qiprofile¶

`qiprofile` Package¶

`breast_pathology`¶

This module updates the qiprofile database Subject pathology information from the pathology Excel workbook file.

class qipipe.qiprofile.breast_pathology.BreastPathologyUpdate(subject)¶

Bases: qipipe.qiprofile.pathology.PathologyUpdate

The Breast pathology update facade.

Parameters:	subject – the `Subject` Mongo Engine database object to update

__init__(subject)¶

Parameters:	subject – the `Subject` Mongo Engine database object to update

encounter_type(row)¶

Overrides qipipe.qiprofile.Pathology.encounter_type() to specialize the intervention_type to BreastSurgery.

Parameters:	row – the input row
Returns:	the REST data model Encounter subclass

pathology_content(row)¶

Collects the pathology object from the given input row. This subclass implementation adds the non-empty embedded fields specific to this tumor type.

Parameters:	row – the input row
Returns:	the {attribute: value} content dictionary

qipipe.qiprofile.breast_pathology.HORMONES = ['estrogen', 'progesterone']¶: The receptor status hormones.

qipipe.qiprofile.breast_pathology.read(workbook, **condition)¶

This is a convenience method that wraps BreastPathologyWorksheet qipipe.qiprofile.xls.Worksheet.read().

Parameters:	workbook – the read-only `openpyxl` workbook object condition – the `qipipe.qiprofile.xls.Worksheet.read()` filter condition
Returns:	the `qipipe.qiprofile.xls.Worksheet.read()` rows

qipipe.qiprofile.breast_pathology.update(subject, rows)¶

Updates the given subject data object from the Breast pathology XLS rows.

Parameters:	subject – the `Subject` Mongo Engine database object to update rows – the input pathology `read()` rows list

`chemotherapy`¶

This module updates the qiprofile database Subject chemotherapy protocol information from a Chemotherapy Excel worksheet.

qipipe.qiprofile.chemotherapy.COL_ATTRS = {'Cumulative Amount (mg/m2 BSA)': 'amount'}¶: The following non-standard column-attribute associations: * The Cumulative Amount column is the amount attribute.

qipipe.qiprofile.chemotherapy.SHEET = 'Chemotherapy'¶: The input XLS sheet name.

qipipe.qiprofile.chemotherapy.read(workbook, **condition)¶

This is a convenience method that wraps ChemotherapyWorksheet qipipe.qiprofile.xls.Worksheet.read().

Parameters:	workbook – the read-only `openpyxl` workbook object condition – the `qipipe.qiprofile.xls.Worksheet.read()` filter condition
Returns:	the `qipipe.qiprofile.xls.Worksheet.read()` rows

qipipe.qiprofile.chemotherapy.update(subject, rows)¶

Updates the given subject data object from the dosage XLS rows.

Parameters:	subject – the `Subject` Mongo Engine database object to update rows – the input chemotherapy `read()` rows list

`clinical`¶

This module updates the qiprofile database clinical information from the clinical Excel workbook file.

qipipe.qiprofile.clinical.update(subject, in_file)¶

Updates the subject clinical database content from the given workbook file.

Parameters:	subject – the target qiprofile Subject to update filename – the input file location

`demographics`¶

This module updates the qiprofile database Subject demographics information from the demographics Excel workbook file.

qipipe.qiprofile.demographics.COL_ATTRS = {'Race': 'races'}¶: The following non-standard column-attribute associations: * The Race column is the races attribute.

qipipe.qiprofile.demographics.SHEET = 'Demographics'¶: The input XLS sheet name.

qipipe.qiprofile.demographics.read(workbook, **condition)¶

Reads the demographics XLS row which matches the given subject.

Parameters:	condition – the row selection filter
Returns:	the Demographics sheet `qipipe.qiprofile.xls.Worksheet.read()` row bundle which matches the given subject, or None if no match was found

qipipe.qiprofile.demographics.update(subject, rows)¶

Updates the given subject data object from the given Demographics sheet rows.

There can be no more than one Demographics update input row for the given subject. The rows parameter is an iterable in order to conform to other sheet facade modules.

Parameters:	subject – the `Subject` Mongo Engine database object to update rows – the input Demographics `read()` rows
Raises:	DemographicsError – if there is more than one input row

`dosage`¶

This module updates the qiprofile database Subject drug dosage information from a Chemotherapy Excel worksheet.

class qipipe.qiprofile.dosage.DosageUpdate(subject, agent_class, **defaults)¶

Bases: object

The dosage update abstract class.

Parameters:	subject – the `Subject` Mongo Engine database object to update agent_class – the dosage agent class defaults – the {attribute: value} row defaults

DEFAULTS = {'duration': 1}¶: The default duration is 1 day.

__init__(subject, agent_class, **defaults)¶

Parameters:	subject – the `Subject` Mongo Engine database object to update agent_class – the dosage agent class defaults – the {attribute: value} row defaults

update(rows)¶

Updates the subject data object from the given dosage XLS rows.

Parameters:	rows – the input dosage `qipipe.qiprofile.xls.Worksheet.read()` rows list

class qipipe.qiprofile.dosage.DosageWorksheet(workbook, sheet, agent_class, **opts)¶

Bases: qipipe.qiprofile.xls.Worksheet

The dosage worksheet facade.

Parameters:	workbook – the `qipipe.qiprofile.xls.Workbook` object sheet – the sheet name agent_class – the agent class opts – the additional `qipipe.qiprofile.xls.Worksheet` initializer options

__init__(workbook, sheet, agent_class, **opts)¶

Parameters:	workbook – the `qipipe.qiprofile.xls.Workbook` object sheet – the sheet name agent_class – the agent class opts – the additional `qipipe.qiprofile.xls.Worksheet` initializer options

`imaging`¶

`modeling`¶

This module updates the qiprofile database modeling information from a XNAT experiment.

qipipe.qiprofile.modeling.update(session, resource)¶

Updates the modeling content for the given qiprofile session database object from the given XNAT modeling resource object.

Parameters:	session – the target qiprofile Session to update resource – the XNAT modeling resource object

`parse`¶

qipipe.qiprofile.parse.COMMA_DELIM_REGEX = <_sre.SRE_Pattern object>¶: Match a comma with optional white space.

qipipe.qiprofile.parse.FALSE_REGEX = <_sre.SRE_Pattern object>¶: The valid False string representations are a case-insensitive match for F(alse)?, Neg(ative)?, Absent or N(o)?.

qipipe.qiprofile.parse.TRAILING_NUM_REGEX = <_sre.SRE_Pattern object>¶: A regular expression to extract the trailing number from a string.

qipipe.qiprofile.parse.TRUE_REGEX = <_sre.SRE_Pattern object>¶: The valid True string representations are a case-insensitive match for T(rue)?, Pos(itive)?, Present or Y(es)?.

qipipe.qiprofile.parse.TYPE_PARSERS = {<class 'mongoengine.fields.FloatField'>: <type 'float'>, <class 'mongoengine.fields.BooleanField'>: <function <lambda>>, <class 'mongoengine.fields.ListField'>: <function <lambda>>, <class 'mongoengine.fields.StringField'>: <type 'str'>, <class 'mongoengine.fields.DateTimeField'>: <function <lambda>>, <class 'mongoengine.fields.IntField'>: <type 'int'>}¶: The following type cast conversion parsers: * string field => str * integer field => int * float field => float * boolean field => parse_boolean() * list field => parse_list_string()

qipipe.qiprofile.parse.default_parsers(*classes)¶

Associates the data model class fields to a parse function composed as follows:

The type cast function in TYPE_PARSERS, if present
The controlled value lookup, if the field has controlled values

Parameters:	classes – the data model classes
Returns:	the {attribute: function} dictionary

qipipe.qiprofile.parse.extract_trailing_number(value)¶

Returns the integer at the end of the given input value, as follows:

If the input value is an integer, then the result is the input value.
Otherwise, if the input value has a string type, then the result is the trailing digits converted to an integer.
Any other value is an error.

Parameters:	value – the input integer or string
Returns:	the trailing integer
Raises:	ParseError – if the input value type is not int or a string type

qipipe.qiprofile.parse.parse_boolean(value)¶

Parses the input value as follows:

If the input value is already a boolean, then return the value
If the input is None or the empty string, then return None
Otherwise, if the input is a string which matches

TRUE_REGEX, then return True
Otherwise, if the input is a string which matches

FALSE_REGEX, then return False
Any other value is an error.

Parameters:	value – the input value
Returns:	the value as a boolean
Raises:	ParseError – if the value cannot be converted

qipipe.qiprofile.parse.parse_list_string(value)¶

Converts a comma-separated list input string to a list, e.g.:

>> from qipipe.qiprofile.parse import parse_list_string >> parse_list_string(‘White, Asian’) [‘White’, ‘Asian’]

Parameters:	value – the input value
Returns:	the value converted to a list

qipipe.qiprofile.parse.parse_trailing_number(s)¶

Parameters:	s – the input string
Returns:	the trailing number in the string
Raises:	ParseError – if the input string does not have a trailing number

`pathology`¶

This module updates the qiprofile database Subject pathology information from the pathology Excel workbook file.

qipipe.qiprofile.pathology.COL_ATTRS = {'Tumor Width (mm)': 'width', 'Tumor Depth (mm)': 'depth', 'Tumor Size Score': 'size', 'Patient Weight (kg)': 'weight', 'Tumor Length (mm)': 'length'}¶

The following non-standard column-attribute associations:

Patient Weight (kg): Encounter.weight attribute
Tumor Size Score: TNM.size attribute
Tumor Length (mm): TumorExtent.length attribute
Tumor Width (mm): TumorExtent.width attribute
Tumor Depth (mm): TumorExtent.depth attribute

qipipe.qiprofile.pathology.ENCOUNTER_TYPES = {'Surgery': <class 'qirest_client.model.clinical.Surgery'>, 'Biopsy': <class 'qirest_client.model.clinical.Biopsy'>}¶: The encounter {name: class} dictionary.

qipipe.qiprofile.pathology.PARSERS = {'size': <function <lambda>>, 'body_part': <function <lambda>>, 'lesion_number': <type 'int'>, 'subject_number': <type 'int'>, 'intervention_type': <function <lambda>>}¶

The following parser associations:

subject_number is an int
intervention_type converts the string to an Encounter subclass
body_part is capitalized
size is a qirest_client.clinical.TNM.Size object

class qipipe.qiprofile.pathology.PathologyUpdate(subject, tumor_type, grade_class, pathology_class)¶

Bases: object

The pathology update abstract class.

Option pathology_class:
Parameters:	subject – the `Subject` Mongo Engine database object to update tumor_type – the subclass tumor type
	the REST data model TumorPathology subclass
Option grade_class:
	the REST data model Grade subclass

__init__(subject, tumor_type, grade_class, pathology_class)¶

Option pathology_class:
Parameters:	subject – the `Subject` Mongo Engine database object to update tumor_type – the subclass tumor type
	the REST data model TumorPathology subclass
Option grade_class:
	the REST data model Grade subclass

encounter_type(row)¶

Infers the encounter type from the given row. This base implementation returns the parsed row intervention_type value.

Parameters:	row – the input row
Returns:	the REST data model Encounter subclass

pathology_content(row)¶

Collects the TumorPathology content from the given input row. This base implementation collects the pathology attribute values from the matching input row attribute value. Other updates are a subclass responsibility.

Parameters:	row – the input row
Returns:	the {attribute: value} content dictionary

update(rows)¶

Updates the subject data object from the given pathology XLS rows.

Parameters:	rows – the input pathology `read()` rows list

update_encounter(encounter, rows)¶

Update the encounter object from the given input row. This base implementation sets the encounter attribute values from the matching input row attribute value and calls update_pathology() to update the pathology. Other updates are a subclass responsibility.

Parameters:	encounter – the encounter object rows – the input pathology `read()` rows for the encounter

class qipipe.qiprofile.pathology.PathologyWorksheet(workbook, *classes, **opts)¶

Bases: qipipe.qiprofile.xls.Worksheet

The Pathology worksheet facade.

Option column_attributes:
Parameters:	workbook – the `qipipe.qiprofile.xls.Workbook` object classes – the subclass-specific REST data model subclasses opts – the following keyword arguments:
Option parsers:	the non-standard parsers {attribute: function} dictionary
	the non-standard {column name: attribute} dictionary

__init__(workbook, *classes, **opts)¶

Option column_attributes:
Parameters:	workbook – the `qipipe.qiprofile.xls.Workbook` object classes – the subclass-specific REST data model subclasses opts – the following keyword arguments:
Option parsers:	the non-standard parsers {attribute: function} dictionary
	the non-standard {column name: attribute} dictionary

qipipe.qiprofile.pathology.SHEET = 'Pathology'¶: The worksheet name.

`radiotherapy`¶

This module updates the qiprofile database Subject radiation protocol information from a Radiotherapy Excel worksheet.

qipipe.qiprofile.radiotherapy.AGENT_DEFAULTS = {'beam_type': 'photon'}¶: The default beam type is photon.

qipipe.qiprofile.radiotherapy.COL_ATTRS = {'Cumulative Amount (Gy)': 'amount'}¶: The following non-standard column-attribute associations: * The Cumulative Amount column is the amount attribute.

qipipe.qiprofile.radiotherapy.SHEET = 'Radiotherapy'¶: The input XLS sheet name.

qipipe.qiprofile.radiotherapy.read(workbook, **condition)¶

This is a convenience method that wraps RadiotherapyWorksheet qipipe.qiprofile.xls.Worksheet.read().

Parameters:	workbook – the read-only `openpyxl` workbook object condition – the `qipipe.qiprofile.xls.Worksheet.read()` filter condition
Returns:	the `qipipe.qiprofile.xls.Worksheet.read()` rows

qipipe.qiprofile.radiotherapy.update(subject, rows)¶

Updates the given subject data object from the dosage XLS rows.

Parameters:	subject – the `Subject` Mongo Engine database object to update rows – the input radiotherapy `read()` rows list

`sarcoma_pathology`¶

This module updates the qiprofile database Subject pathology information from the pathology Excel workbook file.

qipipe.qiprofile.sarcoma_pathology.COL_ATTRS = {'Tumor Location': 'location'}¶

The following special column: attribute associations:

The Tumor Location column corresponds to the pathology location attribute

qipipe.qiprofile.sarcoma_pathology.PARSERS = {'necrosis_percent': <function <lambda>>}¶: The following special parsers: * The necrosis percent can be an integer or a range, e.g. 80-90.

class qipipe.qiprofile.sarcoma_pathology.SarcomaPathologyUpdate(subject)¶

Bases: qipipe.qiprofile.pathology.PathologyUpdate

The Sarcoma pathology update facade.

Parameters:	subject – the `Subject` Mongo Engine database object to update

__init__(subject)¶

Parameters:	subject – the `Subject` Mongo Engine database object to update

pathology_content(row)¶

Collects the pathology object from the given input row. This subclass implementation adds the following items:

If there are necrosis_percent and tnm items, then the TNM necrosis_score is inferred from the necrosis percent

Parameters:	row – the input row
Returns:	the {attribute: value} content dictionary

qipipe.qiprofile.sarcoma_pathology.read(workbook, **condition)¶

This is a convenience method that wraps SarcomaPathologyWorksheet qipipe.qiprofile.xls.Worksheet.read().

Parameters:	workbook – the read-only `openpyxl` workbook object condition – the `qipipe.qiprofile.xls.Worksheet.read()` filter condition
Returns:	the `qipipe.qiprofile.xls.Worksheet.read()` rows

qipipe.qiprofile.sarcoma_pathology.update(subject, rows)¶

Updates the given subject data object from the Sarcoma pathology XLS rows.

Parameters:	subject – the `Subject` Mongo Engine database object to update rows – the input pathology `read()` rows list

`scan`¶

This module updates the qiprofile database scan information from a XNAT experiment.

qipipe.qiprofile.scan.update(session, xscan)¶

Updates the scan content for the given qiprofile session database object from the given XNAT scan object.

Parameters:	session – the target qiprofile Session to update xscan – the XNAT scan object

`update`¶

`xls`¶

class qipipe.qiprofile.xls.Reader(worksheet, attributes, **condition)¶

Bases: object

Reads an Excel worksheet.

Parameters:	worksheet – the `worksheet` object conditional – the optional {attribute: value} row filter condition

__init__(worksheet, attributes, **condition)¶

Parameters:	worksheet – the `worksheet` object conditional – the optional {attribute: value} row filter condition

read()¶

Returns a row generator, where each row is a {attribute: value} bunch. This generator yields each row which satisfies the following condition:

the row is non-empty, i.e. has at least one cell value, and
if this reader has a filter, then the row satisfies the filter condition

Returns:	the filtered `openpyxl` row iterator

worksheet = None¶: The wrapped openpyxl worksheet.

qipipe.qiprofile.xls.load_workbook(filename)¶

Parameters:	filename – the XLS workbook file location
Returns:	the read-only `openpyxl` workbook object

qiprofile¶

qiprofile Package¶

breast_pathology¶

chemotherapy¶

clinical¶

demographics¶

dosage¶

imaging¶

modeling¶

parse¶

pathology¶

radiotherapy¶

sarcoma_pathology¶

scan¶

update¶

xls¶

`qiprofile` Package¶

`breast_pathology`¶

`chemotherapy`¶

`clinical`¶

`demographics`¶

`dosage`¶

`imaging`¶

`modeling`¶

`parse`¶

`pathology`¶

`radiotherapy`¶

`sarcoma_pathology`¶

`scan`¶

`update`¶

`xls`¶