update

2025.03.08_matrix_running_time/matrix_running_time.py

@@ -71,7 +71,7 @@ for n in n_array:
     start_time = time.time()
     det_A = np.linalg.det(A)
     det_time = time.time() - start_time
-    print(f"矩阵行列式时间: {det_time:.2f} 秒")
+    print(f"矩阵行列式时间: {det_time:.3f} 秒")
 
     # 矩阵乘法
     start_time = time.time()

2025.03.08_matrix_running_time_for_different_num_of_cpu_cores/make_qsub_files.py

@@ -0,0 +1,11 @@
+import guan  # https://py.guanjihuan.com | install: pip install --upgrade guan
+import numpy as np
+
+cpu_num_array = np.arange(1, 11)
+
+sh_filename = 'task'
+task_name = 'test'
+py_filename='matrix_running_time_for_different_num_of_cpu_cores'
+
+for cpu_num in cpu_num_array:
+    guan.make_sh_file_for_qsub(sh_filename=sh_filename+'_'+str(cpu_num), command_line=f'python {py_filename}.py', cpu_num=cpu_num, task_name=task_name+'_'+str(cpu_num), cd_dir=0)

2025.03.08_matrix_running_time_for_different_num_of_cpu_cores/matrix_running_time_for_different_num_of_cpu_cores.py

@@ -0,0 +1,47 @@
+"""
+This code is supported by the website: https://www.guanjihuan.com
+The newest version of this code is on the web page: https://www.guanjihuan.com/archives/45324
+"""
+
+import numpy as np
+import time
+
+n = 7000
+A = np.random.rand(n, n)
+B = np.random.rand(n, n)
+
+# 矩阵行列式
+start_time = time.time()
+det_A = np.linalg.det(A)
+det_time = time.time() - start_time
+print(f"矩阵行列式时间: {det_time:.2f} 秒")
+
+# 矩阵乘法
+start_time = time.time()
+C = np.dot(A, B)
+multiply_time = time.time() - start_time
+print(f"矩阵乘法时间: {multiply_time:.3f} 秒")
+
+# 矩阵求逆
+start_time = time.time()
+inv_A = np.linalg.inv(A)
+inv_time = time.time() - start_time
+print(f"矩阵求逆时间: {inv_time:.3f} 秒")
+
+# 矩阵的秩
+start_time = time.time()
+rank_A = np.linalg.matrix_rank(A)
+rank_time = time.time() - start_time
+print(f"矩阵的秩时间: {rank_time:.3f} 秒")
+
+# 矩阵的特征值
+start_time = time.time()
+eigenvalues_A = np.linalg.eigvals(A)
+eigen_time = time.time() - start_time
+print(f"矩阵特征值时间: {eigen_time:.3f} 秒")
+
+# 矩阵的特征值和特征向量
+start_time = time.time()
+eigenvalues_A, eigenvector_A = np.linalg.eig(A)
+eigen_time = time.time() - start_time
+print(f"矩阵特征值和特征向量时间: {eigen_time:.3f} 秒")

2025.03.08_matrix_running_time_for_different_num_of_cpu_cores/qsub_task.py

@@ -0,0 +1,7 @@
+import numpy as np
+import os
+
+cpu_num_array = np.arange(1, 11)
+
+for cpu_num in cpu_num_array:
+    os.system(f'qsub task_{cpu_num}.sh')