Score all problem

Having a problem using classifier. The data and images are loaded correctly, and I can fetch cells to classifier, find rules and Score Image without a problem, but when trying to use the Score All, CPA generates the following error:

An error occurred in the program:
IndexError: list index out of range

Traceback (most recent call last):
File “ClassifierGUI.pyc”, line 892, in OnScoreAll
File “ClassifierGUI.pyc”, line 942, in ScoreAll
File “MulticlassSQL.pyc”, line 235, in PerImageCounts
File “MulticlassSQL.pyc”, line 199, in do_by_steps
File “MulticlassSQL.pyc”, line 189, in where_clauses

Upon loading CPA:

Logging level: DEBUG
Creating filter tables.
PROPERTIES WARNING: Unrecognized field “image_path_cols” in properties file
PROPERTIES WARNING: Unrecognized field “image_file_cols” in properties file
PROPERTIES WARNING: Unrecognized field “image_thumbnail_cols” in properties file
PROPERTIES WARNING: Unrecognized field “image_names” in properties file
PROPERTIES WARNING (image_channel_names): No value(s) specified. CPA will use generic channel names.
PROPERTIES WARNING (channels_per_image): No value(s) specified. CPA will assume 1 channel per image.
PROPERTIES: Using default image_buffer_size=1
PROPERTIES: Using default tile_buffer_size=1
PROPERTIES WARNING (plate_id): Field is required for plate map viewer.
PROPERTIES WARNING (well_id): Field is required for plate map viewer.
PROPERTIES WARNING (plate_type): Field is required for plate map viewer.

The properties file:

#Tue Jul 27 10:35:36 2010

==============================================

CellProfiler Analyst 2.0 properties file

==============================================

==== Database Info ====

db_type = sqlite
db_sqlite_file = C:\Users\euglab\Desktop\Anna arrested helaoutput/DefaultDB.db

==== Database Tables ====

image_table = Per_Image
object_table = Per_Object

==== Database Columns ====

Specify the database column names that contain unique IDs for images and

objects (and optionally tables).

table_id (OPTIONAL): This field lets Classifier handle multiple tables if

you merge them into one and add a table_number column as a foreign

key to your per-image and per-object tables.

image_id: must be a foreign key column between your per-image and per-object

tables

object_id: the object key column from your per-object table

image_id = ImageNumber
object_id = ObjectNumber
plate_id =
well_id =

Also specify the column names that contain X and Y coordinates for each

object within an image.

cell_x_loc = Nuclei_Location_Center_X
cell_y_loc = Nuclei_Location_Center_Y

==== Image Path and File Name Columns ====

Classifier needs to know where to find the images from your experiment.

Specify the column names from your per-image table that contain the image

paths and file names here.

Individual image files are expected to be monochromatic and represent a single

channel. However, any number of images may be combined by adding a new channel

path and filename column to the per-image table of your database and then

adding those column names here.

NOTE: These lists must have equal length!

image_path_cols = Image_PathName_OGray,Image_PathName_Orig
image_file_cols = Image_FileName_OGray,Image_FileName_Orig

CPA will now read image thumbnails directly from the database, if chosen in ExportToDatabase.

image_thumbnail_cols =

Give short names for each of the channels (respectively)…

image_names = OGray,Orig

Specify a default color for each of the channels (respectively)

Valid colors are: [red, green, blue, magenta, cyan, yellow, gray, none]

image_channel_colors = red, green, blue, cyan, magenta, yellow, gray, none, none
image_channel_paths = Image_PathName_OGray
image_channel_files = Image_FileName_OGray

==== Image Accesss Info ====

image_url_prepend =

==== Dynamic Groups ====

Here you can define groupings to choose from when classifier scores your experiment. (eg: per-well)

This is OPTIONAL, you may leave "groups = ".

FORMAT:

group_XXX = MySQL select statement that returns image-keys and group-keys. This will be associated with the group name “XXX” from above.

EXAMPLE GROUPS:

groups = Well, Gene, Well+Gene,

group_SQL_Well = SELECT Per_Image_Table.TableNumber, Per_Image_Table.ImageNumber, Per_Image_Table.well FROM Per_Image_Table

group_SQL_Gene = SELECT Per_Image_Table.TableNumber, Per_Image_Table.ImageNumber, Well_ID_Table.gene FROM Per_Image_Table, Well_ID_Table WHERE Per_Image_Table.well=Well_ID_Table.well

group_SQL_Well+Gene = SELECT Per_Image_Table.TableNumber, Per_Image_Table.ImageNumber, Well_ID_Table.well, Well_ID_Table.gene FROM Per_Image_Table, Well_ID_Table WHERE Per_Image_Table.well=Well_ID_Table.well

==== Image Filters ====

Here you can define image filters to let you select objects from a subset of your experiment when training the classifier.

This is OPTIONAL, you may leave "filters = ".

FORMAT:

filter_SQL_XXX = MySQL select statement that returns image keys you wish to filter out. This will be associated with the filter name “XXX” from above.

EXAMPLE FILTERS:

filters = EMPTY, CDKs,

filter_SQL_EMPTY = SELECT TableNumber, ImageNumber FROM CPA_per_image, Well_ID_Table WHERE CPA_per_image.well=Well_ID_Table.well AND Well_ID_Table.Gene=“EMPTY”

filter_SQL_CDKs = SELECT TableNumber, ImageNumber FROM CPA_per_image, Well_ID_Table WHERE CPA_per_image.well=Well_ID_Table.well AND Well_ID_Table.Gene REGEXP ‘CDK.*’

==== Meta data ====

What are your objects called?

FORMAT:

object_name = singular object name, plural object name,

object_name = cell, cells,

What size plates were used? 384 or 96? This is for use in the PlateViewer

plate_type =

==== Excluded Columns ====

OPTIONAL

Classifier uses columns in your per_object table to find rules. It will

automatically ignore ID columns defined in table_id, image_id, and object_id

as well as any columns that contain non-numeric data.

Here you may list other columns in your per_object table that you wish the

classifier to ignore when finding rules.

You may also use regular expressions here to match more general column names.

Example: classifier_ignore_columns = WellID, Meta_., ._Position

This will ignore any column named “WellID”, any columns that start with

“Meta_”, and any columns that end in “_Position”.

A more restrictive example:

classifier_ignore_columns = ImageNumber, ObjectNumber, .Parent., .Children., .Location_Center.,.Metadata.

classifier_ignore_columns = table_number_key_column, image_number_key_column, object_number_key_column

==== Other ====

Specify the approximate diameter of your objects in pixels here.

image_tile_size = 50

======== Auto Load Training Set ========

OPTIONAL

You may enter the full path to a training set that you would like Classifier

to automatically load when started.

training_set =

======== Area Based Scoring ========

OPTIONAL

You may specify a column in your per-object table which will be summed and

reported in place of object-counts when scoring. The typical use for this

is to report the areas of objects on a per-image or per-group basis.

area_scoring_column =

======== Output Per-Object Classes ========

OPTIONAL

Here you can specify a MySQL table in your Database where you would like

Classifier to write out class information for each object in the

object_table

class_table =

======== Check Tables ========

OPTIONAL

[yes/no] You can ask classifier to check your tables for anomalies such

as orphaned objects or missing column indices. Default is on.

This check is run when Classifier starts and may take up to a minute if

your object_table is extremely large.

check_tables = yes

Any idea which index is out of range? The images are all converted to grayscale, and since the image viewer is working I figure it’s not a problem with RGB-images.

ANNA

First of all, I’m so sorry to have gotten around to this so late. It appears that I didn’t get alerted to this message being posted. Do let me know if you were able to resolve your problem or have any other questions and I’ll be sure to get back to you as soon as possible.