Used the following versions.
- Python 3.6
- Pandas 0.20.3
- Matplotlib 2.2.2
- Matlab > 2015
The following scripts should be present in the Matlab path.
- Legendflex package from
https://github.com/kakearney/legendflex-pkg
- Save2PDF from
https://uk.mathworks.com/matlabcentral/fileexchange/16179-save2pdf
The columns are as follows:
CRN
the CRN number.unique
is the CRN the exemplar for a specification isomorphic class.one
the unoptimized score (rate 1.0).score
the best optimized rate.r0
reaction 0 optimised rate.r1
reaction 1 optimised rate etc.
The columns are as follows:
- Column 0 input
s0
initial value. - Column 1 input
s1
initial value. - Column 2 unoptimized score (rate 1.0).
- Column 3 optimized score.
The columns are as follows:
i1
initial values of speciess1
etc.r0
optimized rate for reactionr0
etc.opt_time
absorption time of rates (r0, r1 etc)one_time
absorption time with rates all 1.0.
The columns are as follows:
i0
initial values of speciess0
. same fori1
etc.r0
the optimized rate of reaction 0, same forr1
etc.opt_time
the absorption time with optimised rates.one_time
the absorption time with rate 1.0.score
the accuracy of with the optimized rates.
Figure showing all the pre and post optimisation scores for AM_{3,3} and AM_{4,4} CRNs. Also shows the top scoring AM_{4,4} CRNs and shows how they compare to the top two AM_{3,3} CRNs.
-
3 reactions 3 species Approximate Majority results -
AMno11_S3_R3/summary_archetype.tsv
-
4 reactions 4 species Approximate Majority results -
AMno11_S4_R4/summary_archetype.tsv
-
4 reactions 4 species Approximate Majority results (specification isomorphic only) extra columns marking presence of different sub-networks. -
AMno11_S4_R4/summary_unique_subnets.tsv
python paper/fig_am_overview/overview_am_horiz.py
Heat maps of selected AM_{3,3} and AM_{4,4} CRNs.
paper/AMno11_S3_R3/Bimol_28.lbs
- LBS file with reactionspaper/AMno11_S3_R3/Bimol_28.time
- Hitting time datapaper/AMno11_S3_R3/Bimol_28.tsv
- Heat mappaper/AMno11_S3_R3/Bimol_36.lbs
paper/AMno11_S3_R3/Bimol_36.time
paper/AMno11_S3_R3/Bimol_36.tsv
paper/AMno11_S4_R4/Bimol_3750.lbs
paper/AMno11_S4_R4/Bimol_3750.time
paper/AMno11_S4_R4/Bimol_3750.tsv
paper/AMno11_S4_R4/Bimol_4854.lbs
paper/AMno11_S4_R4/Bimol_4854.time
paper/AMno11_S4_R4/Bimol_4854.tsv
Uncomment the appropriate directory in lines 8 to 13.
matlab Matlab/create_heatmaps.m
Figure showing the phase space and sepaatrix for two AM_{3,3} CRNs.
matlab Matlab/run_separatrix.m
Figure showing how long it takes to find CRNs with different numbers of reactions and species.
This data format is as follows
- Column 0 is the CRN number
- Column 1 is
$K + 1$ where the CRN was found - Column 2 is the time in seconds (since process start) when the CRN was found.
The files used are
paper/AMno11_z3_timmings/ApproximateMajorityNo11_3_3.tsv
paper/AMno11_z3_timmings/ApproximateMajorityNo11_4_4.tsv
paper/AMno11_z3_timmings/ApproximateMajorityNo11_4_3.tsv
paper/AMno11_z3_timmings/ApproximateMajorityNo11_3_4.tsv
matlab Matlab/z3_am_time.m
Showing how CME calculations scale with species numbers.
The data for this figure is stored in
Matlab/CMECalcEfficiency/times1.mat
matlab Matlab/CMECalcEfficiency/cme_am_time.m
Maximum 4 species 3 reactions, pre and post optimisation histograms.
paper/maximum_out_S4_R3/summary_archetype.tsv
python paper/fig_max_speed_ac/fig_max_histo.py
Maximum 4 species 3 reactions, Example speed/accuracy trade off figure.
paper/maximum_out_S4_R3/Bimol_1.speedtime
- Speed-accuracy trade off datapaper/maximum_out_S4_R3/Bimol_1.lbs
- CRN file usedpaper/maximum_out_S4_R3/Bimol_1_tf10000.tsv
- heatmap file
python paper/fig_max_speed_ac/fig_max_histo.py
Figure showing all the Division CRNs and how they score.
These are the results of optimising all the Division CRNs.
paper/DivNsel_S3_R3/summary.tsv
paper/DivNsel_S6_R2/summary.tsv
paper/DivNsel_S3_R5/summary.tsv
paper/DivNsel_S3_R2/summary.tsv
paper/DivNsel_S5_R4/summary.tsv
paper/DivNsel_S4_R5/summary.tsv
paper/DivNsel_S5_R3/summary.tsv
paper/DivNsel_S4_R2/summary.tsv
paper/DivNsel_S4_R3/summary.tsv
paper/DivNsel_S5_R2/summary.tsv
paper/DivNsel_S3_R4/summary.tsv
paper/DivNsel_S6_R3/summary.tsv
paper/DivNsel_S4_R4/summary.tsv
python paper/fig_div/fig_div_sumary.py
Selected heatmaps to display division CRN behaviour.
The heat maps and CRNs selected for accuracy heatmap.
DivNsel_S4_R4/Bimol_61586.tsv
- HeatmapDivNsel_S4_R4/Bimol_61586.lbs
- CRN codeDivNsel_S4_R4/Bimol_79523.tsv
DivNsel_S4_R4/Bimol_79523.lbs
DivNsel_S5_R4/Bimol_751168.tsv
DivNsel_S5_R4/Bimol_751168.lbs
DivNsel_leader/Bimol_2.tsv
DivNsel_leader/Bimol_2.lbs
Uncomment the appropriate directory in lines 8 to 13.
matlab Matlab/create_heatmaps.m
All CRNs shown in the paper are stored in a compressed format in the Storage
directory. To decompress all CRNs of a particular specification, you can call (for example)
python python/lbs_storage.py --crn_storage_file Storage\AMno11_S3_R3_CRNs.tsv -d AMno11_S3_R3 -r all
Alternatively, you can choose to decompress a single CRN by using its integer identifier as the argument for r
.