We want to support many different plot types with many different 
ways to define what and how it should be plotted. There is a high 
overlap of settings that can be used for each plot type.

Here is an attempt to group everything.

Presentation
* subplots (n x m)
* single plot
* gallery
* table
* p-values / ANOVA / Chi-Square

Plot Types
* x-y relation
** Scatter
** Bubble (?)
* x-y relation for high number of points
** contour 
** 2d bins
** hex bins
* distributions: only one can be drawn
** histogram (bar) (?)
** density plot (filled) (?)
* distributions: many can be drawn
** histogram (line)
** density plot (line)
** cumulative distribution
** quantile-quantile plot (?)
** boxplots
** violins
** strip charts / sina plots 
** overlapping densities (?)
** ridgeline plots
* proportions
** pie chart 
** bars (horizontal / vertical / stacked)
* custom
** parallel requests 


Filters
* query
* group by
** field
** intervals (1m, 5m, 15m, 1h, ...)
* split by
* limit
* date ranges (1...n)
* find all method calls active at a specific time 

Axis
* log/linear
* y-range

options
* error bars
* trend lines (cubic splines, B-splines, thin-plate splines, Gaussian process splines)

Metrics
* min/max
* count
* average
* percentiles (median, 90-percentile, ...)


Format 
* color palette
* highlight selected lines 


The presentation defines how many plots you can define. It also influences some of 
the available filters. E.g. the gallery requires to define a 'split by' field. 
Each plot type defines which subset of filters, axis definitions, decorations and 
metrics is available. It also defines which plot types are available for the X2 axis.
For example, you cannot combine a pie chart with a scatter plot.

Plots in more detail
Scatter
	x: time
	y: duration
	filters (required): query, date range
	filters (optional): group by, limit, intervals
	filters (forbidden):
	axis: log/linear, y-range
	options: trend lines
	metrics: min/max, count, average, percentiles
	combine: contour
	X2-axis: cumulative distribution, histogram (line), density plot (line), Parallel Requests

Cumulative Distribution:
	x: percent
	y: duration
	filters (required): query, date range
	filters (optional): group by, limit, intervals
	filters (forbidden):
	axis: log/linear, y-range
	options: 
	metrics: min/max, count, average, percentiles
	combine: 
	X2-axis: scatter, Parallel Requests
	
Contour:
	x: time
	y: duration
	filters (required): query, date range
	filters (optional): intervals
	filters (forbidden): group by, limit
	options:
	combine: scatter
	X2:axis: 
	
	
Parallel Requests:
	x: time
	y: count
	filters (required): query, date range
	filters (optional): 
	filters (forbidden): group by, limit, intervals
	axis: log/linear, y-range
	options: 
	metrics: min/max, average
	combine: 
	X2-axis: scatter, cumulative distribution, 


Violin:
	x: group
	y: duration
	filters (required): query, date range, group by, limit, intervals
	filters (optional): 
	filters (forbidden):  
	axis: log/linear, y-range
	decorations: 
	options: 
	combine: strip charts
	
bar chart:
	x: group
	y: metric
	filters (required): query, date range, group by, limit, intervals
	filters (optional): 
	filters (forbidden):
	axis: log/linear, y-range
	decorations: 
	options: 
	combine: 












Use Cases:
* Find slow requests
* Find requests with unusually slow requests.
** max value > x
** 95-percentile/90-percentile > x
** num values > x
* How many requests were active at some point in time?
* Understand the distribution of response times.
* Identify locking issues.
* Find regressions.