(global-set-key (kbd "a" ) "α") ; F9 followed by a (global-set-key (kbd "b" ) "β")
mgp parameter option. The mgp
setting is defined by a three item vector wherein the first value
represents the distance of the axis labels or titles from the axes, the
second value is the distance of the tick mark labels from the axes, and
the third is the distance of the tick mark symbols from the axes. As
with the oma option discussed above, the distances are given in line widths. The defaults for the mgp setting are c(3, 1, 0). The examples below illustrate the effects of changing the various mgp values. Note: the mgp.axis() function in the Hmisc package can be used to change these settings for each axis individually.
plot(0,xaxt='n',yaxt='n',bty='n',pch='',ylab='',xlab='')plot.new()grid.newpage()grid()
proc save_vp {view_num} {
global viewpoints
if [info exists viewpoints($view_num)] {unset viewpoints($view_num)}
# get the current matricies
foreach mol [molinfo list] {
set viewpoints($view_num,$mol,0) [molinfo $mol get rotate_matrix]
set viewpoints($view_num,$mol,1) [molinfo $mol get center_matrix]
set viewpoints($view_num,$mol,2) [molinfo $mol get scale_matrix]
set viewpoints($view_num,$mol,3) [molinfo $mol get global_matrix]
}
}
proc retrieve_vp {view_num} {
global viewpoints
foreach mol [molinfo list] {
if [info exists viewpoints($view_num,$mol,0)] {
molinfo $mol set rotate_matrix $viewpoints($view_num,$mol,0)
molinfo $mol set center_matrix $viewpoints($view_num,$mol,1)
molinfo $mol set scale_matrix $viewpoints($view_num,$mol,2)
molinfo $mol set global_matrix $viewpoints($view_num,$mol,3)
} else {
puts "View $view_num was not saved"}
}
}
proc get_vp {view_num} {
global viewpoints
foreach mol [molinfo list] {
if [info exists viewpoints($view_num,$mol,0)] {
puts "global viewpoints"
puts "molinfo $mol set rotate_matrix \"$viewpoints($view_num,$mol,0)\""
puts "molinfo $mol set center_matrix \"$viewpoints($view_num,$mol,1)\""
puts "molinfo $mol set scale_matrix \"$viewpoints($view_num,$mol,2)\""
puts "molinfo $mol set global_matrix \"$viewpoints($view_num,$mol,3)\""
} else {
puts "View $view_num was not saved"}
}
}
Once you save this output (as a text file) it becomes very easy to retrieve the view even
after closing down VMD. Simply copy and paste the output of get_vp.
if { test1 } {
body1
} elseif { test2 } {
body2
} else {
bodyn
}for { set i 1 } { $i <= 10 } { incr i } {
# This will append all multiples of all numbers for the number n
# into a variable called table
set table "$table $i x $n = [expr $i \* $n]\n"
} Foreach loop#Make the list set list [list "Item 1" {Item 2} Last] set text "" foreach item $list { #Append the every item to $text set text "$text\n$item" }
#Make the list set list [list "Item 1" {Item 2} Last] set text "" foreach item $list { #Append the every item to $text set text "$text\n$item" }# initial config
coordinates alanin.pdb
temperature 0
# output params
outputname /tmp/alanin-analyze
binaryoutput no
# integrator params
timestep 1.0
# force field params
structure alanin.psf
parameters alanin.params
exclude scaled1-4
1-4scaling 1.0
switching on
switchdist 8.0
cutoff 12.0
pairlistdist 13.5
stepspercycle 20
# Atoms in group 1 have a 1 in the B column; group 2 has a 2.
pairInteraction on
pairInteractionFile pair.pdb
pairInteractionCol B
pairInteractionGroup1 1
pairInteractionGroup2 2
# First frame saved was frame 1000.
set ts 1000
coorfile open dcd /tmp/alanin.dcd
# Read all frames until nonzero is returned.
while { ![coorfile read] } {
# Set firstTimestep so our energy output has the correct TS.
firstTimestep $ts
# Compute energies and forces, but don't try to move the atoms.
run 0
incr ts 1000
}
coorfile close
names(myTable)
a<-read.csv("file.csv", header=T, sep=",")
names(a)
motility<-subset(a, Putative.orf.function=="Motility & Attachment")
write.csv(motolity, file="motility.csv")
Edit Feb 15th 2012
grep("Motility", a$Putative.orf.function)
gives the list of rows whose Putative.orf.function column contains the string "Motility".
Using this, one can get the entire row information.
df<-read.csv("file.csv", header=T, sep=",")
names(df)
> names(df)
[1] "Strain.Name" "ID" "Location"
[4] "PA.ORF" "Gene" "Gene.Abbrev."
[7] "Putative.orf.function" "Position.in.ORF" "Frame"
[10] "Genome.Position" "Transposon.Direction" "Transposon"
[13] "F.Primer.Name" "F.Primer.Seq" "F.Primer.Position"
[16] "F.Primer.Tm" "Insert...F" "R.Primer.Name"
[19] "R.Primer.Seq" "R.Primer.Position" "R.Primer.Tm"
[22] "R...Insert" "WT.PCR.Len" "Confirmed."
[25] "How.confirmed." "Notes"
> df$Strain.Name[grep("Attachment",df$Putative.orf.function)]
[1] PW10299 PW10300 PW1728 PW1729 PW1730 PW1731 PW1749 PW1750 PW1751
[10] PW1752 PW1753 PW1754 PW1755 PW1756 PW1757 PW2791 PW2792 PW2794
[19] PW2795 PW2941 PW2942 PW2943 PW2944 PW2945 PW2946 PW2947 PW2948
...
[118] PW8681 PW8682 PW9465 PW9466 PW9467 PW9468 PW9469 PW9470 PW9471 [127] PW9472 PW9473 PW9474
load xxx.pdbsudo -u pkc /usr/sbin/cupsenable HP_LaserJet_6MP