pysme.atmosphere package

pysme.atmosphere package#

Subpackages#

Submodules#

pysme.atmosphere.atmosphere module#

Handles reading and interpolation of atmopshere (grid) data

exception pysme.atmosphere.atmosphere.AtmosphereError[source]#

Bases: RuntimeError

Something went wrong with the atmosphere interpolation

class pysme.atmosphere.atmosphere.Atmosphere(*args, **kwargs)[source]#

Bases: Collection

Atmosphere structure contains all information to describe the solar atmosphere i.e. temperature etc in the different layers as well as stellar parameters and abundances

property abund#

elemental abundances

Type:

Abund

property citation_info#

citation for this atmosphere

Type:

str

property depth#

flag that determines whether to use RHOX or TAU for calculations

Type:

str

property dtype#
property geom#

the geometry of the atmopshere model

Type:

str

property height#

height of the spherical model

Type:

array

property interp#

flag that determines whether to use RHOX or TAU for interpolation

Type:

str

property logg#

surface gravity in log10(cgs)

Type:

float

property lonh#

?

Type:

float

property method#

whether the data source is a grid or a fixed atmosphere

Type:

str

property monh#

metallicity

Type:

float

property names#
property ndep#
property opflag#

opacity flags

Type:

array of size (20,)

property radius#

radius of the spherical model

Type:

float

property rho#

density profile

Type:

array

property rhox#

mass column density

Type:

array

property source#

datafile name of this data, or atmosphere grid/file

Type:

str

property tau#

continuum optical depth

Type:

array

property teff#

effective temperature in Kelvin

Type:

float

property temp#

temperature profile in Kelvin

Type:

array

property vturb#

turbulence velocity in km/s

Type:

float

property wlstd#

wavelength standard deviation

Type:

float

property xna#

number density of atoms in 1/cm**3

Type:

array

property xne#

number density of electrons in 1/cm**3

Type:

array

class pysme.atmosphere.atmosphere.AtmosphereGrid(natmo, npoints, **kwargs)[source]#

Bases: recarray

A grid of atmospheres, used for the interpolation of model atmospheres. Each entry represents one atmosphere model.

get(teff, logg, monh)[source]#
classmethod load(filename)[source]#

Load the atmosphere grid data from disk

save(filename)[source]#

Save the Atmopshere grid to a file using a numpy save format

property abund_format#

format of the Abundance field, as defined by the Abund class

Type:

str

property citation_info#

Citation text to cite in your papers

Type:

str

property depth#

flag that determines whether to use RHOX or TAU for calculations

Type:

str

property geom#

the geometry of the atmopshere model

Type:

str

property interp#

flag that determines whether to use RHOX or TAU for interpolation

Type:

str

property method#

whether the data source is a grid or a fixed atmosphere

Type:

str

property ndep#
property source#

datafile name of this data

Type:

str

pysme.atmosphere.interpolation module#

Handles reading and interpolation of atmopshere (grid) data

class pysme.atmosphere.interpolation.AtmosphereInterpolator(depth=None, interp=None, geom=None, lfs_atmo=None, verbose=0)[source]#

Bases: object

determine_depth_scale(depth, atmo_grid)[source]#

Determine ATMO.DEPTH radiative transfer depth variable. Order of precedence:

  1. Value of ATMO_IN.DEPTH, if it exists and is set

  2. Value of ATMO_GRID[0].DEPTH, if it exists and is set

  3. ‘RHOX’, if ATMO_GRID.RHOX exists (preferred over ‘TAU’ for depth)

  4. ‘TAU’, if ATMO_GRID.TAU exists

Check that INTERP is valid and the corresponding field exists in ATMO.

Parameters:

  • depth ({"RHOX", "TAU", None}) – requested value, or None for autoselection based in available grid

  • atmo_grid (AtmosphereGrid) – input atmosphere grid to interpolate on

Returns:

depth – The chosen depth scale

Return type:

{“TAU”, “RHOX”}

Raises:

AtmosphereError – If an invalid value was set in atmo_in/atmo_grid

determine_interpolation_scale(interp, atmo_grid)[source]#

Determine ATMO.INTERP interpolation variable. Order of precedence:

  1. Value of ATMO_IN.INTERP, if it exists and is set

  2. Value of ATMO_GRID[0].INTERP, if it exists and is set

  3. ‘TAU’, if ATMO_GRID.TAU exists (preferred over ‘RHOX’ for interpolation)

  4. ‘RHOX’, if ATMO_GRID.RHOX exists

Check that INTERP is valid and the corresponding field exists in ATMO.

Parameters:

  • interp ({"RHOX", "TAU", None}) – requested interpolation axis, or None for autoselect

  • atmo_grid (AtmosphereGrid) – Atmosphere grid for interpolation

Returns:

interp – the interpolation axis

Return type:

{“RHOX”, “TAU”}

Raises:

AtmosphereError – if a non valid parameter is set in atmo_in/atmo_grid

find_corner_models(teff, logg, monh, atmo_grid)[source]#

Find the models in the grid that bracket the given stellar parameters

The purpose of the first major set of code blocks is to find values of [M/H] in the grid that bracket the requested [M/H]. Then in this subset of models, find values of log(g) in the subgrid that bracket the requested log(g). Then in this subset of models, find values of Teff in the subgrid that bracket the requested Teff. The net result is a set of 8 models in the grid that bracket the requested stellar parameters. Only these 8 “corner” models will be used in the interpolation that constitutes the remainder of the program.

Parameters:

  • teff (float) – effective temperature

  • logg (float) – surface gravity

  • monh (float) – metallicity

  • atmo_grid (AtmosphereGrid) – atmosphere grid to search models in

  • verbose (int, optional) – determines how many debugging messages to print, by default 0

interp_atmo_constrained(x, y, err, par, x2, y2, constraints=None, **kwargs)[source]#

Apply a constraint on each parameter, to have it approach zero

Parameters:

  • x (array[n]) – x data

  • y (array[n]) – y data

  • err (array[n]) – errors on y data

  • par (list[4]) – initial guess for fit parameters - see interp_atmo_func

  • x2 (array) – independent variable for tabulated input function

  • y2 (array) – dependent variable for tabulated input function

  • kwargs (**) –

    passes keyword arguments to interp_atmo_func

    ndepint

    number of depth points in supplied quantities

    constraintsarray[nconstraint], optional

    error vector for constrained parameters. Use errors of 0 for unconstrained parameters.

Returns:

  • ret (list of floats) – best fit parameters

  • yfit (array of size (n,)) – best fit to data

interp_atmo_func(x1, par, x2, y2, ndep=None, y1=None)[source]#

Apply a horizontal shift to x2. Apply a vertical shift to y2. Interpolate onto x1 the shifted y2 as a function of shifted x2.

Parameters:

  • x1 (array[ndep1]) – independent variable for output function

  • par (array[3]) – shift parameters par[0] - horizontal shift for x2 par[1] - vertical shift for y2 par[2] - vertical scale factor for y2

  • x2 (array[ndep2]) – independent variable for tabulated input function

  • y2 (array[ndep2]) – dependent variable for tabulated input function

  • ndep (int, optional) – number of depth points in atmospheric structure (default is use all)

  • y1 (array[ndep2], optional) – data values being fitted

Note

Only pass y1 if you want to restrict the y-values of extrapolated data points. This is useful when solving for the shifts, but should not be used when calculating shifted functions for actual use, since this restriction can cause discontinuities.

interp_atmo_grid(atmo_grid, teff, logg, monh)[source]#

General routine to interpolate in 3D grid of model atmospheres

Parameters:

  • Teff (float) – effective temperature of desired model (K).

  • logg (float) – logarithmic gravity of desired model (log cm/s/s).

  • MonH (float) – metalicity of desired model.

  • atmo_in (Atmosphere) – Input atmosphere

  • verbose ({0, 1}, optional) – how much information to plot/print (default: 0)

  • plot (bool, optional) – wether to plot debug information (default: False)

  • reload (bool) – wether to reload atmosphere information from disk (default: False)

Returns:

atmo – interpolated atmosphere data

Return type:

Atmosphere

interp_atmo_pair(atmo1, atmo2, frac, interpvar='RHOX', itop=0)[source]#

Interpolate between two model atmospheres, accounting for shifts in the mass column density or optical depth scale.

How it works:

1. The second atmosphere is fitted onto the first, individually for each of the four atmospheric quantitites: T, xne, xna, rho. The fitting uses a linear shift in both the (log) depth parameter and in the (log) atmospheric quantity. For T, the midpoint of the two atmospheres is aligned for the initial guess. The result of this fit is used as initial guess for the other quantities. A penalty function is applied to each fit, to avoid excessively large shifts on the depth scale. 2. The mean of the horizontal shift in each parameter is used to construct the common output depth scale. 3. Each atmospheric quantity is interpolated after shifting the two corner models by the amount determined in step 1), rescaled by the interpolation fraction (frac).

Parameters:

  • atmo1 (Atmosphere) – first atmosphere to interpolate

  • atmo2 (Atmosphere) – second atmosphere to interpolate

  • frac (float) – interpolation fraction: 0.0 -> atmo1 and 1.0 -> atmo2

  • interpvar ({"RHOX", "TAU"}, optional) – atmosphere interpolation variable (default:”RHOX”).

  • itop (int, optional) – index of top point in the atmosphere to use. default is to use all points (itop=0). use itop=1 to clip top depth point.

  • atmop (array[5, ndep], optional) – interpolated atmosphere prediction (for plots) Not needed if atmospheres are provided as structures. (default: None)

  • verbose ({0, 5}, optional) – diagnostic print level (default 0: no printing)

  • plot ({-1, 0, 1}, optional) – diagnostic plot level. Larger absolute value yields more plots. Negative values cause a wait for keypress after each plot. (default: 0, no plots)

  • old (bool, optional) – also plot result from the old interpkrz2 algorithm. (default: False)

Returns:

atmo – interpolated atmosphere .RHOX (vector[ndep]) mass column density (g/cm^2) .TAU (vector[ndep]) reference optical depth (at 5000 Å) .temp (vector[ndep]) temperature (K) .xne (vector[ndep]) electron number density (1/cm^3) .xna (vector[ndep]) atomic number density (1/cm^3) .rho (vector[ndep]) mass density (g/cm^3)

Return type:

Atmosphere

interpolate_corner_models(teff, logg, monh, icor, atmo_grid, interp='RHOX', itop=1)[source]#

Interpolate over the 8 corner models in the cube around the stellar parameters

The code below interpolates between 8 corner models to produce the output atmosphere. In the first step, pairs of models at each of the 4 combinations of log(g) and Teff are interpolated to the desired value of [M/H]. These 4 new models are then interpolated to the desired value of log(g), yielding 2 models at the requested [M/H] and log(g). Finally, this pair of models is interpolated to the desired Teff, producing a single output model.

Interpolation is done on the logarithm of all quantities to improve linearity of the fitted data. Kurucz models sometimes have very small fractional steps in mass column at the top of the atmosphere. These cause wild oscillations in splines fitted to facilitate interpolation onto a common depth scale. To circumvent this problem, we ignore the top point in the atmosphere by setting itop=1.

Parameters:

  • teff (float) – effective temperature

  • logg (float) – surface gravity

  • monh (float) – metallicity

  • icor (array_like) – indices of the corner models

  • atmo_grid (AtmosphereGrid) – atmosphere grid with input models

  • interp (str, optional) – interpolation axis, by default “RHOX”

  • itop (int, optional) – index of the topmost point in the RHOX scale, by default 1

Returns:

atmo3 – Interpolated atmosphere

Return type:

Atmosphere

spherical_model_correction(atmo_grid, icor, logg)[source]#

Correct the radius of the model grids, for the stellar parameters if necessary

If all interpolated models were spherical, the interpolated model should also be reported as spherical. This enables spherical-symmetric radiative transfer in the spectral synthesis.

Formulae for mass and radius at the corners of interpolation cube:

log(M/Msol) = log g - log g_sol - 2*log(R_sol / R) 2 * log(R / R_sol) = log g_sol - log g + log(M / M_sol)

Parameters:

  • atmo_grid (AtmosphereGrid) – complete atmosphere grid

  • icor (array_like) – indices for the corner models that were interpolated from the atmosphere grid

Returns:

  • geom ({“PP”, “SPH”}) – The geometry of the interpolated models

  • radius (None, array) – The corrected radius of the models, if geom == “SPH”. Otherwise None.

pysme.atmosphere.krzfile module#

class pysme.atmosphere.krzfile.KrzFile(filename, source=None)[source]#

Bases: Atmosphere

Read .krz atmosphere files

get_mu_from_abund()[source]#
load(filename)[source]#

Load data from krz files. The code will automatically judge the file source of ATLAS or MARCS.

Parameters:

filename (str) – name of the file to load

pysme.atmosphere.savfile module#

class pysme.atmosphere.savfile.SavFile(filename, source=None, lfs=None)[source]#

Bases: AtmosphereGrid

IDL savefile atmosphere grid

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