def f_plot(**kwargs):
args = read_kwargs(**kwargs)
C.debug_var(args.debug, kwargs = kwargs)
H = args.H
mask = args.x.mask | args.y.mask
xm = np.ma.masked_array(args.x, mask = mask)
ym = np.ma.masked_array(args.y, mask = mask)
zm = np.ma.masked_array(args.z, mask = mask)
f = plt.figure()
f.set_size_inches(10, 8)
ax = f.gca()
plotScatterColorAxis(f, xm, ym, zm, args.xlabel, args.ylabel, args.zlabel, args.xlim, args.ylim, args.zlim, contour = args.contour, run_stats = args.run_stats, OLS = args.OLS)
ax.xaxis.set_major_locator(MultipleLocator(args.x_major_locator))
ax.xaxis.set_minor_locator(MultipleLocator(args.x_minor_locator))
ax.yaxis.set_major_locator(MultipleLocator(args.y_major_locator))
ax.yaxis.set_minor_locator(MultipleLocator(args.y_minor_locator))
txt = r'DGR = $10^{%.2f}$' % (np.log10(args.DGR))
plot_text_ax(ax, txt, 0.02, 0.98, 14, 'top', 'left')
ax.grid(which = 'major')
f.suptitle(r'%d galaxies - tSF:%.2fMyr $x_Y$(min):%.0f%% $\tau_V^\star$(min):%.2f $\tau_V^{neb}$(min):%.2f $\epsilon\tau_V^{neb}$(max):%.2f' % (H.N_gals, (args.tSF / 1e6), H.xOkMin * 100., H.tauVOkMin, H.tauVNebOkMin, H.tauVNebErrMax), fontsize=14)
f.savefig(args.fname)
plt.close(f)
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
if __name__ == '__main__':
Zsun = 0.019
t_init_gal = time.clock()
args = parser_args()
debug = args.debug
iT = args.itSF
H = C.H5SFRData(args.hdf5)
paths = C.CALIFAPaths()
C.debug_var(debug, args = args)
if (len(np.where(H.califaIDs == args.califaID)[0]) == 0):
exit('<<< plot: %s: no data in HDF5 file.' % args.califaID)
K = C.read_one_cube(args.califaID, EL = True, GP = True)
age = H.tSF__T[iT]
ageMyr = age / 1e6
# Setup elliptical-rings geometry
pa, ba = K.getEllipseParams()
K.setGeometry(pa, ba)
tipos, tipo, tipo_m, tipo_p = C.get_morfologia(args.califaID)
for line in l.linesbpt:
ax.plot(l.x[line], l.y[line], label = line)
ax.text(-0.7, -0.5, 'SF')
ax.text(-0.3, 0.6, 'Seyfert')
ax.text(0.15, -0.5, 'LINER')
C.plot_zbins(
debug = True,
cb = False,
write_N = True,
zmask = None,
f = f,
ax = ax,
x = logN2Ha__g,
y = logO3Hb__g,
z = H.zone_dist_HLR__g,
zlim = zlim,
xlim = (-1.5, 0.5),
ylim = (-1.5, 1.0),
x_major_locator = 1.,
x_minor_locator = 0.2,
y_major_locator = 1.,
y_minor_locator = 0.2,
kwargs_scatter = dict(marker = 'o', s = 10, edgecolor = 'none', alpha = 0.45, label = ''),
xlabel = r'$\log [NII]/H\alpha$',
ylabel = r'$\log [OIII]/H\beta$',
zlabel = r'R (HLR)',
)
ax = plt.subplot2grid(grid_shape, loc = (0, 1))
ax.set_axis_on()
for line in l.linesbpt:
ax.plot(l.x[line], l.y[line], label = line)
help = 'Name of the output PDF file.',
metavar = 'FILENAME',
type = str,
default = default['output'])
parser.add_argument('--bamin', '-B',
help = 'min b/a',
metavar = '',
type = float,
default = default['bamin'])
return parser.parse_args()
if __name__ == '__main__':
args = parser_args()
C.debug_var(args.debug, args = args)
H = C.H5SFRData(args.hdf5)
iT = args.itSF
iU = -1
fnamesuffix = '.pdf'
minR = args.maskradius
if minR is None:
maskRadiusOk__g = np.ones_like(H.zone_dist_HLR__g, dtype = np.bool)
maskRadiusOk__rg = np.ones((H.NRbins, H.N_gals_all), dtype = np.bool)
else:
maxR = H.Rbin__r[-1]
maskRadiusOk__g = (H.zone_dist_HLR__g >= minR) & (H.zone_dist_HLR__g <= maxR)
maskRadiusOk__rg = (np.ones((H.NRbins, H.N_gals_all), dtype = np.bool).T * ((H.RbinCenter__r >= minR) & (H.RbinCenter__r <= maxR))).T
SFR_int = get_h5_data_masked(h5, 'SFR_int__Tg', **dict(dtype = np.float_))
SFR_Ha_int = get_h5_data_masked(h5, 'SFR_Ha_int__Tg', **dict(dtype = np.float_))
SFR_Ha_int_masked = get_h5_data_masked(h5, 'SFR_Ha_int_masked__Tg', **dict(dtype = np.float_))
O3N2_int_masked = get_h5_data_masked(h5, 'O3N2M13_int_masked__Tg', **dict(dtype = np.float_))
O3N2_int = np.array(h5['data/O3N2M13_int__g'].value, dtype = np.float_)
O3N2_int = np.ma.masked_array(O3N2_int, mask = np.isnan(O3N2_int))
sc_kwargs = dict(marker = 'o', s = 50, edgecolor = 'none', label = '')
kwargs_ols_plot = dict(c = 'r', ls = '--', lw = 2, label = 'OLS')
kwargs_ols = dict(c = 'k', pos_x = 0.98, pos_y = 0.01, fs = 12, rms = True, text = True, kwargs_plot = kwargs_ols_plot)
f = plt.figure()
grid_shape = (1, 2)
ax1 = plt.subplot2grid(grid_shape, loc = (0, 0))
ax2 = plt.subplot2grid(grid_shape, loc = (0, 1))
xm1, ym1 = C.ma_mask_xyz(x = O3N2_int, y = np.ma.log10(SFR_int[1]) - np.ma.log10(SFR_Ha_int[1]))
ax1.scatter(xm1, ym1, **sc_kwargs)
_ = plotOLSbisectorAxis(ax1, xm1.compressed(), ym1.compressed(), **kwargs_ols)
ax1.set_xlabel(r'12 + $\log$ O/H M13')
ax1.set_ylabel(r'$\Delta$SFR (syn - $H\alpha$)')
sc = ax2.scatter(np.ma.log10(SFR_int[1]), np.ma.log10(SFR_Ha_int[1]), c = O3N2_int, cmap = 'viridis', **sc_kwargs)
ax2.set_xlabel(r'$\log$ SFR(syn) [$M_\odot\ yr^{-1}$]')
ax2.set_ylabel(r'$\log$ SFR(H$\alpha$) [$M_\odot\ yr^{-1}$]')
f.colorbar(sc)
f.savefig('Zneb_SFR.pdf')
f.subplots_adjust(bottom = 0.15, hspace = 0.15, wspace = 0., right = 0.95, left = 0.10)
f = plt.figure()
grid_shape = (1, 2)
ax1 = plt.subplot2grid(grid_shape, loc = (0, 0))
ax2 = plt.subplot2grid(grid_shape, loc = (0, 1))
tickpos = np.linspace(mtypes[0] + halfbinstep, mtypes[-1] - halfbinstep, Ntype)
aSFRSD__Ttr = np.empty((N_T, Ntype, NRbins), dtype = np.float_)
aSFRSD_Ha__Ttr = np.empty((N_T, Ntype, NRbins), dtype = np.float_)
nbinelem_aSFRSD__Ttr = np.empty((N_T, Ntype, NRbins), dtype = np.int_)
nbinelem_aSFRSD_Ha__Ttr = np.empty((N_T, Ntype, NRbins), dtype = np.int_)
perc_aSFRSD__pTtr = np.ma.masked_all((3, N_T, Ntype, NRbins), dtype = np.float_)
perc_aSFRSD_Ha__pTtr = np.ma.masked_all((3, N_T, Ntype, NRbins), dtype = np.float_)
Ngals__t = np.empty((Ntype), dtype = np.int_)
for it, t in enumerate(mtypes):
mask_morf__g = (morf__g == t)
Ngals__t[it] = np.sum(mask_morf__g)
for iT in range(N_T):
C.debug_var(debug, iT = iT, it = it, NGals = Ngals__t[it])
# G means masked g
aSFRSD__rG = aSFRSD__Trg[iT][:, mask_morf__g]
aSFRSD_Ha__rG = aSFRSD_Ha__Trg[iT][:, mask_morf__g]
for ir in np.where(RbinCenter__r <= 2 + rbinstep)[0]:
for ig in xrange(Ngals__t[it]):
if aSFRSD__rG[ir].mask[ig]:
aSFRSD__rG[ir, ig] = 0
if aSFRSD_Ha__rG[ir].mask[ig]:
aSFRSD_Ha__rG[ir, ig] = 0.
C.debug_var(debug, aSFRSD__rG = aSFRSD__rG)
aSFRSD__Ttr[iT][it] = aSFRSD__rG.mean(axis = 1)
nbinelem_aSFRSD__Ttr[iT][it] = aSFRSD__rG.count(axis = 1)
aSFRSD_Ha__Ttr[iT][it] = aSFRSD_Ha__rG.mean(axis = 1)
Rp, _ = st.pearsonr(xm.compressed(), ym.compressed())
C.debug_var(debug, Rs = Rs)
C.debug_var(debug, Rp = Rp)
return Rs, Rp
if __name__ == '__main__':
try:
h5file = sys.argv[1]
except IndexError:
print 'usage: %s HDF5FILE' % (sys.argv[0])
exit(1)
H = C.H5SFRData(h5file)
tSF__T = H.tSF__T
C.debug_var(debug, tSF__T = tSF__T)
iT__t = np.arange(len(tSF__T))
C.debug_var(debug, iTs = iT__t)
RsSFR = np.empty(iT__t.shape, dtype = np.double)
RpSFR = np.empty(iT__t.shape, dtype = np.double)
RsSFRSD = np.empty(iT__t.shape, dtype = np.double)
RpSFRSD = np.empty(iT__t.shape, dtype = np.double)
RsaSFRSD = np.empty(iT__t.shape, dtype = np.double)
RpaSFRSD = np.empty(iT__t.shape, dtype = np.double)
RsaSFRSDn = np.empty(iT__t.shape, dtype = np.double)
RpaSFRSDn = np.empty(iT__t.shape, dtype = np.double)
RsiSFR = np.empty(iT__t.shape, dtype = np.double)
RpiSFR = np.empty(iT__t.shape, dtype = np.double)
RsiSFRSD = np.empty(iT__t.shape, dtype = np.double)
RpiSFRSD = np.empty(iT__t.shape, dtype = np.double)
fnamesuffix = '.pdf'
if args.slice_gals is None:
N_gals = H.N_gals
gals_slice__g = np.ones_like(H.zone_dist_HLR__g, dtype = np.bool)
gals_slice__rg = np.ones((NRbins, H.N_gals_all), dtype = np.bool)
gals_slice__integr = np.ones(H.califaIDs_all.shape, dtype = np.bool)
gals_txt = ''
else:
gals_slice__g, N_gals = H.get_mask_zones_list(args.slice_gals, return_ngals = True)
gals_slice__rg, N_gals = H.get_mask_radius_list(args.slice_gals, return_ngals = True)
gals_txt = (args.slice_gals).split('/')[-1]
fnamesuffix = '_%s%s' % (gals_txt, fnamesuffix)
#integrated
l_gals, _ = C.sort_gals(args.slice_gals)
l_gals = sorted(l_gals)
gals_slice__integr = np.zeros(H.califaIDs_all.shape, dtype = np.bool)
for g in l_gals:
i = H.califaIDs_all.tolist().index(g)
gals_slice__integr[i] = True
mask__Tg = np.zeros((N_T, H.N_zones__g.sum()), dtype = bool)
for iT in xrange(N_T):
mask__Tg[iT] = mask_zones_iT(iT, H, args.bamin, gals_slice__g)
for iGal, califaID in enumerate(H.califaIDs):
K = C.read_one_cube(califaID, EL = True, GP = True, debug = args.debug, v_run = args.v_run)
tipos, tipo, tipo_m, tipo_p = C.get_morfologia(califaID)
my_type = C.my_morf(tipos)
N_zone = K.N_zone
help = 'Name of the output PDF file.',
metavar = 'FILENAME',
type = str,
default = default['output'])
parser.add_argument('--bamin', '-B',
help = 'min b/a',
metavar = '',
type = float,
default = default['bamin'])
return parser.parse_args()
if __name__ == '__main__':
args = parser_args()
C.debug_var(args.debug, args = args)
H = C.H5SFRData(args.hdf5)
iT = args.itSF
iU = -1
minR = 0
fnamesuffix = '.pdf'
if args.maskradius is None:
maskRadiusOk__g = np.ones_like(H.zone_dist_HLR__g, dtype = np.bool)
maskRadiusOk__rg = np.ones((H.NRbins, H.N_gals_all), dtype = np.bool)
else:
minR = args.maskradius
maskRadiusOk__g = (H.zone_dist_HLR__g >= args.maskradius) & (H.zone_dist_HLR__g <= H.Rbin__r[-1])
maskRadiusOk__rg = (np.ones((H.NRbins, H.N_gals_all), dtype = np.bool).T * (H.RbinCenter__r >= args.maskradius)).T
m_gal_not_OK = np.bitwise_or(m_gal_not_OK, N2_obs.mask)
m_gal_not_OK = np.bitwise_or(m_gal_not_OK, np.ma.less(SN_Ha_obs, 3))
m_gal_not_OK = np.bitwise_or(m_gal_not_OK, np.ma.less(SN_Hb_obs, 3))
m_gal_not_OK = np.bitwise_or(m_gal_not_OK, np.ma.less(SN_O3_obs, 3))
m_gal_not_OK = np.bitwise_or(m_gal_not_OK, np.ma.less(SN_N2_obs, 3))
tau_V_lines = AV_lines * 1. / (2.5 * np.log10(np.exp(1.)))
logO3Hb, logN2Ha, logO3N2 = calc_O3N2(Hb_obs, O3_obs,
Ha_obs, N2_obs,
m_gal_not_OK, tau_V_lines,
correct = True)
logOH_M13 = 8.533 - 0.214 * logO3N2
xm, ym = CALIFAUtils.ma_mask_xyz(x = logOH_M13, y = Zneb_mpa)
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
# f = plt.figure()
# f.set_dpi(100)
# f.set_size_inches(10, 8)
# ax = f.gca()
# ax.scatter(logN2Ha, logO3Hb, marker = '.', s = 1, c = '0.7', edgecolor = 'none', alpha = 0.6, label = '')
# #m_aux = l.maskAbovelinebpt('K01', logN2Ha, logO3Hb)
# ax.scatter(logN2Ha[~(Zneb_mpa.mask | m_aux)], logO3Hb[~(Zneb_mpa.mask | m_aux)], marker = '.', s = 5, c = 'b', edgecolor = 'none', alpha = 0.6, label = '')
# for line in l.linesbpt:
# ax.plot(l.x[line], l.y[line], label = line)
# #axis = [-2.5, 1.0, -1.6, 1.6]
# ax.set_xlim(-2.5, 1.0)
# ax.set_ylim(-1.6, 1.6)
# ax.set_xlabel(r'$\log\ ([NII]\lambda 6584 / H\alpha)$')
f, axArr = plt.subplots(1, 2)
f.set_dpi(100)
f.set_size_inches(14, 8)
ax = f.gca()
i = 0
filename = '%s_%s_%s_%.2fMyr.png' % (xk, yk, zk, tSF / 1e6)
suptitle = r'NGals:%d tSF:%.2f Myr $x_Y$(min):%.0f%% $\tau_V^\star$(min):%.2f $\tau_V^{neb}$(min):%.2f $\epsilon\tau_V^{neb}$(max):%.2f' % (H.N_gals, (tSF / 1e6), H.xOkMin * 100., H.tauVOkMin, H.tauVNebOkMin, H.tauVNebErrMax)
cbarr = [ False, False ]
for Rn in [ 0.5, 1.0 ]:
print '######' , i
x = np.ma.copy(xv['v'])
y = np.ma.copy(yv['v'])
if mask_radius is True:
x[~(H.RbinCenter__r > Rn)] = np.ma.masked
y[~(H.RbinCenter__r > Rn)] = np.ma.masked
xm, ym, zm = CALIFAUtils.ma_mask_xyz(x = x.flatten(), y = y.flatten(), z = H.reply_arr_by_radius(H.morfType_GAL__g).flatten())
zticks_mask = [
np.ma.bitwise_or(np.ma.equal(zm, 9.), np.ma.equal(zm, 9.5)),
np.ma.equal(zm, 10),
np.ma.equal(zm, 10.5),
np.ma.bitwise_or(np.ma.equal(zm, 11.), np.ma.equal(zm, 11.5)),
]
#zticks_mask = [(zm == 9), (zm == 9.5), (zm == 10), (zm == 10.5), (zm == 11.), (zm == 11.5)]
zticks = [9., 9.5, 10, 10.5, 11., 11.5]
zticklabels = ['Sa', 'Sab', 'Sb', 'Sbc', 'Sc', 'Scd']
zbins_colors = ['r', 'g', 'y', 'b']
#zbins_labels = ['Sa + Sab: %d' % len(xm[zticks_mask[0]]), 'Sb: %d' % len(xm[zticks_mask[1]]), 'Sbc: %d' % len(xm[zticks_mask[2]]), 'Sc + Scd: %d' % len(xm[zticks_mask[3]])]
zbins_labels = ['Sa + Sab', 'Sb', 'Sbc', 'Sc + Scd']
#zbins_labels = ['Sa', 'Sab', 'Sb', 'Sbc', 'Sc', 'Scd']
kw = plot_zbins(
return_kwargs = True,
v = np.ma.log10((H.Mcor_GAL__g[..., np.newaxis] * np.ones((20))).T),
label = r'$\log\ M_\star^{GAL}$ [$M_\odot$]',
)
for xk, xv in xaxis.iteritems():
for yk, yv in yaxis.iteritems():
if xk != yk:
tSF = H.tSF__T[iT]
f = plt.figure()
f.set_dpi(100)
f.set_size_inches(14, 8)
ax = f.gca()
i = 0
filename = '%s_%s_%s_%.2fMyr.png' % (xk, yk, zk, tSF / 1e6)
suptitle = r'NGals:%d tSF:%.2f Myr $x_Y$(min):%.0f%% $\tau_V^\star$(min):%.2f $\tau_V^{neb}$(min):%.2f $\epsilon\tau_V^{neb}$(max):%.2f' % (H.N_gals, (tSF / 1e6), H.xOkMin * 100., H.tauVOkMin, H.tauVNebOkMin, H.tauVNebErrMax)
xm, ym, zm = CALIFAUtils.ma_mask_xyz(x = xv['v'], y = yv['v'], z = np.ma.log10((H.Mcor_GAL__g[..., np.newaxis] * np.ones((20))).T))
zticks_mask = [
np.ma.bitwise_and(np.ma.greater_equal(zm, 8.8), np.ma.less(zm, 9.6)),
np.ma.bitwise_and(np.ma.greater_equal(zm, 9.6), np.ma.less(zm, 10.1)),
np.ma.bitwise_and(np.ma.greater_equal(zm, 10.1), np.ma.less(zm, 10.6)),
np.ma.bitwise_and(np.ma.greater_equal(zm, 10.6), np.ma.less(zm, 10.9)),
np.ma.bitwise_and(np.ma.greater_equal(zm, 10.9), np.ma.less(zm, 11.2)),
np.ma.bitwise_and(np.ma.greater_equal(zm, 11.2), np.ma.less(zm, 11.6)),
]
zbins_labels = ['9.6--8.8', '10.1--9.6', '10.6--10.1', '10.9--10.6', '11.2--10.9', '11.6--11.2']
kw = plot_zbins(
return_kwargs = True,
f = f,
ax = ax,
debug = debug,
x = xv['v'],
f.set_size_inches(15,8)
kw = C.plot_zbins(
return_kwargs = True,
f = f,
ax = axArr[0],
debug = True,
x = np.ma.log10(x1),
y = np.ma.log10(y1),
xlabel = x1label,
ylabel = y1label,
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
# z = H.zone_dist_HLR__g,
# zmask = None,
# zlim = [RNuc, 3],
# zlabel = r'R (HLR)',
# cb = None,
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
xlim = [-5, 1],
ylim = [-5, 1],
x_major_locator = 1.,
x_minor_locator = 0.2,
y_major_locator = 1.,
y_minor_locator = 0.2,
ols = True,
spearmanr = True,
kwargs_figure = dict(figsize = (10, 8), dpi = 100),
kwargs_scatter = dict(marker = 'o', s = 10, edgecolor = 'none', alpha = 0.3, label = ''),
kwargs_ols = dict(c = 'k', pos_x = 0.98, pos_y = 0.01, fs = 12, rms = True, text = True),
kwargs_ols_plot = dict(c = 'r', ls = '-', lw = 2, label = 'OLS'),
)
kw['ax'].plot(kw['ax'].get_xlim(), kw['ax'].get_xlim(), ls = '--', label = '', c = 'k')
help = 'initial RDisc value in HLR',
metavar = 'NUM',
type = float,
default = default['maskradius'])
parser.add_argument('--output', '-o',
help = 'Name of the output PDF file.',
metavar = 'FILENAME',
type = str,
default = default['output'])
return parser.parse_args()
if __name__ == '__main__':
args = parser_args()
C.debug_var(args.debug, args = args)
H = C.H5SFRData(args.hdf5)
iT = args.itSF
iU = -1
minR = 0
if args.maskradius is None:
maskRadiusOk__g = np.ones_like(H.zone_dist_HLR__g, dtype = np.bool)
maskRadiusOk__rg = np.ones((H.NRbins, H.N_gals_all), dtype = np.bool)
else:
minR = args.maskradius
maskRadiusOk__g = (H.zone_dist_HLR__g >= args.maskradius) & (H.zone_dist_HLR__g <= H.Rbin__r[-1])
maskRadiusOk__rg = (np.ones((H.NRbins, H.N_gals_all), dtype = np.bool).T * (H.RbinCenter__r >= args.maskradius)).T
print '<<< %s galaxy: miss gasprop file' % califaID
return 2, False
# Problem in FITS file
return 0, True
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
if __name__ == '__main__':
# Saving the initial time
t_init_prog = time.clock()
# Parse arguments
args = parser_args(sys.argv[0])
C.debug_var(True, args = args.__dict__)
Zsun = 0.019
# Creating radial bins.
Rbin__r = np.arange(args.rbinini, args.rbinfin + args.rbinstep, args.rbinstep)
RbinCenter__r = (Rbin__r[:-1] + Rbin__r[1:]) / 2.0
NRbins = len(RbinCenter__r)
RColor = [ 'r', 'y', 'b', 'k' ]
RRange = [ .5, 1., 1.5, 2. ]
Rbin_oneHLR = [1. - args.rbinstep, 1. + args.rbinstep]
# Reading galaxies file,
gals, _ = C.sort_gals(gals = args.gals_filename, order = 1)
N_gals = len(gals)
maxGals = None
'logWHaWHbR' : dict(lim = [-0., 0.8]),
'tauVdiffR' : dict(lim = [-0.75, 1.5]),
'tauVRatioR' : dict(lim = [0., 6.]),
'baR' : dict(lim = [0, 1.]),
}
xkeys = [ 'RadDist', 'morfTypeR', 'atfluxR', 'alogZmassR', 'logO3N2S06R', 'logMcorSDR', 'xYR', 'logWHaWHbR', 'tauVdiffR', 'tauVRatioR', 'baR' ]
for iT in iT_values:
tSF = H.tSF__T[iT]
xk, xv = H.get_plot_dict(iT = iT, iU = -1, key = 'logtauVR')
yk, yv = H.get_plot_dict(iT = iT, iU = -1, key = 'alogSFRSDR')
xname = H.get_plot_dict(iT = iT, iU = -1)[xk[:-1]]['legendname']
yname = H.get_plot_dict(iT = iT, iU = -1)[yk[1:-1]]['legendname']
xm, ym = C.ma_mask_xyz(xv['v'], yv['v'])
a, b, sig_a, sig_b = OLS_bisector(xm, ym)
R = ym - (a * xm + b)
Yrms = R.std()
Yrms_str = r' : $y_{rms}$:%.2f' % Yrms
if b > 0:
txt_y = r'$y_{OLS}$ = %.2f %s + %.2f %s' % (yname, a, xname, b, Yrms_str)
else:
txt_y = r'$y_{OLS}\ \equiv$ %s = %.2f %s - %.2f %s' % (yname, a, xname, b * -1., Yrms_str)
C.debug_var(debug, txt_y = txt_y)
for xk in xkeys:
fnamepref = 'SKdevOLS_%s' % xk
if xk != 'RadDist':
_, xv = H.get_plot_dict(iT = iT, iU = -1, key = xk)
xv.update(updates.get(xk, {}))
else:
continue
xv.update(dict(limprc = [0, 100]))
yv.update(dict(limprc = [0, 100]))
xv.update(updates[xk])
yv.update(updates[yk])
C.plot_zbins(
debug = debug,
x = xv['v'],
y = yv['v'],
xlim = xv['lim'],
ylim = yv['lim'],
xlabel = xv['label'],
ylabel = yv['label'],
running_stats = True,
rs_percentiles = True,
rs_errorbar = False,
rs_gaussian_smooth = True,
rs_gs_fwhm = 4.,
kwargs_figure = dict(figsize = (10, 8), dpi = 100),
kwargs_scatter = dict(marker = 'o', s = 10, edgecolor = 'none', alpha = 0.5, label = ''),
kwargs_plot_rs = dict(c = 'k', lw = 2, label = 'Median (run. stats)'),
kwargs_suptitle = dict(fontsize = 12),
kwargs_legend = dict(fontsize = 12, loc = 'best'),
suptitle = r'NGals:%d tSF:%.2f Myr $x_Y$(min):%.0f%% $\tau_V^\star$(min):%.2f $\tau_V^{neb}$(min):%.2f $\epsilon\tau_V^{neb}$(max):%.2f' % (H.N_gals, (tSF / 1e6), H.xOkMin * 100., H.tauVOkMin, H.tauVNebOkMin, H.tauVNebErrMax),
filename = filename,
)
mask = []
ba = H.reply_arr_by_radius(H.ba_GAL__g)
balimsup = [0.39, 0.63, 1.]
titles = [
# Sebas
SFR_int__Tg = np.ma.masked_all((N_T, N_gals), dtype=np.float_)
SFR_Ha_int__Tg = np.ma.masked_all((N_T, N_gals), dtype=np.float_)
SFR_Ha_int_masked__Tg = np.ma.masked_all((N_T, N_gals), dtype=np.float_)
O3N2M13_int__g = np.ma.masked_all((N_gals), dtype=np.float_)
O3N2M13_int_masked__Tg = np.ma.masked_all((N_T, N_gals), dtype=np.float_)
morf__g = np.ma.masked_all((N_gals), dtype=np.int_)
N_zones__g = np.ma.masked_all((N_gals), dtype=np.int_)
N_zones_notmasked__Tg = np.ma.masked_all((N_T, N_gals), dtype=np.int_)
# automatically read PyCASSO and EmLines data cubes.
EL = True
baseCode = "Bgsd6e"
for iGal, K in C.loop_cubes(
gals.tolist(), imax=maxGals, EL=EL, GP=args.gasprop, v_run=args.v_run, baseCode=baseCode
):
# for iGal in xrange(len(gals)):
t_init_gal = time.clock()
califaID = gals[iGal]
sit, verify = verify_files(K, califaID, EL=EL, GP=args.gasprop)
if verify is not True:
print "<<< ", califaID, sit
if sit == 1:
K.close()
elif sit == 2:
K.EL.close()
K.close()
continue
for i in range(Nres_bins):
f3.write(fmt % (res_bin_cen[i], histR[i], histS[i], histU[i]))
f3.close()
# npz file with the full Dictionary
fname4 = 'SpecResidStats4DR2_AllDict.' + suf
np.savez_compressed(fname4, D)
sys.exit('bai')
frac = 0.999
l_int = np.arange(3650, 7200, 2)
Nl_int = len(l_int)
import CALIFAUtils
gals, _ = CALIFAUtils.sort_gals('/Users/lacerda/CALIFA/listv20_q050.d15a.txt')
#gals, _ = CALIFAUtils.sort_gals('/Users/lacerda/CALIFA/listq50test.txt')
RF_SumR__l = np.ma.zeros((1601))
RF_SumR2__l = np.ma.zeros((1601))
RF_NOk__l = np.ma.zeros((1601))
for iGal, K in CALIFAUtils.loop_cubes(gals.tolist(), v_run=-1):
isFlagOk__lz = np.where(K.f_flag == 0, 1, 0)
isErrOk__lz = np.where(K.f_err > 0, 1, 0)
isWeiOk__lz = np.where(K.f_wei > 0, 1, 0)
isOk__lz = isFlagOk__lz * isWeiOk__lz * isErrOk__lz
rad__z = np.sqrt((K.zonePos['x'] - K.x0)**2. +
(K.zonePos['y'] - K.y0)**2.) / K.HLR_pix
isInRad__z = np.where(rad__z >= 1., 1, 0) * np.where(rad__z < 999.0, 1, 0)
isOkAndInRad__lz = isOk__lz * isInRad__z
#rs_gaussian_smooth = True,
#rs_percentiles = True,
#rs_gs_fwhm = 0.4,
#kwargs_plot_rs = dict(c = c_rs, lw = 2, label = 'Median (run. stats)'),
#rs_errorbar = False,
#x_major_locator = xv['majloc'],
#x_minor_locator = xv['minloc'],
#y_major_locator = yv['majloc'],
#y_minor_locator = yv['minloc'],
)
suptitle = r'NGals:%d tSF:%.2f Myr $x_Y$(min):%.0f%% $\tau_V^\star$(min):%.2f $\tau_V^{neb}$(min):%.2f $\epsilon\tau_V^{neb}$(max):%.2f' % (H.N_gals, (tSF / 1e6), H.xOkMin * 100., H.tauVOkMin, H.tauVNebOkMin, H.tauVNebErrMax)
f.suptitle(suptitle, fontsize = 12)
filename = '%s_%.2fMyr.png' % ('logSFRSD_tauV', tSF / 1e6)
#filename = '%s_%.2fMyr.png' % ('logSFRSDR_tauVR', tSF / 1e6)
CALIFAUtils.debug_var(True, filename = filename)
f.savefig(filename)
plt.close(f)
#################################################################################
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
# xkeys = [ 'logtauVR', 'logtauVNebR' ]
# ykeys = [ 'alogSFRSDR', 'alogSFRSDHaR' ]
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
xkeys = [ 'logtauV', 'logtauVNeb' ]
ykeys = [ 'logSFRSD', 'logSFRSDHa' ]
for fnamepref, xv, yv in H.plot_xyz_keys_iter(iT = iT, iU = -1, xkeys = xkeys, ykeys = ykeys):
xk = fnamepref.split('_')[0]
yk = fnamepref.split('_')[1]
plot_zbins(
def corr_xy_SFR(H, v, tSF__T, iT, mask_radius = False):
C.debug_var(debug, corr = v)
C.debug_var(debug, iT = iT)
C.debug_var(debug, tSF = tSF__T[iT])
if v == 'aSFRSD':
dim = 'rg'
else:
dim = 'g'
x = H.get_data_h5('%s__T%s' % (v, dim))[iT]
y = H.get_data_h5('%s_Ha__%s' % (v, dim))
xm, ym = C.ma_mask_xyz(x, y)
if mask_radius is True:
m = (H.zone_dist_HLR__g > 0.5)
xm[~m] = np.ma.masked
ym[~m] = np.ma.masked
Rs, _ = st.spearmanr(xm.compressed(), ym.compressed())
Rp, _ = st.pearsonr(xm.compressed(), ym.compressed())
C.debug_var(debug, Rs = Rs)
C.debug_var(debug, Rp = Rp)
return Rs, Rp
#example(listfile, sortby, order = 1)
f = open('/Users/lacerda/CALIFA/list_SFR/rem_ba_morph/list_1234.txt', 'r')
l = f.readlines()
f.close()
listgals_toberemoved = [l[i].strip() for i in np.arange(len(l))]
f = open('/Users/lacerda/CALIFA/list_SFR/rem_ba_morph/list_0_si_si.txt',
'r')
l = f.readlines()
f.close()
listgals_zero = [l[i].strip() for i in np.arange(len(l))]
kwargs = dict(EL=True, nuc_R=0.15)
gals, data__g = C.sort_gals(
gals='/Users/lacerda/CALIFA/listOf298GalPrefixes.txt',
func=sort_f,
order=1,
**kwargs)
for i, g in enumerate(gals):
j = -1
try:
j = listgals_zero.index(g)
mark = '0'
except:
mark = None
#EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
# if mark == None:
# try:
