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Global dictionaries/parameters

00image_counts database

Every EMAN2DB directory will contain an image count cache database which will contain a number of parameters associated with each image in that directory, updated as necessary.

filename

(timestamp,# particles,(nx,ny,nz) of particle 1)

Timestamp indicates time other values were last updated

Parameters/Metadata for applications stored in the project

These are metadata parameters associated with a 'Project', like a single particle reconstruction, and may be application specific or global. If an application wishes to make parameters available for other applications to see, it should put them in 'bdb:project' in the local directory and name them as described below. Documentation for application specific parameters not really intended for use by other applications appears here as well. This does NOT document parameters stored in the header of individual images, though we strive to use the same names whereever possible.

These parameters can be found in bdb:project

Parameters starting with 'global.' are those which could be used equally by any application, other applications wishing to publish parameters for use by others should prefix them with 'appname.'

global.apix

float

Default A/pix value for a project

global.microscope_voltage

float

Default microscope voltage in kV for a project

global.microscope_cs

float

Default microscope Cs in mm for a project

global.spr_raw_data_dict

Dictionary, key is a string, value is a dictionary

The keys in this dictionary are all the micrograph and/or CCD data file names that are associated with a single particle reconstruction project. The value (which is a dictionary) is currently unused - it is present in anticipation of potential future needs

global.spr_stacks_map

Dictionary, key is a string, value is a dictionary

In this dictionary the key is the name of the stack file that would be created from the raw particles corresponding to the filtered particles in the filtered stacks enumerated by the dictionary values - The values, which are dictionaries, contains keys which are descriptive strings such as "phase", and values which are the names of filtered file stacks that exist on disk. The raw stack key of this dictionary does not necessarily have to exist, but having this as the 'theoretical' name helps with the management side of things in the workflow

global.spr_filt_ptcls_dict

Dictionary, key is a string, value is a dictionary

In this dictionary the key is the name of a particle file that should almost certainly also exist in the global.spr_ptcls list. The value, which is a dictionary, contains keys which are descriptive strings such as "phase", and values which are the names of filtered files that exist on disk.

global.spr_ref_free_class_aves

list of strings

A list of all reference free class averages associated with the project

global.spr_rfca_dict

Dictionary, key is a string, value is a dictionary

In this dictionary the key is the name of all reference free class averages associated with the project. The dictionary value is currently unused but may be useful in future

global.spr_sets_dict

Dictionary, key is a string, value is a dictionary

All of the 'sets' in the project are in this dictionary. The key is the name of the overall 'set'. The value dictionary is keyed by filter type and has values containing the actual filenames of the filtered particles. Standard filter types are: 'Original Data', 'Phase flipped', 'Wiener filtered', 'Phase flipped-hp' (case sensitive).

global.spr_init_models_dict

Dictionary, key is a string, value is a dictionary

e keys in this dictionary are a list of all initial models that are associated with the project. The dictionary value is currently unused but may be useful in future

global.num_cpus

int

Number of cpus available to this project

global.memory_available

int

Maximum memory usage for this project

global.particle_mass

float

The mass of the particle in kilodaltons

workflow.process_ids

list of ints

A list of process ids that is managed by the workflow system

These parameters are application specific and subject to change

Dictionary names should begin with the application name, the contents of each dictionary can be freely defined by the application.

e2ctf.parms

filename

[ EMAN2Ctf object,1D pow spec,1D bg pow spec,Image Quality]

A list with a CTF object as a string (from_string to restore), the 2 1-D power spectra, and a user defined image quality value, images default to quality 5, quality 0 images will not be post-processed

e2ctf.im2d

filename

EMData

The averaged 2-D 'signal' power spectrum for all particles from filename

e2ctf.bg2d

filename

EMData

The averaged 2-D 'background' power spectrum for all particles from filename

e2ctf.misc

strucfac

list of (x,y) tuples

Computed Envelope*StrucFact curve from CTF maxima from all sets processed during one run

e2boxer.cache

This is the cache associated with e2boxer.py.

Not that by filename_DD it is meant to be a string constructed from the original file name, for instance if the file name was 123458.mrc then filename_DD would be literally "123458_DD".

filename_DD

Python dictionary

Image Database Dictionary

filename_DD.auto_boxer_state_TS

string

Greenwich Mean time stamp of the associated Autoboxer when it was last used to autobox this image. This information can be used to force reboxing if the associated autoboxer has been updated

filename_DD.auto_boxer_unique_id

string

stores the unique ID of an associated Autoboxer instance which is also stored in the boxer_cache database

filename_DD.auto_boxes

boxertools.TrimBox list

stores the current set of automatically selected boxes by the associated Autoboxer instance

filename_DD.coarse_flat_image

EMData

stores the image generated by the boxertools.CoarsenedFlattenedImage object that is associated with this image

filename_DD.frozen_state

boolean

indicates whether or not the image is frozen. If the image is frozen then no changes can be made to the currently associated boxes

filename_DD.image_tag

string

Stores the original name of the image

filename_DD.manual_boxes

boxertools.TrimBox list

stores boxes that have been manually placed in this image

filename_DD.moved_boxes

Python list of 2D coordinates

effectively a memorization of all the box movements enforced by the user. Can be used to perform collision detection and automatically correct the results of automatic boxing

filename_DD.quality

integer [0-4]

in the special case of the quality being equal to zero this means the image is excluded from boxing and that no boxes should ever be generated for it. Otherwise this is just metadata that may be acted upon autonomously by the user

filename_DD.reference_boxes

boxertools.TrimBox list

stores the reference boxes located in this image that are also being used by the associated Autoboxer instance

filename_DD.template_ts

string

Greenwich Mean time stamp that records when the associated template (that was used to generate the correlation image, which is potentially stored in the database also) was created

autoboxer_ts

Python dictionary

the key here is literally the string "autobxer_" followed the a unique time stamp as a string. This dictionary object stores the essential parameters of a an Autoboxer instance

autoboxer_ts.autoboxer

boxertools.AutoBoxer or boxertools.TrimAutoBoxer

the Autoboxer instance itself (or similar)

autoboxer_ts.autoboxer_type

string

this is the unique associated with the Autoboxer type, for example "Swarm" or "Gauss"

autoboxer_ts.convenience_name

string

the user may optionally supply a convenience name for this autoboxer in the e2boxer interface, otherwise the name is generated automatically

current_autoboxer

boxertools.AutoBoxer or boxertools.TrimAutoBoxer

the most recently use Autoboxer instance

current_autoboxer_type

string

the type of the most recently used Autoboxer instance. This should become deprecated.

e2classaverage.indices

class number (integer stored as a string)*

list of integers

The indexes of particles that went into each class. Generated by e2classaverage if correct command line arguments are passed. Used automatically be e2refine and accessed by e2eulerxplor

* Stored as a string because of some database complication during development

emform.e2boxer

This dictionary stores the most recently used parameters associated with boxing in e2workflow.py

interface_boxsize

int

The box size that is used to launch e2boxer from within the project/workflow setting

output_boxsize

int

The last box size that was used for generating boxed output with e2boxer

force

boolean

The force flagged used for writing output in e2boxer

write_coord_files

boolean

The write coordinates flagged used for writing output in e2boxer

write_box_images

boolean

The write box images flag used for writing output in e2boxer

normproc

string

The normalization processor name used writing boxed output in e2boxer

outformat

string

The image format for boxed images generated when writing output in e2boxer

filenames

string list

The last set of filenames that was used to launch or spawn e2boxer

emform.e2ctf

This dictionary stores the most recently used parameters associated with ctf correction in e2workflow.py

ac

float

Amplitude contrast constant used to launch e2ctf from within the project/workflow setting

oversamp

float

Oversample factor used to launch e2ctf from within the project/workflow setting

nosmooth

boolean

Last nosmooth program argument used to run e2ctf from within the project/workflow setting

autohp

boolean

Last autohp program argument used to run e2ctf from within the project/workflow setting

wiener

boolean

Last wiener program argument used to run e2ctf from within the project/workflow setting

phaseflip

boolean

Last phaseflip program argument used to run e2ctf from within the project/workflow setting

filenames

string list

The last set of filenames that was used to launch or spawn e2ctf

emform.e2initialmodel

filenames

string list

The last set of filenames that was used to launch or spawn e2initialmodel

iter

int

Last iterations argument used to run e2initialmodel

symname

string

Symmetry type, i.e. c,d,icos etc, used to create the symmetry argument last used to run e2initialmodel

symnumber

string

Symmetry number ("","1","2" and so on) used to create the symmetry argument last used to run e2initialmodel

tries

int

Last tries argument used to run e2initialmodel

This dictionary stores the most recently used parameters associated with initial model generation in e2workflow.py

emform.e2refine

This dictionary stores the most recently used parameters associated with 3D refinement in e2workflow.py

amnshellsgauss

int

The nshellsgauss parameter of the mask.auto3d processor

amnshells

int

The nshells parameter of the mask.auto3d processor

amradius

int

The radius parameter of the mask.auto3d processor

amthreshold

float

The isosurface threshold parameter of the mask.auto3d processor

automask3d

boolean

The last state of the automask3d checkbox on the main page, which cause e2refine to use the mask.auto3d processor following e2make3d

classalign

string

The aligner used for alignment during iterative class averaging

classalignargs

string

classalign (The aligner) parameters

classaligncmp

string

The comparator used by the main aligner during iterative class averaging

classaligncmpargs

string

classaligncmp (comparator) parameters

classaverager

string

Averager used for averaging the images in each class

classcmp

string

The main comparator used to quality and exclude bad particles in iterative class averaging

classcmpargs

string

classcmp (comparator) parameters

classiter

int

The number of class averaging iterations

classkeep

float

The keep threshold used for excluding bad particles in iterative class averaging

classkeepsig

bool

The sigma thresholding flag used in conjunction with classkeep

classnormproc

string

The normalization processor used in class averaging

classralign

string

The refinement aligner used in iterative class averagin

classralignargs

string

classralign (aligner) parameters

classraligncmp

string

The comparator used by the refinement aligner in iterative class averaging

classraligncmpargs

string

classraligncmp (comparator) parameters

filenames

string list

The most recently selected/specified files used to create the input stack from within the workflow setting

iter

int

The number of refinement iterations

lowmem

boolean

A low memory flag used to indicate memory should be used as sparsely as possible

m3diter

int

The number of iterations used my make3d when performing the Fourier inversion method of 3D reconstruction

m3dkeep

float

The keep threshold used by e2make3d for the purpose of slice exclusion during 3D reconstruction

m3dpreprocess

string:args

The normalization processor applied prior to slice insertion during 3D reconstruction

model

string list (length 1)

The seeding 3D model, this is not an absolute path, but rather the file tag (see get_file_tag in EMAN2.py) of an image in the initial models database

orientgen

string

The method (OrientationGenerator) used to generate orientations in the asymmetric unit of the 3D model

orientopt

string

Reflects the user's choice between number based and angle based orientation generation (eventually becomes an OrientationGenerator parameter)

orientopt_entry

float

A value closely tied with orientopt, this is either an angle of, or the total number of, desired orientations

pad

int

The amount of padding used by the Fourier inversion 3D reconstruction technique

particle_set_choice

string

Stores which data set the user chose to supply as main input into the refinement process (e.g. Wiener, phase flipped, etc)

projector

string

The projector used for generating projections

recon

string

The reconstructor used for performing 3D reconstruction

sep

int

The number of classes each particles can be associated with

shrink

int

The shrink factor applied to particles prior to generation of the similarity matrix (e2simmx.py)

simalign

string

The main aligner used during similarity matrix generation

simalignargs

string

simalign (aligner) parameters

simaligncmp

string

The comparator used by the main aligner during similarity matrix generation

simaligncmpargs

string

simaligncmp (comparator) parameters

simcmp

string

The comparator used to generate the final score which is stored in the similarity matrix

simcmpargs

string

simcmp (comparator) parameters

simralign

string

The refinement aligners used during similarity matrix generation

simralignargs

string

simralign (aligner) parameters

simraligncmp

string

The comparator used by the refine align in similarity matrix generation

simraligncmpargs

string

simraligncmp (comparator) arguments

symname

string

Symmetry type, i.e. c,d,icos etc

symnumber

string

Symmetry number ("","1","2" and so on)

usefilt_choice

string

Most recently chosen usefilt option

usefilt_string

string

Most recently specified usefilt filename

emform.e2refine2d

filenames

string list

The most recently selected/specified files used to create the input stack from within the workflow setting

initial

string

Name of file containing initial class averages

iter

int

The number of refinement iterations

iterclassav

int

The number of iterations to perform when performing class averaging

naliref

int

e2refine2d argument

nbasisfp

int

e2refine2d argument

ncls

int

The number of classes to produce

normproj

boolean

e2refine2d argument

parallel

int

The number of available CPUs

particle_set_choice

string

Stores which data set the user chose to supply as main input into the refinement process (e.g. Wiener, phase flipped, etc)

shrink

int

Shrink factor for speed

simalign

string

The main aligner used during similarity matrix generation

simalignargs

string

simalign (aligner) parameters

simaligncmp

string

The comparator used by the main aligner during similarity matrix generation

simaligncmpargs

string

simaligncmp (comparator) parameters

simcmp

string

The comparator used to generate the final score which is stored in the similarity matrix

simcmpargs

string

simcmp (comparator) parameters

simralign

string

The refinement aligners used during similarity matrix generation

simralignargs

string

simralign (aligner) parameters

simraligncmp

string

The comparator used by the refine align in similarity matrix generation

simraligncmpargs

string

simraligncmp (comparator) arguments

This dictionary stores the most recently used parameters associated with 2D refinement in e2workflow.py

These parameters can be found in bdb:raw_data#

The raw_directory is used by e2workflow.py for storing imported micrograph/CCD data. The image file tag (e.g. the file tag of /home/somewhere/something.mrc is "something") may be used to access the image, for example

   1 a = EMData("bdb:raw_data#something",0)
   2 b = EMData()
   3 b.read_image("bdb:raw_data#something",0)

These parameters can be found in bdb:particles#

The short story is e2boxer stores particles in this directory, it uses a naming convention where "_ptcls" is appended to the end of the input image names.

e2ctf stores particles in this directory and appends "_ctf_flip" or "_ctf_wiener", depending whether the output data are phase flipped or Wiener filtered.

The longer story is - The particles directory is used by e2ctf, e2boxer and e2workflow for storing boxed particle data that has optionally been filtered. In general e2boxer will be the first program that stores data here, and it can be done in a number of ways. People can save directly to the particles directory from e2boxer using the 'write box particle images' button (name may be different) and by making sure the output format is 'bdb'. e2boxer can also be used from the command line for writing output (output format is a command line argument). This is precisely what occurs from the context of e2workflow, which spawns output writing processes using e2boxer.

Note that a naming convention is employed by e2boxer - if the input image names is something.mrc or "bdb:raw_data#something" then the output particles will be written using the filename "something_ptcls". You can access these images from Python using any of these approaches:

   1 a = EMData.read_images("bdb:raw_data#something_ptcls",[])
   2 n = EMUtil.get_image_count("bdb:raw_data#something_ptcls")
   3 images = []
   4 for i in range(n):
   5     images.append(EMData("bdb:raw_data#something_ptcls",i))

e2ctf will also store filtered particle images in the this directory, and these will be either phase flipped or Wiener filtered. Note that the Wiener filtered data are also phase flipped. These particles are stored in the database with "_ctf_flip" and "_ctf_wiener" appended to the input file names, respectively.

These parameters can be found in bdb:e2boxercache#

The e2boxercache directory has many dedicated particle stacks in it. The currently existing stacks are listed in this table

exclusion_image

EMData database

A binary exclusion image, in shrunken image coordinates

image_thumb

EMData database

A thumbnail of the image

subsampled_image

EMData database

A subsampled version of the image generated by the Gauss mode - Sparx group please add details

coarse_flat_image

EMData database

A coarsened version of the image that has its background flattened

coarse_sigma_image

EMData database

A specialized image that stores the inverse of the local pixel standard deviation - should probably called inverse_sigma_image - this image is in shrunken image coordinates and is used to normalize the correlation image (Roseman). Note that pixels representing 0 standard deviation are left unchanged

flcf_image

EMData database

Locally normalized correlation image (Roseman, Ultramicroscopy)

see also the e2boxer.cache database.

Eman2AppMetadata (last edited 2013-08-11 18:07:28 by SteveLudtke)