Module tf.convert.variants
Variants
This module contains functions to help you constructing nodes when you convert TEI material and encounter elements from the Critical Apparatus Module.
An extensive description of the problems and solutions is in
tf.about.variants.
Expand source code Browse git
"""
# Variants
This module contains functions to help you constructing nodes
when you convert TEI material and encounter elements from
the
[Critical Apparatus Module](https://www.tei-c.org/release/doc/tei-p5-doc/en/html/examples-lem.html#TC).
An extensive description of the problems and solutions is in
`tf.about.variants`.
"""
APP = "app"
N_SENT = "nSent"
PARENT = "parent"
RDGS = "rdgs"
SLOTS = "slots"
VARIANTS = "variants"
WIT = "wit"
# Start new keys in cur
APP_STACK = "appstack"
APPS = "apps"
N_APP = "nApp"
TRANS_LAST = "translast"
TRANS_NEXT = "transnext"
WITNESSES = "witnesses"
WITS = "wits"
X_WITS = "xwits"
# End new keys in cur
# Start existing keys in cur
RDG = "rdg"
LEM = "lem"
# End existing keys in cur
class Variants:
def __init__(self, cv, cur, baseWitness, sentType, checkPunc, addWarning, addError):
"""Handlers to turn boundaries into nodes even across variants.
This class works inside converters of the type `tf.convert.walker`.
Import it as
``` python
from tf.convert.variants import Variants
```
It should typically be instantiated inside the `director()` function,
at a point where `cv` and `cur` are known.
Then issue `Variants.initApps`, either once or for each volume in the corpus.
After initialization you should call `Variants.collectWitnesses()` for
each TEI file in the corpus.
After collecting the witnesses you should prepare for the final walk through
the data by `Variants.resetApps()`. This should match the call(s) to
`Variants.initApps`.
Then, at the start of each `app`-, `lem`-, `rdg`- element, call
`Variants.startApp(tag)` with tag the corresponding tag name (
`app`, `lem`, or `rdg`).
Likewise, at the end, call `Variants.endApp(tag)`.
Whenever you create slots, issue a `Variants.startSent()` first,
and a `Variants.checkSent()` after.
Close every TEI file with a `Variants.endSent()`, to finish off all
pending sentences.
Parameters
----------
cv: object
The `tf.convert.walker.CV` object. This is the machinery that constructs
nodes and assigns features.
cur: dict
Keys and values by which a conversion program maintains current information.
The conversion proceeds by executing a custom `director()` function,
and this director walks through the source material and fires `cv` actions.
During the walk, the director can remember incoming data as needed in a
dict, and it is this dict that should be passed. The `Variants` object
stores additional information here under specific keys.
Those keys are mentioned in constants in the source code and there are
a few keys dependent on the `sentType` parameter, namely
f"n{sentType}"
f"stack{sentType}"
f"var{sentType}"
baseWitness: string
The name of the base text. Take care that it is different from the names
of the witnesses.
sentType: string
The name of the node type of the nodes that will be constructed on the
basis of boundaries. It could be "sentence", but it could also be any
other name, and it is not assumed that the nodes in question represent
sentences. It could be anything, provided we have access to its boundaries.
checkPunc: function(string, string, punc): boolean
Given the texts of the last two slots and the punctuation after that,
it determines whether is contains a boundary.
This function should be written in the converter program.
Hence it is up to the conversion code to define what constitutes a boundary,
and whether it are sentences or some things else that are being bounded.
This function is called and depending on the outcome sentence nodes are
terminated and / or created, or nothing is done.
addWarning, addError: function(string, dict)
Functions taking a message string and a dict with current information
(typically cur).
They will be called if a warning or error has to be issued.
When they is called, `cur` will be passed as dict.
This function should be defined in the conversion program. It may use values
in `cur` to generate an indication where the warning / error occurred.
"""
self.cv = cv
self.cur = cur
self.sentType = sentType
self.baseWitness = baseWitness
self.checkPunc = checkPunc
self.addWarning = addWarning
self.addError = addError
self.nSent = f"n{sentType}"
self.stackSent = f"stack{sentType}"
self.varSent = f"variants{sentType}"
cur[WITNESSES] = set()
def collectWitnesses(self, node):
"""Collect all witnesses.
Call this for the root nodes of every TEI file of the corpus.
Collects the witnesses from all `rdg`-elements.
For each `lem`-element the set of witnesses of its `rdg` siblings is collected in
such a way that it can be retrieved later on.
We also store a pointer to the parent `app`-element of each nested
`app`-element.
We also check that multiple direct-`rdg` children of the same
app have disjoint witnesses.
"""
cur = self.cur
addWarning = self.addWarning
tag = node.tag.lower()
atts = node.attrib
appStack = cur[APP_STACK]
apps = cur[APPS]
if tag == APP:
parentApp = appStack[-1] if len(appStack) else None
nApp = cur[N_APP]
cur[N_APP] = nApp + 1
appStack.append(nApp + 1)
apps[nApp + 1] = dict(parent=parentApp, xwits=set(), rdgs=[])
elif tag == RDG:
att = WIT
if att in atts:
ws = {w.strip(".").lower() for w in atts[att].split()}
cur[WITNESSES] |= ws
apps[appStack[-1]][X_WITS] |= ws
rdgSeen = apps[appStack[-1]][RDGS]
for rdg in rdgSeen:
if rdg & ws:
addWarning(
"witnesses of rdg not disjoint from sibling rdgs", cur
)
apps[appStack[-1]][RDGS].append(ws)
for child in node:
self.collectWitnesses(child)
if tag == APP:
appStack.pop()
def initApps(self):
"""Initialize app- processing and witness collection.
You can issue this command once for the whole corpus,
or each time before entering a volume.
"""
cur = self.cur
cur[APPS] = dict()
cur[APP_STACK] = []
cur[TRANS_NEXT] = []
cur[N_APP] = 0
def resetApps(self):
"""Initialize app- and "sentence" processing.
Set up the data store for collecting information and "sentence" processing.
Do this after collecting the witnesses.
You can issue this command once for the whole corpus,
or each time before entering a volume.
But it should be kept in tandem with `Variants.initApps`.
"""
cur = self.cur
baseWitness = self.baseWitness
nSent = self.nSent
stackSent = self.stackSent
varSent = self.varSent
cur[N_APP] = 0
cur[WITS] = []
cur[X_WITS] = []
cur[TRANS_LAST] = None
cur[nSent] = 0
cur[stackSent] = []
cur[varSent] = {baseWitness: None}
def startApp(self, tag, atts):
"""Actions at the start of `app`- `lem`- and `rdg`-elements.
Use this each time you enter one of these XML elements.
Parameters
----------
tag: string
The tag name of the XML element that is being entered
atts: dict
The attributes of the XML element that is being entered
"""
cur = self.cur
curStackSent = cur[self.stackSent]
if tag == APP:
nApp = cur[N_APP]
cur[N_APP] = nApp + 1
appInfo = cur[APPS][nApp + 1]
parentApp = appInfo[PARENT]
xwits = appInfo[X_WITS]
slots = self._diverge()
cur[TRANS_NEXT].append("")
curStackSent.append(
dict(
translast=cur[TRANS_LAST],
slots=slots,
)
)
while parentApp is not None:
appInfo = cur[APPS][parentApp]
# keep xwits immutable, don't say xwits |= blabla
# because that will change xwits in place
xwits = xwits | appInfo[X_WITS]
parentApp = appInfo[PARENT]
cur[X_WITS].append(xwits)
elif tag == LEM:
xWits = self._getXwits()
for wit in self._getWits():
if wit in xWits:
self._suspend(wit)
else:
self._resume(wit)
elif tag == RDG:
wits = set()
if WIT in atts:
wits = {w.strip(".").lower() for w in atts[WIT].split()}
atts[WIT] = " ".join(wits)
cur[WITS].append(wits)
for wit in self._getWits():
if wit in wits:
self._resume(wit)
else:
self._suspend(wit)
def endApp(self, tag):
"""Actions at the end of `app`- `lem`- and `rdg`-elements.
Use this each time you leave one of these XML elements.
Parameters
----------
tag: string
The tag name of the XML element that is being left
"""
cur = self.cur
curStackSent = cur[self.stackSent]
if tag == APP:
cur[X_WITS].pop()
xWits = self._getXwits()
for wit in self._getWits():
if wit not in xWits:
self._resume(wit)
curStackSent.pop()
cur[TRANS_LAST] = cur[TRANS_NEXT].pop()
elif tag == LEM:
cur[TRANS_NEXT][-1] = cur[TRANS_LAST]
xWits = self._getXwits()
for wit in self._getWits():
if wit not in xWits:
self._suspend(wit)
elif tag == RDG:
wits = cur[WITS][-1]
for wit in wits:
self._suspend(wit)
cur[WITS].pop()
def checkSent(self, trans, punc):
"""Checks whether there is a "sentence" boundary at this point.
Use this every time you have added a slot node.
Parameters
----------
trans: string
The text of the newly added slot node.
If this is empty, the text of the slot before that will be consulted.
This value is taken from the context information.
This very function is responsible for putting the last text value into
the context.
punc: string
The non-alphanumeric text material after the text of the last slot.
Will be used to determine whether there is a "sentence" break here.
The actual check will be done by the function `checkPunc`,
which has been passed as parameter when the `Variants` object was
created.
"""
cur = self.cur
checkPunc = self.checkPunc
lastTrans = trans or cur[TRANS_LAST] or ""
if checkPunc(lastTrans, trans, punc):
self.endSent()
else:
cur[TRANS_LAST] = trans
def startSent(self):
"""Starts a "sentence" if there is no current sentence.
When in an `rdg`-element, witness-dependent "sentence" nodes
are created for each witness for the `rdg`.
Use this before creating a slot and / or at the start of certain elements
such as paragraphs.
"""
cur = self.cur
baseWitness = self.baseWitness
inRdg = RDG in cur and len(cur[RDG]) > 0
inLem = LEM in cur and len(cur[LEM]) > 0
if inLem:
self._startSentLem()
elif inRdg:
self._startSentRdg()
else:
self._start(baseWitness, witAtt=False)
def endSent(self):
"""Ends a "sentence" if there is a current sentence.
Use this at the end of each XML file if you are sure that
there should not remain pending sentences. You can also call this
at the end of certain elements, such as paragraphs.
When in a `lem`-element, all pending "sentences" of all witnesses
that agree with the base text here are also ended.
No new sentences for these witnesses are started, since we are in
the base text.
"""
cur = self.cur
inRdg = RDG in cur and len(cur[RDG]) > 0
inLem = LEM in cur and len(cur[LEM]) > 0
if inLem:
self._endSentLem()
elif inRdg:
self._endSentRdg()
else:
for wit in self._getWits():
self._terminate(wit)
def _startSentLem(self):
baseWitness = self.baseWitness
self._start(baseWitness)
def _endSentLem(self):
xWits = self._getXwits()
for wit in self._getWits():
if wit not in xWits:
self._terminate(wit)
def _startSentRdg(self):
cur = self.cur
curStackSent = cur[self.stackSent]
wits = cur[WITS][-1]
topStack = curStackSent[-1]
cur[TRANS_LAST] = topStack[TRANS_LAST]
for wit in wits:
self._prepend(wit)
def _endSentRdg(self):
cur = self.cur
wits = cur[WITS][-1]
for wit in wits:
self._terminate(wit)
def _get(self, wit):
cur = self.cur
baseWitness = self.baseWitness
curVarSent = cur[self.varSent]
isBase = wit == baseWitness
if isBase:
return curVarSent[baseWitness]
return curVarSent.get(wit, None)
def _getWits(self):
cur = self.cur
curVarSent = cur[self.varSent]
return list(curVarSent)
def _getXwits(self):
cur = self.cur
xWits = cur[X_WITS]
return xWits[-1] if xWits else set()
def _start(self, wit, witAtt=True):
s = self._get(wit)
if s is not None:
return s
cv = self.cv
cur = self.cur
sentType = self.sentType
curVarSent = cur[self.varSent]
nSent = self.nSent
baseWitness = self.baseWitness
isBase = wit == baseWitness
s = cv.node(sentType)
cur[nSent] += 1
cv.feature(s, n=cur[nSent])
if witAtt:
cv.feature(s, wit=wit)
if isBase:
curVarSent[baseWitness] = s
else:
curVarSent[wit] = s
return s
def _terminate(self, wit):
cv = self.cv
cur = self.cur
baseWitness = self.baseWitness
curVarSent = cur[self.varSent]
isBase = wit == baseWitness
s = self._get(wit)
if s is not None:
cv.terminate(s)
if isBase:
curVarSent[wit] = None
else:
del curVarSent[wit]
def _resume(self, wit):
cv = self.cv
s = self._get(wit)
if s is not None:
cv.resume(s)
def _suspend(self, wit):
cv = self.cv
s = self._get(wit)
if s is not None:
cv.terminate(s)
def _diverge(self):
cv = self.cv
baseWitness = self.baseWitness
s = self._get(baseWitness)
if s is None:
return None
cv.feature(s, wit=baseWitness)
return cv.linked(s)
def _prepend(self, wit):
if self._get(wit) is None:
cv = self.cv
cur = self.cur
curStackSent = cur[self.stackSent]
topStack = curStackSent[-1]
slots = topStack[SLOTS]
s = self._start(wit)
if s is not None and slots is not None:
cv.link(s, topStack[SLOTS])Classes
class Variants (cv, cur, baseWitness, sentType, checkPunc, addWarning, addError)-
Handlers to turn boundaries into nodes even across variants.
This class works inside converters of the type
tf.convert.walker. Import it asfrom tf.convert.variants import VariantsIt should typically be instantiated inside the
director()function, at a point wherecvandcurare known.Then issue
Variants.initApps(), either once or for each volume in the corpus.After initialization you should call
Variants.collectWitnesses()for each TEI file in the corpus.After collecting the witnesses you should prepare for the final walk through the data by
Variants.resetApps(). This should match the call(s) toVariants.initApps().Then, at the start of each
app-,lem-,rdg- element, callVariants.startApp()(tag)with tag the corresponding tag name (app,lem, orrdg).Likewise, at the end, call
Variants.endApp()(tag).Whenever you create slots, issue a
Variants.startSent()first, and aVariants.checkSent()after.Close every TEI file with a
Variants.endSent(), to finish off all pending sentences.Parameters
cv:object- The
CVobject. This is the machinery that constructs nodes and assigns features. cur:dict-
Keys and values by which a conversion program maintains current information. The conversion proceeds by executing a custom
director()function, and this director walks through the source material and firescvactions. During the walk, the director can remember incoming data as needed in a dict, and it is this dict that should be passed. TheVariantsobject stores additional information here under specific keys.Those keys are mentioned in constants in the source code and there are a few keys dependent on the
sentTypeparameter, namelyf"n{sentType}" f"stack{sentType}" f"var{sentType}" baseWitness:string- The name of the base text. Take care that it is different from the names of the witnesses.
sentType:string- The name of the node type of the nodes that will be constructed on the basis of boundaries. It could be "sentence", but it could also be any other name, and it is not assumed that the nodes in question represent sentences. It could be anything, provided we have access to its boundaries.
checkPunc:function(string, string, punc): boolean- Given the texts of the last two slots and the punctuation after that, it determines whether is contains a boundary. This function should be written in the converter program. Hence it is up to the conversion code to define what constitutes a boundary, and whether it are sentences or some things else that are being bounded. This function is called and depending on the outcome sentence nodes are terminated and / or created, or nothing is done.
addWarning,addError:function(string, dict)- Functions taking a message string and a dict with current information
(typically cur).
They will be called if a warning or error has to be issued.
When they is called,
curwill be passed as dict. This function should be defined in the conversion program. It may use values incurto generate an indication where the warning / error occurred.
Expand source code Browse git
class Variants: def __init__(self, cv, cur, baseWitness, sentType, checkPunc, addWarning, addError): """Handlers to turn boundaries into nodes even across variants. This class works inside converters of the type `tf.convert.walker`. Import it as ``` python from tf.convert.variants import Variants ``` It should typically be instantiated inside the `director()` function, at a point where `cv` and `cur` are known. Then issue `Variants.initApps`, either once or for each volume in the corpus. After initialization you should call `Variants.collectWitnesses()` for each TEI file in the corpus. After collecting the witnesses you should prepare for the final walk through the data by `Variants.resetApps()`. This should match the call(s) to `Variants.initApps`. Then, at the start of each `app`-, `lem`-, `rdg`- element, call `Variants.startApp(tag)` with tag the corresponding tag name ( `app`, `lem`, or `rdg`). Likewise, at the end, call `Variants.endApp(tag)`. Whenever you create slots, issue a `Variants.startSent()` first, and a `Variants.checkSent()` after. Close every TEI file with a `Variants.endSent()`, to finish off all pending sentences. Parameters ---------- cv: object The `tf.convert.walker.CV` object. This is the machinery that constructs nodes and assigns features. cur: dict Keys and values by which a conversion program maintains current information. The conversion proceeds by executing a custom `director()` function, and this director walks through the source material and fires `cv` actions. During the walk, the director can remember incoming data as needed in a dict, and it is this dict that should be passed. The `Variants` object stores additional information here under specific keys. Those keys are mentioned in constants in the source code and there are a few keys dependent on the `sentType` parameter, namely f"n{sentType}" f"stack{sentType}" f"var{sentType}" baseWitness: string The name of the base text. Take care that it is different from the names of the witnesses. sentType: string The name of the node type of the nodes that will be constructed on the basis of boundaries. It could be "sentence", but it could also be any other name, and it is not assumed that the nodes in question represent sentences. It could be anything, provided we have access to its boundaries. checkPunc: function(string, string, punc): boolean Given the texts of the last two slots and the punctuation after that, it determines whether is contains a boundary. This function should be written in the converter program. Hence it is up to the conversion code to define what constitutes a boundary, and whether it are sentences or some things else that are being bounded. This function is called and depending on the outcome sentence nodes are terminated and / or created, or nothing is done. addWarning, addError: function(string, dict) Functions taking a message string and a dict with current information (typically cur). They will be called if a warning or error has to be issued. When they is called, `cur` will be passed as dict. This function should be defined in the conversion program. It may use values in `cur` to generate an indication where the warning / error occurred. """ self.cv = cv self.cur = cur self.sentType = sentType self.baseWitness = baseWitness self.checkPunc = checkPunc self.addWarning = addWarning self.addError = addError self.nSent = f"n{sentType}" self.stackSent = f"stack{sentType}" self.varSent = f"variants{sentType}" cur[WITNESSES] = set() def collectWitnesses(self, node): """Collect all witnesses. Call this for the root nodes of every TEI file of the corpus. Collects the witnesses from all `rdg`-elements. For each `lem`-element the set of witnesses of its `rdg` siblings is collected in such a way that it can be retrieved later on. We also store a pointer to the parent `app`-element of each nested `app`-element. We also check that multiple direct-`rdg` children of the same app have disjoint witnesses. """ cur = self.cur addWarning = self.addWarning tag = node.tag.lower() atts = node.attrib appStack = cur[APP_STACK] apps = cur[APPS] if tag == APP: parentApp = appStack[-1] if len(appStack) else None nApp = cur[N_APP] cur[N_APP] = nApp + 1 appStack.append(nApp + 1) apps[nApp + 1] = dict(parent=parentApp, xwits=set(), rdgs=[]) elif tag == RDG: att = WIT if att in atts: ws = {w.strip(".").lower() for w in atts[att].split()} cur[WITNESSES] |= ws apps[appStack[-1]][X_WITS] |= ws rdgSeen = apps[appStack[-1]][RDGS] for rdg in rdgSeen: if rdg & ws: addWarning( "witnesses of rdg not disjoint from sibling rdgs", cur ) apps[appStack[-1]][RDGS].append(ws) for child in node: self.collectWitnesses(child) if tag == APP: appStack.pop() def initApps(self): """Initialize app- processing and witness collection. You can issue this command once for the whole corpus, or each time before entering a volume. """ cur = self.cur cur[APPS] = dict() cur[APP_STACK] = [] cur[TRANS_NEXT] = [] cur[N_APP] = 0 def resetApps(self): """Initialize app- and "sentence" processing. Set up the data store for collecting information and "sentence" processing. Do this after collecting the witnesses. You can issue this command once for the whole corpus, or each time before entering a volume. But it should be kept in tandem with `Variants.initApps`. """ cur = self.cur baseWitness = self.baseWitness nSent = self.nSent stackSent = self.stackSent varSent = self.varSent cur[N_APP] = 0 cur[WITS] = [] cur[X_WITS] = [] cur[TRANS_LAST] = None cur[nSent] = 0 cur[stackSent] = [] cur[varSent] = {baseWitness: None} def startApp(self, tag, atts): """Actions at the start of `app`- `lem`- and `rdg`-elements. Use this each time you enter one of these XML elements. Parameters ---------- tag: string The tag name of the XML element that is being entered atts: dict The attributes of the XML element that is being entered """ cur = self.cur curStackSent = cur[self.stackSent] if tag == APP: nApp = cur[N_APP] cur[N_APP] = nApp + 1 appInfo = cur[APPS][nApp + 1] parentApp = appInfo[PARENT] xwits = appInfo[X_WITS] slots = self._diverge() cur[TRANS_NEXT].append("") curStackSent.append( dict( translast=cur[TRANS_LAST], slots=slots, ) ) while parentApp is not None: appInfo = cur[APPS][parentApp] # keep xwits immutable, don't say xwits |= blabla # because that will change xwits in place xwits = xwits | appInfo[X_WITS] parentApp = appInfo[PARENT] cur[X_WITS].append(xwits) elif tag == LEM: xWits = self._getXwits() for wit in self._getWits(): if wit in xWits: self._suspend(wit) else: self._resume(wit) elif tag == RDG: wits = set() if WIT in atts: wits = {w.strip(".").lower() for w in atts[WIT].split()} atts[WIT] = " ".join(wits) cur[WITS].append(wits) for wit in self._getWits(): if wit in wits: self._resume(wit) else: self._suspend(wit) def endApp(self, tag): """Actions at the end of `app`- `lem`- and `rdg`-elements. Use this each time you leave one of these XML elements. Parameters ---------- tag: string The tag name of the XML element that is being left """ cur = self.cur curStackSent = cur[self.stackSent] if tag == APP: cur[X_WITS].pop() xWits = self._getXwits() for wit in self._getWits(): if wit not in xWits: self._resume(wit) curStackSent.pop() cur[TRANS_LAST] = cur[TRANS_NEXT].pop() elif tag == LEM: cur[TRANS_NEXT][-1] = cur[TRANS_LAST] xWits = self._getXwits() for wit in self._getWits(): if wit not in xWits: self._suspend(wit) elif tag == RDG: wits = cur[WITS][-1] for wit in wits: self._suspend(wit) cur[WITS].pop() def checkSent(self, trans, punc): """Checks whether there is a "sentence" boundary at this point. Use this every time you have added a slot node. Parameters ---------- trans: string The text of the newly added slot node. If this is empty, the text of the slot before that will be consulted. This value is taken from the context information. This very function is responsible for putting the last text value into the context. punc: string The non-alphanumeric text material after the text of the last slot. Will be used to determine whether there is a "sentence" break here. The actual check will be done by the function `checkPunc`, which has been passed as parameter when the `Variants` object was created. """ cur = self.cur checkPunc = self.checkPunc lastTrans = trans or cur[TRANS_LAST] or "" if checkPunc(lastTrans, trans, punc): self.endSent() else: cur[TRANS_LAST] = trans def startSent(self): """Starts a "sentence" if there is no current sentence. When in an `rdg`-element, witness-dependent "sentence" nodes are created for each witness for the `rdg`. Use this before creating a slot and / or at the start of certain elements such as paragraphs. """ cur = self.cur baseWitness = self.baseWitness inRdg = RDG in cur and len(cur[RDG]) > 0 inLem = LEM in cur and len(cur[LEM]) > 0 if inLem: self._startSentLem() elif inRdg: self._startSentRdg() else: self._start(baseWitness, witAtt=False) def endSent(self): """Ends a "sentence" if there is a current sentence. Use this at the end of each XML file if you are sure that there should not remain pending sentences. You can also call this at the end of certain elements, such as paragraphs. When in a `lem`-element, all pending "sentences" of all witnesses that agree with the base text here are also ended. No new sentences for these witnesses are started, since we are in the base text. """ cur = self.cur inRdg = RDG in cur and len(cur[RDG]) > 0 inLem = LEM in cur and len(cur[LEM]) > 0 if inLem: self._endSentLem() elif inRdg: self._endSentRdg() else: for wit in self._getWits(): self._terminate(wit) def _startSentLem(self): baseWitness = self.baseWitness self._start(baseWitness) def _endSentLem(self): xWits = self._getXwits() for wit in self._getWits(): if wit not in xWits: self._terminate(wit) def _startSentRdg(self): cur = self.cur curStackSent = cur[self.stackSent] wits = cur[WITS][-1] topStack = curStackSent[-1] cur[TRANS_LAST] = topStack[TRANS_LAST] for wit in wits: self._prepend(wit) def _endSentRdg(self): cur = self.cur wits = cur[WITS][-1] for wit in wits: self._terminate(wit) def _get(self, wit): cur = self.cur baseWitness = self.baseWitness curVarSent = cur[self.varSent] isBase = wit == baseWitness if isBase: return curVarSent[baseWitness] return curVarSent.get(wit, None) def _getWits(self): cur = self.cur curVarSent = cur[self.varSent] return list(curVarSent) def _getXwits(self): cur = self.cur xWits = cur[X_WITS] return xWits[-1] if xWits else set() def _start(self, wit, witAtt=True): s = self._get(wit) if s is not None: return s cv = self.cv cur = self.cur sentType = self.sentType curVarSent = cur[self.varSent] nSent = self.nSent baseWitness = self.baseWitness isBase = wit == baseWitness s = cv.node(sentType) cur[nSent] += 1 cv.feature(s, n=cur[nSent]) if witAtt: cv.feature(s, wit=wit) if isBase: curVarSent[baseWitness] = s else: curVarSent[wit] = s return s def _terminate(self, wit): cv = self.cv cur = self.cur baseWitness = self.baseWitness curVarSent = cur[self.varSent] isBase = wit == baseWitness s = self._get(wit) if s is not None: cv.terminate(s) if isBase: curVarSent[wit] = None else: del curVarSent[wit] def _resume(self, wit): cv = self.cv s = self._get(wit) if s is not None: cv.resume(s) def _suspend(self, wit): cv = self.cv s = self._get(wit) if s is not None: cv.terminate(s) def _diverge(self): cv = self.cv baseWitness = self.baseWitness s = self._get(baseWitness) if s is None: return None cv.feature(s, wit=baseWitness) return cv.linked(s) def _prepend(self, wit): if self._get(wit) is None: cv = self.cv cur = self.cur curStackSent = cur[self.stackSent] topStack = curStackSent[-1] slots = topStack[SLOTS] s = self._start(wit) if s is not None and slots is not None: cv.link(s, topStack[SLOTS])Methods
def checkSent(self, trans, punc)-
Checks whether there is a "sentence" boundary at this point.
Use this every time you have added a slot node.
Parameters
trans:string- The text of the newly added slot node. If this is empty, the text of the slot before that will be consulted. This value is taken from the context information. This very function is responsible for putting the last text value into the context.
punc:string- The non-alphanumeric text material after the text of the last slot.
Will be used to determine whether there is a "sentence" break here.
The actual check will be done by the function
checkPunc, which has been passed as parameter when theVariantsobject was created.
def collectWitnesses(self, node)-
Collect all witnesses.
Call this for the root nodes of every TEI file of the corpus.
Collects the witnesses from all
rdg-elements. For eachlem-element the set of witnesses of itsrdgsiblings is collected in such a way that it can be retrieved later on.We also store a pointer to the parent
app-element of each nestedapp-element.We also check that multiple direct-
rdgchildren of the same app have disjoint witnesses. def endApp(self, tag)-
Actions at the end of
app-lem- andrdg-elements.Use this each time you leave one of these XML elements.
Parameters
tag:string- The tag name of the XML element that is being left
def endSent(self)-
Ends a "sentence" if there is a current sentence.
Use this at the end of each XML file if you are sure that there should not remain pending sentences. You can also call this at the end of certain elements, such as paragraphs.
When in a
lem-element, all pending "sentences" of all witnesses that agree with the base text here are also ended. No new sentences for these witnesses are started, since we are in the base text. def initApps(self)-
Initialize app- processing and witness collection.
You can issue this command once for the whole corpus, or each time before entering a volume.
def resetApps(self)-
Initialize app- and "sentence" processing.
Set up the data store for collecting information and "sentence" processing. Do this after collecting the witnesses.
You can issue this command once for the whole corpus, or each time before entering a volume. But it should be kept in tandem with
Variants.initApps(). def startApp(self, tag, atts)-
Actions at the start of
app-lem- andrdg-elements.Use this each time you enter one of these XML elements.
Parameters
tag:string- The tag name of the XML element that is being entered
atts:dict- The attributes of the XML element that is being entered
def startSent(self)-
Starts a "sentence" if there is no current sentence.
When in an
rdg-element, witness-dependent "sentence" nodes are created for each witness for therdg.Use this before creating a slot and / or at the start of certain elements such as paragraphs.