Observer module#

Fov Angles#

class cherab.iter.observer.fov_angles.FoV(view, phi_step=0.025, theta_step=0.025)#

Diagnostic field of view Selects rays for a given line of sight (LoS). Returns ray’s indeces.

Parameters:

view (str | Mapping) – ITER H-alpha spectroscopy view: ‘EP11_top’ (default), ‘EP11_bottom’ or ‘EP12’.
phi_step (float) – Azimuthal (horizontal) angle grid step in degrees, by default 0.025.
theta_step (float) – Polar (vertical) angle grid step in degrees, by default 0.025.

Variables:

cs (ndarray) – center of sight
theta_max (float) – maximum of theta angle in units of radius
phi_max (float) – maximum of phi angle in units of radius
rays (ndarray) – rays array
theta (ndarray) – theta array
phi (ndarray) – phi array
view (Mapping) – view config mapping

calc_coordination_system_view()#

calculate coordinate system view using ray corners coords.

Returns:: tuple include (cs, theta_max, phi_max)
Return type:: tuple[ndarray, float, float]

euler()#

Returns (yaw, pitch, roll) for (-Y)*(-X)’Z’’ intrinsic rotation

Returns:: (yaw, pitch, roll)
Return type:: tuple[float, float, float]

create_rays(phi_step=0.025, theta_step=0.025)#

create rays

Parameters:

phi_step (float) – Azimuthal (horizontal) angle grid step in degrees, by default 0.025
theta_step (float) – Polar (vertical) angle grid step in degrees, by default 0.025

Returns:

rays, theta-1d, phi-1d array

Return type:

tuple[ndarray, ndarray, ndarray]

Fov Camera#

class cherab.iter.observer.fov_camera.FovCamera(pixels, fov=(90.0, 90.0), sensitivity=1.0, frame_sampler=None, pipelines=None, **kewargs)#

Bases: Observer2D

Angular field-of-view observer.

A camera that launches rays from the observer’s origin point over a specified field of view in spherical coordinates. Unlike pinhole camera, each pixel of the final image represents a solid angle of collection, not a rectangle on the plane.

Parameters:

pixels (tuple[int, int]) – A tuple of pixel dimensions for the camera, i.e. (512, 512).
fov (tuple[float, float]) – The field of view of the camera in degrees in horizontal and vertical directions, by default (90., 90.)
sensitivity (float) – The sensitivity of each pixel, by default 1.0
frame_sampler (FrameSampler2D) – The frame sampling strategy, defaults to adaptive sampling RGBAdaptiveSampler2D (i.e. extra samples for noisier pixels).
pipelines (list[Pipeline2D]) – The list of pipelines that will process the spectrum measured at each pixel by the camera, by default RGBPipeline2D
**kwargs (Observer2D and _ObserverBase. properties, optional) – kwargs are used to specify properties like a parent, transform, pipelines, etc.

property fov: tuple[float, float]#: The field of view of the camera in degrees in horizontal and vertical directions

property sensitivity: float#: The sensitivity of each pixel

RTM Pipelines#

class cherab.iter.observer.rtm_pipelines.RtmPipeline0D(name=None)#

Bases: Pipeline0D

initialise(min_wavelength, max_wavelength, spectral_bins, spectral_slices, quiet)#

Initialises containers for the pipeline’s processing output.

The deriving class should use this method to perform any initialisation needed for their calculations.

This is a virtual method and must be implemented in a sub class.

Parameters:

min_wavelength (float) – The minimum wavelength in the spectral range.
max_wavelength (float) – The maximum wavelength in the spectral range.
spectral_bins (int) – Number of spectral samples across wavelength range.
spectral_slices (list) – List of spectral sub-ranges for cases where spectral rays is > 1 (i.e. dispersion effects turned on).
quiet (bool) – When True, suppresses output to the terminal.

pixel_processor(slice_id)#

Initialise and return a pixel processor for this pipeline.

Called by worker threads, each worker will request a pixel processor for processing the output of their work from each pipeline.

This is a virtual method and must be implemented in a sub class.

Parameters:: slice_id (int) – The integer identifying the spectral slice being worked on by the requesting worker thread.
Return type:: PixelProcessor

update(slice_id, packed_result, pixel_samples)#

Updates the internal results array with packed results from the pixel processor.

After worker threads have observed the world and used the pixel processor to process the spectra into packed results, the worker then passes the packed results to the pipeline with the update() method.

If this pipeline implements some form of visualisation, update the visualisation at the end of this method.

This is a virtual method and must be implemented in a sub class.

Parameters:

slice_id (int) – The integer identifying the spectral slice being worked on by the worker thread.
packed_result (tuple) – The tuple of results generated by this pipeline’s PixelProcessor.
samples (int) – The number of samples taken by the worker. Needed for ensuring accuracy of statistical errors when combining new samples with previous results.

finalise()#

Finalises the results when rendering has finished.

This method is called when all workers have finished sampling and the results need to undergo any final processing.

If this pipeline implements some form of visualisation, use this method to plot the final visualisation of results.

This is a virtual method and must be implemented in a sub class.

class cherab.iter.observer.rtm_pipelines.RtmPipeline1D(name=None)#

Bases: Pipeline1D

initialise(pixels, pixel_samples, min_wavelength, max_wavelength, spectral_bins, spectral_slices, quiet)#

Initialises containers for the pipeline’s processing output.

The deriving class should use this method to perform any initialisation needed for their calculations.

This is a virtual method and must be implemented in a sub class.

Parameters:

pixels (tuple) – A tuple defining the pixel dimensions being sampled (i.e. (256,)).
pixel_samples (int) – The number of samples being taken per pixel. Needed for statistical calculations.
min_wavelength (float) – The minimum wavelength in the spectral range.
max_wavelength (float) – The maximum wavelength in the spectral range.
spectral_bins (int) – Number of spectral samples across wavelength range.
spectral_slices (list) – List of spectral sub-ranges for cases where spectral rays is > 1 (i.e. dispersion effects turned on).
quiet (bool) – When True, suppresses output to the terminal.

pixel_processor(pixel, slice_id)#

Initialise and return a pixel processor for this pipeline and pixel coordinate.

Called by worker threads, each worker will request a pixel processor for the pixel they are processing.

This is a virtual method and must be implemented in a sub class.

Parameters:

pixel (int) – The pixel coordinate of the pixel being sampled by the worker.
slice_id (int) – The integer identifying the spectral slice being worked on by the requesting worker thread.

Return type:

PixelProcessor

update(pixel, slice_id, packed_result)#

Updates the internal results array with packed results from the pixel processor.

After worker threads have observed the world and used the pixel processor to process the spectra into packed results, the worker then passes the packed results for the current pixel to the pipeline with the update() method. This method should add the results for this pixel to the pipeline’s results array.

If this pipeline implements some form of visualisation, update the visualisation at the end of this method.

This is a virtual method and must be implemented in a sub class.

Parameters:

pixel (int) – The integer identifying the pixel being worked on.
slice_id (int) – The integer identifying the spectral slice being worked on by the worker thread.
packed_result (tuple) – The tuple of results generated by this pipeline’s PixelProcessor.

finalise()#

Finalises the results when rendering has finished.

This method is called when all workers have finished sampling and the results need to undergo any final processing.

If this pipeline implements some form of visualisation, use this method to plot the final visualisation of results.

This is a virtual method and must be implemented in a sub class.

class cherab.iter.observer.rtm_pipelines.RtmPipeline2D(name=None)#

Bases: Pipeline2D

initialise(pixels, pixel_samples, min_wavelength, max_wavelength, spectral_bins, spectral_slices, quiet)#

Initialises containers for the pipeline’s processing output.

The deriving class should use this method to perform any initialisation needed for their calculations.

This is a virtual method and must be implemented in a sub class.

Parameters:

pixels (tuple) – A tuple defining the pixel dimensions being sampled (i.e. (512, 512)).
pixel_samples (int) – The number of samples being taken per pixel. Needed for statistical calculations.
min_wavelength (float) – The minimum wavelength in the spectral range.
max_wavelength (float) – The maximum wavelength in the spectral range.
spectral_bins (int) – Number of spectral samples across wavelength range.
spectral_slices (list) – List of spectral sub-ranges for cases where spectral rays is > 1 (i.e. dispersion effects turned on).
quiet (bool) – When True, suppresses output to the terminal.

pixel_processor(x, y, slice_id)#

Initialise and return a pixel processor for this pipeline and pixel coordinate.

Called by worker threads, each worker will request a pixel processor for the pixel they are currently processing.

This is a virtual method and must be implemented in a sub class.

Parameters:

x (int) – The x pixel coordinate (x, y) of the pixel being sampled by the worker.
y (int) – The y pixel coordinate (x, y) of the pixel being sampled by the worker.
slice_id (int) – The integer identifying the spectral slice being worked on by the requesting worker thread.

Return type:

PixelProcessor

update(x, y, slice_id, packed_result)#

Updates the internal results array with packed results from the pixel processor.

If this pipeline implements some form of visualisation, update the visualisation at the end of this method.

This is a virtual method and must be implemented in a sub class.

Parameters:

x (int) – The x pixel coordinate (x, y) of the pixel being sampled by the worker.
y (int) – The y pixel coordinate (x, y) of the pixel being sampled by the worker.
slice_id (int) – The integer identifying the spectral slice being worked on by the worker thread.
packed_result (tuple) – The tuple of results generated by this pipeline’s PixelProcessor.

finalise()#

Finalises the results when rendering has finished.

This method is called when all workers have finished sampling and the results need to undergo any final processing.

If this pipeline implements some form of visualisation, use this method to plot the final visualisation of results.

This is a virtual method and must be implemented in a sub class.

class cherab.iter.observer.rtm_pipelines.RtmPixelProcessor(bins)#

Bases: PixelProcessor

PixelProcessor that stores ray transfer matrix for each pixel.

add_sample(spectrum, sensitivity)#

Processes a spectrum and adds it to internal buffer.

This is a virtual method and must be implemented in a sub class.

Parameters:

spectrum (Spectrum) – The sampled spectrum.
sensitivity (float) – The pixel sensitivity.

pack_results()#

Packs the contents of the internal buffer.

This method must return a tuple. The contents and length of the tuple are entirely defined by the needs of the pipeline.

This is a virtual method and must be implemented in a sub class.

Return type:: tuple

Sampler#

class cherab.iter.observer.sampler.SequentialFullFrameSampler1D#

Bases: FrameSampler1D

generate_tasks(pixels)#

Generates a list of tuples that selects the pixels to render.

Must return a list of tuples where each tuple contains the id of a pixel to render. For example:

tasks = [(1,), (5,), (512,), …]

This is a virtual method and must be implemented in a sub class.

Parameters:: pixels (int) – The number of pixels in the frame.
Return type:: list

class cherab.iter.observer.sampler.SequentialMaskedSampler1D(mask)#

Bases: FrameSampler1D

generate_tasks(pixels)#

Generates a list of tuples that selects the pixels to render.

Must return a list of tuples where each tuple contains the id of a pixel to render. For example:

tasks = [(1,), (5,), (512,), …]

This is a virtual method and must be implemented in a sub class.

Parameters:: pixels (int) – The number of pixels in the frame.
Return type:: list

class cherab.iter.observer.sampler.SequentialFullFrameSampler2D#

Bases: FrameSampler2D

generate_tasks(pixels)#

Generates a list of tuples that selects the pixels to render.

Must return a list of tuples where each tuple contains the id of a pixel to render. For example:

tasks = [(1, 10), (5, 53), (512, 354), …]

This is a virtual method and must be implemented in a sub class.

Parameters:: pixels (tuple) – Contains the (x, y) pixel dimensions of the frame.
Return type:: list

class cherab.iter.observer.sampler.SequentialMaskedSampler2D(mask)#

Bases: FrameSampler2D

generate_tasks(pixels)#

Generates a list of tuples that selects the pixels to render.

Must return a list of tuples where each tuple contains the id of a pixel to render. For example:

tasks = [(1, 10), (5, 53), (512, 354), …]

This is a virtual method and must be implemented in a sub class.

Parameters:: pixels (tuple) – Contains the (x, y) pixel dimensions of the frame.
Return type:: list

class cherab.iter.observer.sampler.SpectralAdaptiveSampler1D(pipeline, fraction=0.2, ratio=10.0, min_samples=1000, cutoff=0.0)#

Bases: FrameSampler1D

The adaptive sampler to use with spectral pipelines. Based on MonoAdaptiveSampler1D from Raysect

generate_tasks(pixels)#

Generates a list of tuples that selects the pixels to render.

Must return a list of tuples where each tuple contains the id of a pixel to render. For example:

tasks = [(1,), (5,), (512,), …]

This is a virtual method and must be implemented in a sub class.

Parameters:: pixels (int) – The number of pixels in the frame.
Return type:: list

class cherab.iter.observer.sampler.SpectralAdaptiveSampler2D(pipeline, fraction=0.2, ratio=10.0, min_samples=1000, cutoff=0.0)#

Bases: FrameSampler2D

The adaptive sampler to use with spectral pipelines. Based on MonoAdaptiveSampler2D from Raysect

generate_tasks(pixels)#

Generates a list of tuples that selects the pixels to render.

Must return a list of tuples where each tuple contains the id of a pixel to render. For example:

tasks = [(1, 10), (5, 53), (512, 354), …]

This is a virtual method and must be implemented in a sub class.

Parameters:: pixels (tuple) – Contains the (x, y) pixel dimensions of the frame.
Return type:: list