Observation.jl

This module implements the observation logic itself.

add_to_dataframe!(df, stats)
add_to_dataframe!(df, stats, pre)
add_to_dataframe!(df, stats, pre, post)

Store results from observation type stats_t in dataframe df. With pre and post additional data that is not contained in the stats object can be added.

create_dataframe!(stats_t, df)

Add columns to a dataframe df, so that it can record the data from an observation type stats_t.

concatenate named tuple and/or struct types into one single named tuple

log_results(out, stats; FS, LS)

Print results stored in stats to output using field separator FS and line separator LS.

print_header(output, stats_t; FS, NS, LS)

Print a header for an observation type stats_t to output using field separator FS, name separator NS and line separator LS.

translate accumulator types into prefixes for the header (e.g. min, max, etc.)

construct a named tuple from x

obtain a named tuple type with the same field types and names as struct_T

@observe(statstype, user_arg1 [, user_arg2...], declarations)

Generate a full analysis and logging suite for a set of data structures.

Observe expects a (new) type name, a number of user arguments and a block of declarations. It will generate a function observe that takes the user arguments and returns an instance of the data type. The declaration block will be copied verbatim to the body of the observe function, but all occurences of the "pseudo-macros" @record and @stat will be replaced with corresponding analysis code.

The newly defined result data type will contain properties for all calculated results.

So, given a declaration

@observe Data model stat1 stat2 begin
	@record "time"      model.time
	@record "N"     Int length(model.population)

	for ind in model.population 
		@stat("capital", MaxMinAcc{Float64}, MeanVarAcc{FloatT}) <| ind.capital
		@stat("n_alone", CountAcc)           <| has_neighbours(ind)
	end

	@record s1			stat1
	@record s2			stat1 * stat2
end

a type Data will be generated that provides (at least) the following members:

struct Data
	time :: Float64
	N :: Int
	capital :: @NamedTuple{max :: Float64, min :: Float64, mean :: Float64, var :: Float64}
	n_alone :: @NamedTuple{N :: Int}
	s1 :: Float64
	s2 :: Float64
end

The macro will also create a method observe(::Type{Data), model, stat1, stat2) that will perform the required calculations and returns a Data object.

Use print_header to print a header for the generated type to an output and log_results to print the content of a data object.