ggplot2 | An implementation of the Grammar of Graphics in R | Data Visualization library

I am trying to convert a geom_tile plot built with ggplot to ggplotly. However, the tiles are distorted in plotly. The same issues takes place with geom_raster.

Showcase:

I have measurements of a quantity (value) at specific points (lon and lat), like the example data below:

There are so many ways to define colour scales within ggplot2. After just loading ggplot2 I count 22 functions beginging with scale_color_* (or scale_colour_*) and same number beginging with scale_fill_*. Is it possible to briefly name the purpose of the functions below? Particularly I struggle with the differences of some of the functions and when to use them.

• scale_*_binned()
• scale_*_brewer()
• scale_*_continuous()
• scale_*_date()
• scale_*_datetime()
• scale_*_discrete()
• scale_*_distiller()
• scale_*_fermenter()
• scale_*_gradient()
• scale_*_gradient2()
• scale_*_gradientn()
• scale_*_grey()
• scale_*_hue()
• scale_*_identity()
• scale_*_manual()
• scale_*_ordinal()
• scale_*_steps()
• scale_*_steps2()
• scale_*_stepsn()
• scale_*_viridis_b()
• scale_*_viridis_c()
• scale_*_viridis_d()

What I tried

I've tried to make some research on the web but the more I read the more I get onfused. To drop some random example: "The default scale for continuous fill scales is scale_fill_continuous() which in turn defaults to scale_fill_gradient()". I do not get what the difference of both functions is. Again, this is just an example. Same is true for scale_color_binned() and scale_color_discrete() where I can not name the difference. And in case of scale_color_date() and scale_color_datetime() the destription says "scale_*_gradient creates a two colour gradient (low-high), scale_*_gradient2 creates a diverging colour gradient (low-mid-high), scale_*_gradientn creates a n-colour gradient." which is nice to know but how is this related to scale_color_date() and scale_color_datetime()? Looking for those functions on the web does not give me very informative sources either. Reading on this topic gets also chaotic because there are tons of color palettes in different packages which are sequential/ diverging/ qualitative plus one can set same color in different ways, i.e. by color name, rgb, number, hex code or palette name. In part this is not directly related to the question about the 2*22 functions but in some cases it is because providing a "wrong" palette results in an error (e.g. the error"Continuous value supplied to discrete scale).

Why I ask this

I need to do many plots for my work and I am supposed to provide some function that returns all kind of plots. The plots are supposed to have similiar layout so that they fit well together. One aspect I need to consider here is that the colour scales of the plots go well together. See here for example, where so many different kind of plots have same colour scale. I was hoping I could use some general function which provides a colour palette to any data, regardless of whether the data is continuous or categorical, whether it is a fill or col easthetic. But since this is not how colour scales are defined in ggplot2 I need to understand what all those functions are good for.

Is there a way to put text along a density line, or for that matter, any path, in ggplot2? By that, I mean either once as a label, in this style of xkcd: 1835, 1950 (middle panel), 1392, or 2234 (middle panel). Alternatively, is there a way to have the line be repeating text, such as this xkcd #930 ? My apologies for all the xkcd, I'm not sure what these styles are called, and it's the only place I can think of that I've seen this before to differentiate areas in this way.

Note: I'm not talking about the hand-drawn xkcd style, nor putting flat labels at the top

I know I can place a straight/flat piece of text, such as via annotate or geom_text, but I'm curious about bending such text so it appears to be along the curve of the data.

I'm also curious if there is a name for this style of text-along-line?

Example ggplot2 graph using annotate(...):

Above example graph modified with curved text in Inkscape:

Edit: Here's the data for the first two trial runs in March and April, as requested:

I've built this new ggplot2 geom layer I'm calling geom_triangles (see https://github.com/ctesta01/ggtriangles/) that plots isosceles triangles given aesthetics including x, y, z where z is the height of the triangle and the base of the isosceles triangle has midpoint (x,y) on the graph.

What I want is for the geom_triangles() layer to automatically provide legend components for the height and width of the triangles, but I am not sure how to do that.

I understand based on this reference that I may need to adjust the draw_key argument in the ggproto StatTriangles object, but I'm not sure how I would do that and can't seem to find examples online of how to do it. I've been looking at the source code in ggplot2 for the draw_key functions, but I'm not sure how I would introduce multiple legend components (one for each of height and width) in a single draw_key argument in the StatTriangles ggproto.

There are existing questions asking about labeling a single geom_abline() in ggplot2:

• R ggplot2: Labelling a horizontal line on the y axis with a numeric value
• R ggplot2: Labeling a horizontal line without associating the label with a series
• Add label to abline ggplot2 [duplicate]

None of these get at a use-case where I wanted to add multiple reference lines to a scatter plot, with the intent of allowing easy categorization of points within slope ranges. Here is a reproducible example of the plot:

I've got data with time (seconds) on the x axis and intensity (in relative fluorescent units, or rfu) on the y-axis. It's generated by watching fragments of DNA pass a camera - the bigger the DNA fragment the bigger the time. There are 23 fragments of known size (in DNA base pair units, bp), and therefore there should be 23 peaks. As I know the size of the DNA fragments in bp, I want to recalibrate the x-axis from time (seconds) to base pairs (bp) using a linear model.

Unfortunately there is quite a lot of noise in the data that produces spurious peaks. The only way to confidently tell the true ones from the false ones is that the false ones don't fit the expected pattern in DNA base pairs.

I've provided data from one sample at this link in a data frame called demo. Unfortunately it's too large to paste below.

https://1drv.ms/t/s!AvBi5ipmBYfrhf0v_kvWuN2foLyBgg?e=RWfdXZ

I can pick out all the peaks as follows.

I was wondering if anyone knows a way to combine a table and ggplot legend so that the legend appears as a column in the table as shown in the image. Sorry if this has been asked before but I haven't been able to find a way to do this.

Edit: attached is code to produce the output below (minus the legend/table combination, which I am trying to produce, as I stitched that together in Powerpoint)

This is my code: