+ coord_equal()
Or if x and y are long and lat, + coord_map()
Hadley
On Sun, Nov 7, 2010 at 1:55 PM, Edzer Pebesma
<edzer.pebe...@uni-muenster.de> wrote:
> Paul, this nicely illustrates the power of ggplot2.
>
> In the resulting plot, however, it seems to me that the
>
> + opts(aspect.ratio = 1)
>
> does not result in the desired effect that 1 m in the x direction equals
> 1 m in the y direction. Standard plot (asp = 1), and lattice plots (asp
> = "iso") have this; what does ggplot2 need?
>
> On 10/31/2010 11:31 AM, Paul Hiemstra wrote:
>> Hi Peter,
>>
>> When creating such a large amount of illustrations with the same
>> colorscale, I automatically think of lattice graphics. Under the hood
>> spplot also uses lattice graphics. Take a look at the levelplot()
>> function from lattice which produces the grid plots for spplot (if I'm
>> correct). Alternatively, I've been using ggplot now for quite a while to
>> make plots of a lot of grids. A small example says more than a thousand
>> words:
>>
>> library(ggplot2)
>> library(sp)
>>
>> data(meuse.grid)
>> summary(meuse.grid)
>>
>> # Note that I do not transform meuse.grid to SpatialPixelsDataFrame
>> # Let's make a simple grid plot
>> dum = meuse.grid[c("x","y","dist")]
>> ggplot(aes(x = x, y = y, fill = dist), data = dum) + geom_tile()
>>
>> # Let's make a few more attributes to the grid
>> # could be measurements on other dates for example
>> new_atts = do.call("cbind", lapply(1:100, function(num) dum$dist +
>> runif(dum$dist)))
>> summary(new_atts)
>> dum = data.frame(cbind(dum, new_atts))
>>
>> # Important step now is to
>> # restructure the data
>> dum_ggplot = melt(dum, id.vars = c("x","y"))
>>
>> # Now make a plot using dum_ggplot
>> # of 'x' and 'y' using value as a 'fill'
>> # with a plot per 'variable', can take a minute to plot
>> ggplot(aes(x = x, y = y, fill = value), data = dum_ggplot) + geom_tile()
>> + facet_wrap(~variable) +
>> scale_x_continuous('', labels = NA, breaks = NA) +
>> scale_y_continuous('', labels = NA, breaks = NA) +
>> opts(aspect.ratio = 1)
>> # These last two lines get rid of the labels on the axes and set aspect
>> ratio to 1
>>
>> Now you have a plot with 101 maps with the same colorscale, with ggplot
>> doing all the hard work. It takes some time to get the hang of ggplot,
>> but I think it is worth the investment, also for spatial plots.
>>
>> cheers and hope this helps,
>> Paul
>>
>> On 10/28/2010 09:12 PM, Peter Larson wrote:
>>> Hello!
>>>
>>> I have a problem.
>>>
>>> I am using IDW to interpolate a daily series of geospatial
>>> observations. Thus, I want to produce a large number of sequential
>>> maps.
>>>
>>> I want them to all represent the same color scale. Is there any way to
>>> fix the color scale so that it is the same for all the plots?
>>>
>>> Thanks,
>>>
>>> Pete
>>>
>>> _______________________________________________
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>>> R-sig-Geo@stat.math.ethz.ch
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>>>
>>
>>
>
> --
> Edzer Pebesma
> Institute for Geoinformatics (ifgi), University of Münster
> Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251
> 8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de
> http://www.52north.org/geostatistics e.pebe...@wwu.de
>
> _______________________________________________
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>
--
Assistant Professor / Dobelman Family Junior Chair
Department of Statistics / Rice University
http://had.co.nz/
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