def fit_rotcur(galaxy, vmode):
try:
data = fits.getdata("./fits/%s.%s_model.fits" % (galaxy, vmode))
R = data[0]
V = data[1]
mask = V > 5
R = R[mask]
V = V[mask]
min_vel, max_vel = int(np.nanmin(V)), int(np.nanmax(V))
temp = []
v_max_temp = []
R_turn_temp = []
for i in model:
best_params = fit_RC(R, V, i)
data = best_params[:-1]
Vmax, Rturn = data[0], data[1]
if Vmax > 340: Vmax = 0
if Vmax == 0: Vmax = np.nan
temp.append(Vmax)
temp.append(Rturn)
v_max_temp.append(Vmax)
R_turn_temp.append(Rturn)
ax.plot(R, V, "k-")
ax.plot(R, V, "ks")
ax.plot(R, best_params[-1], label=i)
mean_V, median_V, std_V = np.nanmedian(v_max_temp), np.nanmean(
v_max_temp), np.nanstd(v_max_temp)
mean_R, median_R, std_R = np.nanmedian(R_turn_temp), np.nanmean(
R_turn_temp), np.nanstd(R_turn_temp)
table = [
galaxy, temp[0], temp[1], temp[2], temp[3], temp[4], temp[5],
temp[6], temp[7], temp[8], temp[9], temp[10], temp[11], mean_V,
median_V, std_V, mean_R, median_R, std_R
]
write(table, "manga_vmax_velfit_1.5.%s.csv" % vmode, column=False)
plt.legend(fontsize="xx-small")
ax.set_xlabel("r (arcsec)", fontsize=12, labelpad=0)
ax.set_ylabel('V$_\mathrm{ROT}$ (km/s)', fontsize=12, labelpad=0)
ax.set_ylim(-50, max_vel + 50)
AXIS(ax)
plt.savefig("./vmax_rturn/%s.fit_rotcur.%s.png" % (galaxy, vmode),
dpi=300)
#plt.show()
plt.cla()
return median_V, median_R
except (IOError, OSError):
table = [galaxy, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
write(table, "manga_vmax_velfit_1.5.%s.csv" % vmode, column=False)
return 1, 1
pass
def plot_kin_models(galaxy,
vmode,
vel_ha,
R,
Vrot,
eVrot,
Vrad,
eVrad,
Vtan,
eVtan,
VSYS,
MODEL,
ext,
plot=0,
save=1):
e1, e2, e3 = len(eVrot[0]), len(eVrad[0]), len(eVtan[0])
mask_MODEL = np.divide(MODEL, MODEL)
MODEL_copy = np.copy(MODEL - VSYS)
MODEL = MODEL * np.divide(vel_ha, vel_ha)
MODEL = MODEL - VSYS
vel_ha = vel_ha - VSYS
fig = plt.figure(figsize=(6, 2))
gs2 = GridSpec(1, 3)
gs2.update(left=0.045,
right=0.62,
top=0.815,
hspace=0.01,
bottom=0.135,
wspace=0.)
ax = plt.subplot(gs2[0, 0])
ax1 = plt.subplot(gs2[0, 1])
ax2 = plt.subplot(gs2[0, 2])
#cmap = plt.cm.get_cmap('bwr')
#cmap = c_map.reversed()
vmin = abs(np.nanmin(MODEL))
vmax = abs(np.nanmax(MODEL))
max_vel = np.nanmax([vmin, vmax])
vmin = -(max_vel // 50 + 1) * 50
vmax = (max_vel // 50 + 1) * 50
im0 = ax.imshow(vel_ha,
cmap=cmap,
origin="lower",
vmin=vmin,
vmax=vmax,
aspect="auto",
extent=ext,
interpolation="nearest")
im1 = ax1.imshow(MODEL_copy,
cmap=cmap,
origin="lower",
aspect="auto",
vmin=vmin,
vmax=vmax,
extent=ext,
interpolation="nearest")
residual = (vel_ha - MODEL)
im2 = ax2.imshow(residual,
cmap=cmap,
origin="lower",
aspect="auto",
vmin=-50,
vmax=50,
extent=ext,
interpolation="nearest")
AXIS(ax, tickscolor="k")
AXIS(ax1, tickscolor="k", remove_yticks=True)
AXIS(ax2, tickscolor="k", remove_yticks=True)
ax.set_ylabel('$\mathrm{ \Delta Dec~(pix)}$', fontsize=8, labelpad=0)
ax.set_xlabel('$\mathrm{ \Delta RA~(pix)}$', fontsize=8, labelpad=0)
ax1.set_xlabel('$\mathrm{ \Delta RA~(pix)}$', fontsize=8, labelpad=0)
ax2.set_xlabel('$\mathrm{ \Delta RA~(pix)}$', fontsize=8, labelpad=0)
ax.text(0.05, 1.01, "$\mathrm{vlos}$", fontsize=7, transform=ax.transAxes)
ax1.text(0.05,
1.01,
"$\mathrm{model}$",
fontsize=7,
transform=ax1.transAxes)
ax2.text(0.05,
1.01,
"$\mathrm{residual}$",
fontsize=7,
transform=ax2.transAxes)
#ax.set_facecolor('#e8ebf2')
#ax1.set_facecolor('#e8ebf2')
#ax2.set_facecolor('#e8ebf2')
gs2 = GridSpec(1, 1)
gs2.update(left=0.68, right=0.995, top=0.815, bottom=0.135)
ax3 = plt.subplot(gs2[0, 0])
#from plot_simulated_model import plot_true
#plot_true(galaxy,vmode,ax3)
if vmode == "circular":
ax3.plot(R,
Vrot,
color="k",
linestyle='-',
alpha=0.6,
linewidth=0.8,
label="$\mathrm{V_{t}}$")
if e1 > 0:
ax3.errorbar(R,
Vrot,
yerr=[eVrot[0], eVrot[1]],
fmt='o',
color="k",
markersize=1,
elinewidth=0.6,
capsize=1.5)
ax3.fill_between(R,
Vrot - eVrot[0],
Vrot + eVrot[1],
color="darkgray",
alpha=0.4)
#error_bar(ax3,R,Vrot, eVrot[0],eVrot[1],color = "y")
if vmode == "radial":
ax3.plot(R,
Vrot,
color="k",
linestyle='-',
alpha=0.6,
linewidth=0.8,
label="$\mathrm{V_{t}}$")
if e1 > 0:
ax3.errorbar(R,
Vrot,
yerr=[eVrot[0], eVrot[1]],
fmt='o',
color="k",
markersize=1.5,
elinewidth=0.6,
capsize=1.5)
ax3.fill_between(R,
Vrot - eVrot[0],
Vrot + eVrot[1],
color="darkgray",
alpha=0.4)
#error_bar(ax3,R,Vrot, eVrot[0],eVrot[1],color = "darkgray")
ax3.plot(R,
Vrad,
color="orange",
linestyle='-',
alpha=0.6,
linewidth=0.8,
label="$\mathrm{V_{r}}$")
if e2 > 0:
ax3.errorbar(R,
Vrad,
yerr=[eVrad[0], eVrad[1]],
fmt='o',
color="k",
markersize=1.5,
elinewidth=0.6,
capsize=1.5)
ax3.fill_between(R,
Vrad - eVrad[0],
Vrad + eVrad[1],
color="orange",
alpha=0.4)
#error_bar(ax3,R,Vrad, eVrad[0],eVrad[1],color = "darkorange")
if vmode == "bisymmetric":
ax3.plot(R,
Vrot,
color="k",
linestyle='-',
alpha=0.6,
linewidth=0.8,
label="$\mathrm{V_{t}}$")
if e1 > 0:
ax3.errorbar(R,
Vrot,
yerr=[eVrot[0], eVrot[1]],
fmt='o',
color="k",
markersize=1.5,
elinewidth=0.6,
capsize=1.5)
ax3.fill_between(R,
Vrot - eVrot[0],
Vrot + eVrot[1],
color="darkgray",
alpha=0.4)
ax3.plot(R,
Vrad,
color="orange",
linestyle='-',
alpha=0.6,
linewidth=0.8,
label="$\mathrm{V_{2,r}}$")
if e2 > 0:
ax3.errorbar(R,
Vrad,
yerr=[eVrad[0], eVrad[1]],
fmt='o',
color="orange",
markersize=1.5,
elinewidth=0.6,
capsize=1.5)
ax3.fill_between(R,
Vrad - eVrad[0],
Vrad + eVrad[1],
color="orange",
alpha=0.4)
ax3.plot(R,
Vtan,
color="skyblue",
linestyle='-',
alpha=0.6,
linewidth=0.8,
label="$\mathrm{V_{2,t}}$")
if e3 > 0:
ax3.errorbar(R,
Vtan,
yerr=[eVtan[0], eVtan[1]],
fmt='o',
color="dodgerblue",
markersize=1.5,
elinewidth=0.6,
capsize=1.5)
ax3.fill_between(R,
Vtan - eVtan[0],
Vtan + eVtan[1],
color="dodgerblue",
alpha=0.4)
ax3.legend(loc="center",
fontsize=6.5,
bbox_to_anchor=(0, 1, 1, 0.1),
ncol=3,
frameon=False)
vels = [Vrot, Vrad, Vtan]
max_vel, min_vel = int(np.nanmax(vels)), int(np.nanmin(vels))
min_vel = abs(min_vel)
#ax3.set_ylim(min_vel-50,max_vel+50)
ax3.set_ylim(-50 * (min_vel // 50) - 50, 50 * (max_vel // 50) + 80)
ax3.plot([0, np.nanmax(R)], [0, 0],
color="k",
linestyle='-',
alpha=0.6,
linewidth=0.5)
ax3.set_xlabel('$\mathrm{r~(arcsec)}$', fontsize=8, labelpad=0)
ax3.set_ylabel('$\mathrm{V_{rot}~(km~s^{-1})}$', fontsize=8, labelpad=0)
ax3.set_facecolor('#e8ebf2')
AXIS(ax3, tickscolor="k")
# Make a plot with major ticks that are multiples of 10 and minor ticks that
# are multiples of 5. Label major ticks with '%d' formatting but don't label
# minor ticks.
if np.nanmax(R) // 10 > 1:
ax3.xaxis.set_major_locator(MultipleLocator(10))
ax3.xaxis.set_major_formatter(FormatStrFormatter('%d'))
# For the minor ticks, use no labels; default NullFormatter.
ax3.xaxis.set_minor_locator(MultipleLocator(2))
else:
ax3.xaxis.set_major_locator(MultipleLocator(2))
ax3.xaxis.set_major_formatter(FormatStrFormatter('%d'))
# For the minor ticks, use no labels; default NullFormatter.
ax3.xaxis.set_minor_locator(MultipleLocator(1))
if np.nanmax(R) // 100 > 1:
ax3.xaxis.set_major_locator(MultipleLocator(200))
ax3.xaxis.set_major_formatter(FormatStrFormatter('%d'))
# For the minor ticks, use no labels; default NullFormatter.
ax3.xaxis.set_minor_locator(MultipleLocator(100))
if np.nanmax(Vrot) // 100 > 1:
ax3.yaxis.set_major_locator(MultipleLocator(100))
ax3.yaxis.set_major_formatter(FormatStrFormatter('%d'))
# For the minor ticks, use no labels; default NullFormatter.
ax3.yaxis.set_minor_locator(MultipleLocator(20))
else:
ax3.yaxis.set_major_locator(MultipleLocator(50))
ax3.yaxis.set_major_formatter(FormatStrFormatter('%d'))
# For the minor ticks, use no labels; default NullFormatter.
ax3.yaxis.set_minor_locator(MultipleLocator(25))
cb(im1,
ax,
orientation="horizontal",
colormap=cmap,
bbox=(0.5, 1.135, 1, 1),
width="100%",
height="5%",
label_pad=-17,
label="$\mathrm{(km~s^{-1})}$",
font_size=6)
cb(im2,
ax2,
orientation="horizontal",
colormap=cmap,
bbox=(0, 1.135, 1, 1),
width="100%",
height="5%",
label_pad=-17,
label="$\mathrm{(km~s^{-1})}$",
font_size=6)
if save == 1 and plot == 1:
plt.savefig("./plots/kin_%s_model_%s.png" % (vmode, galaxy), dpi=300)
plt.show()
plt.clf()
else:
if plot == 1:
plt.show()
plt.clf()
if save == 1:
plt.savefig("./plots/kin_%s_model_%s.png" % (vmode, galaxy),
dpi=300)
plt.clf()
def fit_rotcur(galaxy,vmode,e_Vrot,survey):
try:
data = fits.getdata("./fits/%s.%s_model.fits"%(galaxy,vmode))
R = data[0]
V = data[1]
R_plot = np.linspace(0.1,np.nanmax(R),100)
min_vel,max_vel = int(np.nanmin(V)),int(np.nanmax(V))
temp = []
v_max_temp = []
R_turn_temp = []
for_table = [galaxy]
for i in model:
best_params = fit_RC(R,V,i)
data = best_params[:-1]
Vmax,Rturn = data[0],data[1]
if Vmax > 340: Vmax = 0
if Vmax == 0: Vmax = np.nan
temp.append(Vmax)
temp.append(Rturn)
for_table.append(Vmax)
for_table.append(Rturn)
v_max_temp.append(Vmax)
R_turn_temp.append(Rturn)
ax.plot(R,V,"k-",alpha = 0.6, linewidth=0.8,zorder = 100)
ax.scatter(R,V, marker='s', c = "k",s = 5,zorder = 100)
ax.fill_between(R, V-e_Vrot[0], V+e_Vrot[1], color = "deepskyblue", alpha = 0.4)
ax.plot(R_plot,best_params[-1],label = i,linewidth=0.5)
#The average values for Vmax and Rturn
mean_Vmax,median_Vmax,std_Vmax = np.nanmedian(v_max_temp),np.nanmean(v_max_temp),np.nanstd(v_max_temp)
mean_Rt,median_Rt,std_Rt = np.nanmedian(R_turn_temp),np.nanmean(R_turn_temp),np.nanstd(R_turn_temp)
for_table.extend([mean_Vmax,median_Vmax,std_Vmax,mean_Rt,median_Rt,std_Rt])
table = for_table
if survey != "":
table_name = "vmax_out_params.%s_model.%s.csv"%(vmode,survey)
#write(table,table_name,column = False)
else:
table_name = "vmax_out_params.%s_model.%s.csv"%(vmode,galaxy)
# write header of table
if path.exists(table_name) == True:
pass
else:
hdr = ["object"]
for i in model: hdr.extend(["Vmax_%s_model"%(i), "Rturn_%s_model"%(i)])
hdr.extend(["mean_Vmax","median_Vmax","std_Vmax","mean_Rt","median_Rt","std_Rt"])
write(hdr,table_name,column = False)
write(table,table_name,column = False)
plt.legend( fontsize = "xx-small")
ax.set_xlabel("$\mathrm{r~(arcsec)}$", fontsize = 8,labelpad = 0)
ax.set_ylabel("$\mathrm{V_{rot}~(km~s^{-1})}$",fontsize=8,labelpad = 0)
ax.set_ylim(-50,max_vel+50)
AXIS(ax)
plt.savefig("./vmax_rturn/%s.fit_rotcur.%s.png"%(galaxy,vmode),dpi = 300)
#plt.show()
plt.cla()
return median_Vmax,median_Rt
except(IOError, OSError):
table = [galaxy, 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
if survey != "":
write(table,"vmax_out_params.%s_model.%s.csv"%(vmode,survey),column = False)
else:
write(table,"vmax_out_params.%s_model.%s.csv"%(vmode,galaxy),column = False)
return 1,1
pass
def rotcur(galaxy, z_star, PA, INC, X0, Y0):
p1, p2 = [pos for pos, char in enumerate(galaxy) if char == "-"]
direc = galaxy[p1 + 1:p2]
hdu0 = fits.open("%s/%s/%s.Pipe3D.cube.fits.gz" % (path, direc, galaxy))
#data_extensions = hdu0[2].data
data = hdu0[3].data
hdr = hdu0[0].header
pixel_size = abs(hdr["CD2_2"] * 3600)
[nz, ny, nx] = data.shape
ext = [nx / 2., -nx / 2, -ny / 2., ny / 2.]
ha_flux = data[45]
e_ha = data[249]
mask_SN = SN(ha_flux, e_ha, 5)
M_ones = np.ones((ny, nx)) * mask_SN
mask_good = np.ones((ny, nx)) * mask_SN
for i in range(nx):
for j in range(ny):
check_ones = M_ones[j - 1:j + 2, i - 1:i + 2]
not_ones = np.nansum(check_ones)
if not_ones >= 7:
mask_good[j][i] = 1
else:
mask_good[j][i] = np.nan
if vel == "gas":
vel_ha = data[102]
e_vel_ha = data[330]
#hdu = fits.open("%s/%s.ELINES.cube.fits.gz"%(path,galaxy))
#data = hdu[0].data
#vel_ha =data[0]
#e_vel_ha =data[0]
if vel == "stars":
e_vel_ha = data[300]
hdu = fits.open("%s/%s.SSP.cube.fits.gz" % (path, galaxy))
ssp = hdu[0].data
#ssp = pyfits.getdata("./CALIFA/dataproducts/%s.SSP.cube.fits.gz"%galaxy)
vel_ha = ssp[13]
#e_vel_ha= ssp[14]
e_vel_ha[e_vel_ha > 10] = np.nan
mask_vel = np.divide(e_vel_ha, e_vel_ha)
vel_ha = vel_ha * mask_vel
vel_ha[vel_ha == 0] = np.nan
XK, YK, VSYS, e_vsys = KC(vel_ha, X0, Y0)
VSYS = z_star * c
"""
print ("...................................................................................................")
print ("..............................%s............................................................"%galaxy)
print ("........................Examine initial values: ...................................................")
print ("Guess : PA,INC,X0,Y0:", PA,INC,XK,YK,VSYS)
print ("...................................................................................................")
print ("...................................................................................................")
print ("................... step 1: All free parameters: estiamate X0,Y0, Vsys ..........................." )
print ("...................................................................................................")
"""
nrings = int(36)
guess = [50, 10, PA, INC, XK, YK, VSYS]
vary = [True, True, True, True, False, False, True]
mode_ring = ["pixel", "arcsec", "broad"]
mode_ring = ["pixel"]
def first():
pa, r, x0, y0, vsys = [], [], [], [], []
pa2, inc2, x02, y02, vsys2 = [], [], [], [], []
delta_arcsec = int(2 / 1)
median_pa, median_inc, median_vsys, sigma_pa, sigma_inc, sigma_vsys, R, vrot, vrad, model = RC_sigma(
vel_ha,
e_vel_ha,
nrings,
guess,
vary,
delta=delta_arcsec,
ring="pixel",
mode="bisymetric",
iter=1,
model=True,
pixel_scale=pixel_size)
return median_pa, median_inc, median_vsys, sigma_pa, sigma_inc, sigma_vsys, R, vrot, vrad, model
median_pa, median_inc, median_vsys, sigma_pa, sigma_inc, sigma_vsys, R, vrot, vr2, model = first(
)
def sec():
vary = [True, True, True, True, False, False, True]
guess = [60, 0, median_pa, median_inc, XK, YK, median_vsys]
sigma = [0, 0, 2 * sigma_pa, 2 * sigma_inc, 0, 0, 2 * sigma_vsys]
delta_arcsec = int(2 / 1)
vr_e, vr20_e, pa_e, inc_e, vsys_e = RC_sigma_rnd2(
vel_ha,
e_vel_ha,
nrings,
guess,
vary,
sigma,
mode="bisymetric",
delta=delta_arcsec,
ring="pixel",
iter=10,
ring_position=R,
pixel_scale=pixel_size)
return vr_e, vr20_e, pa_e, inc_e, vsys_e
def emcee():
vary = [True, True, True, True, False, False, True]
guess = [60, 0, pa_med, inc_med, XK, YK, vsys_med]
sigma = [0, 0, 5 * e_pa, 5 * e_inc, 0, 0, 5 * e_vsys]
delta_arcsec = int(2 / 1)
print("sigma:", sigma)
a = RC_emcee(vel_ha,
e_vel_ha,
nrings,
guess,
vary,
sigma,
mode="bisymetric",
delta=delta_arcsec,
ring="pixel",
iter=5,
pixel_scale=pixel_size)
return a
#c = emcee()
e_vr, e_vr2, e_pa, e_inc, e_vsys = sec()
mask_model = np.divide(model, model)
fig = plt.figure(figsize=(6, 2))
gs2 = GridSpec(1, 3)
gs2.update(left=0.06,
right=0.62,
top=0.83,
hspace=0.01,
bottom=0.15,
wspace=0.)
ax = plt.subplot(gs2[0, 0])
ax1 = plt.subplot(gs2[0, 1])
ax2 = plt.subplot(gs2[0, 2])
im0 = ax.imshow(vel_ha - median_vsys,
cmap=califa,
origin="l",
vmin=-250,
vmax=250,
aspect="auto",
extent=ext,
interpolation="nearest")
im2 = ax1.imshow(model,
cmap=califa,
origin="l",
aspect="auto",
vmin=-250,
vmax=250,
extent=ext,
interpolation="nearest")
residual = (vel_ha * mask_model - median_vsys) - model
im2 = ax2.imshow(residual,
cmap=califa,
origin="l",
aspect="auto",
vmin=-50,
vmax=50,
extent=ext,
interpolation="nearest")
AXIS(ax, tickscolor="k")
AXIS(ax1, tickscolor="k", remove_yticks=True)
AXIS(ax2, tickscolor="k", remove_yticks=True)
ax.set_ylabel(r'$\Delta$ Dec (pix)', fontsize=8, labelpad=0)
ax.set_xlabel(r'$\Delta$ RA (pix)', fontsize=8, labelpad=0)
ax1.set_xlabel(r'$\Delta$ RA (pix)', fontsize=8, labelpad=0)
ax2.set_xlabel(r'$\Delta$ RA (pix)', fontsize=8, labelpad=0)
ax.text(0.05, 0.9, "VLOS", fontsize=7, transform=ax.transAxes)
ax1.text(0.05, 0.9, "MODEL", fontsize=7, transform=ax1.transAxes)
ax2.text(0.05, 0.9, "RESIDUAL", fontsize=7, transform=ax2.transAxes)
ax.set_facecolor('#e8ebf2')
ax1.set_facecolor('#e8ebf2')
ax2.set_facecolor('#e8ebf2')
gs2 = GridSpec(1, 1)
gs2.update(left=0.68, right=0.995, top=0.83, bottom=0.15)
ax3 = plt.subplot(gs2[0, 0])
ax3.errorbar(R, vrot, yerr=e_vr, fmt='s', color="k", markersize=3)
ax3.plot(R, vrot, color="k", linestyle='-', alpha=0.6)
ax3.plot(R, vr2, color="skyblue", linestyle='-', alpha=0.6)
ax3.errorbar(R, vr2, yerr=e_vr2, fmt='s', color="skyblue", markersize=3)
#ax3.set_ylim(-50,300)
ax3.set_ylim(int(np.nanmin(vr2)) - 20, int(np.nanmax(vrot)) + 20)
ax3.plot([0, np.nanmax(R)], [0, 0], color="k", linestyle='-', alpha=0.6)
ax3.set_xlabel('r (arcsec)', fontsize=8, labelpad=0)
ax3.set_ylabel('V$_\mathrm{ROT}$ (km/s)', fontsize=8, labelpad=0)
ax3.set_facecolor('#e8ebf2')
AXIS(ax3, tickscolor="k")
cb(im0,
ax,
orientation="horizontal",
colormap=califa,
bbox=(0, 1.12, 1, 1),
width="100%",
height="5%",
label_pad=-23,
label="(km/s)",
font_size=7)
cb(im2,
ax2,
orientation="horizontal",
colormap=califa,
bbox=(0, 1.12, 1, 1),
width="100%",
height="5%",
label_pad=-23,
label="(km/s)",
font_size=7)
plt.savefig("./plots/kin_model_%s.png" % galaxy, dpi=300)
#plt.savefig("./kin_model_%s.pdf"%galaxy)
plt.clf()
#plt.show()
try:
from fit_rotcurve import Rturn_Vmax
vmax, r_turn, beta, gamma = Rturn_Vmax(R, vrot)
def vrot_fit(r_sky, v_max, R_turn, beta, gamma):
x = R_turn / r_sky
A = (1 + x)**beta
B = (1 + x**gamma)**(1. / gamma)
v = v_max * A / B
return v
fig = plt.figure(figsize=(2.5, 2.5))
ax = plt.subplot(111)
ax.scatter(R, vrot, s=10, marker="o", c="k")
ax.plot(R, vrot_fit(R, vmax, r_turn, beta, gamma), "b-", alpha=0.3)
AXIS(ax, tickscolor="k")
ax.set_xlabel('r (arcsec)', fontsize=8, labelpad=0)
ax.set_ylabel('V$_\mathrm{ROT}$ (km/s)', fontsize=8, labelpad=0)
ax.set_ylim(-5, int(np.nanmax(vrot)) + 20)
ax.set_facecolor('#e8ebf2')
plt.savefig("./vflat/vflat_r_turn_%s.png" % galaxy, dpi=300)
#plt.savefig("./vflat_rotcur_%s.pdf"%galaxy)
plt.clf()
#plt.show()
return galaxy, XK, YK, median_pa, sigma_pa, median_inc, sigma_inc, median_vsys, sigma_vsys, vmax, r_turn, beta, gamma
except (1):
return galaxy, XK, YK, median_pa, sigma_pa, median_inc, sigma_inc, median_vsys, sigma_vsys, 0, 0, 0, 0
def plot_kin_models(galaxy,
vmode,
vel_ha,
R,
Vrot,
Vrad,
Vtan,
VSYS,
MODEL,
ext,
plot=0,
save=1):
mask_MODEL = np.divide(MODEL, MODEL)
fig = plt.figure(figsize=(6, 2))
gs2 = GridSpec(1, 3)
gs2.update(left=0.06,
right=0.62,
top=0.83,
hspace=0.01,
bottom=0.15,
wspace=0.)
ax = plt.subplot(gs2[0, 0])
ax1 = plt.subplot(gs2[0, 1])
ax2 = plt.subplot(gs2[0, 2])
im0 = ax.imshow(vel_ha - VSYS,
cmap=califa,
origin="lower",
vmin=-250,
vmax=250,
aspect="auto",
extent=ext,
interpolation="nearest")
im2 = ax1.imshow(MODEL,
cmap=califa,
origin="lower",
aspect="auto",
vmin=-250,
vmax=250,
extent=ext,
interpolation="nearest")
residual = (vel_ha * mask_MODEL - VSYS) - MODEL
im2 = ax2.imshow(residual,
cmap=califa,
origin="lower",
aspect="auto",
vmin=-50,
vmax=50,
extent=ext,
interpolation="nearest")
AXIS(ax, tickscolor="k")
AXIS(ax1, tickscolor="k", remove_yticks=True)
AXIS(ax2, tickscolor="k", remove_yticks=True)
ax.set_ylabel(r'$\Delta$ Dec (pix)', fontsize=8, labelpad=0)
ax.set_xlabel(r'$\Delta$ RA (pix)', fontsize=8, labelpad=0)
ax1.set_xlabel(r'$\Delta$ RA (pix)', fontsize=8, labelpad=0)
ax2.set_xlabel(r'$\Delta$ RA (pix)', fontsize=8, labelpad=0)
ax.text(0.05, 0.9, "VLOS", fontsize=7, transform=ax.transAxes)
ax1.text(0.05, 0.9, "MODEL", fontsize=7, transform=ax1.transAxes)
ax2.text(0.05, 0.9, "RESIDUAL", fontsize=7, transform=ax2.transAxes)
ax.set_facecolor('#e8ebf2')
ax1.set_facecolor('#e8ebf2')
ax2.set_facecolor('#e8ebf2')
gs2 = GridSpec(1, 1)
gs2.update(left=0.68, right=0.995, top=0.83, bottom=0.15)
ax3 = plt.subplot(gs2[0, 0])
ax3.plot(R,
Vrot,
color="k",
linestyle='-',
alpha=0.6,
label="V$_\mathrm{circ}$")
ax3.scatter(R, Vrot, color="k", s=5, marker="s")
#ax3.errorbar(R,Vrot, yerr=e_vr, fmt='s', color = "k",markersize = 3, label = "V_\mathrm{circ}")
ax3.plot(R,
Vrad,
color="orange",
linestyle='-',
alpha=0.6,
label="V$_\mathrm{rad}$")
ax3.scatter(R, Vrad, color="orange", s=5, marker="s")
#ax3.errorbar(R,Vrad, yerr=e_Vrad, fmt='s', color = "orange",markersize = 3)
ax3.plot(R,
Vtan,
color="skyblue",
linestyle='-',
alpha=0.6,
label="V$_\mathrm{tan}$")
ax3.scatter(R, Vtan, color="skyblue", s=5, marker="s")
#ax3.errorbar(R,Vtan, yerr=e_Vtan, fmt='s', color = "skyblue",markersize = 3)
ax3.legend(loc="center",
fontsize=6.5,
bbox_to_anchor=(0, 1, 1, 0.1),
ncol=3,
frameon=False)
vels = [Vrot, Vrad, Vtan]
max_vel, min_vel = int(np.nanmax(vels)), int(np.nanmin(vels))
ax3.set_ylim(min_vel - 50, max_vel + 50)
ax3.plot([0, np.nanmax(R)], [0, 0], color="k", linestyle='-', alpha=0.6)
ax3.set_xlabel('r (arcsec)', fontsize=8, labelpad=0)
ax3.set_ylabel('V$_\mathrm{ROT}$ (km/s)', fontsize=8, labelpad=0)
ax3.set_facecolor('#e8ebf2')
AXIS(ax3, tickscolor="k")
cb(im0,
ax,
orientation="horizontal",
colormap=califa,
bbox=(0, 1.12, 1, 1),
width="100%",
height="5%",
label_pad=-23,
label="(km/s)",
font_size=7)
cb(im2,
ax2,
orientation="horizontal",
colormap=califa,
bbox=(0, 1.12, 1, 1),
width="100%",
height="5%",
label_pad=-23,
label="(km/s)",
font_size=7)
if save == 1 and plot == 1:
plt.savefig("./plots/kin_%s_model_%s.png" % (vmode, galaxy), dpi=300)
plt.show()
plt.clf()
else:
if plot == 1:
plt.show()
plt.clf()
if save == 1:
plt.savefig("./plots/kin_%s_model_%s.png" % (vmode, galaxy),
dpi=300)
plt.clf()