Dear Contributors, I have a data of the form: Lat Lon 30.1426 104.7854 30.5622 105.0837 30.0966 104.6213 29.9795 104.8430 39.2802 147.7295 30.2469 104.6543 26.4428 157.7293 29.4782 104.5590 32.3839 105.3293 26.4746 157.8411 25.1014 159.6959 25.1242 159.6558 30.1607 104.9100 31.4900 -71.8919 43.3655 -74.9994 30.0811 104.8462 29.0912 -85.5138 26.6204 -80.9342 31.5462 -71.9638 26.8619 97.3844 30.2534 104.6134 29.9311 -85.3434 26.1524 159.6806 26.5112 158.0233 26.5441 158.0565 27.8901 -105.8554 30.3175 104.7135 26.4822 157.6127 30.1887 104.5986 29.5058 104.5661 26.4010 157.5749 30.2281 104.7585 31.4556 110.5619 30.1700 104.5861 26.3911 157.4776 30.6493 104.9949 30.2209 104.6629 26.0488 97.3608 30.2142 104.8023 30.1806 104.8158 25.2107 160.1690 30.6708 104.9385 30.4152 104.7002 30.2446 104.7804 29.5760 -85.1535 26.4484 92.4312 26.3914 157.4189 26.3986 157.4421 30.4903 -88.2271 30.6727 104.8768 30.2518 104.6466 41.6979 -78.4136 33.7575 72.1089 26.8333 -80.9485 25.3103 124.0978 30.1742 104.7554 30.6345 104.9739 30.2075 104.7960 30.2226 104.7517 30.5948 105.0532. The record is for lightning flashes in the continental U.S. and surrounding waters within the latitudinal band between 258 and 458N. I want to display the result in x-y co-ordinate plot. However, the data is very large such that when plotted, everything just appeared blurred. Is there a way of using color codes to indicate the regions of higher or lower flash densities? I can attach the plot I generated but I am not sure if the moderator will allow it to go with this. I will send it in a separate email if required. Thank you so much for sparing your time. Best Ogbos
Yes, there are many ways to do this. Search rseek.org for "2d density plots". Also check the CRAN "Spatial" task view. Also see the kde2d function in the MASS package and especially the examples there that use the image() function to plot densities. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Sun, Dec 9, 2018 at 7:50 AM Ogbos Okike <giftedlife2014 at gmail.com> wrote:> Dear Contributors, > > I have a data of the form: > Lat Lon > 30.1426 104.7854 > 30.5622 105.0837 > 30.0966 104.6213 > 29.9795 104.8430 > 39.2802 147.7295 > 30.2469 104.6543 > 26.4428 157.7293 > 29.4782 104.5590 > 32.3839 105.3293 > 26.4746 157.8411 > 25.1014 159.6959 > 25.1242 159.6558 > 30.1607 104.9100 > 31.4900 -71.8919 > 43.3655 -74.9994 > 30.0811 104.8462 > 29.0912 -85.5138 > 26.6204 -80.9342 > 31.5462 -71.9638 > 26.8619 97.3844 > 30.2534 104.6134 > 29.9311 -85.3434 > 26.1524 159.6806 > 26.5112 158.0233 > 26.5441 158.0565 > 27.8901 -105.8554 > 30.3175 104.7135 > 26.4822 157.6127 > 30.1887 104.5986 > 29.5058 104.5661 > 26.4010 157.5749 > 30.2281 104.7585 > 31.4556 110.5619 > 30.1700 104.5861 > 26.3911 157.4776 > 30.6493 104.9949 > 30.2209 104.6629 > 26.0488 97.3608 > 30.2142 104.8023 > 30.1806 104.8158 > 25.2107 160.1690 > 30.6708 104.9385 > 30.4152 104.7002 > 30.2446 104.7804 > 29.5760 -85.1535 > 26.4484 92.4312 > 26.3914 157.4189 > 26.3986 157.4421 > 30.4903 -88.2271 > 30.6727 104.8768 > 30.2518 104.6466 > 41.6979 -78.4136 > 33.7575 72.1089 > 26.8333 -80.9485 > 25.3103 124.0978 > 30.1742 104.7554 > 30.6345 104.9739 > 30.2075 104.7960 > 30.2226 104.7517 > 30.5948 105.0532. > The record is for lightning flashes in the continental U.S. and > surrounding waters within the latitudinal band between > 258 and 458N. > > I want to display the result in x-y co-ordinate plot. However, the > data is very large such that when plotted, everything just appeared > blurred. > > > Is there a way of using color codes to indicate the regions of higher > or lower flash densities? > > I can attach the plot I generated but I am not sure if the moderator > will allow it to go with this. > > I will send it in a separate email if required. > > Thank you so much for sparing your time. > > Best > Ogbos > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Hi Ogbos,
Here is a slight modification of a method I use to display trip
density on a map:
oolt<-read.table(text="Lat Lon
30.1426 104.7854
30.5622 105.0837
30.0966 104.6213
29.9795 104.8430
39.2802 147.7295
30.2469 104.6543
26.4428 157.7293
29.4782 104.5590
32.3839 105.3293
26.4746 157.8411
25.1014 159.6959
25.1242 159.6558
30.1607 104.9100
31.4900 -71.8919
43.3655 -74.9994
30.0811 104.8462
29.0912 -85.5138
26.6204 -80.9342
31.5462 -71.9638
26.8619 97.3844
30.2534 104.6134
29.9311 -85.3434
26.1524 159.6806
26.5112 158.0233
26.5441 158.0565
27.8901 -105.8554
30.3175 104.7135
26.4822 157.6127
30.1887 104.5986
29.5058 104.5661
26.4010 157.5749
30.2281 104.7585
31.4556 110.5619
30.1700 104.5861
26.3911 157.4776
30.6493 104.9949
30.2209 104.6629
26.0488 97.3608
30.2142 104.8023
30.1806 104.8158
25.2107 160.1690
30.6708 104.9385
30.4152 104.7002
30.2446 104.7804
29.5760 -85.1535
26.4484 92.4312
26.3914 157.4189
26.3986 157.4421
30.4903 -88.2271
30.6727 104.8768
30.2518 104.6466
41.6979 -78.4136
33.7575 72.1089
26.8333 -80.9485
25.3103 124.0978
30.1742 104.7554
30.6345 104.9739
30.2075 104.7960
30.2226 104.7517
30.5948 105.0532",
header=TRUE)
latlim<-c(20,45)
lonlim<-c(-90,160)
latbreaks<-seq(latlim[1],latlim[2],by=5)
lonbreaks<-seq(lonlim[1],lonlim[2],by=10)
mids<-function(x) {
lenx<-length(x)
return((x[1:(lenx-1)]+x[2:lenx])/2)
}
lonmids<-mids(lonbreaks)
latmids<-mids(latbreaks)
oolt$loncuts<-cut(oolt$Lon,lonbreaks)
oolt$latcuts<-cut(oolt$Lat,latbreaks)
counts<-table(oolt$latcuts,oolt$loncuts)
library(plotrix)
countcol<-color.scale(counts,extremes=c("blue","red"))
map("world",xlim=c(-90,160),ylim=c(20,45))
for(lon in 1:length(lonmids)) {
for(lat in 1:length(latmids)) {
if(counts[lat,lon] > 0)
draw.circle(lonmids[lon],latmids[lat],radius=sqrt(counts[lat,lon]),
border=countcol[lat,lon],col=countcol[lat,lon])
}
}
If you have very large counts in some places you may need to adjust
the radius of the circles.
Jim
On Mon, Dec 10, 2018 at 2:50 AM Ogbos Okike <giftedlife2014 at gmail.com>
wrote:>
> Dear Contributors,
>
> I have a data of the form:
> Lat Lon
> 30.1426 104.7854
> 30.5622 105.0837
> 30.0966 104.6213
> 29.9795 104.8430
> 39.2802 147.7295
> 30.2469 104.6543
> 26.4428 157.7293
> 29.4782 104.5590
> 32.3839 105.3293
> 26.4746 157.8411
> 25.1014 159.6959
> 25.1242 159.6558
> 30.1607 104.9100
> 31.4900 -71.8919
> 43.3655 -74.9994
> 30.0811 104.8462
> 29.0912 -85.5138
> 26.6204 -80.9342
> 31.5462 -71.9638
> 26.8619 97.3844
> 30.2534 104.6134
> 29.9311 -85.3434
> 26.1524 159.6806
> 26.5112 158.0233
> 26.5441 158.0565
> 27.8901 -105.8554
> 30.3175 104.7135
> 26.4822 157.6127
> 30.1887 104.5986
> 29.5058 104.5661
> 26.4010 157.5749
> 30.2281 104.7585
> 31.4556 110.5619
> 30.1700 104.5861
> 26.3911 157.4776
> 30.6493 104.9949
> 30.2209 104.6629
> 26.0488 97.3608
> 30.2142 104.8023
> 30.1806 104.8158
> 25.2107 160.1690
> 30.6708 104.9385
> 30.4152 104.7002
> 30.2446 104.7804
> 29.5760 -85.1535
> 26.4484 92.4312
> 26.3914 157.4189
> 26.3986 157.4421
> 30.4903 -88.2271
> 30.6727 104.8768
> 30.2518 104.6466
> 41.6979 -78.4136
> 33.7575 72.1089
> 26.8333 -80.9485
> 25.3103 124.0978
> 30.1742 104.7554
> 30.6345 104.9739
> 30.2075 104.7960
> 30.2226 104.7517
> 30.5948 105.0532.
> The record is for lightning flashes in the continental U.S. and
> surrounding waters within the latitudinal band between
> 258 and 458N.
>
> I want to display the result in x-y co-ordinate plot. However, the
> data is very large such that when plotted, everything just appeared
> blurred.
>
>
> Is there a way of using color codes to indicate the regions of higher
> or lower flash densities?
>
> I can attach the plot I generated but I am not sure if the moderator
> will allow it to go with this.
>
> I will send it in a separate email if required.
>
> Thank you so much for sparing your time.
>
> Best
> Ogbos
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
Dear Jim, I used a bit of my data in my attempt to follow the code. I got the attached plot after some tweaks. I would like to add horizontal color bar legend that could be used to explain the number of lightning counts at different points on the latitude band as plotted. Thank you Warm regards Ogbos On Sun, Dec 9, 2018 at 9:46 PM Jim Lemon <drjimlemon at gmail.com> wrote:> > Hi Ogbos, > Here is a slight modification of a method I use to display trip > density on a map: > > oolt<-read.table(text="Lat Lon > 30.1426 104.7854 > 30.5622 105.0837 > 30.0966 104.6213 > 29.9795 104.8430 > 39.2802 147.7295 > 30.2469 104.6543 > 26.4428 157.7293 > 29.4782 104.5590 > 32.3839 105.3293 > 26.4746 157.8411 > 25.1014 159.6959 > 25.1242 159.6558 > 30.1607 104.9100 > 31.4900 -71.8919 > 43.3655 -74.9994 > 30.0811 104.8462 > 29.0912 -85.5138 > 26.6204 -80.9342 > 31.5462 -71.9638 > 26.8619 97.3844 > 30.2534 104.6134 > 29.9311 -85.3434 > 26.1524 159.6806 > 26.5112 158.0233 > 26.5441 158.0565 > 27.8901 -105.8554 > 30.3175 104.7135 > 26.4822 157.6127 > 30.1887 104.5986 > 29.5058 104.5661 > 26.4010 157.5749 > 30.2281 104.7585 > 31.4556 110.5619 > 30.1700 104.5861 > 26.3911 157.4776 > 30.6493 104.9949 > 30.2209 104.6629 > 26.0488 97.3608 > 30.2142 104.8023 > 30.1806 104.8158 > 25.2107 160.1690 > 30.6708 104.9385 > 30.4152 104.7002 > 30.2446 104.7804 > 29.5760 -85.1535 > 26.4484 92.4312 > 26.3914 157.4189 > 26.3986 157.4421 > 30.4903 -88.2271 > 30.6727 104.8768 > 30.2518 104.6466 > 41.6979 -78.4136 > 33.7575 72.1089 > 26.8333 -80.9485 > 25.3103 124.0978 > 30.1742 104.7554 > 30.6345 104.9739 > 30.2075 104.7960 > 30.2226 104.7517 > 30.5948 105.0532", > header=TRUE) > latlim<-c(20,45) > lonlim<-c(-90,160) > latbreaks<-seq(latlim[1],latlim[2],by=5) > lonbreaks<-seq(lonlim[1],lonlim[2],by=10) > > mids<-function(x) { > lenx<-length(x) > return((x[1:(lenx-1)]+x[2:lenx])/2) > } > lonmids<-mids(lonbreaks) > latmids<-mids(latbreaks) > oolt$loncuts<-cut(oolt$Lon,lonbreaks) > oolt$latcuts<-cut(oolt$Lat,latbreaks) > counts<-table(oolt$latcuts,oolt$loncuts) > library(plotrix) > countcol<-color.scale(counts,extremes=c("blue","red")) > map("world",xlim=c(-90,160),ylim=c(20,45)) > for(lon in 1:length(lonmids)) { > for(lat in 1:length(latmids)) { > if(counts[lat,lon] > 0) > draw.circle(lonmids[lon],latmids[lat],radius=sqrt(counts[lat,lon]), > border=countcol[lat,lon],col=countcol[lat,lon]) > } > } > > If you have very large counts in some places you may need to adjust > the radius of the circles. > > Jim > On Mon, Dec 10, 2018 at 2:50 AM Ogbos Okike <giftedlife2014 at gmail.com> wrote: > > > > Dear Contributors, > > > > I have a data of the form: > > Lat Lon > > 30.1426 104.7854 > > 30.5622 105.0837 > > 30.0966 104.6213 > > 29.9795 104.8430 > > 39.2802 147.7295 > > 30.2469 104.6543 > > 26.4428 157.7293 > > 29.4782 104.5590 > > 32.3839 105.3293 > > 26.4746 157.8411 > > 25.1014 159.6959 > > 25.1242 159.6558 > > 30.1607 104.9100 > > 31.4900 -71.8919 > > 43.3655 -74.9994 > > 30.0811 104.8462 > > 29.0912 -85.5138 > > 26.6204 -80.9342 > > 31.5462 -71.9638 > > 26.8619 97.3844 > > 30.2534 104.6134 > > 29.9311 -85.3434 > > 26.1524 159.6806 > > 26.5112 158.0233 > > 26.5441 158.0565 > > 27.8901 -105.8554 > > 30.3175 104.7135 > > 26.4822 157.6127 > > 30.1887 104.5986 > > 29.5058 104.5661 > > 26.4010 157.5749 > > 30.2281 104.7585 > > 31.4556 110.5619 > > 30.1700 104.5861 > > 26.3911 157.4776 > > 30.6493 104.9949 > > 30.2209 104.6629 > > 26.0488 97.3608 > > 30.2142 104.8023 > > 30.1806 104.8158 > > 25.2107 160.1690 > > 30.6708 104.9385 > > 30.4152 104.7002 > > 30.2446 104.7804 > > 29.5760 -85.1535 > > 26.4484 92.4312 > > 26.3914 157.4189 > > 26.3986 157.4421 > > 30.4903 -88.2271 > > 30.6727 104.8768 > > 30.2518 104.6466 > > 41.6979 -78.4136 > > 33.7575 72.1089 > > 26.8333 -80.9485 > > 25.3103 124.0978 > > 30.1742 104.7554 > > 30.6345 104.9739 > > 30.2075 104.7960 > > 30.2226 104.7517 > > 30.5948 105.0532. > > The record is for lightning flashes in the continental U.S. and > > surrounding waters within the latitudinal band between > > 258 and 458N. > > > > I want to display the result in x-y co-ordinate plot. However, the > > data is very large such that when plotted, everything just appeared > > blurred. > > > > > > Is there a way of using color codes to indicate the regions of higher > > or lower flash densities? > > > > I can attach the plot I generated but I am not sure if the moderator > > will allow it to go with this. > > > > I will send it in a separate email if required. > > > > Thank you so much for sparing your time. > > > > Best > > Ogbos > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code.-------------- next part -------------- A non-text attachment was scrubbed... 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Hi Ogbos, I have been off the air for a couple of days. Look at the color.legend function in the plotrix package. Jim On Tue, Dec 11, 2018 at 12:39 PM Ogbos Okike <giftedlife2014 at gmail.com> wrote:> > Dear Jim, > I am still having trouble with the colour code. I await your help when > you are less busy. > > Thank you. > Best > Ogbos > On Mon, Dec 10, 2018 at 6:25 AM Ogbos Okike <giftedlife2014 at gmail.com> wrote: > > > > Dear Jim, > > > > I used a bit of my data in my attempt to follow the code. > > > > I got the attached plot after some tweaks. > > > > I would like to add horizontal color bar legend that could be used to > > explain the number of lightning counts at different points on the > > latitude band as plotted. > > > > Thank you > > Warm regards > > Ogbos > > > > On Sun, Dec 9, 2018 at 9:46 PM Jim Lemon <drjimlemon at gmail.com> wrote: > > > > > > Hi Ogbos, > > > Here is a slight modification of a method I use to display trip > > > density on a map: > > > > > > oolt<-read.table(text="Lat Lon > > > 30.1426 104.7854 > > > 30.5622 105.0837 > > > 30.0966 104.6213 > > > 29.9795 104.8430 > > > 39.2802 147.7295 > > > 30.2469 104.6543 > > > 26.4428 157.7293 > > > 29.4782 104.5590 > > > 32.3839 105.3293 > > > 26.4746 157.8411 > > > 25.1014 159.6959 > > > 25.1242 159.6558 > > > 30.1607 104.9100 > > > 31.4900 -71.8919 > > > 43.3655 -74.9994 > > > 30.0811 104.8462 > > > 29.0912 -85.5138 > > > 26.6204 -80.9342 > > > 31.5462 -71.9638 > > > 26.8619 97.3844 > > > 30.2534 104.6134 > > > 29.9311 -85.3434 > > > 26.1524 159.6806 > > > 26.5112 158.0233 > > > 26.5441 158.0565 > > > 27.8901 -105.8554 > > > 30.3175 104.7135 > > > 26.4822 157.6127 > > > 30.1887 104.5986 > > > 29.5058 104.5661 > > > 26.4010 157.5749 > > > 30.2281 104.7585 > > > 31.4556 110.5619 > > > 30.1700 104.5861 > > > 26.3911 157.4776 > > > 30.6493 104.9949 > > > 30.2209 104.6629 > > > 26.0488 97.3608 > > > 30.2142 104.8023 > > > 30.1806 104.8158 > > > 25.2107 160.1690 > > > 30.6708 104.9385 > > > 30.4152 104.7002 > > > 30.2446 104.7804 > > > 29.5760 -85.1535 > > > 26.4484 92.4312 > > > 26.3914 157.4189 > > > 26.3986 157.4421 > > > 30.4903 -88.2271 > > > 30.6727 104.8768 > > > 30.2518 104.6466 > > > 41.6979 -78.4136 > > > 33.7575 72.1089 > > > 26.8333 -80.9485 > > > 25.3103 124.0978 > > > 30.1742 104.7554 > > > 30.6345 104.9739 > > > 30.2075 104.7960 > > > 30.2226 104.7517 > > > 30.5948 105.0532", > > > header=TRUE) > > > latlim<-c(20,45) > > > lonlim<-c(-90,160) > > > latbreaks<-seq(latlim[1],latlim[2],by=5) > > > lonbreaks<-seq(lonlim[1],lonlim[2],by=10) > > > > > > mids<-function(x) { > > > lenx<-length(x) > > > return((x[1:(lenx-1)]+x[2:lenx])/2) > > > } > > > lonmids<-mids(lonbreaks) > > > latmids<-mids(latbreaks) > > > oolt$loncuts<-cut(oolt$Lon,lonbreaks) > > > oolt$latcuts<-cut(oolt$Lat,latbreaks) > > > counts<-table(oolt$latcuts,oolt$loncuts) > > > library(plotrix) > > > countcol<-color.scale(counts,extremes=c("blue","red")) > > > map("world",xlim=c(-90,160),ylim=c(20,45)) > > > for(lon in 1:length(lonmids)) { > > > for(lat in 1:length(latmids)) { > > > if(counts[lat,lon] > 0) > > > draw.circle(lonmids[lon],latmids[lat],radius=sqrt(counts[lat,lon]), > > > border=countcol[lat,lon],col=countcol[lat,lon]) > > > } > > > } > > > > > > If you have very large counts in some places you may need to adjust > > > the radius of the circles. > > > > > > Jim > > > On Mon, Dec 10, 2018 at 2:50 AM Ogbos Okike <giftedlife2014 at gmail.com> wrote: > > > > > > > > Dear Contributors, > > > > > > > > I have a data of the form: > > > > Lat Lon > > > > 30.1426 104.7854 > > > > 30.5622 105.0837 > > > > 30.0966 104.6213 > > > > 29.9795 104.8430 > > > > 39.2802 147.7295 > > > > 30.2469 104.6543 > > > > 26.4428 157.7293 > > > > 29.4782 104.5590 > > > > 32.3839 105.3293 > > > > 26.4746 157.8411 > > > > 25.1014 159.6959 > > > > 25.1242 159.6558 > > > > 30.1607 104.9100 > > > > 31.4900 -71.8919 > > > > 43.3655 -74.9994 > > > > 30.0811 104.8462 > > > > 29.0912 -85.5138 > > > > 26.6204 -80.9342 > > > > 31.5462 -71.9638 > > > > 26.8619 97.3844 > > > > 30.2534 104.6134 > > > > 29.9311 -85.3434 > > > > 26.1524 159.6806 > > > > 26.5112 158.0233 > > > > 26.5441 158.0565 > > > > 27.8901 -105.8554 > > > > 30.3175 104.7135 > > > > 26.4822 157.6127 > > > > 30.1887 104.5986 > > > > 29.5058 104.5661 > > > > 26.4010 157.5749 > > > > 30.2281 104.7585 > > > > 31.4556 110.5619 > > > > 30.1700 104.5861 > > > > 26.3911 157.4776 > > > > 30.6493 104.9949 > > > > 30.2209 104.6629 > > > > 26.0488 97.3608 > > > > 30.2142 104.8023 > > > > 30.1806 104.8158 > > > > 25.2107 160.1690 > > > > 30.6708 104.9385 > > > > 30.4152 104.7002 > > > > 30.2446 104.7804 > > > > 29.5760 -85.1535 > > > > 26.4484 92.4312 > > > > 26.3914 157.4189 > > > > 26.3986 157.4421 > > > > 30.4903 -88.2271 > > > > 30.6727 104.8768 > > > > 30.2518 104.6466 > > > > 41.6979 -78.4136 > > > > 33.7575 72.1089 > > > > 26.8333 -80.9485 > > > > 25.3103 124.0978 > > > > 30.1742 104.7554 > > > > 30.6345 104.9739 > > > > 30.2075 104.7960 > > > > 30.2226 104.7517 > > > > 30.5948 105.0532. > > > > The record is for lightning flashes in the continental U.S. and > > > > surrounding waters within the latitudinal band between > > > > 258 and 458N. > > > > > > > > I want to display the result in x-y co-ordinate plot. However, the > > > > data is very large such that when plotted, everything just appeared > > > > blurred. > > > > > > > > > > > > Is there a way of using color codes to indicate the regions of higher > > > > or lower flash densities? > > > > > > > > I can attach the plot I generated but I am not sure if the moderator > > > > will allow it to go with this. > > > > > > > > I will send it in a separate email if required. > > > > > > > > Thank you so much for sparing your time. > > > > > > > > Best > > > > Ogbos > > > > > > > > ______________________________________________ > > > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > > > https://stat.ethz.ch/mailman/listinfo/r-help > > > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > > > > and provide commented, minimal, self-contained, reproducible code.
Dear All,
Thank you for your advice.
I have looked at the plotrix package and with what I gathered, I
tinkered with the code below and obtain the attached graph:
oolt<-read.table("QUERY2",col.names=c("Lat","Lon"))
latlim<-c(20,45)
lonlim<-c(-180,180)
latbreaks<-seq(latlim[1],latlim[2],by=5)
lonbreaks<-seq(lonlim[1],lonlim[2],by=10)
mids<-function(x) {
lenx<-length(x)
return((x[1:(lenx-1)]+x[2:lenx])/2)
}
lonmids<-mids(lonbreaks)
latmids<-mids(latbreaks)
oolt$loncuts<-cut(oolt$Lon,lonbreaks)
oolt$latcuts<-cut(oolt$Lat,latbreaks)
counts<-table(oolt$latcuts,oolt$loncuts)
png("test.png")
library(plotrix)
countcol<-color.scale(counts,extremes=c("blue","red"))
library(maps)
map("world",xlim=c(-180,180),ylim=c(20,45))
w = map("world")
for(lon in 1:length(lonmids)) {
for(lat in 1:length(latmids)) {
if(counts[lat,lon] > 0)
draw.circle(lonmids[lon],latmids[lat],radius=sqrt(counts[lat,lon]),
border=countcol[lat,lon],col=countcol[lat,lon])
}
}
box()
axis(1)
axis(2)
x<-seq(-180,180,30)
y<-seq(-90,90,30)
nx = 12
ny = 6
grid(nx,ny,col =
"red",lty="dotted",lwd=par("lwd"),equilogs=TRUE)
testcol<-color.gradient(c(10,30),0,c(30,10),nslices=5)
color.legend(-180,-130,100,-150,countcol,testcol,gradient="x")
I now have the horizontal color legend.
But I have two major problems still.
(1) The black line on top of the color bar is meaningless and I want it go.
(2) I want the numerical values plotted to appear on the color bar
(see the color.legend.png attached please) such that it can be used to
interpret the map.
I would be most grateful for any further assistance.
Very best wishes
Ogbos
On Tue, Dec 11, 2018 at 11:14 AM Jim Lemon <drjimlemon at gmail.com>
wrote:>
> Hi Ogbos,
> I have been off the air for a couple of days. Look at the color.legend
> function in the plotrix package.
>
> Jim
> On Tue, Dec 11, 2018 at 12:39 PM Ogbos Okike <giftedlife2014 at
gmail.com> wrote:
> >
> > Dear Jim,
> > I am still having trouble with the colour code. I await your help when
> > you are less busy.
> >
> > Thank you.
> > Best
> > Ogbos
> > On Mon, Dec 10, 2018 at 6:25 AM Ogbos Okike <giftedlife2014 at
gmail.com> wrote:
> > >
> > > Dear Jim,
> > >
> > > I used a bit of my data in my attempt to follow the code.
> > >
> > > I got the attached plot after some tweaks.
> > >
> > > I would like to add horizontal color bar legend that could be
used to
> > > explain the number of lightning counts at different points on the
> > > latitude band as plotted.
> > >
> > > Thank you
> > > Warm regards
> > > Ogbos
> > >
> > > On Sun, Dec 9, 2018 at 9:46 PM Jim Lemon <drjimlemon at
gmail.com> wrote:
> > > >
> > > > Hi Ogbos,
> > > > Here is a slight modification of a method I use to display
trip
> > > > density on a map:
> > > >
> > > > oolt<-read.table(text="Lat Lon
> > > > 30.1426 104.7854
> > > > 30.5622 105.0837
> > > > 30.0966 104.6213
> > > > 29.9795 104.8430
> > > > 39.2802 147.7295
> > > > 30.2469 104.6543
> > > > 26.4428 157.7293
> > > > 29.4782 104.5590
> > > > 32.3839 105.3293
> > > > 26.4746 157.8411
> > > > 25.1014 159.6959
> > > > 25.1242 159.6558
> > > > 30.1607 104.9100
> > > > 31.4900 -71.8919
> > > > 43.3655 -74.9994
> > > > 30.0811 104.8462
> > > > 29.0912 -85.5138
> > > > 26.6204 -80.9342
> > > > 31.5462 -71.9638
> > > > 26.8619 97.3844
> > > > 30.2534 104.6134
> > > > 29.9311 -85.3434
> > > > 26.1524 159.6806
> > > > 26.5112 158.0233
> > > > 26.5441 158.0565
> > > > 27.8901 -105.8554
> > > > 30.3175 104.7135
> > > > 26.4822 157.6127
> > > > 30.1887 104.5986
> > > > 29.5058 104.5661
> > > > 26.4010 157.5749
> > > > 30.2281 104.7585
> > > > 31.4556 110.5619
> > > > 30.1700 104.5861
> > > > 26.3911 157.4776
> > > > 30.6493 104.9949
> > > > 30.2209 104.6629
> > > > 26.0488 97.3608
> > > > 30.2142 104.8023
> > > > 30.1806 104.8158
> > > > 25.2107 160.1690
> > > > 30.6708 104.9385
> > > > 30.4152 104.7002
> > > > 30.2446 104.7804
> > > > 29.5760 -85.1535
> > > > 26.4484 92.4312
> > > > 26.3914 157.4189
> > > > 26.3986 157.4421
> > > > 30.4903 -88.2271
> > > > 30.6727 104.8768
> > > > 30.2518 104.6466
> > > > 41.6979 -78.4136
> > > > 33.7575 72.1089
> > > > 26.8333 -80.9485
> > > > 25.3103 124.0978
> > > > 30.1742 104.7554
> > > > 30.6345 104.9739
> > > > 30.2075 104.7960
> > > > 30.2226 104.7517
> > > > 30.5948 105.0532",
> > > > header=TRUE)
> > > > latlim<-c(20,45)
> > > > lonlim<-c(-90,160)
> > > > latbreaks<-seq(latlim[1],latlim[2],by=5)
> > > > lonbreaks<-seq(lonlim[1],lonlim[2],by=10)
> > > >
> > > > mids<-function(x) {
> > > > lenx<-length(x)
> > > > return((x[1:(lenx-1)]+x[2:lenx])/2)
> > > > }
> > > > lonmids<-mids(lonbreaks)
> > > > latmids<-mids(latbreaks)
> > > > oolt$loncuts<-cut(oolt$Lon,lonbreaks)
> > > > oolt$latcuts<-cut(oolt$Lat,latbreaks)
> > > > counts<-table(oolt$latcuts,oolt$loncuts)
> > > > library(plotrix)
> > > >
countcol<-color.scale(counts,extremes=c("blue","red"))
> > > > map("world",xlim=c(-90,160),ylim=c(20,45))
> > > > for(lon in 1:length(lonmids)) {
> > > > for(lat in 1:length(latmids)) {
> > > > if(counts[lat,lon] > 0)
> > > >
draw.circle(lonmids[lon],latmids[lat],radius=sqrt(counts[lat,lon]),
> > > > border=countcol[lat,lon],col=countcol[lat,lon])
> > > > }
> > > > }
> > > >
> > > > If you have very large counts in some places you may need to
adjust
> > > > the radius of the circles.
> > > >
> > > > Jim
> > > > On Mon, Dec 10, 2018 at 2:50 AM Ogbos Okike
<giftedlife2014 at gmail.com> wrote:
> > > > >
> > > > > Dear Contributors,
> > > > >
> > > > > I have a data of the form:
> > > > > Lat Lon
> > > > > 30.1426 104.7854
> > > > > 30.5622 105.0837
> > > > > 30.0966 104.6213
> > > > > 29.9795 104.8430
> > > > > 39.2802 147.7295
> > > > > 30.2469 104.6543
> > > > > 26.4428 157.7293
> > > > > 29.4782 104.5590
> > > > > 32.3839 105.3293
> > > > > 26.4746 157.8411
> > > > > 25.1014 159.6959
> > > > > 25.1242 159.6558
> > > > > 30.1607 104.9100
> > > > > 31.4900 -71.8919
> > > > > 43.3655 -74.9994
> > > > > 30.0811 104.8462
> > > > > 29.0912 -85.5138
> > > > > 26.6204 -80.9342
> > > > > 31.5462 -71.9638
> > > > > 26.8619 97.3844
> > > > > 30.2534 104.6134
> > > > > 29.9311 -85.3434
> > > > > 26.1524 159.6806
> > > > > 26.5112 158.0233
> > > > > 26.5441 158.0565
> > > > > 27.8901 -105.8554
> > > > > 30.3175 104.7135
> > > > > 26.4822 157.6127
> > > > > 30.1887 104.5986
> > > > > 29.5058 104.5661
> > > > > 26.4010 157.5749
> > > > > 30.2281 104.7585
> > > > > 31.4556 110.5619
> > > > > 30.1700 104.5861
> > > > > 26.3911 157.4776
> > > > > 30.6493 104.9949
> > > > > 30.2209 104.6629
> > > > > 26.0488 97.3608
> > > > > 30.2142 104.8023
> > > > > 30.1806 104.8158
> > > > > 25.2107 160.1690
> > > > > 30.6708 104.9385
> > > > > 30.4152 104.7002
> > > > > 30.2446 104.7804
> > > > > 29.5760 -85.1535
> > > > > 26.4484 92.4312
> > > > > 26.3914 157.4189
> > > > > 26.3986 157.4421
> > > > > 30.4903 -88.2271
> > > > > 30.6727 104.8768
> > > > > 30.2518 104.6466
> > > > > 41.6979 -78.4136
> > > > > 33.7575 72.1089
> > > > > 26.8333 -80.9485
> > > > > 25.3103 124.0978
> > > > > 30.1742 104.7554
> > > > > 30.6345 104.9739
> > > > > 30.2075 104.7960
> > > > > 30.2226 104.7517
> > > > > 30.5948 105.0532.
> > > > > The record is for lightning flashes in the continental
U.S. and
> > > > > surrounding waters within the latitudinal band between
> > > > > 258 and 458N.
> > > > >
> > > > > I want to display the result in x-y co-ordinate plot.
However, the
> > > > > data is very large such that when plotted, everything
just appeared
> > > > > blurred.
> > > > >
> > > > >
> > > > > Is there a way of using color codes to indicate the
regions of higher
> > > > > or lower flash densities?
> > > > >
> > > > > I can attach the plot I generated but I am not sure if
the moderator
> > > > > will allow it to go with this.
> > > > >
> > > > > I will send it in a separate email if required.
> > > > >
> > > > > Thank you so much for sparing your time.
> > > > >
> > > > > Best
> > > > > Ogbos
> > > > >
> > > > > ______________________________________________
> > > > > R-help at r-project.org mailing list -- To UNSUBSCRIBE
and more, see
> > > > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > > > PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> > > > > and provide commented, minimal, self-contained,
reproducible code.
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