params):
+    fv    = params["fv"]
+    sig   = params["sig"]
+    xmed  = params["median_rho"]
+    ymed  = params["median_T"]
+    A,B,C = params["factors"]
+
+    norm  = np.array([fv[i] * np.exp(xmed[i] + C[i]*(sig[i,0]*sig[i,1])**2.)  
+                      for i in range(fv.shape[0])])  
+    Norm = np.sum(norm)
+
+    prob  = np.array([fv[i] * np.exp(xmed[i] + C[i]*(sig[i,0]*sig[i,1])**2.)/ \
+                     (2.*sig[i,0]*sig[i,1]*np.sqrt(np.pi*A[i])) *\
+                     np.exp( -(y-ymed[i]+B[i]*(sig[i,0]*sig[i,1])**2.)**2./(4.*A[i]*(sig[i,0]*sig[i,1])**2.))
+            for i in range(fv.shape[0])])  
+
+    return prob/Norm
+
+Z0 = 1.0
+ZrCGM = 0.3
+p = Z0 / ZrCGM
+metallicity = (
+    1.5
+    * (p - (p**2 - 1) * np.arcsin(1.0 / np.sqrt(p**2 - 1)))
+    * Z0
+    * np.sqrt(p**2 - 1)
+)
+
+def lum_PDF(y, params):
+    fv    = params["fv"]
+    sig   = params["sig"]
+    xmed  = params["median_rho"]
+    ymed  = params["median_T"]
+    A,B,C = params["factors"]
+    T_medV_u = params["T_medV_u"]
+
+    #yy = np.logspace(-2,2,1000)
+    yy = np.copy(y)
+    norm = np.array([fv[i]/(2.*sig[i,0]*sig[i,1]*np.sqrt(np.pi*A[i]))* \
+                np.exp(2.*xmed[i] + 4.*C[i]*(sig[i,0]*sig[i,1])**2.)*\
+                simpson(cooling_approx(np.exp(yy)*T_medV_u, metallicity)*1.e22*\
+                np.exp(-(yy-ymed[i]+2.*B[i]*(sig[i,0]*sig[i,1])**2.)**2./(4.*A[i]*(sig[i,0]*sig[i,1])**2.)),yy)
+                for i in range(fv.shape[0])])
+
+    Norm = np.sum(norm)
+
+    prob  = np.array([(fv[i]/(2.*sig[i,0]*sig[i,1]*np.sqrt(np.pi*A[i])) * \
+                     np.exp(2.*xmed[i] + 4.*C[i]*(sig[i,0]*sig[i,1])**2.)*\
+                     cooling_approx(np.exp(y)*T_medV_u, metallicity)*1.e22 *\
+                     np.exp(-(y-ymed[i]+2.*B[i]*(sig[i,0]*sig[i,1])**2.)**2./(4.*A[i]*(sig[i,0]*sig[i,1])**2.)))
+            for i in range(fv.shape[0])])  
+    return prob/Norm
+
+data_dump = None
+
+with open("params_data.pickle", "rb") as file_obj:
+    data_dump = pickle.load(file_obj)
+
+for key_val in data_dump.keys():
+    exec(f"{key_val} = data_dump[\"{key_val}\"]")
+
+A, B, C = ABC
+xi, yi = xy_meds
+
+pdf_vol_T = probT(np.log(Temperature/T_medV_u), 
+                  {"fv": fV,
+                   "sig": sigs,
+                   "median_T": yi,
+                   "factors": [A,B,C]
+                   })*np.log(10)
+
+pdf_mass = mass_PDF(np.log(Temperature/T_medV_u), 
+                  {"fv": fV,
+                   "sig": sigs,
+                   "median_rho": xi,
+                   "median_T": yi,
+                   "factors": [A,B,C]
+                   })*np.log(10)
+
+norm_mass = simpson(pdf_mass,np.log10(Temperature/T_medV_u))
+print("mass normalization is :", np.sum(norm_mass))
+
+pdf_lum = lum_PDF(np.log(Temperature/T_medV_u), 
+                  {"fv": fV,
+                   "sig": sigs,
+                   "median_rho": xi,
+                   "median_T": yi,
+                   "factors": [A,B,C],
+                   "T_medV_u": T_medV_u,
+                   })*np.log(10)
+
+norm_lum = simpson(pdf_lum,np.log10(Temperature/T_medV_u))
+print("lum normalization is :", np.sum(norm_lum))
+
+mass_pdf = np.sum(pdf_mass, axis = 0)
+lum_pdf  = np.sum(pdf_lum, axis = 0)
+vol_pdf  = np.sum(pdf_vol_T, axis=0)
+
+plt.plot(Temperature, vol_pdf, color="darkgoldenrod", label="volume PDF", linewidth=4)
+plt.plot(Temperature, mass_pdf, color="yellowgreen", label="mass PDF", linewidth=4)
+plt.plot(Temperature, lum_pdf, color="slateblue", label="luminosity PDF", linewidth=4)
+'''
+plt.plot(Temperature,pdf_vol_T[0,:], color="darkgoldenrod", linestyle=":", linewidth=2)
+plt.plot(Temperature,pdf_vol_T[1,:], color="darkgoldenrod", linestyle=":", linewidth=2)
+plt.plot(Temperature,pdf_vol_T[2,:], color="darkgoldenrod", linestyle=":", linewidth=2)
+plt.plot(Temperature, pdf_mass[0,:], color="yellowgreen", linestyle=":", linewidth=2)
+plt.plot(Temperature, pdf_mass[1,:], color="yellowgreen", linestyle=":", linewidth=2)
+plt.plot(Temperature, pdf_mass[2,:], color="yellowgreen", linestyle=":", linewidth=2)
+
+plt.plot(Temperature, pdf_lum[0,:], color="slateblue", linestyle=":", linewidth=2)
+plt.plot(Temperature, pdf_lum[1,:], color="slateblue", linestyle=":", linewidth=2)
+plt.plot(Temperature, pdf_lum[2,:], color="slateblue", linestyle=":", linewidth=2)
+'''
+plt.xscale("log")
+plt.yscale("log")
+plt.ylim(10.0**-2.8, 10**0.6)
+plt.xlim(10.0**3.99, 10.0**6.4)
+plt.xlabel(r"Temperature [$K$]", size=28)
+plt.ylabel(r"$T \mathscr{P}(T)$", size=28)
+leg = plt.legend(loc="lower center", ncol=1, fancybox=True, fontsize=28, framealpha=0.5)
+plt.tick_params(axis="both", which="major", length=10, width=2, labelsize=24)
+plt.tick_params(axis="both", which="minor", length=6, width=1, labelsize=24)
+plt.tight_layout()
+#plt.grid()
+# leg.set_title("Three phase PDF compared with a typical Illustris TNG50 Halo PDF", prop={'size':20})
+plt.savefig("./figures/3-phases-pdf.png", transparent = False)
+plt.show()
+plt.close()