Contents

Installation

>cd $BISICLES_HOME/BISICLES/code
>R CMD INSTALL libamrfile

require libamrfile

amr.load, amr.free, amr.free.all

amrID1 <- amr.load("plot1.2d.hdf5") #load plot1 data
amrID2 <- amr.load("plot2.2d.hdf5") #load plot2 data
foo(amrID1,amrID2) #some function that acesses data from plot1 and plot2
amr.free(amrID1) #free plot1 data from memory 
baz(amrID1) # would fail, since this memory was freed
bar(amrID2) # ought to succeed, since plot2 is still in memory
amr.free.all() #any remaining memory is freed

amr.read.box

require(libamrfile)
amrID <- amr.load("plot.amundsen.2d.hdf5")


#read a box of thickness data from level 0
#first, determine the domain corners
dom = amr.query.domaincorners(amrID,lev=0)
b0 <- amr.read.box(amrID,lev=0,lo=dom$lo,hi=dom$hi,comp="thickness")


#read a box of thickness data from level 0. some of this data
#will be copied from level 0, other data will be from finer levels

#here we use piecewise interpolation, use interpolation_order=1 for linear
b1 <- amr.read.box(amrID,lev=1,lo=c(50,50),hi=c(150,150),comp="thickness",interpolation_order=0)


#free up memory storing the the amr data
amr.free(amrID)


#plot box data 
par(mfrow=c(1,1))
thkzl <- c(1,4000.0) #suitable range for thickness data
thkcol <- topo.colors(128)

#low res data
image(b0$x,b0$y,b0$v,zlim=thkzl,col=thkcol,xlab="x (m)", ylab="y (m)")
contour(b0$x,b0$y,b0$v,add=TRUE,lev=c(0,500,1000,1500,2000))

#paste the higher res data on top
image(b1$x,b1$y,b1$v,add=TRUE,zlim=thkzl,col=thkcol)
contour(b1$x,b1$y,b1$v,add=TRUE,lev=c(0,500,1000,1500,2000))
#draw a border round the high res box
dx = b1$x[2] - b1$x[1]
rect(min(b1$x)-dx/2, min(b1$y)-dx/2,max(b1$x)+dx/2, max(b1$y)+ dx/2,border="pink")

amr.free.all()

The resulting figure should show a color-map and contour plot of ice thickness, with a high resolution box

> cd $BISICLES_HOME/BISICLES/code/libamrfile
> make libamrfile.so 

Python then needs to know where to look for this library and the modules that access it. Set the relevant environment variables : assuming bash

> export LD_LIBRARY_PATH=$BISICLES_HOME/BISICLES/code/libamrfile:$LD_LIBRARY_PATH
> export PYTHONPATH=$BISICLES_HOME/BISICLES/code/libamrfile/python/AMRFile:$PYTHONPATH

The Python package is called amrfile, so far it has one module (io), which can be imported in the usual manner

Python 2.7.4 (default, Apr 30 2013, 14:13:25) 
[GCC 4.7.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from amrfile import io as amrio

load, free, freeAll

>>> from amrfile import io as amrio
>>> #load a file and create a lookup
>>> amrID1 = amrio.load("plot1.2d.hdf5")
>>> amrID2 = amrio.load("plot1.2d.hdf5")
>>> #operations should be able to access plot1 and plot2 data through amrID1 and amrDI2
>>> amrio.free(amrID1)
>>> #operations should no longer able to access plot1 data through amrID1
>>> amrio.freeAll()
>>> #operations should no longer able to access any data

readBox2D

The easiest way to plot maps and integrate quantities of interest is through the the readBox2D function. It allows the user to specify a rectangular box, defined as a grid on one of the AMR levels, which will be filled with uniform resolution data derived from AMR data. Some data might be piecewise or linearly interpolated from a coarser resolution part of the mesh, other data could be averaged from finer resolution regions.

The example code below assumes a file named plot.amundsen.2d.hdf5 is in the current working directory

from amrfile import io as amrio
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as col
import matplotlib.patches as pat

amrID = amrio.load("plot.amundsen.2d.hdf5")

thkcomp = "thickness"
thklim = col.Normalize(0.0,4000.0) # limits for thickness colormap
thkc = [0,1000,1500,2000]
#read a box of thickness data at the lowest resolution
level = 0
#first, work out the domain corners
lo,hi = amrio.queryDomainCorners(amrID, level)
order = 0 # interpolation order, 0 for piecewise constant, 1 for linear
x0,y0,thk0 = amrio.readBox2D(amrID, level, lo, hi, thkcomp, order)

#set up figure axes
asp = (max(y0)-min(y0))/(max(x0)-min(x0))
fig = plt.figure(1,figsize=(6, 6*asp))
plt.xlim (min(x0),max(x0))
plt.ylim (min(y0),max(y0))
plt.xticks([0,250e+3,500e+3])
plt.yticks([0,250e+3,500e+3],rotation=90)

#color and contour plot
fig = plt.pcolormesh(x0,y0,thk0,norm=thklim,figure=fig)
cs = plt.contour(x0,y0,thk0,thkc,figure=fig,norm=thklim,colors='black')

plt.clabel(cs, inline=1, fontsize=10)
#read thickness data at level 1 resolution
lo = [50,50]
hi = [150,150]
level = 1
x1,y1,thk1 = amrio.readBox2D(amrID, level, lo, hi, thkcomp, order)
plt.pcolormesh(x1,y1,thk1,figure=fig,norm=thklim)
plt.contour(x1,y1,thk1,thkc,figure=fig,norm=thklim,colors='black')

#rectangle around the highres area
dx = x1[1] - x1[0]
c=[min(x1)-dx/2.0,min(y1)-dx/2.0]
w = max(x1)-min(x1) + dx/2.0
h = max(y1)-min(y1) + dx/2.0
plt.gca().add_patch(pat.Rectangle((min(x1)-dx/2.0,min(y1)-dx/2.0) , w, h, edgecolor = 'pink', fill=False))
plt.savefig("libamrfile_python.png")
amrio.free(amrID)

The resulting figure should show a color-map and contour plot of ice thickness, with a high resolution box

MATLAB access is through a collection of functions that interface with the shared library (libamrfile.so). First, the library needs to be built

> cd $BISICLES_HOME/BISICLES/code/libamrfile
> make libamrfile.so