https://github.com/annotation/text-fabric
Tip revision: ca48fedeb67f02eee7b42e2e8dda24e85af84c95 authored by Dirk Roorda on 30 November 2016, 15:06:11 UTC
New minor release 0.0.6
New minor release 0.0.6
Tip revision: ca48fed
api.py
import collections
from .helpers import *
from .layer import Layer
from .text import Text
class OtypeFeature(object):
def __init__(self, api, data=None):
self.api = api
self.data = data
self.slotType = self.data[-2]
self.maxSlot = self.data[-1]
self.maxNode = len(self.data) + self.data[-1] - 1
def v(self, n):
if n < self.maxSlot + 1:
return self.data[-2]
m = n - self.maxSlot - 1
if m < len(self.data) - 2:
return self.data[m]
return None
def s(self, val):
Crank = self.api.C.rank.data
maxSlot = self.maxSlot
if val == self.data[-2]:
return range(maxSlot+1)
return sorted(
[n+maxSlot+1 for n in range(len(self.data)-2) if self.data[n] == val],
key=lambda n: Crank[n],
)
class OslotsFeature(object):
def __init__(self, api, data=None):
self.api = api
self.data = data
self.maxSlot = self.data[-1]
def s(self, n):
if n < self.maxSlot + 1:
return [n]
m = n - self.maxSlot - 1
if m < len(self.data) - 1:
return self.data[m]
return []
class NodeFeature(object):
def __init__(self, api, data):
self.api = api
self.data = data
def v(self, n):
if n in self.data:
return self.data[n]
return None
def s(self, val):
Crank = self.api.C.rank.data
return sorted(
[n for n in self.data if self.data[n] == val],
key=lambda n: Crank[n],
)
class EdgeFeature(object):
def __init__(self, api, data, doValues):
self.api = api
self.data = data
self.doValues = doValues
self.dataInv = makeInverseVal(self.data) if doValues else makeInverse(self.data)
def f(self, n):
Crank = self.api.C.rank.data
if n in self.data:
if self.doValues:
return sorted(
self.data[n].items(),
key=lambda n: Crank[n[0]],
)
else:
return sorted(
self.data[n],
key=lambda n: Crank[n],
)
return None
def t(self, n):
Crank = self.api.C.rank.data
if n in self.dataInv:
if self.doValues:
return sorted(
self.dataInv[n].items(),
key=lambda n: Crank[n[0]],
)
else:
return sorted(
self.dataInv[n],
key=lambda n: Crank[n],
)
return None
class Computed(object):
def __init__(self, api, data):
self.api = api
self.data = data
class NodeFeatures(object): pass
class EdgeFeatures(object): pass
class Computeds(object): pass
class Api(object):
def __init__(self, tf):
self.ignored = tuple(sorted(tf.featuresIgnored))
self.F = NodeFeatures()
self.E = EdgeFeatures()
self.C = Computeds()
self.info = tf.tm.info
self.error = tf.tm.error
self.indent = tf.tm.indent
def Fs(self, fName):
if not hasattr(self.F, fName):
self.tm.error('Node feature "{}" not loaded'.format(fName))
return None
return getattr(self.F, fName)
def Es(self, fName):
if not hasattr(self.E, fName):
self.tm.error('Edge feature "{}" not loaded'.format(fName))
return None
return getattr(self.E, fName)
def Cs(self, fName):
if not hasattr(self.C, fName):
self.tm.error('Computed feature "{}" not loaded'.format(fName))
return None
return getattr(self.C, fName)
def N(self):
for n in self.C.order.data: yield n
def sorted(self, nodeSet):
Crank = self.C.rank.data
return sorted(nodeSet, key=lambda n: Crank[n])
def Fall(self): return sorted(x[0] for x in self.F.__dict__.items())
def Eall(self): return sorted(x[0] for x in self.E.__dict__.items())
def Call(self): return sorted(x[0] for x in self.C.__dict__.items())
def addOtype(api):
setattr(api.F.otype, 'all', tuple(o[0] for o in api.C.levels.data))
def addLayer(api):
api.L = Layer(api)
def addText(api, tf):
api.T = Text(api, tf)