Commit fafb4927 authored by Yoann Dufresne's avatar Yoann Dufresne

rename the snakefile for evaluation

parent adaaa105
......@@ -32,7 +32,7 @@ To know how to use it please use the -h command line option.
### Test the complete pipeline on simulated data
For a complete test, we made a bunch of snakemake files.
If you are looking for a complete pipeline from synthetic data generation, you should look into the "Snakefile_d2_eval" file.
If you are looking for a complete pipeline from synthetic data generation, you should look into the "Snakefile_lcpg_eval" file.
You can play with the N (number of molecules in the interval graph), M (average number of merge to perform in a barcode), DEV (standard deviation on merge) variables to see impact on performances.
These values are arrays. You can enter multiple values and all the combinations will be done.
A summary is output in the tsv file "{WORKDIR}/eval_compare_maxclique.tsv.
......@@ -40,7 +40,7 @@ Warning: the pipeline can be very slow for huge number of parameters.
Command to run the pipeline:
```
snakemake -s Snakefile_d2_eval
snakemake -s Snakefile_lcpg_eval
```
### Data simulation
......
......@@ -3,7 +3,7 @@ number_try = 5
threshold = 0.9
rule d2_path_generation:
rule lcp_path_generation:
input:
d2="{path}_d2_{type}_{method}.gexf"
output:
......
include: "Snakefile_data_simu"
include: "Snakefile_lcpg"
include: "Snakefile_d2_path"
include: "Snakefile_lcp_path"
WORKDIR = "snake_experiments" if "workdir" not in config else config["workdir"]
N = [500]
......@@ -32,7 +32,7 @@ rule comparable_tsv:
splits = "/".join(path_eval_lines[-2].strip().split(': ')[-1].split(' - '))
print(f"{n}\t{m}\t{dev}\t{longest_path_d2}\t{greedy_path}\t{splits}", file=out)
rule eval_d2:
rule eval_lcpg:
input:
"{file}_d2_{type}_maxclq.gexf"
output:
......
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