def init(_):
parser = argparse.ArgumentParser(description='Conversation Analyzer')
parser.add_argument('-p', metavar='conversationfilePath', dest='filepath')
parser.add_argument('-n',
metavar='numberOfMessages',
type=int,
dest='numMsgs',
default=0)
parser.add_argument('-l',
metavar='wordsCountLimit',
type=int,
dest='wCountLimit',
default=20)
args = parser.parse_args()
filepath = args.filepath
numMsgs = args.numMsgs
wCountLimit = args.wCountLimit
initLogger()
#conv = ConversationDataframe(mio.getResourcesPath() + "\\unittest\\test_plotting.txt")
conv = ConversationDataframe(filepath)
conv.loadMessages(numMsgs)
return
res = conv.messages.rename(columns={'text': 'numMsgs'})
res['lenMsgs'] = res['numMsgs'].apply(lambda x: len(x))
x = pd.to_numeric(res['hour'])
testCorrelation(x, res['lenMsgs'])
def main(_):
parser = argparse.ArgumentParser(description='Conversation Analyzer')
parser.add_argument('-p', metavar='conversationFilepath', dest='filepath', required=True)
parser.add_argument('-n', metavar='numberOfMessages', type=int, dest='numMsgs', default=0,
help='number of conversation messages to be analyzed')
baseFolderPath = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir))
parser.add_argument('--conf', metavar='configFilepath', dest='configFilepath', default= baseFolderPath+'\\config.ini')
args = parser.parse_args()
filepath = args.filepath
numMsgs = args.numMsgs
CONFIG_FILEPATH = args.configFilepath
STATS_SECTION = "Stats"
config = configparser.ConfigParser()
config.read(CONFIG_FILEPATH)
P_BASIC_LENGTH_STATS = config.getboolean(STATS_SECTION, "P_BASIC_LENGTH_STATS")
P_INTERVAL_STATS = config.getboolean(STATS_SECTION, "P_INTERVAL_STATS")
P_WORDS_COUNT = config.getboolean(STATS_SECTION, "P_WORDS_COUNT")
WORDS_COUNT_LIMIT = config.getint(STATS_SECTION, "WORDS_COUNT_LIMIT")
P_WORDS_USEDJUSTBY = config.getboolean(STATS_SECTION, "P_WORDS_USEDJUSTBY")
P_DELAY_STATS = config.getboolean(STATS_SECTION, "P_DELAY_STATS")
P_EMOTICONS_STATS = config.getboolean(STATS_SECTION, "P_EMOTICONS_STATS")
P_LEXICAL_STATS = config.getboolean(STATS_SECTION, "P_LEXICAL_STATS")
#conv = Conversation(filepath)
conv = ConversationDataframe(filepath)
conv.loadMessages(numMsgs)
if P_BASIC_LENGTH_STATS:
stats = conv.stats.generateStats(IConvStats.STATS_NAME_BASICLENGTH)
mio.printBasicLengthStats(stats)
if P_INTERVAL_STATS:
start, end, interval = conv.stats.getIntervalStats()
days = conv.stats.getDaysWithoutMessages()
mio.printIntervalStatsFor(start, end, interval, days)
if P_LEXICAL_STATS:
stats = conv.stats.generateStats(IConvStats.STATS_NAME_LEXICAL)
mio.printLexicalStats(stats)
if P_WORDS_COUNT:
filepath = conv.statsFolder + '\\' + 'wordCount.txt'
stats = conv.stats.generateStats(IConvStats.STATS_NAME_WORDCOUNT)
mio.printDataFrameToFile(stats, filepath)
#Works just with two senders
if P_WORDS_USEDJUSTBY:
mio.printWordsUsedJustByToFile(conv)
if P_EMOTICONS_STATS:
stats = conv.stats.generateStats(IConvStats.STATS_NAME_EMOTICONS)
mio.printEmoticonsStats(stats)
def getConversation(filepath):
conv = ConversationDataframe(filepath)
conv.loadMessages(0)
#anonymise conversation
if PlottingTestCase.anonymise:
sendersAliases = ['Donnie', 'Frank']
if len(sendersAliases) == len(conv.senders):
aliasesMap = {key:sendersAliases[i] for i, key in enumerate(conv.senders)}
conv.messages.replace({'sender':aliasesMap}, inplace=True)
conv.senders = sendersAliases
return conv
def getConversation(filepath):
conv = ConversationDataframe(filepath)
conv.loadMessages(0)
#anonymise conversation
if PlottingTestCase.anonymise:
sendersAliases = ['Donnie', 'Frank']
if len(sendersAliases) == len(conv.senders):
aliasesMap = {key:sendersAliases[i] for i, key in enumerate(conv.senders)}
conv.messages.replace({'sender':aliasesMap}, inplace=True)
conv.senders = sendersAliases
return conv
def init(_):
parser = argparse.ArgumentParser(description='Conversation Analyzer')
parser.add_argument('-p', metavar='conversationfilePath', dest='filepath')
parser.add_argument('-n', metavar='numberOfMessages', type=int,
dest='numMsgs', default=0)
parser.add_argument('-l', metavar='wordsCountLimit', type=int,
dest='wCountLimit', default=20)
args = parser.parse_args()
filepath = args.filepath
numMsgs = args.numMsgs
wCountLimit = args.wCountLimit
initLogger()
#conv = ConversationDataframe(mio.getResourcesPath() + "\\unittest\\test_plotting.txt")
conv = ConversationDataframe(filepath)
conv.loadMessages(numMsgs)
return
res = conv.messages.rename(columns={'text':'numMsgs'})
res['lenMsgs'] = res['numMsgs'].apply(lambda x: len(x))
x = pd.to_numeric(res['hour'])
testCorrelation(x, res['lenMsgs'])
def getConversation(self, filepath):
#conv = Conversation(filepath)
conv = ConversationDataframe(filepath)
conv.loadMessages(0)
return conv
def getConversation(self, filepath):
#conv = Conversation(filepath)
conv = ConversationDataframe(filepath)
conv.loadMessages(0)
return conv