DistortionParameters#

class esis.optics.DistortionParameters(yaw_grating, pitch_grating, roll_grating, roll_field_stop, spacing_rulings, displacement_primary, pitch, yaw, roll)[source]#

Bases: Printable

The degrees of freedom adjusted when fitting an instrument model to images.

An instance of this class serves both as a point in parameter space and as the prototype that defines the units and structure of the flat vector seen by scipy.optimize routines: named_arrays.pack() flattens it into a dimensionless vector and named_arrays.unpack() rebuilds it.

Examples

Gather the distortion parameters of the ESIS flight-1 design and flatten them into a vector suitable for scipy.optimize.

import named_arrays as na
import esis

instrument = esis.flights.f1.optics.design(num_distribution=0)
parameters = esis.optics.DistortionParameters.from_instrument(instrument)
na.pack(parameters)

ScalarArray(
    ndarray=[-268.17403457,    0.        ,    0.        ,    0.        ,    0.38660662,   -0.        ,    0.        ,
                0.        ,    0.        ],
    axes=('pack',),
)

Attributes

`yaw_grating`	The yaw angle of the diffraction grating.
`pitch_grating`	The pitch angle of the diffraction grating.
`roll_grating`	The roll angle of the diffraction grating.
`roll_field_stop`	The roll angle of the field stop.
`spacing_rulings`	The constant coefficient of the grating ruling spacing polynomial.
`displacement_primary`	The displacement of the primary mirror along the optic axis relative to its nominal focal length.
`pitch`	The pitch angle of the entire instrument.
`yaw`	The yaw angle of the entire instrument.
`roll`	The roll angle of the entire instrument.

Methods

`__init__`(yaw_grating, pitch_grating, ...)
`from_file`(path[, axis])	Load parameters saved by `to_file()`.
`from_instrument`(instrument)	Gather the current distortion parameters of the given instrument.
`to_file`(path[, metadata])	Save these parameters as a plain-text ECSV table.
`to_instrument`(instrument)	Apply these parameters to a copy of the given instrument.
`to_string`([prefix])	Public-facing version of the `__repr__` method that allows for defining a prefix string, which can be used to calculate how much whitespace to add to the beginning of each line of the result.

Inheritance Diagram

Parameters:

yaw_grating (Quantity | AbstractScalar)
pitch_grating (Quantity | AbstractScalar)
roll_grating (Quantity | AbstractScalar)
roll_field_stop (Quantity | AbstractScalar)
spacing_rulings (Quantity | AbstractScalar)
displacement_primary (Quantity | AbstractScalar)
pitch (Quantity | AbstractScalar)
yaw (Quantity | AbstractScalar)
roll (Quantity | AbstractScalar)

classmethod from_file(path, axis=None)[source]#

Load parameters saved by to_file().

The logical axis of the parameters is recovered from the axis entry of the table header.

Parameters:

path (str | Path) – The path of the file to read.
axis (None | str) – The name to use for the logical axis of the parameters, overriding the name recorded in the file.

Return type:

DistortionParameters

classmethod from_instrument(instrument)[source]#

Gather the current distortion parameters of the given instrument.

The parameters are converted to a canonical set of units (arcmin for the grating angles, arcsec for the instrument pointing, etc.) so that the components of the packed vector are of order unity and bounds built from different instances are consistent.

Parameters:: instrument (AbstractInstrument) – The instrument model to gather the parameters from.
Return type:: DistortionParameters

to_file(path, metadata=None)[source]#

Save these parameters as a plain-text ECSV table.

The fields become the columns of the table (with their units), and the elements along the (single) logical axis of the parameters become its rows, so that fit results can be committed to version control and reviewed as text. Scalar fields are broadcast along the axis.

Parameters:

path (str | Path) – The path of the file to write.
metadata (None | dict[str, Any]) – Additional provenance recorded in the table header, for example the date and configuration of the fit that produced the parameters.

Raises:

ValueError – If the parameters have more than one logical axis.

Return type:

None