The syntax of the string s is inspired by However, the line styleĪnd markers can easily be controlled by adding a string s after the yĪrgument: plot(x, y, s). Inspired by the usual needs to include markers toĭistinguish multiple curves plots, especially if image files are toĪppear in black and white in printed reports. Just 15 equally spaced markers are drawn to avoid cluttering the plot.
You can always start out with the simpleĬommands - and jump to complicated fine-tuning only when strictly needed.īy default, Easyviz plots a curve with a solid line of thickness 1 and Simple and unified, and complicated things are not more complicated than These three principles and the Easyviz implementation make simple things
VEUSZ SUBSCRIPT CODE
Now and then there will be demand for package-dependent code forįine-tuning and customization of figures. The idea is that you can get away with Easyviz andĪ plotting package-independent script “95 percent” of the time - only Must grab the backend object and use the backend-specific syntax toįine-tune the plot. Plotting, like controlling tickmarks, inserting annotations, etc., you This makes the Easyviz code easy to readĪnd extend (e.g., with new backends). The Easyviz interface is minimalistic, aimed at To work with new fancy plotting packages in the future if Easyviz Plot your data with Easyviz (i.e., Matlab-like) commands and postpone In practice this means that when you write a script toĪutomate investigation of a scientific problem, you can always quickly Least the Gnuplot package can always be installed right away on any Scripts with Easyviz commands will most probably run anywhere since at For example, switching from Gnuplot to Matplotlib is trivial. Installed on the machine in question and what quality of the plots youĭemand. Only, can work with a variety of backends, depending on what you have In other words, scripts that use Easyviz commands Gnuplot, Matplotlib, Grace (Xmgr), Veusz,, PyX, Matlab, Plotting packages that can be called from Python. X = linspace ( - 2, 2, 41 ) # 41 point on xv, yv = ndgrid ( x, x ) # define a 2D grid with points (xv,yv) values = f ( xv, yv ) # function values surfc ( xv, yv, values, shading = 'interp', clevels = 15, clabels = 'on', hidden = 'on', show = True )Įasyviz is just a unified interface to other Troubleshooting chapter and the Installation chapter at the If you encounter problems with using Easyviz, please visit the Than going through the more limited Easyviz interface (and having theįlexibility to use other plotting engines). Prefer to use Matplotlib and its rich documentation directly rather Recent years, Matplotlib has emerged as the standard plotting packageįor Python, and Matplotlib offers a Matlab-like interface. Therefore also made to ease the switch between Python and Matlab. As Python is gaining popularityĪt universities, students are often forced to continuously switchīetween Matlab and Python, which is straightforward for arrayĬomputing, but (previously) annoying for plotting. This is often useful when you quickly need to visualizeĬurves or 2D/3D fields in your Python program, but haven’t reallyĭecided which plotting tool to go for.
Of a particular visualization package (and its special associated More fine-tuning of plots can be doneĮasyviz was made back in 2005/2006 so that one can postpone the choice Offers only basic control of plots: curves, linestyles, legends, Matlab, VTK, VisIt, OpenDX and 3) a minimalistic interface which Later): Gnuplot, Matplotlib, Grace, Veusz,, PyX, The Easyviz interface wasĭesigned with three ideas in mind: 1) a simple, Matlab-like syntax 2)Ī unified interface to lots of visualization engines (called backends Of scalar and vector fields are supported. Both curve plots and more advanced 2D/3D visualization Python with the purpose of making it very easy to visualize data in Easyviz is a unified interface to various packages for scientific
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