option for logscale on histogram y axis

slurm-eff-tool.py

@@ -1479,7 +1479,8 @@ def histogram_table(
 
     return edges, counts
 
-def histo_graphs(out_rows: list[OutputRow], colnames: list[str]):
+def histo_graphs(out_rows: list[OutputRow], args: argparse.Namespace):
+    colnames = args.histo.lower().split(',')
     for metric in colnames:
         tmpfile = tempfile.NamedTemporaryFile(mode='w+t', delete=False,
                                          dir='.',prefix=f"tmp-seff-{metric}",
@@ -1503,6 +1504,9 @@ def histo_graphs(out_rows: list[OutputRow], colnames: list[str]):
             tmpfile.write("\n")
         tmpfile.close()
 
+        logy = ""
+        if args.hlogy:
+            logy = "set logscale y\n"
         gnuplot_cmd = f"""set title "{metric} distribution" noenhanced
 set xlabel "{metric}" noenhanced
 set ylabel "Jobs"
@@ -1513,6 +1517,7 @@ set terminal dumb enhanced size 120, 30
 
 set colorsequence classic
 set terminal dumb ansi size 120, 30
+{logy}
 plot_cmd = 'plot "{tmpfile.name}" \\
 """
         # gnuplot_cmd += f' using 1:2 with boxes title "{names[0]}" \\\n'
@@ -1621,6 +1626,8 @@ def parse_args(argv: list[str]) -> argparse.Namespace:
     p.add_argument("--expr", help="filter using an arithmetic expression using column names as variables (case insensitive). Don't use for state (use --state flag instead).",
                    default=None)
     p.add_argument("-H", "--histo", help=f"print histogram of the given metric (Supported columns: {', '.join(HISTO_COLUMNS)}).", default=None)
+    p.add_argument("--hlogy", action="store_true", help="use logscale for histogram y axis")
+
     # Options for writing/reading cache files
     p.add_argument("-B", "--write-binary-cache", help="write a binary cache file in gzipped msgpack format")
     p.add_argument("-L", "--load-binary-cache", help="load a binary cache file in gzipped msgpack format")
@@ -1711,7 +1718,7 @@ def main(argv: list[str] | None = None) -> int:
 
     # Histogramming
     if args.histo:
-        histo_graphs(out_rows, args.histo.lower().split(','))
+        histo_graphs(out_rows, args)
 
     return 0