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These operators can be used to compare any two expressions when the two items being compared are compatible. You would not want to compare a string value to a numerical value or a string value to a logical value. Simple expressions are easy to understand. For example, (myRsi > 20) is clearly understood to mean myRsi value is greater than 20. Since we are human and traders (smarter than the average person, right ), most of our thought processes are not this simple. For this reason, EasyLanguage has provided the or operator and the and operator. Most of the time we will use these operators in the form of logical operators; we will use them for comparison purposes. They can also be used in the form of arithmetic operators, but for our purposes we rarely do this. To fully understand these operators, you must understand the following truth table.

FIGURE 7.8. Multipass Twyman Green interferometer. (From Langenbeck, 1969a.)

Angle of incidence,

. . . . .

G F (+s, e) ( s, +e)

A wide range of transformations can be applied to spectral data before they are analyzed. The main purpose of transformations is to make the latent variables better available for powerful analysis. One of the most widely used is logarithmic transformation, which is especially useful to make skewed variables more symmetrically

(2.6)

Computers typically work with two types of images: raster and vector Raster images (also known as bitmap images) are made up of pixel data; in a 20-pixel-wide by 20-pixel-high color image there are 400 individual pixels making up the image, and each of these pixels has its own RGB color value In contrast, a vector image uses mathematical equations to describe the shapes that make up the image The SVG (Scalable Vector Graphics) format is a good example of a vector image Vector images are great for diagrams that include lines, curves, and blocks of color, but are not suitable for photographs or images with lots of detail In this chapter you concentrate on working with raster images, which tend to be more common on the Web.

PHP s GD image functions let you work with four main raster image formats JPEG, PNG, and GIF for desktop Web browsers, and WBMP images for mobile browsers (You concentrate on desktop Web images in this chapter) These four image formats are all compressed formats, which means that they use mathematical algorithms to reduce the amount of storage required to describe the image They play a key role in keeping your file sizes small and download times short! It s important to know when to use each of these image formats Although they are all raster images, they use quite different compression techniques, and in certain situations one format works much better than another The JPEG format uses lossy compression, in which some of the data in the original image is lost during compression.

From here we will use a spur plot for a xed IF (rather than a xed LO), possibly normalized to the IF. Such plots are shown in Figs. 7.10 and 7.11, the latter being a logarithmic plot. (These are 61-curve plots, but 116-curve plots are available in the workbook that contains these plots.) The version of Eq. (7.2) that we plot now is fL = (fI nfR )/m (7.19) with fI xed. The version normalized to fI is obtained by dividing by fI : fL /fI = (1 nfR /fI )/m, (7.20)

The format is designed to work best with images like photographs, where there s a lot of subtle shading and few large blocks of a single color It s the format to use when a slight loss in quality won t be too apparent to the viewer Images in the PNG and GIF formats, on the other hand, are compressed in a lossless fashion, meaning that no image data is lost during the compression process Sharp edges and straight lines (which suffer under JPEG compression) are reproduced faithfully This technique works best with images that contain lines and large blocks of color cartoons and diagrams, for example..