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 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 box(data):
"""
Creates a box and whiskers plot.
*data* is a ``dict`` whose keys are category names and values are list of
numeric values.
"""
dataset = DefaultBoxAndWhiskerCategoryDataset()
for name, values in data.iteritems():
dataset.add(values, "", name);
chart = ChartFactory.createBoxAndWhiskerChart("", "", "", dataset, True)
return Chart(chart)
def pie(data, name='', trid=False):
"""
Creates a pie chart.
*data* is a ``dict`` whose keys are category names and values are numeric
values.
Setting *trid* to ``True`` results in a 3D char.
"""
dataset = DefaultPieDataset();
for k,v in data.iteritems():
dataset.setValue(k, v)
if trid:
chart = ChartFactory.createPieChart3D(name, dataset, True, True, False)
else:
chart = ChartFactory.createPieChart(name, dataset, 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 category(data, name='', xlabel='', ylabel='', stacked=False, trid=False):
"""
Creates a category bar chart.
*data* is a ``dict`` whose keys are category names and whose values are
numerical (the height of the bar).
To plot multiple series *data* is specified as a ``dict`` whose keys are
series names and values are a ``dict`` of category names to numerical values.
Setting *stacked* to ``True`` results in a stacked bar char. Setting *trid*
to ``True`` results in a 3D bar chart.
"""
dataset = DefaultCategoryDataset()
for k, v in data.iteritems():
if isinstance(v, dict):
for k2, v2 in v.iteritems():
dataset.addValue(v2, k2, k)
else:
dataset.addValue(v, "", k)
if trid:
if stacked:
chart = ChartFactory.createStackedBarChart3D(
name, xlabel, ylabel, dataset, PlotOrientation.VERTICAL, True,
True, True)
else:
chart = ChartFactory.createBarChart3D(name, xlabel, ylabel,
dataset,
PlotOrientation.VERTICAL,
True, True, True)
else:
if stacked:
chart = ChartFactory.createStackedBarChart(
name, xlabel, ylabel, dataset, PlotOrientation.VERTICAL, True,
True, True)
else:
chart = ChartFactory.createBarChart(name, xlabel, ylabel, dataset,
PlotOrientation.VERTICAL, True,
True, True)
return Chart(chart)