def get_absmag(
self, filter_name: str
) -> Union[Tuple[float, Optional[float]], Tuple[np.ndarray,
Optional[np.ndarray]]]:
"""
Function for calculating the absolute magnitudes of the object from the apparent
magnitudes and distance. The errors on the apparent magnitude and distance are propagated
into an error on the absolute magnitude.
Parameters
----------
filter_name : str
Filter name.
Returns
-------
float, np.ndarray
Absolute magnitude (mag)
float, np.ndarray
Error (mag).
"""
with h5py.File(self.database, 'r') as h5_file:
obj_distance = np.asarray(
h5_file[f'objects/{self.object_name}/distance'])
if filter_name in h5_file[f'objects/{self.object_name}']:
obj_phot = np.asarray(
h5_file[f'objects/{self.object_name}/{filter_name}'])
else:
raise ValueError(
f'There is no photometric data of \'{self.object_name}\' '
f'available with the {filter_name}.')
if obj_phot.ndim == 1:
abs_mag = phot_util.apparent_to_absolute(
(obj_phot[0], obj_phot[1]), (obj_distance[0], obj_distance[1]))
elif obj_phot.ndim == 2:
abs_mag = phot_util.apparent_to_absolute(
(obj_phot[0, :], obj_phot[1, :]),
(obj_distance[0], obj_distance[1]))
return abs_mag
def get_absmag(self,
filter_name):
"""
Parameters
----------
filter_name : str
Filter name.
Returns
-------
float, float
Absolute magnitude (mag), magnitude error (error).
"""
h5_file = h5py.File(self.database, 'r')
obj_distance = np.asarray(h5_file['objects/'+self.object_name+'/distance'])
obj_phot = np.asarray(h5_file['objects/'+self.object_name+'/'+filter_name])
h5_file.close()
abs_mag = phot_util.apparent_to_absolute(obj_phot[0], obj_distance)
return abs_mag, obj_phot[1]
def get_color_magnitude(self,
object_type: Optional[str] = None
) -> box.ColorMagBox:
"""
Function for extracting color-magnitude data from the selected
library.
Parameters
----------
object_type : str, None
Object type for which the colors and magnitudes are
extracted. Either field dwarfs ('field') or
young/low-gravity objects ('young'). All objects are
selected if set to ``None``.
Returns
-------
species.core.box.ColorMagBox
Box with the colors and magnitudes.
"""
if self.lib_type == "phot_lib":
with h5py.File(self.database, "r") as h5_file:
sptype = np.asarray(
h5_file[f"photometry/{self.library}/sptype"])
parallax = np.asarray(
h5_file[f"photometry/{self.library}/parallax"])
parallax_error = np.asarray(
h5_file[f"photometry/{self.library}/parallax_error"])
flag = np.asarray(h5_file[f"photometry/{self.library}/flag"])
obj_names = np.asarray(
h5_file[f"photometry/{self.library}/name"])
for i in range(sptype.shape[0]):
if isinstance(sptype[i], bytes):
sptype[i] = sptype[i].decode("utf-8")
if isinstance(flag[i], bytes):
flag[i] = flag[i].decode("utf-8")
if isinstance(obj_names[i], bytes):
obj_names[i] = obj_names[i].decode("utf-8")
if object_type is None:
indices = np.arange(0, np.size(sptype), 1)
elif object_type == "field":
indices = np.where(flag == "null")[0]
elif object_type == "young":
indices = []
for j, object_flag in enumerate(flag):
if "young" in object_flag:
indices.append(j)
elif "lowg" in object_flag:
indices.append(j)
indices = np.array(indices)
if indices.size > 0:
with h5py.File(self.database, "r") as h5_file:
mag1 = np.asarray(h5_file[
f"photometry/{self.library}/{self.filters_color[0]}"])
mag2 = np.asarray(h5_file[
f"photometry/{self.library}/{self.filters_color[1]}"])
else:
raise ValueError(
f"There is not data available from '{self.library}' for "
f"'{object_type}' type objects with the chosen filters.")
color = mag1 - mag2
distance = phot_util.parallax_to_distance(
(parallax, parallax_error))
if self.filter_mag == self.filters_color[0]:
mag, _ = phot_util.apparent_to_absolute(
(mag1, None), (distance[0], distance[1]))
elif self.filter_mag == self.filters_color[1]:
mag, _ = phot_util.apparent_to_absolute(
(mag2, None), (distance[0], distance[1]))
color = color[indices]
mag = mag[indices]
sptype = sptype[indices]
obj_names = obj_names[indices]
indices = []
for i in range(color.size):
if not np.isnan(color[i]) and not np.isnan(mag[i]):
indices.append(i)
colormag_box = box.create_box(
boxtype="colormag",
library=self.library,
object_type=object_type,
filters_color=self.filters_color,
filter_mag=self.filter_mag,
color=color[indices],
magnitude=mag[indices],
sptype=sptype[indices],
names=obj_names[indices],
)
elif self.lib_type == "spec_lib":
read_spec_0 = read_spectrum.ReadSpectrum(
spec_library=self.library, filter_name=self.filters_color[0])
read_spec_1 = read_spectrum.ReadSpectrum(
spec_library=self.library, filter_name=self.filters_color[1])
read_spec_2 = read_spectrum.ReadSpectrum(
spec_library=self.library, filter_name=self.filter_mag)
phot_box_0 = read_spec_0.get_magnitude(sptypes=None)
phot_box_1 = read_spec_1.get_magnitude(sptypes=None)
phot_box_2 = read_spec_2.get_magnitude(sptypes=None)
colormag_box = box.create_box(
boxtype="colormag",
library=self.library,
object_type=object_type,
filters_color=self.filters_color,
filter_mag=self.filter_mag,
color=phot_box_0.app_mag[:, 0] - phot_box_1.app_mag[:, 0],
magnitude=phot_box_2.abs_mag[:, 0],
sptype=phot_box_0.sptype,
names=None,
)
return colormag_box
def flux_to_magnitude(
self,
flux: float,
error: Optional[Union[float, np.ndarray]] = None,
parallax: Optional[Union[Tuple[float, Optional[float]],
Tuple[np.ndarray,
Optional[np.ndarray]]]] = None,
distance: Optional[Union[Tuple[float, Optional[float]],
Tuple[np.ndarray,
Optional[np.ndarray]]]] = None,
) -> Tuple[Union[Tuple[float, Optional[float]], Tuple[
np.ndarray, Optional[np.ndarray]]], Union[Tuple[
float, Optional[float]], Tuple[np.ndarray,
Optional[np.ndarray]]], ]:
"""
Function for converting a flux into a magnitude.
Parameters
----------
flux : float, np.ndarray
Flux (W m-2 um-1).
error : float, np.ndarray, None
Uncertainty (W m-2 um-1). Not used if set to None.
parallax : tuple(float, float), , tuple(np.ndarray, np.ndarray), None
Parallax and uncertainty (mas). The returned absolute
magnitude is set to ``None`` in case ``parallax`` and
``distance`` are set to ``None``. The error is not
propagated into the error on the absolute magnitude
in case the parallax uncertainty is set to ``None``,
for example ``parallax=(10., None)``.
distance : tuple(float, float), tuple(np.ndarray, np.ndarray), None
Distance and uncertainty (pc). The returned absolute
magnitude is set to ``None`` in case ``distance`` and
``parallax`` are set to ``None``. The error is not
propagated into the error on the absolute magnitude in
case the distance uncertainty is set to ``None``, for
example ``distance=(20., None)``. This parameter is
ignored if the ``parallax`` parameter is used.
Returns
-------
tuple(float, float), tuple(np.ndarray, np.ndarray)
Apparent magnitude and uncertainty.
tuple(float, float), tuple(np.ndarray, np.ndarray)
Absolute magnitude and uncertainty.
"""
if parallax is not None:
distance = phot_util.parallax_to_distance(parallax)
zp_flux = self.zero_point()
app_mag = self.vega_mag - 2.5 * np.log10(flux / zp_flux)
if error is None:
error_app_mag = None
error_abs_mag = None
else:
error_app_lower = app_mag - (self.vega_mag - 2.5 * np.log10(
(flux + error) / zp_flux))
error_app_upper = (self.vega_mag - 2.5 * np.log10(
(flux - error) / zp_flux)) - app_mag
error_app_mag = (error_app_lower + error_app_upper) / 2.0
if distance is None:
abs_mag = None
error_abs_mag = None
else:
abs_mag, error_abs_mag = phot_util.apparent_to_absolute(
(app_mag, error_app_mag), distance)
return (app_mag, error_app_mag), (abs_mag, error_abs_mag)
def get_color_magnitude(self,
object_type: Optional[str] = None) -> box.ColorMagBox:
"""
Function for extracting color-magnitude data from the selected library.
Parameters
----------
object_type : str, None
Object type for which the colors and magnitudes are extracted. Either field dwarfs
('field') or young/low-gravity objects ('young'). All objects are selected if set
to ``None``.
Returns
-------
species.core.box.ColorMagBox
Box with the colors and magnitudes.
"""
if self.lib_type == 'phot_lib':
with h5py.File(self.database, 'r') as h5_file:
sptype = np.asarray(h5_file[f'photometry/{self.library}/sptype'])
dist = np.asarray(h5_file[f'photometry/{self.library}/distance'])
dist_error = np.asarray(h5_file[f'photometry/{self.library}/distance_error'])
flag = np.asarray(h5_file[f'photometry/{self.library}/flag'])
obj_names = np.asarray(h5_file[f'photometry/{self.library}/name'])
if object_type is None:
indices = np.arange(0, np.size(sptype), 1)
elif object_type == 'field':
indices = np.where(flag == 'null')[0]
elif object_type == 'young':
indices = []
for j, object_flag in enumerate(flag):
if 'young' in object_flag:
indices.append(j)
elif 'lowg' in object_flag:
indices.append(j)
indices = np.array(indices)
if indices.size > 0:
with h5py.File(self.database, 'r') as h5_file:
mag1 = np.asarray(h5_file[f'photometry/{self.library}/{self.filters_color[0]}'])
mag2 = np.asarray(h5_file[f'photometry/{self.library}/{self.filters_color[1]}'])
else:
raise ValueError(f'There is not data available from \'{self.library}\' for '
f'\'{object_type}\' type objects with the chosen filters.')
color = mag1 - mag2
if self.filter_mag == self.filters_color[0]:
mag, _ = phot_util.apparent_to_absolute((mag1, None), (dist, dist_error))
elif self.filter_mag == self.filters_color[1]:
mag, _ = phot_util.apparent_to_absolute((mag2, None), (dist, dist_error))
color = color[indices]
mag = mag[indices]
sptype = sptype[indices]
obj_names = obj_names[indices]
indices = []
for i in range(color.size):
if not np.isnan(color[i]) and not np.isnan(mag[i]):
indices.append(i)
colormag_box = box.create_box(boxtype='colormag',
library=self.library,
object_type=object_type,
filters_color=self.filters_color,
filter_mag=self.filter_mag,
color=color[indices],
magnitude=mag[indices],
sptype=sptype[indices],
names=obj_names[indices])
elif self.lib_type == 'spec_lib':
read_spec_0 = read_spectrum.ReadSpectrum(spec_library=self.library,
filter_name=self.filters_color[0])
read_spec_1 = read_spectrum.ReadSpectrum(spec_library=self.library,
filter_name=self.filters_color[1])
read_spec_2 = read_spectrum.ReadSpectrum(spec_library=self.library,
filter_name=self.filter_mag)
phot_box_0 = read_spec_0.get_magnitude(sptypes=None)
phot_box_1 = read_spec_1.get_magnitude(sptypes=None)
phot_box_2 = read_spec_2.get_magnitude(sptypes=None)
colormag_box = box.create_box(boxtype='colormag',
library=self.library,
object_type=object_type,
filters_color=self.filters_color,
filter_mag=self.filter_mag,
color=phot_box_0.app_mag[:, 0]-phot_box_1.app_mag[:, 0],
magnitude=phot_box_2.abs_mag[:, 0],
sptype=phot_box_0.sptype,
names=None)
return colormag_box
def get_color_magnitude(self,
object_type):
"""
Parameters
----------
object_type : str
Returns
-------
species.core.box.ColorMagBox
Box with the colors and magnitudes.
"""
h5_file = h5py.File(self.database, 'r')
for i, item in enumerate(self.library):
try:
h5_file['photometry/'+item]
except KeyError:
h5_file.close()
species_db = database.Database()
species_db.add_photometry(item)
h5_file = h5py.File(self.database, 'r')
sptype_tmp = np.asarray(h5_file['photometry/'+item+'/sptype'])
distance_tmp = np.asarray(h5_file['photometry/'+item+'/distance']) # [pc]
flag_tmp = np.asarray(h5_file['photometry/'+item+'/flag'])
if object_type == 'field':
indices_tmp = np.where(flag_tmp == b'null')[0]
else:
indices_tmp = np.arange(0, np.size(sptype_tmp), 1)
if i == 0:
sptype = sptype_tmp
distance = distance_tmp
flag = flag_tmp
indices = indices_tmp
mag1 = np.asarray(h5_file['photometry/'+item+'/'+self.filters_color[0]])
mag2 = np.asarray(h5_file['photometry/'+item+'/'+self.filters_color[1]])
else:
distance_tmp = np.asarray(h5_file['photometry/'+item+'/distance']) # [pc]
distance = np.concatenate((distance, distance_tmp), axis=0)
sptype_tmp = np.asarray(h5_file['photometry/'+item+'/sptype'])
sptype = np.concatenate((sptype, sptype_tmp), axis=0)
flag = np.concatenate((flag, flag_tmp), axis=0)
indices = np.concatenate((indices, indices.shape+indices_tmp), axis=0)
mag1_tmp = np.asarray(h5_file['photometry/'+item+'/'+self.filters_color[0]])
mag2_tmp = np.asarray(h5_file['photometry/'+item+'/'+self.filters_color[1]])
mag1 = np.concatenate((mag1, mag1_tmp), axis=0)
mag2 = np.concatenate((mag2, mag2_tmp), axis=0)
color = mag1 - mag2
if self.filter_mag == self.filters_color[0]:
mag = phot_util.apparent_to_absolute(mag1, distance)
elif self.filter_mag == self.filters_color[1]:
mag = phot_util.apparent_to_absolute(mag2, distance)
h5_file.close()
return box.create_box(boxtype='colormag',
library=self.library,
object_type=object_type,
filters_color=self.filters_color,
filter_mag=self.filter_mag,
color=color[indices],
magnitude=mag[indices],
sptype=sptype[indices])