2.1 vis_04 data visualization lecture 2 fundamental concepts - reference model visualization...
Post on 20-Dec-2015
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2.1Vis_04
Data VisualizationData Visualization
Lecture 2Fundamental Concepts - Reference
ModelVisualization Techniques – Overview
Visualization Systems - Overview
2.2Vis_04
A Simple ExampleA Simple Example
TIME (mins)
OXYGEN (%)
0 2 4 10 28 30 32
20.8 8.8 4.2 0.5 3.9 6.2 9.6
This table shows the observed oxygen levels inthe flue gas, when coal undergoes combustionin a furnace
2.3Vis_04
Visualizing the Data - but is this what we want to
see?
Visualizing the Data - but is this what we want to
see?
2.4Vis_04
Estimating behaviour between the data - but is
this believable?
Estimating behaviour between the data - but is
this believable?
2.5Vis_04
Now it looks believable… but something is wrongNow it looks believable… but something is wrong
2.6Vis_04
At least this is credible..At least this is credible..
2.7Vis_04
What have we learnt?What have we learnt?
It is not only the data that we wish to visualize - it is also the bits inbetween!
The data are samples from some underlying ‘field’ which we wish to understand
First step is to create from the data a ‘best’ estimate of the underlying field - we shall call this a MODEL
This needs to be done with care and may need guidance from the scientist
2.8Vis_04
Data EnrichmentData Enrichment
This process is sometimes called ‘data enrichment’ or ‘enhancement’
If data is sparse, but accurate, we INTERPOLATE to get sufficient data to create a meaningful representation of our model
If sparse, but in error, we may need to APPROXIMATE
2.9Vis_04
The Visualization ProcessThe Visualization Process
Overall the Visualization Process can be divided into four logical operations:– DATA SELECTION: choose the portion
of data we want to analyse– DATA ENRICHMENT: interpolating, or
approximating raw data - effectively creating a model
– MAPPING: conversion of data into a geometric representation
– RENDERING: assigning visual properties to the geometrical objects (eg colour, texture) and creating an image
2.10Vis_04
Back to the Simple Example
Back to the Simple Example
Data
Enrich
Map
Render
Interpolate to create model
Select a line graph as techniqueand create line segments fromenriched data
Draw line segments on display insuitable colour, line style and width
Select Extract part of data we are interested in
2.11Vis_04
Classification of Mapping Techniques
Classification of Mapping Techniques
The mapping stage is where we decide which visualization technique to apply to our ‘enriched’ data
There are a bewildering range of these techniques - how do we know which to choose?
First step is to classify the data into sets and associate different techniques with different sets.
2.12Vis_04
Back to the Simple Example
Back to the Simple Example
The underlying field is a function F(x) – F represents the oxygen level and is
the DEPENDENT variable– x represents the time and is the
INDEPENDENT variable It is a one dimensional scalar field
because– the independent variable x is 1D– the dependent variable F is a scalar
value
2.13Vis_04
General Classification Scheme
General Classification Scheme
The underlying field can be regarded as a function of many variables: say
F(x)where F and x are both vectors:
F = (F1, F2, ... Fm)
x = (x1, x2, ... xn) The dimension is n The dependent variable can be
scalar (m=1) or vector (m>1)
2.14Vis_04
A Simple NotationA Simple Notation
This leads to a simple classification of data as:
EnS/V
So the simple example is of type:
E1S
Flow within a volume can be classed as:
E3V3
2.15Vis_04
ExerciseExercise
Can you give suitable techniques for the following classes:
ES1
ES2
ES3
EV33
2.16Vis_04
Overview of Visualization Techniques
Overview of Visualization Techniques
Using the classification to organise the various visualization
techniques
2.17Vis_04
ES1ES1
The humble graph!
How can we represent errors in the data?
A nice example of web-basedvisualization….
http://fx.sauder.ubc.ca/plot.html
2.18Vis_04
ES2ES2
Here we see a contour map of wind speed over the USA (28-Sep-04)
What can you observe?
Can you use an ES
1 technique for this sort of data?
http://weather.unisys.com/surface/
2.19Vis_04
ES3ES3
As dimension increases, it becomes harder to visualize on a 2D surface
Here we see a lobster within resin.. where the resin is represented as semi-transparent
Technique known as volume rendering
Image from D. Bartz and M. Meissner
2.20Vis_04
ES3ES3
Corresponding to contours for ES
2, we can generate isosurfaces
What are the limitations of this approach compared with volume rendering? Image from D. Bartz and M. Meissner
2.21Vis_04
EV22EV22
This is a flow field in two dimensions
Simple technique is to use arrows..
What are the strengths and weaknesses of this approach?
During the module, we will discover better techniques for this
2.22Vis_04
EV33EV33
This is flow in a volume
Arrows become extremely cluttered
Here we are tracing the path of a particle through the volume
2.23Vis_04
Visualization SystemsVisualization Systems
Showing how the map and render steps are realised in a visualization system
2.24Vis_04
IRIS ExplorerIRIS Explorer