def make_spec_plot(s,
fname,
smooth_factor=10,
angles=True,
components=False,
with_composite=False):
'''
make a spectrum plot from astropy.table.table.Table object
Parameters
----------
s: astropy.table.table.Table
table containing spectrum data outputted from Python
fname: str
filename to save as e.g. sv
smooth_factor: int
factor you would like to smooth by, default 10
angles: Bool
Would you like to plot the viewing angle spectra?
components: Bool
would you like to plot the individual components e.g. Disk Wind
Returns
----------
Success returns 0
Failure returns 1
Saves output as "spectrum_%s.png" % (fname)
'''
if type(s) != astropy.table.table.Table:
raise TypeError(
"make_spec_plot takes astropy.table.table.Table object as first arg"
)
return 1
if s.colnames[8] != "Scattered":
print("Warning- colnames are not in expected order! {} != Scattered".
format(s.colnames[8]))
ncomponents = 9
if angles:
# first make viewing angle plot
p.figure(figsize=(8, 12))
nspecs = len(s.dtype.names) - ncomponents
nx = 1
ny = nspecs
if nspecs > 4:
nx = 2
ny = (1 + nspecs) / nx
print("Making a {} by {} plot, {} spectra".format(nx, ny, nspecs))
if with_composite:
lambda_composite, f_composite, errors = np.loadtxt(
"%s/examples/telfer_qso_composite_hst.asc" %
(os.environ["PYTHON"]),
unpack=True,
comments="#")
for i in range(nspecs):
p.subplot(ny, nx, i + 1)
if with_composite:
f_1100 = util.get_flux_at_wavelength(
s["Lambda"], s[s.dtype.names[ncomponents + i]], 1100.0)
p.plot(s["Lambda"],
util.smooth(s[s.dtype.names[ncomponents + i]] / f_1100,
window_len=smooth_factor),
label="Model")
p.plot(lambda_composite, f_composite, label="HST composite")
p.legend()
else:
p.plot(
s["Lambda"],
util.smooth(s[s.dtype.names[ncomponents + i]],
window_len=smooth_factor))
p.title(s.dtype.names[ncomponents + i])
p.xlabel("Wavelength")
p.ylabel("Flux")
p.savefig("spectrum_%s.png" % (fname), dpi=300)
p.clf()
if components:
p.figure(figsize=(8, 12))
p.subplot(211)
p.plot(s["Lambda"],
util.smooth(s["Created"], window_len=smooth_factor),
label="Created")
p.plot(s["Lambda"],
util.smooth(s["Emitted"], window_len=smooth_factor),
label="Emitted")
p.legend()
p.subplot(212)
for i in range(4, 9):
p.plot(s["Lambda"],
util.smooth(s[s.dtype.names[i]], window_len=smooth_factor),
label=s.dtype.names[i])
p.xlabel("Wavelength")
p.ylabel("Flux")
p.legend()
p.savefig("spec_components_%s.png" % (fname), dpi=300)
p.clf()
return 0
def make_spec_plot_from_class(s,
fname,
smooth_factor=10,
angles=True,
components=False):
'''
make a spectrum plot from py_classes.specclass object
Parameters
----------
s: specclass object
table containing spectrum data outputted from Python
fname: str
filename to save as e.g. sv
smooth_factor: int
factor you would like to smooth by, default 10
angles: Bool
Would you like to plot the viewing angle spectra?
components: Bool
would you like to plot the individual components e.g. Disk Wind
Returns
----------
Success returns 0
Failure returns 1
Saves output as "spectrum_%s.png" % (fname)
'''
if angles:
# first make viewing angle plot
p.figure(figsize=(8, 12))
nspecs = len(s.spec)
nx = 1
ny = nspecs
if nspecs > 4:
nx = 2
ny = (1 + nspecs) / nx
print("Making a {} by {} plot, {} spectra".format(nx, ny, nspecs))
for i in range(nspecs):
p.subplot(ny, nx, i + 1)
p.plot(s.wavelength,
util.smooth(s.spec[i], window_len=smooth_factor))
p.xlabel("Wavelength")
p.ylabel("Flux")
p.savefig("spectrum_%s.png" % (fname))
p.clf()
if components:
p.figure(figsize=(8, 12))
p.subplot(211)
p.plot(s.wavelength,
util.smooth(s.created, window_len=smooth_factor),
label="Created")
p.plot(s.wavelength,
util.smooth(s.emitted, window_len=smooth_factor),
label="Emitted")
p.subplot(212)
p.plot(s.wavelength,
util.smooth(s.censrc, window_len=smooth_factor),
label="CenSrc")
p.plot(s.wavelength,
util.smooth(s.disk, window_len=smooth_factor),
label="Disk")
p.plot(s.wavelength,
util.smooth(s.wind, window_len=smooth_factor),
label="Wind")
p.plot(s.wavelength,
util.smooth(s.hitsurf, window_len=smooth_factor),
label="HitSurf")
p.plot(s.wavelength,
util.smooth(s.scattered, window_len=smooth_factor),
label="Scattered")
p.xlabel("Wavelength")
p.ylabel("Flux")
p.legend()
p.savefig("spec_components_%s.png" % (fname))
p.clf()
return 0
def make_spec_comparison_plot(s_array,
labels,
fname="comparison",
smooth_factor=10,
angles=True,
components=False):
'''
make a spectrum comparison plot from array of astropy.table.table.Table objects
Parameters
----------
s_array: array-like of astropy.table.table.Table objects
table containing spectrum data outputted from Python
labels: array-like
strings of labels for each spectrum
fname: str
filename to save as e.g. sv
smooth_factor: int
factor you would like to smooth by, default 10
angles: Bool
Would you like to plot the viewing angle spectra?
components: Bool
would you like to plot the individual components e.g. Disk Wind
Returns
----------
Success returns 0
Failure returns 1
Saves output as "spectrum_%s.png" % (fname)
'''
ncomponents = 9
if angles:
# first make viewing angle plot
p.figure(figsize=(8, 12))
nspecs = len(s_array[0].dtype.names) - ncomponents
nx = 1
ny = nspecs
if nspecs > 4:
nx = 2
ny = (1 + nspecs) / nx
print("Making a {} by {} comparison plot, {} spectra".format(
nx, ny, nspecs))
for j in range(len(s_array)):
for i in range(nspecs):
p.subplot(ny, nx, i + 1)
p.plot(s_array[j]["Lambda"],
util.smooth(
s_array[j][s_array[j].dtype.names[ncomponents + i]],
window_len=smooth_factor),
label=labels[j])
p.xlabel("Wavelength")
p.ylabel("Flux")
if i == 0 and j == (len(s_array) - 1):
p.legend()
p.savefig("spectrum_%s.png" % (fname), dpi=300)
p.clf()
if components:
p.figure(figsize=(8, 12))
n = len(s_array)
for j in range(n):
p.subplot(j + 1, 1, 1)
s = s_array[j]
p.plot(s["Lambda"],
util.smooth(s["Created"], window_len=smooth_factor),
label="Created")
p.plot(s["Lambda"],
util.smooth(s["Emitted"], window_len=smooth_factor),
label="Emitted")
for i in range(4, 9):
p.plot(s["Lambda"],
util.smooth(s[s.dtype.names[i]],
window_len=smooth_factor),
label=s.dtype.names[i])
p.xlabel("Wavelength")
p.ylabel("Flux")
p.legend()
p.savefig("spec_components_%s.png" % (fname), dpi=300)
p.clf()
return 0
# spectrum_wl = False # except KeyError or IndexError: # spectrum_wl = False spectrum = spectrum_wave if spectrum: ly_alpha_mask = (np.fabs(wrest - 1215.0) > 2.0) flux_mask = (flux > 0.0) #line_mask = (np.fabs(w - 1550.) < 300.0) mask = flux_mask * ly_alpha_mask wuse = w[mask] fuse = util.smooth(flux[mask]) try: wmin = min(wuse) wmax = max(wuse) except ValueError: spectrum = False #spectrum = False if spectrum: # flags to decide if we print out or not bal_flags_this_file = np.zeros(len(lines))