simulate_snia

Attributes

logger

Functions

construct_snia_source(oversampled_observations, zpdf)

Create a SNIA source/host pair with characteristics from an OpSim.

load_and_register_passband(passbands_dir, to_use)

Load the passband from files and register with sncosmo.

draw_single_random_sn(source, opsim, passbands[, ...])

Process a single random SN realization.

run_snia_end2end(oversampled_observations, passbands_dir)

Test that we can sample and create SN Ia simulation using the salt3 model.

Module Contents

logger[source]
construct_snia_source(oversampled_observations, zpdf)[source]

Create a SNIA source/host pair with characteristics from an OpSim.

Parameters:

  • oversampled_observations (OpSim) – The opsim data to use.

  • zpdf (interp1d) – The PDF for the redshift.

Returns:

source – The SEDModel to sample.

Return type:

SEDModel

load_and_register_passband(passbands_dir, to_use)[source]

Load the passband from files and register with sncosmo.

Parameters:

  • passbands_dir (str) – The directory containing the passband files to use.

  • to_use (list) – A list of the passbands to use. Example: [“g”, “r”]

Returns:

passbands – The loaded and processed PassbandGroup.

Return type:

PassbandGroup

draw_single_random_sn(source, opsim, passbands, state=None, rng_info=None)[source]

Process a single random SN realization.

Parameters:

  • source (BasePhysicalModel) – The BasePhysicalModel to use for the flux computation.

  • opsim (OpSim) – The OpSim for the simulations

  • passbands (PassbandGroup) – The passbands to use in generating the observations.

  • state (GraphState) – The sample values to use. If None resamples the state.

  • rng_info (numpy.random._generator.Generator, optional) – A given numpy random number generator to use for this computation. If not provided, the function uses the default random number generator.

Returns:

res – A dictionary of useful information about the run.

Return type:

dict

run_snia_end2end(oversampled_observations, passbands_dir, solid_angle=0.0001, nsample=1, check_sncosmo=False, rng_info=None)[source]

Test that we can sample and create SN Ia simulation using the salt3 model.

Parameters:

  • oversampled_observations (OpSim) – The opsim data to use.

  • passbands_dir (str) – The name of the directory holding the passband information.

  • solid_angle (float) – Solid angle for calculating number of SN.

  • nsample (int) – The number of samples to test. Default: 1

  • check_sncosmo (bool) – Run the simulation a second time directly with sncosmo and compare the answers. This should only be turned on for testing. Default: False

  • rng_info (numpy.random._generator.Generator, optional) – A given numpy random number generator to use for this computation. If not provided, the function uses the default random number generator.

Returns:

  • res_list (dict) – A dictionary of lists of sampling and result information.

  • passbands (PassbandGroup) – The passbands used.