forjinrange(len(list_1)): list_1[j] = math.sin(list_1[j]) print("使用纯Python用时{}s".format(time.time()-start)) start = time.time() foriinrange(10): list_1 = np.array(np.arange(1,10000)) list_1 = np.sin(list_1) pr...
temple = rgb2gray(img_as_float(imread('../images/temple.jpg'))) image_original = np.zeros(list(temple.shape) + [3]) image_original[..., 0] = temple gradient_row, gradient_col = (np.mgrid[0:image_original.shape[0], 0:image_original.shape[1]] / float(image_original.shape[0]))...
# Initialize an accumulator for the sum of depth maps sum_depth_map = np.zeros_like(depth_maps[0], dtype=np.float64) # Compute the sum of all depth maps for depth_map in depth_maps: sum_depth_map += depth_map.astype(np.float64) # Calculate the mean depth map by dividing the su...
# Python program to compute factorial # of big numbers import sys # This function finds factorial of large # numbers and prints them def factorial( n) : res = [None]*500 # Initialize result res[0] = 1 res_size = 1 # Apply simple factorial formula # n! = 1 * 2 * 3 * 4...*...
NumPy Zeros NumPy zeros is a built-in function that creates a new array filled withzero values. The numpy.zeros() function is one of the most fundamental array creation routines in NumPy, allowing us to quickly initialize arrays of any shape and size. ...
= np.concatenate((np.zeros(900), np.ones(100)))# 计算每个类的频率class_counts = [len(labels[labels == 0]), len(labels[labels == 1])]# 使用条形图绘制类频率plt.figure(figsize=(8, 6)) plt.bar(['多数类(类 0)', '少数类(类 1)'], class_counts, color=['blue', 'red']) ...
zeros(len(x)) d[1:-1] = 6*(self.dy[1:]/self.h[1:] - self.dy[:-1]/self.h[:-1]) return H,d ncs = NaK_cubic_spline(x,y) ncs.fit() xn = np.linspace(1,10.5,100) yn = ccs.eval(xn) plt.scatter(x,y) plt.plot(xn,yn) [<matplotlib.lines.Line2D at 0x20a8ebff400...
def _train(self): self.__network() # TensorFlow graph execution with tf.Session() as sess: self.saver = tf.train.Saver() #saver = tf.train.Saver(write_version=tf.train.SaverDef.V2) # Initialize the variables of the Model init = tf.global_variables_initializer() sess.run(init) total...
首先,我们需要直接从这里下载《战争与和平》的.txt文件。 或者,我们可以从Gutenberg 项目下载该文件,但是我们将需要进行一些清理,例如,从文件以及目录中删除开头部分Project Gutenberg EBook,以及结尾的End of the Project。 然后,我们读取文件,将文本转换为小写,并通过打印出前 100 个字符来快速查看它: ...
numpy.arange 是 NumPy 中一个常用的函数,用于生成一个包含等差数列的数组。本文主要介绍一下NumPy中arange方法的使用。 numpy.arange numpy.arange([start, ]stop, [step, ]dtype=None) 返回给定间隔内的均匀间隔的值。 在半开间隔[start,stop)(换句话说,该间隔包括start但不包括stop)内生成值。 对于整数参数...