From a6b88f3f9b3c4199d74314bbd5047af0178957c9 Mon Sep 17 00:00:00 2001
From: Ting-Jun Wang <levi900227@gmail.com>
Date: Wed, 15 Nov 2023 15:51:07 +0800
Subject: [PATCH] style: main function

---
 hw4/hw4_10.py | 48 +++++++++++++++++++++++++-----------------------
 1 file changed, 25 insertions(+), 23 deletions(-)

diff --git a/hw4/hw4_10.py b/hw4/hw4_10.py
index 38c0fa3..1241d1d 100644
--- a/hw4/hw4_10.py
+++ b/hw4/hw4_10.py
@@ -14,7 +14,7 @@ def read_data(filename):
             y.append(int(numbers[-1]))
     return x, y
 
-def format(features):
+def form(features):
     '''
         change to LIBSVM format
     '''
@@ -33,31 +33,33 @@ def error(gt, pred):
         err = (err+1) if gt[index]!=pred[index] else err
     return err/len(gt)
 
-x, y = read_data(FILENAME)
-x = format(x)
-prob = problem(y, x)
-lambda_powers = [-6, -4, -2, 0, 2]
+if __name__ == '__main__':
+    x, y = read_data(FILENAME)
+    x = form(x)
+    prob = problem(y, x)
+    lambda_powers = [-6, -4, -2, 0, 2]
 
-results = []
-for lambda_power in lambda_powers:
-    lambda_value = 10 ** lambda_power
-    param_C = 1/(2*lambda_value) 
-    param = parameter('-s 0 -c {} -e 0.000001 -q'.format(param_C))
-    model = train(prob, param)
-    p_label, p_acc, p_val = predict(y, x, model)
-    err = error(y, p_label)
-    print("0/1 error: ", err)
-    print()
-    results.append({'lambda': lambda_power, 'error': err})
+    results = []
+    for lambda_power in lambda_powers:
+        lambda_value = 10 ** lambda_power
+        param_C = 1/(2*lambda_value) 
+        param = parameter('-s 0 -c {} -e 0.000001 -q'.format(param_C))
+        model = train(prob, param)
+        p_label, p_acc, p_val = predict(y, x, model)
+        err = error(y, p_label)
+        print("0/1 error: ", err)
+        print()
+        results.append({'lambda': lambda_power, 'error': err})
 
-ans, min_err = None, 1
-for i in results:
-    if i['error'] <= min_err:
-        min_err = i['error']
-        ans = i
+    ans, min_err = None, 1
+    for i in results:
+        print(i['error'])
+        if i['error'] <= min_err:
+            min_err = i['error']
+            ans = i
 
-print("the largest lambda: {}, log_10(lambda*): {}".format(10**ans['lambda'], ans['lambda']))
+    print("the largest lambda: {}, log_10(lambda*): {}".format(10**ans['lambda'], ans['lambda']))
 
-    
+