synthesizer.emissions.sed

Functionality related to spectra storage and manipulation.

When a spectra is computed from a Galaxy or a Galaxy component the resulting calculated spectra are stored in Sed objects. These provide helper functions for quick manipulation of the spectra. Seds can contain a single spectra or arbitrarily many, with all methods capable of acting on both consistently.

Example usage:

sed = Sed(lams, lnu) sed.get_fnu(redshift) sed.apply_attenutation(tau_v=0.7) sed.get_photo_fnu(filters, nthreads=4)

Functions

synthesizer.emissions.sed.plot_observed_spectra(spectra, redshift, fig=None, ax=None, show=False, ylimits=(), xlimits=(), figsize=(3.5, 5), label=None, draw_legend=True, x_units=None, y_units=None, filters=None, quantity_to_plot='fnu')[source]

Plot a spectra or dictionary of spectra.

Plots either a specific observed spectra or all observed spectra provided in a dictionary.

This function is a wrapper around plot_spectra.

This is a generic plotting function to be used either directly or to be wrapped by helper methods through Synthesizer.

Parameters:

  • spectra (dict/Sed) – The Sed objects from which to plot. This can either be a dictionary of Sed objects to plot multiple or a single Sed object to only plot one.

  • redshift (float) – The redshift of the observation.

  • fig (matplotlib.pyplot.figure) – The figure containing the axis. By default one is created in this function.

  • ax (matplotlib.axes) – The axis to plot the data on. By default one is created in this function.

  • 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.

  • label (str) – The label to give the spectra. Only applicable when Sed is a single spectra.

  • draw_legend (bool) – Whether to draw the legend.

  • x_units (unyt.unit_object.Unit) – The units of the x axis. This will be converted to a string and included in the axis label. By default the internal unit system is assumed unless this is passed.

  • y_units (unyt.unit_object.Unit) – The units of the y axis. This will be converted to a string and included in the axis label. By default the internal unit system is assumed unless this is passed.

  • filters (FilterCollection) – If given then the photometry is computed and both the photometry and filter curves are plotted

  • quantity_to_plot (str) – The sed property to plot. Can be “fnu”, “flam”, or “flux”. Defaults to “fnu”.

Returns:

fig (matplotlib.pyplot.figure)

The matplotlib figure object for the plot.

ax (matplotlib.axes)

The matplotlib axes object containing the plotted data.

synthesizer.emissions.sed.plot_spectra(spectra, fig=None, ax=None, show=False, ylimits=(), xlimits=(), figsize=(3.5, 5), label=None, draw_legend=True, x_units=None, y_units=None, quantity_to_plot='lnu')[source]

Plot a spectra or dictionary of spectra.

Plots either a specific spectra or all spectra provided in a dictionary. The plotted “type” of spectra is defined by the quantity_to_plot keyword arrgument which defaults to “lnu”.

This is a generic plotting function to be used either directly or to be wrapped by helper methods through Synthesizer.

Parameters:

  • spectra (dict/Sed) – The Sed objects from which to plot. This can either be a dictionary of Sed objects to plot multiple or a single Sed object to only plot one.

  • fig (matplotlib.pyplot.figure) – The figure containing the axis. By default one is created in this function.

  • ax (matplotlib.axes) – The axis to plot the data on. By default one is created in this function.

  • 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.

  • label (str) – The label to give the spectra. Only applicable when Sed is a single spectra.

  • draw_legend (bool) – Whether to draw the legend.

  • x_units (unyt.unit_object.Unit) – The units of the x axis. This will be converted to a string and included in the axis label. By default the internal unit system is assumed unless this is passed.

  • y_units (unyt.unit_object.Unit) – The units of the y axis. This will be converted to a string and included in the axis label. By default the internal unit system is assumed unless this is passed.

  • quantity_to_plot (str) – 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:

The matplotlib figure object for the plot. ax (matplotlib.axes):

The matplotlib axes object containing the plotted data.

Return type:

fig (matplotlib.pyplot.figure)

synthesizer.emissions.sed.plot_spectra_as_rainbow(sed, figsize=(5, 0.5), lam_min=3000, lam_max=8000, include_xaxis=True, logged=False, min_log_lnu=-2.0, use_fnu=False)[source]

Create a plot of the spectrum as a rainbow.

Parameters:

  • sed (synthesizer.emissions.Sed) – A synthesizer.emissions object.

  • figsize (tuple) – Fig-size tuple (width, height).

  • lam_min (float) – The min wavelength to plot in Angstroms.

  • lam_max (float) – The max wavelength to plot in Angstroms.

  • include_xaxis (bool) – Flag whther to include x-axis ticks and label.

  • logged (bool) – Flag whether to use logged luminosity.

  • min_log_lnu (float) – Minium luminosity to plot relative to the maximum.

  • use_fnu (bool) – Whether to plot fluxes or luminosities. If True fluxes are plotted, otherwise luminosities.

Returns:

fig (matplotlib.pyplot.figure)

The matplotlib figure object for the plot.

ax (matplotlib.axes)

The matplotlib axes object containing the plotted data.

Classes

class synthesizer.emissions.sed.Sed(lam, lnu=None, description=None)[source]

A class representing a spectral energy distribution (SED).

lam

The rest frame wavelength array.

Type:

Quantity, np.ndarray of float

nu

The rest frame frequency array.

Type:

Quantity, np.ndarray of float

lnu

The spectral luminosity density.

Type:

Quantity, np.ndarray of float

bolometric_luminosity

The bolometric luminosity.

Type:

Quantity, float

fnu

The spectral flux density.

Type:

Quantity, np.ndarray of float

obslam

The observed wavelength array.

Type:

Quantity, np.ndarray of float

obsnu

The observed frequency array.

Type:

Quantity, np.ndarray of float

description

An optional descriptive string defining the Sed.

Type:

str

redshift

The redshift of the Sed.

Type:

float

photo_lnu

The rest frame broadband photometry in arbitrary filters (filter_code: photometry).

Type:

dict, float

photo_fnu

The observed broadband photometry in arbitrary filters (filter_code: photometry).

Type:

dict, float

apply_attenuation(tau_v, dust_curve, mask=None)[source]

Apply attenuation to spectra.

Parameters:

  • tau_v (float/np.ndarray of float) – The V-band optical depth for every star particle.

  • dust_curve (synthesizer.emission_models.attenuation.*) – An instance of one of the dust attenuation models. (defined in synthesizer/emission_models.attenuation.py)

  • mask (array-like, bool) – A mask array with an entry for each spectra. Masked out spectra will be ignored when applying the attenuation. Only applicable for Sed’s holding an (N, Nlam) array.

Returns:

Sed

A new Sed containing the rest frame spectra of self attenuated by the transmission defined from tau_v and the dust curve.

apply_instrument_lams(instrument, nthreads=1)[source]

Apply an instrument to the spectra.

This will resample a Sed object on to the instrument’s wavelength array. It is actually just an intuitive wrapper around get_resampled_sed which will handle the actual resampling of both lnu and fnu (if applicable) using the instrument’s wavelength array.

Parameters:

  • instrument (Instrument) – An instance of the Instrument class.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

Returns:

Sed

A new Sed with the instrument applied.

property bolometric_luminosity

Return the bolometric luminosity of the SED with units.

This will integrate the SED using the trapezium method over the final axis (which is always the wavelength axis) for an arbitrary number of dimensions.

Returns:

The bolometric luminosity.

Return type:

bolometric_luminosity (unyt_array)

calculate_ionising_photon_production_rate(ionisation_energy=unyt_quantity(13.6, 'eV'), limit=100, nthreads=1)[source]

Calculate the ionising photon production rate.

Parameters:

  • ionisation_energy (unyt_array) – The ionisation energy.

  • limit (float/int) – An upper bound on the number of subintervals used in the integration adaptive algorithm.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

Returns:

Ionising photon luminosity (s^-1).

Return type:

float

concat(*other_seds)[source]

Concatenate the spectra arrays of multiple Sed objects.

This will combine the arrays along the first axis. For example concatenating two Seds with Sed.lnu.shape = (10, 1000) and Sed.lnu.shape = (20, 1000) will result in a new Sed with Sed.lnu.shape = (30, 1000). The wavelength array of the resulting Sed will be the array on self.

Incompatible spectra shapes will raise an error.

Parameters:

other_seds (object, Sed) – Any number of Sed objects to concatenate with self. These must have the same wavelength array.

Returns:

Sed

A new instance of Sed with the concatenated lnu arrays.

Raises:

InconsistentAddition – If wavelength arrays are incompatible an error is raised.

property energy

Get the wavelengths in terms of photon energies in eV.

Returns:

The energy coordinate.

Return type:

energy (unyt_array)

property flux

Get the spectra in terms fo flux.

Returns:

The flux array.

Return type:

flux (unyt_array)

property frequency

Alias to nu (frequency array).

Returns:

The frequency array.

Return type:

frequency (unyt_array)

get_fnu(cosmo, z, igm=None)[source]

Calculate the observed frame spectral energy distribution.

This will also populate the observed wavelength and frequency arrays with the observer frame values.

NOTE: if a redshift of 0 is passed the flux return will be calculated assuming a distance of 10 pc omitting IGM since at this distance IGM contribution makes no sense.

Parameters:

  • cosmo (astropy.cosmology) – astropy cosmology instance.

  • z (float) – The redshift of the spectra.

  • igm (igm) – The IGM class. e.g. synthesizer.igm.Inoue14. Defaults to None.

Returns:

fnu (ndarray)

Spectral flux density calcualted at d=10 pc

get_fnu0()[source]

Calculate the rest frame spectral flux density.

Uses a standard distance of 10 pcs.

This will also populate the observed wavelength and frequency arrays which in this case are the same as the emitted arrays.

Returns:

Spectral flux density calcualted at d=10 pc.

Return type:

fnu (ndarray)

get_lnu_at_lam(lam, kind=False)[source]

Return lnu at a provided wavelength.

Parameters:

  • lam (float/np.ndarray of float) – The wavelength(s) of interest.

  • kind (str) – Interpolation kind, see scipy.interp1d docs for more information. Possible values are ‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’, ‘previous’, and ‘next’.

Returns:

The luminosity (lnu) at the provided wavelength.

Return type:

luminosity (unyt-array)

get_lnu_at_nu(nu, kind=False)[source]

Return lnu at a provided frequency using 1d interpolation.

Parameters:

  • nu (float/np.ndarray of float) – The frequency(s) of interest.

  • kind (str) – Interpolation kind, see scipy.interp1d docs for more information. Possible values are ‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’, ‘previous’, and ‘next’.

Returns:

The luminosity (lnu) at the provided wavelength.

Return type:

unyt_array

get_photo_fnu(filters, verbose=True, nthreads=1)[source]

Calculate broadband fluxes using a FilterCollection object.

Parameters:

  • filters (FilterCollection) – A FilterCollection object.

  • verbose (bool) – Are we talking?

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

Returns:

A dictionary of fluxes in each filter in filters.

Return type:

(dict)

get_photo_lnu(filters, verbose=True, nthreads=1)[source]

Calculate broadband luminosities using a FilterCollection object.

Parameters:

  • filters (FilterCollection) – A FilterCollection object.

  • verbose (bool) – Are we talking?

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

Returns:

A dictionary of rest frame broadband luminosities.

Return type:

photo_lnu (dict)

get_resampled_sed(resample_factor=None, new_lam=None)[source]

Resample the spectra onto a new set of wavelength points.

This resampling can either be done by an integer number of wavelength elements per original wavelength element (i.e. up sampling), or by providing a new wavelength grid to resample on to.

Parameters:

  • resample_factor (int) – The number of additional wavelength elements to resample to.

  • new_lam (np.ndarray of float) – The wavelength array to resample onto.

Returns:

Sed

A new Sed with the rebinned rest frame spectra.

Raises:

InconsistentArgument – Either resample factor or new_lam must be supplied. If neither or both are passed an error is raised.

property llam

Get the spectral luminosity density per Angstrom.

Returns:

The spectral luminosity density per Angstrom array.

Return type:

luminosity (unyt_array)

property luminosity

Get the spectra in terms of luminosity.

Returns:

The luminosity array.

Return type:

luminosity (unyt_array)

property luminosity_lambda

Alias to llam.

Returns:

The spectral luminosity density per Angstrom array.

Return type:

luminosity (unyt_array)

property luminosity_nu

Alias to lnu.

Returns:

The spectral luminosity density per Hz array.

Return type:

luminosity (unyt_array)

measure_balmer_break(nthreads=1, integration_method='trapz')[source]

Measure the Balmer break.

This will use two windows at (3400,3600) and (4150,4250).

Parameters:

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

  • integration_method (str) – The integration method used. Options include ‘trapz’ and ‘simps’.

Returns:

float

The Balmer break strength

Raises:

UnrecognisedOption – If integration_method is an incompatible option an error is raised.

measure_beta(window=(unyt_quantity(1250., 'Å'), unyt_quantity(3000., 'Å')), nthreads=1, integration_method='trapz')[source]

Measure the UV continuum slope (beta).

If the provided window is len(2) a full fit to the spectra is performed otherwise the luminosity in two windows is calculated and used to determine the slope, similar to observations.

Parameters:

  • window (tuple, float) – The window in which to measure in terms of wavelength.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

  • integration_method (str) – The integration method used to calculate the window luminosity. Options include ‘trapz’ and ‘simps’.

Returns:

The UV continuum slope (beta)

Return type:

float

Raises:

UnrecognisedOption – If integration_method is an incompatible option an error is raised.

measure_break(blue, red, nthreads=1, integration_method='trapz')[source]

Measure a spectral break (e.g. the Balmer break) using two windows.

Parameters:

  • blue (tuple, float) – The wavelength limits of the blue window.

  • red (tuple, float) – The wavelength limits of the red window.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

  • integration_method (str) – The integration method used. Options include ‘trapz’ and ‘simps’.

Returns:

The ratio of the luminosity in the two windows.

Return type:

float

Raises:

UnrecognisedOption – If integration_method is an incompatible option an error is raised.

measure_colour(f1, f2)[source]

Measure a broadband colour.

Parameters:

  • f1 (str) – The blue filter code.

  • f2 (str) – The red filter code.

Returns:

The broadband colour.

Return type:

(float)

measure_d4000(definition='Bruzual83', nthreads=1, integration_method='trapz')[source]

Measure the D4000 index.

This can optionally use either the Bruzual83 or Balogh definitions.

Parameters:

  • definition (str) – The choice of definition: ‘Bruzual83’ or ‘Balogh’.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

  • integration_method (str) – The integration method used. Options include ‘trapz’ and ‘simps’.

Returns:

float

The Balmer break strength.

Raises:

UnrecognisedOption – If definition or integration_method is an incompatible option an error is raised.

measure_index(feature, blue, red)[source]

Measure an absorption feature index.

Parameters:

  • feature (tuple) – Absorption feature window.

  • blue (tuple) – Blue continuum window for fitting.

  • red (tuple) – Red continuum window for fitting.

Returns:

Absorption feature index in units of wavelength

Return type:

index (float)

measure_window_lnu(window, integration_method='trapz', nthreads=1)[source]

Measure lnu in a spectral window.

Parameters:

  • window (tuple, float) – The window in wavelength.

  • integration_method (str) – The integration method to use on the window. Options include ‘average’, or for integration ‘trapz’, and ‘simps’.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

Returns:

The luminosity in the window.

Return type:

luminosity (float)

Raises:

UnrecognisedOption – If integration_method is an incompatible option an error is raised.

measure_window_luminosity(window, integration_method='trapz', nthreads=1)[source]

Measure the luminosity in a spectral window.

Parameters:

  • window (tuple, float) – The window in wavelength.

  • integration_method (str) – The integration method used to calculate the window luminosity. Options include ‘trapz’ and ‘simps’.

  • nthreads (int) – The number of threads to use for the integration. If -1 then all available threads are used.

Returns:

The luminosity in the window.

Return type:

luminosity (float)

Raises:

UnrecognisedOption – If integration_method is an incompatible option an error is raised.

property ndim

Get the dimensions of the spectra array.

Returns:

Tuple

The shape of self.lnu

property nlam

Get the number of wavelength elements.

Returns:

The number of wavelength elements.

Return type:

int

plot_observed_spectra(**kwargs)[source]

Plot the observed spectra.

A wrapper for synthesizer.emissions.plot_observed_spectra()

plot_spectra(**kwargs)[source]

Plot the spectra.

A wrapper for synthesizer.emissions.plot_spectra()

plot_spectra_as_rainbow(**kwargs)[source]

Plot the spectra as a rainbow.

A wrapper for synthesizer.emissions.plot_spectra_as_rainbow()

plot_spectra_stack(nbin=100, fig=None, ax=None, show=False, order=None, quantity_to_plot='lnu', cmap='magma', vmin=None, vmax=None, xlimits=())[source]

Plot a stack of the top nbin spectra in a multi-spectra sed.

This is only applicable for Sed object with ndim == 2. It will plot bin the top nbin spectra into nbin wavelength bins, populate a grid where x is the wavelength and each y row is one of the spectra, and then plot this grid as an image.

This stack can optionally be ordered by their peak (from bluest peak to reddest peak), by their bolometric_luminosity (from dimmest to brightest), or by their luminosity at a specific wavelength (from dimmest to brightest). This is defined by the order keyword, “peak”, “bolometric_luminosity”, or a wavelength with units respectively.

Parameters:

  • nbin (int) – The number of bins to use for the stacking.

  • fig (matplotlib.pyplot.figure) – The figure containing the axis. By default one is created in this function.

  • ax (matplotlib.axes) – The axis to plot the data on. By default one is created in this function.

  • show (bool) – Flag for whether to show the plot or just return the figure and axes.

  • order (str/unyt_quantity) – The order to stack the spectra by. Can be “peak”, “bolometric_luminosity”, a wavelength with units, or None. By default the spectra will be plotted with the same order they have in the Sed object.

  • quantity_to_plot (str) – 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”.

  • cmap (str) – The matplotlib colormap to use for the plot. Defaults to “magma”.

  • vmin (float) – The minimum value for the color scale. If None, then we will use 3 orders of magntitude below the maximum value.

  • vmax (float) – The maximum value for the color scale. If None, then we will use the maximum value of the spectra.

  • xlimits (tuple of unyt_quantity) – The limits for the x axis. If None, then we will use the minimum and maximum wavelength of the spectra.

Returns:

The matplotlib figure object for the plot. ax (matplotlib.axes):

The matplotlib axes object containing the plotted data.

Return type:

fig (matplotlib.pyplot.figure)

scale(scaling, inplace=False, mask=None, lam_mask=None)[source]

Scale the lnu of the Sed object.

Note: only acts on the rest frame spectra. To get the scaled fnu get_fnu must be called on the newly scaled Sed object.

Parameters:

  • scaling (float) – The scaling to apply to lnu.

  • inplace (bool) – If True, the Sed object is modified in place. If False, a new Sed object is returned with the scaled lnu.

  • mask (array-like, bool) – A mask for the lnu array to apply the scaling to. This must be the same shape as the lnu array excluding the wavelength axis.

  • lam_mask (array-like, bool) – A mask for the wavelength array to apply the scaling to.

Returns:

Sed

A new instance of Sed with scaled lnu.

property shape

Get the shape of the spectra array.

Returns:

Tuple

The shape of self.lnu

sum()[source]

Sum the SED over all dimensions.

For multidimensional sed’s, sum the luminosity to provide a 1D integrated SED.

Returns:

Summed 1D SED.

Return type:

sed (object, Sed)

property wavelength

Alias to lam (wavelength array).

Returns:

The wavelength array.

Return type:

wavelength (unyt_array)