scripts/plot_multidir_cost.py

   1 #!/usr/bin/env python3
   2 """Plot scenario's runs cost."""
   3 from json import loads
   4 from os import listdir
   5 from sys import argv, exit
   6 import matplotlib.pyplot as plt
   7 import numpy as np
   8
   9 FN = "test54"
  10 RUNS = 10000
  11 ITERS = 1000
  12
  13 def load(fn=None):
  14     """Load scenario from file.
  15
  16     Keyword arguments
  17     -----------------
  18
  19     - `fn` -- File name.
  20     """
  21     if fn is None:
  22         raise ValueError("File name as argument needed")
  23     s = None
  24     with open(fn, "r") as f:
  25         s = loads(f.read())
  26     return s
  27
  28 def load_dir(dn=None, fn=None):
  29     """Load scenarios from directory.
  30
  31     Keyword arguments
  32     -----------------
  33
  34     - `dn` -- Directory name.
  35     """
  36     if dn is None:
  37         raise ValueError("Directory name as argument needed")
  38     scenarios = []
  39     for d in listdir(dn):
  40         if int(d) >= RUNS:
  41             continue
  42         s = load("{}/{}/{}.json".format(dn, d, fn))
  43         s["dn"] = dn
  44         s["subdn"] = d
  45         s["fn"] = fn
  46         scenarios.append(s)
  47     return scenarios
  48
  49 def perc(li=[], p=0):
  50     return np.percentile(li, p) if len(li) > 0 else p
  51
  52 if __name__ == "__main__":
  53     WHAT_PLOT = 1
  54     colors = [
  55         "tab:red",
  56         "tab:orange",
  57         "tab:blue",
  58         "tab:green",
  59         "tab:red"]
  60     names = [
  61         "OSP-WK",
  62         "OSP-WK + cost heur.",
  63         "OSP-WK + goal zone",
  64         "OSP-WK + path opt.",
  65         "OSP-All"]
  66     #names = [
  67     #    "RRT",
  68     #    "No cost heuristics",
  69     #    "No goal zone",
  70     #    "No path optimization",
  71     #    "Out-of-slot planner"]
  72     titles = [
  73         "Failure rate",
  74         "Average final path cost",
  75         "Maximum final path cost"]
  76
  77     plt.rcParams["figure.figsize"] = [14, 7]
  78     plt.rcParams["font.size"] = 24
  79     plt.rcParams["font.family"] = "cmr10"
  80     plt.rcParams["hatch.linewidth"] = 1.0
  81     plt.rcParams["lines.linewidth"] = 1.0
  82     plt.rc('axes', unicode_minus=False)
  83
  84     f, ax = plt.subplots()
  85     ax.grid(which="major", linestyle=":", color="tab:gray")
  86     #eax = ax.twinx()
  87
  88     #ax.set_title("Scenario 3: {}".format(titles[WHAT_PLOT - 1]))
  89     #ax.set_title("Scenario 3: {}".format(titles[WHAT_PLOT - 1]))
  90
  91     #ax.set_title("Scenario 8: Final path cost after optimization")
  92     #ax.set_title("Scenario 2: Final path cost after optimization")
  93     #ax.set_title("Scenario 7: Final path cost after optimization")
  94     ax.set_xlabel("Number of iterations [-]")
  95     if WHAT_PLOT == 1:
  96         ax.set_ylabel("Failure rate [%]")
  97     else:
  98         ax.set_ylabel("Cost [m]")
  99     #ax.set_ylim([20.1, 57]) # scenario 7
 100     #ax.set_ylim([18, 43]) # scenario 2
 101     if WHAT_PLOT > 1:
 102         ax.set_ylim([10, 40])
 103     #ax.set_ylim([0, 100])
 104
 105     ci = -1
 106     p1 = 0
 107     p2 = 0
 108     c1 = 0
 109     c2 = 0
 110     result_dir = "rwps-additional/rwps-1"
 111     for test_fn in [
 112         "test54-no-improvement",
 113         "test54-w-cost-heuristics",
 114         "test54-w-goal-zone",
 115         "test54-w-opt",
 116         "test55"]:
 117         ci += 1
 118         scenarios = load_dir(result_dir, test_fn)
 119         L = ITERS
 120         err_hist = [0 for i in range(L)]
 121         val_list = [[] for i in range(L)]
 122         icnt_list = []
 123         bcnt_list = []
 124         rcnt_list = []
 125         time_list = []
 126         otime_list = []
 127         min_s = 0
 128         min_c = 0.0
 129         max_s = 0
 130         max_c = 0.0
 131         for s in scenarios:
 132             lpc = s["log_path_cost"]
 133             for i in range(L):
 134                 if len(lpc) <= i:
 135                     lpc.append(lpc[-1])
 136                 if lpc[i] == 0:
 137                     err_hist[i] += 1
 138                 else:
 139                     val_list[i].append(lpc[i])
 140             if min_c == 0.0 or s["goal_cc"] < min_c:
 141                 min_c = s["goal_cc"]
 142                 min_s = s["subdn"]
 143             if s["goal_cc"] > max_c:
 144                 max_c = s["goal_cc"]
 145                 max_s = s["subdn"]
 146             try:
 147                 icnt_list.append(s["icnt"])
 148                 bcnt_list.append(s["bcnt"])
 149                 rcnt_list.append(s["rcnt"])
 150             except:
 151                 pass
 152             try:
 153                 time_list.append(s["time"])
 154             except:
 155                 pass
 156             try:
 157                 otime_list.append(s["otime"])
 158             except:
 159                 pass
 160         o_err_hist = list(err_hist)
 161         err_hist = [i * 100.0 / RUNS for i in o_err_hist]
 162         #print("{} {}".format(min_s, max_s))
 163         icnt_avg = np.average(icnt_list)
 164         bcnt_avg = np.average(bcnt_list)
 165         rcnt_avg = np.average(rcnt_list)
 166         br_avg = np.average([b / r for (b, r) in zip(bcnt_list, rcnt_list)])
 167         #print("avg. icnt = {}".format(icnt_avg))
 168         #print("avg. bcnt = {}".format(bcnt_avg))
 169         #print("avg. rcnt = {}".format(rcnt_avg))
 170         #print("b/r avg. {}".format(br_avg))
 171         print("last avg. cost = {}".format(np.average(val_list[-1])))
 172         #print("last max. cost = {}".format(perc(val_list[-1], 100)))
 173         print("failure rate = {}".format(err_hist[-1]))
 174         for i in range(len(err_hist)):
 175             if err_hist[i] == 0:
 176                 print(i)
 177                 break
 178
 179         #eax.fill_between(
 180         #    x=range(L),
 181         #    y1=0,
 182         #    y2=[i for i in err_hist],
 183         #    color=colors[ci],
 184         #    alpha=0.2,
 185         #    label="Succes rate {}".format(ci),
 186         #)
 187         if WHAT_PLOT == 1:
 188             ax.plot(
 189                 range(L),
 190                 [i for i in err_hist],
 191                 color=colors[ci],
 192                 #alpha=0.45,
 193                 label=names[ci],
 194                 linestyle=(0, (5, 5)) if ci == 0 else "solid",
 195             )
 196         if WHAT_PLOT == 2:
 197             ax.plot(
 198                 range(L),
 199                 [np.average(val_list[i]) for i in range(L)],
 200                 color=colors[ci],
 201                 #alpha=0.45,
 202                 label=names[ci],
 203                 linestyle=(0, (5, 5)) if ci == 0 else "solid",
 204             )
 205         if WHAT_PLOT == 3:
 206             ax.plot(
 207                 range(L),
 208                 [perc(val_list[i], 100) for i in range(L)],
 209                 color=colors[ci],
 210                 #alpha=0.45,
 211                 label=names[ci],
 212                 linestyle=(0, (5, 5)) if ci == 0 else "solid",
 213             )
 214
 215     ax.minorticks_on()
 216     ax.tick_params(axis='x', labelrotation=45)
 217     h1, la1 = ax.get_legend_handles_labels()
 218     #h2, la2 = eax.get_legend_handles_labels()
 219
 220     h = h1# + h2
 221     la = la1# + la2
 222
 223     ax.legend(h, la, loc="upper right", ncol=1)
 224     if WHAT_PLOT == 2:
 225         ax.legend(h, la, loc="upper right", ncol=2)
 226     plt.savefig("out.pdf", bbox_inches="tight")
 227     plt.close()