navigate.model.features.autofocus.Autofocus

class navigate.model.features.autofocus.Autofocus(model, device='stage', device_ref='f')

Bases: object

Autofocus Data Process

This function is called by the data thread. It will get the data from the autofocus_frame_queue and calculate the entropy of the image. The entropy is then compared to the maximum entropy and the position is saved if it is higher. The autofocus_pos_queue is then filled with the next position to move to. If the autofocus_pos_queue is empty, the autofocus is finished.

__init__(model, device='stage', device_ref='f')

Initialize the Autofocus class.

Parameters:

• model (Model) – Model object

• device (str) – Device name

• device_ref (str) – Device reference

Methods

__init__(model[, device, device_ref])	Initialize the Autofocus class.
end_func_data()	End the autofocus routine.
end_func_signal()	End the autofocus routine.
get_autofocus_frame_num()	Calculate how many frames are needed to get the best focus position.
get_steps(ranges, step_size)	Calculate number of steps for autofocusing routine.
in_func_data([frame_ids])	Run the autofocus routine.
in_func_signal()	Run the autofocus routine.
pre_func_data()	Prepare the autofocus routine.
pre_func_signal()	Prepare the autofocus routine.
robust_autofocus()	Robust autofocus routine.
run()	Run the Autofocusing Routine

Attributes

model	Model object
max_entropy	Maximum entropy
f_frame_id	Frame id
frame_num	Number of frames
init_pos	Initial position
f_pos	Focus position
focus_pos	Focus position
target_frame_id	Target frame id
get_frames_num	Number of frames
plot_data	Plot data
total_frame_num	Total frame number
fine_step_size	Fine step size
fine_pos_offset	Fine position offset
coarse_step_size	Coarse step size
coarse_steps	Coarse steps
signal_id	Signal id
autofocus_frame_queue	Autofocus frame queue
autofocus_pos_queue	Autofocus position queue
target_channel	Target channel
config_table	Configuration table
device	Device name
device_ref	Device reference

end_func_data()

End the autofocus routine.

Returns:

True if the autofocus routine is finished.

Return type:

bool

end_func_signal()

End the autofocus routine.

get_autofocus_frame_num()

Calculate how many frames are needed to get the best focus position.

Returns:

Number of frames to be processed.

Return type:

int

static get_steps(ranges, step_size)

Calculate number of steps for autofocusing routine.

Parameters:

• ranges (float) – Distance to be traveled during the autofocusing routine

• step_size (float) – Step size for autofocusing routine

Returns:

• steps (float) – Number of steps for the stack

• pos_offset (float) – Need to figure out.

in_func_data(frame_ids=[])

Run the autofocus routine.

Parameters:

frame_ids (list) – List of frame ids to be processed.

Returns:

frame_ids – List of frame ids to be processed.

Return type:

list

in_func_signal()

Run the autofocus routine.

pre_func_data()

Prepare the autofocus routine.

pre_func_signal()

Prepare the autofocus routine.

robust_autofocus()

Robust autofocus routine.

TODO: Current values for amplitude, sigma, and alpha are hard-coded. Fitting is unfortunately unstable.

Returns:

• fit_data (list) – Autofocus data

• focus_position (float) – Focus position

• r_squared (float) – R-Squared value

run()

Run the Autofocusing Routine

Returns:

Autofocus parameters.

Return type:

dict

autofocus_frame_queue

Autofocus frame queue

Type:

Queue

autofocus_pos_queue

Autofocus position queue

Type:

Queue

coarse_step_size

Coarse step size

Type:

float

coarse_steps

Coarse steps

Type:

int

config_table

Configuration table

Type:

dict

device

Device name

Type:

str

device_ref

Device reference

Type:

str

f_frame_id

Frame id

Type:

int

f_pos

Focus position

Type:

float

fine_pos_offset

Fine position offset

Type:

float

fine_step_size

Fine step size

Type:

float

focus_pos

Focus position

Type:

float

frame_num

Number of frames

Type:

int

get_frames_num

Number of frames

Type:

int

init_pos

Initial position

Type:

float

max_entropy

Maximum entropy

Type:

float

model

Model object

Type:

Model

plot_data

Plot data

Type:

list

signal_id

Signal id

Type:

int

target_channel

Target channel

Type:

int

target_frame_id

Target frame id

Type:

int

total_frame_num

Total frame number

Type:

int