ImsimCmpt¶

class lsst.ts.imsim.ImsimCmpt(num_of_zk: int)¶

Bases: object

Class to take configurations for each imsim component and generate full imsim configuration files.

Attributes¶

_output_dirstr: Output directory.
_output_img_dirstr: Output image directory.
opd_file_pathstr: OPD file path.
opd_metrlsst.ts.imsim.OpdMetrology: OPD metrology.
num_of_zkint: Number of Zernikes.
num_of_dofint: Number of degrees of freedom.
dof_in_umnumpy.ndarray: Degrees of freedom in microns.

Attributes Summary

`output_dir`
`output_img_dir`

Methods Summary

`add_config_header`(obs_metadata)	Write out the header section of the config file.
`add_sources_to_config`(config_yaml, inst_cat_path)	Add source information to config.
`analyze_opd_data`(cam_type[, zk_file_name, ...])	Analyze the OPD data.
`assemble_config_yaml`(obs_metadata, ...[, ...])	Parameters obs_metadata lsst.ts.imsim.ObsMetadata ObsMetadata dataclass object with observation information. config_pointer_file str The location of the config pointer file that specifies the location of configurations files for each imsim component. cam_type lsst.ts.imsim.utils.CamType Camera type. required_modules_file str or None Path to yaml file with required imsim modules. If None, then will use policy/requiredModulesDefault.yaml. (The default is None.)
`convert_obs_metadata_to_text`(obs_metadata)	Write out the evalVariables section of the config file.
`format_opd_text`(obs_metadata, cam_type)	Write out the OPD section of the config file.
`gen_inst_cat_stars`(sky_sim)	Add stars to the instance catalog.
`gen_instance_catalog`(sky_sim)	Generate the instance catalog.
`generate_star`(star_id, ra, dec, mag_norm[, ...])	Generate the star source.
`get_list_of_fwhm_sensor_data`(pssn_file_name)	Get the list of FWHM sensor data based on the OPD PSSN file.
`get_opd_gq_eff_fwhm_from_file`(pssn_file_name)	Get the OPD GQ effective FWHM from file.
`get_opd_pssn_from_file`(pssn_file_name)	Get the OPD PSSN from file.
`map_opd_data_to_list_of_wf_err`(...)	Map the OPD data to the list of wavefront error.
`reorder_and_save_wf_err_file`(list_of_wf_err, ...)	Reorder the wavefront error in the wavefront error list according to the reference sensor name list and save to a file.
`run_imsim`(config_file_path[, imsim_log_file])	Run imSim with the given configuration file.
`save_dof_in_um_file_for_next_iter`([...])	Save the DOF in um data to file for the next iteration.
`write_yaml_and_run_imsim`(config_path, ...[, ...])	Write yaml config file and run Imsim.

Attributes Documentation

output_dir¶

output_img_dir¶

Methods Documentation

add_config_header(obs_metadata: ObsMetadata) → str¶

Write out the header section of the config file.

Parameters¶

obs_metadatalsst.ts.imsim.ObsMetadata: ObsMetadata dataclass object with observation information.

Returns¶

str: Header information for ImSim config

add_sources_to_config(config_yaml: dict[str, Any], inst_cat_path: str, use_ccd_img: bool = True) → dict[str, Any]¶

Add source information to config. If using CCD it will add the instance catalog details. If only using OPD it will remove the instance catalog info so that we are not generating unnecessary images.

Parameters¶

config_yamldict: Dictionary that contains imsim config details to write to yaml.
inst_cat_pathstr: Path to instance catalog file.
use_ccd_imgbool, optional: When outputting CCD images this is set to True so that the instance catalog information is included in the configuration. For OPD only this should be set to False. (The default is True.)

Returns¶

dict: Updated yaml configuration.

analyze_opd_data(cam_type: CamType, zk_file_name: str = 'opd.zer', rot_opd_in_deg: float = 0.0, pssn_file_name: str = 'PSSN.txt') → None¶

Analyze the OPD data.

Rotate OPD to simulate the output by rotated camera. When anaylzing the PSSN, the unrotated OPD is used.

OPD: Optical path difference. PSSN: Normalized point source sensitivity.

Parameters¶

cam_typelsst.ts.imsim.utils.CamType: Camera type.
zk_file_namestr, optional: OPD in zk file name. (the default is “opd.zer”.)
rot_opd_in_degfloat, optional: Rotate OPD in degree in the counter-clockwise direction. (the default is 0.0.)
pssn_file_namestr, optional: PSSN file name. (the default is “PSSN.txt”.)

assemble_config_yaml(obs_metadata: ObsMetadata, config_pointer_file: str, cam_type: CamType, required_modules_file: str | None = None) → dict[str, Any]¶

Parameters¶

obs_metadatalsst.ts.imsim.ObsMetadata: ObsMetadata dataclass object with observation information.
config_pointer_filestr: The location of the config pointer file that specifies the location of configurations files for each imsim component.
cam_typelsst.ts.imsim.utils.CamType: Camera type.
required_modules_filestr or None: Path to yaml file with required imsim modules. If None, then will use policy/requiredModulesDefault.yaml. (The default is None.)

convert_obs_metadata_to_text(obs_metadata: ObsMetadata) → str¶

Write out the evalVariables section of the config file.

Parameters¶

obs_metadatalsst.ts.imsim.ObsMetadata: ObsMetadata dataclass object with observation information.

Returns¶

str: eval_variables for ImSim config

format_opd_text(obs_metadata: ObsMetadata, cam_type: CamType) → str¶

Write out the OPD section of the config file.

Parameters¶

obs_metadatalsst.ts.imsim.ObsMetadata: ObsMetadata dataclass object with observation information.
cam_typelsst.ts.imsim.utils.CamType: Camera type.

Returns¶

str: OPD information for ImSim config

gen_inst_cat_stars(sky_sim: SkySim) → str¶

Add stars to the instance catalog.

Parameters¶

sky_simlsst.ts.imsim.skySim.SkySim: The SkySim object with the stars to simulate.

Returns¶

str: Instance catalog text for the stars in the SkySim catalog.

gen_instance_catalog(sky_sim: SkySim) → str¶

Generate the instance catalog.

Parameters¶

sky_simlsst.ts.imsim.skySim.SkySim: The SkySim object with the stars to simulate.

Returns¶

str: Text to write to instance catalog file.

generate_star(star_id: int, ra: float, dec: float, mag_norm: float, sed_name: str = 'flatSED/sed_flat.txt.gz', redshift: float = 0, gamma_1: float = 0, gamma_2: float = 0, kappa: float = 0, delta_ra: float = 0, delta_dec: float = 0, source_type: str = 'point') → str¶

Generate the star source.

Parameters¶

star_idint: Star Id.
rafloat: The right ascension of the center of the object or image in decimal degrees.
decfloat: The declination of the center of the object in decimal degrees.
mag_normfloat: The normalization of the flux of the object in AB magnitudes at (500 nm)/(1+z) (which is roughly equivalent to V (AB) or g (AB)).
sed_namestr, optional: The name of the SED file with a file path that is relative to the $SIMS_SED_LIBRARY_DIR directory environment variable required for imSim.. (The default is “flatSED/sed_flat.txt.gz”)
redshiftfloat, optional: The redshift (or blueshift) of the object. Note that the SED does not need to be redshifted if using this. (the default is 0.)
gamma_1float, optional: The value of the shear parameter gamma1 used in weak lensing. (the default is 0.)
gamma_2float, optional: The value of the shear parameter gamma2 used in weak lensing. (the default is 0.)
kappafloat, optional: The value of the magnification parameter in weak lensing. (the default is 0.)
delta_rafloat, optional: The value of the declination offset in radians. This can be used either for weak lensing or objects that moved from another exposure if you do not want to change the source position in the first two columns. (the default is 0.)
delta_decfloat, optional: The value of the declination offset in radians. This can be used either for weak lensing or objects that moved from another exposure if you do not want to change the source position in the first two columns. (the default is 0.)
source_typestr, optional: The name of the spatial model to be used as defined below. (the default is “point”.)

Returns¶

str: Instance catalog entry for star.

get_list_of_fwhm_sensor_data(pssn_file_name: str) → tuple[numpy.ndarray, numpy.ndarray]¶

Get the list of FWHM sensor data based on the OPD PSSN file.

FWHM: Full width at half maximum. OPD: Optical path difference. PSSN: Normalized point source sensitivity.

Parameters¶

pssn_file_namestr: PSSN file name.
sensor_id_listlist: Reference sensor id list.

Returns¶

np.ndarray [object]: Numpy array with fwhm data. This is a numpy array of arrays. The data type is object because each element may have different number of elements.

get_opd_gq_eff_fwhm_from_file(pssn_file_name: str) → float¶

Get the OPD GQ effective FWHM from file.

OPD: Optical path difference. GQ: Gaussian quadrature. FWHM: Full width at half maximum. PSSN: Normalized point source sensitivity.

Parameters¶

pssn_file_namestr: PSSN file name.

Returns¶

float: OPD GQ effective FWHM.

get_opd_pssn_from_file(pssn_file_name: str) → ndarray¶

Get the OPD PSSN from file.

OPD: Optical path difference. PSSN: Normalized point source sensitivity.

Parameters¶

pssn_file_namestr: PSSN file name.

Returns¶

numpy.ndarray: PSSN.

map_opd_data_to_list_of_wf_err(opd_zk_file_name: str, sensor_id_list: list[int], sensor_name_list: list[str]) → list[lsst.ts.imsim.utils.sensor_wavefront_error.SensorWavefrontError]¶

Map the OPD data to the list of wavefront error.

OPD: Optical path difference.

Parameters¶

opd_zk_file_namestr: OPD zk file name.
sensor_id_listlist: Reference sensor ID list.
sensor_name_listlist: Reference sensor name list.

Returns¶

list [lsst.ts.wep.ctrlIntf.SensorWavefrontError]: List of SensorWavefrontError object.

reorder_and_save_wf_err_file(list_of_wf_err: list[lsst.ts.imsim.utils.sensor_wavefront_error.SensorWavefrontError], ref_sensor_name_list: list[str], camera: Camera, zk_file_name: str = 'wfs.zer') → None¶

Reorder the wavefront error in the wavefront error list according to the reference sensor name list and save to a file.

The unexisted wavefront error will be a numpy zero array. The unit is um.

Parameters¶

list_of_wf_errlist [lsst.ts.wep.ctrlIntf.SensorWavefrontData]: List of SensorWavefrontData object.
ref_sensor_name_listlist: Reference sensor name list.
cameralsst.afw.cameraGeom.Camera: Instrument.
zk_file_namestr, optional: Wavefront error file name. (the default is “wfs.zer”.)

run_imsim(config_file_path: str, imsim_log_file: str = '') → None¶

Run imSim with the given configuration file.

Parameters¶

config_file_pathstr: Path to the imSim configuration yaml file.
imsim_log_filestr, optional: Path to save imSim log output. If empty string then the code will just default to sending it to stdout. (The default is “”.)

save_dof_in_um_file_for_next_iter(dof_in_um_file_name: str = 'dofPertInNextIter.mat') → None¶

Save the DOF in um data to file for the next iteration.

DOF: degree of freedom.

Parameters¶

dof_in_um_file_namestr, optional: File name to save the DOF in um. (the default is “dofPertInNextIter.mat”.)

write_yaml_and_run_imsim(config_path: str, config_yaml: dict[str, Any], imsim_log_file: str = '') → None¶

Write yaml config file and run Imsim.

Parameters¶

config_pathstr: Path to write config yaml file.
config_yamldict: Dictionary that contains imsim config details to write to yaml.
imsim_log_filestr, optional: Path to save imSim log output. If empty string then the code will just default to sending it to stdout. (The default is “”.)

Navigation

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