This document aims to show how to produce plots using Diana and combine them to create new products.
To get access to the Python modules that expose Diana's plotting features, you need to install the python-diana
package from the local package repository. Either use the package manager to do this, or enter the following in a
terminal:
apt-get install python-diana
Some examples can also be found in the python-diana-examples package.
You can use Diana's functionality from Python by importing the bdiana and plotcommands
modules from the metno package. If you are using an old version of ipython (earlier than
version 1.0) then it is also useful to import the embed function from the
metno.ipython_extensions module. The pyproj module is used to describe projections in a
way that Diana understands. We also import the datetime module so that we can pass a time
to Diana without needing to obtain one from a data file.
In [1]:
# Import the modules needed to use Diana.
from metno import bdiana, plotcommands
# Import an extension that lets us embed an image into a worksheet.
from metno.ipython_extensions import embed
The bdiana module contains the BDiana class. This provides a convenient interface to Diana's functions and also
wraps several initialisation steps into one object. To start using Diana, we simply create an instance of this class
and load a setup file that describes where various resources are located and set it up
using a setup file located on the user's system.
In [2]:
b = bdiana.BDiana()
b.setup("/etc/diana/setup/diana.setup-COMMON")
In [3]:
a = plotcommands.Area(name="Norge")
m = plotcommands.Map(map="Gshhs-Auto", backcolour="white", land="on")
m.setOption("land.colour", "flesh")
f = plotcommands.Field(model="HIRLAM.12KM.00", plot="air_temperature_2m",
plottype="contour", palettecolours="standard",
linetype="solid", linewidth=1, unit="celsius")
f.setOption("line.interval", 2)
times = b.getFieldTimes(f.options["model"], f.options["plot"])
b.setPlotCommands([a.text(), m.text(), f.text()])
b.setPlotTime(times[-1])
When we create the plot, we use the plotPicture method. This causes a QPicture object
to be created that can be reused, resized and transformed later without loss of
information.
In [4]:
pic1 = b.plotPicture(600, 800)
embed(pic1)
To demonstrate how plots can be combined, we create a smaller plot that shows a different area, and generate another picture from it.
In [5]:
a = plotcommands.Area(name="Europa")
m = plotcommands.Map(map="Gshhs-Auto", backcolour="white", land="on")
m.setOption("land.colour", "flesh")
f.setOption("linewidth", "off")
b.setPlotCommands([a.text(), m.text(), f.text()])
b.setPlotTime(times[-1])
pic2 = b.plotPicture(180, 240)
embed(pic2)
In [6]:
from PyQt4.QtCore import QRect, QSizeF
from PyQt4.QtGui import QColor, QPainter, QPicture, QPrinter
pic3 = QPicture()
pic3.setBoundingRect(QRect(0, 0, 600, 800))
p = QPainter()
p.begin(pic3)
p.drawPicture(0, 0, pic1)
p.fillRect(10, 10, 200, 260, QColor(255, 255, 255))
p.drawPicture(20, 20, pic2)
p.end()
embed(pic3)
In [7]:
pr = QPrinter()
pr.setOutputFormat(QPrinter.PdfFormat)
pr.setOutputFileName("/tmp/plot.pdf")
pr.setPaperSize(QSizeF(pic3.width(), pic3.height()), QPrinter.DevicePixel)
pr.setFullPage(True)
With the paint device ready to use, we paint the picture onto it to generate the PDF file.
In [8]:
p = QPainter()
p.begin(pr)
p.drawPicture(0, 0, pic3)
p.end()