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four_agb_plotter.py
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four_agb_plotter.py
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import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,
AutoMinorLocator)
from data_read import data_reader
from subhess import subhess
from selection_utils import selection_utils
class four_agb_plotter:
def __init__(self, stage='agb_crossed', arcmin_radius=False):
self.n147 = data_reader(stage=stage, galaxy='ngc147')
self.n185 = data_reader(stage=stage, galaxy='ngc185')
self.n205 = data_reader(stage=stage, galaxy='ngc205')
self.m32 = data_reader(stage=stage, galaxy='m32')
self.dEs = np.array([self.n147, self.n185, self.n205, self.m32])
self.n147_cm = data_reader(stage='cm', galaxy='ngc147')
self.n185_cm = data_reader(stage='cm', galaxy='ngc185')
self.n205_cm = data_reader(stage='cm', galaxy='ngc205')
self.m32_cm = data_reader(stage='cm', galaxy='m32')
if arcmin_radius != False:
e = selection_utils()
for i in self.dEs:
i.data = e.select_ellipse(i.data, afl=arcmin_radius/60)[0]
def plot_kj_cmd_hess(self, save=False):
def jk_errors(data, binsize, start_loc):
bin_locs = []
binsy = []
binsx = []
while start_loc > np.min(data.kmag.dropna()):
biny = []
binx = []
for i in data.index:
if start_loc > data.kmag[i] > start_loc - binsize:
biny.append(data.kerr[i])
binx.append(np.sqrt(data.kerr[i]**2 + data.jerr[i]**2))
biny = np.array(biny)
binx = np.array(binx)
avgbiny = np.average(biny)
avgbinx = np.average(binx)
binsy.append(avgbiny)
binsx.append(avgbinx)
bin_locs.append(start_loc-binsize/2)
start_loc = start_loc-binsize
return bin_locs, binsx, binsy
n147 = self.n147
n185 = self.n185
n205 = self.n205
m32 = self.m32
dim_data = [[n147.data, n185.data], [n205.data, m32.data]]
sns.set_context('paper')
params = {'legend.fontsize': '12', 'axes.labelsize': '15',
'axes.titlesize': '12', 'xtick.labelsize': '10',
'ytick.labelsize': '10', 'lines.linewidth': 2, 'axes.linewidth': 2, 'animation.html': 'html5'}
plt.rcParams.update(params)
plt.rcParams.update({'figure.max_open_warning': 0})
markersize = 0.5
marker = 'o'
trgb_locs = [18.1, 17.86, 17.93, 17.8]
trgb_lims = (0, 4.5)
fore_locs = [0.992, 0.964, 1.00, 0.92]
fore_lims = (19, 11)
trgb_locs_dim = [[trgb_locs[0], trgb_locs[1]],
[trgb_locs[2], trgb_locs[3]]]
fore_locs_dim = [[fore_locs[0], fore_locs[1]],
[fore_locs[2], fore_locs[3]]]
fig, axs = plt.subplots(2, 2, sharex=True, sharey=True, figsize=[6, 6])
subhess.plot_kj_cmd(n147, ax=axs[0, 0], label='NGC147')
subhess.plot_kj_cmd(n185, ax=axs[0, 1], label='NGC185')
subhess.plot_kj_cmd(n205, ax=axs[1, 0], label='NGC205')
subhess.plot_kj_cmd(m32, ax=axs[1, 1], label='M32')
start_loc = 18
binsize = 1
err_xpos = -0.5
for i in range(2):
for j in range(2):
xtrgb = trgb_lims
ytrgb = (trgb_locs_dim[i][j], trgb_locs_dim[i][j])
xfore = (fore_locs_dim[i][j], fore_locs_dim[i][j])
yfore = fore_lims
err_ypos, xerr, yerr = jk_errors(
dim_data[i][j], binsize=binsize, start_loc=start_loc)
err_xpos = np.full(shape=len(err_ypos), fill_value=-0.5)
axs[i, j].errorbar(err_xpos, err_ypos, xerr=xerr, yerr=yerr,
linestyle='none', elinewidth=1, capsize=0, color='black')
axs[i, j].plot(xtrgb, ytrgb, linestyle='--', color='black')
axs[i, j].plot(
xfore, yfore, linestyle='dashdot', color='black')
plt.subplots_adjust(wspace=0, hspace=0)
axes = [axs[0, 0], axs[0, 1], axs[1, 0], axs[1, 1]]
for i in axes:
# i.label_outer()
leg = i.legend(handlelength=0, handletextpad=0,
frameon=False, loc='upper right', markerscale=0.001)
for item in leg.legendHandles:
item.set_visible(False)
for i in range(2):
for j in range(2):
# axs[i,j].invert_yaxis()
axs[i, j].set_ylim(bottom=19, top=13)
# axs[i,j].set_xlim(left=-1)
axs[i, j].xaxis.set_major_locator(plt.MaxNLocator(5))
axs[i, j].yaxis.set_major_locator(plt.MaxNLocator(5))
axs[i, j].xaxis.set_minor_locator(MultipleLocator(0.5))
axs[i, j].yaxis.set_minor_locator(MultipleLocator(0.5))
axs[1, 0].set_xlabel('(J-K)$_0$')
axs[1, 1].set_xlabel('(J-K)$_0$')
axs[1, 0].set_ylabel('K$_0$')
axs[0, 0].set_ylabel('K$_0$')
if save == True:
plt.savefig('4_kj_cmd_hess.png')
plt.savefig('4_kj_cmd_hess.pdf')
# axs[0,0].set_title('NGC147')
# axs[0,1].set_title('NGC185')
# axs[1,0].set_title('NGC205')
# axs[1,1].set_title('M32')
def plot_cc_hess(self, save=False):
n147 = self.n147
n185 = self.n185
n205 = self.n205
m32 = self.m32
sns.set_context('paper')
params = {'legend.fontsize': '12', 'axes.labelsize': '15',
'axes.titlesize': '12', 'xtick.labelsize': '10',
'ytick.labelsize': '10', 'lines.linewidth': 2, 'axes.linewidth': 2, 'animation.html': 'html5'}
plt.rcParams.update(params)
plt.rcParams.update({'figure.max_open_warning': 0})
fig, axs = plt.subplots(2, 2, sharex=True, sharey=True, figsize=[6, 6])
hkcut = [[0.337, 0.323], [0.407, 0.477]]
hklim = 2.3
jhcut = [[0.883, 0.857], [0.930, 0.913]]
jhlim = 3.18
subhess.plot_cc(n147, ax=axs[0, 0], label='NGC147')
subhess.plot_cc(n185, ax=axs[0, 1], label='NGC185')
subhess.plot_cc(n205, ax=axs[1, 0], label='NGC205')
subhess.plot_cc(m32, ax=axs[1, 1], label='M32')
plt.subplots_adjust(wspace=0, hspace=0)
for i in range(2):
for j in range(2):
# i.label_outer()
leg = axs[i, j].legend(
handlelength=0, handletextpad=0, frameon=False, loc='upper left', markerscale=0.001)
for item in leg.legendHandles:
item.set_visible(False)
#axs[i,j].xaxis.grid(True, which='minor')
xhk = (jhcut[i][j], jhlim)
yhk = (hkcut[i][j], hkcut[i][j])
xjh = (jhcut[i][j], jhcut[i][j])
yjh = (hkcut[i][j], hklim)
axs[i, j].plot(xhk, yhk, linestyle='--', color='black')
axs[i, j].plot(xjh, yjh, linestyle='--', color='black')
axs[i, j].set_xlim(-0.93, jhlim)
axs[i, j].set_ylim(0, hklim)
axs[i, j].xaxis.set_minor_locator(MultipleLocator(0.2))
axs[i, j].yaxis.set_minor_locator(MultipleLocator(0.2))
axs[1, 0].set_xlabel('(J-H)$_0$')
axs[1, 1].set_xlabel('(J-H)$_0$')
axs[1, 0].set_ylabel('(H-K)$_0$')
axs[0, 0].set_ylabel('(H-K)$_0$')
if save == True:
plt.savefig('4_cc_hess.png')
plt.savefig('4_cc_hess.pdf')
def plot_spatial(self, save=False):
n147 = self.n147.data
n185 = self.n185.data
n205 = self.n205.data
m32 = self.m32.data
sns.set_context('paper')
params = {'legend.fontsize': '12', 'axes.labelsize': '15',
'axes.titlesize': '12', 'xtick.labelsize': '10',
'ytick.labelsize': '10', 'lines.linewidth': 2, 'axes.linewidth': 2, 'animation.html': 'html5'}
plt.rcParams.update(params)
plt.rcParams.update({'figure.max_open_warning': 0})
markersize = 3
marker = 'o'
fig, axs = plt.subplots(
2, 2, sharex=False, sharey=False, figsize=[6, 6])
sns.scatterplot(
n147.xi, n147.eta, ax=axs[0, 0], s=markersize, linewidth=0, marker=marker, color='k', label='NGC147')
sns.scatterplot(
n185.xi, n185.eta, ax=axs[0, 1], s=markersize, linewidth=0, marker=marker, color='k', label='NGC185')
sns.scatterplot(
n205.xi, n205.eta, ax=axs[1, 0], s=markersize, linewidth=0, marker=marker, color='k', label='NGC205')
sns.scatterplot(
m32.xi, m32.eta, ax=axs[1, 1], s=markersize, linewidth=0, marker=marker, color='k', label='M32')
#plt.subplots_adjust(wspace=0, hspace=0)
axes = [axs[0, 0], axs[0, 1], axs[1, 0], axs[1, 1]]
for i in axes:
# i.label_outer()
leg = i.legend(handlelength=0, handletextpad=0,
frameon=False, loc='upper right', markerscale=0.001)
for item in leg.legendHandles:
item.set_visible(False)
# for i in range(2):
# for j in range(2):
#axs[i, j].xaxis.set_major_locator(plt.MaxNLocator(5))
#axs[i, j].yaxis.set_major_locator(plt.MaxNLocator(5))
#axs[i, j].xaxis.set_minor_locator(MultipleLocator(0.5))
#axs[i, j].yaxis.set_minor_locator(MultipleLocator(0.5))
axs[1, 0].set_xlabel(r'$\xi$')
axs[1, 1].set_xlabel(r'$\xi$')
axs[1, 0].set_ylabel(r'$\eta$')
axs[0, 0].set_ylabel(r'$\eta$')
axs[1, 1].set(ylabel=None)
axs[0, 1].set(xlabel=None)
axs[0, 0].set(xlabel=None)
axs[0, 1].set(ylabel=None)
if save == True:
plt.savefig('4_spatial.png')
plt.savefig('4_spatial.pdf')