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eb1797e8a9
* Get rid of utils * Clean up imports * Move some utils here * Rename file * Add simname to boxsize * Add imports * Delete old files * Update README * Update imports * Add a new draft of the density calculator * Update fields * Draft of new density field calculatiosn * Add snapshot * Add boxsizes * Little updates * Bring back utils * Edit docstrings * Edits imports * Add progress on snapshots * edit improts * add basic snapshot catalogue * Add support for CSiBORG2 snapshot reader * add paths to fofcat for csiborg2 * Add more imports * Add more boxsize * Add more imports * Add field readers * Simplify field paths * Fix typo * Add observer vp * Clean up density field calculation * Add a short note * Edit args * Remove old comments * Edit docs * Remove blank line * Stop flipping RAMSES * Remove comment * Edit desc * Remove normalization * Remove old dist array * Remove non-volume weighting * Remove non-volume weight * Add ignore of flake8 notebooks * Fix path typo * Fix units * Edit paths docs * Update nb
764 KiB
764 KiB
In [9]:
import numpy as np
import matplotlib.pyplot as plt
import scienceplots
import seaborn as sns
import healpy as hp
from h5py import File
from reconstruction_comparison import *
SPEED_OF_LIGHT = 299_792.458
from csiborgtools import radec_to_galactic
%load_ext autoreload
%autoreload 2
%matplotlib inline
Paper plots¶
In [3]:
with File("/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5", 'r') as f:
SFI = {}
for key in f["SFI_gals"].keys():
SFI[key] = f["SFI_gals"][key][...]
TWOMTF = {}
for key in f["2MTF"].keys():
TWOMTF[key] = f["2MTF"][key][...]
FOUNDATION = {}
for key in f["Foundation"].keys():
FOUNDATION[key] = f["Foundation"][key][...]
LOSS = {}
for key in f["LOSS"].keys():
LOSS[key] = f["LOSS"][key][...]
with File("/mnt/extraspace/rstiskalek/catalogs/PV/CF4/CF4_TF-distances.hdf5", 'r') as f:
CF4_TFR = {}
for key in f.keys():
CF4_TFR[key] = f[key][...]
RA = f["RA"][...] * 360 / 24
CF4_TFR["RA"] = RA
CF4_TFR["DEC"] = f["DE"][...]
l, b = radec_to_galactic(CF4_TFR["RA"], CF4_TFR["DE"])
m = np.abs(b) > 7.5
for key in CF4_TFR.keys():
CF4_TFR[key] = CF4_TFR[key][m]
1. Redshift distribution¶
In [28]:
with plt.style.context('science'):
plt.rcParams.update({'font.size': 9})
plt.figure()
sns.kdeplot(LOSS["z_CMB"], label="LOSS", fill=True, bw_adjust=0.75)
sns.kdeplot(FOUNDATION["z_CMB"], label="Foundation", fill=True, bw_adjust=0.75)
sns.kdeplot(SFI["z_CMB"], label="SFI", fill=True, bw_adjust=0.75)
sns.kdeplot(TWOMTF["z_CMB"], label="2MTF", fill=True, bw_adjust=0.75)
m = CF4_TFR["i"] > 5
sns.kdeplot(CF4_TFR["Vcmb"][m] / SPEED_OF_LIGHT, label=catalogue_to_pretty("CF4_TFR_i"), fill=True)
m = CF4_TFR["w1"] > 5
sns.kdeplot(CF4_TFR["Vcmb"][m] / SPEED_OF_LIGHT, label=catalogue_to_pretty("CF4_TFR_w1"), fill=True)
plt.xlabel(r"$z_{\rm CMB}$")
plt.ylabel("Normalised PDF")
plt.legend()
plt.xlim(0, 0.07)
plt.tight_layout()
plt.savefig(f"../../plots/zcmb_dist.pdf", dpi=450)
plt.show()
2. Sky distribution¶
In [29]:
with plt.style.context('science'):
plt.rcParams.update({'font.size': 9})
figwidth = 8.3
fig, axs = plt.subplots(2, 3, figsize=(figwidth, 0.4 * figwidth),
sharex=True, sharey=True)
names = ["LOSS", "Foundation", "SFI", "2MTF", "CF4_TFR_i", "CF4_TFR_w1"]
vals = [LOSS, FOUNDATION, SFI, TWOMTF, CF4_TFR, CF4_TFR]
for i, ax in enumerate(axs.flat):
RA = vals[i]["RA"]
DEC = vals[i]["DEC"]
if names[i] == "CF4_TFR_i":
m = vals[i]["i"] > 5
RA = RA[m]
DEC = DEC[m]
if names[i] == "CF4_TFR_w1":
m = vals[i]["w1"] > 5
RA = RA[m]
DEC = DEC[m]
sns.scatterplot(x=RA, y=DEC, ax=ax, s=1.5, rasterized=True)
# Add panel name in top-left corner of each subplot
ax.text(0.04, 0.16, catalogue_to_pretty(names[i]), transform=ax.transAxes,
fontsize=9, verticalalignment='top',
bbox=dict(boxstyle="round", facecolor='lightgray', alpha=1),
zorder=10) # Ensure text is on top of other plot elements
axs[0, 0].set_xlim(0, 360)
axs[0, 0].set_ylim(-90, 90)
for i in range(3):
axs[-1, i].set_xlabel(r"$\mathrm{RA} ~ [\mathrm{deg}]$")
for i in range(2):
axs[i, 0].set_ylabel(r"$\delta ~ [\mathrm{deg]}$")
fig.tight_layout()
plt.savefig(f"../../plots/sky_dist.pdf", dpi=350)
fig.show()
In [72]:
with plt.style.context('science'):
plt.rcParams.update({'font.size': 9})
RA = CF4_TFR["RA"]
DEC = CF4_TFR["DEC"]
fig, axs = plt.subplots(2, 1, figsize=(3.5, 2.45), sharex=True, sharey=True)
fig.subplots_adjust(hspace=0.0, wspace=0.0)
m = CF4_TFR["w1"] > 5
sns.scatterplot(x=RA[m], y=DEC[m], s=5, rasterized=True, ax=axs[0])
axs[0].text(0.15, 0.15, catalogue_to_pretty("CF4_TFR_w1"),
transform=axs[0].transAxes, fontsize="small",
verticalalignment='center', horizontalalignment='center',
bbox=dict(facecolor='white', alpha=0.75)
)
m = CF4_TFR["i"] > 5
sns.scatterplot(x=RA[m], y=DEC[m], s=5, rasterized=True, ax=axs[1])
axs[1].text(0.15, 0.15, catalogue_to_pretty("CF4_TFR_i"),
transform=axs[1].transAxes, fontsize="small",
verticalalignment='center', horizontalalignment='center',
bbox=dict(facecolor='white', alpha=0.75))
axs[0].set_xlim(0, 360)
axs[0].set_ylim(-90, 90)
for i in range(2):
axs[i].set_ylabel(r"$\delta ~ [\mathrm{deg}]$")
axs[-1].set_xlabel(r"$\mathrm{RA} ~ [\mathrm{deg}]$")
fig.tight_layout()
fig.savefig(f"../../plots/sky_dist_CF4.pdf", dpi=350)
fig.show()
In [ ]:
Experimenting¶
In [21]:
l, b = radec_to_galactic(CF4_TFR["RA"], CF4_TFR["DE"])
# l, b = radec_to_galactic(SFI["RA"], SFI["DEC"])
In [22]:
np.abs(b).min()
Out[22]:
In [26]:
(np.abs(b) < 10).sum()
Out[26]:
In [23]:
plt.figure()
plt.hist(np.abs(b), bins="auto")
plt.show()
In [ ]:
In [17]:
with File("/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5", 'r') as f:
print(f["SFI_gals"].keys())
zCMB_sfi = f["SFI_gals"]["z_CMB"][...]
mag_sfi = f["SFI_gals"]["mag"][...]
eta_sfi = f["SFI_gals"]["eta"][...]
e_mag_sfi = f["SFI_gals"]["e_mag"][...]
e_eta_sfi = f["SFI_gals"]["e_eta"][...]
zCMB_2MTF = f["2MTF"]["z_CMB"][...]
mag_2MTF = f["2MTF"]["mag"][...]
eta_2MTF = f["2MTF"]["eta"][...]
e_mag_2MTF = f["2MTF"]["e_mag"][...]
e_eta_2MTF = f["2MTF"]["e_eta"][...]
In [28]:
with File("/mnt/extraspace/rstiskalek/catalogs/PV/CF4/CF4_TF-distances.hdf5", 'r') as f:
zCMB = f["Vcmb"][...] / 3e5
rband = f["r"][...]
iband = f["i"][...]
w1band = f["w1"][...]
RA = f["RA"][...] * 360 / 24
dec = f["DE"][...]
# m = (iband > 5) #& (w1band > 5)
m = (w1band> 5) #& (w1band > 5)
w1band = w1band[m]
iband = iband[m]
RA = RA[m]
dec = dec[m]
In [29]:
dmag = iband - w1band
In [30]:
plt.figure()
plt.scatter(RA, dec, c=dmag, s=1)
plt.colorbar()
plt.show()
In [11]:
plt.figure()
plt.hist(iband - w1band, bins="auto")
plt.show()
In [ ]:
In [ ]:
In [69]:
m = rband > 0
plt.figure()
plt.hist(rband[m], bins="auto")
plt.axvline(17.6, c="red")
plt.show()
In [ ]:
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In [ ]:
In [64]:
plt.figure()
plt.hist(zCMB, bins="auto")
plt.xlabel(r"$z_{\rm CMB}$")
plt.ylabel("Counts")
plt.xlim(0)
plt.tight_layout()
plt.savefig("../../plots/zCMB_CF4.png")
plt.show()
In [ ]:
In [ ]:
In [53]:
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
df_sfi = pd.DataFrame({
r"$z_{\rm CMB}$": zCMB_sfi,
r"$m$": mag_sfi,
r"$\eta$": eta_sfi,
r"$\sigma_{m}$": e_mag_sfi,
r"$\sigma_\eta$": e_eta_sfi,
"Dataset": "SFI"
})
df_2mtf = pd.DataFrame({
r"$z_{\rm CMB}$": zCMB_2MTF,
r"$m$": mag_2MTF,
r"$\eta$": eta_2MTF,
r"$\sigma_{m}$": e_mag_2MTF,
r"$\sigma_\eta$": e_eta_2MTF,
"Dataset": "2MTF"
})
df_combined = pd.concat([df_sfi, df_2mtf])
g = sns.pairplot(df_combined, hue="Dataset", kind="kde", diag_kind="kde",
palette="Set1", corner=True, plot_kws={"alpha": 0.75},
diag_kws={"fill": True})
sns.move_legend(g, "upper right", bbox_to_anchor=(0.7, 0.7))
# Show the plot
plt.tight_layout()
plt.savefig("../../plots/TFR_data.pdf", dpi=450)
plt.show()
In [ ]: