Plotting API

This section describes the plotting API of cesiumpy. Plotting API allows to add multiple entites at a time easily. You can call each plotting methods via Viewer.plot accessor.

Scatter

Viewer.plot.scatter draws multiple Point entity accepting following keywords. Both x and y must be provided at least.

  • x: Longitude
  • y: Latitude
  • z: Height
  • size: Pixel size
  • color: Color
>>> v = cesiumpy.Viewer()
>>> v.plot.scatter([130, 140, 150], [30, 40, 50])
_images/plotting_scatter01.png

For other keywords, you can use list or scalar. When list is passed, each element is used in the corresponding entity. If scalar is passed, all entities use the specified value.

>>> v = cesiumpy.Viewer()
>>> v.plot.scatter([130, 140, 150], [30, 40, 50],
...                size=[10, 20, 30], color=cesiumpy.color.RED)
_images/plotting_scatter02.png

Bar

Viewer.plot.bar draws 3d bar using Cylinder entity accepting following keywords. x, y and z must be provided at least.

  • x: Longitude
  • y: Latitude
  • z: Height
  • size: Radius
  • color: Color
  • bottom: Bottom heights
>>> v = cesiumpy.Viewer()
>>> v.plot.bar([130, 140, 150], [30, 40, 50],
...            z=[10e5, 20e5, 30e5], color=cesiumpy.color.AQUA)
_images/plotting_bar01.png 
>>> v = cesiumpy.Viewer()
>>> v.plot.bar([130, 140, 150], [30, 40, 50], z=[10e5, 20e5, 30e5],
...            color=cesiumpy.color.AQUA, size=1e5)
_images/plotting_bar02.png

Specifying bottom keyword allows to draw stacked bar plot.

>>> v = cesiumpy.Viewer('viewertest')
>>> v.plot.bar([130, 140, 150], [30, 40, 50], [1e6, 2e6, 3e6],
...            size=1e5, color=cesiumpy.color.RED)
>>> v.plot.bar([130, 140, 150], [30, 40, 50], [3e6, 2e6, 1e6],
...            size=1e5, color=cesiumpy.color.BLUE,
...            bottom=[1e6, 2e6, 3e6])
_images/plotting_bar03.png

Label

Viewer.plot.label draws texts using Label entity accepting following keywords. text, x and y must be provided at least.

  • text: Labels
  • x: Longitude
  • y: Latitude
  • z: Height
  • size: Text size
  • color: Color
>>> v = cesiumpy.Viewer()
>>> v.plot.label(['A', 'B', 'C'], [130, 140, 150], [30, 40, 50])
_images/plotting_label01.png

Pin

Viewer.plot.pin draws pins using Billboard entity accepting following keywords. Both x and y must be provided at least.

  • x: Longitude
  • y: Latitude
  • z: Height
  • text: Label
  • size: Pin size
  • color: Color
>>> v = cesiumpy.Viewer()
>>> v.plot.pin([130, 140, 150], [30, 40, 50])
_images/plotting_pin01.png 
>>> v = cesiumpy.Viewer()
>>> v.plot.pin([130, 140, 150], [30, 40, 50],
...            color=cesiumpy.color.RED, text=['!', '?', '!?'])
_images/plotting_pin02.png

Specifying Color

You can colorize each entity using cesiumpy.color.Color instance. Common colors are defined under cesiumpy.color. Refer to Cesium Documentation to see the list of constants.

>>> cesiumpy.color.AQUA
Color.AQUA

Also, you can pass RGB or RGBA values to instanciate Color.

# RGB
>>> cesiumpy.color.Color(1, 0, 0)
Color(1.0, 0.0, 0.0)

# RGBA
>>> cesiumpy.color.Color(1, 0, 0, 0.5)
Color(1.0, 0.0, 0.0, 0.5)

If you want to use str representation, use fromString method.

>>> cesiumpy.color.Color.fromString("#FF0000")
Color.fromCssColorString("#FF0000")

There are 2 functions to prepare color at random.

  • choice: Get a single color constant randomly.
  • sample: Get a list of random color constants with specified length.
>>> cesiumpy.color.choice()
Color.DARKSLATEGREY

>>> cesiumpy.color.sample(3)
[Color.THISTLE, Color.PINK, Color.DARKKHAKI]

ColorMap

Also, cesiumpy has ColorMap class which internally uses matplotlib ColorMap. This is convenient to prepare multiple colors based on external values.

>>> cmap = cesiumpy.color.get_cmap('winter')
>>> cmap
ColorMap("winter")

>>> cmap(0.5)
Color(0.0, 0.501960784314, 0.749019607843, 1.0)

>>> cmap([0.2, 0.6])
[Color(0.0, 0.2, 0.9, 1.0), Color(0.0, 0.6, 0.7, 1.0)]