I am trying to plot a heat map or color intensity using data from a numpy array using rpy2 and a grid. I am using python 2.6.2, R 2.10.1, rpy2 2.1.9, not sure which version of the lattice. I got it working perfectly, except that I need to change the default lattice setting for the color ramp used to plot the levels of the corresponding variable (z). In particular, I want a grayscale instead of the default magenta punch. Here is the code for creating a dummy frame and creating a gray scale scale for vanilla R:
library(lattice)
x <- rep(seq(1,10), each=10)
y <- rep(seq(1,10), 10)
z <- abs(rnorm(100))
z <- z/max(z)
df <- data.frame(x=x, y=y, z=z)
grayvector <- gray(seq(0,1,1/100))
foo <- levelplot(z ~ x * y, data=df, col.regions = grayvector)
print foo
With rpy2, I cannot set the col.regions argument. According to the documentation, rpy2 should convert any. characters in the arguments to _. However, this does not work, since using col_regions ignores the argument. Here is the python code that creates levelplot, but without shades of gray:
from __future__ import division
import rpy2.robjects as ro
from rpy2.robjects.packages import importr
r = ro.r
lattice = importr("lattice")
grayvector = r.gray( r.seq(0, 1, 1/100))
x = r.rep(r.seq(1,10), each=10)
y = r.rep(r.seq(1,10), 10)
z = r.abs(r.rnorm(100))
df = {'x': x, 'y' :y, 'z':z}
df = ro.DataFrame(foo)
formula = ro.Formula('z ~ x * y')
formula.getenvironment()['z'] = df.rx2('z')
formula.getenvironment()['y'] = df.rx2('y')
formula.getenvironment()['z'] = df.rx2('z')
foo = lattice.levelplot(formula, data=df, col_regions = grayvector)
print foo
Does anyone know how to use lattice function arguments with. in them in rpy2?