The document provides an overview of the Visualization and Control System (VCS) and its functionalities, including the use of graphic methods, templates, and primitives for rendering data plots. It discusses different 2D and 1D graphic methods available in VCS, how to create and manipulate canvases, and the process for plotting data. Additionally, it mentions the capability to incorporate GIS data and references related plotting packages like xmgrace.

1. Lesson 4
Visualization ‐ vcs and xmgrace

2. Preview
• Visualization and Control System (VCS)
• Xmgrace

3. VCS Concepts and Terminology
Basic concepts:
• VCS Canvas – where the plots are drawn
• Graphic Methods – how the data is rendered (the
plot type). E.g. “boxfill”, “isofill”, “isoline”,
“vector”, etc,. Multiple projections may be
available for a given Graphic Method.
• Templates – define the location where things are
drawn on the canvas (data, legend, title,
comments, units, etc..)
• Primitives – additional secondary items such as
lines, polygons, text, markers, etc.,

4. The VCS Canvas
• VCS canvas needs to be initialized (created)
>>> x=vcs.init() # without any arguments
• Up to 8 Canvases at once.
• Canvas as “magic board”, can clean or destroy it:
>>> x.clear()
>>> x.close()
• Can have multiple plots on a single Canvas (not
covered here)

5. VCS Help
• Basic help on VCS can be obtain inline via: >>>
vcs.help()
• This will list available function in VCS, notably
functions to create/get/query VCS objects…

6. VCS First Help
This also can be used to get help on a specific
command:
>>> vcs.help(‘createboxfill’)
Function: createboxfill
# Construct a new boxfill graphics method
Description of Function:
Create a new boxfill graphics method given the name and the existing boxfill
graphics method to copy the attributes from. If no existing boxfill graphics
method name is given, then the default boxfill graphics method will be used
as the graphics method to which the attributes will be copied from.
If the name provided already exists, then a error will be returned. Graphics
method names must be unique.

7. Graphic Methods Concepts (1)
• Essentially a graphic method represents HOW
data are going to be plotted (the WHERE will be
determined via templates, see later)
• There are 13 type of graphic methods in VCS:
– 2D Graphic Methods
• Boxfill, Isofill, Isoline, Meshfill, Vector, Outfill,
Outline, Continents , (Taylordiagrams)
– 1D Graphic Methods
• Yxvsx, Xyvsy, XvsY, Scatter

8. Specifying a Graphic Method
To specify a graphic method use a “create” function, then use
plot:
• For example, for a boxfill:
>>> gm = x.createboxfill(‘name’)
>>> x.plot(data, gm)
• If a graphic method already exists, use “get” functions:
>>> gm = x.getboxfill(‘name’)
>>> x.plot(data, gm)
• Replace ‘boxfill’ in the above for other methods.

9. 2D ‐ “boxfill”
• The boxfill graphic method takes a 2D array and represents it
by filling a “box” (determined by the bounds on each axis
values) with a color linked to the array’s value at this location:
>>> box=x.createboxfill(‘new’)
>>> x.plot(data,box)

10. 2D ‐“isofill”
• Isofill graphic methods draws filled isocontour
• They are extremely similar to boxfill “custom” type
• Known Limitation:
– No control on labels position
– No control on isolines “Smoothness”
>>> iso=x.createisofill(‘new’)

11. 2D ‐ “isoline”
• Isoline, draws isocontours, color, style, can be
controlled.
• Limitation:
– No control on the labels location
– No control of “smoothness”
>>> iso=x.createisoline(‘new’)

12. 2D ‐ “vector”
• The “Vector” graphic method represents the
combination of 2 arrays, via “vector” the first
array representing the “X” axis component
and the second array representing the “Y”
axis component.
>>> f=cdms.open(’sample_data/clt.bc’)
>>> u=f(‘u’)
>>> v=f(‘v’)
>>> vec=x.createvector(‘new’)
>>> x.plot(u,v,vec)

13. 1D – Y(x) vs x
• All 1D plots in VCS basically work the same way.
There are 4 types of 1D graphic method, we’ll
start with the basic: Yxvsx, which stands for Y(x)
vs x
• This graphic method draws a 1D array (Y) as a
function of its 1D axis (x)
• Example zonal mean of the first time point of our
data array
>>> zm=MV.average(data[0],1) # Zm.shape is (46,)
>>> x.plot(zm) # knows to plot 1D with yxvsx
>>> yx=x.createyxvsx(‘new’)
>>> x.plot(zm,yx) # same

14. 1D ‐ “VCS” Yxvsx attributes
• As in isoline, or vector, line, linecolor,
linewidth, determine the line.
• marker, markercolor, markersize, determine
the markers to be drawn:
>>> yx.line='dot'
>>> yx.linecolor=242
>>> yx.linewidth=2
>>> yx.marker='star’
>>> yx.markercolor=244

15. Graphic Methods Attributes
>>> b=x.createboxfill(‘new_one’)
>>> b.list()
‐‐‐‐‐‐‐‐‐‐Boxfill (Gfb) member (attribute) listings ‐‐‐‐‐‐‐‐‐‐
Canvas Mode = 1
graphics method = Gfb # indicates the graphic method type: Graphic Filled
Boxes (Gfb)
name = new # Name of the specific graphic method
projection = linear # projection to use (see projection section)
xticlabels1 = * # 1st set of tic labels, ‘*’ means ‘automatic’
xticlabels2 = * # 2nd set of labels (pos determined by template)
xmtics1 = # 1st set of sub ti for details)
xmtics2 =
yticlabels1 = *
…
…

16. 2D ‐ World Coordinates – example
attributes
• worldcoordinate attributes are present on all
graphic methods.
• can select a subset area.
• for example to visualise Africa:
>>> b.datawc_x1 = -45.
>>> b.datawc_x2 = 70.
>>> b.datawc_y1 = -38.
>>> b.datawc_y2 = 38.
>>> x.plot(s,b)

17. Projections
• P=x.createprojection()
• Graphicmethod.projection=P
• P.type=n
– N can be one of 28 possible
• print P.__doc__
– Each type has specific parameters
• P.list()
import vcs,cdms2,sys
f=cdms2.open(sys.prefix+
’/sample_data/clt.nc’)
s=f(“clt”,time=slice(0,1),
longitude=(‐210,50))
x=vcs.init()
iso=x.createisofill()
p=x.createprojection()
p.type=‘orthographic’
iso.projection=p
x.plot(s,iso,ratio=‘1t’)
x.clear()
p.type=‘lambert’
x.plot(s(latitude=(20,70),
longitude=(‐150,‐50)),iso)

18. Projection attributes of Graphic
Methods
Each graphic method may have a number of
projections, the full list is available from:
>>> v.show('projection')
************************Projection Names List*************************
( 1): default linear mollweide
( 4): robinson polyconic polar
( 7): lambert orthographic mercator
************************End Projection Names List*********************
mollweide polar robinson

19. Introducing Templates
• Template tell VCS WHERE to draw objects on the
canvas (whereas Graphic Methods specify HOW to
draw them).
• 4 aspects of the plot controlled templates:
– Text location for things like title, comments, name, etc..
– Data area
– Tick marks and label locations
– Legend

20. VCS: template manipulation
• Template ratio
X.ratio=2 : y is twice as big as x
X.ratio=‘auto’
X.ratio=‘2t’ : also moves tick marks
• Template scaling (lower left data area unchanged)
T.scale(.5) # half size
T.scale(.5, axis=‘x’) #half size in X, font
unchanged
T.scale(.5, axis=‘x’, font=1) # also alter
fonts
• Template moving
T.move(.2, .4) # move by 20% in x, 40% in y
Positive values means up/right
T.moveto(x,y) # move lower left corner of
data to x,y

21. VCS: template manipulation
• Using EzTemplate
• Also available: EzTemplate.oneD,
for 1D plots, uses the provided
“base” template and move the
legend according to the number
of dataset
from vcsaddons import EzTemplate
import vcs
x=vcs.init()
M=EzTemplate.Multi(rows=4,columns=3)
for i in range(12):
t=M.get()
x.plot(s,t,iso)
OD = EzTemplate.oneD(n=n,template=t)
for i in range(n):
y = MV2.sin((i+1)*x)
y.setAxis(0,ax)
yx = X.createyxvsx()
yx.linecolor=241+i
yx.datawc_y1=‐1.
yx.datawc_y2=1.
t = OD.get()
X.plot(y,t,yx,bg=bg)

22. vcs: text primitives
• text=x.createtext()
‐‐‐‐‐‐‐‐‐‐Text Table (Tt) member (attribute) listings ‐‐‐‐‐‐‐‐‐‐
Tt_name = new
font = 1
spacing = 2
expansion = 100
color = 1
priority = 1
string = None
viewport = [0, 1, 0, 1]
worldcoordinate = [0, 1, 0, 1]
x = None
y = None
projection = default
‐‐‐‐‐‐‐‐‐‐Text Orientation (To) member (attribute) listings ‐‐‐‐‐‐‐‐‐‐
To_name = new
height = 14
angle = 0
path = right
halign = left
valign = half
• Font_name = x.addfont(path_to_ttf_font)
• Font = x.getfont(Font_name) # usable in template
• Available fonts by default: ['Adelon', 'Arabic', 'AvantGarde', 'Chinese', 'Clarendon', 'Courier',
'Greek', 'Hebrew', 'Helvetica', 'Maths1', 'Maths2', 'Maths3', 'Maths4', 'Russian', 'Times',
'default']

23. vcs: other primitives
• fa=x.createfillarea(‘new’)
• l=x.createline(‘new’)
• m=x.createmarker(‘new’)
• Each primitive has the 2 following attributes:
– Prim.viewport=[xv1,xv2,yv1,yv2] # default: [0,1,0,1]
• In % of page, area of the primitive extends
– Prim.worldcoordinates = [x1,x2,y1,y2] # defalut [0,1,0,1]
• Coordinates corresponding to xv1,xv2,yv1,yv2
• Primitive units are in the worldcoordinate system
– Example
• text.viewport=[.25,.75,.25,.75] # define smaller zone on page
• text.worldcoordinate=[‐180, ‐90, 180, 90] # Define the coordinate system
• text.x=[‐122.4428 ]
• text.y=[37.7709 ]
• text.string=[‘San Francisco, CA, 94117’]
• For overlay with an existing graphic method
– Prim.viewport # set to your template.data
– Prim.worldcoordinates # set to your graphic method.data.wc

24. Animating through the GUI

25. Animating at the command line
Just keep write a frame to a canvas, to gif and
clear, then do all over again…
>>> x=vcs.init()
>>> templ=canvas.gettemplate('BADC_ERA40')
>>> plot_type=canvas.getisofill(‘ASD’)
>>> for i in range(loop_num):
... x.clear()
... x.plot( data( time=slice(i,i+1) ), templ,
plot_type)
... x.gif(outfile) # Second arg of merge="a"
# needed on some versions
Or call up GUI with x.animate.gui()

26. Example: VCS
• Look at the sample program “test_vcs.py” and
run it through step by step.

27. vcsaddons
• GIS capability. You can read and plot gis/shapefiles.
import vcs,vcsaddons
import cdms2,sys
x=vcs.init()
import vcs.test.support
bg=0
c=vcsaddons.createusercontinents(x=x)
lon1=‐125
lon2=‐75.
lat1=20.
lat2=55.
c.types = ['shapefile','shapefile']
c.sources = ['../Data/co1990p020','../Data/fe_2007_06_county',]
c.colors = [246,241,244,241]
c.widths=[1,1,1]
c.lines=['solid','solid','solid','dot']
f=cdms2.open(sys.prefix+’/sample_data/clt.nc’)
s=f("clt",latitude=(lat1,lat2),longitude=(lon1,lon2),time=slice(0,1
))
t=x.createtemplate()
iso=x.createisofill()
x.plot(s,t,iso,continents=0,ratio='autot',bg=bg)
x.plot(s,c,t,ratio='autot',bg=bg)
x.png('uscounties')
import vcsaddons._gis
sources =
['../Data/fe_2007_06_county.dbf','../Dat
a/co1990p020.dbf’]
for s in sources:
D = vcsaddons._gis.readdbffile(s)
print D.keys()
try:
print D['NAME']
except:
print D['COUNTY']

28. Xmgrace
• Xmgrace is a very nice plotting package – for
1‐d data.
• If you have xmgrace installed on your
computer, you can script it via CDAT. Its
interface has been mapped to be as close as
possible from the “parameter” files from
xmgrace.

29. Example: Xmgrace
• Look at the sample program
“test_xmgrace.py” and run it through step by
step.

30. Other packages
• Matplotlib: http://matplotlib.sourceforge.net
• Visus
• IaGraphics

31. Acknowledgements
• Dean Williams, Charles Doutriaux (PCMDI,
LLNL)
• Dr. Johnny Lin