- How To Change Color Palette On Research Ireland
- How To Change Color Palette On Research Irvine
- How To Change Color Palette On Research Irs
- How To Change Color Palette On Research Irving
R/ggsurvplot.RThe proposed rating prediction model is trained using a human color preference dataset. The model allows a user to extend a color palette, e.g., from three colors to five or seven colors, while retaining color harmony. In addition, we present a color search scheme for a given palette and a customized version of the proposed model for a specific. While good color palettes are easy to come by these days, finding the right color palette for data visualizations is still quite challenging. At Graphiq, things are arguably made even more difficult, as we need to convey information across thousands of unique data sets in many different types of visualization layouts. Every three-color primary palette will have some weaknesses in color rendering, and artists who want to be able to achieve pure purples, oranges, and greens will have to add colors to it. One way to address this weakness is by adding a single missing pigment, such as green or orange, or by choosing to use a six-color split primary palette instead.
ggsurvplot() is a generic function to plot survival curves. Wrapper around the ggsurvplot_xx() family functions. Plot one or a list of survfit objects as generated by the survfit.formula() and surv_fit functions:
ggsurvplot_list()
ggsurvplot_facet()
ggsurvplot_group_by()
ggsurvplot_add_all()
ggsurvplot_combine()
See the documentation for each function to learn how to control that aspect of the ggsurvplot(). ggsurvplot() accepts further arguments to be passed to the ggsurvplot_xx() functions. Has options to:
plot a list of survfit objects,
facet survival curves into multiple panels,
group dataset by one or two grouping variables and to create the survival curves in each subset,
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combine multiple
survfitobjects into one plot,add survival curves of the pooled patients (null model) onto the main stratified plot,
plot survival curves from a data frame containing survival curve summary as returned by surv_summary().
Arguments
| fit | allowed values include:
|
|---|---|
| data | a dataset used to fit survival curves. If not supplied then datawill be extracted from 'fit' object. |
| fun | an arbitrary function defining a transformation of the survivalcurve. Often used transformations can be specified with a characterargument: 'event' plots cumulative events (f(y) = 1-y), 'cumhaz' plots thecumulative hazard function (f(y) = -log(y)), and 'pct' for survivalprobability in percentage. |
| color | color to be used for the survival curves.
|
| palette | the color palette to be used. Allowed values include 'hue' forthe default hue color scale; 'grey' for grey color palettes; brewer palettese.g. 'RdBu', 'Blues', ..; or custom color palette e.g. c('blue', 'red'); and scientific journal palettes from ggsci R package, e.g.: 'npg', 'aaas', 'lancet', 'jco', 'ucscgb', 'uchicago', 'simpsons' and 'rickandmorty'.See details section for more information. Can be also a numeric vector oflength(groups); in this case a basic color palette is created using thefunction palette. |
| linetype | line types. Allowed values includes i) 'strata' for changinglinetypes by strata (i.e. groups); ii) a numeric vector (e.g., c(1, 2)) or acharacter vector c('solid', 'dashed'). |
| conf.int | logical value. If TRUE, plots confidence interval. |
| pval | logical value, a numeric or a string. If logical and TRUE, thep-value is added on the plot. If numeric, than the computet p-value issubstituted with the one passed with this parameter. If character, then thecustomized string appears on the plot. See examples - Example 3. |
| pval.method | whether to add a text with the test name used forcalculating the pvalue, that corresponds to survival curves' comparison -used only when |
| test.for.trend | logical value. Default is FALSE. If TRUE, returns thetest for trend p-values. Tests for trend are designed to detect ordereddifferences in survival curves. That is, for at least one group. The testfor trend can be only performed when the number of groups is > 2. |
| surv.median.line | character vector for drawing a horizontal/verticalline at median survival. Allowed values include one of c('none', 'hv', 'h','v'). v: vertical, h:horizontal. |
| risk.table | Allowed values include:
|
| cumevents | logical value specifying whether to show or not the table ofthe cumulative number of events. Default is FALSE. |
| cumcensor | logical value specifying whether to show or not the table ofthe cumulative number of censoring. Default is FALSE. |
| tables.height | numeric value (in [0 - 1]) specifying the general heightof all tables under the main survival plot. |
| group.by | a character vector containing the name of grouping variables. Should be of length <= 2.Alias of the |
| facet.by | a character vector containing the name of grouping variablesto facet the survival curves into multiple panels. Should be of length <= 2.Alias of the |
| add.all | a logical value. If TRUE, add the survival curve of pooled patients (null model) onto the main plot.Alias of the |
| combine | a logical value. If TRUE, combine a list survfit objects on the same plot.Alias of the |
| ggtheme | function, ggplot2 theme name. Default value istheme_survminer. Allowed values include ggplot2 official themes: see |
| tables.theme | function, ggplot2 theme name. Default value istheme_survminer. Allowed values include ggplot2 official themes: see |
| .. | Futher arguments as described hereafter andother arguments to be passed i) to ggplot2 geom_*() functions such as linetype, size, ii) or to the function ggpar() for customizing the plots. See details section. |
| x | an object of class ggsurvplot |
| surv.plot.height | the height of the survival plot on the grid. Defaultis 0.75. Ignored when risk.table = FALSE. |
| risk.table.height | the height of the risk table on the grid. Increasethe value when you have many strata. Default is 0.25. Ignored whenrisk.table = FALSE. |
| ncensor.plot.height | The height of the censor plot. Used when |
| newpage | open a new page. See |
Value
return an object of class ggsurvplot which is list containing the following components:
plot: the survival plot (ggplot object)
table: the number of subjects at risk table per time (ggplot object).
cumevents: the cumulative number of events table (ggplot object).
ncensor.plot: the number of censoring (ggplot object).
data.survplot: the data used to plot the survival curves (data.frame).
data.survtable: the data used to plot the tables under the main survival curves (data.frame).
Details
How To Change Color Palette On Research Ireland
Color palettes: The argument palette can be used to specify the color to be used for each group. By default, the first color in the palette is used to color the first level of the factor variable. This default behavior can be changed by assigning correctly a named vector. That is, the names of colors should match the strata names as generated by the
ggsurvplot()function in the legend.
FURTHER ARGUMENTS
Customize survival plots and tables. See also ggsurvplot_arguments.
Plot title and axis labels
title: main title.
xlab, ylab: x and y axis labels, respectively.
Legend title, labels and position
legend: character specifying legend position. Allowed values are one of c('top', 'bottom', 'left', 'right', 'none'). Default is 'top' side position. to remove the legend use legend = 'none'. Legend position can be also specified using a numeric vector c(x, y). In this case it is possible to position the legend inside the plotting area. x and y are the coordinates of the legend box. Their values should be between 0 and 1. c(0,0) corresponds to the 'bottom left' and c(1,1) corresponds to the 'top right' position. For instance use legend = c(0.8, 0.2).
legend.title: legend title.
legend.labs: character vector specifying legend labels. Used to replace the names of the strata from the fit. Should be given in the same order as those strata.
Axis limits, breaks and scales
break.time.by: numeric value controlling time axis breaks. Default value is NULL.
break.x.by: alias of break.time.by. Numeric value controlling x axis breaks. Default value is NULL.
break.y.by: same as break.x.by but for y axis.
surv.scale: scale transformation of survival curves. Allowed values are 'default' or 'percent'.
xscale: numeric or character value specifying x-axis scale.
If numeric, the value is used to divide the labels on the x axis. For example, a value of 365.25 will give labels in years instead of the original days.
If character, allowed options include one of - 'd_m', 'd_y', 'm_d', 'm_y', 'y_d' and 'y_m' - where
d = days,m = monthsandy = years. For example,xscale = 'd_m'will transform labels from days to months;xscale = 'm_y', will transform labels from months to years.
xlim,ylim: x and y axis limits e.g. xlim = c(0, 1000), ylim = c(0, 1).
axes.offset: logical value. Default is TRUE. If FALSE, set the plot axes to start at the origin.
Confidence interval
conf.int.fill: fill color to be used for confidence interval.
conf.int.style: confidence interval style. Allowed values include c('ribbon', 'step').
conf.int.alpha: numeric value specifying confidence fill color transparency. Value should be in [0, 1], where 0 is full transparency and 1 is no transparency.
P-value
pval.size: numeric value specifying the p-value text size. Default is 5.
pval.coord: numeric vector, of length 2, specifying the x and y coordinates of the p-value. Default values are NULL.
pval.method.size: the same as
pval.sizebut for displayinglog.rank.weightsname.pval.method.coord: the same as
pval.coordbut for displayinglog.rank.weightsname.log.rank.weights: the name for the type of weights to be used in computing the p-value for log-rank test. By default
survdiffis used to calculate regular log-rank test (with weights 1). A user can specify'1', 'n', 'sqrtN', 'S1', 'S2', 'FH'to use weights specified in comp, so that weight correspond to the test as : 1 - log-rank, n - Gehan-Breslow (generalized Wilcoxon), sqrtN - Tarone-Ware, S1 - Peto-Peto's modified survival estimate, S2 - modified Peto-Peto (by Andersen), FH - Fleming-Harrington(p=1, q=1).
Median survival
surv.median.line: character vector for drawing a horizontal/vertical line at median survival. Allowed values include one of c('none', 'hv', 'h', 'v'). v: vertical, h:horizontal.
Censor points
censor: logical value. If TRUE (default), censors will be drawn.
censor.shape: character or numeric value specifying the point shape of censors. Default value is '+' (3), a sensible choice is '|' (124).
censor.size: numveric value specifying the point size of censors. Default is 4.5.
How To Change Color Palette On Research Irvine
Survival tables
General parameters for all tables. The arguments below, when specified, will be applied to all survival tables at once (risk, cumulative events and cumulative censoring tables).
tables.col: color to be used for all tables under the main plot. Default value is 'black'. If you want to color by strata (i.e. groups), use tables.col = 'strata'.
fontsize: font size to be used for the risk table and the cumulative events table.
font.family: character vector specifying text element font family, e.g.: font.family = 'Courier New'.
tables.y.text: logical. Default is TRUE. If FALSE, the y axis tick labels of tables will be hidden.
tables.y.text.col: logical. Default value is FALSE. If TRUE, the y tick labels of tables will be colored by strata.
tables.height: numeric value (in [0 - 1]) specifying the general height of all tables under the main survival plot. Increase the value when you have many strata. Default is 0.25.
Specific to the risk table
risk.table.title: the title to be used for the risk table.
risk.table.pos: character vector specifying the risk table position. Allowed options are one of c('out', 'in') indicating 'outside' or 'inside' the main plot, respectively. Default value is 'out'.
risk.table.col,risk.table.fontsize,risk.table.y.text,risk.table.y.text.colandrisk.table.height: same as for the general parameters but applied to the risk table only.
Specific to the number of cumulative events table (cumevents)
cumevents.title: the title to be used for the cumulative events table.
cumevents.col, cumevents.y.text, cumevents.y.text, cumevents.height: same as for the general parameters but for the cumevents table only.
Specific to the number of cumulative censoring table (cumcensor)
cumcensor.title: the title to be used for the cumcensor table.
cumcensor.col,cumcensor.y.text,cumcensor.y.text.col,cumcensor.height: same as for the general parameters but for cumcensor table only.
Survival plot height
surv.plot.height: the height of the survival plot on the grid. Default is 0.75. Ignored when risk.table = FALSE.
How To Change Color Palette On Research Irs
Number of censored subjects barplot
ncensor.plot: logical value. If TRUE, the number of censored subjects at time t is plotted. Default is FALSE. Ignored when cumcensor = TRUE.
ncensor.plot.title: the title to be used for the censor plot. Used when
ncensor.plot = TRUE.ncensor.plot.height: the height of the censor plot. Used when
ncensor.plot = TRUE.
Other graphical parameters
The plot can be easily customized using additional arguments to be passed to the function ggpar().
These arguments include font.title, font.subtitle, font.caption, font.x, font.y, font.tickslab and font.legend, which are vectors of length 3 indicating respectively the size (e.g.: 14), the style (e.g.: 'plain', 'bold', 'italic', 'bold.italic') and the color (e.g.: 'red') of main title, subtitle, caption, xlab and ylab, axis tick labels and legend, respectively. For example font.x = c(14, 'bold', 'red').
Use font.x = 14, to change only font size; or use font.x = 'bold', to change only font face.
Examples
Recently, I had a Level I student ask me a question I’d never heard before. He asked why there were so many palette choices on his infrared camera. Often I’m asked which palette works best, or which my personal preference is. I’d never had anyone ask me why there are so many choices. He went on to say that he had trouble picking which one to use. That’s actually kind of a nice problem to have!
By and large, which palette you apply to your images, either while inspecting or when generating a report, is a matter of personal choice. Your inspection program might dictate such things, but often they don’t, so the thermographer is given free rein to pick as they like. As sweet a deal as this is, there are some points to consider when exercising this freedom.
- Most importantly, what might your customer want? The “WOW” factor of a multicolor palette goes a long way with some folks, while others like to keep it simple.
- Another point, how intuitive are the colors you choose? Your report loses impact when the end user has to try and decipher which color or shade corresponds with which range of apparent temperatures.
- Are you delivering the data accurately? Beyond impressing your customer with brilliant images, your chief goal is to deliver useful data. Sometimes the color palette matters in that regard.
Infrared Camera Color Palette Choices
How To Change Color Palette On Research Irving
Infrared Camera Color Palette Choices
Whichever you choose, make sure you explain to your customer which colors denote which ranges of temperature to reduce confusion. Freedom of choice is a wonderful thing in the thermal world, just makes sure you use it wisely.
Thinking Thermally,
The Snell Group, a Fluke Thermal Imaging Blog content partner