A dataframe of theme options for things like colours and line widths

This is an example of the dataframe used to specify the colour themes and plot options (like line thickness). If you want to modify this file, see the section on Defining your own theme options below.

Format

An .rda file containing 23 objects of 2 variables

gray_shading_colour

Hex code for the colour used to fill the violin plots.

line_col

Hex code for the colour used for the line indicating periods when a hormone was applied.

rectangle_shading_colour

Hex code for the colour used to shade the rectangles.

both_sexes_shape

Numeric value representing the point shape used for data values where both sexes are included. Defaults to 15, which is a square.

male_shape

Numeric value representing the point shape used for data values where Sex == Male. Defaults to 16, which is a circle.

female_shape

Numeric value representing the point shape used for data values where Sex == Female. Defaults to 17, which is a triangle.

mean_point_colour

Hex code for the colour used to fill the mean data point in plots like the PPR comparison plot.

connecting_line_width

The width of the connecting line in action potential comparison plots.

connecting_line_colour

The colour of the connecting line in action potential comparison plots.

connecting_line_width_PPR

The width of the connecting line in paired-pulse ratio comparison plots.

mean_point_size

The size of the mean data point in plots like the PPR comparison plot.

baseline_group_colour

Hex code for the colour used when state == "Baseline" in plot_AP_comparison() and plot_AP_frequencies_single_treatment().

Defining your own theme options

Step 1: Create a .csv file with two columns (option and value) modelled after this sample dataset. Important!: Your .csv must have identical columns and rows as the sample data, or else some plots won't work!

Step 2: Read in the .csv file in using utils::read_csv(). This will now be an object in your R environment.

Step 3: Important!! You must convert the first column (option) into the rownames. This is a mandatory step to allow the theme_options to be indexed by row name in plotting functions.

Step 4: Run the following code:

library(tibble) my_sample_theme_options <- read.csv(here::here("Data/your_sample_theme_options.csv")) %>% remove_rownames %>% column_to_rownames(var="option")

Step 5: Check the resulting object. You should now have 11 objects of 1 variable, and the row names should be gray_shading_colour, line_col, etc.

Step 6: Go to a plotting function like plot_raw_current_data() and replace sample_theme_options with your newly created object from Step 5.