def __init__(self, thisData, thisConfig, thisExpName, thisDebug=True): Format.__init__(self, thisDebug) self.data = thisData self.config = thisConfig self._printToFilename = thisExpName self.debug = thisDebug self.colorMap = plt.get_cmap(self.config.getMatrixColorMap()) self.SPECIAL_SCORE = 12345 self.plotType = 'matrix_plot' self.title = self.data.getTitle() self.event = None
def __init__(self, thisConfig, thisDebug=True): self.debug = thisDebug Format.__init__(self, self.debug) self._config = thisConfig # N must be bigger than 3 otherwise the matrix will be all white. self._N = 4 self._metaValues = ['condA', 'condB', 'condC', 'condD', 'condE', 'condF'] #self._metaValues = ['condA'] self.getMaximum4ThisType = self._config.getMaximum4Type3 self.getMinimum4ThisType = self._config.getMinimum4Type3 self._ma = self.getMinimum4ThisType() self._mi = self.getMaximum4ThisType() self._data = collections.defaultdict(list) self._title = 'dummy test title for matrix data'
def __init__(self, thisConfig, thisDebug=True): self.debug = thisDebug Format.__init__(self, self.debug) self._config = thisConfig # N must be bigger than 3 otherwise the matrix will be all white. self._N = 4 self._metaValues = [ 'condA', 'condB', 'condC', 'condD', 'condE', 'condF' ] #self._metaValues = ['condA'] self.getMaximum4ThisType = self._config.getMaximum4Type3 self.getMinimum4ThisType = self._config.getMinimum4Type3 self._ma = self.getMinimum4ThisType() self._mi = self.getMaximum4ThisType() self._data = collections.defaultdict(list) self._title = 'dummy test title for matrix data'
def __init__(self, thisPattern, thisAgmsv, thisAimsv, thisNumberOfTargets, thisNumberOfNonTargets, thisDebug=True): Format.__init__(self, thisDebug) self._pattern = thisPattern self._aimsv = thisAimsv self._agmsv = thisAgmsv self._numberOfTargets = thisNumberOfTargets self._numberOfNonTargets = thisNumberOfNonTargets self.debug = thisDebug self._agmStdDev = 0.0 self._aimStdDev = 0.0 self._agmNormStdDev = 0.0 self._aimNormStdDev = 0.0 self._singleTargetScore = False self._singleNonTargetScore = False # wasLimited can be used to display points that were limited in stdev in a # different way than other points. self._wasLimited = False
def __init__(self, thisData, thisConfig, thisExpName, thisType='normal', thisDebug=True, thisUseMeta=False): Format.__init__(self, thisDebug) self.data = thisData self.config = thisConfig self._printToFilename = thisExpName self.type = thisType self.debug = thisDebug self.title = self.data.getTitle() self.useMeta = thisUseMeta self.plotType = "histogram_plot" self.fig = None self.event = None self.colors = None self.nrColors = None
def __init__(self): Format.__init__(self, "[:;|]", 2, '''CREATE TABLE data (user text, password text)''', '''INSERT INTO data VALUES (?, ?)''')
def __init__(self, thisConfig, thisTitle, thisThreshold, thisDataType, maxNrTargetSamplesPerLabel, maxNrNonTargetSamplesPerLabel, thisDebug=True, thisSources='database'): Format.__init__(self, thisDebug) self.config = thisConfig self._title = thisTitle self._defaultThreshold = thisThreshold self._dataType = thisDataType # Annotate _doves, _phantoms, _worms and _chameleons self._maxNrTargetSamplesPerLabel = maxNrTargetSamplesPerLabel self._maxNrNonTargetSamplesPerLabel = maxNrNonTargetSamplesPerLabel self.debug = thisDebug self._sources = thisSources self._format = Format(self.debug) self._plotType = None # Target scores per label and meta value pattern. self._targetScores = collections.defaultdict(list) # Number of targets per label. self._targetCnt = collections.Counter() # Non target scores per label and meta value pattern. self._nonTargetScores = collections.defaultdict(list) # Number of non targets per label. self._nonTargetCnt = collections.Counter() # Target scores per label. self._targetScores4Label = collections.defaultdict(list) self._targetScores4MetaValue = collections.defaultdict(list) # Non target scores per label. self._nonTargetScores4Label = collections.defaultdict(list) self._nonTargetScores4MetaValue = collections.defaultdict(list) self._results = collections.defaultdict(list) # Count which labels + condition exceed the maxNrTargetSamplesPerLabel # and maxNrNonTargetSamplesPerLabel self._targetScoresInExcess = collections.Counter() self._nonTargetScoresInExcess = collections.Counter() self._nrDistinctMetaDataValues = 0 # Contains: { speakerId: metaDataValue } self._metaDataValues = collections.defaultdict(set) self._LabelsToShowAlways = [] self._minimumScore = collections.defaultdict(dict) self._maximumScore = collections.defaultdict(dict) # Keep track of labels. self._targetLabels = set() self._nonTargetLabels = set() # Do we allow both scores (A vs B and B vs A) in a symmetric tests or only the first read? self._allowDups = self.config.getAllowDups() if self.debug: print('Data._source(s):') for el in self._sources: print(el) # If the user did not specify a filename, we assume a database as the source. if self._sources == 'database': print("You need to add some code for this to work!") # And remove the sys.exit(1) statement. #res = self._readFromDatabase() sys.exit(1) else: res = self._readFromFiles(self._sources) # # Choose between decoder for type of results. # if self._dataType == 'type3': self._decodeType3Results(res) elif self._dataType == 'type2': print("Type2 data is not supported anymore. Convert it to type3!") sys.exit(1) elif self._dataType == 'type1': self._decodeType1Results(res) else: print("Unknown data type, must be 'type1' or 'type3'.") sys.exit(1)
def __init__(self, thisConfig, thisTitle, thisThreshold, thisDataType, thisDebug=True, thisSources='database'): Format.__init__(self, thisDebug) self.config = thisConfig self._title = thisTitle self._defaultThreshold = thisThreshold self._dataType = thisDataType # Annotate _doves, _phantoms, _worms and _chameleons self.debug = thisDebug self._sources = thisSources self._format = Format(self.debug) self._plotType = None # Target scores per label and meta value pattern. self._targetScores = collections.defaultdict(list) # Number of targets per label. self._targetCnt = collections.Counter() # Non target scores per label and meta value pattern. self._nonTargetScores = collections.defaultdict(list) # Number of non targets per label. self._nonTargetCnt = collections.Counter() # Target scores per label. self._targetScores4Label = collections.defaultdict(list) self._targetScores4MetaValue = collections.defaultdict(list) # Non target scores per label. self._nonTargetScores4Label = collections.defaultdict(list) self._nonTargetScores4MetaValue = collections.defaultdict(list) self._results = collections.defaultdict(list) self._results4Subject = collections.defaultdict(list) self._nrDistinctMetaDataValues = 0 # Contains: { speakerId: metaDataValue } self._metaDataValues = collections.defaultdict(set) self._LabelsToShowAlways = [] self._minimumScore = collections.defaultdict(dict) self._maximumScore = collections.defaultdict(dict) # Keep track of labels. self._targetLabels = set() self._nonTargetLabels = set() # Do we allow both scores (A vs B and B vs A) in a symmetric tests or only the first read? self._allowDups = self.config.getAllowDups() if self.debug: print('Data._source(s):') for el in self._sources: print(el) # If the user did not specify a filename, we assume a database as the source. if self._sources == 'database': print("You need to add some code for this to work!") # And remove the sys.exit(1) statement. sys.exit(1) res = self._readFromDatabase() else: res = self._readFromFiles(self._sources) # # Choose between decoder for type of results. # if self._dataType == 'type3': self._decodeType3Results(res) elif self._dataType == 'type2': print("Type2 data is not supported anymore. Convert it to type3!") sys.exit(1) elif self._dataType == 'type1': self._decodeType1Results(res) else: print("Unknown data type, must be 'type1' or 'type3'.") sys.exit(1)