Added fit line using numpy.polyfit function.

Author: marek-trtik

scripts/make_performance_scatter_plots.py

@@ -3,6 +3,7 @@
 import json
 import matplotlib.pyplot as plt
 import matplotlib.lines as mlines
+import numpy
 import random
 
 
@@ -56,6 +57,8 @@ def make_scatter_plot(
         faxis_name=None,
         xaxis_log=False,
         faxis_log=False,
+        draw_diagonal=False,
+        draw_fitline=False,
         size_xy=None,
         dpi=None
         ):
@@ -79,17 +82,27 @@ def make_scatter_plot(
     if xaxis_log:
         ax.set_xscale('log')
     if faxis_log:
-        ax.set_yscale('log')
+        ax.set_yscale('symlog')
     ax.grid(True, linestyle='dotted')
     xs = []
     ys = []
     for x, y in points:
         xs.append(x)
         ys.append(y)
     ax.scatter(xs, ys)
-    line = mlines.Line2D([0, 1], [0, 1], color="red")
-    line.set_transform(ax.transAxes)
-    ax.add_line(line)
+    if draw_diagonal:
+        line = mlines.Line2D([0, 1], [0, 1], color=("blue" if draw_fitline else "red"))
+        line.set_transform(ax.transAxes)
+        ax.add_line(line)
+    if draw_fitline:
+        line_coefs = numpy.polyfit(xs, ys, 1)
+        x_lo = min(xs)
+        x_hi = max(xs)
+        n_steps = 1000
+        dx = (x_hi - x_lo) / n_steps
+        lxs = sorted(xs + [x_lo + t * dx for t in range(n_steps + 1)])
+        lys = [line_coefs[0] * x + line_coefs[1] for x in lxs]
+        ax.plot(lxs, lys, "r-")
     fig.savefig(pathname, bbox_inches='tight', format=format)
 
 
@@ -113,6 +126,7 @@ def _main(cmdline):
         "goto-program locations",
         "seconds",
         True,
+        True,
         True
         )
     make_scatter_plot(
@@ -123,6 +137,7 @@ def _main(cmdline):
         "goto-program locations",
         "MB",
         True,
+        True,
         True
         )