# IMPORTANT:        Users must change the following 4 arguments before trying to generate the superplot
# tidy or untidy format
data_format: tidy

# variable to display on the x axis
condition: drug

# variable to display on the y axis
value: variable

# variable used to denote experimental replicates
replicate: replicate

# csv file or Microsoft Excel file containing data in tidy data format
filename: demo_data.csv


# the label for the x axis. To have no label on the x axis, don't change the default value.
xlabel: REPLACE_ME

# label for the y axis. To have no label on the y axis, don't change the default value.
ylabel: Spreading area ($\mu$$m^2$)


# The following arguments below may be changed as the user desires

# order of the experimental conditions from left to right
# must be separated by ", " e.g. Control, Drug
order: Control, Drug

# use mean (default) or median to position the scatterpoints over each replicate
centre_val: mean

# use mean or median from each experimental replicate. Used to calculate the centre_val. Default: mean
middle_vals: mean

# standard deviation (SD, default) or 95% confidence interval (CI) if using median
error_bars: SD

# bandwidth of the fitted kernel density estimators. Determines smoothening of the
# stripes in each violin. "None" is the default value, which means an "optimal" # factor will be calculated
bw: None

# overlay statistics on plot. Only works for 2 or 3 conditions.
statistics: yes

# minimum and maximum y values to display on the y-axis e.g. 1, 5. Default value: None
ylimits: None

# width of each violinplot. Default value: 0.8
total_width: 0.8

# width of the black lines around each violinplot and the skeleton plot. Default value: 1
linewidth: 1

# width of the black lines separating replicates in each violin. Default value: 0.5
sep_linewidth: 0.5

# colours used for each individual replicates. List of potential colours available
# at https://matplotlib.org/stable/gallery/color/named_colors.html
# under the "CSS Colors" heading. Separate colours by ", " e.g. red, blue, green
# alternatively, use a colour map from
# https://matplotlib.org/stable/tutorials/colors/colormaps.html
cmap: Set2

# dpi used for rendering and saving Violin SuperPlots
dpi: 600
