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moment_panel.py
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moment_panel.py
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from astropy.io import fits
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import PowerNorm
from scipy.interpolate import interp2d
from matplotlib.patches import Ellipse
import matplotlib.gridspec as gs
from modules.casa_cube import casa_cube
#plt.rc('text', usetex=True)
#plt.rc('font', family='serif')
def plot_beam(ax, bmaj, bmin, bpa, color='w'):
dx = 0.125
dy = 0.125
beam = Ellipse(ax.transLimits.inverted().transform((dx, dy)),
width=bmin,
height=bmaj,
angle=bpa,
fill=True,
color=color)
ax.add_patch(beam)
files = []
bf_files = []
vel_type = 'M9'
if vel_type == 'M9':
files = ['../Output/S2_Final/Moment/IM_Lupi_M9.fits', '../Output/S2_Final/Moment/pseudo_casa_M9.fits']
true_casa = [True, True]
scale_velocity = [True, True]
shift_velocity = [True, False]
elif vel_type == 'v0':
files = ['../data/CASA/pseudo_casa_v0.fits', '../observations/hd_163296_CO_v0.fits']
true_casa = [False, False]
scale_velocity = [False, False]
shift_velocity = [False, True]
elif vel_type == 'M1':
files = ['../data/CASA/pseudo_casa_M1.fits', 'observations/hd_163296_CO_M1.fits']
true_casa = [True, True]
scale_velocity = [True, True]
shift_velocity = [False, True]
# Fiddle with limits
# Limit in arcseconds
limit = 3.0
limit_tick = 2 * int(limit / 1.0) + 1
x_limits = [limit, -limit]
y_limits = [-limit, limit]
x_ticks = np.linspace(limit, -limit, limit_tick)
y_ticks = np.linspace(-limit, limit, limit_tick)
# Set up figure
nrows = 1
ncols = 2
print(nrows, ncols)
const = 1.8
fig = plt.figure(figsize=[const*2.5*ncols, const*2.8*nrows])
g = gs.GridSpec(
nrows=nrows, ncols=ncols, left=0.06, bottom=0.06, right=0.88, top=0.95,
wspace=0.08, hspace=0.02)
axes = np.array([[fig.add_subplot(g[i, j]) for i in range(0, nrows)] for j in range(0, ncols)]).T
colorbar_kwargs = {'extend': 'both', 'pad': 0.01}
pad = 0.01
bbox = dict(boxstyle="round", fc="black", alpha=0.4)
num_pixels = (2048, 2048)
colorbar_kwargs = {'extend': 'both', 'pad': pad}
plots = []
vlsr = 4500
for i in range(len(files)):
file = files[i]
print(file)
moment_1_fits = fits.open(file)
if true_casa[i]:
data = moment_1_fits[0].data[0]
else:
data = moment_1_fits[0].data
print(np.shape(data))
if scale_velocity[i]:
data *= 1000
if shift_velocity[i]:
print('scaling', i)
data = data - vlsr
header = moment_1_fits[0].header
naxis1 = header['NAXIS1']
naxis2 = header['NAXIS2']
cdelt1 = header['CDELT1']
cdelt2 = header['CDELT2']
crpix1 = header['CRPIX1']
crpix2 = header['CRPIX2']
edge_ra = naxis1 * cdelt1 * 3600
edge_dec = naxis2 * cdelt2 * 3600
truemiddle_ra = edge_ra/2
truemiddle_dec = edge_dec/2
midpoint_ra = crpix1*cdelt1*3600
midpoint_dec = crpix2*cdelt2*3600
offset_ra = truemiddle_ra - midpoint_ra
offset_dec = truemiddle_dec - midpoint_dec
extent = np.array([-truemiddle_ra + offset_ra, truemiddle_ra + offset_ra, -truemiddle_dec + offset_dec, truemiddle_dec + offset_dec])
h = axes[0][i].imshow(data/1000, origin='lower', cmap='RdBu_r', extent=extent, vmin=-2.0, vmax=2.0)
axes[0][i].set_xlim(x_limits)
axes[0][i].set_ylim(y_limits)
plots.append(h)
titles = ['Observation', '$5\mathrm{M_{J}}$ Model']
for i, ax in enumerate(axes[0][:]):
ax.set_title(titles[i])
bmaj = 0.15
bmin = 0.15
bpa = 27.6
if i == 0:
axes[0][i].set_ylabel('$\Delta$ Dec [\"]')
plot_beam(ax, bmaj, bmin, -bpa, color=b_color[i])
cbar_labels = ['Velocity [km/s]', 'Velocity [km/s]', 'Velocity [km/s]']
b_color = ['black', 'black', 'white']
for i in range(nrows):
for j in range(ncols):
if j == 0:
axes[i][j].set_ylabel('$\Delta$ Dec [\"]')
if i == nrows-1:
axes[i][j].set_xlabel('$\Delta$ RA [\"]')
else:
axes[i][j].xaxis.set_ticklabels('')
axes[i][j].set_xticks(x_ticks)
axes[i][j].set_yticks(y_ticks)
if j == ncols -1:
ax = axes[i][j]
ax_pos = ax.get_position()
size = 0.05
pad = colorbar_kwargs['pad']
width = ax_pos.width * size
height = ax_pos.height
bottom = ax_pos.y0 # + ax_pos.height + pad
left = ax_pos.x0 + ax_pos.width + pad
cax = fig.add_axes((left, bottom, width, height))
fig.colorbar(plots[i], cax=cax, orientation='vertical', label=cbar_labels[i], **colorbar_kwargs)
cax.xaxis.set_ticks_position('top')
cax.xaxis.set_label_position('top')
for i in range(nrows):
for j in range(ncols):
axes[i][j].set_adjustable('box')
axes[i][j].xaxis.set_ticks_position('both')
axes[i][j].xaxis.set_tick_params(direction="in")
axes[i][j].yaxis.set_ticks_position('both')
axes[i][j].yaxis.set_tick_params(direction="in")
axes[i][j].set_aspect('equal')
if j != 0:
axes[i][j].yaxis.set_ticklabels('')
axes[i][j].set_ylabel('')
# plt.axis('equal')
plt.savefig('../Output/S2_Final/Moment/model_comparison_{}.pdf'.format(vel_type), dpi=300)
plt.savefig('../Output/S2_Final/Moment/model_comparison_{}.png'.format(vel_type), dpi=600)
plt.show()