[R] add median value and standard deviation bar to lattice plot
Luigi Marongiu
marongiu.luigi at gmail.com
Fri Mar 17 09:27:01 CET 2017
dear Bert,
the code as I read it draws 30 median lines, one for each cluster.
what I am looking for is a function that will plot 190 individual
confidence intervals, one for each measurement. would the code cover
even that instance?
regards
luigi
On Thu, Mar 16, 2017 at 2:41 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
> Just add whatever further code to decorate the groups as you like
> within the panel.groups function. I believe I have given you
> sufficient information in my code for you to do that if you study the
> code carefully. Depending on what you decide to do -- which is
> statistical and OT here (and not something I would offer specific
> advice on remotely anyway) -- you may also have to pass down
> additional arguments based on computations that you do with *all* the
> data from *all* groups together.
>
> 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 Thu, Mar 16, 2017 at 1:38 AM, Luigi Marongiu
> <marongiu.luigi at gmail.com> wrote:
>> dear Bert,
>> thank you for the solution, it worked perfectly. However I still would
>> like to know how reliable are the dots that are plotted, that is why i
>> would like to have individual bars on each dot (if possible). the
>> standard deviation maybe is not the right tool and the confidence
>> interval is perhaps better, but the procedure should be the same: draw
>> an arrow from the lower to the upper limit. is that possible?
>> regards,
>> luigi
>>
>> PS sorry for the formatting, usually plain text is my default; it
>> should have switched to html when i replied to a previous email but
>> the difference does not show up when i type...
>>
>> On Wed, Mar 15, 2017 at 4:28 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
>>> There may be a specific function that handles this for you, but to
>>> roll your own, you need a custom panel.groups function, not the
>>> default. You need to modify the panel function (which is
>>> panel.superpose by default) to pass down the "col" argument to the
>>> panel.segments call in the panel.groups function.
>>>
>>> This should get you started:
>>>
>>> useOuterStrips(
>>> strip = strip.custom(par.strip.text = list(cex = 0.75)),
>>> strip.left = strip.custom(par.strip.text = list(cex = 0.75)),
>>> stripplot(
>>> average ~ type|target+cluster,
>>> panel = function(x,y,col,...)
>>> panel.superpose(x,y,col=col,...),
>>> panel.groups = function(x,y,col,...){
>>> panel.stripplot(x,y,col=col,...)
>>> m <- median(y)
>>> panel.segments(x0 = x[1] -.5, y0 = m,
>>> x1 = x[1] +.5, y1 = m,
>>> col=col, lwd=2
>>> )
>>> },
>>> my.data,
>>> groups = type,
>>> pch=1,
>>> jitter.data = TRUE,
>>> main = "Group-wise",
>>> xlab = expression(bold("Target")), ylab = expression(bold("Reading")),
>>> col = c("grey", "green", "red"),
>>> par.settings = list(strip.background = list(col=c("paleturquoise",
>>> "grey"))),
>>> scales = list(alternating = FALSE, x=list(draw=FALSE)),
>>> key = list(
>>> space = "top",
>>> columns = 3,
>>> text = list(c("Blank", "Negative", "Positive"), col="black"),
>>> rectangles = list(col=c("grey", "green", "red"))
>>> )
>>> )
>>> )
>>>
>>> FWIW, I think adding 1 sd bars is a bad idea statistically.
>>>
>>> And though it made no difference here, please post in pain text, not HTML.
>>>
>>> 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 Wed, Mar 15, 2017 at 2:22 AM, Luigi Marongiu
>>> <marongiu.luigi at gmail.com> wrote:
>>>> Dear all,
>>>> I am analyzing some multivariate data that is organized like this:
>>>> 1st variable = cluster (A or B)
>>>> 2nd variable = target (a, b, c, d, e)
>>>> 3rd variable = type (blank, negative, positive)
>>>> 4th variable = sample (the actual name of the sample)
>>>> 5th variable = average (the actual reading -- please not that this is the
>>>> mean of different measures with an assumed normal distribution, but the
>>>> assumption might not always be true)
>>>> 6th variable = stdev (the standard deviation associated with each reading)
>>>> 7th variable = ll (lower limit that is average stdev)
>>>> 8th variable = ul (upper limit that is average + stdev)
>>>>
>>>> I am plotting the data using lattice's stripplot and I would need to add:
>>>> 1. an error bar for each measurement. the bar should be possibly coloured
>>>> in light grey and semitransparent to reduce the noise of the plot.
>>>> 2. a type-based median bar to show differences in measurements between
>>>> blanks, negative and positive samples within each panel.
>>>>
>>>> How would I do that?
>>>> Many thanks,
>>>> Luigi
>>>>
>>>>>>>
>>>> cluster <- c(rep("A", 90), rep("B", 100))
>>>> sample <- c(
>>>> rep(c("cow-01", "cow-02", "cow-03", "cow-04", "cow-05", "cow-06",
>>>> "cow-07", "cow-08", "cow-09", "cow-10", "cow-11",
>>>> "cow-12", "cow-13", "cow-14", "cow-15", "cow-16", "cow-17",
>>>> "blank"), 5),
>>>> rep(c("cow-26", "cow-35", "cow-36", "cow-37", "cow-38", "cow-39",
>>>> "cow-40", "cow-41", "cow-42", "cow-43", "cow-44", "cow-45",
>>>> "cow-46", "cow-47", "cow-48", "cow-49", "cow-50", "cow-51",
>>>> "cow-59", "blank"), 5)
>>>> )
>>>> type <- c(
>>>> rep(c("negative", "negative", "negative", "negative", "negative",
>>>> "negative", "negative", "negative", "positive", "positive",
>>>> "positive", "positive", "positive", "positive", "positive",
>>>> "positive", "positive", "blank"), 5),
>>>> rep(c("negative", "positive", "negative", "negative", "negative",
>>>> "negative", "negative", "negative", "positive", "positive",
>>>> "positive", "positive", "positive", "positive", "positive",
>>>> "positive", "positive", "positive", "positive", "blank"), 5)
>>>> )
>>>> target <- c(
>>>> c(rep("a", 18), rep("b", 18), rep("c", 18), rep("d", 18), rep("e", 18)),
>>>> c(rep("a", 20), rep("b", 20), rep("c", 20), rep("d", 20), rep("e", 20))
>>>> )
>>>> average <- c(88.5, 49, 41, 33, 35, 45, 95, 30, 41, 64, 22, 29, 59, 71, 128, 39,
>>>> 42, 47, 86, 100,
>>>> 69, 44, 53, 66, 66, 71, 161, 69, 22.5, 30, 67, 99, 129, 94, 49,
>>>> 33, 28, 31, 26, 23,
>>>> 30, 41, 35, 23, 38, 43, 15, 21, 45, 51.5, 34, 26, 43, 32.5, 59,
>>>> 58.5, 61, 62.5, 58,
>>>> 59.5, 60.5, 60, 64, 110, 55, 66, 197, 83.5, 155, 76, 125, 90, 73,
>>>> 84, 95.5, 62, 82, 138,
>>>> 103.5, 57, 138, 149.5, 57, 54, 245.5, 191, 131, 96, 176, 45, 76,
>>>> 33, 37, 51, 44, 50, 54,
>>>> 66, 49, 90, 66.5, 42.5, 67, 56, 54, 50, 45, 99, 50, 51.5, 212, 40,
>>>> 68, 121, 80, 57,
>>>> 81.5, 128, 77, 119.5, 126, 184, 101, 103, 88, 100, 140, 186, 297,
>>>> 32, 184, 36, 45, 45, 44,
>>>> 86, 65, 61, 76, 62, 136, 84, 80, 56, 109, 116, 54, 59,
>>>> 79, 34, 74.5,
>>>> 54, 49, 55, 56,
>>>> 59, 56, 56, 57, 67, 65, 63, 52, 58, 59, 56, 54, 66, 92, 87, 59,
>>>> 33, 58, 51, 54,
>>>> 52, 47, 45, 42, 52, 57, 79, 42, 45.5, 47, 47, 36, 50, 53, 49 )
>>>> stdev <- c(17.85, 6.31, 3.42, 1.04, 0.51, 6.04, 38.43, 2.78, 5.55, 26.72, 1.83,
>>>> 9.92, 4.59, 19, 7.96,
>>>> 7.5, 1.06, 9.66, 75.94, 36.79, 50.45, 9.79, 1.55, 11.42, 64.12,
>>>> 0.79, 15.14, 16.15, 8.12, 4.04, 92.57, 35.35,
>>>> 42.28, 52.96, 7.06, 4.97, 1.15, 4.77, 6.59, 7.27, 0.75, 4.25,
>>>> 9, 0.1, 1.14, 4.17, 6.73, 3.81, 3.27,
>>>> 97.44, 9.74, 0.45, 8.14, 5.91, 13.1, 98.22, 8.92, 72.62, 70.26,
>>>> 59.46, 29.89, 56.35, 91.25, 49.94, 20.65, 62.04,
>>>> 95.13, 35.89, 99.64, 29.44, 33.12, 45.91, 96.69, 9.05, 38.56,
>>>> 3.09, 0.6, 8.69, 16.95, 74.03, 84.05, 39.87, 15.52,
>>>> 27.92, 35.72, 80.26, 71.93, 66.73, 87.8, 5.43, 98.3, 7.41, 9.86,
>>>> 63.64, 0.36, 5.84, 1.58, 20.1, 4.21, 82.12,
>>>> 19.29, 9.02, 22.12, 54.08, 74.95, 3.24, 9.67, 67.98,
>>>> 9.92, 40.69,
>>>> 6.24, 8.76, 74.25, 46.34, 25.69, 90.63, 83.71,
>>>> 73.53, 57.88, 15.84, 82.07, 67.45, 47.39, 98.77, 75.1,
>>>> 64.9, 3.71,
>>>> 87.44, 61.06, 4.77, 57.54, 7.68, 4.54, 6.15,
>>>> 3.32, 60.39, 33.78, 66.22, 18.67, 76.53, 63.54, 47.06, 38.47,
>>>> 88.15, 18.25, 4.26, 67.19, 88.87, 29.65, 7.33, 68.18,
>>>> 28.03, 6.91, 77.82, 22.23, 73.23, 95.21, 27.11, 37.01, 34.88,
>>>> 28.15, 11.27, 15.67, 96.08, 89.52, 28.6, 8.22, 23.55,
>>>> 59.2, 36.38, 41.38, 0.4, 56.82, 32.35, 20.6, 18.13, 8.15, 1.08,
>>>> 9.85, 1.07, 37.75, 97.6, 7.16, 8.51, 4.42,
>>>> 0.15, 1.28, 7.42, 71.15, 9.39)
>>>> ll <- c(70.65, 42.69, 37.58, 31.96, 34.49, 38.96, 56.57, 27.22, 35.45,
>>>> 37.28, 20.17, 19.08, 54.41, 52, 120.04, 31.5, 40.94, 37.34,
>>>> 10.06, 63.21, 18.55, 34.21, 51.45, 54.58, 1.88, 70.21, 145.86,
>>>> 52.85, 14.38, 25.96, -25.57, 63.65, 86.72, 41.04, 41.94, 28.03,
>>>> 26.85, 26.23, 19.41, 15.73, 29.25, 36.75, 26, 22.9, 36.86, 38.83,
>>>> 8.27, 17.19, 41.73, -45.94, 24.26, 25.55, 34.86, 26.59, 45.9,
>>>> -39.72, 52.08, -10.12, -12.26, 0.0399999999999991, 30.61, 3.65,
>>>> -27.25, 60.06, 34.35, 3.96, 101.87, 47.61, 55.36, 46.56, 91.88, 44.09,
>>>> -23.69, 74.95, 56.94, 58.91, 81.4, 129.31, 86.55, -17.03, 53.95,
>>>> 109.63, 41.48, 26.08, 209.78, 110.74, 59.07, 29.27, 88.2, 39.57,
>>>> -22.3, 25.59, 27.14, -12.64, 43.64, 44.16, 52.42, 45.9, 44.79, 7.88,
>>>> 47.21, 33.48, 44.88, 1.92, -20.95, 46.76, 35.33, 31.02,
>>>> 40.08, 10.81, 205.76, 31.24, -6.25, 74.66, 54.31, -33.63,
>>>> -2.20999999999999, 54.47, 19.12, 103.66, 43.93, 116.55, 53.61, 4.23,
>>>> 12.9, 35.1, 136.29, 98.56, 235.94, 27.23, 126.46, 28.32, 40.46,
>>>> 38.85, 40.68, 25.61, 31.22, -5.22, 57.33, -14.53, 72.46, 36.94,
>>>> 41.53, -32.15, 90.75, 111.74, -13.19, -29.87, 49.35, 26.67,
>>>> 6.31999999999999, 25.97, 42.09, -22.82, 33.77, -14.23, -39.21, 28.89,
>>>> 19.99, 32.12, 36.85, 51.73, 36.33, -38.08, -30.52, 27.4, 45.78,
>>>> 42.45, 32.8, 50.62, 17.62, 32.6, 1.18, 18.65, 33.4, 33.87, 38.85,
>>>> 43.92, 32.15, 50.93, 19.25, -18.6, 34.84, 36.99, 42.58, 46.85,
>>>> 34.72, 42.58, -18.15, 39.61)
>>>> ul <- c(106.35, 55.31, 44.42, 34.04, 35.51, 51.04, 133.43, 32.78, 46.55,
>>>> 90.72, 23.83, 38.92, 63.59, 90, 135.96, 46.5, 43.06, 56.66,
>>>> 161.94, 136.79, 119.45, 53.79, 54.55, 77.42, 130.12, 71.79, 176.14,
>>>> 85.15, 30.62, 34.04, 159.57, 134.35, 171.28, 146.96, 56.06, 37.97,
>>>> 29.15, 35.77, 32.59, 30.27, 30.75, 45.25, 44, 23.1, 39.14, 47.17,
>>>> 21.73, 24.81, 48.27, 148.94, 43.74, 26.45, 51.14, 38.41, 72.1,
>>>> 156.72, 69.92, 135.12, 128.26, 118.96, 90.39, 116.35, 155.25,
>>>> 159.94, 75.65, 128.04, 292.13, 119.39, 254.64, 105.44, 158.12, 135.91,
>>>> 169.69,
>>>> 93.05, 134.06, 65.09, 82.6, 146.69, 120.45, 131.03, 222.05, 189.37,
>>>> 72.52, 81.92, 281.22, 271.26, 202.93, 162.73, 263.8, 50.43, 174.3,
>>>> 40.41, 46.86, 114.64, 44.36, 55.84, 55.58, 86.1, 53.21, 172.12,
>>>> 85.79, 51.52, 89.12, 110.08, 128.95, 53.24, 54.67, 166.98, 59.92,
>>>> 92.19, 218.24, 48.76, 142.25, 167.34, 105.69, 147.63, 165.21,
>>>> 201.53, 134.88, 135.34, 208.07, 251.45, 148.39, 201.77, 163.1, 164.9,
>>>> 143.71,
>>>> 273.44, 358.06, 36.77, 241.54, 43.68, 49.54, 51.15, 47.32, 146.39,
>>>> 98.78, 127.22, 94.67, 138.53, 199.54, 131.06, 118.47, 144.15, 127.25,
>>>> 120.26, 121.19, 147.87, 108.65, 41.33, 142.68, 82.03, 55.91, 132.82,
>>>> 78.23, 132.23, 151.21, 83.11, 94.01, 101.88, 93.15, 74.27, 67.67,
>>>> 154.08, 148.52, 84.6, 62.22, 89.55, 151.2, 123.38, 100.38, 33.4,
>>>> 114.82, 83.35, 74.6, 70.13, 55.15, 46.08, 51.85, 53.07, 94.75, 176.6,
>>>> 49.16, 54.01, 51.42, 47.15, 37.28, 57.42, 124.15, 58.39)
>>>> my.data <- data.frame(cluster, type, target, sample, average, stdev, ll,
>>>> ul, stringsAsFactors = FALSE)
>>>>
>>>> library(lattice)
>>>> library(latticeExtra)
>>>> useOuterStrips(
>>>> strip = strip.custom(par.strip.text = list(cex = 0.75)),
>>>> strip.left = strip.custom(par.strip.text = list(cex = 0.75)),
>>>> stripplot(
>>>> average ~ type|target+cluster,
>>>> my.data,
>>>> groups = type,
>>>> pch=1,
>>>> jitter.data = TRUE,
>>>> main = "Group-wise",
>>>> xlab = expression(bold("Target")), ylab = expression(bold("Reading")),
>>>> col = c("grey", "green", "red"),
>>>> par.settings = list(strip.background = list(col=c("paleturquoise",
>>>> "grey"))),
>>>> scales = list(alternating = FALSE, x=list(draw=FALSE)),
>>>> key = list(
>>>> space = "top",
>>>> columns = 3,
>>>> text = list(c("Blank", "Negative", "Positive"), col="black"),
>>>> rectangles = list(col=c("grey", "green", "red"))
>>>> )
>>>> )
>>>> )
>>>>
>>>> [[alternative HTML version deleted]]
>>>>
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