script: added more functions to plot data script

gr_grc/scripts/plot_data.py

+#!/usr/bin/env python2.7
+# -*- encoding: utf-8 -*-
+from __future__ import unicode_literals
+
 import numpy as np
 import matplotlib.pyplot as plt
 import yaml
 import sys
+import matplotlib.patches as mpatches
+import matplotlib.lines as mlines
+from matplotlib.legend_handler import HandlerLine2D
 
 # http://mple.m-artwork.eu/home/posts?offset=10
 
@@ -9,31 +16,87 @@ if len(sys.argv) != 2:
     print("Usage: " + sys.argv[0] + " /path/to/data.yml")
     sys.exit(1)
 
-
 data = None
+fig,ax = plt.subplots()
+# x range 0-100
+x_range = np.arange(0,100,1)
+# first one and last one
+real_transmission_time = []
+# count only ones
+transmission_time = []
+
 with open(sys.argv[1], 'r') as stream:
     data = yaml.load(stream)
 
-fig,ax = plt.subplots()
-
-x = np.arange(0,101,1)
-values = []
 for i, var in enumerate(data['signal_blocks']):
-    values.append(var['real_transmission_time'])
-    ax.plot(i+1,var['real_transmission_time'], linestyle="None", marker=".", color="red")
+    # add values to array for later processing
+    real_transmission_time.append(var['real_transmission_time'])
+    transmission_time.append(var['transmission_time'])
 
-y_mean = [np.mean(values) for i in x]
-y_med = [np.median(values) for i in x]
-print(y_mean)
-print(y_med)
+real_y_mean = [np.mean(real_transmission_time) for i in x_range]
+real_y_med = [np.median(real_transmission_time) for i in x_range]
 
-mean_line = ax.plot(x,y_mean, label='Mittwelwert\t' + str(round(y_mean[0],2)) + 'ms', linestyle='--')
-mean_line = ax.plot(x,y_med, label='Median\t' + str(round(y_med[0],2)) + 'ms', linestyle='-')
+y_mean = [np.mean(transmission_time) for i in x_range]
+y_med = [np.median(transmission_time) for i in x_range]
 
-legend = ax.legend(loc='upper right')
+real_median_set = False
+median_set = False
+for i, var in enumerate(data['signal_blocks']):
+    # plot data points
+    if var['real_transmission_time'] == np.median(real_transmission_time) and \
+            real_median_set is False:
+        real_median_plot = ax.plot(i+1, var['real_transmission_time'],
+                                   linestyle="None", marker=".", color="red",
+                                   label="Transmission [median]")
+        real_median_set = True
+    else:
+        ax.plot(i+1, var['real_transmission_time'],
+                linestyle="None", marker="x", color="red")
+
+    if var['transmission_time'] == np.median(transmission_time) and \
+            median_set is False:
+        median_plot = ax.plot(i+1, var['transmission_time'], linestyle="None",
+                              marker=".", color="blue",
+                              label="Tastgrad [median]")
+        median_set = True
+    else:
+        ax.plot(i+1, var['transmission_time'], linestyle="None",
+                marker="x", color="blue")
+
+ax.plot(x_range,y_mean, linestyle='--', color="blue")
+ax.plot(x_range,real_y_mean, linestyle='--', color="red")
 
 plt.xlabel("Versuch")
 plt.ylabel("Frequenzbelegungszeit [ms]")
-plt.title(data['tag'])
+#plt.title(data['tag'])
+
+# add tick lines for x and y
+ax.yaxis.grid(True, which='major')
+ax.yaxis.grid(True, which='minor')
+ax.xaxis.grid(True, which='major')
+ax.xaxis.grid(True, which='minor')
+# Create custom artists
+tastgrad_legend     = plt.Line2D((0,1), (0,0),
+                                  color='blue', linestyle="", marker="x")
+uebertragung_legend = plt.Line2D((0,1), (0,0),
+                                 color='red', linestyle="", marker="x")
+median_legend       = plt.Line2D((0,1), (0,0),
+                                 color='black', marker='o', linestyle='')
+avg_legend          = plt.Line2D((0,1), (0,0),
+                                 color='black', linestyle="--")
+
+# Create legend from custom artist/label lists
+ax.legend([uebertragung_legend,tastgrad_legend,median_legend, avg_legend],
+          ['Übertragung','Tastgrad','Median', 'Durchschnitt'],
+          numpoints=1, loc="best")
+
+ticks = [ round(x, 1) for x in list(plt.yticks()[0]) ]
+if 0 in ticks:
+    ticks.remove(0)
+
+ax.set_yticks(ticks + [y_mean[0], real_y_mean[0]], minor=False)
+for spine in ['top', 'right']:
+    ax.spines[spine].set_visible(False)
 
+plt.savefig('figure.pgf')
 plt.show()