Source code for synthesizer.base_galaxy

"""A module for common functionality in Parametric and Particle Galaxies

The class described in this module should never be directly instatiated. It
only contains common attributes and methods to reduce boilerplate.
"""

from unyt import Mpc

from synthesizer import exceptions
from synthesizer.emission_models.attenuation.igm import Inoue14
from synthesizer.sed import Sed, plot_observed_spectra, plot_spectra
from synthesizer.units import accepts
from synthesizer.utils import TableFormatter
from synthesizer.warnings import deprecated, deprecation


[docs] class BaseGalaxy: """ The base galaxy class. This should never be directly instantiated. It instead contains the common functionality and attributes needed for parametric and particle galaxies. Attributes: spectra (dict, Sed) The dictionary containing a Galaxy's spectra. Each entry is an Sed object. This dictionary only contains combined spectra from All components that make up the Galaxy (Stars, Gas, BlackHoles). stars (particle.Stars/parametric.Stars) The Stars object holding information about the stellar population. gas (particle.Gas/parametric.Gas) The Gas object holding information about the gas distribution. black_holes (particle.BlackHoles/parametric.BlackHole) The BlackHole/s object holding information about the black hole/s. """ @accepts(centre=Mpc) def __init__(self, stars, gas, black_holes, redshift, centre, **kwargs): """ Instantiate the base Galaxy class. This is the parent class of both parametric.Galaxy and particle.Galaxy. Note: The stars, gas, and black_holes component objects differ for parametric and particle galaxies but are attached at this parent level regardless to unify the Galaxy syntax for both cases. Args: stars (particle.Stars/parametric.Stars) The Stars object holding information about the stellar population. gas (particle.Gas/parametric.Gas) The Gas object holding information about the gas distribution. black_holes (particle.BlackHoles/parametric.BlackHole) The BlackHole/s object holding information about the black hole/s. redshift (float) The redshift of the galaxy. centre (array) The centre of the galaxy. **kwargs Any additional attributes to attach to the galaxy object. """ # Add some place holder attributes which are overloaded on the children self.spectra = {} # Initialise the photometry dictionaries self.photo_lnu = {} self.photo_fnu = {} # Intialise the image dictionaries self.images_lnu = {} self.images_fnu = {} # Attach the components self.stars = stars self.gas = gas self.black_holes = black_holes # The redshift of the galaxy self.redshift = redshift self.centre = centre if getattr(self, "galaxy_type") is None: raise Warning( "Instantiating a BaseGalaxy object is not " "supported behaviour. Instead, you should " "use one of the derived Galaxy classes:\n" "`particle.galaxy.Galaxy`\n" "`parametric.galaxy.Galaxy`" ) # Attach any additional attributes for key, value in kwargs.items(): setattr(self, key, value) @property def photo_fluxes(self): """ Get the photometry fluxes. Returns: dict The photometry fluxes. """ deprecation( "The `photo_fluxes` attribute is deprecated. Use " "`photo_fnu` instead. Will be removed in v1.0.0" ) return self.photo_fnu @property def photo_luminosities(self): """ Get the photometry luminosities. Returns: dict The photometry luminosities. """ deprecation( "The `photo_luminosities` attribute is deprecated. Use " "`photo_lnu` instead. Will be removed in v1.0.0" ) return self.photo_lnu def __str__(self): """ Return a string representation of the galaxy object. Returns: table (str) A string representation of the galaxy object. """ # Intialise the table formatter formatter = TableFormatter(self) return formatter.get_table("Galaxy")
[docs] def get_equivalent_width(self, feature, blue, red, spectra_to_plot=None): """ Get all equivalent widths associated with a sed object Parameters ---------- index: float the index to be used in the computation of equivalent width. spectra_to_plot: float array An empty list of spectra to be populated. Returns ------- equivalent_width : float The calculated equivalent width at the current index. """ equivalent_width = None if not isinstance(spectra_to_plot, list): spectra_to_plot = list(self.spectra.keys()) for sed_name in spectra_to_plot: sed = self.spectra[sed_name] # Compute equivalent width equivalent_width = sed.measure_index(feature, blue, red) return equivalent_width
[docs] def get_observed_spectra(self, cosmo, igm=Inoue14): """ Calculate the observed spectra for all Sed objects within this galaxy. This will run Sed.get_fnu(...) and populate Sed.fnu (and sed.obslam and sed.obsnu) for all spectra in: - Galaxy.spectra - Galaxy.stars.spectra - Galaxy.gas.spectra (WIP) - Galaxy.black_holes.spectra And in the case of particle galaxies - Galaxy.stars.particle_spectra - Galaxy.gas.particle_spectra (WIP) - Galaxy.black_holes.particle_spectra Args: cosmo (astropy.cosmology.Cosmology) The cosmology object containing the cosmological model used to calculate the luminosity distance. igm (igm) The object describing the intergalactic medium (defaults to Inoue14). Raises: MissingAttribute If a galaxy has no redshift we can't get the observed spectra. """ # Ensure we have a redshift if self.redshift is None: raise exceptions.MissingAttribute( "This Galaxy has no redshift! Fluxes can't be" " calculated without one." ) # Loop over all combined spectra for sed in self.spectra.values(): # Calculate the observed spectra sed.get_fnu( cosmo=cosmo, z=self.redshift, igm=igm, ) # Do we have stars? if self.stars is not None: # Loop over all stellar spectra for sed in self.stars.spectra.values(): # Calculate the observed spectra sed.get_fnu( cosmo=cosmo, z=self.redshift, igm=igm, ) # Loop over all stellar particle spectra if getattr(self.stars, "particle_spectra", None) is not None: for sed in self.stars.particle_spectra.values(): # Calculate the observed spectra sed.get_fnu( cosmo=cosmo, z=self.redshift, igm=igm, ) # Do we have black holes? if self.black_holes is not None: # Loop over all black hole spectra for sed in self.black_holes.spectra.values(): # Calculate the observed spectra sed.get_fnu( cosmo=cosmo, z=self.redshift, igm=igm, ) # Loop over all black hole particle spectra if getattr(self.black_holes, "particle_spectra", None) is not None: for sed in self.black_holes.particle_spectra.values(): # Calculate the observed spectra sed.get_fnu( cosmo=cosmo, z=self.redshift, igm=igm, )
[docs] def get_spectra_combined(self): """ Combine all common component spectra from components onto the galaxy. e.g.: intrinsc = stellar_intrinsic + black_hole_intrinsic. For any combined spectra all components with a valid spectra will be combined and stored in Galaxy.spectra under the same key, but only if there are instances of that spectra key on more than 1 component. Possible combined spectra are: - "total" - "intrinsic" - "emergent" Note that this process is only applicable to integrated spectra. """ # Get the spectra we have on the components to combine spectra = {"total": [], "intrinsic": [], "emergent": []} for key in spectra: if self.stars is not None and key in self.stars.spectra: spectra[key].append(self.stars.spectra[key]) if ( self.black_holes is not None and key in self.black_holes.spectra ): spectra[key].append(self.black_holes.spectra[key]) if self.gas is not None and key in self.gas.spectra: spectra[key].append(self.gas.spectra[key]) # Now combine all spectra that have more than one contributing # component. # Note that sum when applied to a list of spectra # with overloaded __add__ methods will produce an Sed object # containing the combined spectra. for key, lst in spectra.items(): if len(lst) > 1: self.spectra[key] = sum(lst)
[docs] def get_photo_lnu(self, filters, verbose=True): """ Calculate luminosity photometry using a FilterCollection object. Photometry is calculated in spectral luminosity density units. Args: filters (filters.FilterCollection) A FilterCollection object. verbose (bool) Are we talking? Returns: PhotometryCollection A PhotometryCollection object containing the luminosity photometry in each filter in filters. """ # Get stellar photometry if self.stars is not None: self.stars.get_photo_lnu(filters, verbose) # If we have particle spectra do that too (not applicable to # parametric Galaxy) if getattr(self.stars, "particle_spectra", None) is not None: self.stars.get_particle_photo_lnu(filters, verbose) # Get black hole photometry if self.black_holes is not None: self.black_holes.get_photo_lnu(filters, verbose) # If we have particle spectra do that too (not applicable to # parametric Galaxy) if getattr(self.black_holes, "particle_spectra", None) is not None: self.black_holes.get_particle_photo_lnu(filters, verbose) # Get the combined photometry for spectra in self.spectra: # Create the photometry collection and store it in the object self.photo_lnu[spectra] = self.spectra[spectra].get_photo_lnu( filters, verbose )
@deprecated( "The `get_photo_luminosities` method is deprecated. Use " "`get_photo_lnu` instead. Will be removed in v1.0.0" ) def get_photo_luminosities(self, filters, verbose=True): """ Calculate luminosity photometry using a FilterCollection object. Alias to get_photo_lnu. Photometry is calculated in spectral luminosity density units. Args: filters (filters.FilterCollection) A FilterCollection object. verbose (bool) Are we talking? Returns: PhotometryCollection A PhotometryCollection object containing the luminosity photometry in each filter in filters. """ return self.get_photo_lnu(filters, verbose)
[docs] def get_photo_fnu(self, filters, verbose=True): """ Calculate flux photometry using a FilterCollection object. Photometry is calculated in spectral flux density units. Args: filters (object) A FilterCollection object. verbose (bool) Are we talking? Returns: PhotometryCollection A PhotometryCollection object containing the flux photometry in each filter in filters. """ # Get stellar photometry if self.stars is not None: self.stars.get_photo_fnu(filters, verbose) # If we have particle spectra do that too (not applicable to # parametric Galaxy) if getattr(self.stars, "particle_spectra", None) is not None: self.stars.get_particle_photo_fnu(filters, verbose) # Get black hole photometry if self.black_holes is not None: self.black_holes.get_photo_fnu(filters, verbose) # If we have particle spectra do that too (not applicable to # parametric Galaxy) if getattr(self.black_holes, "particle_spectra", None) is not None: self.black_holes.get_particle_photo_fnu(filters, verbose) # Get the combined photometry for spectra in self.spectra: # Create the photometry collection and store it in the object self.photo_fnu[spectra] = self.spectra[spectra].get_photo_fnu( filters, verbose )
@deprecated( "The `get_photo_fluxes` method is deprecated. Use " "`get_photo_fnu` instead. Will be removed in v1.0.0" ) def get_photo_fluxes(self, filters, verbose=True): """ Calculate flux photometry using a FilterCollection object. Alias to get_photo_fnu. Photometry is calculated in spectral flux density units. Args: filters (object) A FilterCollection object. verbose (bool) Are we talking? Returns: PhotometryCollection A PhotometryCollection object containing the flux photometry in each filter in filters. """ return self.get_photo_fnu(filters, verbose)
[docs] def plot_spectra( self, combined_spectra=True, stellar_spectra=False, gas_spectra=False, black_hole_spectra=False, show=False, ylimits=(), xlimits=(), figsize=(3.5, 5), quantity_to_plot="lnu", ): """ Plots either specific observed spectra (specified via combined_spectra, stellar_spectra, gas_spectra, and/or black_hole_spectra) or all spectra for any of the spectra arguments that are True. If any are false that component is ignored. Args: combined_spectra (bool/list, string/string) The specific combined galaxy spectra to plot. (e.g "total") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. stellar_spectra (bool/list, string/string) The specific stellar spectra to plot. (e.g. "incident") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. gas_spectra (bool/list, string/string) The specific gas spectra to plot. (e.g. "total") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. black_hole_spectra (bool/list, string/string) The specific black hole spectra to plot. (e.g "blr") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. show (bool) Flag for whether to show the plot or just return the figure and axes. ylimits (tuple) The limits to apply to the y axis. If not provided the limits will be calculated with the lower limit set to 1000 (100) times less than the peak of the spectrum for rest_frame (observed) spectra. xlimits (tuple) The limits to apply to the x axis. If not provided the optimal limits are found based on the ylimits. figsize (tuple) Tuple with size 2 defining the figure size. quantity_to_plot (string) The sed property to plot. Can be "lnu", "luminosity" or "llam" for rest frame spectra or "fnu", "flam" or "flux" for observed spectra. Defaults to "lnu". Returns: fig (matplotlib.pyplot.figure) The matplotlib figure object for the plot. ax (matplotlib.axes) The matplotlib axes object containing the plotted data. """ # We need to construct the dictionary of all spectra to plot for each # component based on what we've been passed spectra = {} # Get the combined spectra if combined_spectra: if isinstance(combined_spectra, list): spectra.update( {key: self.spectra[key] for key in combined_spectra} ) elif isinstance(combined_spectra, Sed): spectra.update( { "combined_spectra": combined_spectra, } ) else: spectra.update(self.spectra) # Get the stellar spectra if stellar_spectra: if isinstance(stellar_spectra, list): spectra.update( { "Stellar " + key: self.stars.spectra[key] for key in stellar_spectra } ) elif isinstance(stellar_spectra, Sed): spectra.update( { "stellar_spectra": stellar_spectra, } ) else: spectra.update( { "Stellar " + key: self.stars.spectra[key] for key in self.stars.spectra } ) # Get the gas spectra if gas_spectra: if isinstance(gas_spectra, list): spectra.update( { "Gas " + key: self.gas.spectra[key] for key in gas_spectra } ) elif isinstance(gas_spectra, Sed): spectra.update( { "gas_spectra": gas_spectra, } ) else: spectra.update( { "Gas " + key: self.gas.spectra[key] for key in self.gas.spectra } ) # Get the black hole spectra if black_hole_spectra: if isinstance(black_hole_spectra, list): spectra.update( { "Black Hole " + key: self.black_holes.spectra[key] for key in black_hole_spectra } ) elif isinstance(black_hole_spectra, Sed): spectra.update( { "black_hole_spectra": black_hole_spectra, } ) else: spectra.update( { "Black Hole " + key: self.black_holes.spectra[key] for key in self.black_holes.spectra } ) return plot_spectra( spectra, show=show, ylimits=ylimits, xlimits=xlimits, figsize=figsize, draw_legend=isinstance(spectra, dict), quantity_to_plot=quantity_to_plot, )
[docs] def plot_observed_spectra( self, combined_spectra=True, stellar_spectra=False, gas_spectra=False, black_hole_spectra=False, show=False, ylimits=(), xlimits=(), figsize=(3.5, 5), filters=None, quantity_to_plot="fnu", ): """ Plots either specific observed spectra (specified via combined_spectra, stellar_spectra, gas_spectra, and/or black_hole_spectra) or all spectra for any of the spectra arguments that are True. If any are false that component is ignored. Args: combined_spectra (bool/list, string/string) The specific combined galaxy spectra to plot. (e.g "total") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. stellar_spectra (bool/list, string/string) The specific stellar spectra to plot. (e.g. "incident") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. gas_spectra (bool/list, string/string) The specific gas spectra to plot. (e.g. "total") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. black_hole_spectra (bool/list, string/string) The specific black hole spectra to plot. (e.g "blr") - If True all spectra are plotted. - If a list of strings each specifc spectra is plotted. - If a single string then only that spectra is plotted. show (bool) Flag for whether to show the plot or just return the figure and axes. ylimits (tuple) The limits to apply to the y axis. If not provided the limits will be calculated with the lower limit set to 1000 (100) times less than the peak of the spectrum for rest_frame (observed) spectra. xlimits (tuple) The limits to apply to the x axis. If not provided the optimal limits are found based on the ylimits. figsize (tuple) Tuple with size 2 defining the figure size. filters (FilterCollection) If given then the photometry is computed and both the photometry and filter curves are plotted quantity_to_plot (string) The sed property to plot. Can be "lnu", "luminosity" or "llam" for rest frame spectra or "fnu", "flam" or "flux" for observed spectra. Defaults to "lnu". Returns: fig (matplotlib.pyplot.figure) The matplotlib figure object for the plot. ax (matplotlib.axes) The matplotlib axes object containing the plotted data. """ # We need to construct the dictionary of all spectra to plot for each # component based on what we've been passed spectra = {} # Get the combined spectra if combined_spectra: if isinstance(combined_spectra, list): spectra.update( {key: self.spectra[key] for key in combined_spectra} ) elif isinstance(combined_spectra, Sed): spectra.update( { "combined_spectra": combined_spectra, } ) else: spectra.update(self.spectra) # Get the stellar spectra if stellar_spectra: if isinstance(stellar_spectra, list): spectra.update( { "Stellar " + key: self.stars.spectra[key] for key in stellar_spectra } ) elif isinstance(stellar_spectra, Sed): spectra.update( { "stellar_spectra": stellar_spectra, } ) else: spectra.update( { "Stellar " + key: self.stars.spectra[key] for key in self.stars.spectra } ) # Get the gas spectra if gas_spectra: if isinstance(gas_spectra, list): spectra.update( { "Gas " + key: self.gas.spectra[key] for key in gas_spectra } ) elif isinstance(gas_spectra, Sed): spectra.update( { "gas_spectra": gas_spectra, } ) else: spectra.update( { "Gas " + key: self.gas.spectra[key] for key in self.gas.spectra } ) # Get the black hole spectra if black_hole_spectra: if isinstance(black_hole_spectra, list): spectra.update( { "Black Hole " + key: self.black_holes.spectra[key] for key in black_hole_spectra } ) elif isinstance(black_hole_spectra, Sed): spectra.update( { "black_hole_spectra": black_hole_spectra, } ) else: spectra.update( { "Black Hole " + key: self.black_holes.spectra[key] for key in self.black_holes.spectra } ) return plot_observed_spectra( spectra, self.redshift, show=show, ylimits=ylimits, xlimits=xlimits, figsize=figsize, draw_legend=isinstance(spectra, dict), filters=filters, quantity_to_plot=quantity_to_plot, )
[docs] def get_spectra( self, emission_model, dust_curves=None, tau_v=None, fesc=None, covering_fraction=None, mask=None, verbose=True, **kwargs, ): """ Generate spectra as described by the emission model. Args: emission_model (EmissionModel): The emission model to use. dust_curves (dict): An override to the emission model dust curves. Either: - None, indicating the dust_curves defined on the emission models should be used. - A single dust curve to apply to all emission models. - A dictionary of the form {<label>: <dust_curve instance>} to use a specific dust curve instance with particular properties. tau_v (dict): An override to the dust model optical depth. Either: - None, indicating the tau_v defined on the emission model should be used. - A float to use as the optical depth for all models. - A dictionary of the form {<label>: float(<tau_v>)} to use a specific optical depth with a particular model or {<label>: str(<attribute>)} to use an attribute of the component as the optical depth. fesc (dict): An override to the emission model escape fraction. Either: - None, indicating the fesc defined on the emission model should be used. - A float to use as the escape fraction for all models. - A dictionary of the form {<label>: float(<fesc>)} to use a specific escape fraction with a particular model or {<label>: str(<attribute>)} to use an attribute of the component as the escape fraction. mask (dict): An override to the emission model mask. Either: - None, indicating the mask defined on the emission model should be used. - A dictionary of the form {<label>: {"attr": attr, "thresh": thresh, "op": op}} to add a specific mask to a particular model. verbose (bool) Are we talking? kwargs (dict) Any additional keyword arguments to pass to the generator function. Returns: dict The combined spectra for the galaxy. """ # Get the spectra spectra, particle_spectra = emission_model._get_spectra( emitters={"stellar": self.stars, "blackhole": self.black_holes}, dust_curves=dust_curves, tau_v=tau_v, covering_fraction=covering_fraction, mask=mask, verbose=verbose, **kwargs, ) # Unpack the spectra to the right component for model in emission_model._models.values(): # Skip models we aren't saving if not model.save: continue if model.emitter == "galaxy": self.spectra[model.label] = spectra[model.label] elif model.emitter == "stellar": self.stars.spectra[model.label] = spectra[model.label] elif model.emitter == "blackhole": self.black_holes.spectra[model.label] = spectra[model.label] else: raise KeyError( f"Unknown emitter in emission model. ({model.emitter})" ) # If the model is particle based then we need to save the particle # spectra if model.per_particle: if model.emitter == "stellar": self.stars.particle_spectra[model.label] = ( particle_spectra[model.label] ) elif model.emitter == "blackhole": self.black_holes.particle_spectra[model.label] = ( particle_spectra[model.label] ) else: raise KeyError( "Unknown emitter in per particle " f"emission model. ({model.emitter})" ) return self.spectra[emission_model.label]
[docs] def get_lines( self, line_ids, emission_model, dust_curves=None, tau_v=None, fesc=None, covering_fraction=None, mask=None, verbose=True, **kwargs, ): """ Generate lines as described by the emission model. Args: line_ids (list): A list of line ids to include in the spectra. emission_model (EmissionModel): The emission model to use. dust_curves (dict): An override to the emission model dust curves. Either: - None, indicating the dust_curves defined on the emission models should be used. - A single dust curve to apply to all emission models. - A dictionary of the form {<label>: <dust_curve instance>} to use a specific dust curve instance with particular properties. tau_v (dict): An override to the dust model optical depth. Either: - None, indicating the tau_v defined on the emission model should be used. - A float to use as the optical depth for all models. - A dictionary of the form {<label>: float(<tau_v>)} to use a specific optical depth with a particular model or {<label>: str(<attribute>)} to use an attribute of the component as the optical depth. fesc (dict): An override to the emission model escape fraction. Either: - None, indicating the fesc defined on the emission model should be used. - A float to use as the escape fraction for all models. - A dictionary of the form {<label>: float(<fesc>)} to use a specific escape fraction with a particular model or {<label>: str(<attribute>)} to use an attribute of the component as the escape fraction. mask (dict): An override to the emission model mask. Either: - None, indicating the mask defined on the emission model should be used. - A dictionary of the form {<label>: {"attr": attr, "thresh": thresh, "op": op}} to add a specific mask to a particular model. verbose (bool) Are we talking? kwargs (dict) Any additional keyword arguments to pass to the generator function. Returns: dict The combined lines for the galaxy. """ # Get the lines lines, particle_lines = emission_model._get_lines( line_ids=line_ids, emitters={"stellar": self.stars, "blackhole": self.black_holes}, dust_curves=dust_curves, tau_v=tau_v, covering_fraction=covering_fraction, mask=mask, verbose=verbose, **kwargs, ) # Unpack the lines to the right component for model in emission_model._models.values(): # Skip models we aren't saving if not model.save: continue if model.emitter == "galaxy": self.lines[model.label] = lines[model.label] elif model.emitter == "stellar": self.stars.lines[model.label] = lines[model.label] elif model.emitter == "blackhole": self.black_holes.lines[model.label] = lines[model.label] else: raise KeyError( f"Unknown emitter in emission model. ({model.emitter})" ) # If the model is particle based then we need to save the particle # lines if model.per_particle: if model.emitter == "stellar": self.stars.particle_lines[model.label] = particle_lines[ model.label ] elif model.emitter == "blackhole": self.black_holes.particle_lines[model.label] = ( particle_lines[model.label] ) else: raise KeyError( "Unknown emitter in per particle " f"emission model. ({model.emitter})" ) return self.lines[emission_model.label]
[docs] def get_images_luminosity( self, resolution, fov, emission_model, img_type="smoothed", kernel=None, kernel_threshold=1, nthreads=1, limit_to=None, ): """ Make an ImageCollection from luminosities. For Parametric Galaxy objects, images can only be smoothed. An exception will be raised if a histogram is requested. For Particle Galaxy objects, images can either be a simple histogram ("hist") or an image with particles smoothed over their SPH kernel. Which images are produced is defined by the emission model. If any of the necessary photometry is missing for generating a particular image, an exception will be raised. The limit_to argument can be used if only a specific image is desired. Note that black holes will never be smoothed and only produce a histogram due to the point source nature of black holes. All images that are created will be stored on the emitter (Stars, BlackHole/s, or galaxy) under the images_lnu attribute. The image collection at the root of the emission model will also be returned. Args: resolution (Quantity, float) The size of a pixel. (Ignoring any supersampling defined by psf_resample_factor) fov : float The width of the image in image coordinates. emission_model (EmissionModel) The emission model to use to generate the images. img_type : str The type of image to be made, either "hist" -> a histogram, or "smoothed" -> particles smoothed over a kernel for a particle galaxy. Otherwise, only smoothed is applicable. stellar_photometry (string) The stellar spectra key from which to extract photometry to use for the image. blackhole_photometry (string) The black hole spectra key from which to extract photometry to use for the image. kernel (array-like, float) The values from one of the kernels from the kernel_functions module. Only used for smoothed images. kernel_threshold (float) The kernel's impact parameter threshold (by default 1). nthreads (int) The number of threads to use in the tree search. Default is 1. limit_to (str) Optionally pass a single model label to limit image generation to only that model. Returns: Image : array-like A 2D array containing the image. """ # Ensure we aren't trying to make a histogram for a parametric galaxy if self.galaxy_type == "Parametric" and img_type == "hist": raise exceptions.InconsistentArguments( "Parametric Galaxies can only produce smoothed images." ) # Get the images images = emission_model._get_images( resolution=resolution, fov=fov, emitters={ "stellar": self.stars, "blackhole": self.black_holes, "galaxy": self, }, img_type=img_type, mask=None, kernel=kernel, kernel_threshold=kernel_threshold, nthreads=nthreads, limit_to=limit_to, do_flux=False, ) # Unpack the images to the right component for model in emission_model._models.values(): # Skip models we aren't saving if not model.save or ( limit_to is not None and model.label != limit_to ): continue if model.emitter == "galaxy": self.images_lnu[model.label] = images[model.label] elif model.emitter == "stellar": self.stars.images_lnu[model.label] = images[model.label] elif model.emitter == "blackhole": self.black_holes.images_lnu[model.label] = images[model.label] else: raise KeyError( f"Unknown emitter in emission model. ({model.emitter})" ) # Return the image at the root of the emission model return images[emission_model.label]
[docs] def get_images_flux( self, resolution, fov, emission_model, img_type="smoothed", kernel=None, kernel_threshold=1, nthreads=1, limit_to=None, ): """ Make an ImageCollection from fluxes. For Parametric Galaxy objects, images can only be smoothed. An exception will be raised if a histogram is requested. For Particle Galaxy objects, images can either be a simple histogram ("hist") or an image with particles smoothed over their SPH kernel. Which images are produced is defined by the emission model. If any of the necessary photometry is missing for generating a particular image, an exception will be raised. The limit_to argument can be used if only a specific image is desired. Note that black holes will never be smoothed and only produce a histogram due to the point source nature of black holes. All images that are created will be stored on the emitter (Stars, BlackHole/s, or galaxy) under the images_fnu attribute. The image collection at the root of the emission model will also be returned. Args: resolution (Quantity, float) The size of a pixel. (Ignoring any supersampling defined by psf_resample_factor) fov : float The width of the image in image coordinates. emission_model (EmissionModel) The emission model to use to generate the images. img_type : str The type of image to be made, either "hist" -> a histogram, or "smoothed" -> particles smoothed over a kernel for a particle galaxy. Otherwise, only smoothed is applicable. kernel (array-like, float) The values from one of the kernels from the kernel_functions module. Only used for smoothed images. kernel_threshold (float) The kernel's impact parameter threshold (by default 1). nthreads (int) The number of threads to use in the tree search. Default is 1. Returns: Image : array-like A 2D array containing the image. """ # Ensure we aren't trying to make a histogram for a parametric galaxy if self.galaxy_type == "Parametric" and img_type == "hist": raise exceptions.InconsistentArguments( "Parametric Galaxies can only produce smoothed images." ) # Get the images images = emission_model._get_images( resolution=resolution, fov=fov, emitters={ "stellar": self.stars, "blackhole": self.black_holes, "galaxy": self, }, img_type=img_type, mask=None, kernel=kernel, kernel_threshold=kernel_threshold, nthreads=nthreads, limit_to=limit_to, do_flux=True, ) # Unpack the images to the right component for model in emission_model._models.values(): # Skip models we aren't saving if not model.save or ( limit_to is not None and model.label != limit_to ): continue if model.emitter == "galaxy": self.images_fnu[model.label] = images[model.label] elif model.emitter == "stellar": self.stars.images_fnu[model.label] = images[model.label] elif model.emitter == "blackhole": self.black_holes.images_fnu[model.label] = images[model.label] else: raise KeyError( f"Unknown emitter in emission model. ({model.emitter})" ) # Return the image at the root of the emission model return images[emission_model.label]
[docs] def clear_all_spectra(self): """ Clear all spectra. This method is a quick helper to clear all spectra from the galaxy object and its components. This will cover both integrated and per particle spectra if present. """ # Clear spectra self.spectra = {} if self.stars is not None: self.stars.clear_all_spectra() if self.black_holes is not None: self.black_holes.clear_all_spectra()
[docs] def clear_all_lines(self): """ Clear all lines. This method is a quick helper to clear all lines from the galaxy object and its components. This will cover both integrated and per particle lines if present. """ # Clear lines self.lines = {} if self.stars is not None: self.stars.clear_all_lines() if self.black_holes is not None: self.black_holes.clear_all_lines()
[docs] def clear_all_photometry(self): """ Clear all photometry. This method is a quick helper to clear all photometry from the galaxy object and its components. This will cover both integrated and per particle photometry if present. """ # Clear photometry self.photo_lnu = {} self.photo_fnu = {} if self.stars is not None: self.stars.clear_all_photometry() if self.black_holes is not None: self.black_holes.clear_all_photometry()
[docs] def clear_all_emissions(self): """ Clear all spectra, lines and photometry. This method is a quick helper to clear all spectra, lines, and photometry from the galaxy object and its components. This will cover both integrated and per particle emission. """ # Clear spectra self.clear_all_spectra() # Clear lines self.clear_all_lines() # Clear photometry self.clear_all_photometry()