desk.outputs package

Submodules

desk.outputs.interpolate_dusty module

desk.outputs.interpolate_dusty.check_input_range(grid_name: str, unique_teff: ndarray, unique_tinner: ndarray, unique_tau: ndarray, teff_new: float, tinner_new: float, tau_new: float)[source]

Checks if the user-inputted model values are within the range of the model grid. This is critical for the interpolation.

Parameters:

  • gridname (str) – Name of model grid.

  • unique_teff (array) – Unique effective temperatures within the model grid.

  • unique_tinner (array) – Unique inner dust temperatures within the model grid.

  • unique_tau (array) – Unique effective temperatures within the modelgrid.

  • teff_new (float) – User-defined effective temperature.

  • tinner_new (float) – User-defined inner dust temperature.

  • tau_new (float) – User-defined optical depth at 10 microns.

Returns:

Raises exception if outside of the model ranges of effective temperature, inner dust temperature or optical depth at 10 microns.

Return type:

Error

desk.outputs.interpolate_dusty.interpolate(grid_name: str, luminosity: float, teff_new: float, tinner_new: float, tau_new: float, distance_in_kpc: float, custom_output_name: str, print_outputs: bool)[source]

A script for returning a model within any grid or returning an interpolated model that fits within the given parameter space. The interpolation interpolates over the flux at each wavelength in the model grid.

Parameters:

  • grid_name (str) – Name of grid used.

  • luminosity (float) – luminosity of model (in solar luminosities)

  • teff_new (float) – Effective temperature of desired grid.

  • tinner_new (float) – Inner dust temperature of desired grid.

  • tau_new (float) – optical depth specified at 10 microns.

  • distance_in_kpc (float) – Distance in kpc.

  • custom_output_name (str) – Custom name for output in save_model_spectrum.

  • print_outputs (bool) – Whether to print output expansion velocities and mass loss rates.

Returns:

type – File with desired model. Model parameters are printed.

Return type:

csv file

desk.outputs.parameter_ranges module

desk.outputs.parameter_ranges.create_par()[source]

Creates a figure showing the range of sampling of the used model grid. The inputs are taken from the results file after fitting.

Returns:

Figure showing range and sampling of each parameter in grid by row.

Return type:

png

desk.outputs.plot_pdf module

desk.outputs.plot_pdf.plot(par, pdf, bin_total_prob, best)[source]

Creates png with probability distribution of given parameter.

Parameters:

  • par (str) – paramter name

  • pdf (class) – probability distribtion function from create_pdf.

  • bin_total_prob (1D array) – Description of parameter bin_total_prob.

  • best (float) – best value

Returns:

probability plot.

Return type:

creates png

desk.outputs.plotting_seds module

desk.outputs.plotting_seds.add_axis_labels(fig, fontsize, _flux)[source]
desk.outputs.plotting_seds.counter_annotations(counter: int, ax)[source]
desk.outputs.plotting_seds.create_fig(source_path, source_filename, dest_path, save_name, flux)[source]

Creates single SED figure of all fit SEDs using the source_filename file.

Parameters:

  • source_path (str) – Path to source.

  • source_filename (str) – fit results filename.

  • dest_path (str) – Path to save figure.

  • save_name (str) – Figure filename to be saved.

  • flux (str) – flux type (Wm2 or Jy)

Returns:

SED figure with data in blue and model in black.

Return type:

png

desk.outputs.plotting_seds.get_model_and_data_for_plotting(counter, target, source_path, source_filename, flux)[source]

Gets data from target.csv file and model from grid file.

Parameters:

  • counter (int) – The nth item being fit, starting at 1.

  • target (astropy table row) – Results of fit item read from fitting_plotting_outputs.csv.

  • source_path (str) – Path of source

  • source_filename (str) – Filename of fitting results

  • flux (str) – flux type (Wm2 or Jy)

Returns:

  • x_data (array) – log of the wavelength of the data in microns.

  • y_data (array) – log of the flux of the data in w*m^-2

  • x_model (array) – log of the wavelength of the model in microns.

  • y_model (array) – log of the flux of the model in w*m^-2

desk.outputs.plotting_seds.plot_model(x_model: list, y_model: list, ax)[source]
desk.outputs.plotting_seds.plot_phot(x_data: list, y_data: list, ax)[source]
desk.outputs.plotting_seds.set_inward_ticks(ax)[source]
desk.outputs.plotting_seds.set_limits(x_model, y_model, x_data, y_data, ax)[source]
desk.outputs.plotting_seds.single_figures(source_path, source_filename, dest_path, flux)[source]

Takes results from fitting_plotting_outputs.csv and plots SEDs. Plots in individual figures.

Returns:

SED figures with data in blue and model in black.

Return type:

png’s

desk.outputs.plotting_seds.source_name_annotation(name: str, ax)[source]
desk.outputs.plotting_seds.wm2_to_Jy(wave_in_microns: list, wm2: list)[source]

Module contents