"""
Module with functions for creating color-magnitude and color-color plots.
"""
import os
import math
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
from matplotlib.colorbar import Colorbar
from species.core import box
from species.read import read_object
from species.util import plot_util
mpl.rcParams['font.serif'] = ['Bitstream Vera Serif']
mpl.rcParams['font.family'] = 'serif'
plt.rc('axes', edgecolor='black', linewidth=2.5)
[docs]def plot_color_magnitude(boxes,
objects=None,
mass_labels=None,
companion_labels=False,
field_range=None,
label_x='Color [mag]',
label_y='Magnitude [mag]',
xlim=None,
ylim=None,
offset=None,
legend='upper left',
output='color-magnitude.pdf'):
"""
Parameters
----------
boxes : list(species.core.box.ColorMagBox, species.core.box.IsochroneBox, )
Boxes with the color-magnitude 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_magnitude`. These boxes
contain synthetic colors and magnitudes for a given age and a range of masses.
objects : tuple(tuple(str, str, str, str), ),
tuple(tuple(str, str, str, str, str, str, float, float), ), 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. Optionally, the
horizontal and vertical alignment and fractional offset values can be provided for the
label can be provided (default: 'left', 'bottom', 8e-3, 8e-3). Not used if set to None.
mass_labels : list(float, ), None
Plot labels with masses next to the isochrone data of `models`. The list with masses has
to be provided in Jupiter mass. No labels are shown if set to None.
companion_labels : bool
Plot labels with the names of the directly imaged companions.
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), None
Limits for the x-axis.
ylim : tuple(float, float), None
Limits for the y-axis.
offset : tuple(float, float), None
Offset of the x- and y-axis label.
legend : str, None
Legend position. Not shown if set to None.
output : str
Output filename.
Returns
-------
NoneType
None
"""
print(f'Plotting color-magnitude diagram: {output}... ', end='', flush=True)
model_color = ('#234398', '#f6a432')
model_linestyle = ('-', '--', ':', '-.')
isochrones = []
models = []
empirical = []
for item in boxes:
if isinstance(item, box.IsochroneBox):
isochrones.append(item)
elif isinstance(item, box.ColorMagBox):
if item.object_type == 'model':
models.append(item)
else:
empirical.append(item)
else:
raise ValueError(f'Found a {type(item)} while only ColorMagBox and IsochroneBox '
f'objects can be provided to \'boxes\'.')
if empirical:
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])
else:
plt.figure(1, figsize=(4., 4.5))
gridsp = mpl.gridspec.GridSpec(1, 1)
gridsp.update(wspace=0., hspace=0., left=0, right=1, bottom=0, top=1)
ax1 = 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.set_xlabel(label_x, fontsize=14)
ax1.set_ylabel(label_y, fontsize=14)
ax1.invert_yaxis()
if offset is not None:
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 is not None:
ax1.set_xlim(xlim[0], xlim[1])
if ylim is not None:
ax1.set_ylim(ylim[0], ylim[1])
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 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)
ax1.plot(item.color, item.magnitude, linestyle=model_linestyle[model_count[1]],
linewidth=1.2, color=model_color[model_count[0]], label=label, zorder=0)
if mass_labels is not None:
interp_magnitude = interp1d(item.sptype, item.magnitude)
interp_color = interp1d(item.sptype, item.color)
for i, mass_item in enumerate(mass_labels):
if j == 0 or (j > 0 and mass_item < 20.):
pos_color = interp_color(mass_item)
pos_mag = interp_magnitude(mass_item)
mass_label = str(int(mass_item))+r' M$_\mathregular{J}$'
xlim = ax1.get_xlim()
ylim = ax1.get_ylim()
if xlim[0]+0.2 < pos_color < xlim[1]-0.2 and \
ylim[1]+0.2 < pos_mag < ylim[0]-0.2:
ax1.scatter(pos_color, pos_mag, c=model_color[model_count[0]], s=15,
edgecolor='none', zorder=0)
ax1.annotate(mass_label, (pos_color, pos_mag),
color=model_color[model_count[0]], fontsize=9,
xytext=(pos_color+0.05, pos_mag-0.1), zorder=1)
else:
ax1.plot(item.color, item.magnitude, linestyle=model_linestyle[model_count[1]],
linewidth=0.6, color=model_color[model_count[0]], zorder=0)
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
color = item.color
magnitude = item.magnitude
indices = np.where(sptype != b'None')[0]
sptype = sptype[indices]
color = color[indices]
magnitude = magnitude[indices]
spt_disc = plot_util.sptype_substellar(sptype, color.shape)
_, unique = np.unique(color, return_index=True)
sptype = sptype[unique]
color = color[unique]
magnitude = magnitude[unique]
spt_disc = spt_disc[unique]
if item.object_type == 'field' or item.object_type is None:
scat = ax1.scatter(color, magnitude, 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':
ax1.plot(color, magnitude, 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.color, item.magnitude, linestyle='-', linewidth=1.2, color='black')
if objects is not None:
for i, item in enumerate(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)
x_color = objcolor1[0]-objcolor2[0]
y_mag = abs_mag[0]
# if item[0] in ('PDS 70 b'):
# if item[0] in ('beta Pic b', 'HIP 65426 b', 'PZ Tel B', 'HD 206893 B'):
# marker = '*'
# markersize = 12
# color = '#eb4242'
# markerfacecolor = '#eb4242'
# markeredgecolor = 'black'
#
# else:
# marker = '>'
# markersize = 6
# color = 'black'
# markerfacecolor = 'white'
# markeredgecolor = 'black'
# if item[0] == 'HR 8799 b':
# label = 'Directly imaged'
# elif item[0] == 'beta Pic b':
# label = 'This work'
# elif item[0] == 'PDS 70 b':
# label = 'This work'
# else:
# label = None
marker = '>'
markersize = 6
color = 'black'
markerfacecolor = 'white'
markeredgecolor = 'black'
if i == 0:
label = 'Directly imaged'
else:
label = None
ax1.errorbar(x_color, y_mag, yerr=abs_mag[1], xerr=colorerr, marker=marker,
ms=markersize, color=color, markerfacecolor=markerfacecolor,
zorder=3, markeredgecolor=markeredgecolor, label=label)
if companion_labels:
x_range = ax1.get_xlim()
y_range = ax1.get_ylim()
if len(item) == 8:
ha = item[4]
va = item[5]
x_scaling = item[6]
y_scaling = item[7]
else:
ha = 'left'
va = 'bottom'
x_scaling = 1e-2
y_scaling = 5e-3
x_offset = x_scaling*abs(x_range[1]-x_range[0])
y_offset = y_scaling*abs(y_range[1]-y_range[0])
ax1.text(x_color+x_offset, y_mag-y_offset, objdata.object_name, ha=ha, va=va,
fontsize=8, color=color, zorder=3)
if legend is not None:
handles, labels = ax1.get_legend_handles_labels()
if handles:
ax1.legend(loc=legend, prop={'size': 8.5}, frameon=False, numpoints=1)
plt.savefig(os.getcwd()+'/'+output, bbox_inches='tight')
plt.clf()
plt.close()
print('[DONE]')
[docs]def plot_color_color(boxes,
objects=None,
mass_labels=None,
companion_labels=False,
field_range=None,
label_x='color [mag]',
label_y='color [mag]',
xlim=None,
ylim=None,
offset=None,
legend='upper left',
output='color-color.pdf'):
"""
Parameters
----------
boxes : species.core.box.ColorColorBox, None
Box with the colors and magnitudes.
objects : tuple(tuple(str, str, str, str), ),
tuple(tuple(str, str, str, str, str, str, float, float), ), None
Tuple with individual objects. The objects require a tuple with their database tag, the two
filter IDs for the first color, and the two filter IDs for the second color. Optionally,
the horizontal and vertical alignment and fractional offset values can be provided for the
label can be provided (default: 'left', 'bottom', 8e-3, 8e-3). Not used if set to None.
models : tuple(species.core.box.ColorMagBox, ), None
Tuple with :class:`~species.core.box.ColorColorBox` objects which have been created from
the isochrone data with :func:`~species.read.read_isochrone.ReadIsochrone.get_color_color`.
These boxes contain synthetic photometry for a given age and a range of masses. Not used
if set to None.
mass_labels : list(float, ), None
Plot labels with masses next to the isochrone data of `models`. The list with masses has
to be provided in Jupiter mass. No labels are shown if set to None.
companion_labels : bool
Plot labels with the names of the directly imaged companions.
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.
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), None
Offset of the x- and y-axis label.
legend : str
Legend position.
Returns
-------
NoneType
None
"""
print(f'Plotting color-color diagram: {output}... ', end='', flush=True)
model_color = ('#234398', '#f6a432')
model_linestyle = ('-', '--', ':', '-.')
isochrones = []
models = []
empirical = []
for item in boxes:
if isinstance(item, box.IsochroneBox):
isochrones.append(item)
elif isinstance(item, box.ColorMagBox):
if item.object_type == 'model':
models.append(item)
else:
empirical.append(item)
else:
raise ValueError(f'Found a {type(item)} while only ColorMagBox and IsochroneBox '
f'objects can be provided to \'boxes\'.')
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.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.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:
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 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)
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 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 j == 0 or (j > 0 and mass_item < 20.):
pos_color1 = interp_color1(mass_item)
pos_color2 = interp_color2(mass_item)
mass_label = str(int(mass_item))+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=(pos_color1+0.05, pos_color2-0.1), zorder=1)
else:
ax1.plot(item.color1, item.color2, linestyle=model_linestyle[model_count[1]],
linewidth=0.6, color=model_color[model_count[0]], zorder=0)
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
color1 = item.color1
color2 = item.color2
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]
if item.object_type == 'field':
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':
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=1.2, color='black')
if objects is not None:
for i, item in enumerate(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)
# if item[0] in ('beta Pic b', 'HIP 65426 b', 'PZ Tel B', 'HD 206893 B'):
# marker = '*'
# markersize = 12
# color = '#eb4242'
# markerfacecolor = '#eb4242'
# markeredgecolor = 'black'
#
# else:
# marker = '>'
# markersize = 6
# color = 'black'
# markerfacecolor = 'white'
# markeredgecolor = 'black'
#
# if item[0] == 'HR 8799 b':
# label = 'Directly imaged'
# elif item[0] == 'beta Pic b':
# label = 'This work'
# else:
# label = None
marker = '>'
markersize = 6
color = 'black'
markerfacecolor = 'white'
markeredgecolor = 'black'
if not companion_labels and i == 0:
label = 'Directly imaged'
else:
label = None
ax1.errorbar(color1, color2, xerr=error1, yerr=error2, marker=marker, ms=markersize,
color=color, markerfacecolor=markerfacecolor,
markeredgecolor=markeredgecolor, label=label, zorder=3)
if companion_labels:
x_range = ax1.get_xlim()
y_range = ax1.get_ylim()
if len(item) == 7:
ha = item[3]
va = item[4]
x_scaling = item[5]
y_scaling = item[6]
else:
ha = 'left'
va = 'bottom'
x_scaling = 8e-3
y_scaling = 8e-3
x_offset = x_scaling*abs(x_range[1]-x_range[0])
y_offset = y_scaling*abs(y_range[1]-y_range[0])
ax1.text(color1+x_offset, color2+y_offset, objdata.object_name, ha=ha, va=va,
fontsize=8, color=color, zorder=3)
handles, labels = ax1.get_legend_handles_labels()
if handles:
ax1.legend(loc=legend, prop={'size': 9}, frameon=False, numpoints=1)
plt.savefig(os.getcwd()+'/'+output, bbox_inches='tight')
plt.clf()
plt.close()
print('[DONE]')