def test_docstring(self):
Point = namedlist('Point', '')
self.assertEqual(Point.__doc__, 'Point()')
Point = namedlist('Point', 'dx')
self.assertEqual(Point.__doc__, 'Point(dx)')
Point = namedlist('Point', 'x')
self.assertEqual(Point.__doc__, 'Point(x)')
Point = namedlist('Point', 'dx dy, dz')
self.assertEqual(Point.__doc__, 'Point(dx, dy, dz)')
Point = namedlist('Point', 'dx dy dz', default=10)
self.assertEqual(Point.__doc__, 'Point(dx=10, dy=10, dz=10)')
Point = namedlist('Point', 'dx, dy, dz', default=FACTORY(10))
self.assertEqual(Point.__doc__, 'Point(dx=FACTORY(10), dy=FACTORY(10), dz=FACTORY(10))')
Point = namedlist('Point', ['dx', 'dy', ('dz', 11.0)], default=10)
self.assertEqual(Point.__doc__, 'Point(dx=10, dy=10, dz=11.0)')
Point = namedlist('Point', ['dx', 'dy', ('dz', 11.0)], default=FACTORY(list))
if _PY2:
list_repr = "<type 'list'>"
else:
list_repr = "<class 'list'>"
self.assertEqual(Point.__doc__, "Point(dx=FACTORY({0}), dy=FACTORY({0}), dz=11.0)".format(list_repr))
Point = namedlist('Point', ['dx', 'dy', ('dz', FACTORY(11.0))], default=[])
self.assertEqual(Point.__doc__, 'Point(dx=[], dy=[], dz=FACTORY(11.0))')
def test_factory_for_default(self):
# make sure FACTORY works for the global default
A = namedlist('A', 'x y', default=FACTORY(list))
a = A()
self.assertEqual(a.x, [])
self.assertEqual(a.y, [])
a.x.append(4)
self.assertEqual(a.x, [4])
a.y.append(4)
self.assertEqual(a.y, [4])
b = A()
self.assertEqual(b.x, [])
self.assertEqual(b.y, [])
# mix and match FACTORY and a non-callable mutable default
A = namedlist('A', [('x', []), 'y'], default=FACTORY(list))
a = A()
self.assertEqual(a.x, [])
self.assertEqual(a.y, [])
a.x.append(4)
self.assertEqual(a.x, [4])
a.y.append(4)
self.assertEqual(a.y, [4])
b = A()
self.assertEqual(b.x, [4])
self.assertEqual(b.y, [])
def test_factory_functions(self):
A = namedlist('A', [('x', FACTORY(list))])
a = A()
self.assertEqual(a.x, [])
a.x.append(4)
self.assertEqual(a.x, [4])
b = A()
self.assertEqual(b.x, [])
class Column(namedlist("Column" , [
'key',
('tag', None),
('size', None),
('formatting', FACTORY(dict))
])):
'''Definitions for a spreadsheet column, including key, name and style'''
@property
def name(self):
return self.tag or self.key
from namedlist import namedlist, FACTORY, NO_DEFAULT
from ecnn.defaults import *
class SavedValues(dict):
def __init__(self):
self.name = None
OutputLayer = namedlist('OutputLayer', [('name', 'logits'), ('hidden_units', NUM_CLASSES),
('training_history', [0]*MAX_GENERATIONS*2)], use_slots=True, default=None)
Model = namedlist('Model', [('generation', NO_DEFAULT),
('convolutional_layers', FACTORY(list)),
('dense_layers', FACTORY(list)),
('logits', OutputLayer()),
('name', NO_DEFAULT),
('ancestor', NO_DEFAULT),
('trainable_parameters', NO_DEFAULT),
('learning_rate', NO_DEFAULT),
('validation_accuracy', NO_DEFAULT),
('mutation', NO_DEFAULT)], default=None)
ConvolutionalLayer = namedlist('ConvolutionalLayer', [('filter_size', NO_DEFAULT),
('filters', NO_DEFAULT),
('output_shape', NO_DEFAULT),
('name', NO_DEFAULT),
('max_pool', False),
('training_history', [0]*MAX_GENERATIONS)], default=None)
DenseLayer = namedlist('DenseLayer', [('hidden_units', NO_DEFAULT),
('name', NO_DEFAULT),
@author: QueenPy
'''
from defusedxml.sax import parse
from xml.sax import ContentHandler
from namedlist import namedlist, FACTORY, NO_DEFAULT
from future.utils import iteritems
import pandas as pd
# call = namedlist('call', [('x',[])])
# c=call()
# c.x.apppend(3)
# c2=call()
# print(c2.x)
Data = namedlist('Data', [('attr', []), ('showDataList', FACTORY(list))])
Table = namedlist('Table', [('attr', []), ('name', None),
('showRowList', FACTORY(list))])
Row = namedlist('Row', [('attr', []), ('cells', FACTORY(list))])
Cell = namedlist('Cell', [('attr', []), ('showCellInfo', None)])
coll = {}
def xmlxls2pd(attachedDoc, table=0):
xxh = XmlXlsHandler()
if isinstance(attachedDoc, str):
with open(attachedDoc, 'r') as ad:
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 8 15:14:11 2017
@author: richard
"""
from future.utils import iteritems
from xml.sax import ContentHandler
from defusedxml.sax import parse
from namedlist import namedlist, FACTORY, NO_DEFAULT
from collections import defaultdict
import pandas as pd
Data = namedlist('Data', [('attr', NO_DEFAULT),
('data', FACTORY(list))])
Cell = namedlist('Cell', [('attr', NO_DEFAULT),
('data', None)])
Row = namedlist('Row', [('attr', NO_DEFAULT),
('cells', FACTORY(list))])
Table = namedlist('Table', [('attr', NO_DEFAULT),
('name', None),
('rows', FACTORY(list))])
conversions = {None: lambda x: x,
'DateTime': lambda x: pd.to_datetime(x, utc=True),
'String': lambda x: x,
'Number': pd.to_numeric}
class Protein(namedlist("Protein", [
'sequence',
'name',
('id', None),
('mnemonic', None),
('peptides', FACTORY(Peptides)),
]), PeptideListMixin):
'''Protein definitions'''
# PROPERTIES
@property
def length(self):
return len(self.sequence)
@property
def mw(self):
return chemical.Molecule(peptide=self.sequence, strict=False).mass
# CLASS METHODS
@classmethod
def from_uniprot(cls, entry):
'''Initialize class from a UniProt KB query'''
return cls.from_dict(entry, UNIPROT_FIELDS)
@classmethod
def from_fasta(cls, entry):
'''Initialize class from a FASTA or UniProt KB XML file'''
return cls.from_dict(entry, FASTA_FIELDS)
@classmethod
def from_dict(cls, entry, names=None):
'''
Initialize class from a database query, with fields as
`names` mapping Protein fields to the `entry` keys.
Args:
entry (mapping): database record for a single protein
names (dict, None): maps entry keys to protein fields
'''
if names is not None:
return cls(**{k: entry[v][s] for k, (v, s) in names.items()})
return cls(**entry)
# PUBLIC
def sequencing_peptides(self, protease=None):
'''Create sequencing peptides and bind to class'''
self.cut_sequence(protease)
self.concatenate()
def decoy(self, mode='reversed', in_place=False):
'''
Create decoy protein object, and modify `in_place` or return
copy.
Args:
mode (enum): {'reversed', 'shuffled'}
in_place (bool): mode object in place or make copy
'''
sequence = make_decoy(self.sequence, mode)
if not in_place:
return type(self)(sequence, self.name, DECOY_ID, DECOY_MENMONIC)
self.sequence = sequence
self.id = DECOY_ID
self.mnemonic = DECOY_MENMONIC
_SquareCmutMembrane['electrode_x'] = 40e-6
_SquareCmutMembrane['electrode_y'] = 40e-6
_SquareCmutMembrane['thickness'] = (2e-6, )
_SquareCmutMembrane['density'] = (2040, )
_SquareCmutMembrane['y_modulus'] = (110e9, )
_SquareCmutMembrane['p_ratio'] = (0.22, )
_SquareCmutMembrane['isolation'] = 200e-9
_SquareCmutMembrane['permittivity'] = 6.3
_SquareCmutMembrane['gap'] = 50e-9
_SquareCmutMembrane['damping_freq_a'] = 0
_SquareCmutMembrane['damping_freq_b'] = 0
_SquareCmutMembrane['damping_mode_a'] = 0
_SquareCmutMembrane['damping_mode_b'] = 4
_SquareCmutMembrane['damping_ratio_a'] = 0.0
_SquareCmutMembrane['damping_ratio_b'] = 0.0
_SquareCmutMembrane['patches'] = FACTORY(list)
SquareCmutMembrane = register_type('SquareCmutMembrane',
_SquareCmutMembrane,
excl=['id', 'position', 'patches'])
_CircularCmutMembrane = OrderedDict()
_CircularCmutMembrane['id'] = None
_CircularCmutMembrane['position'] = None
_CircularCmutMembrane['shape'] = 'circle'
_CircularCmutMembrane['radius'] = 40e-6 / 2
_CircularCmutMembrane['electrode_r'] = 40e-6 / 2
_CircularCmutMembrane['thickness'] = (2e-6, )
_CircularCmutMembrane['density'] = (2040, )
_CircularCmutMembrane['y_modulus'] = (110e9, )
_CircularCmutMembrane['p_ratio'] = (0.22, )
_CircularCmutMembrane['isolation'] = 200e-9