Add face recognition plot and plot generating code

1 files changed, 60 insertions, 0 deletions

diff --git a/data/combined/graphs/plots.py b/data/combined/graphs/plots.py
new file mode 100755
index 0000000..4b32f92
--- /dev/null
+++ b/data/combined/graphs/plots.py
@@ -0,0 +1,60 @@
+#! /usr/bin/python
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+l = ["3","5","10","all"]
+
+#10-fold, naive
+plt.cla()
+for i in l:
+    x,y = np.loadtxt(i+"_nb_off.mat",unpack=True)
+    plt.plot(100*x,100*y,label="$n=$ "+i,linewidth=0.8)
+    plt.xlabel("Recall [%]")
+    plt.ylabel("Precision [%]")
+    plt.legend(loc="best")
+    plt.savefig("10fold-naive.pdf")
+
+#online,SHT
+plt.cla()
+for i in l:
+    x,y = np.loadtxt(i+"_sht_on.mat",unpack=True)
+    plt.plot(100*x,100*y,label="$n=$ "+i,linewidth=0.8,markersize=4)
+    plt.xlabel("Recall [%]")
+    plt.ylabel("Precision [%]")
+    plt.legend(loc="best")
+    plt.savefig("online-sht.pdf")
+
+
+#face
+plt.cla()
+x,y = np.loadtxt("all_nb_off.mat",unpack=True)
+a,b = np.loadtxt("face.csv",delimiter=",", unpack=True)
+plt.plot(100*x,100*y,linewidth=0.8,label="Skeleton")
+plt.plot(100*a,100*b,linewidth=0.8,label="Face")
+plt.xlabel("Recall [%]")
+plt.ylabel("Precision [%]")
+plt.legend(loc="best")
+plt.savefig("face.pdf")
+
+#back
+plt.cla()
+x,y = np.loadtxt("back_all_sht_on.mat",unpack=True)
+a,b = np.loadtxt("all_sht_on.mat",unpack=True)
+plt.plot(100*x,100*y,linewidth=0.8,label="Away")
+plt.plot(100*a,100*b,linewidth=0.8,label="Toward")
+plt.xlabel("Recall [%]")
+plt.ylabel("Precision [%]")
+plt.legend(loc="best")
+plt.savefig("back.pdf")
+
+#variance-reduction
+plt.cla()
+x,y = np.loadtxt("half-var-all_sht_on.mat",unpack=True)
+a,b = np.loadtxt("all_sht_on.mat",unpack=True)
+plt.plot(100*x,100*y,linewidth=0.8,label="Reduced noise")
+plt.plot(100*a,100*b,linewidth=0.8,label="Original noise")
+plt.xlabel("Recall [%]")
+plt.ylabel("Precision [%]")
+plt.legend(loc="best")
+plt.savefig("var.pdf")