def scatterplot(data, name="", xlabel="", ylabel="", size= 3):
"""
Creates a scatter plot from x,y data.
*data* is a list of (x,y) tuples.
"""
xAxis = NumberAxis(xlabel)
xAxis.setAutoRangeIncludesZero(False)
yAxis = NumberAxis(ylabel)
yAxis.setAutoRangeIncludesZero(False)
series = XYSeries("Values");
for (i,j) in data:
series.add(i, j)
dataset = XYSeriesCollection()
dataset.addSeries(series);
chart = ChartFactory.createScatterPlot(name, xlabel, ylabel, dataset,
PlotOrientation.VERTICAL, True, True, False)
plot = chart.getPlot()
plot.getRenderer().setSeriesShape(0,
ShapeUtilities.createRegularCross(size,size));
return Chart(chart)
def curve(data, name="", smooth=True, trid=True):
"""
Creates a curve based on a list of (x,y) tuples.
Setting *smooth* to ``True`` results in a spline renderer renderer is used.
Setting *trid* to ``True`` results in a 3D plot. In this case the ``smooth``
argument is ignored.
"""
dataset = XYSeriesCollection()
xy = XYSeries(name)
for d in data:
xy.add(d[0], d[1])
dataset.addSeries(xy)
chart = ChartFactory.createXYLineChart(None, None, None, dataset,
PlotOrientation.VERTICAL, True,
True, False)
if smooth:
chart.getXYPlot().setRenderer(XYSplineRenderer())
if trid:
chart.getXYPlot().setRenderer(XYLine3DRenderer())
return Chart(chart)
def scatterplot(data, name="", xlabel="", ylabel="", size= 3):
"""
Creates a scatter plot from x,y data.
*data* is a list of (x,y) tuples.
"""
xAxis = NumberAxis(xlabel)
xAxis.setAutoRangeIncludesZero(False)
yAxis = NumberAxis(ylabel)
yAxis.setAutoRangeIncludesZero(False)
series = XYSeries("Values");
for (i,j) in data:
series.add(i, j)
dataset = XYSeriesCollection()
dataset.addSeries(series);
chart = ChartFactory.createScatterPlot(name, xlabel, ylabel, dataset,
PlotOrientation.VERTICAL, True, True, False)
plot = chart.getPlot()
plot.getRenderer().setSeriesShape(0,
ShapeUtilities.createRegularCross(size,size));
return Chart(chart)
def resetData(self, justAnnots=False):
if not justAnnots:
self.markers = XYSeries("Markers")
self.drawCI = False
self.chart.getPlot().clearAnnotations()
if hasattr(self, 'pv'):
del (self.pv)
self.updateChartDataset()
def plot(title, x_label, y_label, *curves):
dataset = XYSeriesCollection()
for legend, curve in curves:
series = XYSeries(legend)
for x, y in curve:
series.add(x, y)
dataset.addSeries(series)
chart = ChartFactory.createXYLineChart(title, x_label, y_label, dataset,
PlotOrientation.VERTICAL, True,
True, False)
frame = ChartFrame(title, chart)
frame.setVisible(True)
frame.setSize(400, 300)
def xy(data, name='', xlabel='', ylabel=''):
"""
Creates a xy bar chart.
*data* is a list of (x,y) tuples
"""
series = XYSeries(name);
for x,y in data:
series.add(x,y)
dataset = XYSeriesCollection(series)
chart = ChartFactory.createXYBarChart(None, xlabel, False, ylabel, dataset,
PlotOrientation.VERTICAL, True, True, False)
return Chart(chart)
def resetData(self, justAnnots = False):
if not justAnnots:
self.markers = XYSeries("Markers")
self.drawCI = False
self.chart.getPlot().clearAnnotations()
if hasattr(self, 'pv'):
del(self.pv)
self.updateChartDataset()
def regression(data, regtype=0):
xAxis = NumberAxis("x")
xAxis.setAutoRangeIncludesZero(False)
yAxis = NumberAxis("y")
yAxis.setAutoRangeIncludesZero(False)
series = XYSeries("values");
xmax = xmin = None
for (x,y) in data:
series.add(x, y);
if xmax is None:
xmax = xmin = x
else:
xmax = max(xmax, x)
xmin = min(xmin, x)
dataset = XYSeriesCollection()
dataset.addSeries(series);
renderer1 = XYDotRenderer()
plot = XYPlot(dataset, xAxis, yAxis, renderer1)
if regtype == 1:
coefficients = Regression.getPowerRegression(dataset, 0)
curve = PowerFunction2D(coefficients[0], coefficients[1])
regdesc = "Power Regression"
else:
coefficients = Regression.getOLSRegression(dataset, 0)
curve = LineFunction2D(coefficients[0], coefficients[1])
regdesc = "Linear Regression"
regressionData = DatasetUtilities.sampleFunction2D(curve, xmin, xmax, 100,
"Fitted Regression Line")
plot.setDataset(1, regressionData)
renderer2 = XYLineAndShapeRenderer(True, False)
renderer2.setSeriesPaint(0, Color.blue)
plot.setRenderer(1, renderer2)
jfchart = JFreeChart(regdesc, JFreeChart.DEFAULT_TITLE_FONT, plot, True);
chart = Chart(jfchart)
chart.coeffs = coefficients
return chart
def regression(data, regtype=0):
xAxis = NumberAxis("x")
xAxis.setAutoRangeIncludesZero(False)
yAxis = NumberAxis("y")
yAxis.setAutoRangeIncludesZero(False)
series = XYSeries("values")
xmax = xmin = None
for (x, y) in data:
series.add(x, y)
if xmax is None:
xmax = xmin = x
else:
xmax = max(xmax, x)
xmin = min(xmin, x)
dataset = XYSeriesCollection()
dataset.addSeries(series)
renderer1 = XYDotRenderer()
plot = XYPlot(dataset, xAxis, yAxis, renderer1)
if regtype == 1:
coefficients = Regression.getPowerRegression(dataset, 0)
curve = PowerFunction2D(coefficients[0], coefficients[1])
regdesc = "Power Regression"
else:
coefficients = Regression.getOLSRegression(dataset, 0)
curve = LineFunction2D(coefficients[0], coefficients[1])
regdesc = "Linear Regression"
regressionData = DatasetUtilities.sampleFunction2D(
curve, xmin, xmax, 100, "Fitted Regression Line")
plot.setDataset(1, regressionData)
renderer2 = XYLineAndShapeRenderer(True, False)
renderer2.setSeriesPaint(0, Color.blue)
plot.setRenderer(1, renderer2)
jfchart = JFreeChart(regdesc, JFreeChart.DEFAULT_TITLE_FONT, plot, True)
chart = Chart(jfchart)
chart.coeffs = coefficients
return chart
def xy(data, name="", xlabel="", ylabel=""):
"""
Creates a xy bar chart.
*data* is a list of (x,y) tuples
"""
series = XYSeries(name)
for x, y in data:
series.add(x, y)
dataset = XYSeriesCollection(series)
if len(data) > 1:
# hack to set interval width
x0, x1 = data[0][0], data[1][0]
dataset.setIntervalWidth(x1 - x0)
chart = ChartFactory.createXYBarChart(
None, xlabel, False, ylabel, dataset, PlotOrientation.VERTICAL, True, True, False
)
return Chart(chart)
def xy(data, name='', xlabel='', ylabel=''):
"""
Creates a xy bar chart.
*data* is a list of (x,y) tuples
"""
series = XYSeries(name)
for x, y in data:
series.add(x, y)
dataset = XYSeriesCollection(series)
if len(data) > 1:
# hack to set interval width
x0, x1 = data[0][0], data[1][0]
dataset.setIntervalWidth(x1 - x0)
chart = ChartFactory.createXYBarChart(None, xlabel, False, ylabel, dataset,
PlotOrientation.VERTICAL, True, True,
False)
return Chart(chart)
def addSeries(self, series, label=None):
if not label:
label = "series #" + str(len(self.allSeries) + 1)
xySeries = XYSeries(label)
iterator = iter(series)
t = iterator.next()
if isinstance(t, tuple):
if len(t) >= 3:
raise "Series can have at most two columns"
xySeries.add(t[0], t[1])
for t in iterator:
xySeries.add(t[0], t[1])
else:
xySeries.add(0, t)
for i, t in enumerate(iterator):
xySeries.add(i, t)
self.allSeries.append(xySeries)
def setMarkers(self, markers):
self.markers = XYSeries("Markers")
self.maxX = 0.0
self.maxY = 0.0
self.minY = -0.05
self.out = []
self.valMarkers = markers
for marker in markers:
if not marker:
continue
if marker[0] < 2 and marker[0] > self.maxX:
self.maxX = marker[0]
if marker[1] < 2 and marker[1] > self.maxY:
self.maxY = marker[1]
if marker[1] > -2 and marker[1] < self.minY:
self.minY = marker[1]
#self.markers.add(marker[0], max([0.0, marker[1]]))
self.markers.add(marker[0], marker[1])
self.maxX = max([0.501, self.maxX + 0.001])
self.maxX = min([1, self.maxX])
self.maxY += 0.05
self.minY -= 0.05
def curve(data, name="", smooth=True, trid=True):
"""
Creates a curve based on a list of (x,y) tuples.
Setting *smooth* to ``True`` results in a spline renderer renderer is used.
Setting *trid* to ``True`` results in a 3D plot. In this case the ``smooth``
argument is ignored.
"""
dataset = XYSeriesCollection()
xy = XYSeries(name);
for d in data:
xy.add(d[0], d[1])
dataset.addSeries(xy);
chart = ChartFactory.createXYLineChart(None, None, None, dataset,
PlotOrientation.VERTICAL, True, True, False)
if smooth:
chart.getXYPlot().setRenderer(XYSplineRenderer())
if trid:
chart.getXYPlot().setRenderer(XYLine3DRenderer())
return Chart(chart)
def addSeries(self, series, label=None):
if not label:
label = "series #"+str(len(self.allSeries)+1)
xySeries = XYSeries(label)
iterator = iter(series)
t = iterator.next()
if isinstance(t, tuple):
if len(t) >= 3:
raise "Series can have at most two columns"
xySeries.add(t[0], t[1])
for t in iterator:
xySeries.add(t[0], t[1])
else:
xySeries.add(0, t)
for i, t in enumerate(iterator):
xySeries.add(i, t)
self.allSeries.append(xySeries)
def setMarkers(self, markers):
self.markers = XYSeries("Markers")
self.maxX = 0.0
self.maxY = 0.0
self.minY = -0.05
self.out = []
self.valMarkers = markers
for marker in markers:
if not marker:
continue
if marker[0]<2 and marker[0] > self.maxX:
self.maxX = marker[0]
if marker[1]<2 and marker[1] > self.maxY:
self.maxY = marker[1]
if marker[1]>-2 and marker[1] < self.minY:
self.minY = marker[1]
#self.markers.add(marker[0], max([0.0, marker[1]]))
self.markers.add(marker[0], marker[1])
self.maxX += 0.1
self.maxX = min([1, self.maxX])
self.maxY += 0.05
self.minY -= 0.05
def plot2D(points, Ca, Cb): maxIntensity = 255.0 dataset = XYSeriesCollection() seriesNN = XYSeries(channels[Ca+1]+" -ve "+channels[Cb+1]+" -ve") seriesPP = XYSeries(channels[Ca+1]+" +ve "+channels[Cb+1]+" +ve") seriesNP = XYSeries(channels[Ca+1]+" -ve "+channels[Cb+1]+" +ve") seriesPN = XYSeries(channels[Ca+1]+" +ve "+channels[Cb+1]+" -ve") for p in points: posA = channels[Ca+1] in thresholds and p[Ca]>thresholds[ channels[Ca+1] ] posB = channels[Cb+1] in thresholds and p[Cb]>thresholds[ channels[Cb+1] ] if posA and posB: seriesPP.add(p[Cb], p[Ca]) elif posA: seriesPN.add(p[Cb], p[Ca]) elif posB: seriesNP.add(p[Cb], p[Ca]) else: seriesNN.add(p[Cb], p[Ca]) dataset.addSeries(seriesNN) dataset.addSeries(seriesPN) dataset.addSeries(seriesNP) dataset.addSeries(seriesPP) chart = ChartFactory.createScatterPlot( title+" - "+channels[Cb+1]+" vs "+channels[Ca+1], channels[Cb+1], channels[Ca+1], dataset, PlotOrientation.VERTICAL, False,True,False ) plot = chart.getPlot() plot.getDomainAxis().setRange(Range(0.00, maxIntensity), True, False) plot.getRangeAxis().setRange(Range(0.00, maxIntensity), True, False) renderer = chart.getPlot().getRenderer() renderer.setSeriesPaint(0, Color(64,64,64)) #NN renderer.setSeriesPaint(1, Color(0,255,0)) #PN renderer.setSeriesPaint(2, Color(0,0,255)) #NP renderer.setSeriesPaint(3, Color(0,255,255)) #PP shape = Ellipse2D.Float(-1,-1,3,3) renderer.setSeriesShape(0, shape ) renderer.setSeriesShape(1, shape ) renderer.setSeriesShape(2, shape ) renderer.setSeriesShape(3, shape ) frame = ChartFrame(title+" - "+channels[Cb+1]+" vs "+channels[Ca+1], chart) frame.setSize(800, 800) frame.setLocationRelativeTo(None) frame.setVisible(True)
def getDataSets(self, txName):
"""
For a given txNum name, return a set of JFreeChart datasets
with data on tx/sec, response times, and bandwidth.
"""
logger.debug("getting data sets for " + txName)
if self._txNameDatasets == None:
logger.warn("Building data sets.")
txSecDataset = None
# build 'em
self._txNameDatasets = {}
txNums = self._summaryData.getTxNumNameMap().keys()
for txNum in txNums:
logger.debug("DEBUG: building DS for " + txNum)
dataSetGroup = {}
txSecDataset = XYSeriesCollection() # not returning a new object
bandwidthDataSet = XYSeriesCollection()
simpleResponseTimeDataset = XYSeriesCollection()
httpResponseTimeDataset = DefaultTableXYDataset()
meanMaxResponseTimeDataset = XYSeriesCollection()
txSecPassSeries = XYSeries("tx/sec passed")
txSecFailSeries = XYSeries("tx/sec failed")
meanResponseTimeSeries = XYSeries("mean response time", True, False)
maxResponseTimeSeries = XYSeries("max response time", True, False)
finishTimeSeries = XYSeries("complete", True, False)
resolveHostSeries = XYSeries("resolveHost", True, False)
connectSeries = XYSeries("connect", True, False)
firstByteSeries = XYSeries("firstByte", True, False)
bandwidthSeries = XYSeries("KB/sec")
for bucket in self.bucketList:
txSecPass = bucket.getTxSecPass(txNum)
txSecPassSeries.add(bucket.getStartTime() / 1000.0, txSecPass)
txSecFail = bucket.getTxSecFail(txNum)
txSecFailSeries.add(bucket.getStartTime() / 1000.0, txSecFail)
meanResponseTimeSeries.add(bucket.getStartTime() / 1000.0, bucket.getMeanResponseTime(txNum))
maxResponseTimeSeries.add(bucket.getStartTime() / 1000.0, bucket.getMaxResponseTime(txNum))
if ga.constants.VORPAL.getPlugin("analyzer").isHTTP():
bandwidthSeries.add(bucket.getStartTime() / 1000.0, bucket.getMeanThroughputKBSec(txNum))
finishTimeSeries.add(bucket.getStartTime() / 1000.0, bucket.getMeanFinishTime(txNum))
resolveHostSeries.add(bucket.getStartTime() / 1000.0, bucket.getMeanResolveHostTime(txNum))
connectSeries.add(bucket.getStartTime() / 1000.0, bucket.getMeanConnectTime(txNum))
firstByteSeries.add(bucket.getStartTime() / 1000.0, bucket.getMeanFirstByteTime(txNum))
txSecDataset.addSeries(txSecPassSeries)
txSecDataset.addSeries(txSecFailSeries)
httpResponseTimeDataset.addSeries(resolveHostSeries)
httpResponseTimeDataset.addSeries(connectSeries)
httpResponseTimeDataset.addSeries(firstByteSeries)
httpResponseTimeDataset.addSeries(finishTimeSeries)
simpleResponseTimeDataset.addSeries(meanResponseTimeSeries)
meanMaxResponseTimeDataset.addSeries(meanResponseTimeSeries)
meanMaxResponseTimeDataset.addSeries(maxResponseTimeSeries)
bandwidthDataSet.addSeries(bandwidthSeries)
dataSetGroup[TX_SEC_KEY] = txSecDataset
dataSetGroup[HTTP_RESPONSE_TIME_KEY] = httpResponseTimeDataset
dataSetGroup[THROUGHPUT_KEY] = bandwidthDataSet
dataSetGroup[SIMPLE_RESPONSE_TIME_KEY] = simpleResponseTimeDataset
dataSetGroup[RESPONSE_TIME_MEAN_MAX_KEY] = meanMaxResponseTimeDataset
self._txNameDatasets[txNum] = dataSetGroup
logger.debug("DEBUG: done building data sets.")
return self._txNameDatasets[txName]
def scatter(data,x=None,y=None,**kwargs):
''' Creates a scatter plot comparing two elements. At minimum, takes a collection of data.
The second and third arguments, if they exist, are treated as the two elements to
compare. If these arguments do not exist, the first two elements in the list are
compared. If an optional regress=True argument is present, superimposes a linear
regression for each series and prints some related info (R-value etc).
Note that scatter plots can be zoomed with the mouse. Returns the plot object in
case you want to customize the graph in some way. Takes an optional showMissing argument
which determines whether missing values (-9999.0) should be displayed.
Examples: scatter(data), scatter(data,"tmin","tmax",regress=True)
'''
from org.jfree.data.xy import XYSeriesCollection,XYSeries
from org.jfree.data import UnknownKeyException
from org.jfree.chart import ChartFactory,ChartFrame
from org.jfree.chart.plot import PlotOrientation,DatasetRenderingOrder
from org.jfree.chart.renderer.xy import XYLineAndShapeRenderer
from java.awt import Color
regress=kwargs.get('regress',False)
showMissing=kwargs.get('showMissing',False)
# Try to be flexible about element parameters
if x is not None: x = findElement(x).name
if y is not None: y = findElement(y).name
# Create a dataset from the data
collection = XYSeriesCollection()
for ob in data.groupedByObservation().items():
key,values = ob
name = str(key[0])
if x==None:
x = values[0].element.name
try:
xFact = (i for i in values if i.element.name == x).next()
except StopIteration: # missing value
continue
xval = xFact.value
if xval in missingValues and not showMissing: continue
if y==None:
try:
y = values[1].element.name
except IndexError:
raise Exception("Error! Your data request returned only 1 value per observation. "
"Must have 2 values to generate a scatter plot.")
try:
yFact = (i for i in values if i.element.name == y).next()
except StopIteration: # missing value
continue
yval = yFact.value
if yval in missingValues and not showMissing: continue
try:
series = collection.getSeries(name)
except UnknownKeyException:
collection.addSeries(XYSeries(name))
series = collection.getSeries(name)
series.add(float(xval),float(yval))
# Create chart from dataset
chart = ChartFactory.createScatterPlot( "", x, y, collection, PlotOrientation.VERTICAL,
True, True, False );
plot = chart.getPlot()
frame = ChartFrame("Scatter Plot", chart);
frame.pack();
frame.setVisible(True);
# Superimpose regression if desired
if regress:
regressioncollection = XYSeriesCollection()
for series in collection.getSeries():
regression = _getregression(series)
x1 = series.getMinX()
y1 = regression.predict(x1)
x2 = series.getMaxX()
y2 = regression.predict(x2)
regressionseries = XYSeries(series.getKey())
regressionseries.add(float(x1),float(y1))
regressionseries.add(float(x2),float(y2))
regressioncollection.addSeries(regressionseries)
print series.getKey(),":"
print " R: %8.4f" % regression.getR()
print " R-squared: %8.4f" % regression.getRSquare()
print " Significance: %8.4f" % regression.getSignificance()
print
plot.setDataset(1,regressioncollection)
regressionRenderer = XYLineAndShapeRenderer(True,False)
plot.setRenderer(1,regressionRenderer)
plot.setDatasetRenderingOrder(DatasetRenderingOrder.FORWARD);
colors = [0xec0000,0x58b911,0x6886ea,0xedd612,0xa93bb9,0xffb71b,0xe200df,0x1de2b6,0xdc91db,0x383838,0xb09344,0x4ea958,0xd78c9e,0x64008d,0xb0c95b]
mainRenderer = plot.getRenderer(0)
for i in range(collection.getSeriesCount()):
try:
mainRenderer.setSeriesPaint(i,Color(colors[i]))
regressionRenderer.setSeriesPaint(i,Color(colors[i]))
except IndexError: # Finite # of colors in the color array; beyond that let jfreechart pick
break
'''
# Jump through some hoops to ensure regressions are same color as scatters for each series.
# Initially: doesn't work because series are not indexed the same. And I don't see a way
# to get the actual series from the renderer in order to compare names or something.
mainRenderer = plot.getRenderer(0)
print "Renderer is",type(mainRenderer)
index = 0
paint = mainRenderer.lookupSeriesPaint(index)
print "Paint is",type(paint)
while (paint is not None):
print "Setting paint."
regressionRenderer.setSeriesPaint(index,paint)
index += 1
paint = mainRenderer.getSeriesPaint(index)
'''
return plot
class Chart(JPanel):
def _createEmptyChart(self, dataset=None):
if self.isTemporal:
hText = "Hs"
fText = "Fgt"
else:
hText = "He"
fText = "Fst"
chart = ChartFactory.createXYLineChart(
self.title, # chart title
hText, # x axis label
fText, # y axis label
dataset, # data
PlotOrientation.VERTICAL,
True, # include legend
True, # tooltips
False # urls
)
chart.setBackgroundPaint(Color.white)
# get a reference to the plot for further customisation...
# change the auto tick unit selection to integer units only...
#rangeAxis = plot.getRangeAxis()
#rangeAxis.setStandardTickUnits(NumberAxis.createIntegerTickUnits())
self.confArea = None
return chart
def setSelLoci(self, pv, allLoci, selLoci):
self.pv = pv
self.allLoci = allLoci
self.selLoci = selLoci
self.drawLabels()
def drawLabels(self):
if not hasattr(self, 'pv'): return
plot = self.chart.getPlot()
plot.clearAnnotations()
red = 0
for i in range(len(self.valMarkers)):
if not self.valMarkers[i]:
red += 1
continue
if self.allLoci[i] in self.selLoci:
if not self.labelSelected: continue
else:
if not self.labelNeutral: continue
x = self.pv[i - red][0]
y = self.pv[i - red][1]
locus = self.allLoci[i]
note = XYTextAnnotation(locus, x + 0.002, y + 0.002)
note.setTextAnchor(TextAnchor.BOTTOM_LEFT)
plot.addAnnotation(note)
def setMarkers(self, markers):
self.markers = XYSeries("Markers")
self.maxX = 0.0
self.maxY = 0.0
self.minY = -0.05
self.out = []
self.valMarkers = markers
for marker in markers:
if not marker:
continue
if marker[0] < 2 and marker[0] > self.maxX:
self.maxX = marker[0]
if marker[1] < 2 and marker[1] > self.maxY:
self.maxY = marker[1]
if marker[1] > -2 and marker[1] < self.minY:
self.minY = marker[1]
#self.markers.add(marker[0], max([0.0, marker[1]]))
self.markers.add(marker[0], marker[1])
self.maxX = max([0.501, self.maxX + 0.001])
self.maxX = min([1, self.maxX])
self.maxY += 0.05
self.minY -= 0.05
def setTop(self, markers):
#setBottom has to be done before, as setMarkers
self.top = YIntervalSeries("Candidate neutral")
self.limit = YIntervalSeries("Candidate positive selection")
if len(markers) > 1:
#if self.maxY > markers[0][1]:
# self.limit.add(0.0, markers[0][1], markers[0][0], markers[0][1])
#else: #It does not really matter
# self.limit.add(0.0, -1, 1.1, 1.1)
self.limit.add(0.0, markers[0][1], markers[0][1], 1.1)
for i in range(len(markers)):
self.top.add(markers[i][0], self.bottomList[i][1],
self.bottomList[i][1], markers[i][1])
if self.maxY > markers[i][1]:
self.limit.add(markers[i][0], markers[i][1], markers[i][1],
1.1)
else: #It does not really matter
self.limit.add(markers[i][0], markers[i][1], markers[i][1],
1.1)
#if markers[i][0] > self.maxX: break
#We do this at the end to fill the whole graphic
def setBottom(self, markers):
#print markers
self.bottomList = map(lambda (x, y): (x, y),
markers) #legacy, can remove...
self.bottom = YIntervalSeries("Candidate balancing selection")
if len(markers) > 0:
self.bottom.add(0.0, -1.0, -1.0, self.bottomList[0][1])
for marker in self.bottomList:
self.bottom.add(marker[0], -1.0, -1.0, marker[1])
#if marker[0] > self.maxX: break
#We do this at the end to fill the whole graphic
def updateChartDataset(self, drawLabels=True):
dataset = XYSeriesCollection()
#self._calculateConfArea()
#dataset.addSeries(self.confArea)
dataset.addSeries(self.markers)
plot = self.chart.getPlot()
rangeAxis = plot.getRangeAxis()
domainAxis = plot.getDomainAxis()
rangeAxis.setRange(self.minY, self.maxY) #change
domainAxis.setRange(self.minX, self.maxX)
#plot.setBackgroundPaint(Color.lightGray);
#plot.setAxisOffset(new RectangleInsets(5.0, 5.0, 5.0, 5.0));
#plot.setDomainGridlinePaint(Color.white);
#plot.setRangeGridlinePaint(Color.white);
markerRenderer = XYLineAndShapeRenderer(False, True)
#print self.markerColor
markerRenderer.setSeriesPaint(0, self.markerColor)
markerRenderer.setSeriesShape(0, Ellipse2D.Double(-3, -3, 6, 6))
#markerRenderer.setToolTipGenerator(FDistToolTipGenerator(self.pointNames))
plot.setRenderer(0, markerRenderer)
plot.setDataset(0, dataset)
dataset = XYSeriesCollection()
if self.drawCI:
dataset = YIntervalSeriesCollection()
CIRenderer = DeviationRenderer(True, False)
# CIRenderer.setOutline(True)
# CIRenderer.setRoundXCoordinates(True)
dataset.addSeries(self.bottom)
dataset.addSeries(self.top)
dataset.addSeries(self.limit)
CIRenderer.setSeriesFillPaint(0, self.balColor)
CIRenderer.setSeriesFillPaint(1, self.neuColor)
CIRenderer.setSeriesFillPaint(2, self.posColor)
CIRenderer.setSeriesPaint(0, self.balColor)
CIRenderer.setSeriesPaint(1, self.neuColor)
CIRenderer.setSeriesPaint(2, self.posColor)
plot.setDataset(1, dataset)
plot.setRenderer(1, CIRenderer)
plot.setDataset(1, dataset)
if drawLabels:
self.drawLabels()
def resetData(self, justAnnots=False):
if not justAnnots:
self.markers = XYSeries("Markers")
self.drawCI = False
self.chart.getPlot().clearAnnotations()
if hasattr(self, 'pv'):
del (self.pv)
self.updateChartDataset()
def save(self, parent, format):
chooser = JFileChooser()
# filter = FileNameExtensionFilter(
# format + " files",
# array([format, format.lower()], String))
# chooser.setFileFilter(filter);
returnVal = chooser.showSaveDialog(parent)
if returnVal == JFileChooser.APPROVE_OPTION:
fileName = chooser.getSelectedFile().getPath()
if not fileName.upper().endswith('.' + format):
fileName += '.' + format.lower()
file = File(fileName)
else:
return
if format == 'PNG':
ChartUtils.saveChartAsPNG(file, self.chart, self.exportX,
self.exportY)
elif format == 'SVG':
domImpl = GenericDOMImplementation.getDOMImplementation()
doc = domImpl.createDocument(None, "svg", None)
svgGen = SVGGraphics2D(doc)
svgGen.getGeneratorContext().setPrecision(6)
self.chart.draw(
svgGen, Rectangle2D.Double(0, 0, self.exportX, self.exportY),
None)
out = OutputStreamWriter(FileOutputStream(file), "UTF-8")
svgGen.stream(out, True) #True is for useCSS
out.close()
elif format == 'PDF':
mapper = DefaultFontMapper()
pageSize = Rectangle(self.exportX, self.exportY)
doc = TextDocument(pageSize, 50, 50, 50, 50)
out = BufferedOutputStream(FileOutputStream(file))
writer = PdfWriter.getInstance(doc, out)
doc.open()
cb = writer.getDirectContent()
tp = cb.createTemplate(self.exportX, self.exportY)
g2 = tp.createGraphics(self.exportX, self.exportY, mapper)
r2D = Rectangle2D.Double(0, 0, self.exportX, self.exportY)
self.chart.draw(g2, r2D)
g2.dispose()
cb.addTemplate(tp, 0, 0)
doc.close()
#out.close()
def __init__(self, width, height, isTemporal=False):
JPanel()
self.isTemporal = isTemporal
self.minY = 0.0 # -0.05
self.minX = 0.0 # -0.02
self.maxX = 0.5 # 0.52
self.maxY = 1.0
self.drawCI = False
if isTemporal:
self.title = "Fgt/Hs"
else:
self.title = "Fst/He"
self.labelSelected = True
self.labelNeutral = False
self.posColor = Color.RED
self.neuColor = Color.LIGHT_GRAY
self.balColor = Color.YELLOW
self.markerColor = Color.BLUE
self.exportX = width
self.exportY = height
self.chart = self._createEmptyChart()
self.chart.setAntiAlias(True)
self.resetData()
self.cp = ChartPanel(self.chart)
self.cp.setDisplayToolTips(True)
self.cp.setPreferredSize(Dimension(width, height))
self.add(self.cp)
def getDataSets(self, txName):
'''
For a given txNum name, return a set of JFreeChart datasets
with data on tx/sec, response times, and bandwidth.
'''
logger.debug("getting data sets for " + txName)
if self._txNameDatasets == None:
logger.warn("Building data sets.")
txSecDataset = None
# build 'em
self._txNameDatasets = {}
txNums = self._summaryData.getTxNumNameMap().keys()
for txNum in txNums:
logger.debug("DEBUG: building DS for " + txNum)
dataSetGroup = {}
txSecDataset = XYSeriesCollection(
) # not returning a new object
bandwidthDataSet = XYSeriesCollection()
simpleResponseTimeDataset = XYSeriesCollection()
responseTimeDataset = DefaultTableXYDataset()
txSecPassSeries = XYSeries("passed")
txSecFailSeries = XYSeries("failed")
responseTimeSeries = XYSeries("seconds")
finishTimeSeries = XYSeries("complete", True, False)
resolveHostSeries = XYSeries("resolveHost", True, False)
connectSeries = XYSeries("connect", True, False)
firstByteSeries = XYSeries("firstByte", True, False)
bandwidthSeries = XYSeries("KB/sec")
for bucket in self.bucketList:
txSecPass = bucket.getTxSecPass(txNum)
txSecPassSeries.add(bucket.getStartTime() / 1000.0,
txSecPass)
txSecFail = bucket.getTxSecFail(txNum)
txSecFailSeries.add(bucket.getStartTime() / 1000.0,
txSecFail)
responseTimeSeries.add(bucket.getStartTime() / 1000.0,
bucket.getMeanResponseTime(txNum))
if ga.constants.VORPAL.getPlugin("analyzer").isHTTP():
bandwidthSeries.add(
bucket.getStartTime() / 1000.0,
bucket.getMeanThroughputKBSec(txNum))
finishTimeSeries.add(bucket.getStartTime() / 1000.0,
bucket.getMeanFinishTime(txNum))
resolveHostSeries.add(
bucket.getStartTime() / 1000.0,
bucket.getMeanResolveHostTime(txNum))
connectSeries.add(bucket.getStartTime() / 1000.0,
bucket.getMeanConnectTime(txNum))
firstByteSeries.add(bucket.getStartTime() / 1000.0,
bucket.getMeanFirstByteTime(txNum))
txSecDataset.addSeries(txSecPassSeries)
txSecDataset.addSeries(txSecFailSeries)
responseTimeDataset.addSeries(resolveHostSeries)
responseTimeDataset.addSeries(connectSeries)
responseTimeDataset.addSeries(firstByteSeries)
responseTimeDataset.addSeries(finishTimeSeries)
simpleResponseTimeDataset.addSeries(responseTimeSeries)
bandwidthDataSet.addSeries(bandwidthSeries)
dataSetGroup[TX_SEC_KEY] = txSecDataset
dataSetGroup[FULL_RESPONSE_TIME_KEY] = responseTimeDataset
dataSetGroup[THROUGHPUT_KEY] = bandwidthDataSet
dataSetGroup[
SIMPLE_RESPONSE_TIME_KEY] = simpleResponseTimeDataset
self._txNameDatasets[txNum] = dataSetGroup
logger.debug("DEBUG: done building data sets.")
return self._txNameDatasets[txName]
class Chart(JPanel):
def _createEmptyChart(self, dataset = None):
chart = ChartFactory.createXYLineChart(
self.title, # chart title
"He", # x axis label
"Fst", # y axis label
dataset, # data
PlotOrientation.VERTICAL,
True, # include legend
True, # tooltips
False # urls
)
chart.setBackgroundPaint(Color.white)
# get a reference to the plot for further customisation...
# change the auto tick unit selection to integer units only...
#rangeAxis = plot.getRangeAxis()
#rangeAxis.setStandardTickUnits(NumberAxis.createIntegerTickUnits())
self.confArea = None
return chart
def setSelLoci(self, pv, allLoci, selLoci):
self.pv = pv
self.allLoci = allLoci
self.selLoci = selLoci
self.drawLabels()
def drawLabels(self):
if not hasattr(self, 'pv'): return
plot = self.chart.getPlot()
plot.clearAnnotations()
red = 0
for i in range(len(self.valMarkers)):
if not self.valMarkers[i]:
red += 1
continue
if self.allLoci[i] in self.selLoci:
if not self.labelSelected: continue
else:
if not self.labelNeutral: continue
x = self.pv[i-red][0]
y = self.pv[i-red][1]
locus = self.allLoci[i]
note = XYTextAnnotation(locus, x + 0.002, y + 0.002)
note.setTextAnchor(TextAnchor.BOTTOM_LEFT)
plot.addAnnotation(note)
def setMarkers(self, markers):
self.markers = XYSeries("Markers")
self.maxX = 0.0
self.maxY = 0.0
self.minY = -0.05
self.out = []
self.valMarkers = markers
for marker in markers:
if not marker:
continue
if marker[0]<2 and marker[0] > self.maxX:
self.maxX = marker[0]
if marker[1]<2 and marker[1] > self.maxY:
self.maxY = marker[1]
if marker[1]>-2 and marker[1] < self.minY:
self.minY = marker[1]
#self.markers.add(marker[0], max([0.0, marker[1]]))
self.markers.add(marker[0], marker[1])
self.maxX += 0.1
self.maxX = min([1, self.maxX])
self.maxY += 0.05
self.minY -= 0.05
def setTop(self, markers):
#setBottom has to be done before, as setMarkers
self.top = YIntervalSeries("Candidate neutral")
self.limit = YIntervalSeries("Candidate positive selection")
if len(markers) > 1:
#if self.maxY > markers[0][1]:
# self.limit.add(0.0, markers[0][1], markers[0][0], markers[0][1])
#else: #It does not really matter
# self.limit.add(0.0, -1, 1.1, 1.1)
self.limit.add(0.0, markers[0][1], markers[0][1], 1.1)
for i in range(len(markers)):
self.top.add(markers[i][0], self.bottomList[i][1],self.bottomList[i][1],
markers[i][1] )
if self.maxY > markers[i][1]:
self.limit.add(markers[i][0], markers[i][1],markers[i][1],
1.1)
else: #It does not really matter
self.limit.add(markers[i][0], markers[i][1],markers[i][1], 1.1)
#if markers[i][0] > self.maxX: break
#We do this at the end to fill the whole graphic
def setBottom(self, markers):
#print markers
self.bottomList = map (
lambda (x,y): (x,y),
markers) #legacy, can remove...
self.bottom = YIntervalSeries("Candidate balancing selection")
if len(markers) > 0:
self.bottom.add(0.0, -1.0, -1.0, self.bottomList[0][1])
for marker in self.bottomList:
self.bottom.add(marker[0], -1.0, -1.0, marker[1])
#if marker[0] > self.maxX: break
#We do this at the end to fill the whole graphic
def updateChartDataset(self, drawLabels=True):
dataset = XYSeriesCollection()
#self._calculateConfArea()
#dataset.addSeries(self.confArea)
dataset.addSeries(self.markers)
plot = self.chart.getPlot()
rangeAxis = plot.getRangeAxis()
domainAxis = plot.getDomainAxis()
rangeAxis.setRange(self.minY, self.maxY) #change
domainAxis.setRange(0.0, self.maxX)
#plot.setBackgroundPaint(Color.lightGray);
#plot.setAxisOffset(new RectangleInsets(5.0, 5.0, 5.0, 5.0));
#plot.setDomainGridlinePaint(Color.white);
#plot.setRangeGridlinePaint(Color.white);
markerRenderer = XYLineAndShapeRenderer(False, True)
#print self.markerColor
markerRenderer.setSeriesPaint(0, self.markerColor)
markerRenderer.setSeriesShape(0, Ellipse2D.Double(-3, -3, 6, 6))
#markerRenderer.setToolTipGenerator(FDistToolTipGenerator(self.pointNames))
plot.setRenderer(0, markerRenderer)
plot.setDataset(0, dataset)
dataset = XYSeriesCollection()
if self.drawCI:
dataset = YIntervalSeriesCollection()
CIRenderer = DeviationRenderer(True, False)
#CIRenderer.setOutline(True)
#CIRenderer.setRoundXCoordinates(True)
dataset.addSeries(self.bottom)
dataset.addSeries(self.top)
dataset.addSeries(self.limit)
CIRenderer.setSeriesFillPaint(0, self.balColor)
CIRenderer.setSeriesFillPaint(1, self.neuColor)
CIRenderer.setSeriesFillPaint(2, self.posColor)
CIRenderer.setSeriesPaint(0, self.balColor)
CIRenderer.setSeriesPaint(1, self.neuColor)
CIRenderer.setSeriesPaint(2, self.posColor)
plot.setDataset(1, dataset)
plot.setRenderer(1, CIRenderer)
plot.setDataset(1, dataset)
if drawLabels: self.drawLabels()
def resetData(self, justAnnots = False):
if not justAnnots:
self.markers = XYSeries("Markers")
self.drawCI = False
self.chart.getPlot().clearAnnotations()
if hasattr(self, 'pv'):
del(self.pv)
self.updateChartDataset()
def save(self, parent, format):
chooser = JFileChooser()
#filter = FileNameExtensionFilter(
# format + " files",
# array([format, format.lower()], String))
#chooser.setFileFilter(filter);
returnVal = chooser.showSaveDialog(parent)
if returnVal == JFileChooser.APPROVE_OPTION:
fileName = chooser.getSelectedFile().getPath()
if not fileName.upper().endswith('.' + format):
fileName += '.' + format.lower()
file = File(fileName)
else:
return
if format == 'PNG':
ChartUtilities.saveChartAsPNG(file, self.chart, self.exportX, self.exportY)
elif format == 'SVG':
domImpl = GenericDOMImplementation.getDOMImplementation()
doc = domImpl.createDocument(None, "svg", None)
svgGen = SVGGraphics2D(doc)
svgGen.getGeneratorContext().setPrecision(6)
self.chart.draw(svgGen,
Rectangle2D.Double(0, 0, self.exportX, self.exportY), None)
out = OutputStreamWriter(FileOutputStream(file), "UTF-8")
svgGen.stream(out, True) #True is for useCSS
out.close()
elif format == 'PDF':
mapper = DefaultFontMapper()
pageSize = Rectangle(self.exportX, self.exportY)
doc = TextDocument(pageSize, 50, 50, 50, 50)
out = BufferedOutputStream(FileOutputStream(file))
writer = PdfWriter.getInstance(doc, out)
doc.open()
cb = writer.getDirectContent()
tp = cb.createTemplate(self.exportX, self.exportY)
g2 = tp.createGraphics(self.exportX, self.exportY, mapper)
r2D = Rectangle2D.Double(0, 0, self.exportX, self.exportY)
self.chart.draw(g2, r2D)
g2.dispose()
cb.addTemplate(tp, 0, 0)
doc.close()
#out.close()
def __init__(self, width, height):
JPanel()
self.minY = -0.05
self.maxX = 1.0
self.maxY = 1.0
self.drawCI = False
self.title = "Fst/He"
self.labelSelected = True
self.labelNeutral = False
self.posColor = Color.RED
self.neuColor = Color.LIGHT_GRAY
self.balColor = Color.YELLOW
self.markerColor = Color.BLUE
self.exportX = width
self.exportY = height
self.chart = self._createEmptyChart()
self.chart.setAntiAlias(False)
self.resetData()
self.cp = ChartPanel(self.chart)
self.cp.setDisplayToolTips(True)
self.cp.setPreferredSize(Dimension(width, height))
self.add(self.cp)
def __init__(self, auto):
XYSeries.__init__(self, auto.getName())
self.automation = auto
self.maxItemCount = 0
self.automation.addAutomationExecutionListener(self)
