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import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import *
from sklearn.preprocessing import label_binarize
from coding.llh.static.config import Config
def draw_play_flow(df, p1_name, p2_name, p1_ace, p2_ace, p1_net_pt_won, p2_net_pt_won, p1_break_pt_won, p2_break_pt_won):
plt.figure(figsize=(10, 6))
plt.plot(
df.loc[:, "elapsed_time"].values,
df.loc[:, "p1_points_won"].values,
"-",
color=Config.COLORS_1[6],
alpha=0.5,
label=p1_name
)
plt.plot(
df.loc[:, "elapsed_time"].values,
df.loc[:, "p2_points_won"].values,
"-",
color=Config.COLORS_1[7],
alpha=0.5,
label=p2_name
)
plt.scatter(
p1_ace.loc[:, "elapsed_time"].values,
p1_ace.loc[:, "p1_points_won"].values,
s=40,
c=Config.COLORS_1[0],
marker="v",
label="p1_ace"
)
plt.scatter(
p2_ace.loc[:, "elapsed_time"].values,
p2_ace.loc[:, "p2_points_won"].values,
s=40,
c=Config.COLORS_1[1],
marker="v",
label="p2_ace"
)
plt.scatter(
p1_net_pt_won.loc[:, "elapsed_time"].values,
p1_net_pt_won.loc[:, "p1_points_won"].values,
s=40,
c=Config.COLORS_1[2],
marker="*",
label="p1_net_pt_won"
)
plt.scatter(
p2_net_pt_won.loc[:, "elapsed_time"].values,
p2_net_pt_won.loc[:, "p2_points_won"].values,
s=40,
c=Config.COLORS_1[3],
marker="*",
label="p2_net_pt_won"
)
plt.scatter(
p1_break_pt_won.loc[:, "elapsed_time"].values,
p1_break_pt_won.loc[:, "p1_points_won"].values,
s=40,
c=Config.COLORS_1[4],
marker="+",
label="p1_break_pt_won"
)
plt.scatter(
p2_break_pt_won.loc[:, "elapsed_time"].values,
p2_break_pt_won.loc[:, "p2_points_won"].values,
s=40,
c=Config.COLORS_1[5],
marker="+",
label="p1_break_pt_won"
)
title = "Flow of play"
# plt.title(title)
plt.xlabel("Elapsed time")
plt.ylabel("Points")
plt.legend()
plt.savefig("./diagram/{}.png".format(title), dpi=300)
plt.show() |