tested plot_loss.py

Author: tanaka-hiroki1989

script/plot_loss.py

@@ -1,51 +1,58 @@
 import matplotlib.pyplot as plt
-f = open("log_sample.tsv","r")
-datalist=f.readlines()
+import sys
 
-epoch = []
-train_cost = []
-train_cost_recons = []
-train_cost_temp = []
-train_cost_pred = []
-valid_cost = []
-valid_cost_recons = []
-valid_cost_temp = []
-valid_cost_pred = []
+def plot_loss(loss_txt,loss_image):
+    f = open(loss_txt,"r")
+    datalist=f.readlines()
 
-for data in datalist[1:]:
-    a = data.split('\t')
-    epoch.append(a[1])
-    train_cost.append(float(a[2]))
-    train_cost_recons.append(float(a[9]))
-    train_cost_temp.append(float(a[10])*0.5)
-    train_cost_pred.append(float(a[11])*0.1)
-    valid_cost.append(float(a[3]))
-    valid_cost_recons.append(float(a[12]))
-    valid_cost_temp.append(float(a[13])*0.5)
-    valid_cost_pred.append(float(a[14])*0.1)
+    epoch = []
+    train_cost = []
+    train_cost_recons = []
+    train_cost_temp = []
+    train_cost_pred = []
+    valid_cost = []
+    valid_cost_recons = []
+    valid_cost_temp = []
+    valid_cost_pred = []
 
-plt.style.use("grayscale")
-fig = plt.figure(figsize=(16.0,6.0))
-ax1 = fig.add_subplot(1, 2, 1)
-ax1.set_title("train cost")
-ax1.set_xlabel("epoch")
-ax1.set_xlim([0,1000])
-ax1.set_ylim([0.01,5.0])
-ax1.plot(train_cost,label="total")
-ax1.plot(train_cost_recons,label="recons")
-ax1.plot(train_cost_temp,label="alpha*temporal")
-ax1.plot(train_cost_pred,label="beta*prediction")
-ax1.legend()
+    for data in datalist[1:]:
+        a = data.split('\t')
+        epoch.append(a[1])
+        train_cost.append(float(a[2]))
+        train_cost_recons.append(float(a[9]))
+        train_cost_temp.append(float(a[10])*0.5)
+        train_cost_pred.append(float(a[11])*0.1)
+        valid_cost.append(float(a[3]))
+        valid_cost_recons.append(float(a[12]))
+        valid_cost_temp.append(float(a[13])*0.5)
+        valid_cost_pred.append(float(a[14])*0.1)
 
-ax2 = fig.add_subplot(1, 2, 2)
-ax2.set_title("valid cost")
-ax2.set_xlabel("epoch")
-ax2.set_xlim([0,1000])
-ax2.set_ylim([0.01,5.0])
-ax2.plot(train_cost,label="total")
-ax2.plot(train_cost_recons,label="recons")
-ax2.plot(train_cost_temp,label="alpha*temporal")
-ax2.plot(train_cost_pred,label="beta*prediction")
-ax2.legend()
+    plt.style.use("grayscale")
+    fig = plt.figure(figsize=(16.0,6.0))
+    ax1 = fig.add_subplot(1, 2, 1)
+    ax1.set_title("train cost")
+    ax1.set_xlabel("epoch")
+    ax1.set_xlim([0,1000])
+    ax1.set_ylim([0.01,5.0])
+    ax1.plot(train_cost,label="total")
+    ax1.plot(train_cost_recons,label="recons")
+    ax1.plot(train_cost_temp,label="alpha*temporal")
+    ax1.plot(train_cost_pred,label="beta*prediction")
+    ax1.legend()
 
-plt.savefig("plot_loss_sample.png")
+    ax2 = fig.add_subplot(1, 2, 2)
+    ax2.set_title("valid cost")
+    ax2.set_xlabel("epoch")
+    ax2.set_xlim([0,1000])
+    ax2.set_ylim([0.01,5.0])
+    ax2.plot(train_cost,label="total")
+    ax2.plot(train_cost_recons,label="recons")
+    ax2.plot(train_cost_temp,label="alpha*temporal")
+    ax2.plot(train_cost_pred,label="beta*prediction")
+    ax2.legend()
+
+    plt.savefig(loss_image)
+
+if __name__ == '__main__':
+    args = sys.argv
+    plot_loss(args[1],args[2])

script/sample_plot_loss/sample_plot_loss.png

@@ -0,0 +1 @@
+python plot_loss.py sample_plot_loss/log_sample.txt sample_plot_loss/sample_plot_loss.png