Package schrodinger :: Package application :: Package msv :: Module test_helpers

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Module test_helpers

Classes

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RuleBasedStateMachineMetaClass
A metaclass that makes it easy to create simple rules for a RuleBasedStateMachine.

AlignmentInfo

Functions

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patch_signals(obj)
Patch all the signals on the given object with MagicMocks.

make_alignment(AlnClass, aln_info, patch=True)
Given an alignment class and information to populate an instance returns an instance of an alignment

sample_indices(draw, list_length)
Convenience function that returns a subset of indices in a list, given a hypothesis draw function and the length of the list.

schrodinger.application.msv.domain.residue.Residue

generated_residues()
Returns: A residue suitable for testing

schrodinger.application.msv.domain.sequence.ProteinSequence

generated_sequences()
Returns: A protein sequence suitable for testing

QtGui.QColor

qcolor_strategy()
Returns: A QtColor instance to be used in a test

AlignmentInfo

alignment_info_strategy()
Returns everything we need to create an alignment

Variables

[hide private]

POSSIBLE_RESIDUES = ['PAQ', 'AGM', 'TPQ', 'CCS', 'GSC', 'NEM',...

seq_elements_strategy = lists(elements=sampled_from(('PA...

RESIDUE_NAMES = ['PAQ', 'AGM', 'TPQ', 'CCS', 'GSC', 'NEM', 'TI...

RESIDUE_TYPES = [ResidueType('Y', 'PAQ', 'Tyrosine'), ResidueT...

letters_and_numbers = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h',...

seq_strategy = builds(ProteinSequence, elements=lists(elements...

prot_annotations = [<ANNOTATION_TYPES.indices: 1>, <ANNOTATION...

protein_ann_combinations = [(), (<ANNOTATION_TYPES.indices: 1>...

__package__ = 'schrodinger.application.msv'

name = 'ARN'

Function Details

[hide private]

patch_signals(obj)

Patch all the signals on the given object with MagicMocks.

Parameters:

obj (object) - The object whose signals we want to patch

make_alignment(AlnClass, aln_info, patch=True)

Given an alignment class and information to populate an instance returns an instance of an alignment

Parameters:

AlnClass (type) - An alignment class
aln_info (AlignmentInfo) - Information to populate the instance
patch (bool) - Whether to patch the signals on the alignment instance

Returns:

A ProteinAlignment instance.

sample_indices(draw, list_length)

Convenience function that returns a subset of indices in a list, given a hypothesis draw function and the length of the list.

Parameters:

draw (function) - A function supplied by hypothesis
list_length (int) - The length of the list to get a subset of

generated_residues()

Parameters:

draw (function) - A function supplied by hypothesis

Returns: schrodinger.application.msv.domain.residue.Residue

A residue suitable for testing

Decorators:

@strategies.composite

generated_sequences()

Parameters:

draw (function) - A function supplied by hypothesis

Returns: schrodinger.application.msv.domain.sequence.ProteinSequence

A protein sequence suitable for testing

Decorators:

@strategies.composite

qcolor_strategy()

Returns: QtGui.QColor

A QtColor instance to be used in a test

Decorators:

@strategies.composite

alignment_info_strategy()

Returns everything we need to create an alignment

We return an alignment_info instead of an alignment in order to allow tests to create different kinds of alignments and also to pass along additional test data customized to the alignment that the test will create. For example, a potential_reordering will be a reordering that should work with the alignment, etc., etc.

Returns: AlignmentInfo

A test fixture for alignment tests

Decorators:

@strategies.composite

Variables Details

[hide private]

POSSIBLE_RESIDUES

Value:

['PAQ',
 'AGM',
 'TPQ',
 'CCS',
 'GSC',
 'NEM',
 'TIH',
 'DLY',
...

seq_elements_strategy

Value:

lists(elements=sampled_from(('PAQ',
 'AGM',
 'TPQ',
 'CCS',
 'GSC',
 'NEM',
 'TIH',
 'DLY',
...

RESIDUE_NAMES

Value:

['PAQ',
 'AGM',
 'TPQ',
 'CCS',
 'GSC',
 'NEM',
 'TIH',
 'DLY',
...

RESIDUE_TYPES

Value:

[ResidueType('Y', 'PAQ', 'Tyrosine'),
 ResidueType('R', 'AGM', 'Arginine'),
 ResidueType('A', 'TPQ', 'Alanine'),
 ResidueType('C', 'CCS', 'Cysteine'),
 ResidueType('G', 'GSC', 'Glycine'),
 ResidueType('H', 'NEM', 'Histidine'),
 ResidueType('A', 'TIH', 'Alanine'),
 ResidueType('X', 'DLY', 'Lysine'),
...

letters_and_numbers

Value:

['a',
 'b',
 'c',
 'd',
 'e',
 'f',
 'g',
 'h',
...

seq_strategy

Value:

builds(ProteinSequence, elements=lists(elements=sampled_from(('PAQ',
 'AGM',
 'TPQ',
 'CCS',
 'GSC',
 'NEM',
 'TIH',
 'DLY',
...

prot_annotations

Value:

[<ANNOTATION_TYPES.indices: 1>,
 <ANNOTATION_TYPES.mean_hydrophobicity: 2>,
 <ANNOTATION_TYPES.mean_isoelectric_point: 3>,
 <ANNOTATION_TYPES.consensus_symbols: 4>,
 <ANNOTATION_TYPES.consensus_seq: 5>,
 <ANNOTATION_TYPES.consensus_freq: 6>,
 <ANNOTATION_TYPES.sequence_logo: 7>]

protein_ann_combinations

Value:

[(),
 (<ANNOTATION_TYPES.indices: 1>),
 (<ANNOTATION_TYPES.mean_hydrophobicity: 2>),
 (<ANNOTATION_TYPES.mean_isoelectric_point: 3>),
 (<ANNOTATION_TYPES.consensus_symbols: 4>),
 (<ANNOTATION_TYPES.consensus_seq: 5>),
 (<ANNOTATION_TYPES.consensus_freq: 6>),
 (<ANNOTATION_TYPES.sequence_logo: 7>),
...