Cartesian Plots

Data in Cartesian coordinate plots are defined by x and y quantities. Ziaplot has two types of Cartesian axes. ziaplot.axes.XyPlot draws the x and y axes lines along the bottom and left sides of the frame. The (0, 0) origin can be anywhere, even outside the plot area. ziaplot.axes.XyGraph always draws the x and y axis lines through the (0, 0) origin and includes arrowheads at the end of the axis lines. XyPlot is commonly used to plot discrete x and y values, where XyGraph is used to plot functions.

_images/xyplot_1_0.svg

In terms of adding and displaying data series, the two are identical.

Basic Plotting

The most common data series is the ziaplot.dataseries.Line. Typically, an axis will be created first, then one or more Lines added to it. Lines can be drawn with different colors, strokes (dash style), or with markers, using the chained method interface.

First, make up some data to plot.

x = [i*0.1 for i in range(11)]
y = [math.exp(xi)-1 for xi in x]
y2 = [yi*2 for yi in y]
y3 = [yi*3 for yi in y]
y4 = [yi*4 for yi in y]

Then, create an XyPlot and add several lines to it. Notice the color of each series cycles through the default set of theme colors if not specified manually.

p = zp.XyPlot()
p += zp.Line(x, y)
p += zp.Line(x, y2).marker('round', radius=8)
p += zp.Line(x, y3).stroke('dashed')
p += zp.Line(x, y4).color('purple').strokewidth(4)
p
_images/xyplot_3_0.svg

Line Options

The Color parameter can be an RGB string in the form #FFFFFF or a CSS named color. Another option is to use the theme colors. Providing color C1, C2, etc. will use the first, second, etc. color in the theme cycle.

Stroke or dash-style is one of

  • - (solid line)

  • dotted (or :)

  • dashed (or )

  • dashdot (or -. or .-)

  • Any valid SVG stroke-dasharray parameter.

Available markers include:

  • round (or o)

  • square (or s)

  • triangle (or ^)

  • triangled (or v)

  • larrow (or <)

  • arrow (or >)

  • +

  • x

  • -

  • |

Markers can also be oriented tangent to the data line, for example to show arrows pointing along the path. Or different markers on each endpoint can be set using ziaplot.dataseries.Line.endmarkers().

t = zp.linspace(-10, 10, 30)
tsq = [ti**2 for ti in t]
tsq2 = [tsqi+20 for tsqi in tsq]

p = zp.XyPlot()
p += zp.Line(t, tsq).marker('arrow', orient=True)
p += zp.Line(t, tsq2).endmarkers(start='square', end='arrow')
p
_images/xyplot_4_0.svg

Fading Colors

Sometimes it is useful for different lines to fade between two colors. This can be accomplishsed using the ziaplot.axes.BasePlot.colorfade() method of the axis object. Color fading requires hex string colors.

xf = zp.linspace(0, 10, 10)
p = zp.XyPlot()
p.colorfade('#0000FF', '#FF0000')
for i in range(10):
    yf = [xi*(i+1) for xi in xf]
    p += zp.Line(xf, yf)
p
_images/xyplot_5_0.svg

X-Y Data Series

In addition to ziaplot.dataseries.Line, a few other data series can be plotted. ziaplot.dataseries.Xy is just a subclass of Line that automatically sets the line color to ‘none’ and adds a round marker. ziaplot.dataseries.HLine and ziaplot.dataseries.VLine series are used to draw a line across the entire axis at a given data value.

p = zp.XyPlot()
p += zp.Xy(x, y)
p += zp.HLine(.5).stroke('dotted')
p += zp.VLine(.75).stroke('dashed')
p
_images/xyplot_6_0.svg

The ziaplot.dataseries.ErrorBar series draws lines with added x or y errorbars. The ziaplot.dataseries.ErrorBar.yerrmarker() and ziaplot.dataseries.ErrorBar.xerrmarker() methods control the errorbar end markers.

zp.ErrorBar(x, y, yerr=y2)
_images/xyplot_7_0.svg
zp.ErrorBar(x, y, yerr=y2).yerrmarker('square', length=5, width=1)
_images/xyplot_8_0.svg

And ziaplot.dataseries.LineFill works like an errorbar but draws a filled region:

zp.LineFill(x, ymin=y, ymax=y2).color('black').fill('blue', alpha=.3)
_images/xyplot_9_0.svg

Annotations

To set the axes title and labels for the x and y variables, provide the title, xname, and yname arguments to XyPlot or XyGraph. Calling ziaplot.series.Series.name() on a series adds the series line to a legend on the axes, which is displayed either to the left or right of the axes. Plain text labels can be added at any data point using the ziaplot.dataseries.Text series. ziaplot.dataseries.Arrow series are Lines with an arrowhead on one end, and optional text on the other.

p = zp.XyPlot(title='Title',
              xname='Independent Variable',
              yname='Dependent Variable')
p += zp.Line(x, y).name('Line #1')
p += zp.Line(x, y2).name('Line #2')
p += zp.Text(0.2, 2, 'Text', halign='center')
p += zp.Arrow((.70, 2.3), (.6, 3), 'Arrow', strofst=(-.05, .1)).color('black')
p
_images/xyplot_10_0.svg

Function Series

The ziaplot.dataseries.Function series takes a callable Python function and plots it over a given data range. Often plotted on an XyGraph axis to represent a functional relationship rather than discrete or measured data points. The function must take one float argument (the x value) and return a float (the y value).

p = zp.XyGraph()
p += zp.Function(math.sin, xmin=-2*math.pi, xmax=2*math.pi).name('sine')
p += zp.Function(math.cos, xmin=-2*math.pi, xmax=2*math.pi).name('cosine')
p
_images/xyplot_11_0.svg

Lambda functions work well here, such as

p += zp.Function(lambda x: x**2)

Histogram Series

While the ziaplot.dataseries.Bars series can be added directly to make bar plots, it is often easier to create histogram bars using the ziaplot.dataseries.Histogram series, or use a ziaplot.bar.BarChart axis for qualitative x-value bar charts. Histograms have parameters to specify the total number of bins, or a specific range of bin locations. The data can also be weighted, or plotted as a probability density instead of data count.

import random
v = [random.normalvariate(100, 5) for k in range(1000)]
zp.Histogram(v)
_images/xyplot_12_0.svg

Log-scale Axes

Data can be plotted on logscales using axes ziaplot.axeslog.LogYPlot, ziaplot.axeslog.LogXPlot, and ziaplot.axeslog.LogXYPlot.

_images/xyplot_13_0.svg

Data Limits and Ticks

By default, the axes are scaled to show all the data in all series. To manually set the data range, use ziaplot.axes.BasePlot.xrange() and ziaplot.axes.BasePlot.yrange().

x = [i*0.1 for i in range(11)]
y = [xi**2 for xi in x]

p = zp.XyPlot()
p += zp.Line(x, y)
p.xrange(.5, 1).yrange(.3, 1)
p
_images/xyplot_14_0.svg

Tick locations are also automatically determined. To override, call ziaplot.axes.BasePlot.xticks() or ziaplot.axes.BasePlot.yticks(), providing a tuple of tick values and optional names.

p = zp.XyPlot()
p += zp.Line(x, y)
p.xticks((0, .25, .75, 1))
p.yticks((0, .5, 1), names=('Low', 'Medium', 'High'))
p
_images/xyplot_15_0.svg

To keep the default ticks but change the number formatter, use ziaplot.styletypes.TickStyle with a standard format specification used in Python’s format().

p = zp.XyPlot()
p.style.tick.ystrformat = '.1e'
p += zp.Line(x, y)
p
_images/xyplot_16_0.svg

Minor ticks, without a number label, can also be added between the major, labeled, ticks.

p = zp.XyPlot()
p += zp.Line(x, y)
p.xticks(values=(0, .2, .4, .6, .8, 1),
         minor=(zp.linspace(0, 1, 21)))
p
_images/xyplot_17_0.svg