rem stringlengths 0 322k | add stringlengths 0 2.05M | context stringlengths 8 228k |
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print >>f, '\n f.close | print >> f, '\n f.close() | #ifndef GEANY_FUNCTIONS_H |
def _get_superclass(self, c): | def _get_superclass(self, _object): | def _get_superclass(self, c): """ Python class base-finder (found on http://mail.python.org/pipermail/python-list/2002-November/173949.html) |
@param c (object) | @param _object (object) | def _get_superclass(self, c): """ Python class base-finder (found on http://mail.python.org/pipermail/python-list/2002-November/173949.html) |
if type(c) == types.ClassType: return c.__bases__[0].__name__ | if type(_object) == types.ClassType: return _object.__bases__[0].__name__ | def _get_superclass(self, c): """ Python class base-finder (found on http://mail.python.org/pipermail/python-list/2002-November/173949.html) |
return c.__mro__[1].__name__ except Exception, e: | return _object.__mro__[1].__name__ except IndexError: | def _get_superclass(self, c): """ Python class base-finder (found on http://mail.python.org/pipermail/python-list/2002-November/173949.html) |
return '(' + string.join(specs, ', ') + ')' | return ', '.join(specs) | def _formatargspec(self, args, varargs=None, varkw=None, defaults=None, formatarg=str, formatvarargs=lambda name: '*' + name, formatvarkw=lambda name: '**' + name, formatvalue=lambda value: '=' + repr(value), join=inspect.joinseq): """Format an argument spec from the 4 values returned by getargspec. |
except TypeError, KeyError: | except (TypeError, KeyError): | def _add_tag(self, obj, tag_type, parent=''): """ Verify the found tag name and if it is valid, add it to the list |
except Exception, e: | except IOError, e: print '%s: %s' % (filename, e) return except Exception: | def process_file(self, filename): """ Read the file specified by filename and look for class and function definitions |
continue; | continue | def process_file(self, filename): """ Read the file specified by filename and look for class and function definitions |
fp = open(filename) for line in fp: | filep = open(filename) for line in filep: | def process_file(self, filename): """ Read the file specified by filename and look for class and function definitions |
fp.close() | filep.close() | def process_file(self, filename): """ Read the file specified by filename and look for class and function definitions |
fp = open(filename, 'wb') fp.write( | target_file = open(filename, 'wb') target_file.write( | def write_to_file(self, filename): """ Sort the found tags and write them into the file specified by filename |
for s in result: if not s == '\n': fp.write(s) fp.close() | for symbol in result: if not symbol == '\n': target_file.write(symbol) target_file.close() | def write_to_file(self, filename): """ Sort the found tags and write them into the file specified by filename |
try: firstLine = str(generators.next()) except Exception: s = format_exc() yield 'HTTP/1.0 500 Internal Server Error\r\n\r\n' yield str(s) return if not firstLine.startswith('HTTP/1.'): contentType = 'text/html' if path.endswith('.xml'): contentType = 'text/xml' yield 'HTTP/1.0 200 Ok\r\nContent-Type: %s; charset=utf-... | while True: try: firstValue = generators.next() if callable(firstValue): yield firstValue else: firstLine = str(firstValue) if not firstLine.startswith('HTTP/1.'): contentType = 'text/html' if path.endswith('.xml'): contentType = 'text/xml' yield 'HTTP/1.0 200 Ok\r\nContent-Type: %s; charset=utf-8\r\n\r\n' % contentTy... | def handleRequest(self, scheme='', netloc='', path='', query='', fragments='', arguments={}, Headers={}, **kwargs): |
yield str(line) | yield line if callable(line) else str(line) | def handleRequest(self, scheme='', netloc='', path='', query='', fragments='', arguments={}, Headers={}, **kwargs): |
} | } limit 5 | def test_federation (self): F = SWObjects.AtomFactory() sparqlParser = SWObjects.SPARQLfedDriver("", F) mapSetParser = SWObjects.MapSetDriver("", F) queryMapper = SWObjects.ChainingMapper(F, None) sparqlParser.unnestTree = True |
print "MS nodeshare: ", ms.nodeShare | def test_federation (self): F = SWObjects.AtomFactory() sparqlParser = SWObjects.SPARQLfedDriver("", F) mapSetParser = SWObjects.MapSetDriver("", F) queryMapper = SWObjects.ChainingMapper(F, None) sparqlParser.unnestTree = True | |
transformed = queryMapper.map(query) print transformed.toString() canon = SWObjects.SWObjectCanonicalizer(F) print "canon: ", canon transformed.express(canon) ourlast = canon.last print "our last: ", ourlast transformedNorm = ourlast.operation print transformedNorm.toString() agent = SWObjects.WEBagent_boostASIO()... | try: transformed = queryMapper.map(query) canon = SWObjects.SWObjectCanonicalizer(F) transformed.express(canon) ourlast = canon.last transformedNorm = ourlast.operation agent = SWObjects.WEBagent_boostASIO() xmlParser = SWObjects.SAXparser_expat() DB = SWObjects.RdfDB(agent, xmlParser) rs = SWObjects.ResultSet(F) tr... | def test_federation (self): F = SWObjects.AtomFactory() sparqlParser = SWObjects.SPARQLfedDriver("", F) mapSetParser = SWObjects.MapSetDriver("", F) queryMapper = SWObjects.ChainingMapper(F, None) sparqlParser.unnestTree = True |
ctx.set_source_rgb(255,255,255) | ctx.set_source_rgb(1,1,1) | def __init__(self, image=None, # PIL image size=None, ctx=None, imageType=None, # determines file type fileName=None, # if set determines output file name ): """ Canvas can be used in four modes: 1) using the supplied PIL image 2) using the supplied cairo context ctx 3) writing to a file fileName with image type imag... |
"raw","RGBA",0,1) | "raw","BGRA",0,1) | def flush(self): """temporary interface, must be splitted to different methods, (elif self.imageType == "png":)""" if self.fileName and self.imageType=='png': self.surface.write_to_png(self.fileName) elif self.image is not None: self.image.fromstring(self.surface.get_data(), "raw","RGBA",0,1) self.surface.finish() elif... |
color = (int(color[0]*255),int(color[1]*255),int(color[2]*255)) | def convertColor(color): color = (int(color[0]*255),int(color[1]*255),int(color[2]*255)) return color | |
imgd = image.tostring() | imgd = image.tostring("raw","BGRA") | def __init__(self, image=None, # PIL image size=None, ctx=None, imageType=None, # determines file type fileName=None, # if set determines output file name ): """ Canvas can be used in four modes: 1) using the supplied PIL image 2) using the supplied cairo context ctx 3) writing to a file fileName with image type imag... |
def convertColor(color): return color | def flush(self): """temporary interface, must be splitted to different methods, (elif self.imageType == "png":)""" if self.fileName and self.imageType=='png': self.surface.write_to_png(self.fileName) elif self.image is not None: # on linux at least it seems like the PIL images are BGRA, not RGBA: self.image.fromstring(... | |
color = convertColor(color) | def addCanvasLine(canvas,p1,p2,color=(0,0,0),color2=None,**kwargs): canvas.ctx.set_line_width(kwargs.get('linewidth',1)) if color2 and color2!=color: mp = (p1[0]+p2[0])/2.,(p1[1]+p2[1])/2. color = convertColor(color) canvas.ctx.set_source_rgb(*color) _doLine(canvas,p1,mp,**kwargs) canvas.ctx.stroke() color2 = convertCo... | |
color2 = convertColor(color2) | def addCanvasLine(canvas,p1,p2,color=(0,0,0),color2=None,**kwargs): canvas.ctx.set_line_width(kwargs.get('linewidth',1)) if color2 and color2!=color: mp = (p1[0]+p2[0])/2.,(p1[1]+p2[1])/2. color = convertColor(color) canvas.ctx.set_source_rgb(*color) _doLine(canvas,p1,mp,**kwargs) canvas.ctx.stroke() color2 = convertCo... | |
color = convertColor(color) | def addCanvasText(canvas,text,pos,font,color=(0,0,0),**kwargs): color = convertColor(color) canvas.ctx.select_font_face("Georgia", cairo.FONT_SLANT_NORMAL, cairo.FONT_WEIGHT_BOLD) canvas.ctx.set_font_size(font.size) w,h=canvas.ctx.text_extents(text)[2:4] bw,bh=w*1.8,h*1.4 dPos = pos[0]-bw/2.,pos[1]-bh/2. bgColor=kwargs... | |
bgColor = convertColor(bgColor) | def addCanvasText(canvas,text,pos,font,color=(0,0,0),**kwargs): color = convertColor(color) canvas.ctx.select_font_face("Georgia", cairo.FONT_SLANT_NORMAL, cairo.FONT_WEIGHT_BOLD) canvas.ctx.set_font_size(font.size) w,h=canvas.ctx.text_extents(text)[2:4] bw,bh=w*1.8,h*1.4 dPos = pos[0]-bw/2.,pos[1]-bh/2. bgColor=kwargs... | |
color = convertColor(color) | def addCanvasPolygon(canvas,ps,color=(0,0,0),**kwargs): dps = [] color = convertColor(color) canvas.ctx.set_source_rgb(*color) canvas.ctx.move_to(ps[0][0],ps[0][1]) for p in ps[1:]: canvas.ctx.line_to(p[0],p[1]) canvas.ctx.close_path() canvas.ctx.fill() | |
from aggdraw import Draw2 | from aggdraw import Draw | def MolToImage(mol,size=(300,300),kekulize=True, wedgeBonds=True,highlightAtoms=[]): """ returns a PIL image containing a drawing of the molecule """ if not mol: raise ValueError,'Null molecule provided' import MolDrawing try: from aggdraw import Draw2 import Image MolDrawing.registerCanvas('agg') Canvas = Draw useAGG=... |
m = Chem.MolFromSmiles(smi) | m = Chem.MolFromSmiles(spelling) | def _testSpellings(self,smiList): for smi,spellings in smiList: m = Chem.MolFromSmiles(smi) canSmi = Chem.MolToSmiles(m) for spelling in spellings: m = Chem.MolFromSmiles(smi) trySmi = Chem.MolToSmiles(m) assert canSmi==trySmi,'Non-canonical: mol %s gave %s (should be %s)'%(spelling,trySmi,canSmi) m2 = Chem.MolFromSmil... |
'O=[N+1]([O--1])c1ccc(cc1)[N+1]([O--1])=O', '[O--1][N+1](=O)c1ccc(cc1)[N+1]([O--1])=O')), | 'O=[N+1]([O-1])c1ccc(cc1)[N+1]([O-1])=O', '[O-1][N+1](=O)c1ccc(cc1)[N+1]([O-1])=O')), | def testProblems(self): " testing molecules which have been problematic " smiList = [ ('[Al+3]CCC',('CCC[Al+3]','C(C)(C[Al+3])' ) ), ('C(=O)(Cl)CC(=O)Cl',('ClC(CC(Cl)=O)=O','C(Cl)(=O)CC(=O)Cl','C(Cl)(=O)CC(Cl)=O')), ('C(=O)(Cl)c1ccc(C(=O)Cl)cc1',('O=C(Cl)c1ccc(cc1)C(Cl)=O','C(Cl)(=O)C1=CC=C(C=C1)C(Cl)=O', 'ClC(=O)c1ccc... |
jsonObject["id"] = entry.id.text[indexOfSlash:] | jsonObject["id"] = entry.id.text[indexOfSlash+1:] | def write_feed_to_file(gd_client): jsonFile = open('my/{0}.contacts.json'.format(GetUIDHash(gd_client)), 'w') query = gdata.contacts.service.ContactsQuery() query.max_results = 3000 feed = gd_client.GetContactsFeed(query.ToUri()) for i, entry in enumerate(feed.entry): jsonObject = {} indexOfSlash = entry.id.text.rfind(... |
hosted_image_binary = gd_client.GetPhoto(entry) if hosted_image_binary: image_file = open('my/photos/{0}.jpg'.format(jsonObject["id"]), 'wb') image_file.write(hosted_image_binary) image_file.close() | try: hosted_image_binary = gd_client.GetPhoto(entry) if hosted_image_binary: image_file = open('my/photos/{0}.jpg'.format(jsonObject["id"]), 'wb') image_file.write(hosted_image_binary) image_file.close() except gdata.service.RequestError: pass | def write_feed_to_file(gd_client): jsonFile = open('my/{0}.contacts.json'.format(GetUIDHash(gd_client)), 'w') query = gdata.contacts.service.ContactsQuery() query.max_results = 3000 feed = gd_client.GetContactsFeed(query.ToUri()) for i, entry in enumerate(feed.entry): jsonObject = {} indexOfSlash = entry.id.text.rfind(... |
feed = gd_client.GetContactsFeed() | query = gdata.contacts.service.ContactsQuery() query.max_results = 3000 feed = gd_client.GetContactsFeed(query.ToUri()) | def write_feed_to_file(gd_client): jsonFile = open('my/{0}.contacts.json'.format(GetUIDHash(gd_client)), 'w') feed = gd_client.GetContactsFeed() for i, entry in enumerate(feed.entry): jsonObject = {} jsonObject["id"] = entry.id.text[-16:] print '%s %s' % (i+1, entry.title.text) jsonObject["name"] = entry.title.text if... |
jsonObject["id"] = entry.id.text[-16:] | indexOfSlash = entry.id.text.rfind("/") jsonObject["id"] = entry.id.text[indexOfSlash:] | def write_feed_to_file(gd_client): jsonFile = open('my/{0}.contacts.json'.format(GetUIDHash(gd_client)), 'w') feed = gd_client.GetContactsFeed() for i, entry in enumerate(feed.entry): jsonObject = {} jsonObject["id"] = entry.id.text[-16:] print '%s %s' % (i+1, entry.title.text) jsonObject["name"] = entry.title.text if... |
self.dbg.SetAsync(True) | def run(self): print "Running MyListeningThread:", self count = 0 # Let's only try at most 3 times to retrieve any kind of event. while not count > 3: if listener.WaitForEvent(5, event): print "Got a valid event:", event print "Event type:", event.GetType() print "Event broadcaster:", event.GetBroadcaster().GetName() r... | |
self.process.Continue() | self.process.Kill() | def run(self): print "Running MyListeningThread:", self count = 0 # Let's only try at most 3 times to retrieve any kind of event. while not count > 3: if listener.WaitForEvent(5, event): print "Got a valid event:", event print "Event type:", event.GetType() print "Event broadcaster:", event.GetBroadcaster().GetName() r... |
self.runCmd("image dump symtab a.out") | self.runCmd("image dump symtab -s address a.out") | def order_file(self): """Test debug symbols follow the correct order by the order file.""" exe = os.path.join(os.getcwd(), "a.out") self.runCmd("file " + exe, CURRENT_EXECUTABLE_SET) |
def test_broadcast_event_with_dsym(self): """Exercise SBBroadcaster.BroadcastEvent() API.""" | def test_add_listener_to_broadcaster_dsym(self): """Exercise some SBBroadcaster APIs.""" | def test_broadcast_event_with_dsym(self): """Exercise SBBroadcaster.BroadcastEvent() API.""" self.buildDsym() self.do_broadcast_event() |
self.do_broadcast_event() @python_api_test def test_broadcast_event_with_dwarf(self): """Exercise SBBroadcaster.BroadcastEvent() API.""" | self.do_add_listener_to_broadcaster() @python_api_test def test_add_listener_to_broadcaster_dwarf(self): """Exercise some SBBroadcaster APIs.""" | def test_broadcast_event_with_dsym(self): """Exercise SBBroadcaster.BroadcastEvent() API.""" self.buildDsym() self.do_broadcast_event() |
self.do_broadcast_event() | self.do_add_listener_to_broadcaster() | def test_broadcast_event_with_dwarf(self): """Exercise SBBroadcaster.BroadcastEvent() API.""" self.buildDwarf() self.do_broadcast_event() |
def do_broadcast_event(self): """Get the broadcaster associated with the process and exercise BroadcastEvent API.""" | def do_add_listener_to_broadcaster(self): """Get the broadcaster associated with the process and wait for broadcaster events.""" | def do_broadcast_event(self): """Get the broadcaster associated with the process and exercise BroadcastEvent API.""" exe = os.path.join(os.getcwd(), "a.out") |
if listener.WaitForEvent(5, event): | if listener.WaitForEventForBroadcasterWithType(5, broadcaster, lldb.SBProcess.eBroadcastBitStateChanged, event): | def run(self): #print "Running MyListeningThread:", self |
substrs = ["(MyString *) self", | substrs = ["(MyString) *self", | def data_type_and_expr_objc(self): """Lookup objective-c data types and evaluate expressions.""" exe = os.path.join(os.getcwd(), "a.out") self.runCmd("file " + exe, CURRENT_EXECUTABLE_SET) |
if self.contains_term(t): | try: | def similar_terms(self, t): """ Returns an iterable over the indices of similar terms. Raises KeyError if the term is not found. """ terms = self.terms |
i = self.lookup_term_index(t) | i = self.lookup_term_index(tv) except KeyError: i = None if i is not None: | def similar_terms(self, t): """ Returns an iterable over the indices of similar terms. Raises KeyError if the term is not found. """ terms = self.terms |
for i,st in enumerate(self.terms): if terms[i] in t: | for i,st in enumerate(terms): if st in t: | def similar_terms(self, t): """ Returns an iterable over the indices of similar terms. Raises KeyError if the term is not found. """ terms = self.terms |
elif t in terms[i]: | elif t in st: | def similar_terms(self, t): """ Returns an iterable over the indices of similar terms. Raises KeyError if the term is not found. """ terms = self.terms |
modification_time = time.localtime(os.path.getmtime(self.path)) return time.strftime("%a, %d %b %Y %H:%M:%S %Z", modification_time) | modification_time = time.gmtime(os.path.getmtime(self.path)) return time.strftime("%a, %d %b %Y %H:%M:%S +0000", modification_time) | def last_modified(self): """Get the last time the calendar has been modified. |
answer = self._calendar.read().encode(self._encoding) | answer = self._calendar.text.encode(self._encoding) | def do_GET(self): """Manage GET request.""" answer = self._calendar.read().encode(self._encoding) |
items = items or self.items | items = items if items is not None else self.items | def write(self, headers=None, items=None): """Write calendar with given parameters.""" headers = headers or self.headers or ( Header("PRODID:-//Radicale//NONSGML Radicale Server//EN"), Header("VERSION:2.0")) items = items or self.items |
elements = [calendar] | items = [calendar] | def propfind(path, xml_request, calendar, depth, request): """Read and answer PROPFIND requests. Read rfc4918-9.1 for info. """ # Reading request root = ET.fromstring(xml_request) prop_element = root.find(_tag("D", "prop")) prop_list = prop_element.getchildren() props = [prop.tag for prop in prop_list] # Writing an... |
elements = [calendar] + calendar.events + calendar.todos | items = [calendar] + calendar.events + calendar.todos | def propfind(path, xml_request, calendar, depth, request): """Read and answer PROPFIND requests. Read rfc4918-9.1 for info. """ # Reading request root = ET.fromstring(xml_request) prop_element = root.find(_tag("D", "prop")) prop_list = prop_element.getchildren() props = [prop.tag for prop in prop_list] # Writing an... |
elements = [calendar] + calendar.events + calendar.todos for element in elements: is_calendar = isinstance(element, ical.Calendar) | items = [calendar] + calendar.events + calendar.todos for item in items: is_calendar = isinstance(item, ical.Calendar) | def propfind(path, xml_request, calendar, depth, request): """Read and answer PROPFIND requests. Read rfc4918-9.1 for info. """ # Reading request root = ET.fromstring(xml_request) prop_element = root.find(_tag("D", "prop")) prop_list = prop_element.getchildren() props = [prop.tag for prop in prop_list] # Writing an... |
href.text = path if is_calendar else "%s/%s" % (path, element.name) | href.text = path if is_calendar else "%s/%s" % (path, item.name) | def propfind(path, xml_request, calendar, depth, request): """Read and answer PROPFIND requests. Read rfc4918-9.1 for info. """ # Reading request root = ET.fromstring(xml_request) prop_element = root.find(_tag("D", "prop")) prop_list = prop_element.getchildren() props = [prop.tag for prop in prop_list] # Writing an... |
element.text = element.etag | element.text = item.etag | def propfind(path, xml_request, calendar, depth, request): """Read and answer PROPFIND requests. Read rfc4918-9.1 for info. """ # Reading request root = ET.fromstring(xml_request) prop_element = root.find(_tag("D", "prop")) prop_list = prop_element.getchildren() props = [prop.tag for prop in prop_list] # Writing an... |
content_type = self.headers["Content-Type"] | content_type = self.headers.get("Content-Type", None) | def _decode(self, text): """Try to decode text according to various parameters.""" # List of charsets to try charsets = [] |
items = self._calendar.timezones | def do_HEAD(self): """Manage HEAD request.""" item_name = xmlutils.name_from_path(self.path) if item_name: # Get calendar item items = self._calendar.timezones item = self._calendar.get_item(item_name) items.append(item) answer_text = ical.serialize( headers=self._calendar.headers, items=items) etag = item.etag else: #... | |
items.append(item) answer_text = ical.serialize( headers=self._calendar.headers, items=items) etag = item.etag | if item: items = self._calendar.timezones items.append(item) answer_text = ical.serialize( headers=self._calendar.headers, items=items) etag = item.etag else: self.send_response(client.GONE) return | def do_HEAD(self): """Manage HEAD request.""" item_name = xmlutils.name_from_path(self.path) if item_name: # Get calendar item items = self._calendar.timezones item = self._calendar.get_item(item_name) items.append(item) answer_text = ical.serialize( headers=self._calendar.headers, items=items) etag = item.etag else: #... |
if not os.path.exists(self.path): self.write() | def __init__(self, path): """Initialize the calendar with ``cal`` and ``user`` parameters.""" # TODO: Use properties from the calendar configuration self.encoding = "utf-8" self.owner = path.split("/")[0] self.path = os.path.join(FOLDER, path.replace("/", os.path.sep)) # Create calendar if needed, useful for ``self.las... | |
version="0.1", | version="0.2", | def _should_remove(filename): return (os.path.splitext(filename)[1] == ".pyc" or os.path.splitext(filename)[1] == ".pyo" or filename.endswith("~") or (filename.startswith("#") and filename.endswith("#"))) |
k += 1 | def Solve(self, **kwargs): """ Solve the trust-region subproblem. | |
def store(self, iter, new_s, new_y): | def store(self, new_s, new_y): | def store(self, iter, new_s, new_y): # Simply swap s and y. InverseLBFGS.store(self, iter, new_y, new_s) |
InverseLBFGS.store(self, iter, new_y, new_s) | InverseLBFGS.store(self, new_y, new_s) | def store(self, iter, new_s, new_y): # Simply swap s and y. InverseLBFGS.store(self, iter, new_y, new_s) |
iter = kwargs.get('iter', None) if iter is None: raise ValueError, 'Please specify iteration number.' Hv = self.ldfp.matvec(iter, v) | Hv = self.ldfp.matvec(v) | def hprod(self, z, v, **kwargs): """ Compute the matrix-vector product between the limited-memory DFP approximation kept in storage and the vector `v`. The argument `z` is ignored and is only present for compatibility with the original `hprod`. """ self.Hprod += 1 iter = kwargs.get('iter', None) if iter is None: raise ... |
return x = zeros(n) | x_is_zero = True istop = 0 | def solve(self, rhs, itnlim=0, damp=0.0, atol=1.0e-6, btol=1.0e-7, conlim=1.0e+8, radius=None, show=False, wantvar=False): """ Solve the linear system, linear least-squares problem or regularized linear least-squares problem with specified parameters. All return values below are stored in members of the same name. |
while itn < itnlim: | while itn < itnlim and not x_is_zero: | def solve(self, rhs, itnlim=0, damp=0.0, atol=1.0e-6, btol=1.0e-7, conlim=1.0e+8, radius=None, show=False, wantvar=False): """ Solve the linear system, linear least-squares problem or regularized linear least-squares problem with specified parameters. All return values below are stored in members of the same name. |
test3 = 1.0 / acond | if acond == 0.0: test3 = inf else: test3 = 1.0 / acond | def solve(self, rhs, itnlim=0, damp=0.0, atol=1.0e-6, btol=1.0e-7, conlim=1.0e+8, radius=None, show=False, wantvar=False): """ Solve the linear system, linear least-squares problem or regularized linear least-squares problem with specified parameters. All return values below are stored in members of the same name. |
self.lowerB = np.array(self.nlp.lowerB, dtype=np.int) self.upperB = np.array(self.nlp.upperB, dtype=np.int) self.rangeB = np.array(self.nlp.rangeB, dtype=np.int) self.nlowerB = nlp.nlowerB self.nupperB = nlp.nupperB self.nrangeB = nlp.nrangeB | self.lowerB = np.array(nlp.lowerB) self.upperB = np.array(nlp.upperB) self.rangeB = np.array(nlp.rangeB) self.rlB = np.arange(nlp.nlowerB) self.ruB = np.arange(nlp.nupperB) self.rrB = np.arange(nlp.nrangeB) | def __init__(self, nlp, **kwargs): |
self.ndual = self.nlowerB + self.nupperB + 2 * self.nrangeB | self.ndual = nlp.nlowerB + nlp.nupperB + 2 * nlp.nrangeB | def __init__(self, nlp, **kwargs): |
n = self.nlp.n Lvar = self.nlp.Lvar ; Uvar = self.nlp.Uvar lB = self.lowerB ; uB = self.upperB ; rB = self.rangeB nlB = self.nlowerB ; nuB = self.nupperB ; nrB = self.nrangeB | nlp = self.nlp ; n = nlp.n Lvar = nlp.Lvar ; Uvar = nlp.Uvar lB = nlp.lowerB ; uB = nlp.upperB ; rB = nlp.rangeB nlB = nlp.nlowerB ; nuB = nlp.nupperB ; nrB = nlp.nrangeB | def obj(self, x, z, **kwargs): """ Evaluate the primal-dual merit function at (x,z): |
g = np.empty(n + self.ndual) if gf is None: g[:n] = self.nlp.grad(x) else: g[:n] = gf.copy() if check_optimal: res, self.optimal = self.AtOptimality(x, z, g=g[:n]) self.dRes = res[0] ; self.cRes = res[2] ; self.pRes = res[4] | def grad(self, x, z, **kwargs): """ Evaluate the gradient of the primal-dual merit function at (x,z). The gradient of the objective function at `x`, if known, can be passed via the keyword argument `g`. See :meth:`PDMerit` for a description of `z`. """ mu = kwargs.get('mu', self.mu) check_optimal = kwargs.get('check_op... | |
g[lB] += -2 * mu / slB + zlB g[uB] += 2 * mu / suB + zuB g[rB] += -2 * mu / srlB + zrlB g[rB] += 2 * mu / sruB + zruB n1 = nlB ; n2 = n1 + nuB ; n3 = n2 + nrB g[n:n+n1] = slB - mu/zlB g[n+n1:n+n2] = suB - mu/zuB g[n+n2:n+n3] = srlB - mu/zrlB g[n+n3:] = sruB - mu/zruB return g def primal_hprod(self, x,... | Hp = np.zeros(n + self.ndual) | def grad(self, x, z, **kwargs): """ Evaluate the gradient of the primal-dual merit function at (x,z). The gradient of the objective function at `x`, if known, can be passed via the keyword argument `g`. See :meth:`PDMerit` for a description of `z`. """ mu = kwargs.get('mu', self.mu) check_optimal = kwargs.get('check_op... |
self.maxiter = kwargs.get('maxiter', max(100, 2*self.nlp.n)) | self.maxiter = kwargs.get('maxiter', max(100,2*self.merit.nlp.n)) | def __init__(self, merit, TR, TrSolver, **kwargs): """ Solve the bound-constrained problem |
n = self.nlp.n ; ndual = self.ndual self.B = self.PDHessTemplate() | def __init__(self, merit, TR, TrSolver, **kwargs): """ Solve the bound-constrained problem | |
def StartingPoint(self, **kwargs): | def get_feasible_point(self, **kwargs): | def StartingPoint(self, **kwargs): """ Compute a strictly feasible initial primal-dual estimate (x,z). By default, x is taken as the starting point given in `nlp` and moved strictly into the bounds, and z is taken as the vector of ones. """ n = self.nlp.n Lvar = self.nlp.Lvar ; lB = self.lowerB Uvar = self.nlp.Uvar ; u... |
By default, x is taken as the starting point given in `nlp` and moved strictly into the bounds, and z is taken as the vector of ones. """ n = self.nlp.n Lvar = self.nlp.Lvar ; lB = self.lowerB Uvar = self.nlp.Uvar ; uB = self.upperB ; rB = self.rangeB | By default, x is taken as the starting point given in `nlp` and moved strictly inside the bounds, and z is taken as the vector of ones. """ nlp = self.merit.nlp n = nlp.n Lvar = nlp.Lvar ; lB = nlp.lowerB Uvar = nlp.Uvar ; uB = nlp.upperB ; rB = nlp.rangeB | def StartingPoint(self, **kwargs): """ Compute a strictly feasible initial primal-dual estimate (x,z). By default, x is taken as the starting point given in `nlp` and moved strictly into the bounds, and z is taken as the vector of ones. """ n = self.nlp.n Lvar = self.nlp.Lvar ; lB = self.lowerB Uvar = self.nlp.Uvar ; u... |
x = self.nlp.x0[:] | x = nlp.x0[:] | def StartingPoint(self, **kwargs): """ Compute a strictly feasible initial primal-dual estimate (x,z). By default, x is taken as the starting point given in `nlp` and moved strictly into the bounds, and z is taken as the vector of ones. """ n = self.nlp.n Lvar = self.nlp.Lvar ; lB = self.lowerB Uvar = self.nlp.Uvar ; u... |
z = np.ones(self.ndual) | z = np.ones(self.merit.ndual) | def StartingPoint(self, **kwargs): """ Compute a strictly feasible initial primal-dual estimate (x,z). By default, x is taken as the starting point given in `nlp` and moved strictly into the bounds, and z is taken as the vector of ones. """ n = self.nlp.n Lvar = self.nlp.Lvar ; lB = self.lowerB Uvar = self.nlp.Uvar ; u... |
def PrimalMultipliers(self, x, **kwargs): """ Return the vector of primal multipliers at `x`. The value of the barrier parameter used can either be supplied using the keyword argument `mu` or the current value of the instance is used. | def primal_multipliers(self, x, **kwargs): """ Return the vector of primal multipliers at `x`. The value of the barrier parameter used can either be supplied using the keyword argument `mu` or the current value of the instance is used. | def PrimalMultipliers(self, x, **kwargs): """ Return the vector of primal multipliers at `x`. The value of the barrier parameter used can either be supplied using the keyword argument `mu` or the current value of the instance is used. """ mu = kwargs.get('mu', self.mu) Lvar = self.nlp.Lvar ; Uvar = self.nlp.Uvar lB = s... |
from nlpy.optimize.tr.trustregion import TrustRegionFramework, TrustRegionCG | def grad(self, xz, **kwargs): nx = self.nlp.n return PrimalDualMeritFunction.grad(self, xz[:nx], xz[nx:], **kwargs) | |
TR = TrustRegionFramework(Delta = 1.0, eta1 = 0.0001, eta2 = 0.95, gamma1 = 1.0/3, gamma2 = 2.5) TRIP = PrimalDualInteriorPointFramework( pdmerit, TR, TrustRegionCG, silent = False, | def grad(self, xz, **kwargs): nx = self.nlp.n return PrimalDualMeritFunction.grad(self, xz[:nx], xz[nx:], **kwargs) | |
(x, z) = (pdmerit.x, pdmerit.z) | ) (x, z) = TRIP.get_feasible_point() | def grad(self, xz, **kwargs): nx = self.nlp.n return PrimalDualMeritFunction.grad(self, xz[:nx], xz[nx:], **kwargs) |
derchk.check(verbose=True, hess=False, jac=False, chess=False) | derchk.check(verbose=True, hess=True, jac=False, chess=False) | def grad(self, xz, **kwargs): nx = self.nlp.n return PrimalDualMeritFunction.grad(self, xz[:nx], xz[nx:], **kwargs) |
def _write( self, msg ): sys.stderr.write( self.prefix + msg ) | def _write( self, msg ): sys.stderr.write( self.prefix + msg ) | |
def Factorize( self ): | def _write(self, msg): sys.stderr.write(self.prefix + msg) def Factorize(self): | def Factorize( self ): """ Assemble projection matrix and factorize it |
from nlpy.optimize.solvers import lbfgs | def Solve(self, **kwargs): | |
self.lbfgs = lbfgs_class.LbfgsUpdate(nlp.n, npairs=self.npairs) | self.lbfgs = lbfgs.InverseLBFGS(nlp.n, npairs=self.npairs) | def __init__(self, nlp, TR, TrSolver, **kwargs): |
self.silent = kwargs.get('silent', False) self.ny = kwargs.get('ny', False) | self.silent = kwargs.get('silent', False) self.ny = kwargs.get('ny', False) self.nbk = kwargs.get('nbk', 5) | def __init__(self, nlp, TR, TrSolver, **kwargs): |
self.nIterNonMonotone = kwargs.get('nIterNonMonotone', 25) | self.nIterNonMono = kwargs.get('nIterNonMono', 25) | def __init__(self, nlp, TR, TrSolver, **kwargs): |
if l == self.nIterNonMonotone: | if l == self.nIterNonMono: | def Solve(self, **kwargs): |
while bk < 5 and f_trial >= self.f + 1.0e-4 * self.alpha * slope: | while bk < self.nbk and \ f_trial >= self.f + 1.0e-4 * self.alpha * slope: | def Solve(self, **kwargs): |
stoptol = self.nlp.stop_d * max(1.0, norms.norm2(self.x)) | def solve(self): | |
def to_boundary(self, s, p, Delta, ss = None): """ Given vectors s and p and a trust-region radius Delta > 0, this function returns the positive scalar sigma such that | def to_boundary(self, s, p, Delta, ss=None): """ Given vectors `s` and `p` and a trust-region radius `Delta` > 0, return the positive scalar sigma such that | def to_boundary(self, s, p, Delta, ss = None): """ Given vectors s and p and a trust-region radius Delta > 0, this function returns the positive scalar sigma such that |
in Euclidian norm. If known, supply optional argument ss whose value should be the squared Euclidian norm of argument s. """ | in Euclidian norm. If known, supply optional argument `ss` whose value should be the squared Euclidian norm of argument `s`. """ if Delta is None: raise ValueError, 'Radius value must be positive number.' | def to_boundary(self, s, p, Delta, ss = None): """ Given vectors s and p and a trust-region radius Delta > 0, this function returns the positive scalar sigma such that |
self.infiniteDescentDir = p onBoundary = True | self.infDescent = True self.dir = p | def Solve( self ): if self.A is not None: if self.factorize and not self.factorized: self.Factorize() if self.b is not None: self.FindFeasible() |
z = np.zeros(self.m) ; z[i] = 1 | z = np.zeros(self.m) ; z[i] = -1 | def hiprod(self, i, v, **kwargs): """ Evaluate matrix-vector product Hi(x) * v. Returns a Numpy array. """ z = np.zeros(self.m) ; z[i] = 1 self.Hprod += 1 return _amplpy.H_prod(z, v, 0.) |
if (pHp <= 0 or alpha > sigma) and Delta is not None: | if Delta is not None and (pHp <= 0 or alpha > sigma): | def Solve(self, **kwargs): """ Solve the trust-region subproblem. """ n = self.n g = self.g matvec = self.matvec if matvec is None: H = self.H prec = self.prec |
self.stepNorm = self.xNorm2 | self.stepNorm = 0.0 | def __init__( self, c, **kwargs ): """ Solve the equality-constrained quadratic programming problem |
self.xNorm2 = self.stepNorm = xNorm2 | self.xNorm2 = xNorm2 self.stepNorm = sqrt(xNorm2) | def Solve(self): if self.A is not None: if self.factorize and not self.factorized: self.Factorize() if self.b is not None: self.FindFeasible() |
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