Documented functions with links to source

Program to classify excised in-plane rotated segments using SPARX’s k-means clustering

class segmentclass.SegmentClassPar

Class to initiate default dictionary with input parameters including help and range values and status dictionary

Methods

add_mask_dimension_to_features
define_parameters_and_their_properties
define_program_states
set_class_avg_out_stack
set_class_count
set_class_var_out_stack
set_eigenimg_out_stack
set_frc_based_filter_option
set_iteration_count
set_keep_intermediate_files_option
set_reference_option
set_refinement_option
set_spring_db_prep_rec

add_mask_dimension_to_features()

define_parameters_and_their_properties()

define_program_states()

set_class_avg_out_stack(feature_set)

set_class_var_out_stack(feature_set)

set_eigenimg_out_stack(feature_set)

set_class_count(feature_set)

set_iteration_count(feature_set)

set_keep_intermediate_files_option(feature_set)

set_spring_db_prep_rec(feature_set)

class segmentclass.SegmentClassPreparation(parset=None)

• Class that holds functions for examining segments from micrographs

• __init__ Function to interpret multi-input parameters

Methods

apply_binfactor_if_required
define_helix_or_particle_dimensions
determine_minimal_segment_size
perform_binning_and_trimming_of_input_stack_if_required
perform_binning_and_trimming_of_reference_if_required
prepare_mask
prepare_mask_ori
setup_mask
setup_segmentalign_filter

setup_segmentalign_filter()

define_helix_or_particle_dimensions()

apply_binfactor_if_required()

determine_minimal_segment_size()

perform_binning_and_trimming_of_input_stack_if_required()

perform_binning_and_trimming_of_reference_if_required()

prepare_mask_ori()

prepare_mask()

setup_mask()

class segmentclass.SegmentClassExternalPrograms

Methods

divide_sx_kmeans_in_reasonable_chunks(…[, …])	>>> from spring.segment2d.segmentclass import SegmentClass
spring_align2d(infilestack, reference_stack)	Function to launch helical 2D alignment program segmentalign
sx_kmeans(alistack, maskfile, class_count[, …])	Function to launch SPARX’s k-means analysis
sx_kmeans_groups([alistack, maskfile, noclasses])	Function to launch SPARX’s k-means groups analysis (sx_kmeans_groups.py)

add_mask_dimensions_to_align2d_features
get_dir_name_for_classification
run_segmentalign2d_in_separate_process
sx_kmeans_wrap

add_mask_dimensions_to_align2d_features()

run_segmentalign2d_in_separate_process(aligndict, align_directory, program_to_be_launched)

spring_align2d(infilestack, reference_stack, reference_option=True, local_refinement=False)

• Function to launch helical 2D alignment program segmentalign

1. Input: infilestack, reference stack

2. Output: aligned stack

3. Usage: alistack = spring_align2d(infilestack, reference_stack)

divide_sx_kmeans_in_reasonable_chunks(img_count, class_count, chunk_size=2000)

>>> from spring.segment2d.segmentclass import SegmentClass
>>> SegmentClass().divide_sx_kmeans_in_reasonable_chunks(10, 3, 6)
([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]], [3])
>>> SegmentClass().divide_sx_kmeans_in_reasonable_chunks(10, 4, 6)
([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]], [2, 2])
>>> SegmentClass().divide_sx_kmeans_in_reasonable_chunks(20, 6, 5)
([[0, 1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12], [13, 14, 15, 16, 17, 18, 19]], [2, 2, 2])

sx_kmeans_wrap(alistack, maskfile, class_count)

get_dir_name_for_classification(program_to_be_launched, iteration_id, run_id=None)

sx_kmeans(alistack, maskfile, class_count, run_id=None)

• Function to launch SPARX’s k-means analysis

1. Input: aligned stack, mask file, number of classes

2. Output: stack of averages, stack of variances

3. Usage: avgstack, varstack = sx_kmeans(alistack, maskfile, class_count)

sx_kmeans_groups(alistack=None, maskfile=None, noclasses=None)

• Function to launch SPARX’s k-means groups analysis (sx_kmeans_groups.py)

1. Input: aligned stack, mask file, number of classes

2. Output: statistics data

3. Usage: avgstack, varstack = sx_kmeans_groups(alistack, maskfile, noclasses)

class segmentclass.SegmentClassStatistics

Methods

compute_eigen_images(stack, eigenstack, …)

Perform PCA on stack file and Get eigen images

compute_average_variance_and_eigenimages_on_orignal_stack
create_database_with_stack_id_entries
enter_class_assignment_in_database
finish_classification
get_alignment_info_from_stack
log_member_statistics_from_classes
make_align_named_tuple

compute_eigen_images(stack, eigenstack, mask, avg)

Perform PCA on stack file and Get eigen images

log_member_statistics_from_classes(class_avg_stack, source_stack)

enter_class_assignment_in_database(session, members_class)

make_align_named_tuple()

get_alignment_info_from_stack(aligned_stack, classes)

compute_average_variance_and_eigenimages_on_orignal_stack(output_avgstack, output_varstack, classes, alignment_data)

create_database_with_stack_id_entries(segment_count)

finish_classification(avgstack, varstack, aligned_stack, output_avgstack, output_varstack)

class segmentclass.SegmentClass(parset=None)

Methods

compute_eigen_images(stack, eigenstack, …)	Perform PCA on stack file and Get eigen images
divide_sx_kmeans_in_reasonable_chunks(…[, …])	>>> from spring.segment2d.segmentclass import SegmentClass
spring_align2d(infilestack, reference_stack)	Function to launch helical 2D alignment program segmentalign
sx_kmeans(alistack, maskfile, class_count[, …])	Function to launch SPARX’s k-means analysis
sx_kmeans_groups([alistack, maskfile, noclasses])	Function to launch SPARX’s k-means groups analysis (sx_kmeans_groups.py)

add_mask_dimensions_to_align2d_features
apply_binfactor_if_required
classify
compute_average_variance_and_eigenimages_on_orignal_stack
create_database_with_stack_id_entries
define_helix_or_particle_dimensions
determine_minimal_segment_size
enter_class_assignment_in_database
finish_classification
get_alignment_info_from_stack
get_dir_name_for_classification
log_member_statistics_from_classes
make_align_named_tuple
perform_binning_and_trimming_of_input_stack_if_required
perform_binning_and_trimming_of_reference_if_required
prepare_mask
prepare_mask_ori
run_segmentalign2d_in_separate_process
setup_mask
setup_segmentalign_filter
sx_kmeans_wrap

classify()

segmentclass.main()