Mapping an argument

Key features[ edit ] A number of different kinds of argument map have been proposed but the most common, which Chris Reed and Glenn Rowe called the standard diagram, [5] consists of a tree structure with each of the reasons leading to the conclusion. There is no consensus as to whether the conclusion should be at the top of the tree with the reasons leading up to it or whether it should be at the bottom with the reasons leading down to it.

Mapping an argument

EWA Resampling All the images are exactly the same distortion, just using different 're-sampling' techniques. The last image in the above used the default EWA settings of the Generalized Distortion Operatorand as you can see it produced an extremely high quality result.

However it took 4. The first image has the default EWA resampling turned off by using a " -filter point" setting.

This forces it to use Direct Interpolated Lookup for each pixel. As such this image was generated extremely fast in comparison.

The middle image is as the first image but with the distorted output image being enlarged by a factor of 10, before being scaled back grid resampling to match the other images.

That is more than pixels were looked up and averaged together for each destination pixel, so as to Super Sample the result. It is quite fast to generate 1. The biggest difference between the results is that super-sampling only does a general improvement in quality uniformly over the whole image.

As the distortion gets more sever it starts to break down. The result is the highly visible Resampling Artifacts in the middle ground, and more specifically a line of server moire effects just before the horizon.

A resource consumer group (consumer group) is a collection of user sessions that are grouped together based on their processing needs. When a session is created, it is automatically mapped to a consumer group based on mapping rules that you set up. Concept Mapping. A concept map helps students organize and represent knowledge of a subject. Concept mapping links concepts and ideas together with . Top Sources of Crime Guns in America. This map shows the differences among states' crime gun export rates. To trace the guns, click on a state above or a law to the right.

The moire effect is caused when when the 10 samples across per pixel nearly matches the checker board pattern of the image, producing distorted color effects. On the other hand area-resampling concentrates more on the problem pixels closer to the horizon where it spends almost all of its timethan on foreground pixels, Mapping an argument it does actually out perform super-sampling.

Basically the above is a very extreme distortion, and the time EWA lookup takes is commensurate. More commonly it generates much better results than a single interpolated lookup, as it efficentally looks are every pixel involved, while not using too many samples is areas that don't need it, as super-sampling does.

Using a simple ellipse EWA resampling or a rectangle Resizeto do 'area resampling' does produce good results, Mapping an argument all the source pixels involved in scaled, affine or perspective distortions, will be merged to produce the final color of an individual destination pixel.

In cases of very non-linear distortions, such as in DePolar Distortsor indeterminanate distortions, such as Shepard's Distortion or even ray-tracing, finding the correct 'Area' to resample all the source pixels needed, becomes prohibitive, and super-sampling is the best method to improve results.

Mapping an argument

But for straight tiling, enlargements, and unscaled rotations, a very fast single 'point' interpolated lookup is probably all that is required, and may even be recommended to ensure perfect no-op no change distortions see below.

Remember however all resampling techniques are just methods for determining the color of each individual pixel. It is not actually part of the how an image is distorted, except with regard to the mapping of locations between destination and source or visa-versa if posible.

Generalized Distortion Operator With the generation of these examples, the ensuing discussions in the IM Forumsand multiple requests from users for easier and faster ways to do perspective and other distortions, a new operator was added to IM v6.

This Generalized Distortion Operator is called " -distort ", and you can see what distortion methods it has available on your IM version using " -list Distort". The number floating point values given is however highly dependant on the distortion method being used, and their meanings also depend not only on the method chosen, but can also depend on the exact number of control points or attributes needed for a particular method.

This is especially the case for the ' Scale-Rotate-Translate ' or ' SRT ' for short distortion, which really combines three separate ' Affine ' distortions into a single distortion. Many distortion methods take a list of control points in Image Coordinatesand typically these are given as pairs of coordinates which control how the distortion is to modify the image.

These pairs of coordinates are detailed more fully later in Distortions Using Control Points. There are exceptions to this, such as the ' Arc ' distortion a polar mapping variant where the input source image size really does not have much meaning in the distorted form of the image see Arc Distortion below for details.

However this particular 'mode' of operation also goes further and also sets the Virtual Canvas Offset page of the resulting image. This way you can later Layers Merge this image onto another image, at the correct position according to your control points, using the appropriate Alpha Composition see 3d Cubes, using Affine Layering as a basic example.

See the notes about the individual disortion methods. You also may need to use it after if the virtual canvas and offset is not required. The normal " -distort " will just ignore any existing offset present in the source image in terms of the distortion itself, but will copy that offset unchanged to the distorted image.

Use " -distort " to have results mapped into an image of the same size. Also see Distort Viewport below if you want to override this general viewport selection, and exactly control of what size and what part of the distorted image you want to see in your results. The reason is that these pixels contain semi-transparent pixels that result from the area resampling filter, and these pixels are vital to correct 'edge joining' and overlaying of the distorted image.

Technically the number of pixels added should depend on the output scaling of Resampling Filter Support. That is how much a pixel's area could 'spread' due to the resampling filter. However as the scaling of each pixel can be variable, calculation of the absolutely correct number of additional pixels needed is a very tricky matter, and usually not worth the effort.

The 2 pixel added is thus a 'fudge', as distortions rarely enlarge images which causes pixels to 'spread' more. Also as most standard resampling filters has a support of 2 units, the addition of 2 pixels a reasonable one.

Also as this addition is 'fixed' it allows users the option to simply Crop Image Size in various waysif that is their wish.

Mapping an argument

The 2 pixel 'fudge' does become obviously too small when doing enlargments of images. But those are fairly rare distortions, and users can define there own Viewport see below if this is a problem.By now, Argunet belongs to the senior citizens of the software realm.

While it has grown quiet around this blog, behind the scenes, we were busy experimenting with a different technological approach to argument mapping. Concept Mapping. A concept map helps students organize and represent knowledge of a subject.

Concept mapping links concepts and ideas together with . Argument mapping improves our ability to articulate, comprehend and communicate reasoning, thereby promoting critical thinking. Argument mapping is using graphical methods to display the structure of reasoning and argumentation.

A mind map is a diagram used to visually organize information. A mind map is hierarchical and shows relationships among pieces of the whole.

It is often created around a single concept, drawn as an image in the center of a blank page, to which associated representations of ideas such as images, words and parts of words are added. Search free historic newspaper archives from Chronicling America (United States), Trove (Australia), and many more.

Argument mapping is a way of laying out visually reasoning and evidence for and against a statement or claim. A good map clarifies and organizes thinking by showing the logical relationships between thoughts that are expressed simply and precisely.

Atlas of Prejudice – Alphadesigner