New features included in CDAT 4.3: 

 - LAS CDAT interface to IPCC data
 - New VCDAT  - Light mode
 - TrueType fonts
 - Direct PostScript, PNG, etc. output  
 - improved CDAT Demo

Be prepared for big changes with the next release!

CDAT 4.3 will be the last CDAT version with the Numeric module. From the new version 5.0 and on, we will be only supporting the NumPy module and Python version 2.5.  

Both CDAT 4.3 and 5.0 will only compile with the Python 2.5+ versions. 

Also, please note, that the Numeric Module with Python 2.5 will not compile on the 64 bit platform. 

New Modules

Because of the changes coming with the new NumPy, the CDAT 5.0 will have new modules cdms2 and MV2 and the old cdms and MV modules will be deprecated. We will be supplying the authomatic conversion program that will help you with the transition from the pre-CDAT 5.0 to the post CDAT 5.0 programming with the new modules. 
 

CDAT 5.0 only

CDAT 5.0 will have both Numeric and NumPy included, and also both cdms, MV and cdms2 and MV2 modules. This is to easy up the transition and enable the old scripts to run under CDAT 5.0. Some people may want to check that the results they were getting with Numeric and cdms/MV are the same with the new NumPy + cdms2/MV2 modules.

The new manual CDMS 5.0 is posted on the web.

Do check out the CDAT Demo! At the Xterm prompt, type:

% cdatdemo 

and you ready to try it.  You can see a whole range of demo scripts and you can run them in the PyDebugger. 

For example here is a screen with the CDAT Visualizations tutorials. There are the Diagnostics, Data Analysis, Application Development and other tutorials.

We are excited to introduce new TrueType fonts into CDAT. 

The font number is now not limited to 9, but it is unlimited. By default the fonts are loaded from your PCMDI_GRAPHICS directory. But you can also add you own fonts dynamically when running the application. 

Here are the default fonts distributed with CDAT and their correspondent numbers: 

Here are the functions you can use to modify fonts:

>>> x.addfont(path,name)
Load a font file specified via path and associates it with the name "name"
*) If name is empty then the font name stored in the font file is used
*) If path pints to a directory then all font files (.ttf) in this directory are loaded and associated with their name in the file
*) additionally for directory loading you can specifiy "r" as secand arguments (instead of name) to browse recursively

>>> x.listelements("font")
returns a list of all fonts loaded into CDAT and available to the user

>>> x.setdefaultfont("myfont")
# or number
switches your font with font number 1, useful to simply change the font w/o editing all templates

>>> x.switchfont(font1,font2)
# switch font numbers these allows you for example to make sure that your font named "myfont" always has number 4 (since template refer to font number and not name)
>>> x.switchfonts("myfont",4)

>>> x.getfontnumber("myfont")
# returns number associated with font name

>>> x.getfontname(4)
# returns name associated with font number

>>> x.getfont(arg)
# returns either the font name or number associated with a number/name

>>> x.gettextextent(tx)
# where tx is a text object, returns the surrounding box for each string drawn by the object

Usefull to place string with different fonts next to each other, or for equations building

Example creating a text in vcs

to=x.createtextorientation('my')
to.height=50
tmpl=x.createtemplate()
tmpl.legend.textorientation=to
x.plot(s,tmpl)
to.list()
you can control, path and angle as well
----------Text Orientation (To) member (attribute) listings ----------
Canvas Mode = 1
secondary method = To
name = my
height = 50
angle = 0
path = right
halign = left
valign = half
same with texttable to control the font value and color 

tt=x.createtexttable('my')
tt.list()
----------Text Table (Tt) member (attribute) listings ----------
Canvas Mode = 1
secondary method = Tt
name = my
font = 1
spacing = 2
expansion = 100
color = 241
fillincolor = 240

s=f('clt',slice(0,12),latitude=(0,0,'cob'),squeeze=1,order='xt')
iso=x.createisofill()

dict = {}
a = cdtime.comptime(1979,4)
dict[a.torel('months since 1979').value] = 'April 1974'
iso.xticlabels1=dict
x.plot(s,iso)