def plot_color_color(colorbox,
objects,
label_x,
label_y,
output,
xlim=None,
ylim=None,
offset=None,
legend='upper left'):
"""
Parameters
----------
colorbox : species.core.box.ColorMagBox
Box with the colors and magnitudes.
objects : tuple(tuple(str, str, str, str), )
Tuple with individual objects. The objects require a tuple with their database tag, the
two filter IDs for the color, and the filter ID for the absolute magnitude.
label_x : str
Label for the x-axis.
label_y : str
Label for the y-axis.
output : str
Output filename.
xlim : tuple(float, float)
Limits for the x-axis.
ylim : tuple(float, float)
Limits for the y-axis.
offset : tuple(float, float)
Offset of the x- and y-axis label.
legend : str
Legend position.
Returns
-------
None
"""
marker = itertools.cycle(('o', 's', '<', '>', 'p', 'v', '^', '*',
'd', 'x', '+', '1', '2', '3', '4'))
sys.stdout.write('Plotting color-color diagram: '+output+'... ')
sys.stdout.flush()
plt.figure(1, figsize=(4, 4.3))
gridsp = mpl.gridspec.GridSpec(3, 1, height_ratios=[0.2, 0.1, 4.])
gridsp.update(wspace=0., hspace=0., left=0, right=1, bottom=0, top=1)
ax1 = plt.subplot(gridsp[2, 0])
ax2 = plt.subplot(gridsp[0, 0])
ax1.grid(True, linestyle=':', linewidth=0.7, color='silver', dashes=(1, 4), zorder=0)
ax1.tick_params(axis='both', which='major', colors='black', labelcolor='black',
direction='in', width=0.8, length=5, labelsize=12, top=True,
bottom=True, left=True, right=True)
ax1.tick_params(axis='both', which='minor', colors='black', labelcolor='black',
direction='in', width=0.8, length=3, labelsize=12, top=True,
bottom=True, left=True, right=True)
ax1.set_xlabel(label_x, fontsize=14)
ax1.set_ylabel(label_y, fontsize=14)
ax1.invert_yaxis()
if offset:
ax1.get_xaxis().set_label_coords(0.5, offset[0])
ax1.get_yaxis().set_label_coords(offset[1], 0.5)
else:
ax1.get_xaxis().set_label_coords(0.5, -0.08)
ax1.get_yaxis().set_label_coords(-0.12, 0.5)
if xlim:
ax1.set_xlim(xlim[0], xlim[1])
if ylim:
ax1.set_ylim(ylim[0], ylim[1])
cmap = plt.cm.viridis
bounds = np.arange(0, 8, 1)
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
sptype = colorbox.sptype
color1 = colorbox.color1
color2 = colorbox.color2
indices = np.where(sptype != 'None')[0]
sptype = sptype[indices]
color1 = color1[indices]
color2 = color2[indices]
spt_disc = plot_util.sptype_discrete(sptype, color1.shape)
_, unique = np.unique(color1, return_index=True)
sptype = sptype[unique]
color1 = color1[unique]
color2 = color2[unique]
spt_disc = spt_disc[unique]
scat = ax1.scatter(color1, color2, c=spt_disc, cmap=cmap, norm=norm,
zorder=5, s=40, alpha=0.6, edgecolor='none')
cb = Colorbar(ax=ax2, mappable=scat, orientation='horizontal',
ticklocation='top', format='%.2f')
cb.ax.tick_params(width=0.8, length=5, labelsize=10, direction='in', color='black')
cb.set_ticks(np.arange(0.5, 7., 1.))
cb.set_ticklabels(['M0-M4', 'M5-M9', 'L0-L4', 'L5-L9', 'T0-T4', 'T6-T8', 'Y1-Y2'])
if objects is not None:
for item in objects:
objdata = read_object.ReadObject(item[0])
mag1 = objdata.get_photometry(item[1][0])[0]
mag2 = objdata.get_photometry(item[1][1])[0]
mag3 = objdata.get_photometry(item[2][0])[0]
mag4 = objdata.get_photometry(item[2][1])[0]
err1 = objdata.get_photometry(item[1][0])[1]
err2 = objdata.get_photometry(item[1][1])[1]
err3 = objdata.get_photometry(item[2][0])[1]
err4 = objdata.get_photometry(item[2][1])[1]
color1 = mag1 - mag2
color2 = mag3 - mag4
error1 = math.sqrt(err1**2+err2**2)
error2 = math.sqrt(err3**2+err4**2)
ax1.errorbar(color1, color2, xerr=error1, yerr=error2,
marker=next(marker), ms=6, color='black', label=objdata.object_name,
markerfacecolor='white', markeredgecolor='black', zorder=10)
handles, labels = ax1.get_legend_handles_labels()
if handles:
handles = [h[0] for h in handles]
ax1.legend(handles, labels, loc=legend, prop={'size': 9}, frameon=False, numpoints=1)
plt.savefig(os.getcwd()+'/'+output, bbox_inches='tight')
plt.close()
sys.stdout.write('[DONE]\n')
sys.stdout.flush()
def plot_color_color(boxes: list,
objects: Optional[Union[
List[Tuple[str, Tuple[str, str], Tuple[str, str]]],
List[Tuple[str, Tuple[str, str], Tuple[str, str],
Optional[dict], Optional[dict]]]]] = None,
mass_labels: Optional[Union[List[float],
List[Tuple[float,
str]]]] = None,
teff_labels: Optional[Union[List[float],
List[Tuple[float,
str]]]] = None,
companion_labels: bool = False,
reddening: Optional[List[Tuple[Tuple[str,
str], Tuple[str,
str],
Tuple[str,
float], str, float,
Tuple[float,
float]]]] = None,
field_range: Optional[Tuple[str, str]] = None,
label_x: str = 'Color',
label_y: str = 'Color',
xlim: Optional[Tuple[float, float]] = None,
ylim: Optional[Tuple[float, float]] = None,
offset: Optional[Tuple[float, float]] = None,
legend: Optional[Union[str, dict,
Tuple[float,
float]]] = 'upper left',
figsize: Optional[Tuple[float, float]] = (4., 4.3),
output: str = 'color-color.pdf') -> None:
"""
Function for creating a color-color diagram.
Parameters
----------
boxes : list(species.core.box.ColorColorBox, species.core.box.IsochroneBox, )
Boxes with the color-color and isochrone data from photometric libraries, spectral
libraries, and/or atmospheric models. The synthetic data have to be created with
:func:`~species.read.read_isochrone.ReadIsochrone.get_color_color`. These boxes
contain synthetic colors for a given age and a range of masses.
objects : tuple(tuple(str, tuple(str, str), tuple(str, str)), ),
tuple(tuple(str, tuple(str, str), tuple(str, str), dict, dict), ), None
Tuple with individual objects. The objects require a tuple with their database tag, the two
filter names for the first color, and the two filter names for the second color.
Optionally, a dictionary with keyword arguments can be provided for the object's marker and
label, respectively. For example, ``{'marker': 'o', 'ms': 10}`` for the marker and
``{'ha': 'left', 'va': 'bottom', 'xytext': (5, 5)})`` for the label. Not used if set to
None.
mass_labels : list(float, ), list(tuple(float, str), ), None
Plot labels with masses next to the isochrone data of `models`. The list with masses has
to be provided in Jupiter mass. Alternatively, a list of tuples can be provided with
the planet mass and position of the label ('left' or 'right), for example
``[(10., 'left'), (20., 'right')]``. No labels are shown if set to None.
teff_labels : list(float, ), list(tuple(float, str), ), None
Plot labels with temperatures (K) next to the synthetic Planck photometry. Alternatively,
a list of tuples can be provided with the planet mass and position of the label ('left' or
'right), for example ``[(1000., 'left'), (1200., 'right')]``. No labels are shown if set
to None.
companion_labels : bool
Plot labels with the names of the directly imaged companions.
reddening : list(tuple(tuple(str, str), tuple(str, str), tuple(str, float), str, float, tuple(float, float)), None
Include reddening arrows by providing a list with tuples. Each tuple contains the filter
names for the color, the filter name for the magnitude, the particle radius (um), and the
start position (color, mag) of the arrow in the plot, so (filter_color_1, filter_color_2,
filter_mag, composition, radius, (x_pos, y_pos)). The composition can be either 'Fe' or
'MgSiO3' (both with crystalline structure). The parameter is not used if set to ``None``.
field_range : tuple(str, str), None
Range of the discrete colorbar for the field dwarfs. The tuple should contain the lower
and upper value ('early M', 'late M', 'early L', 'late L', 'early T', 'late T', 'early Y).
The full range is used if set to None.
label_x : str
Label for the x-axis.
label_y : str
Label for the y-axis.
xlim : tuple(float, float)
Limits for the x-axis.
ylim : tuple(float, float)
Limits for the y-axis.
offset : tuple(float, float), None
Offset of the x- and y-axis label.
legend : str, tuple(float, float), dict, None
Legend position or keyword arguments. No legend is shown if set to ``None``.
figsize : tuple(float, float)
Figure size.
output : str
Output filename.
Returns
-------
NoneType
None
"""
mpl.rcParams['font.serif'] = ['Bitstream Vera Serif']
mpl.rcParams['font.family'] = 'serif'
plt.rc('axes', edgecolor='black', linewidth=2.2)
model_color = ('#234398', '#f6a432', 'black')
model_linestyle = ('-', '--', ':', '-.')
isochrones = []
planck = []
models = []
empirical = []
for item in boxes:
if isinstance(item, box.IsochroneBox):
isochrones.append(item)
elif isinstance(item, box.ColorColorBox):
if item.object_type == 'model':
models.append(item)
elif item.library == 'planck':
planck.append(item)
else:
empirical.append(item)
else:
raise ValueError(
f'Found a {type(item)} while only ColorColorBox and IsochroneBox '
f'objects can be provided to \'boxes\'.')
plt.figure(1, figsize=figsize)
gridsp = mpl.gridspec.GridSpec(3, 1, height_ratios=[0.2, 0.1, 4.])
gridsp.update(wspace=0., hspace=0., left=0, right=1, bottom=0, top=1)
ax1 = plt.subplot(gridsp[2, 0])
ax2 = plt.subplot(gridsp[0, 0])
ax1.tick_params(axis='both',
which='major',
colors='black',
labelcolor='black',
direction='in',
width=1,
length=5,
labelsize=12,
top=True,
bottom=True,
left=True,
right=True)
ax1.tick_params(axis='both',
which='minor',
colors='black',
labelcolor='black',
direction='in',
width=1,
length=3,
labelsize=12,
top=True,
bottom=True,
left=True,
right=True)
ax1.xaxis.set_major_locator(MultipleLocator(0.5))
ax1.yaxis.set_major_locator(MultipleLocator(0.5))
ax1.xaxis.set_minor_locator(MultipleLocator(0.1))
ax1.yaxis.set_minor_locator(MultipleLocator(0.1))
ax1.set_xlabel(label_x, fontsize=14)
ax1.set_ylabel(label_y, fontsize=14)
ax1.invert_yaxis()
if offset:
ax1.get_xaxis().set_label_coords(0.5, offset[0])
ax1.get_yaxis().set_label_coords(offset[1], 0.5)
else:
ax1.get_xaxis().set_label_coords(0.5, -0.08)
ax1.get_yaxis().set_label_coords(-0.12, 0.5)
if xlim:
ax1.set_xlim(xlim[0], xlim[1])
if ylim:
ax1.set_ylim(ylim[0], ylim[1])
if models is not None:
count = 0
model_dict = {}
for j, item in enumerate(models):
if item.library not in model_dict:
model_dict[item.library] = [count, 0]
count += 1
else:
model_dict[item.library] = [
model_dict[item.library][0],
model_dict[item.library][1] + 1
]
model_count = model_dict[item.library]
if model_count[1] == 0:
label = plot_util.model_name(item.library)
if item.library == 'zhu2015':
ax1.plot(item.color1,
item.color2,
marker='x',
ms=5,
linestyle=model_linestyle[model_count[1]],
linewidth=0.6,
color='gray',
label=label,
zorder=0)
xlim = ax1.get_xlim()
ylim = ax1.get_ylim()
for i, teff_item in enumerate(item.sptype):
teff_label = rf'{teff_item:.0e} $M_\mathregular{{Jup}}^{2}$ yr$^{{-1}}$'
if item.color2[i] < ylim[1]:
ax1.annotate(teff_label,
(item.color1[i], item.color2[i]),
color='gray',
fontsize=8,
ha='left',
va='center',
xytext=(item.color1[i] + 0.1,
item.color2[i] - 0.05),
zorder=3)
else:
ax1.plot(item.color1,
item.color2,
linestyle=model_linestyle[model_count[1]],
linewidth=1.,
color=model_color[model_count[0]],
label=label,
zorder=0)
if mass_labels is not None:
interp_color1 = interp1d(item.sptype, item.color1)
interp_color2 = interp1d(item.sptype, item.color2)
for i, mass_item in enumerate(mass_labels):
if isinstance(mass_item, tuple):
mass_val = mass_item[0]
mass_pos = mass_item[1]
else:
mass_val = mass_item
mass_pos = 'right'
# if j == 0 or (j > 0 and mass_val < 20.):
if j == 0:
pos_color1 = interp_color1(mass_val)
pos_color2 = interp_color2(mass_val)
if mass_pos == 'left':
mass_ha = 'right'
mass_xytext = (pos_color1 - 0.05,
pos_color2)
else:
mass_ha = 'left'
mass_xytext = (pos_color1 + 0.05,
pos_color2)
mass_label = str(
int(mass_val)) + r' M$_\mathregular{J}$'
xlim = ax1.get_xlim()
ylim = ax1.get_ylim()
if xlim[0]+0.2 < pos_color1 < xlim[1]-0.2 and \
ylim[0]+0.2 < pos_color2 < ylim[1]-0.2:
ax1.scatter(pos_color1,
pos_color2,
c=model_color[model_count[0]],
s=15,
edgecolor='none',
zorder=0)
ax1.annotate(
mass_label, (pos_color1, pos_color2),
color=model_color[model_count[0]],
fontsize=9,
xytext=mass_xytext,
ha=mass_ha,
va='center',
zorder=3)
else:
ax1.plot(item.color1,
item.color2,
linestyle=model_linestyle[model_count[1]],
linewidth=0.6,
color=model_color[model_count[0]],
label=label,
zorder=0)
if planck is not None:
planck_count = 0
for j, item in enumerate(planck):
if planck_count == 0:
label = plot_util.model_name(item.library)
ax1.plot(item.color1,
item.color2,
ls='--',
linewidth=0.8,
color='black',
label=label,
zorder=0)
if teff_labels is not None:
interp_color1 = interp1d(item.sptype, item.color1)
interp_color2 = interp1d(item.sptype, item.color2)
for i, teff_item in enumerate(teff_labels):
if isinstance(teff_item, tuple):
teff_val = teff_item[0]
teff_pos = teff_item[1]
else:
teff_val = teff_item
teff_pos = 'right'
if j == 0 or (j > 0 and teff_val < 20.):
pos_color1 = interp_color1(teff_val)
pos_color2 = interp_color2(teff_val)
if teff_pos == 'left':
teff_ha = 'right'
teff_xytext = (pos_color1 - 0.05, pos_color2)
else:
teff_ha = 'left'
teff_xytext = (pos_color1 + 0.05, pos_color2)
teff_label = f'{int(teff_val)} K'
xlim = ax1.get_xlim()
ylim = ax1.get_ylim()
if xlim[0]+0.2 < pos_color1 < xlim[1]-0.2 and \
ylim[0]+0.2 < pos_color2 < ylim[1]-0.2:
ax1.scatter(pos_color1,
pos_color2,
c='black',
s=15,
edgecolor='none',
zorder=0)
ax1.annotate(teff_label,
(pos_color1, pos_color2),
color='black',
fontsize=9,
xytext=teff_xytext,
zorder=3,
ha=teff_ha,
va='center')
else:
ax1.plot(item.color1,
item.color2,
ls='--',
lw=0.5,
color='black',
zorder=0)
planck_count += 1
if empirical:
cmap = plt.cm.viridis
bounds, ticks, ticklabels = plot_util.field_bounds_ticks(field_range)
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
for item in empirical:
sptype = item.sptype
names = item.names
color1 = item.color1
color2 = item.color2
if isinstance(sptype, list):
sptype = np.array(sptype)
if item.object_type in ['field', None]:
indices = np.where(sptype != 'None')[0]
sptype = sptype[indices]
color1 = color1[indices]
color2 = color2[indices]
spt_disc = plot_util.sptype_substellar(sptype, color1.shape)
_, unique = np.unique(color1, return_index=True)
sptype = sptype[unique]
color1 = color1[unique]
color2 = color2[unique]
spt_disc = spt_disc[unique]
scat = ax1.scatter(color1,
color2,
c=spt_disc,
cmap=cmap,
norm=norm,
s=50,
alpha=0.7,
edgecolor='none',
zorder=2)
cb = Colorbar(ax=ax2,
mappable=scat,
orientation='horizontal',
ticklocation='top',
format='%.2f')
cb.ax.tick_params(width=1,
length=5,
labelsize=10,
direction='in',
color='black')
cb.set_ticks(ticks)
cb.set_ticklabels(ticklabels)
elif item.object_type == 'young':
if objects is not None:
object_names = []
for obj_item in objects:
object_names.append(obj_item[0])
indices = plot_util.remove_color_duplicates(
object_names, names)
color1 = color1[indices]
color2 = color2[indices]
ax1.plot(color1,
color2,
marker='s',
ms=4,
linestyle='none',
alpha=0.7,
color='gray',
markeredgecolor='black',
label='Young/low-gravity',
zorder=2)
if isochrones:
for item in isochrones:
ax1.plot(item.colors[0],
item.colors[1],
linestyle='-',
linewidth=1.,
color='black')
if reddening is not None:
for item in reddening:
ext_1, ext_2 = dust_util.calc_reddening(item[0],
item[2],
composition=item[3],
structure='crystalline',
radius_g=item[4])
ext_3, ext_4 = dust_util.calc_reddening(item[1],
item[2],
composition=item[3],
structure='crystalline',
radius_g=item[4])
delta_x = ext_1 - ext_2
delta_y = ext_3 - ext_4
x_pos = item[5][0] + delta_x
y_pos = item[5][1] + delta_y
ax1.annotate('', (x_pos, y_pos),
xytext=(item[5][0], item[5][1]),
fontsize=8,
arrowprops={'arrowstyle': '->'},
color='black',
zorder=3.)
x_pos_text = item[5][0] + delta_x / 2.
y_pos_text = item[5][1] + delta_y / 2.
vector_len = math.sqrt(delta_x**2 + delta_y**2)
if item[3] == 'MgSiO3':
dust_species = r'MgSiO$_{3}$'
elif item[3] == 'Fe':
dust_species = 'Fe'
if item[4].is_integer():
red_label = f'{dust_species} ({item[4]:.0f} µm)'
else:
red_label = f'{dust_species} ({item[4]:.1f} µm)'
text = ax1.annotate(red_label, (x_pos_text, y_pos_text),
xytext=(-7. * delta_y / vector_len,
7. * delta_x / vector_len),
textcoords='offset points',
fontsize=8.,
color='black',
ha='center',
va='center')
ax1.plot([item[5][0], x_pos], [item[5][1], y_pos],
'-',
color='white')
sp1 = ax1.transData.transform_point((item[5][0], item[5][1]))
sp2 = ax1.transData.transform_point((x_pos, y_pos))
angle = np.degrees(np.arctan2(sp2[1] - sp1[1], sp2[0] - sp1[0]))
text.set_rotation(angle)
if objects is not None:
for i, item in enumerate(objects):
objdata = read_object.ReadObject(item[0])
objphot1 = objdata.get_photometry(item[1][0])
objphot2 = objdata.get_photometry(item[1][1])
objphot3 = objdata.get_photometry(item[2][0])
objphot4 = objdata.get_photometry(item[2][1])
if objphot1.ndim == 2:
print(
f'Found {objphot1.shape[1]} values for filter {item[1][0]} of {item[0]}'
)
print(
f'so using the first value: {objphot1[0, 0]} +/- {objphot1[1, 0]} mag'
)
objphot1 = objphot1[:, 0]
if objphot2.ndim == 2:
print(
f'Found {objphot2.shape[1]} values for filter {item[1][1]} of {item[0]}'
)
print(
f'so using the first value: {objphot2[0, 0]} +/- {objphot2[1, 0]} mag'
)
objphot2 = objphot2[:, 0]
if objphot3.ndim == 2:
print(
f'Found {objphot3.shape[1]} values for filter {item[2][0]} of {item[0]}'
)
print(
f'so using the first value: {objphot3[0, 0]} +/- {objphot3[1, 0]} mag'
)
objphot3 = objphot3[:, 0]
if objphot4.ndim == 2:
print(
f'Found {objphot4.shape[1]} values for filter {item[2][1]} of {item[0]}'
)
print(
f'so using the first value: {objphot4[0, 0]} +/- {objphot4[1, 0]} mag'
)
objphot4 = objphot4[:, 0]
color1 = objphot1[0] - objphot2[0]
color2 = objphot3[0] - objphot4[0]
error1 = math.sqrt(objphot1[1]**2 + objphot2[1]**2)
error2 = math.sqrt(objphot3[1]**2 + objphot4[1]**2)
if len(item) > 3 and item[3] is not None:
kwargs = item[3]
else:
kwargs = {
'marker': '>',
'ms': 6.,
'color': 'black',
'mfc': 'white',
'mec': 'black',
'label': 'Direct imaging'
}
ax1.errorbar(color1,
color2,
xerr=error1,
yerr=error2,
zorder=3,
**kwargs)
if companion_labels:
if len(item) > 3:
kwargs = item[4]
else:
kwargs = {
'ha': 'left',
'va': 'bottom',
'fontsize': 8.5,
'xytext': (5., 5.),
'color': 'black'
}
ax1.annotate(objdata.object_name, (color1, color2),
zorder=3,
textcoords='offset points',
**kwargs)
print(f'Plotting color-color diagram: {output}...', end='', flush=True)
handles, labels = ax1.get_legend_handles_labels()
if legend is not None:
handles, labels = ax1.get_legend_handles_labels()
# prevent duplicates
by_label = dict(zip(labels, handles))
if handles:
ax1.legend(by_label.values(),
by_label.keys(),
loc=legend,
fontsize=8.5,
frameon=False,
numpoints=1)
plt.savefig(os.getcwd() + '/' + output, bbox_inches='tight')
plt.clf()
plt.close()
print(' [DONE]')
def plot_color_magnitude(colorbox=None,
objects=None,
isochrones=None,
models=None,
label_x='color [mag]',
label_y='M [mag]',
xlim=None,
ylim=None,
offset=None,
legend='upper left',
output='color-magnitude.pdf'):
"""
Parameters
----------
colorbox : species.core.box.ColorMagBox, None
Box with the colors and magnitudes.
objects : tuple(tuple(str, str, str, str), ), None
Tuple with individual objects. The objects require a tuple with their database tag, the two
filter IDs for the color, and the filter ID for the absolute magnitude.
isochrones : tuple(species.core.box.IsochroneBox, ), None
Tuple with boxes of isochrone data. Not used if set to None.
models : tuple(species.core.box.ColorMagBox, ), None
label_x : str
Label for the x-axis.
label_y : str
Label for the y-axis.
xlim : tuple(float, float)
Limits for the x-axis.
ylim : tuple(float, float)
Limits for the y-axis.
legend : str
Legend position.
output : str
Output filename.
Returns
-------
None
"""
marker = itertools.cycle(('o', 's', '<', '>', 'p', 'v', '^', '*',
'd', 'x', '+', '1', '2', '3', '4'))
model_color = ('tomato', 'teal', 'dodgerblue')
model_linestyle = ('-', '--', ':', '-.')
sys.stdout.write('Plotting color-magnitude diagram: '+output+'... ')
sys.stdout.flush()
if (models is not None and colorbox is None) or \
(models is not None and colorbox.object_type == 'temperature'):
plt.figure(1, figsize=(4.4, 4.5))
gridsp = mpl.gridspec.GridSpec(1, 3, width_ratios=[4, 0.15, 0.25])
gridsp.update(wspace=0., hspace=0., left=0, right=1, bottom=0, top=1)
ax1 = plt.subplot(gridsp[0, 0])
ax2 = plt.subplot(gridsp[0, 2])
elif colorbox.object_type != 'temperature':
plt.figure(1, figsize=(4., 4.8))
gridsp = mpl.gridspec.GridSpec(3, 1, height_ratios=[0.2, 0.1, 4.5])
gridsp.update(wspace=0., hspace=0., left=0, right=1, bottom=0, top=1)
ax1 = plt.subplot(gridsp[2, 0])
ax2 = plt.subplot(gridsp[0, 0])
# elif models is not None and colorbox.object_type != 'temperature':
# plt.figure(1, figsize=(4.2, 4.8))
# gridsp = mpl.gridspec.GridSpec(3, 3, width_ratios=[3.7, 0.15, 0.25], height_ratios=[0.25, 0.15, 4.4])
# gridsp.update(wspace=0., hspace=0., left=0, right=1, bottom=0, top=1)
#
# ax1 = plt.subplot(gridsp[2, 0])
# ax2 = plt.subplot(gridsp[0, 0])
# ax3 = plt.subplot(gridsp[2, 2])
if colorbox is not None:
sptype = colorbox.sptype
color = colorbox.color
magnitude = colorbox.magnitude
ax1.grid(True, linestyle=':', linewidth=0.7, color='silver', dashes=(1, 4), zorder=0)
ax1.tick_params(axis='both', which='major', colors='black', labelcolor='black',
direction='in', width=0.8, length=5, labelsize=12, top=True,
bottom=True, left=True, right=True)
ax1.tick_params(axis='both', which='minor', colors='black', labelcolor='black',
direction='in', width=0.8, length=3, labelsize=12, top=True,
bottom=True, left=True, right=True)
ax1.set_xlabel(label_x, fontsize=14)
ax1.set_ylabel(label_y, fontsize=14)
ax1.invert_yaxis()
if offset:
ax1.get_xaxis().set_label_coords(0.5, offset[0])
ax1.get_yaxis().set_label_coords(offset[1], 0.5)
else:
ax1.get_xaxis().set_label_coords(0.5, -0.08)
ax1.get_yaxis().set_label_coords(-0.12, 0.5)
if xlim:
ax1.set_xlim(xlim[0], xlim[1])
if ylim:
ax1.set_ylim(ylim[0], ylim[1])
if colorbox is not None:
cmap_sptype = plt.cm.viridis
if colorbox.object_type == 'star':
bounds_sptype = np.arange(0, 11, 1)
else:
bounds_sptype = np.arange(0, 8, 1)
if colorbox.object_type != 'temperature':
norm_sptype = mpl.colors.BoundaryNorm(bounds_sptype, cmap_sptype.N)
indices = np.where(sptype != b'None')[0]
sptype = sptype[indices]
color = color[indices]
magnitude = magnitude[indices]
if colorbox.object_type == 'star':
spt_disc = plot_util.sptype_stellar(sptype, color.shape)
unique = np.arange(0, color.size, 1)
elif colorbox.object_type != 'temperature':
spt_disc = plot_util.sptype_substellar(sptype, color.shape)
_, unique = np.unique(color, return_index=True)
if colorbox.object_type == 'temperature':
scat_sptype = ax1.scatter(color, magnitude, c=sptype, cmap=cmap_sptype,
zorder=6, s=40, alpha=0.6, edgecolor='none')
else:
sptype = sptype[unique]
color = color[unique]
magnitude = magnitude[unique]
spt_disc = spt_disc[unique]
scat_sptype = ax1.scatter(color, magnitude, c=spt_disc, cmap=cmap_sptype,
norm=norm_sptype, zorder=6, s=40, alpha=0.6,
edgecolor='none')
if colorbox is not None:
if colorbox.object_type == 'temperature':
cb1 = Colorbar(ax=ax2, mappable=scat_sptype, orientation='vertical',
ticklocation='right', format='%i')
cb1.ax.tick_params(width=0.8, length=5, labelsize=10, direction='in', color='black')
cb1.ax.set_ylabel('Temperature [K]', rotation=270, fontsize=12, labelpad=22)
cb1.solids.set_edgecolor("face")
else:
cb1 = Colorbar(ax=ax2, mappable=scat_sptype, orientation='horizontal',
ticklocation='top', format='%.2f')
cb1.ax.tick_params(width=0.8, length=5, labelsize=10, direction='in', color='black')
if colorbox.object_type == 'star':
cb1.set_ticks(np.arange(0.5, 10., 1.))
cb1.set_ticklabels(['O', 'B', 'A', 'F', 'G', 'K', 'M', 'L', 'T', 'Y'])
else:
cb1.set_ticks(np.arange(0.5, 7., 1.))
cb1.set_ticklabels(['M0-M4', 'M5-M9', 'L0-L4', 'L5-L9', 'T0-T4', 'T6-T8', 'Y1-Y2'])
if models is not None:
cmap_teff = plt.cm.afmhot
teff_min = np.inf
teff_max = -np.inf
for item in models:
if np.amin(item.sptype) < teff_min:
teff_min = np.amin(item.sptype)
if np.amax(item.sptype) > teff_max:
teff_max = np.amax(item.sptype)
norm_teff = mpl.colors.Normalize(vmin=teff_min, vmax=teff_max)
count = 0
model_dict = {}
for item in models:
if item.library not in model_dict:
model_dict[item.library] = [count, 0]
count += 1
else:
model_dict[item.library] = [model_dict[item.library][0], model_dict[item.library][1]+1]
model_count = model_dict[item.library]
if model_count[1] == 0:
label = plot_util.model_name(item.library)
ax1.plot(item.color, item.magnitude, linestyle=model_linestyle[model_count[1]],
linewidth=0.6, zorder=3, color=model_color[model_count[0]], label=label)
else:
ax1.plot(item.color, item.magnitude, linestyle=model_linestyle[model_count[1]],
linewidth=0.6, zorder=3, color=model_color[model_count[0]])
# scat_teff = ax1.scatter(item.color, item.magnitude, c=item.sptype, cmap=cmap_teff,
# norm=norm_teff, zorder=4, s=15, alpha=1.0, edgecolor='none')
# cb2 = ColorbarBase(ax=ax3, cmap=cmap_teff, norm=norm_teff, orientation='vertical', ticklocation='right')
# cb2.ax.tick_params(width=0.8, length=5, labelsize=10, direction='in', color='black')
# cb2.ax.set_ylabel('Temperature [K]', rotation=270, fontsize=12, labelpad=22)
if isochrones is not None:
for item in isochrones:
ax1.plot(item.color, item.magnitude, linestyle='-', linewidth=1., color='black')
if objects is not None:
for item in objects:
objdata = read_object.ReadObject(item[0])
objcolor1 = objdata.get_photometry(item[1])
objcolor2 = objdata.get_photometry(item[2])
abs_mag = objdata.get_absmag(item[3])
colorerr = math.sqrt(objcolor1[1]**2+objcolor2[1]**2)
ax1.errorbar(objcolor1[0]-objcolor2[0], abs_mag[0], yerr=abs_mag[1], xerr=colorerr,
marker=next(marker), ms=6, color='black', label=objdata.object_name,
markerfacecolor='white', markeredgecolor='black', zorder=10)
handles, labels = ax1.get_legend_handles_labels()
if handles:
# handles = [h[0] for h in handles]
# ax1.legend(handles, labels, loc=legend, prop={'size': 9}, frameon=False, numpoints=1)
ax1.legend(loc=legend, prop={'size': 9}, frameon=False, numpoints=1)
plt.savefig(os.getcwd()+'/'+output, bbox_inches='tight')
plt.close()
sys.stdout.write('[DONE]\n')
sys.stdout.flush()
