Limb darkened maps

class starry.Map

The starry map class for purely limb-darkened maps.

This class handles light curves of purely limb-darkened objects in emitted light.

Note

Instantiate this class by calling starry.Map() with ydeg set to zero and both rv and reflected set to False.

property N

Total number of map coefficients. Read-only

This is equal to \(N_\mathrm{y} + N_\mathrm{u} + N_\mathrm{f}\).

property Nf

Number of spherical harmonic coefficients in the filter. Read-only

This is equal to \((f_\mathrm{deg} + 1)^2\).

property Nu

Number of limb darkening coefficients, including \(u_0\). Read-only

This is equal to \(u_\mathrm{deg} + 1\).

property Ny

Number of spherical harmonic coefficients. Read-only

This is equal to \((y_\mathrm{deg} + 1)^2\).

property amp

The overall amplitude of the map in arbitrary units. This factor multiplies the intensity and the flux and is thus proportional to the luminosity of the object. For multi-wavelength maps, this is a vector corresponding to the amplitude of each wavelength bin.

property angle_unit

An astropy.units unit defining the angle metric for this map.

property deg

Total degree of the map. Read-only

This is equal to \(y_\mathrm{deg} + u_\mathrm{deg} + f_\mathrm{deg}\).

draw()

Draw a map from the posterior distribution.

This method draws a random map from the posterior distribution and sets the y map vector and amp map amplitude accordingly. Users should call solve() to enable this attribute.

property drorder

Differential rotation order. Read-only

property fdeg

Degree of the multiplicative filter. Read-only

flux(**kwargs)

Compute and return the light curve.

Parameters

  • xo (scalar or vector, optional) – x coordinate of the occultor relative to this body in units of this body’s radius.

  • yo (scalar or vector, optional) – y coordinate of the occultor relative to this body in units of this body’s radius.

  • zo (scalar or vector, optional) – z coordinate of the occultor relative to this body in units of this body’s radius.

  • ro (scalar, optional) – Radius of the occultor in units of this body’s radius.

intensity(mu=None, x=None, y=None)

Compute and return the intensity of the map.

Parameters

  • mu (scalar or vector, optional) – the radial parameter \(\mu\), equal to the cosine of the angle between the line of sight and the normal to the surface. Default is None.

  • x (scalar or vector, optional) – the Cartesian x position on the surface in units of the body’s radius. Default is None.

  • y (scalar or vector, optional) – the Cartesian y position on the surface in units of the body’s radius. Default is None.

Note

Users must provide either mu or x and y.

limbdark_is_physical()

Check whether the limb darkening profile (if any) is physical.

This method uses Sturm’s theorem to ensure that the limb darkening intensity is positive everywhere and decreases monotonically toward the limb.

Returns

Whether or not the limb darkening profile is physical.

Return type

bool

lnlike(*, design_matrix=None, woodbury=True, **kwargs)

Returns the log marginal likelihood of the data given a design matrix.

This method computes the marginal likelihood (marginalized over the spherical harmonic coefficients) given a light curve and its covariance (set via the set_data() method) and a Gaussian prior on the spherical harmonic coefficients (set via the set_prior() method).

Parameters

  • design_matrix (matrix, optional) – The flux design matrix, the quantity returned by design_matrix(). Default is None, in which case this is computed based on kwargs.

  • woodbury (bool, optional) – Solve the linear problem using the Woodbury identity? Default is True. The Woodbury identity is used to speed up matrix operations in the case that the number of data points is much larger than the number of spherical harmonic coefficients. In this limit, it can speed up the code by more than an order of magnitude. Keep in mind that the numerical stability of the Woodbury identity is not great, so if you’re getting strange results try disabling this. It’s also a good idea to disable this in the limit of few data points and large spherical harmonic degree.

  • kwargs (optional) – Keyword arguments to be passed directly to design_matrix(), if a design matrix is not provided.

Returns

The log marginal likelihood, a scalar.

property nw

Number of wavelength bins. Read-only

remove_prior()

Remove the prior on the map coefficients.

render(res=300)

Compute and return the intensity of the map on a grid.

Returns an image of shape (res, res).

Parameters

res (int, optional) – The resolution of the map in pixels on a side. Defaults to 300.

reset(**kwargs)

Reset all map coefficients and attributes.

Note

Does not reset custom unit settings.

set_data(flux, C=None, cho_C=None)

Set the data vector and covariance matrix.

This method is required by the solve() method, which analytically computes the posterior over surface maps given a dataset and a prior, provided both are described as multivariate Gaussians.

Parameters

  • flux (vector) – The observed light curve.

  • C (scalar, vector, or matrix) – The data covariance. This may be a scalar, in which case the noise is assumed to be homoscedastic, a vector, in which case the covariance is assumed to be diagonal, or a matrix specifying the full covariance of the dataset. Default is None. Either C or cho_C must be provided.

  • cho_C (matrix) – The lower Cholesky factorization of the data covariance matrix. Defaults to None. Either C or cho_C must be provided.

set_prior(*, mu=None, L=None, cho_L=None)

Set the prior mean and covariance of the spherical harmonic coefficients.

This method is required by the solve() method, which analytically computes the posterior over surface maps given a dataset and a prior, provided both are described as multivariate Gaussians.

Note that the prior is placed on the amplitude-weighted coefficients, i.e., the quantity x = map.amp * map.y. Because the first spherical harmonic coefficient is fixed at unity, x[0] is the amplitude of the map. The actual spherical harmonic coefficients are given by x / map.amp.

This convention allows one to linearly fit for an arbitrary map normalization at the same time as the spherical harmonic coefficients, while ensuring the starry requirement that the coefficient of the \(Y_{0,0}\) harmonic is always unity.

Parameters

  • mu (scalar or vector) – The prior mean on the amplitude-weighted spherical harmonic coefficients. Default is unity for the first term and zero for the remaining terms. If this is a vector, it must have length equal to Ny.

  • L (scalar, vector, or matrix) – The prior covariance. This may be a scalar, in which case the covariance is assumed to be homoscedastic, a vector, in which case the covariance is assumed to be diagonal, or a matrix specifying the full prior covariance. Default is None. Either L or cho_L must be provided.

  • cho_L (matrix) – The lower Cholesky factorization of the prior covariance matrix. Defaults to None. Either L or cho_L must be provided.

show(**kwargs)

Display an image of the map, with optional animation. See the docstring of render() for more details and additional keywords accepted by this method.

Parameters

  • ax (optional) – A matplotlib axis instance to use. Default is to create a new figure.

  • cmap (string or colormap instance, optional) – The matplotlib colormap to use. Defaults to plasma.

  • figsize (tuple, optional) – Figure size in inches. Default is (3, 3) for orthographic maps and (7, 3.5) for rectangular maps.

  • projection (string, optional) – The map projection. Accepted values are ortho, corresponding to an orthographic projection (as seen on the sky), and rect, corresponding to an equirectangular latitude-longitude projection. Defaults to ortho.

  • colorbar (bool, optional) – Display a colorbar? Default is False.

  • grid (bool, optional) – Show latitude/longitude grid lines? Defaults to True.

  • interval (int, optional) – Interval between frames in milliseconds (animated maps only). Defaults to 75.

  • file (string, optional) – The file name (including the extension) to save the figure or animation to. Defaults to None.

  • html5_video (bool, optional) – If rendering in a Jupyter notebook, display as an HTML5 video? Default is True. If False, displays the animation using Javascript (file size will be larger.)

  • dpi (int, optional) – Image resolution in dots per square inch. Defaults to the value defined in matplotlib.rcParams.

  • bitrate (int, optional) – Bitrate in kbps (animations only). Defaults to the value defined in matplotlib.rcParams.

  • norm (optional) – The color normalization passed to matplotlib.pyplot.imshow. Default is None.

Note

Pure limb-darkened maps do not accept a projection keyword.

property solution

The posterior probability distribution for the map.

This is a tuple containing the mean and lower Cholesky factorization of the covariance of the amplitude-weighted spherical harmonic coefficient vector, obtained by solving the regularized least-squares problem via the solve() method.

Note that to obtain the actual covariance matrix from the lower Cholesky factorization \(L\), simply compute \(L L^\top\).

Note also that this is the posterior for the amplitude-weighted map vector. Under this convention, the map amplitude is equal to the first term of the vector and the spherical harmonic coefficients are equal to the vector normalized by the first term.

solve(*, design_matrix=None, **kwargs)

Solve the linear least-squares problem for the posterior over maps.

This method solves the generalized least squares problem given a light curve and its covariance (set via the set_data() method) and a Gaussian prior on the spherical harmonic coefficients (set via the set_prior() method). The map amplitude and coefficients are set to the maximum a posteriori (MAP) solution.

Parameters

  • design_matrix (matrix, optional) – The flux design matrix, the quantity returned by design_matrix(). Default is None, in which case this is computed based on kwargs.

  • kwargs (optional) – Keyword arguments to be passed directly to design_matrix(), if a design matrix is not provided.

Returns

A tuple containing the posterior mean for the amplitude-weighted spherical harmonic coefficients (a vector) and the Cholesky factorization of the posterior covariance (a lower triangular matrix).

Note

Users may call draw() to draw from the posterior after calling this method.

property u

The vector of limb darkening coefficients. Read-only

To set this vector, index the map directly using one index: map[n] = ... where n is the degree of the limb darkening coefficient. This may be an integer or an array of integers. Slice notation may also be used.

property udeg

Limb darkening degree. Read-only

property y

The spherical harmonic coefficient vector. Read-only

To set this vector, index the map directly using two indices: map[l, m] = ... where l is the spherical harmonic degree and m is the spherical harmonic order. These may be integers or arrays of integers. Slice notation may also be used.

property ydeg

Spherical harmonic degree of the map. Read-only