diff options
Diffstat (limited to 'bin/analyze-kconfig.py')
| -rwxr-xr-x | bin/analyze-kconfig.py | 17 |
1 files changed, 14 insertions, 3 deletions
diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py index aea441e..1ff98cf 100755 --- a/bin/analyze-kconfig.py +++ b/bin/analyze-kconfig.py @@ -25,11 +25,16 @@ from dfatool.model import AnalyticModel from dfatool.validation import CrossValidator -def write_csv(f, model, attr): +def write_csv(f, model, attr, precision=None): model_attr = model.attr_by_name[attr] attributes = sorted(model_attr.keys()) print(", ".join(model.parameters) + ", " + ", ".join(attributes), file=f) + if precision is not None: + data_wrapper = lambda x: f"{x:.{precision}f}" + else: + data_wrapper = str + # by convention, model_attr[attr].param_values is the same regardless of 'attr' for param_tuple in model_attr[attributes[0]].param_values: param_data = map( @@ -38,7 +43,7 @@ def write_csv(f, model, attr): print( ", ".join(map(str, param_tuple)) + ", " - + ", ".join(map(str, map(np.mean, param_data))), + + ", ".join(map(data_wrapper, map(np.mean, param_data))), file=f, ) @@ -75,6 +80,12 @@ def main(): help="Specify desired maximum standard deviation for decision tree generation, either as float (global) or <key>/<attribute>=<value>[,<key>/<attribute>=<value>,...]", ) parser.add_argument( + "--csv-precision", + type=int, + metavar="NDIGITS", + help="Precision (number of decimal digits) for CSV export", + ) + parser.add_argument( "--export-csv", type=str, metavar="FILE", @@ -323,7 +334,7 @@ def main(): target = f"{args.export_csv}-{name}.csv" print(f"Exporting aggregated data to {target}") with open(target, "w") as f: - write_csv(f, model, name) + write_csv(f, model, name, args.csv_precision) if args.export_csv_only: return |