rem stringlengths 0 322k | add stringlengths 0 2.05M | context stringlengths 8 228k |
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msg['From'] = 'cedric.moullet@gmail.com' | msg['From'] = 'cedric.moullet@openaddresses.org' | def mail(self, to, subject, text): # http://kutuma.blogspot.com/2007/08/sending-emails-via-gmail-with-python.html msg = MIMEMultipart() |
return os.getcwd() | return "Not implemented, for now" | def index(self, format='html'): """GET /uploads: All items in the collection""" # url('uploads') return os.getcwd() |
permanent_file = open(archive.filename.lstrip(os.sep),'w') | permanent_file = open(os.path.join(self.main_root + '/trunk/openaddresses/uploads',archive.filename.lstrip(os.sep)), 'w') | def create(self): """POST /uploads: Create a new item""" archive = request.POST['uploaded_file'] email = request.POST['email'] permanent_file = open(archive.filename.lstrip(os.sep),'w') shutil.copyfileobj(archive.file, permanent_file) archive.file.close() permanent_file.close() self.mail(email,"OpenAddresses.org upload... |
return dumps({"success": True}) | return dumps({"success": True, "filename": permanent_file.name}) | def create(self): """POST /uploads: Create a new item""" archive = request.POST['uploaded_file'] email = request.POST['email'] permanent_file = open(archive.filename.lstrip(os.sep),'w') shutil.copyfileobj(archive.file, permanent_file) archive.file.close() permanent_file.close() self.mail(email,"OpenAddresses.org upload... |
sqlQuery = sqlQuery + " WHERE tsvector_street_housenumber_city @@ to_tsquery('" + tsquery + "')" | sqlQuery = sqlQuery + " WHERE tsvector_street_housenumber_city @@ to_tsquery('english', '" + tsquery + "')" | def fullTextSearch(self,request): # addresses/fullTextSearch?fields=street,city,housenumber&query=ch%20du%2028&tolerance=0.005&easting=6.62379551&northing=46.51687241&limit=20&distinct=true # Read request parameters fields = request.params['fields'] |
sqlQuery = sqlQuery + " WHERE tsvector_street @@ to_tsquery('" + tsquery + "')" | sqlQuery = sqlQuery + " WHERE tsvector_street @@ to_tsquery('english','" + tsquery + "')" | def fullTextSearch(self,request): # addresses/fullTextSearch?fields=street,city,housenumber&query=ch%20du%2028&tolerance=0.005&easting=6.62379551&northing=46.51687241&limit=20&distinct=true # Read request parameters fields = request.params['fields'] |
sqlQuery = sqlQuery + " WHERE to_tsvector(" + tsvector + ") @@ to_tsquery('" + tsquery + "')" | sqlQuery = sqlQuery + " WHERE to_tsvector(" + tsvector + ") @@ to_tsquery('english','" + tsquery + "')" | def fullTextSearch(self,request): # addresses/fullTextSearch?fields=street,city,housenumber&query=ch%20du%2028&tolerance=0.005&easting=6.62379551&northing=46.51687241&limit=20&distinct=true # Read request parameters fields = request.params['fields'] |
responseElements = responseText.split('\'') housenumber = responseElements[7] street = responseElements[3] postcode = responseElements[5] city = responseElements[11] | responseElements = responseText.split('\n') for element in responseElements: if element.rfind('strname1') > -1: strname1_s = element.split('=') street = strname1_s[1].lstrip().lstrip('\'').rstrip().rstrip('\'') if element.rfind('plz4') > -1: plz4_s = element.split('=') postcode = plz4_s[1].lstrip().lstrip('\'').rstrip(... | def index(self): if 'latitude' in request.params and 'longitude' in request.params: latitude = float(request.params['latitude']) longitude = float(request.params['longitude']) if 'easting' in request.params: easting = float(request.params['easting']) if 'northing' in request.params: northing = float(request.params['nor... |
tsvector = 'tsvector_street_housenumber_city' | tsvector = "to_tsvector('english', coalesce(street,'') || ' ' || coalesce(housenumber,'') || ' ' || coalesce(city,''))" | def index(self, format='json'): """GET /: return all features.""" # If no filter argument is passed to the protocol index method # then the default MapFish filter is used. This default filter # is constructed based on the box, lon, lat, tolerance GET # params. # # If you need your own filter with application-specific p... |
tsvector = 'tsvector_street' | tsvector = "to_tsvector('english', coalesce(street,''))" | def index(self, format='json'): """GET /: return all features.""" # If no filter argument is passed to the protocol index method # then the default MapFish filter is used. This default filter # is constructed based on the box, lon, lat, tolerance GET # params. # # If you need your own filter with application-specific p... |
limit = request.params['limit'] | limit = int(request.params['limit']) | def fullTextSearch(self,request): # addresses/fullTextSearch?fields=street,city,housenumber&query=ch%20du%2028&tolerance=0.005&easting=6.62379551&northing=46.51687241&limit=20&distinct=true # Read request parameters fields = request.params['fields'] |
yield UInt16(self, "left", "Text Grid Left") yield UInt16(self, "top", "Text Grid Top") yield UInt16(self, "width", "Text Grid Width") yield UInt16(self, "height", "Text Grid Height") | yield UInt16(parent, "left", "Text Grid Left") yield UInt16(parent, "top", "Text Grid Top") yield UInt16(parent, "width", "Text Grid Width") yield UInt16(parent, "height", "Text Grid Height") | def parseTextExtension(parent): yield UInt8(parent, "block_size", "Block Size") yield UInt16(self, "left", "Text Grid Left") yield UInt16(self, "top", "Text Grid Top") yield UInt16(self, "width", "Text Grid Width") yield UInt16(self, "height", "Text Grid Height") yield UInt8(parent, "cell_width", "Character Cell Width"... |
cvt_time=lambda v:datetime(2001,1,1) + timedelta(seconds=v) | def cvt_time(v): v=timedelta(seconds=v) epoch2001 = datetime(2001,1,1) epoch1970 = datetime(1970,1,1) if (epoch2001 + v - datetime.today()).days > 5*365: return epoch1970 + v return epoch2001 + v | def createFields(self): yield Enum(Bits(self, "marker_type", 4), {0: "Simple", 1: "Int", 2: "Real", 3: "Date", 4: "Data", 5: "ASCII String", 6: "UTF-16-BE String", 8: "UID", 10: "Array", 13: "Dict",}) markertype = self['marker_type'].value if markertype == 0: # Simple (Null) yield Enum(Bits(self, "value", 4), {0: "Null... |
self.xml=lambda prefix:prefix + "<date>%s</date>"%(cvt_time(self['value'].value).isoformat()) | self.xml=lambda prefix:prefix + "<date>%sZ</date>"%(cvt_time(self['value'].value).isoformat()) | def createFields(self): yield Enum(Bits(self, "marker_type", 4), {0: "Simple", 1: "Int", 2: "Real", 3: "Date", 4: "Data", 5: "ASCII String", 6: "UTF-16-BE String", 8: "UID", 10: "Array", 13: "Dict",}) markertype = self['marker_type'].value if markertype == 0: # Simple (Null) yield Enum(Bits(self, "value", 4), {0: "Null... |
self.xml=lambda prefix:prefix + "<string>%s</string>"%(self['value'].value.encode('iso-8859-1')) | self.xml=lambda prefix:prefix + "<string>%s</string>"%(self['value'].value.replace('&','&').encode('iso-8859-1')) | def createFields(self): yield Enum(Bits(self, "marker_type", 4), {0: "Simple", 1: "Int", 2: "Real", 3: "Date", 4: "Data", 5: "ASCII String", 6: "UTF-16-BE String", 8: "UID", 10: "Array", 13: "Dict",}) markertype = self['marker_type'].value if markertype == 0: # Simple (Null) yield Enum(Bits(self, "value", 4), {0: "Null... |
self.xml=lambda prefix:prefix + "<string>%s</string>"%(self['value'].value.encode('utf-8')) | self.xml=lambda prefix:prefix + "<string>%s</string>"%(self['value'].value.replace('&','&').encode('utf-8')) | def createFields(self): yield Enum(Bits(self, "marker_type", 4), {0: "Simple", 1: "Int", 2: "Real", 3: "Date", 4: "Data", 5: "ASCII String", 6: "UTF-16-BE String", 8: "UID", 10: "Array", 13: "Dict",}) markertype = self['marker_type'].value if markertype == 0: # Simple (Null) yield Enum(Bits(self, "value", 4), {0: "Null... |
while field: | while field is not None: | def _getPath(self): if not self._parent: return '/' names = [] field = self while field: names.append(field._name) field = field._parent names[-1] = '' return '/'.join(reversed(names)) |
addr_text = '' | addr_text_list = [] | def update_addr_view(self): addr_text = '' for i in xrange(self.view.get_height_chars()): addr_text += self.format_addr(self.pos+i*self.view.get_width_chars())+'\n' self.view.addr_view.SetValue(addr_text) |
addr_text += self.format_addr(self.pos+i*self.view.get_width_chars())+'\n' self.view.addr_view.SetValue(addr_text) | addr_text_list.append( self.format_addr(self.pos+i*self.view.get_width_chars())+'\n') self.view.addr_view.SetValue(''.join(addr_text_list)) | def update_addr_view(self): addr_text = '' for i in xrange(self.view.get_height_chars()): addr_text += self.format_addr(self.pos+i*self.view.get_width_chars())+'\n' self.view.addr_view.SetValue(addr_text) |
self.trackCommon(track, video) | def processVideo(self, track): video = Metadata(self) try: self.trackCommon(track, video) video.compression = track["CodecID/string"].value if "Video" in track: video.width = track["Video/PixelWidth/unsigned"].value video.height = track["Video/PixelHeight/unsigned"].value except MissingField: pass self.addGroup("video[... | |
try: self.trackCommon(track, audio) if "Audio" in track: audio.sample_rate = track["Audio/SamplingFrequency/float"].value | self.trackCommon(track, audio) if "Audio" in track: frequency = self.getDouble(track, "Audio/SamplingFrequency") if frequency is not None: audio.sample_rate = frequency if "Audio/Channels/unsigned" in track: | def processAudio(self, track): audio = Metadata(self) try: self.trackCommon(track, audio) if "Audio" in track: audio.sample_rate = track["Audio/SamplingFrequency/float"].value audio.nb_channel = track["Audio/Channels/unsigned"].value audio.compression = track["CodecID/string"].value except MissingField: pass self.addGr... |
except MissingField: pass | def processAudio(self, track): audio = Metadata(self) try: self.trackCommon(track, audio) if "Audio" in track: audio.sample_rate = track["Audio/SamplingFrequency/float"].value audio.nb_channel = track["Audio/Channels/unsigned"].value audio.compression = track["CodecID/string"].value except MissingField: pass self.addGr... | |
self.trackCommon(track, sub) | def processSubtitle(self, track): sub = Metadata(self) try: self.trackCommon(track, sub) sub.compression = track["CodecID/string"].value except MissingField: pass self.addGroup("subtitle[]", sub, "Subtitle") | |
@fault_tolerant def readDuration(self, duration, timecode_scale): seconds = duration * timecode_scale self.duration = timedelta(seconds=seconds) | def processSimpleTag(self, tag): if "TagName/unicode" not in tag \ or "TagString/unicode" not in tag: return name = tag["TagName/unicode"].value if name not in self.tag_key: return key = self.tag_key[name] value = tag["TagString/unicode"].value setattr(self, key, value) | |
timecode_scale = info["TimecodeScale/unsigned"].value * 1e-9 if "Duration/float" in info: self.readDuration(info["Duration/float"].value, timecode_scale) elif "Duration/double" in info: self.readDuration(info["Duration/double"].value, timecode_scale) | duration = self.getDouble(info, "Duration") if duration is not None: try: seconds = duration * info["TimecodeScale/unsigned"].value * 1e-9 self.duration = timedelta(seconds=seconds) except OverflowError: pass | def processInfo(self, info): if "TimecodeScale/unsigned" in info: timecode_scale = info["TimecodeScale/unsigned"].value * 1e-9 if "Duration/float" in info: self.readDuration(info["Duration/float"].value, timecode_scale) elif "Duration/double" in info: self.readDuration(info["Duration/double"].value, timecode_scale) if ... |
"stbl": (AtomList, "stbl", ""), | "stbl": (AtomList, "stbl", "Sample Table"), "stco": (STCO, "stsd", "Sample Table Chunk Offset"), "stsd": (STSD, "stsd", "Sample Table Sample Description"), "stss": (STSS, "stss", "Sample Table Sync Samples"), "stsz": (STSZ, "stsz", "Sample Table Sizes"), | def createFields(self): yield UInt32(self, "unk") yield AtomList(self, "tags") |
"file_ext": ("mka", "mkv"), | "file_ext": ("mka", "mkv", "webm"), | def createFields(self): yield RawInt(self, 'id') yield Unsigned(self, 'size') for val in self.val[1:]: if callable(val): yield val(self) else: while not self.eof: yield EBML(self, val) |
return False return self.stream.searchBytes('\x42\x82\x88matroska', 5*8, first._size) is not None | return "First chunk size is invalid" if self[0]['DocType/string'].value not in ('matroska', 'webm'): return "Stream isn't a matroska document." return True | def validate(self): if self.stream.readBits(0, 32, self.endian) != self.EBML_SIGNATURE: return False try: first = self[0] except ParserError: return False if None < self._size < first._size: return False return self.stream.searchBytes('\x42\x82\x88matroska', 5*8, first._size) is not None |
if hdr['DocType/string'].value != 'matroska': raise ParserError("Stream isn't a matroska document.") | def createFields(self): hdr = EBML(self, ebml) yield hdr if hdr['DocType/string'].value != 'matroska': raise ParserError("Stream isn't a matroska document.") | |
yield UInt32(parent, "gamma", "Gamma (x10,000)") | yield UInt32(parent, "gamma", "Gamma (x100,000)") | def gammaParse(parent): yield UInt32(parent, "gamma", "Gamma (x10,000)") |
return float(parent["gamma"].value) / 10000 | return float(parent["gamma"].value) / 100000 | def gammaValue(parent): return float(parent["gamma"].value) / 10000 |
if index+3 < len(text) \ | elif index+3 < len(text) \ | def parseRange(text, start): r""" >>> parseRange('[a]b', 1) (<RegexRange '[a]'>, 3) >>> parseRange('[a-z]b', 1) (<RegexRange '[a-z]'>, 5) >>> parseRange('[^a-z-]b', 1) (<RegexRange '[^a-z-]'>, 7) >>> parseRange('[^]-]b', 1) (<RegexRange '[^]-]'>, 5) """ index = start char_range = [] exclude = False if text[index] == '^... |
if "Duration/float" in info \ and "TimecodeScale/unsigned" in info \ and 0 < info["Duration/float"].value: try: seconds = info["Duration/float"].value * info["TimecodeScale/unsigned"].value * 1e-9 self.duration = timedelta(seconds=seconds) except OverflowError: pass | if "TimecodeScale/unsigned" in info: timecode_scale = info["TimecodeScale/unsigned"].value * 1e-9 if "Duration/float" in info: self.readDuration(info["Duration/float"].value, timecode_scale) elif "Duration/double" in info: self.readDuration(info["Duration/double"].value, timecode_scale) | def processInfo(self, info): if "Duration/float" in info \ and "TimecodeScale/unsigned" in info \ and 0 < info["Duration/float"].value: try: seconds = info["Duration/float"].value * info["TimecodeScale/unsigned"].value * 1e-9 self.duration = timedelta(seconds=seconds) except OverflowError: # Catch OverflowError for tim... |
install_options["install_requires"] = "hachoir-core>=1.2.1" | install_options["install_requires"] = "hachoir-core>=1.3" | def main(): if "--setuptools" in argv: argv.remove("--setuptools") from setuptools import setup use_setuptools = True else: from distutils.core import setup use_setuptools = False hachoir_parser = load_source("version", path.join("hachoir_parser", "version.py")) PACKAGES = {"hachoir_parser": "hachoir_parser"} for nam... |
title=title, desc=desc, tags=tags, search_hidden=not visible, safety=safety, is_public=is_public, is_family=is_family, is_friend=is_friend, content_type=content_type) | title=title, desc=desc, tags=tags, search_hidden=not visible, safety=safety, is_public=is_public, is_family=is_family, is_friend=is_friend, content_type=content_type, progress_tracker=self.upload_progress_tracker) | def upload(self, response=None): """Upload worker function, called by the File->Upload callback. As this calls itself in the deferred callback, it takes a response argument.""" |
search_hidden=not visible, safety=safety, is_public=is_public, is_family=is_family, is_friend=is_friend, content_type=content_type) | search_hidden=not visible, safety=safety, is_public=is_public, is_family=is_family, is_friend=is_friend, content_type=content_type, progress_tracker=self.upload_progress_tracker) | def upload(self, response=None): """Upload worker function, called by the File->Upload callback. As this calls itself in the deferred callback, it takes a response argument.""" |
lock = "org.gtk.PyUnique.lock" | lock = "%s.lock" % name | def __init__(self, name, startup_id=None): gobject.GObject.__init__(self) self._is_running = False self._name = name self._screen = gdk.screen_get_default() |
self._check_for_errors(stderr) | def _download(self): self.log = '' self.information['status'] = DownloadStatus.RUNNING if self.information['download_type'] == DownloadTypes.TORRENT: # download torrent if necessary torrent_filename = os.path.join(self._config.get('general', 'folder_new_otrkeys'), self.filename + '.torrent') if not os.path.exists(tor... | |
This path is by default <mfm_lib_path>/../data/ in trunk and /usr/share/mfm in an installed version but this path | This path is by default <otrverwaltung_lib_path>/../data/ in trunk and /usr/share/otrverwaltung in an installed version but this path | def getdatapath(*args): """Retrieve otrverwaltung data path This path is by default <mfm_lib_path>/../data/ in trunk and /usr/share/mfm in an installed version but this path is specified at installation time. """ return os.path.join(os.path.dirname(__file__), data_dir, *args) |
self.combobox_archive.fill(archive_directory) self.combobox_archive.set_active(0) self.combobox_archive.connect('changed', self._on_combobox_archive_changed) | if action != Action.DECODE: self.combobox_archive.fill(archive_directory) self.combobox_archive.set_active(0) self.combobox_archive.connect('changed', self._on_combobox_archive_changed) | def _run(self, file_conclusions, action, rename_by_schema, archive_directory): self.action = action self.rename_by_schema = rename_by_schema self.__file_conclusions = file_conclusions self.forward_clicks = 0 self.show_all() self.combobox_archive.fill(archive_directory) self.combobox_archive.set_active(0) self.combobo... |
self.builder.get_object('button_play_cut').props.visible = cut_ok | self.builder.get_object('button_play_cut').props.visible = cut_ok self.builder.get_object('box_archive').props.visible = cut_ok | def show_conclusion(self, new_iter): self.conclusion_iter = new_iter self.file_conclusion = self.__file_conclusions[self.conclusion_iter] self.builder.get_object('label_count').set_text("Zeige Datei %s/%s" % (str(new_iter + 1), len(self.__file_conclusions))) |
url = "%sgetxml.php?ofsb=%s" % (server, str(size)) | urls = ["%sgetxml.php?ofsb=%s" % (server, str(size)), "%sgetxml.php?ofsb=%s" % (server, str((size+2*1024**3)%(4*1024**3)- 2*1024**3))] | def download_cutlists(filename, server, choose_cutlists_by, cutlist_mp4_as_hq, error_cb=None, cutlist_found_cb=None): """ Downloads all cutlists for the given file. filename - movie filename server - cutlist server choose_cutlists_by - 0 by size, 1 by name error_cb - callback: an err... |
url = "%sgetxml.php?name=%s" % (server, root) print url try: handle = urllib.urlopen(url) except IOError: if error_cb: error_cb("Verbindungsprobleme") return "Verbindungsprobleme", None | urls = ["%sgetxml.php?name=%s" % (server, root)] cutlists = [] for url in urls: print "[Cutlists] Download by : %s" % url try: handle = urllib.urlopen(url) except IOError: if error_cb: error_cb("Verbindungsprobleme") return "Verbindungsprobleme", None try: dom_cutlists = xml.dom.minidom.parse(handle) handle.close() ... | def download_cutlists(filename, server, choose_cutlists_by, cutlist_mp4_as_hq, error_cb=None, cutlist_found_cb=None): """ Downloads all cutlists for the given file. filename - movie filename server - cutlist server choose_cutlists_by - 0 by size, 1 by name error_cb - callback: an err... |
try: dom_cutlists = xml.dom.minidom.parse(handle) handle.close() dom_cutlists = dom_cutlists.getElementsByTagName('cutlist') except: if error_cb: error_cb("Keine Cutlists gefunden") return "Keine Cutlists gefunden", None cutlists = [] for cutlist in dom_cutlists: c = Cutlist() c.id = __read_v... | cutlists.append(c) | def download_cutlists(filename, server, choose_cutlists_by, cutlist_mp4_as_hq, error_cb=None, cutlist_found_cb=None): """ Downloads all cutlists for the given file. filename - movie filename server - cutlist server choose_cutlists_by - 0 by size, 1 by name error_cb - callback: an err... |
def foreach(model, path, iter, data=None): index = model.get_value(iter, 0) stamp = self.app.planned_broadcasts[index].datetime if stamp < now: selection.select_iter(iter) self.builder.get_object('treeview_planning').get_model().foreach(foreach) | for row in self.builder.get_object('treeview_planning').get_model(): if row[0].datetime < now: selection.select_iter(row.iter) | def foreach(model, path, iter, data=None): index = model.get_value(iter, 0) stamp = self.app.planned_broadcasts[index].datetime |
return "%s %s" % (self.user.username, self.group) | if self.user: username = self.user.username else: username = 'anonymous return "%s %s" % (username, self.group) | def __unicode__(self): return "%s %s" % (self.user.username, self.group) |
raise | if settings.DEBUG: raise l.warning("Can't find the GoalType named %s" % goal_name) | def record(cls, goal_name, experiment_user): try: return cls._record(goal_name, experiment_user) except GoalType.DoesNotExist: raise except Exception, e: l.error("Unexpected exception in GoalRecord.record:\n" "%s" % traceback.format_exc) |
goal_types = [GoalType.objects.create(name=i) for i in range(3)] | goal_types = [GoalType.objects.create(name=str(i)) for i in range(3)] | def testParticipantConversionCalculator(self): goal_types = [GoalType.objects.create(name=i) for i in range(3)] anonymous_visitor = AnonymousVisitor.objects.create() participant = self.create_participant( anonymous_visitor=anonymous_visitor, experiment=self.experiment, enrollment_date=self.experiment.start_date + timed... |
l.error("Unexpected exception in GoalRecord.record:\n" "%s" % traceback.format_exc) | l.exception("Unexpected exception in GoalRecord.record") | def record(cls, goal_name, experiment_user): try: return cls._record(goal_name, experiment_user) except GoalType.DoesNotExist: if settings.DEBUG: raise l.warning("Can't find the GoalType named %s" % goal_name) except Exception, e: l.error("Unexpected exception in GoalRecord.record:\n" "%s" % traceback.format_exc) |
scores a, and b. From Numerical Recipies, p.483. If printit=1, results are printed to the screen. If printit='filename', the results are output to 'filename' using the given writemode (default=append). Returns t-value, and prob. Originally written by Gary Strangman. Usage: lttest_ind(a,b,printit=0,name1='Samp1'... | scores a, and b. Returns t-value, and prob. Originally written by Gary Strangman. Usage: lttest_ind(a,b) | def ttest_ind(a, b): """ Calculates the t-obtained T-test on TWO INDEPENDENT samples of scores a, and b. From Numerical Recipies, p.483. If printit=1, results are printed to the screen. If printit='filename', the results are output to 'filename' using the given writemode (default=append). Returns t-value, and prob.... |
x1 = mean(a) x2 = mean(b) v1 = stdev(a)**2 v2 = stdev(b)**2 n1 = len(a) n2 = len(b) | x1, x2 = mean(a), mean(b) v1, v2 = stdev(a)**2, stdev(b)**2 n1, n2 = len(a), len(b) | def ttest_ind(a, b): """ Calculates the t-obtained T-test on TWO INDEPENDENT samples of scores a, and b. From Numerical Recipies, p.483. If printit=1, results are printed to the screen. If printit='filename', the results are output to 'filename' using the given writemode (default=append). Returns t-value, and prob.... |
svar = ((n1-1)*v1+(n2-1)*v2)/float(df) t = (x1-x2)/sqrt(svar*(1.0/n1 + 1.0/n2)) | try: svar = ((n1-1)*v1+(n2-1)*v2)/float(df) except ZeroDivisionError: return float('nan'), float('nan') try: t = (x1-x2)/sqrt(svar*(1.0/n1 + 1.0/n2)) except ZeroDivisionError: t = 1.0 | def ttest_ind(a, b): """ Calculates the t-obtained T-test on TWO INDEPENDENT samples of scores a, and b. From Numerical Recipies, p.483. If printit=1, results are printed to the screen. If printit='filename', the results are output to 'filename' using the given writemode (default=append). Returns t-value, and prob.... |
arg = len(names) | arg = len(proposals) | def code_assist(self, prefix): proposals = self._calculate_proposals() if prefix is not None: arg = self.env.prefix_value(prefix) if arg == 0: arg = len(names) common_start = self._calculate_prefix(proposals[:arg]) self.env.insert(common_start[self.offset - self.starting_offset:]) self._starting = common_start self._of... |
proposals = codeassist.sorted_proposals(proposals) | if self.env.get('sorted_completions', True): proposals = codeassist.sorted_proposals(proposals) | def _calculate_proposals(self): self.interface._check_project() resource = self.interface.resource maxfixes = self.env.get('codeassist_maxfixes') proposals = codeassist.code_assist( self.interface.project, self.source, self.offset, resource, maxfixes=maxfixes) proposals = codeassist.sorted_proposals(proposals) if self.... |
response = self.requestor.request('execute_cql_query', request_params) | try: response = self.requestor.request('execute_cql_query', request_params) except AvroRemoteException, are: raise CQLException(are) | def execute(self, query, compression=None): compress = compression is None and DEFAULT_COMPRESSION \ or compression.upper() if not compress in COMPRESSION_SCHEMES: raise InvalidCompressionScheme(compress) compressed_query = Connection.compress_query(query, compress) request_params = dict(query=compressed_query, compre... |
newSnpData = SNPData(col_id_ls=copy.deepcopy(snpData.col_id_ls), row_id_ls=[]) newSnpData.data_matrix = num.zeros([no_of_rows, no_of_cols], num.int8) | new_col_id_ls = copy.deepcopy(snpData.col_id_ls) new_row_id_ls = [] new_data_matrix = num.zeros([no_of_rows, no_of_cols], num.int8) | def keepRowsByRowID(cls, snpData, row_id_ls): """ 2009-05-19 keep certain rows in snpData given row_id_ls """ sys.stderr.write("Keeping rows given row_id_ls ...") no_of_rows = len(row_id_ls) row_id_wanted_set = set(row_id_ls) no_of_cols = len(snpData.col_id_ls) newSnpData = SNPData(col_id_ls=copy.deepcopy(snpData.col_... |
newSnpData.row_id_ls.append(row_id) newSnpData.data_matrix[row_index] = snpData.data_matrix[i] | new_row_id_ls.append(row_id) new_data_matrix[row_index] = snpData.data_matrix[i] | def keepRowsByRowID(cls, snpData, row_id_ls): """ 2009-05-19 keep certain rows in snpData given row_id_ls """ sys.stderr.write("Keeping rows given row_id_ls ...") no_of_rows = len(row_id_ls) row_id_wanted_set = set(row_id_ls) no_of_cols = len(snpData.col_id_ls) newSnpData = SNPData(col_id_ls=copy.deepcopy(snpData.col_... |
report=1, run_type=1): """ | cofactor_phenotype_id_ls=[], report=1, run_type=1,): """ 2010-1-11 add argument cofactor_phenotype_id_ls to have the functionality of treating some phenotypes as cofactors | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) | one phenotype at a time: 1. create a new SNP matrix which includes accessions whose phenotypes (this phenotype + cofactor_phenotype_id_ls) are non-NA 2. one SNP at a time 1. add cofactor SNP matrix if cofactors are present 2. add cofactor phenotype matrix if cofactor_phenotype_id_ls exist 3. run association parameter ... | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
chromosome, start_pos = start_snp.split('_')[:2] | start_chr, start_pos = start_snp.split('_')[:2] start_chr = int(start_chr) | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
stop_pos = int(stop_snp.split('_')[1]) | stop_chr, stop_pos = stop_snp.split('_')[:2] stop_chr = int(stop_chr) stop_pos = int(stop_pos) | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
if not numpy.isnan(phenotype_ls[i]): | this_row_has_NA_phenotype = False if cofactor_phenotype_index_ls: for phenotype_index in cofactor_phenotype_index_ls: if numpy.isnan(initData.phenData.data_matrix[i, phenotype_index]): this_row_has_NA_phenotype = True break if numpy.isnan(phenotype_ls[i]): this_row_has_NA_phenotype = True if not this_row_has_NA_phenot... | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
if chr==chromosome and pos>=start_pos and pos<=stop_pos: | if chr>=start_chr and chr<=stop_chr and pos>=start_pos and pos<=stop_pos: | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
phenotype_method_id_ls = [43] | phenotype_method_id_ls = [285] | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
GWA.cofactorLM(genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=cofactors) | cofactor_phenotype_id_ls = [77] GWA.cofactorLM(genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, \ cofactors=cofactors, cofactor_phenotype_id_ls=cofactor_phenotype_id_ls) | def cofactorLM(cls, genotype_fname, phenotype_fname, phenotype_method_id_ls, output_fname_prefix, start_snp, stop_snp, cofactors=[],\ report=1, run_type=1): """ 2009-8-26 run_type 1: pure linear model by python run_type 2: EMMA run_type 3: pure linear model by R (Field test shows run_type 3 is same as 1.) start_snp an... |
max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False): """ | max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False, \ min_reciprocal_overlap=0.6, report=True): """ 2010-1-26 value of the ecotype_id2cnv_qc_call_data dictionary is a RBDict (RBTree dictionary) structure. 2009-12-8 add argument min_reciprocal_overlap | def compareCNVSegmentsAgainstQCHandler(cls, input_fname_ls, ecotype_id2cnv_qc_call_data, function_handler, param_obj, \ deletion_cutoff=None, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False): """ 2009-11-4 a general handler to compare CNV segments from input_fnam... |
if boundary_diff1<=max_boundary_diff and boundary_diff2<=max_boundary_diff and diff1_perc<=max_diff_perc and \ diff2_perc<=max_diff_perc: | is_overlap = is_reciprocal_overlap([segment_start_pos, segment_stop_pos], [qc_start, qc_stop], \ min_reciprocal_overlap=min_reciprocal_overlap) if is_overlap: | def compareCNVSegmentsAgainstQCHandler(cls, input_fname_ls, ecotype_id2cnv_qc_call_data, function_handler, param_obj, \ deletion_cutoff=None, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False): """ 2009-11-4 a general handler to compare CNV segments from input_fnam... |
elif count_embedded_segment_as_match and segment_start_pos>=qc_start and segment_stop_pos<=qc_stop: no_of_valid_deletions += 1 valid_match = True | def compareCNVSegmentsAgainstQCHandler(cls, input_fname_ls, ecotype_id2cnv_qc_call_data, function_handler, param_obj, \ deletion_cutoff=None, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False): """ 2009-11-4 a general handler to compare CNV segments from input_fnam... | |
cnv_segment_obj = PassingData(ecotype_id=cnv_ecotype_id, start_probe=start_probe, stop_probe=stop_probe,\ no_of_probes=no_of_probes, amplitude=amplitude, segment_length=segment_length,\ segment_chromosome=segment_chromosome, ) function_handler(cnv_segment_obj, cnv_qc_call, param_obj) | function_handler(param_obj, cnv_segment_obj, cnv_qc_call, ) | def compareCNVSegmentsAgainstQCHandler(cls, input_fname_ls, ecotype_id2cnv_qc_call_data, function_handler, param_obj, \ deletion_cutoff=None, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False): """ 2009-11-4 a general handler to compare CNV segments from input_fnam... |
if counter%10000==0: | """ if report and counter%10000==0: | def compareCNVSegmentsAgainstQCHandler(cls, input_fname_ls, ecotype_id2cnv_qc_call_data, function_handler, param_obj, \ deletion_cutoff=None, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5, count_embedded_segment_as_match=False): """ 2009-11-4 a general handler to compare CNV segments from input_fnam... |
def getCNVQCDataFromDB(cls, data_source_id=1, ecotype_id=None, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=None): """ | def getCNVQCDataFromDB(cls, data_source_id=1, ecotype_id=None, cnv_type_id=None, \ min_QC_segment_size=None, min_no_of_probes=None, min_reciprocal_overlap=0.6): """ 2010-1-26 replace the list structure of cnv_qc_call_data in ecotype_id2cnv_qc_call_data with binary_tree structure 2009-12-9 add no_of_probes_covered into ... | def getCNVQCDataFromDB(cls, data_source_id=1, ecotype_id=None, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=None): """ 2009-11-4 get CNV QC data from database """ sys.stderr.write("Getting CNV QC data ... \n") import Stock_250kDB sql_string = "select a.ecotype_id, c.chromosome, c.start, c.stop, c.size_aff... |
sql_string = "select a.ecotype_id, c.chromosome, c.start, c.stop, c.size_affected, c.id from %s c,\ %s a where c.accession_id=a.id and a.data_source_id=%s and c.size_affected>=%s \ and c.cnv_type_id=%s"%\ (Stock_250kDB.CNVQCCalls.table.name, Stock_250kDB.CNVQCAccession.table.name, data_source_id,\ min_QC_segment_size, ... | sql_string = "select a.ecotype_id, c.chromosome, c.start, c.stop, c.size_affected, c.no_of_probes_covered, c.copy_number, c.id from %s c,\ %s a where c.accession_id=a.id and a.data_source_id=%s order by RAND()"%\ (Stock_250kDB.CNVQCCalls.table.name, Stock_250kDB.CNVQCAccession.table.name, data_source_id) if cnv_type_i... | def getCNVQCDataFromDB(cls, data_source_id=1, ecotype_id=None, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=None): """ 2009-11-4 get CNV QC data from database """ sys.stderr.write("Getting CNV QC data ... \n") import Stock_250kDB sql_string = "select a.ecotype_id, c.chromosome, c.start, c.stop, c.size_aff... |
ecotype_id2cnv_qc_call_data[row.ecotype_id] = [] cnv_qc_call_data = ecotype_id2cnv_qc_call_data[row.ecotype_id] cnv_qc_call_data.append((row.chromosome, row.start, row.stop, row.size_affected, row.id)) | ecotype_id2cnv_qc_call_data[row.ecotype_id] = RBDict() segmentKey = CNVSegmentBinarySearchTreeKey(chromosome=row.chromosome, span_ls=[row.start, row.stop], \ min_reciprocal_overlap=min_reciprocal_overlap) ecotype_id2cnv_qc_call_data[row.ecotype_id][segmentKey] = (row.chromosome, row.start, row.stop, row.size_affected,... | def getCNVQCDataFromDB(cls, data_source_id=1, ecotype_id=None, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=None): """ 2009-11-4 get CNV QC data from database """ sys.stderr.write("Getting CNV QC data ... \n") import Stock_250kDB sql_string = "select a.ecotype_id, c.chromosome, c.start, c.stop, c.size_aff... |
for ecotype_id, cnv_qc_call_data in ecotype_id2cnv_qc_call_data.iteritems(): cnv_qc_call_data.sort() ecotype_id2cnv_qc_call_data[ecotype_id] = cnv_qc_call_data sys.stderr.write("%s cnv qc calls for %s ecotypes. Done.\n"%(count, len(ecotype_id2cnv_qc_call_data))) | import math for ecotype_id, tree in ecotype_id2cnv_qc_call_data.iteritems(): print "\tDepth of Ecotype %s's tree: %d" % (ecotype_id, tree.depth()) print "\tOptimum Depth: %f (%d) (%f%% depth efficiency)" % (tree.optimumdepth(), math.ceil(tree.optimumdepth()), math.ceil(tree.optimumdepth()) / tree.depth()) sys.stderr... | def getCNVQCDataFromDB(cls, data_source_id=1, ecotype_id=None, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=None): """ 2009-11-4 get CNV QC data from database """ sys.stderr.write("Getting CNV QC data ... \n") import Stock_250kDB sql_string = "select a.ecotype_id, c.chromosome, c.start, c.stop, c.size_aff... |
def countMatchedDeletionsFunctor(cls, cnv_segment_obj, cnv_qc_call, param_obj): """ | def countMatchedDeletionsFunctor(cls, param_obj, cnv_segment_obj=None, cnv_qc_call=None): """ 2009-12-9 store qc data in param_obj.array_id2qc_data | def countMatchedDeletionsFunctor(cls, cnv_segment_obj, cnv_qc_call, param_obj): """ 2009-11-4 a functor to be called in """ if not hasattr(param_obj, 'no_of_valid_deletions'): setattr(param_obj, 'no_of_valid_deletions', 0) qc_chromosome, qc_start, qc_stop = cnv_qc_call[:3] cnv_qc_call_id = cnv_qc_call[-1] param_obj.cnv... |
qc_chromosome, qc_start, qc_stop = cnv_qc_call[:3] cnv_qc_call_id = cnv_qc_call[-1] param_obj.cnv_qc_call_id_set.add(cnv_qc_call_id) param_obj.no_of_valid_deletions += 1 | if not hasattr(param_obj, "array_id2qc_data"): param_obj.array_id2qc_data = {} if not hasattr(param_obj, "array_id2no_of_probes2qc_data"): param_obj.array_id2no_of_probes2qc_data = {} if not hasattr(param_obj, "array_id2qc_no_of_probes2qc_data"): param_obj.array_id2qc_no_of_probes2qc_data = {} array_id = cnv_segment_o... | def countMatchedDeletionsFunctor(cls, cnv_segment_obj, cnv_qc_call, param_obj): """ 2009-11-4 a functor to be called in """ if not hasattr(param_obj, 'no_of_valid_deletions'): setattr(param_obj, 'no_of_valid_deletions', 0) qc_chromosome, qc_start, qc_stop = cnv_qc_call[:3] cnv_qc_call_id = cnv_qc_call[-1] param_obj.cnv... |
no_of_QCCalls_matched = len(param_obj.cnv_qc_call_id_set) no_of_total_QCCalls = sum(map(len, param_obj.ecotype_id2cnv_qc_call_data.values())) false_negative_rate = (no_of_total_QCCalls-no_of_QCCalls_matched)/float(no_of_total_QCCalls) sys.stderr.write("False negative rate: %s/%s(%s).\n"%(no_of_total_QCCalls-no_of_QCCal... | for array_id, qc_data in param_obj.array_id2qc_data.iteritems(): no_of_QCCalls_matched = len(qc_data.cnv_qc_call_id_set) no_of_total_QCCalls = len(param_obj.ecotype_id2cnv_qc_call_data[qc_data.ecotype_id]) false_negative_rate = (no_of_total_QCCalls-no_of_QCCalls_matched)/float(no_of_total_QCCalls) sys.stderr.write("Arr... | def outputFalseNegativeRate(cls, param_obj): """ 2009-11-4 """ no_of_QCCalls_matched = len(param_obj.cnv_qc_call_id_set) no_of_total_QCCalls = sum(map(len, param_obj.ecotype_id2cnv_qc_call_data.values())) false_negative_rate = (no_of_total_QCCalls-no_of_QCCalls_matched)/float(no_of_total_QCCalls) sys.stderr.write("Fals... |
no_of_valid_deletions = param_obj.no_of_valid_deletions no_of_deletions = param_obj.no_of_deletions no_of_non_valid_deletions = no_of_deletions-no_of_valid_deletions false_positive_rate = no_of_non_valid_deletions/float(no_of_deletions) sys.stderr.write("False positive rate: %s/%s(%s).\n"%\ (no_of_non_valid_deletions, ... | for array_id, qc_data in param_obj.array_id2qc_data.iteritems(): no_of_valid_deletions = qc_data.no_of_valid_deletions no_of_deletions = qc_data.no_of_deletions no_of_non_valid_deletions = no_of_deletions-no_of_valid_deletions false_positive_rate = no_of_non_valid_deletions/float(no_of_deletions) sys.stderr.write("Arra... | def outputFalsePositiveRate(cls, param_obj): """ 2009-11-4 """ no_of_valid_deletions = param_obj.no_of_valid_deletions no_of_deletions = param_obj.no_of_deletions no_of_non_valid_deletions = no_of_deletions-no_of_valid_deletions false_positive_rate = no_of_non_valid_deletions/float(no_of_deletions) sys.stderr.write("Fa... |
count_embedded_segment_as_match=True): """ | count_embedded_segment_as_match=True, min_reciprocal_overlap=0.6): """ 2010-1-26 pass min_reciprocal_overlap to cls.getCNVQCDataFromDB() 2009-12-9 calculate FNR for each class with same number of probes | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
ecotype_id2cnv_qc_call_data = cls.getCNVQCDataFromDB(data_source_id, ecotype_id, cnv_type_id, min_QC_segment_size, min_no_of_probes) | ecotype_id2cnv_qc_call_data = cls.getCNVQCDataFromDB(data_source_id, ecotype_id, cnv_type_id, min_QC_segment_size, min_no_of_probes,\ min_reciprocal_overlap=min_reciprocal_overlap) | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
param_obj = PassingData(no_of_valid_deletions=0, cnv_qc_call_id_set=set()) | param_obj = PassingData(no_of_valid_deletions=0, cnv_qc_call_id_set=set(), array_id2qc_data={}) | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
count_embedded_segment_as_match=count_embedded_segment_as_match) sys.stderr.write("For ecotype_id %s, data_source_id %s, min_QC_segment_size %s, deletion_cutoff: %s, min_no_of_probes: %s, max_boundary_diff: %s, max_diff_perc %s.\n"%\ | count_embedded_segment_as_match=count_embedded_segment_as_match, \ min_reciprocal_overlap=min_reciprocal_overlap, report=False) sys.stderr.write("For ecotype_id %s, data_source_id %s, min_QC_segment_size %s, deletion_cutoff: %s, min_no_of_probes: %s, min_reciprocal_overlap: %s.\n"%\ | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
data_source_id, min_QC_segment_size, deletion_cutoff, min_no_of_probes, max_boundary_diff, max_diff_perc)) | data_source_id, min_QC_segment_size, deletion_cutoff, min_no_of_probes, min_reciprocal_overlap)) | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
for max_boundary_diff in [10000]: for max_diff_perc in [0.20, 0.3]: CNV.countNoOfCNVDeletionsMatchQC(db_250k, input_fname_ls, ecotype_id=ecotype_id, data_source_id=data_source_id, \ cnv_type_id=1,\ | for min_reciprocal_overlap in [0.4, 0.6, 0.8]: CNV.countNoOfCNVDeletionsMatchQC(db_250k, input_fname_ls, ecotype_id=ecotype_id, data_source_id=data_source_id, \ cnv_type_id=1,\ | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
max_boundary_diff=max_boundary_diff, max_diff_perc=max_diff_perc, \ | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... | |
count_embedded_segment_as_match=count_embedded_segment_as_match) """ @classmethod def addAmplitudeFunctor(cls, cnv_segment_obj, cnv_qc_call, param_obj): """ | count_embedded_segment_as_match=count_embedded_segment_as_match,\ min_reciprocal_overlap=min_reciprocal_overlap) input_fname_ls = [] for i in range(1,6): input_fname_ls.append(os.path.expanduser('~/mnt2/panfs/250k/CNV/call_method_48_CNV_intensity_QNorm_sub_ref_chr%s.GADA_A0.5T4M5.tsv'%i)) ecotype_id_data_source... | def countNoOfCNVDeletionsMatchQC(cls, db_250k, input_fname_ls, ecotype_id=6909, data_source_id=3, cnv_type_id=1, \ min_QC_segment_size=200, deletion_cutoff=-0.33, max_boundary_diff=10000, \ max_diff_perc=0.10, min_no_of_probes=5,\ count_embedded_segment_as_match=True): """ 2009-10-29 for all CNV deletions, check how ma... |
qc_chromosome, qc_start, qc_stop = cnv_qc_call[:3] cnv_qc_call_id = cnv_qc_call[-1] param_obj.cnv_qc_call_id_set.add(cnv_qc_call_id) param_obj.amp_ls.append(cnv_segment_obj.amplitude) | if cnv_qc_call is not None: qc_chromosome, qc_start, qc_stop = cnv_qc_call[:3] cnv_qc_call_id = cnv_qc_call[-1] param_obj.cnv_qc_call_id_set.add(cnv_qc_call_id) param_obj.amp_ls.append(cnv_segment_obj.amplitude) | def addAmplitudeFunctor(cls, cnv_segment_obj, cnv_qc_call, param_obj): """ 2009-11-4 """ if not hasattr(param_obj, 'amp_ls'): setattr(param_obj, 'amp_ls', []) qc_chromosome, qc_start, qc_stop = cnv_qc_call[:3] cnv_qc_call_id = cnv_qc_call[-1] param_obj.cnv_qc_call_id_set.add(cnv_qc_call_id) param_obj.amp_ls.append(cnv_... |
max_diff_perc=0.10, count_embedded_segment_as_match=True): | max_diff_perc=0.10, count_embedded_segment_as_match=True, min_reciprocal_overlap=0.6): | def drawHistOfAmpOfValidatedDeletions(cls, db_250k, input_fname_ls, output_fname_prefix, data_source_id=1, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=5, max_boundary_diff=10000, \ max_diff_perc=0.10, count_embedded_segment_as_match=True): """ 2009-11-4 draw histogram of amplitude of segments who are val... |
min_no_of_probes=min_no_of_probes) | min_no_of_probes=min_no_of_probes, \ min_reciprocal_overlap=min_reciprocal_overlap) | def drawHistOfAmpOfValidatedDeletions(cls, db_250k, input_fname_ls, output_fname_prefix, data_source_id=1, cnv_type_id=1, \ min_QC_segment_size=200, min_no_of_probes=5, max_boundary_diff=10000, \ max_diff_perc=0.10, count_embedded_segment_as_match=True): """ 2009-11-4 draw histogram of amplitude of segments who are val... |
overlap_length = max(0, stop-self.start) - max(0, stop-self.stop) - max(0, start-self.start) overlap_length = float(overlap_length) overlap1 = overlap_length/(stop-start) overlap2 = overlap_length/self.segment_length if overlap1>=self.min_reciprocal_overlap and overlap2>=self.min_reciprocal_overlap: | is_overlap = is_reciprocal_overlap([start, stop], [self.start, self.stop], \ min_reciprocal_overlap=self.min_reciprocal_overlap) if is_overlap: | def addNewCNV(self, chromosome, start, stop, array_id=None): """ """ if self.chromosome is None: self.addOneCNV(chromosome, start, stop, array_id) elif self.chromosome is not None and chromosome!=self.chromosome: return False else: """ boundary_diff1 = abs(start-self.start) boundary_diff2 = abs(stop-self.stop) diff1_pe... |
2 functions: 1. detect deletions. make sure the deletion is covered by the sequencing. | Two functions: 1. deletion_only=True. make sure the deletion is covered by the sequencing. | def discoverLerDeletionDuplication(cls, db_250k, ler_blast_result_fname, output_fname, deletion_only=True, min_no_of_matches=25): """ 2009-12-7 ler_blast_result_fname is the output of blasting all CNV probes against Ler contigs http://www.arabidopsis.org/browse/Cereon/index.jsp. 2 functions: 1. detect deletions. make s... |
2. detect copy number changes. If two adjacent probes have different number of contigs, then it's a copy number change point. | 2. deletion_only=False, detect copy number changes. If two adjacent probes have different number of contigs, then it's a copy number change point. | def discoverLerDeletionDuplication(cls, db_250k, ler_blast_result_fname, output_fname, deletion_only=True, min_no_of_matches=25): """ 2009-12-7 ler_blast_result_fname is the output of blasting all CNV probes against Ler contigs http://www.arabidopsis.org/browse/Cereon/index.jsp. 2 functions: 1. detect deletions. make s... |
session = db_250k.session | def discoverLerDeletionDuplication(cls, db_250k, ler_blast_result_fname, output_fname, deletion_only=True, min_no_of_matches=25): """ 2009-12-7 ler_blast_result_fname is the output of blasting all CNV probes against Ler contigs http://www.arabidopsis.org/browse/Cereon/index.jsp. 2 functions: 1. detect deletions. make s... | |
snpData = SNPData(input_fname=inputFname, turn_into_array=1) | row_id_key_set = set([row_id1, row_id2]) snpData = SNPData(input_fname=inputFname, turn_into_array=1, row_id_key_set=row_id_key_set) | def cmpOneRowToTheOther(cls, inputFname, row_id1, row_id2): """ 2009-6-17 compare SNP data of one accession to the other in the same dataset """ sys.stderr.write("Comparing one row to the other ... \n") from pymodule import SNPData, TwoSNPData, PassingData snpData = SNPData(input_fname=inputFname, turn_into_array=1) tw... |
inputFname = '/Network/Data/250k/db/dataset/call_method_29.tsv' row_id1 = ('6910', '62') row_id2 = ('8290', '181') AnalyzeSNPData.cmpOneRowToTheOther(inputFname, row_id1, row_id2) | inputFname = '/Network/Data/250k/db/dataset/call_method_29.tsv' row_id1 = ('6910', '62') row_id2 = ('8290', '181') AnalyzeSNPData.cmpOneRowToTheOther(inputFname, row_id1, row_id2) inputFname = os.path.expanduser('~/mnt2/panfs/NPUTE_data/input/250k_l3_y.85_20091208.tsv') row_id1 = ('7034', '1338') row_id2 = ('7035', '... | def cmpOneRowToTheOther(cls, inputFname, row_id1, row_id2): """ 2009-6-17 compare SNP data of one accession to the other in the same dataset """ sys.stderr.write("Comparing one row to the other ... \n") from pymodule import SNPData, TwoSNPData, PassingData snpData = SNPData(input_fname=inputFname, turn_into_array=1) tw... |
ler_blast_result_fname = '/Network/Data/250k/tmp-dazhe/tair9_raw.csv' output_fname = '/tmp/Col-copy-number.tsv' CNV.discoverLerDeletionDuplication(db_250k, ler_blast_result_fname, output_fname, deletion_only=False) """ cnv_intensity_fname = os.path.expanduser('~/mnt2/panfs/250k/CNV/call_method_48_CNV_intensity.tsv') a... | ler_blast_result_fname = '/Network/Data/250k/tmp-dazhe/ler_raw_CNV_QC.csv' max_delta_ratio = 0.4 max_length_delta = 10000 for max_length_delta in range(1,7): max_length_delta = max_length_delta*10000 output_fname = '/tmp/Ler-span-over-Col-mdr%s-mld%s.tsv'%(max_delta_ratio, max_length_delta) CNV.discoverLerContigSpanOve... | def linkEcotypeIDFromSuziPhenotype(cls, fname_with_ID, fname_with_phenotype, output_fname): """ 2009-7-31 she gave me two files one has phenotype data and accession names but with no ecotype ID 2nd is a map from accession name to ecotype ID """ sys.stderr.write("Linking accession names to ecotype ID ... ") import csv i... |
overlap1 = overlap_length/(qc_stop-qc_start) overlap2 = overlap_length/(segment_stop_pos-segment_start_pos) | overlap1 = overlap_length/(segment_stop_pos-segment_start_pos) overlap2 = overlap_length/(qc_stop-qc_start) | def get_overlap_ratio(span1_ls, span2_ls): """ 2009-12-13 calculate the two overlap ratios for two segments """ segment_start_pos, segment_stop_pos = span1_ls qc_start, qc_stop = span2_ls overlap_length = max(0, segment_stop_pos - qc_start) - max(0, segment_stop_pos - qc_stop) - max(0, segment_start_pos - qc_start) # a... |
a key designed to represent a CNV segment in a binary search tree (BinarySearchTree.py), which could be used to do == or >, or < operators | a key designed to represent a CNV segment in the node of a binary search tree (BinarySearchTree.py) or RBTree (RBTree.py), It has custom comparison function based on the is_reciprocal_overlap() function. | def is_reciprocal_overlap(span1_ls, span2_ls, min_reciprocal_overlap=0.6): """ 2009-12-12 return True if both overlap ratios are above the min_reciprocal_overlap """ overlap1, overlap2 = get_overlap_ratio(span1_ls, span2_ls) if overlap1>=min_reciprocal_overlap and overlap2>=min_reciprocal_overlap: return True else: ret... |
return self.span_ls[0]>=other.span_ls[0] and self.span_ls[1]<=other.span_ls[0] | return self.span_ls[0]<=other.span_ls[0] and self.span_ls[1]>=other.span_ls[0] | def __eq__(self, other): """ 2009-12-12 """ if self.chromosome==other.chromosome: if len(self.span_ls)==1: if len(other.span_ls)==1: return self.span_ls[0]==other.span_ls[0] elif len(other.span_ls)>1: return self.span_ls[0]>=other.span_ls[0] and self.span_ls[0]<=other.span_ls[1] # equal if self is within the "other" se... |
import os, sys | import os, sys, math | def getCNVDataFromFileInGWA(input_fname_ls, array_id, max_amp=-0.33, min_amp=-0.33, min_size=50, min_no_of_probes=None, report=False): """ 2009-10-31 get deletion (below max_amp) or duplication (above min_amp) from files (output by RunGADA.py) """ sys.stderr.write("Getting CNV calls for array %s, min_size %s, min_no_of... |
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