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A temporal raster plot is a graphic representation of occurrences in a certain temporal relation. Temporal raster plots are also sometimes referred to as carpet plots . Each occurrence is registered in a Cartesian coordinate system, in which both axes show time but have different time resolutions: one axis shows slices of data, the other some ...
Plotting the line from (0,1) to (6,4) showing a plot of grid lines and pixels. All of the derivation for the algorithm is done. One performance issue is the 1/2 factor in the initial value of D. Since all of this is about the sign of the accumulated difference, then everything can be multiplied by 2 with no consequence.
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Carpet plots have common applications within areas such as material science for showing elastic modulus in laminates, [1] and within aeronautics. [2] [3] Another plot sometimes referred to as a carpet plot is the temporal raster plot.
Waterfall plots are often used to show how two-dimensional phenomena change over time. [1] A three-dimensional spectral waterfall plot is a plot in which multiple curves of data, typically spectra, are displayed simultaneously. Typically the curves are staggered both across the screen and vertically, with "nearer" curves masking the ones behind.
# set terminal svg enhanced size 875 1250 fname "Times" fsize 25 set terminal postscript enhanced portrait dashed lw 1 "Helvetica" 14 set output "bode.ps" # ugly part of something G(w,n) = 0 * w * n + 100000 # 1 / (sqrt(1 + w**(2*n))) dB(x) = 0 + x + 100000 # 20 * log10(abs(x)) P(w) = w * 0 + 200 # -atan(w)*180/pi # Gridlines set grid # Set x axis to logarithmic scale set logscale x 10 set ...
The top row is a series of plots using the escape time algorithm for 10000, 1000 and 100 maximum iterations per pixel respectively. The bottom row uses the same maximum iteration values but utilizes the histogram coloring method. Notice how little the coloring changes per different maximum iteration counts for the histogram coloring method plots.
The DDA method can be implemented using floating-point or integer arithmetic. The native floating-point implementation requires one addition and one rounding operation per interpolated value (e.g. coordinate x, y, depth, color component etc.) and output result.