Documented functions with links to source

Program to examine micrograph quality by computing a localized power spectrum using EMAN2’s e2scaneval.py and an averaged power spectrum from overlapping tiles using SPARX’ sx_welch_pw2.py

class micexam.MicrographExamPar[source]

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

Methods

define_parameters_and_their_properties

define_program_states

set_complete_tile_array_option
define_parameters_and_their_properties()[source]
define_program_states()[source]
set_complete_tile_array_option(feature_set)[source]
class micexam.MicrographExamEval(parset=None)[source]

  • Class that holds functions for examining micrograph quality

  • __init__ Function to read in the entered parameter dictionary and load micrograph

  1. Usage: MicrographExam(pardict)

  2. Input: pardict = OrderedDict of program parameters

Methods

e2scaneval(tilesize, fullarropt, pixelsize)

  • Function to use EMAN2’s e2scaneval.py

adjust_columns_and_rows_depending_on_array_option

bin_micrograph

insert_tiles_onto_micrograph

prepare_parameters_for_tiling
bin_micrograph(each_micrograph_file, binoption, binfactor, ori_pixelsize, tile_size_A=None, tempdir=None)[source]
prepare_parameters_for_tiling(tilesize, pixelsize)[source]
adjust_columns_and_rows_depending_on_array_option(tilesize, fullarropt, nx, ny)[source]
insert_tiles_onto_micrograph(tilesize, powermic, sigma, box_count_columns, box_count_rows, separation_columns, separation_rows)[source]
e2scaneval(tilesize, fullarropt, pixelsize)[source]

  • Function to use EMAN2’s e2scaneval.py

  1. Usage: output1 = e2scaneval(tilesize)

  2. Input: tilesize in pixels

  3. Output: MRC file with ‘eval’ appended

class micexam.MicrographExamExtract(parset=None)[source]

Methods

compute_power_spectra(mic, pixelsize, …)

  • Function to compute rotational power spectrum

e2scaneval(tilesize, fullarropt, pixelsize)

  • Function to use EMAN2’s e2scaneval.py

enhance_ps(powerspec, tilesize)

  • Function that enhances power spectrum by compensating against decay of amplitudes

reduce_twod2oned(rotpowspec)

  • Function to reduce 2D rotational power spectrum to 1D image

adjust_columns_and_rows_depending_on_array_option

bin_micrograph

insert_tiles_onto_micrograph

prepare_parameters_for_tiling
enhance_ps(powerspec, tilesize)[source]

  • Function that enhances power spectrum by compensating against decay of amplitudes

  1. Usage: output = enhance_ps(powerspec)

  2. Input: 2D powerspec

  3. Output: 2D powerspec compensated for decay of amplitudes

reduce_twod2oned(rotpowspec)[source]

  • Function to reduce 2D rotational power spectrum to 1D image

  1. Usage: output = reduce_twod2oned(rotpowspec)

  2. Input: 2D power spectrum

  3. Output: 1D power spectrum

compute_power_spectra(mic, pixelsize, tilesize, tile_overlap)[source]

  • Function to compute rotational power spectrum

  1. Usage: compute_power_spectra

class micexam.MicrographExam(parset=None)[source]

Methods

compute_power_spectra(mic, pixelsize, …)

  • Function to compute rotational power spectrum

e2scaneval(tilesize, fullarropt, pixelsize)

  • Function to use EMAN2’s e2scaneval.py

enhance_ps(powerspec, tilesize)

  • Function that enhances power spectrum by compensating against decay of amplitudes

reduce_twod2oned(rotpowspec)

  • Function to reduce 2D rotational power spectrum to 1D image

visualize_power(evalpng, pw2sum, …)

  • Function to visualize power analysis of micrograph

add_entire_micrograph_with_power_tile_overlay

add_one_dimensional_power_spectra

add_rotational_avg_of_above

add_sum_of_overlapping_powerspectra

adjust_columns_and_rows_depending_on_array_option

bin_micrograph

exam_scans

examine_scans_computing_total_and_local_powerspectra

insert_tiles_onto_micrograph

prepare_parameters_for_tiling
add_entire_micrograph_with_power_tile_overlay(evalpng, infile, ax1)[source]
add_sum_of_overlapping_powerspectra(pw2sum, ax2)[source]
add_rotational_avg_of_above(pw2sumrotavg, ax3)[source]
add_one_dimensional_power_spectra(pw2oned, pw2lineenh, pixelsize, ax4)[source]
visualize_power(evalpng, pw2sum, pw2sumrotavg, pw2oned, pw2lineenh, pixelsize, infile, outfile)[source]

  • Function to visualize power analysis of micrograph

  1. Usage: fig = visualize_power(evalpng, pw2sum, pw2sumrotavg, pw2oned, pw2lineenh)

  2. Input: evalpng = micrograph montage from e2scaneval.py, pw2sum = computed sum of overlapping powerspectra, pw2sumrotavg = rotational average of sum, pw2oned = 1D profile of rotational average, pw2lineenh = enhanced 1D profile comensated against amplitude decay

examine_scans_computing_total_and_local_powerspectra(micrograph_files, outfiles)[source]
exam_scans()[source]
micexam.main()[source]
class micexam_mpi.MicrographExamMpi(parset=None)[source]

Methods

compute_power_spectra(mic, pixelsize, …)

  • Function to compute rotational power spectrum

e2scaneval(tilesize, fullarropt, pixelsize)

  • Function to use EMAN2’s e2scaneval.py

enhance_ps(powerspec, tilesize)

  • Function that enhances power spectrum by compensating against decay of amplitudes

reduce_twod2oned(rotpowspec)

  • Function to reduce 2D rotational power spectrum to 1D image

visualize_power(evalpng, pw2sum, …)

  • Function to visualize power analysis of micrograph

add_entire_micrograph_with_power_tile_overlay

add_one_dimensional_power_spectra

add_rotational_avg_of_above

add_sum_of_overlapping_powerspectra

adjust_columns_and_rows_depending_on_array_option

bin_micrograph

end_scan_mpi_programs

exam_scans

examine_scans_computing_total_and_local_powerspectra

insert_tiles_onto_micrograph

prepare_parameters_for_tiling

startup_scan_mpi_programs
exam_scans()[source]
micexam_mpi.main()[source]