~= improved CDF efficiency

xlap/analyse/cdf.py

@@ -25,7 +25,8 @@ def multi_cdf(dfs, config, export=False, file_name="CDF.pdf"):
         for df in dfs:
             cdf(df[duration], grid=True, ax=ax)
 
-        ax.legend(names)
+        if(idx == 0):
+            ax.legend(names)
         ax.set_xlabel("{} [us]".format(duration))
         ax.set_ylabel("CDF")
     plt.subplots_adjust(wspace=0.3,hspace=0.3)

xlap/analyse/util.py

@@ -2,18 +2,15 @@ import matplotlib.pyplot as plt
 import numpy as np
 import math
 
-
-def cdf(values, grid=False, ax=None):
-    # empirical CDF
-    def F(x,data):
-        return float(len(data[data <= x]))/len(data)
-
-    vF = np.vectorize(F, excluded=['data'])
-
+def cdf(values, ax=None, grid=False, **kwargs):
     if ax is None:
         ax = plt
 
-    ax.semilogx(np.sort(values),vF(x=np.sort(values), data=values))
+    if not "linestyle" in kwargs:
+        kwargs["linestyle"] = "-"
+
+    s = np.sort(values)
+    ax.semilogx(s, np.searchsorted(s, s, side='right') / len(s), **kwargs)
     if grid:
         ax.grid()