From: Bryce Guinta <bryce.guinta@seagate.com>
Date: Tue, 6 Feb 2018 00:36:33 +0000 (-0700)
Subject: Make fiologparser_hist compatible with python3
X-Git-Tag: fio-3.4~6^2
X-Git-Url: https://git.kernel.dk/?p=fio.git;a=commitdiff_plain;h=bb36ebad32a8fc50cb11f5bb661064754cc0e54e;hp=-c

Make fiologparser_hist compatible with python3

In python3, map functions return generators, which caused numpy to break
in this script.

Use list comprehensions instead of map (more pythonic)
They also have the added benefit of behaving the same
between python2 and python3.
---

bb36ebad32a8fc50cb11f5bb661064754cc0e54e
diff --git a/tools/hist/fiologparser_hist.py b/tools/hist/fiologparser_hist.py
index 2e05b92c..62a4eb49 100755
--- a/tools/hist/fiologparser_hist.py
+++ b/tools/hist/fiologparser_hist.py
@@ -177,7 +177,7 @@ def print_all_stats(ctx, end, mn, ss_cnt, vs, ws, mx):
 
     avg = weighted_average(vs, ws)
     values = [mn, avg] + list(ps) + [mx]
-    row = [end, ss_cnt] + map(lambda x: float(x) / ctx.divisor, values)
+    row = [end, ss_cnt] + [float(x) / ctx.divisor for x in values]
     fmt = "%d, %d, %d, " + fmt_float_list(ctx, 5) + ", %d"
     print (fmt % tuple(row))
 
@@ -288,9 +288,9 @@ def main(ctx):
 
         max_cols = guess_max_from_bins(ctx, __HIST_COLUMNS)
         coarseness = int(np.log2(float(max_cols) / __HIST_COLUMNS))
-        bin_vals = np.array(map(lambda x: plat_idx_to_val_coarse(x, coarseness), np.arange(__HIST_COLUMNS)), dtype=float)
-        lower_bin_vals = np.array(map(lambda x: plat_idx_to_val_coarse(x, coarseness, 0.0), np.arange(__HIST_COLUMNS)), dtype=float)
-        upper_bin_vals = np.array(map(lambda x: plat_idx_to_val_coarse(x, coarseness, 1.0), np.arange(__HIST_COLUMNS)), dtype=float)
+        bin_vals = np.array([plat_idx_to_val_coarse(x, coarseness) for x in np.arange(__HIST_COLUMNS)], dtype=float)
+        lower_bin_vals = np.array([plat_idx_to_val_coarse(x, coarseness, 0.0) for x in np.arange(__HIST_COLUMNS)], dtype=float)
+        upper_bin_vals = np.array([plat_idx_to_val_coarse(x, coarseness, 1.0) for x in np.arange(__HIST_COLUMNS)], dtype=float)
 
     fps = [open(f, 'r') for f in ctx.FILE]
     gen = histogram_generator(ctx, fps, ctx.buff_size)
@@ -333,7 +333,8 @@ def main(ctx):
             start += ctx.interval
             end = start + ctx.interval
     finally:
-        map(lambda f: f.close(), fps)
+        for fp in fps:
+            fp.close()
 
 
 if __name__ == '__main__':