ggplot2 manually specifying colour with geom_line - r

I'm trying to plot the graph below, and want to manually specify colours.
I need to plot by genotype, since there are multiple genotypes belonging to the same Bgrnd_All, and I want them to come up separately in the lines plotted.
However, I want to colour the lines by Bgrnd_All, and specifically in the order/colour I use in scale_fill_manual.
When I do this, the values in scale_fill_manual do not overwrite the existing colour as defined in geom_line. How can I do this?
I'd be grateful for pointers.
[Data for graph below][1]https://www.dropbox.com/s/9nmu87wkh2yqfxn/summary_200_exp2.csv?dl=0
pd <- position_dodge(1)
ggplot(data=summary.200.exp2, aes(x=Time, y=Length, colour=Genotype, group=Genotype)) +
geom_errorbar(aes(ymin=Length - se, ymax=Length + se), colour="black", width=1, position=pd) +
geom_line(aes(colour=Bgrnd_All), position=pd, size =1) +
scale_x_continuous(breaks=c(0,17,22,41,89)) + #using breaks of when sampled
scale_fill_manual(values=c(Avalon="#000066",Av_A="#663399",Av_B="#339999",Cadenza="CC0033",Cad_A="FF6600",Cad_B="FF9933"))+
ylab("leaf segment width (mm)") +
xlab("Time") +
theme(axis.title = element_text(size=14,face="bold"),
axis.text = element_text(size=14),
strip.text.y = element_text(size=14))
A dput of the data:
summary.200.exp2 <- structure(list(X = 1:40,
Genotype = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L), .Label = c("4.18", "4.41", "7.50", "7.59", "8.51", "8.77", "Avalon", "Cadenza"), class = "factor"),
Time = c(0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L, 0L, 17L, 22L, 41L, 89L),
Bgrnd_All = structure(c(4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 6L), .Label = c("Av_A", "Av_B", "Avalon", "Cad_A", "Cad_B", "Cadenza"), class = "factor"),
N = c(43L, 48L, 44L, 47L, 48L, 22L, 21L, 26L, 27L, 25L, 36L, 24L, 44L, 48L, 45L, 50L, 26L, 52L, 54L, 53L, 38L, 52L, 52L, 49L, 50L, 39L, 39L, 42L, 38L, 42L, 84L, 42L, 84L, 42L, 42L, 50L, 26L, 53L, 27L, 27L),
Length = c(1.17423255813953, 1.58852083333333, 1.71263636363636, 1.86736170212766, 2.0331875, 1.07563636363636, 1.49866666666667, 1.48734615384615, 1.66796296296296, 2.15416, 1.08716666666667, 1.09858333333333, 1.24593181818182, 1.30827083333333, 1.81537777777778, 1.15672, 1.8475, 1.96815384615385, 2.01822222222222, 2.5057358490566, 1.14697368421053, 1.40276923076923, 1.49832692307692, 1.76981632653061, 2.27954, 1.18312820512821, 1.75928205128205, 1.86195238095238, 1.91426315789474, 2.26883333333333, 1.10839285714286, 1.97902380952381, 2.03271428571429, 2.15685714285714, 2.8227380952381, 1.08658, 1.68880769230769, 1.7277358490566, 1.9232962962963, 2.13466666666667),
sd = c(0.218740641945063, 0.357307960001092, 0.377931031662453, 0.416137123383518, 0.440003996899158, 0.176915784499843, 0.426273190962478, 0.305677731254037, 0.450036449932454, 0.48642939535627, 0.15212823538055, 0.175160775008132, 0.293836087650785, 0.282464815326021, 0.346608194369436, 0.211422397593258, 0.408328617659845, 0.413460118977535, 0.419730221832425, 0.508692484972064, 0.217587942685885, 0.207510416973071, 0.245473270071832, 0.377310585673427, 0.536134471785516, 0.159925670150259, 0.298319411009668, 0.338847829173593, 0.296186727462412, 0.445638589029855, 0.162594700328365, 0.308723610551514, 0.318831396748337, 0.381781291715339, 0.402059458017902, 0.167826451905484, 0.257140275994371, 0.338637947743116, 0.362428434825926, 0.343680867174096),
se = c(0.0333576351702583, 0.0515729617225566, 0.0569752467571038, 0.0606998379642952, 0.06350910651356, 0.0377185719899813, 0.0930204363959963, 0.0599483352513503, 0.0866095551712153, 0.097285879071254, 0.0253547058967583, 0.0357545434766975, 0.0442974569365289, 0.040770284291269, 0.0516692989445678, 0.0298996422065822, 0.0800798303617661, 0.0573366022820362, 0.0571180485063685, 0.0698742866122227, 0.0352974252834232, 0.0287765172534354, 0.0340410177692235, 0.053901512239061, 0.0758208641254813, 0.0256086023072023, 0.0477693365291991, 0.052285355168868, 0.0480478318490224, 0.0687635271596866, 0.0177405362346046, 0.0476370873204908, 0.0347873573697084, 0.0589101322645314, 0.0620391212561054, 0.0237342444409691, 0.0504293571163821, 0.046515499476421, 0.0697493848029077, 0.0661414137260961),
ci = c(0.0673184331863912, 0.103751416510302, 0.114901535684132, 0.122182436693452, 0.127763842564108, 0.0784400645137227, 0.194037230170767, 0.123465907623535, 0.178028490322197, 0.200788185881879, 0.0514727894594648, 0.0739639084701291, 0.0893343358495282, 0.0820192326650262, 0.104132629687123, 0.0600855805773719, 0.164927497928001, 0.11510803218647, 0.11456429705202, 0.140213013986381, 0.0715193770736051, 0.0577712690042106, 0.0683401947985261, 0.108376253996364, 0.152367731004308, 0.0518419050566429, 0.0967039660836575, 0.105592416917608, 0.0973541547573791, 0.138870760371045, 0.0352852130493688, 0.0962050495562246, 0.06919065466693, 0.118971425682342, 0.125290547146885, 0.0476957499005439, 0.103861205171753, 0.0933401784102089, 0.143371913789607, 0.135955623027448)),
.Names = c("X", "Genotype", "Time", "Bgrnd_All", "N", "Length", "sd", "se", "ci"), class = "data.frame", row.names = c(NA, -40L))


As stated by #juba in the comments, you should use scale_colour_manual instead of scale_fill_manual. Moreover, you are trying to plot to many lines and errorbars in one plot. They overlap each other to much and it is therefore hard to distuinguish between the lines/errorbars.
An example with the use of facetting (and some simplification of your code):
ggplot(summary.200.exp2, aes(x=Time, y=Length, group=Genotype)) +
geom_line(aes(colour=Bgrnd_All), size =1) +
geom_errorbar(aes(ymin=Length-se, ymax=Length+se, colour=Bgrnd_All), width=2) +
scale_x_continuous("Time", breaks=c(0,17,22,41,89)) +
scale_colour_manual(values=c(Avalon="#000066",Av_A="#663399",Av_B="#339999",Cadenza="#CC0033",Cad_A="#FF6600",Cad_B="#FF9933"))+
ylab("leaf segment width (mm)") +
theme_bw() +
theme(axis.title = element_text(size=14,face="bold"), axis.text = element_text(size=10)) +
facet_wrap(~Bgrnd_All, ncol=3)
this gives:

Related

R plotly multiple plots only show last figure

I would like to make an interactive graphs based on user input. However I'm struggle to make more than one graphs using R plotly. Suppose I have following data and codes,
dput(norwd5)
structure(list(LENGTH_OF_STAY = c(57L, 28L, 15L, 28L, 14L, 49L,
15L, 22L, 17L, 81L, 34L, 24L, 31L, 38L, 33L, 22L, 21L, 49L, 188L,
21L, 21L, 36L, 24L, 23L, 48L, 54L, 42L, 62L, 13L, 139L, 29L,
49L, 15L, 7L, 43L, 28L, 31L, 22L, 23L, 26L, 33L, 30L, 127L, 22L,
22L, 15L, 28L, 26L, 15L, 31L, 22L, 89L, 28L, 60L, 54L, 37L, 20L,
135L, 155L, 51L, 15L, 8L, 38L, 16L, 16L, 22L, 30L, 14L, 16L,
18L, 14L, 272L, 25L, 22L, 18L, 21L, 188L, 264L, 34L, 34L, 136L,
23L, 142L, 25L, 32L, 58L, 163L, 16L, 35L, 23L, 50L, 71L, 10L,
19L, 22L, 24L, 45L, 29L, 15L, 82L), PRE_OPERATIVE_LOS = c(2L,
2L, 3L, 1L, 3L, 6L, 3L, 7L, 2L, 2L, 11L, 2L, 6L, 3L, 6L, 3L,
5L, 3L, 179L, 2L, 5L, 3L, 4L, 2L, 5L, 6L, 2L, 4L, 2L, 6L, 3L,
2L, 2L, 6L, 6L, 1L, 4L, 5L, 6L, 5L, 0L, 4L, 6L, 2L, 4L, 4L, 7L,
4L, 4L, 6L, 2L, 4L, 3L, 3L, 2L, 6L, 4L, 110L, 63L, 6L, 4L, 7L,
5L, 1L, 6L, 1L, 4L, 2L, 6L, 3L, 2L, 8L, 2L, 2L, 4L, 3L, 6L, 171L,
5L, 4L, 116L, 6L, 47L, 3L, 7L, 3L, 60L, 1L, 3L, 20L, 31L, 49L,
9L, 8L, 3L, 4L, 35L, 7L, 4L, 9L), POST_OPERATIVE_LOS = c(55L,
26L, 12L, 27L, 11L, 43L, 12L, 15L, 15L, 79L, 23L, 22L, 25L, 35L,
27L, 19L, 16L, 46L, 9L, 19L, 16L, 33L, 20L, 21L, 43L, 48L, 40L,
58L, 11L, 133L, 26L, 47L, 13L, 1L, 37L, 27L, 27L, 17L, 17L, 21L,
33L, 26L, 121L, 20L, 18L, 11L, 21L, 22L, 11L, 25L, 20L, 85L,
25L, 57L, 52L, 31L, 16L, 25L, 92L, 45L, 11L, 1L, 33L, 15L, 10L,
21L, 26L, 12L, 10L, 15L, 12L, 264L, 23L, 20L, 14L, 18L, 182L,
93L, 29L, 30L, 20L, 17L, 95L, 22L, 25L, 55L, 103L, 15L, 32L,
3L, 19L, 22L, 1L, 11L, 19L, 20L, 10L, 22L, 11L, 73L), digoxin_any = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L,
2L, 1L, 2L), .Label = c("0:No", "1.Yes"), class = "factor")), row.names = c(NA,
-100L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000012f36b61ef0>)
num <- c('PRE_OPERATIVE_LOS','POST_OPERATIVE_LOS')
plist <- scan(text=num,what = "",quiet = T)
groups <- 'digoxin_any'
bygrp <- scan(text=groups,what="",quiet=T)
norwd5[, (bygrp) := lapply(.SD, as.factor), .SDcols = bygrp]
plotList = list()
for(i in length(plist)){
gplot <- ggplot(norwd5,aes_string(x=plist[i],group=bygrp,color=bygrp))+geom_histogram(aes(y=..density..),position = "dodge")+geom_density(alpha=.5) +theme(legend.position = "left")
plotList[[i]] <- plotly_build(gplot)
}
for(i in length(plist)){
print(plotList[[i]])
}
The goal is to show both graphs for PRE_OPERATIVE_LOS and POST_OPERATIVE_LOS. However, the codes above only show histogram for POST_OPERATIVE_LOS.
I checked maybe subplot is the way to go but how to make subplot work in a loop? Any hints?
Thanks!

There is an error in your first loop and calling each subplot won't make both appear at the same time.
First-- the issue with your first for call- when you wrote
for(i in length(plist))
You wrote for i in 2 or i == 2, meaning that you never looped. If you modify it to a range of values, now it's written: for i in 1 to 2.
for(i in 1:length(plist))
So you're aware, if you had written for(i in plist) it would have done both loops, but instead of a value, i would be the strings.
Okay, so now there are two graphs. From the plotly library, you can use the function subplot. You will want to turn the legend off for one of them, though.
subplot(plotList[[1]],
style(plotList[[2]], showlegend = FALSE))
If you wanted the outline color, that's more than okay! However, if you wanted to bars to be filled, you need to assign fill instead of color.
If you change color = bygrp to fill = bygrp, this is how this would change:
If you leave the color assignment and add fill = bygrp (so you have both), this is how this would change:

Adding points to persp 3D plot - hide or obscure points when behind surface

Background:
I'm attempting to add a 3D plot to a Shiny application. I've added a button to rotate the plot ~ 90 degrees. I'd also like to include radio buttons to plot points on the surface.
Problem:
When points are plotted they simply appear on top of the image, even when they should be behind the surface.
Question:
Is there a way to plot the surface so that it's transparent and points appear either behind or in front? Or hide the points if they land out of eyesight?
Data:
d <- list(x = c(0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6,
6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10), y = c(0, 0.5, 1, 1.5, 2, 2.5,
3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10),
z = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.000147818839413345, 0.00112553487724733,
0.00210325091508131, 0.00308096695291529, 0.00405868299074927,
0.00503639902858325, 0.00601411506641723, 0.00699183110425121,
0.00796954714208519, 0.00894726317991917, 0.00992497921775315,
0.0109026952555871, 0.0118804112934211, 0.0128581273312551,
0.0138358433690891, 0.0148135594069231, 0.015791275444757,
0.016768991482591, 0.017746707520425, 0.018724423558259,
0.019702139596093, 0.00332663525507192, 0.0253299512993333,
0.0473332673435947, 0.0693365833878561, 0.0913398994321175,
0.113343215476379, 0.13534653152064, 0.157349847564902, 0.179353163609163,
0.201356479653424, 0.223359795697686, 0.245363111741947,
0.267366427786209, 0.28936974383047, 0.311373059874731, 0.333376375918993,
0.355379691963254, 0.377383008007516, 0.399386324051777,
0.421389640096038, 0.4433929561403, 0.0185048854236584, 0.140901484725856,
0.263298084028054, 0.385694683330252, 0.50809128263245, 0.630487881934648,
0.752884481236846, 0.875281080539044, 0.997677679841242,
1.12007427914344, 1.24247087844564, 1.36486747774784, 1.48726407705003,
1.60966067635223, 1.73205727565443, 1.85445387495663, 1.97685047425883,
2.09924707356102, 2.22164367286322, 2.34404027216542, 2.46643687146762,
0.0575583422570596, 0.438265663185897, 0.818972984114734,
1.19968030504357, 1.58038762597241, 1.96109494690124, 2.34180226783008,
2.72250958875892, 3.10321690968776, 3.48392423061659, 3.86463155154543,
4.24533887247427, 4.6260461934031, 5.00675351433194, 5.38746083526078,
5.76816815618962, 6.14887547711845, 6.52958279804729, 6.91029011897613,
7.29099743990496, 7.6717047608338, 0.129117933403967, 0.98314083577592,
1.83716373814787, 2.69118664051983, 3.54520954289178, 4.39923244526373,
5.25325534763568, 6.10727825000764, 6.96130115237959, 7.81532405475154,
8.6693469571235, 9.52336985949545, 10.3773927618674, 11.2314156642394,
12.0854385666113, 12.9394614689833, 13.7934843713552, 14.6475072737272,
15.5015301760991, 16.3555530784711, 17.209575980843, 0.23363441995763,
1.77895922624881, 3.32428403254, 4.86960883883118, 6.41493364512237,
7.96025845141355, 9.50558325770473, 11.0509080639959, 12.5962328702871,
14.1415576765783, 15.6868824828695, 17.2322072891607, 18.7775320954518,
20.322856901743, 21.8681817080342, 23.4135065143254, 24.9588313206166,
26.5041561269078, 28.0494809331989, 29.5948057394901, 31.1401305457813,
0.36143039040365, 2.75203425835922, 5.14263812631479, 7.53324199427035,
9.92384586222592, 12.3144497301815, 14.7050535981371, 17.0956574660926,
19.4862613340482, 21.8768652020038, 24.2674690699593, 26.6580729379149,
29.0486768058705, 31.439280673826, 33.8298845417816, 36.2204884097372,
38.6110922776927, 41.0016961456483, 43.3923000136039, 45.7829038815594,
48.173507749515, 0.494048345421132, 3.76182525870662, 7.02960217199211,
10.2973790852776, 13.5651559985631, 16.8329329118486, 20.1007098251341,
23.3684867384196, 26.636263651705, 29.9040405649905, 33.171817478276,
36.4395943915615, 39.707371304847, 42.9751482181325, 46.242925131418,
49.5107020447035, 52.778478957989, 56.0462558712744, 59.3140327845599,
62.5818096978454, 65.8495866111309, 0.608277972936286, 4.63160227964344,
8.65492658635059, 12.6782508930577, 16.7015751997649, 20.724899506472,
24.7482238131792, 28.7715481198863, 32.7948724265935, 36.8181967333006,
40.8415210400078, 44.8648453467149, 48.8881696534221, 52.9114939601292,
56.9348182668364, 60.9581425735435, 64.9814668802507, 69.0047911869578,
73.028115493665, 77.0514398003722, 81.0747641070793, 0.68169864474794,
5.19064825215217, 9.6995978595564, 14.2085474669606, 18.7174970743649,
23.2264466817691, 27.7353962891733, 32.2443458965776, 36.7532955039818,
41.262245111386, 45.7711947187903, 50.2801443261945, 54.7890939335987,
59.298043541003, 63.8069931484072, 68.3159427558114, 72.8248923632157,
77.3338419706199, 81.8427915780241, 86.3517411854284, 90.8606907928326,
0.698331143785818, 5.31729285196915, 9.93625456015249, 14.5552162683358,
19.1741779765192, 23.7931396847025, 28.4121013928858, 33.0310631010692,
37.6500248092525, 42.2689865174358, 46.8879482256192, 51.5069099338025,
56.1258716419859, 60.7448333501692, 65.3637950583525, 69.9827567665359,
74.6017184747192, 79.2206801829025, 83.8396418910859, 88.4586035992692,
93.0775653074525, 0.653010606586468, 4.9722093330084, 9.29140805943032,
13.6106067858523, 17.9298055122742, 22.2490042386961, 26.568202965118,
30.88740169154, 35.2066004179619, 39.5257991443838, 43.8449978708057,
48.1641965972277, 52.4833953236496, 56.8025940500715, 61.1217927764935,
65.4409915029154, 69.7601902293373, 74.0793889557592, 78.3985876821812,
82.7177864086031, 87.036985135025, 0.553337675961259, 4.21327116124787,
7.87320464653448, 11.5331381318211, 15.1930716171077, 18.8530051023943,
22.5129385876809, 26.1728720729675, 29.8328055582542, 33.4927390435408,
37.1526725288274, 40.812606014114, 44.4725394994006, 48.1324729846872,
51.7924064699738, 55.4523399552604, 59.112273440547, 62.7722069258337,
66.4321404111203, 70.0920738964069, 73.7520073816935, 0.418509049668882,
3.18664747819306, 5.95478590671724, 8.72292433524142, 11.4910627637656,
14.2592011922898, 17.027339620814, 19.7954780493381, 22.5636164778623,
25.3317549063865, 28.0998933349107, 30.8680317634349, 33.636170191959,
36.4043086204832, 39.1724470490074, 41.9405854775316, 44.7087239060558,
47.4768623345799, 50.2450007631041, 53.0131391916283, 55.7812776201525,
0.274945103406177, 2.09351057307846, 3.91207604275075, 5.73064151242304,
7.54920698209532, 9.36777245176761, 11.1863379214399, 13.0049033911122,
14.8234688607845, 16.6420343304568, 18.460599800129, 20.2791652698013,
22.0977307394736, 23.9162962091459, 25.7348616788182, 27.5534271484905,
29.3719926181628, 31.1905580878351, 33.0091235575073, 34.8276890271796,
36.6462544968519, 0.14939138421548, 1.1375086826693, 2.12562598112311,
3.11374327957693, 4.10186057803075, 5.08997787648456, 6.07809517493838,
7.06621247339219, 8.05432977184601, 9.04244707029983, 10.0305643687536,
11.0186816672075, 12.0067989656613, 12.9949162641151, 13.9830335625689,
14.9711508610227, 15.9592681594765, 16.9473854579304, 17.9355027563842,
18.923620054838, 19.9117373532918, 0.0610345623904979, 0.464734596487648,
0.868434630584799, 1.27213466468195, 1.6758346987791, 2.07953473287625,
2.4832347669734, 2.88693480107055, 3.2906348351677, 3.69433486926485,
4.098034903362, 4.50173493745915, 4.9054349715563, 5.30913500565345,
5.7128350397506, 6.11653507384775, 6.52023510794491, 6.92393514204206,
7.32763517613921, 7.73133521023636, 8.13503524433351, 0.0150842607904164,
0.114855871447028, 0.214627482103639, 0.31439909276025, 0.414170703416861,
0.513942314073472, 0.613713924730083, 0.713485535386694,
0.813257146043305, 0.913028756699917, 1.01280036735653, 1.11257197801314,
1.21234358866975, 1.31211519932636, 1.41188680998297, 1.51165842063958,
1.61143003129619, 1.71120164195281, 1.81097325260942, 1.91074486326603,
2.01051647392264, 0.00112075907879118, 0.00853377984279572,
0.0159468006068003, 0.0233598213708048, 0.0307728421348093,
0.0381858628988139, 0.0455988836628184, 0.0530119044268229,
0.0604249251908275, 0.067837945954832, 0.0752509667188366,
0.0826639874828411, 0.0900770082468456, 0.0974900290108502,
0.104903049774855, 0.112316070538859, 0.119729091302864,
0.127142112066868, 0.134555132830873, 0.141968153594877,
0.149381174358882, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(21L, 21L)), facetcol = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L,
5L, 5L, 6L, 6L, 1L, 2L, 2L, 3L, 4L, 4L, 5L, 6L, 6L, 7L, 8L,
9L, 9L, 10L, 11L, 11L, 12L, 13L, 13L, 14L, 1L, 3L, 4L, 5L,
7L, 8L, 9L, 11L, 12L, 13L, 15L, 16L, 17L, 19L, 20L, 21L,
23L, 24L, 25L, 27L, 2L, 4L, 6L, 9L, 11L, 13L, 15L, 17L, 19L,
22L, 24L, 26L, 28L, 30L, 33L, 35L, 37L, 39L, 41L, 44L, 3L,
6L, 9L, 12L, 15L, 18L, 21L, 25L, 28L, 31L, 34L, 37L, 40L,
44L, 47L, 50L, 53L, 56L, 59L, 62L, 3L, 7L, 11L, 15L, 19L,
23L, 28L, 32L, 36L, 40L, 44L, 48L, 52L, 56L, 60L, 64L, 68L,
72L, 76L, 80L, 4L, 8L, 13L, 18L, 23L, 27L, 32L, 37L, 42L,
46L, 51L, 56L, 61L, 65L, 70L, 75L, 80L, 84L, 89L, 94L, 4L,
9L, 14L, 19L, 24L, 29L, 34L, 39L, 45L, 50L, 55L, 60L, 65L,
70L, 75L, 80L, 85L, 90L, 95L, 100L, 4L, 9L, 14L, 19L, 24L,
29L, 34L, 39L, 44L, 49L, 54L, 59L, 64L, 69L, 74L, 78L, 83L,
88L, 93L, 98L, 3L, 8L, 12L, 17L, 21L, 26L, 30L, 35L, 39L,
43L, 48L, 52L, 57L, 61L, 66L, 70L, 75L, 79L, 83L, 88L, 3L,
6L, 10L, 14L, 17L, 21L, 24L, 28L, 32L, 35L, 39L, 42L, 46L,
49L, 53L, 57L, 60L, 64L, 67L, 71L, 2L, 5L, 7L, 10L, 12L,
15L, 18L, 20L, 23L, 25L, 28L, 30L, 33L, 35L, 38L, 41L, 43L,
46L, 48L, 51L, 2L, 3L, 5L, 6L, 8L, 9L, 11L, 12L, 14L, 16L,
17L, 19L, 20L, 22L, 23L, 25L, 27L, 28L, 30L, 31L, 1L, 2L,
3L, 3L, 4L, 5L, 6L, 6L, 7L, 8L, 9L, 10L, 10L, 11L, 12L, 13L,
13L, 14L, 15L, 16L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 6L, 6L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L), .Label = c("(-0.357,3.59]", "(3.59,7.18]",
"(7.18,10.8]", "(10.8,14.4]", "(14.4,17.9]", "(17.9,21.5]",
"(21.5,25.1]", "(25.1,28.7]", "(28.7,32.3]", "(32.3,35.9]",
"(35.9,39.5]", "(39.5,43.1]", "(43.1,46.6]", "(46.6,50.2]",
"(50.2,53.8]", "(53.8,57.4]", "(57.4,61]", "(61,64.6]", "(64.6,68.2]",
"(68.2,71.8]", "(71.8,75.3]", "(75.3,78.9]", "(78.9,82.5]",
"(82.5,86.1]", "(86.1,89.7]", "(89.7,93.3]", "(93.3,96.9]",
"(96.9,100]", "(100,104]", "(104,108]", "(108,111]", "(111,115]",
"(115,118]", "(118,122]", "(122,126]", "(126,129]", "(129,133]",
"(133,136]", "(136,140]", "(140,144]", "(144,147]", "(147,151]",
"(151,154]", "(154,158]", "(158,161]", "(161,165]", "(165,169]",
"(169,172]", "(172,176]", "(176,179]", "(179,183]", "(183,187]",
"(187,190]", "(190,194]", "(194,197]", "(197,201]", "(201,204]",
"(204,208]", "(208,212]", "(212,215]", "(215,219]", "(219,222]",
"(222,226]", "(226,230]", "(230,233]", "(233,237]", "(237,240]",
"(240,244]", "(244,248]", "(248,251]", "(251,255]", "(255,258]",
"(258,262]", "(262,265]", "(265,269]", "(269,273]", "(273,276]",
"(276,280]", "(280,283]", "(283,287]", "(287,291]", "(291,294]",
"(294,298]", "(298,301]", "(301,305]", "(305,309]", "(309,312]",
"(312,316]", "(316,319]", "(319,323]", "(323,326]", "(326,330]",
"(330,334]", "(334,337]", "(337,341]", "(341,344]", "(344,348]",
"(348,352]", "(352,355]", "(355,359]"), class = "factor"))
Code
flip <- 1 # 1 or 2
theta = c(-300,120)[flip]
pmat <- persp(d$x, d$y, d$z, asp = 1,col = color[d$facetcol], phi = 30, theta = theta, border = "grey10"
,d = .8,r = 2.8,expand = .6,shade = .2,axes = F,box = T,cex = .1)
xx <- c(7.76245335753423, 6.73123147037805)
yy <- c(4.88402435072353, 4.20867046100364)
zz <- c(68.727, 48.558)
mypoints <- trans3d(xx,yy,zz,pmat = pmat)
points(mypoints,pch = 16,col = 2)
The image below is correct, but when the plot is rotated (set flip to 2) the points do not jive. In other words, when the plot is rotated the points should be hidden from view, or seen through a semi-transparent surface. Help is appreciated!

In case this is helpful to anyone. I ended up using the persp3D() function from the plot3D package. All my custom axes labels and tick marks transferred seamlessly from the base persp() with the added bonus of a transparency argument (alpha =) and proper point plotting (points3D).

R and NLS: singular gradient matrix at initial parameter

I'm trying to use nls to estimate the parameters of a non linear model.
I first use nls2 to find good initial parameters with Random Search and I then use nls to improve the estimation with a Gauss-Newton approach.
The problem is I always get an "singular gradient matrix at initial parameter estimates" error.
I'm not sure I understand, because the input matrix doesn't seem to be a singular gradient matrix.
Moreover even if the fits I'm looking for is not perfect for this data, nls should find a way to improve the
parameters estimations. Isn't it ?
Question: Is there a way to improve the parameters estimation?
I've tried NLS.lm but I had the same problem.
Here is a reproductible example:
Data:
structure(list(x1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), x2 = c(1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L,
45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L,
58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 0L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L,
43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L,
56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 0L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L,
42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L,
55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 0L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L,
42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L,
55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 0L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L,
43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L,
56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 0L, 1L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L,
45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L,
58L, 59L, 60L, 61L, 62L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L,
35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L,
48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L,
61L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L,
40L, 41L, 42L, 43L, 44L, 45L), y = c(0.0689464583349188, 0.0358227182166929,
0.0187034836294036, 0.0227081421239796, 0.0146603483536504, 0.00562771204350896,
0.00411351161052011, 0.00356917888321555, 0.0028017552960605,
0.0024750328652541, 0.00243175013170564, 0.00242654283706898,
0.00235224917236107, 0.00176144220485858, 0.00138071934398105,
0.000696375069179013, 0.00106282865382483, 0.00114735219137874,
0.00277256441625284, 0.00214359572321392, 0.00144935953386591,
0.00249732559162499, 0.00225859018399108, 0.00201642941663214,
0.00232438586834105, 0.0016083751355862, 0.00143118376291818,
0.00158323933266031, 0.00157585431454131, 0.00169206800399143,
0.00158514119474578, 0.00134506293557103, 0.00119442163345335,
0.00101284069499962, 0.0012621113004254, 0.00128964367655383,
0.00102819258807122, 0.00125345601171754, 0.00116155619985178,
0.00142466624262548, 0.00141075318725309, 0.00106556656123991,
0.0010976347045814, 0.0012442089226047, 0.0010627617251863, 0.00125322168410487,
0.00112108560656369, 0.0012459199320756, 0.00135773322693401,
0.0013997982284804, 0.00155012485145915, 0.00151108062240688,
0.00149570655260348, 0.00152598641103596, 0.00108261570337346,
0.000992225418429453, 0.000769588971038765, 0.000700496873143604,
0.000688378351958078, 0.000595007407260441, 0.000557615594951187,
0.00040476923690092, 0.000492276455560289, 0.000447248723966691,
0.000388694992851599, 0.000346087542525691, 0.000189803623801549,
0.0709302325562937, 0.0424623423412875, 0.019085896698975, 0.0190650552541205,
0.014276898897581, 0.00593407290200902, 0.00445528598343583,
0.00371231334350143, 0.00253909496678967, 0.00263487912423124,
0.00248012072619926, 0.00263786771266913, 0.00219351150766708,
0.00179271674850348, 0.00139646119589996, 0.000911560061336614,
0.000989537441246412, 0.001046390000492, 0.00223993432619926,
0.00164189356162362, 0.00106041866437064, 0.00194151698794588,
0.0014213192200082, 0.00165239495268553, 0.00196583929282493,
0.00120501090643706, 0.001141403899631, 0.00122398595424354,
0.00124538223829438, 0.00123370121853218, 0.00136883147552275,
0.00110907318146781, 0.000965843164247642, 0.000859986264862649,
0.00104695561918819, 0.00103985460139401, 0.000455832014104141,
0.000704296760639607, 0.000870145383845838, 0.000919870911357114,
0.00101396309667897, 0.000781894087412874, 0.000909712365723658,
0.000889897365477655, 0.000933063039278393, 0.000779395399425994,
0.000789546295038951, 0.000773432990897909, 0.00125614787798278,
0.00123172652693727, 0.00078936677195572, 0.000952107503075031,
0.00105449131480115, 0.00123128091742517, 0.000889501370397704,
0.00085648642099221, 0.000830097733497335, 0.000653482256334563,
0.000521696831160312, 0.000612702433456335, 0.000513576588109881,
0.000475289330709307, 0.00041141913800738, 0.000328157997211972,
0.00031336264403444, 0.000328784093808938, 0.000237448446412464,
0.0520691145678866, 0.0281929482152033, 0.0219024230330532, 0.0141074098760277,
0.00691341703402584, 0.00445785262213699, 0.0034569415664917,
0.00234406584844369, 0.00257369504707459, 0.00234047371531346,
0.00227286083862502, 0.00248544382019894, 0.00180810413760828,
0.00138986347039715, 0.000911936124008956, 0.000932783218782117,
0.00108887529088974, 0.0017855660833578, 0.00159768589505946,
0.00124091041330201, 0.00203036436876009, 0.00154489107876964,
0.00111687975012847, 0.00163256939968433, 0.00143626193198502,
0.000996683818914256, 0.0010781399542101, 0.00122575793431581,
0.00115671467616723, 0.001069532453476, 0.0010106869893371, 0.000978618104445015,
0.000894478048836441, 0.000842874700392747, 0.000819009288742475,
0.000843003919670386, 0.000964158733115548, 0.000877802228013507,
0.00087592051873807, 0.000935810596369843, 0.000879047729316546,
0.000829181439950081, 0.0010295792954412, 0.000765620227389517,
0.00102511256239906, 0.000823109180461753, 0.00111669534392894,
0.000802757620485245, 0.00103231207284173, 0.000884354083467919,
0.00109278942886507, 0.000969283099489796, 0.000827480664091176,
0.000798564447676552, 0.000909248326695786, 0.000682209033640434,
0.000780593294853913, 0.000485172195712818, 0.000467514093470122,
0.000295219649739392, 0.000460636351123183, 0.00045060371687344,
0.000492590160218764, 0.000402536549331963, 0.000271941766535751,
0.000171012123770371, 0.0267385565244063, 0.0275426278720772,
0.0154589149018475, 0.00729065000152096, 0.00513675524527996,
0.00378848397112206, 0.00305965140790087, 0.00240428827949139,
0.00233604733730811, 0.00199601458903693, 0.00198302547453915,
0.00137121122011316, 0.00126241982975401, 0.0012413298189045,
0.00103044327584109, 0.00106759120581615, 0.00190957422380402,
0.00124400301656831, 0.000989035353673623, 0.00160702520431547,
0.0011515826661394, 0.00153203681379408, 0.00134897491229138,
0.000916492937174261, 0.00072393419977287, 0.00115124473393361,
0.00104241370079698, 0.000953324905193568, 0.00121656899373365,
0.000891420608484922, 0.000671666092758208, 0.000659860761797571,
0.000586145968952161, 0.00072735268499929, 0.000658407622538582,
0.000498831767252743, 0.000658345030520574, 0.000542106922897528,
0.000874560054044737, 0.000543320226217274, 0.000751139509440084,
0.000668632963233356, 0.000656903021131188, 0.000574965903652329,
0.0006661524076778, 0.000605171890653201, 0.000527045917239561,
0.000985791370586684, 0.000899420142057553, 0.000933015548254953,
0.00082137283567561, 0.000870124781995904, 0.000498046123582973,
0.000540181050881142, 0.000596948101336416, 0.000405622486362069,
0.000631594016548032, 0.000468749313033603, 0.000389576698910993,
0.000335624642574679, 0.000286763668856847, 0.000439039581432135,
0.000244767908276044, 0.000303911794528604, 0.000160988671898765,
0.0365772382134747, 0.0255898183301035, 0.010327803963121, 0.00714710822108354,
0.00506253612461807, 0.00447056668291465, 0.00322822676102386,
0.00328154620569948, 0.0028470908747756, 0.00253477302081723,
0.00187837758253778, 0.00116416512964702, 0.00119557763663167,
0.000993575112051645, 0.00136274483135782, 0.00204131052512691,
0.00157953945941769, 0.00116523253183218, 0.00190793844827791,
0.00144595416523011, 0.00157423646879793, 0.00126996001866537,
0.00115283860342634, 0.00116894693507543, 0.000930041619012519,
0.00106545753272384, 0.00123507493015348, 0.00130865599847824,
0.000940647984853709, 0.000836521897923032, 0.000778436697656724,
0.00100773629284415, 0.000956581999215341, 0.000808036977042788,
0.000597930101173421, 0.000776453419209873, 0.000630241947142534,
0.000649832426616575, 0.000782188275296327, 0.00102823806308181,
0.000830656989407107, 0.00051915559901561, 0.000537114715917872,
0.000872430107712244, 0.000549284113632851, 0.000738257038745497,
0.00097442578198376, 0.000879724260815807, 0.000884543540237537,
0.00100038027474944, 0.00103543285342337, 0.000875585441608313,
0.000829083410412184, 0.000760316116414823, 0.000712211369823927,
0.000386744815307978, 0.000428331410721292, 0.000397681982571065,
0.000213938551710199, 0.000370800615243779, 0.000281234314553042,
0.000267359921177464, 0.000358376119030352, 0.000337361541022196,
0.0310029062887812, 0.0154963087949333, 0.00959302943445506,
0.00645674376405936, 0.00525321947702945, 0.00386084394749159,
0.00374364242039947, 0.00351047952579374, 0.00298556939927835,
0.00199158625919048, 0.00206559575086432, 0.00169077836254661,
0.00139156751815451, 0.00170363478493893, 0.00250481301085496,
0.00182474837251083, 0.00116804333227652, 0.00155778636185214,
0.00183778204100427, 0.00135012918459471, 0.00166904872503284,
0.00120137403943415, 0.00108307957787943, 0.00146041465872549,
0.0014437889563235, 0.000975926161359965, 0.00102580511345623,
0.00112145083941, 0.000921884915530595, 0.00082253191796126,
0.000634876416504371, 0.00108601324863747, 0.000830573067167897,
0.000965052460105379, 0.000922667052402736, 0.000863193817654785,
0.000982111173513293, 0.000763009170856168, 0.000921755812461313,
0.000771609983091022, 0.000669047474976222, 0.000773869648383834,
0.00072022523061129, 0.000742426347056781, 0.000718728249316847,
0.000761437280522971, 0.000833112611531319, 0.000794451658438637,
0.000907360341651947, 0.00112083735676435, 0.00102996529205731,
0.000651843453054939, 0.000640968179416338, 0.000549646466476441,
0.000778958256714525, 0.000627413038784969, 0.000523658918731223,
0.000418571973368359, 0.000643352520494588, 0.000351378727146459,
0.000504093577607682, 0.000333827596358531, 0.000339505558071773,
0.0181836504450303, 0.0135527124187004, 0.00780738765319868,
0.00643260738080874, 0.00476881905655232, 0.00406986745617877,
0.00400325917456592, 0.00277499160186111, 0.00198311377238581,
0.00241837807740304, 0.00141018451525995, 0.00166798657140732,
0.0013970042073337, 0.00237332662413329, 0.00146721126831566,
0.000990562316636778, 0.00186106889002752, 0.00186322276224556,
0.00140391140302307, 0.00139027556176293, 0.00125730361478641,
0.00127044200804939, 0.00126655503830484, 0.00133956330669488,
0.00128219844136096, 0.00109531452608613, 0.00112195611926977,
0.00101411381866565, 0.00104786051750783, 0.000798711632769435,
0.000852432172756047, 0.000852720107765923, 0.00110385307389073,
0.00081385514739304, 0.00102898862672826, 0.000710330768658628,
0.000803425598538879, 0.000723455383750816, 0.00075034248654992,
0.000864917906994041, 0.000799733114881449, 0.000608518601191706,
0.000855476747683942, 0.000988548021123443, 0.00104800683206201,
0.000997051779707941, 0.000796235203259423, 0.000910577791459715,
0.000869997383535945, 0.000557402535474327, 0.000757813148434336,
0.000480807445269952, 0.000553425518375578, 0.000633029237291637,
0.00050222863978579, 0.000390945889771328, 0.000430333228928208,
0.000425167676834459, 0.000239604519722651, 0.000357021364759551,
0.000292330910803864, 0.000288851701197491, 0.0198837196044917,
0.0142208140311702, 0.00733039271103269, 0.00609158853724431,
0.00487605866828399, 0.00382636157210858, 0.00411545257392807,
0.00235906433257981, 0.00228491326937568, 0.00109255715480326,
0.00158036861847788, 0.00122011020381908, 0.00223761733564904,
0.00173284341769128, 0.00117538923471357, 0.00219622963095698,
0.00214263916211795, 0.0013198229549172, 0.00172951959530242,
0.00128074705482347, 0.00124062569884766, 0.00144218669111025,
0.00148407512819099, 0.00100716026446858, 0.0010842890711437,
0.000800686408079248, 0.000890454658065465, 0.000887152794471706,
0.00105780722647994, 0.000874948318354744, 0.000569126715186268,
0.000924642167943982, 0.000857013884141074, 0.000823122890591976,
0.00073038777177409, 0.000522615873628494, 0.00070936497950782,
0.000823074755104667, 0.000720588701733105, 0.000722724038337836,
0.00063458965098969, 0.000620049346639466, 0.000842327487089008,
0.000617708212493797, 0.000783953750160813, 0.00112567150392384
)), .Names = c("x1", "x2", "y"), class = c("tbl_df", "data.frame"
), row.names = c(NA, -500L))
Initial parameters: initial_par
structure(list(A1 = 0.0529486559121727, alpha1 = 0.00888818269595504,
B1 = 0.250994319084551, beta1 = 0.471984946168959, A2 = 0.281956987357551,
alpha2 = 0.325086771510541, B2 = 0.0562204262765557, beta2 = 0.725645614322275), class = "data.frame", row.names = c(NA,
-1L), .Names = c("A1", "alpha1", "B1", "beta1", "A2", "alpha2",
"B2", "beta2"))
Formula:
formula = y ~
(A1*exp(-alpha1*x1) + B1*exp(-beta1*x1)) *
(A2*exp(-alpha2*x2) + B2*exp(-beta2*x2))
Nls and the error message
final = nls(formula,
data=df,
start = as.list(as.vector(initial_par)))
Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates

The problem is that there is not a one to one relationship between your model and parameters. To see this write A1 = exp(a1+d), A2 = exp(a2-d), B1 = exp(b1+d), B2 = exp(b2-d) in which case we have:
y ~ exp(-alpha1 * x1 + a1 + d) * exp(-alpha2 * x2 + a2 - d) +
exp(-alpha1 * x1 + a1 + d) * exp(-beta2 * x2 + b2 - d) +
exp(-beta1 * x1 + b1 + d) * exp(-alpha2 * x2 + a2 - d) +
exp(-beta1 * x1 + b1 + d) * exp(-beta2 * x2 + b2 - d)
But d cancels in each of the 4 terms and so cancels entirely from the RHS. That is, the RHS is the same for any value of d thus the model is overparameterized and so will give a singular gradient.
Fix one of A1, A2, B1, B2 and then you should be able to get a solution:
A1 <- 1
nls(formula, df, start = initial_par[-1])
giving:
Nonlinear regression model
model: y ~ (A1 * exp(-alpha1 * x1) + B1 * exp(-beta1 * x1)) * (A2 * exp(-alpha2 * x2) + B2 * exp(-beta2 * x2))
data: df
alpha1 B1 beta1 A2 alpha2 B2 beta2
0.11902 1.21030 0.79076 0.04604 0.51697 0.00183 0.02317
residual sum-of-squares: 0.000685
Number of iterations to convergence: 11
Achieved convergence tolerance: 6.686e-06

Bars in geom_bar have unwanted different widths when using facet_wrap

I can'd find a solution for the following problem(s). I would appreciate some help a lot!
The following code produces bar charts using facet. However, due to "extra space" ggplot2 has in some groups it makes the bars much wider, even if I specify a width of 0.1 or similar. I find that very annoying since it makes it look very unprofessional. I want all the bars to look the same (except for the fill). I hope somebody can tell me how to fix this.
Secondly, how can I reorder the different classes in the facet windows so that the order is always C1, C2 ... C5, M, F, All where applicable. I tried it with ordering the levels of the factor, but since not all classes are present in every graph part it did not work, or at least I assume that was the reason.
Thirdly, how can I reduce the space between the bars? So that the whole graph is more compressed. Even if I make the image smaller for exporting, R will scale the bars smaller but the spaces between the bars are still huge.
I would appreciate feedback for any of those answers!
My Data:
http://pastebin.com/embed_iframe.php?i=kNVnmcR1
My Code:
library(dplyr)
library(gdata)
library(ggplot2)
library(directlabels)
library(scales)
all<-read.xls('all_auto_visual_c.xls')
all$station<-as.factor(all$station)
#all$group.new<-factor(all$group, levels=c('C. hyperboreus','C. glacialis','Special Calanus','M. longa','Pseudocalanus sp.','Copepoda'))
allp <- ggplot(data = all, aes(x=shortname2, y=perc_correct, group=group,fill=sample_size)) +
geom_bar(aes(fill=sample_size),stat="identity", position="dodge", width=0.1, colour="NA") + scale_fill_gradient("Sample size (n)",low="lightblue",high="navyblue")+
facet_wrap(group~station,ncol=2,scales="free_x")+
xlab("Species and stages") + ylab("Automatic identification and visual validation concur (%)") +
ggtitle("Visual validation of predictions") +
theme_bw() +
theme(plot.title = element_text(lineheight=.8, face="bold", size=20,vjust=1), axis.text.x = element_text(colour="grey20",size=12,angle=0,hjust=.5,vjust=.5,face="bold"), axis.text.y = element_text(colour="grey20",size=12,angle=0,hjust=1,vjust=0,face="bold"), axis.title.x = element_text(colour="grey20",size=15,angle=0,hjust=.5,vjust=0,face="bold"), axis.title.y = element_text(colour="grey20",size=15,angle=90,hjust=.5,vjust=1,face="bold"),legend.position="none", strip.text.x = element_text(size = 12, face="bold", colour = "black", angle = 0), strip.text.y = element_text(size = 12, face="bold", colour = "black"))
allp
#ggsave(allp, file="auto_visual_stackover.jpeg", height= 11, width= 8.5, dpi= 400,)
The current graph that needs some fixing:
Thanks a lot!

Here what I did after suggestion from Gregor. Using geom_segment and geom_point makes a nice graph as I think.
library(ggplot2)
all<-read.xls('all_auto_visual_c.xls')
all$station<-as.factor(all$station)
all$group.new<-factor(all$group, levels=c('C. hyperboreus','C. glacialis','Combined','M. longa','Pseudocalanus sp.','Copepoda'))
all$shortname2.new<-factor(all$shortname2, levels=c('All','F','M','C5','C4','C3','C2','C1','Micro', 'Oith','Tric','Cegg','Cnaup','C3&2','C2&1'))
allp<-ggplot(all, aes(x=perc_correct, y=shortname2.new)) +
geom_segment(aes(yend=shortname2.new), xend=0, colour="grey50") +
geom_point(size=4, aes(colour=sample_size)) +
scale_colour_gradient("Sample size (n)",low="lightblue",high="navyblue") +
geom_text(aes(label = perc_correct, hjust = -0.5)) +
theme_bw() +
theme(panel.grid.major.y = element_blank()) +
facet_grid(group.new~station,scales="free_y",space="free") +
xlab("Automatic identification and visual validation concur (%)") + ylab("Species and stages")+
ggtitle("Visual validation of predictions")+
theme_bw() +
theme(plot.title = element_text(lineheight=.8, face="bold", size=20,vjust=1), axis.text.x = element_text(colour="grey20",size=12,angle=0,hjust=.5,vjust=.5,face="bold"), axis.text.y = element_text(colour="grey20",size=12,angle=0,hjust=1,vjust=0,face="bold"), axis.title.x = element_text(colour="grey20",size=15,angle=0,hjust=.5,vjust=0,face="bold"), axis.title.y = element_text(colour="grey20",size=15,angle=90,hjust=.5,vjust=1,face="bold"),legend.position="none", strip.text.x = element_text(size = 12, face="bold", colour = "black", angle = 0), strip.text.y = element_text(size = 8, face="bold", colour = "black"))
allp
ggsave(allp, file="auto_visual_no_label.jpeg", height= 11, width= 8.5, dpi= 400,)
This is what it produces!

Assuming the bar widths are inversely proportional to the number of x-breaks, an appropriate scaling factor can be entered as a width aesthetic to control the width of the bars. But first, calculate the number of x-breaks in each panel, calculate the scaling factor, and put them back into the "all" data frame.
Updating to ggplot2 2.0.0 Each column mentioned in facet_wrap gets its own line in the strip. In the edit, a new label variable is setup in the dataframe so that the strip label remains on one line.
library(ggplot2)
library(plyr)
all = structure(list(station = structure(c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Station 101",
"Station 126"), class = "factor"), shortname2 = structure(c(2L,
7L, 8L, 11L, 1L, 5L, 7L, 8L, 11L, 1L, 2L, 3L, 5L, 7L, 8L, 12L,
11L, 1L, 6L, 8L, 15L, 14L, 9L, 10L, 4L, 6L, 2L, 7L, 8L, 11L,
1L, 5L, 7L, 8L, 11L, 1L, 2L, 3L, 5L, 7L, 8L, 12L, 11L, 1L, 8L,
11L, 1L, 15L, 14L, 13L, 9L, 10L), .Label = c("All", "C1", "C2",
"C2&1", "C3", "C3&2", "C4", "C5", "Cegg", "Cnaup", "F", "M",
"Micro", "Oith", "Tric"), class = "factor"), color = c(1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 21L, 26L, 30L, 31L, 33L, 34L, 20L, 21L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L,
19L, 26L, 28L, 29L, 30L, 31L, 32L, 33L, 34L), group = structure(c(1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 6L, 5L, 3L, 3L, 3L, 3L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 3L, 3L,
3L, 3L, 3L), .Label = c("cgla", "Chyp", "Cope", "mlong", "pseudo",
"specC"), class = "factor"), sample_size = c(11L, 37L, 55L, 16L,
119L, 21L, 55L, 42L, 40L, 158L, 24L, 16L, 17L, 27L, 14L, 45L,
98L, 241L, 30L, 34L, 51L, 22L, 14L, 47L, 13L, 41L, 24L, 41L,
74L, 20L, 159L, 18L, 100L, 32L, 29L, 184L, 31L, 17L, 27L, 23L,
21L, 17L, 49L, 185L, 30L, 16L, 46L, 57L, 16L, 12L, 30L, 42L),
perc_correct = c(91L, 78L, 89L, 81L, 85L, 90L, 91L, 93L,
80L, 89L, 75L, 75L, 76L, 81L, 86L, 76L, 79L, 78L, 90L, 97L,
75L, 86L, 93L, 74L, 85L, 88L, 88L, 90L, 92L, 90L, 91L, 89L,
89L, 91L, 90L, 89L, 81L, 88L, 74L, 78L, 90L, 82L, 84L, 82L,
90L, 94L, 91L, 81L, 69L, 83L, 90L, 81L)), class = "data.frame", row.names = c(NA,
-52L))
all$station <- as.factor(all$station)
# Calculate scaling factor and insert into data frame
library(plyr)
N = ddply(all, .(station, group), function(x) length(row.names(x)))
N$Fac = N$V1 / max(N$V1)
all = merge(all, N[,-3], by = c("station", "group"))
all$label = paste(all$group, all$station, sep = ", ")
allp <- ggplot(data = all, aes(x=shortname2, y=perc_correct, group=group, fill=sample_size, width = .5*Fac)) +
geom_bar(stat="identity", position="dodge", colour="NA") +
scale_fill_gradient("Sample size (n)",low="lightblue",high="navyblue")+
facet_wrap(~label,ncol=2,scales="free_x") +
xlab("Species and stages") + ylab("Automatic identification and visual validation concur (%)") +
ggtitle("Visual validation of predictions") +
theme_bw() +
theme(plot.title = element_text(lineheight=.8, face="bold", size=20,vjust=1),
axis.text.x = element_text(colour="grey20",size=12,angle=0,hjust=.5,vjust=.5,face="bold"),
axis.text.y = element_text(colour="grey20",size=12,angle=0,hjust=1,vjust=0,face="bold"),
axis.title.x = element_text(colour="grey20",size=15,angle=0,hjust=.5,vjust=0,face="bold"),
axis.title.y = element_text(colour="grey20",size=15,angle=90,hjust=.5,vjust=1,face="bold"),
legend.position="none",
strip.text.x = element_text(size = 12, face="bold", colour = "black", angle = 0),
strip.text.y = element_text(size = 12, face="bold", colour = "black"))
allp

Variable label position in ggplot line chart

I have the following data frame summary created with dplyr
structure(list(maxrep = c(7L, 7L, 8L, 8L, 9L, 9L, 10L, 10L, 11L,
11L, 12L, 12L, 13L, 13L, 14L, 14L, 15L, 15L, 16L, 16L, 17L, 17L,
18L, 18L, 19L, 19L, 20L, 20L, 21L, 21L, 22L, 22L, 23L, 23L, 24L,
24L, 26L, 26L), div = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c("Premier Division",
"Second Division"), class = "factor"), freq = c(1L, 10L, 4L,
39L, 26L, 89L, 73L, 146L, 107L, 162L, 117L, 133L, 121L, 125L,
116L, 91L, 110L, 65L, 95L, 43L, 75L, 38L, 43L, 24L, 38L, 16L,
36L, 5L, 15L, 2L, 9L, 7L, 9L, 1L, 3L, 3L, 2L, 1L)), .Names = c("maxrep",
"div", "freq"), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -38L))
My intention is to use ggplot2 to plot line graphs of 2 lines with different colour with text labels for each value.
What I did was
ggplot(df, aes(x=maxrep, y=freq, colour=div)) +
geom_line() +
geom_text(aes(label=freq), vjust=-.5)
The result was
Now my question: All the labels in the chart are above the points in respective lines. I want to have the labels for the different colours to be in different relative position, e.g. labels for cyan above the line, and labels for red below the line (i.e. variable vjust). Is there a way to do that?
Also, is there a way to get read of the letter a in the colour legend on the right?

What about plotting the lines separately wich differing vjust values? You can get rid of a in the legend setting show_guide = FALSE.
ggplot(df, aes(x=maxrep, y=freq, colour=div, label = freq)) +
geom_line() +
geom_text(data = df[df$div == "Second Division",], vjust=2, show_guide = FALSE) + geom_text(data = df[df$div == "Premier Division",], vjust=-2, show_guide = FALSE)
Which returns:

Create a new variable in the data.frame holding the vjust adjustment parameter:
df$pos <- c(2, -2)[(df$div == "Premier Division")+1]
And you could call vjust inside aes with the new pos vector:
ggplot(df, aes(x=maxrep, y=freq, colour=div)) +
geom_line() +
geom_text(aes(label=freq, vjust=pos))

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