Python code to demonstrate the purpose of numpy.where() returning a tuple# Import numpy import numpy as np # Creating a numpy array arr = np.array([ [1, 2, 3, 4, 5, 6], [-2, 1, 2, 3, 4, 5]]) # Display original array print("Original array:\n",arr,"\n") # using ...
Kerasis an Open Source Neural Network library written in Python that runs on top of Theano or Tensorflow. It is designed to be modular, fast and easy to use. It was developed by François Chollet, a Google engineer. Keras doesn’t handle low-level computation. Instead, it uses another l...
and the plot of number of the popular names in top 50% :param top1000: :return:'''table= top1000.pivot_table(values='prop', index=['year'], columns='sex', aggfunc=sum) table.plot(title="sum of top1000.prop by year and sex", yticks=np.linspace(0, 1.2, 13), xticks=range(188...
(x_outliers) #separate the two features and use it to plot the data F1 = X_train[:,[0]].reshape(-1,1) F2 = X_train[:,[1]].reshape(-1,1) # create a meshgrid xx , yy = np.meshgrid(np.linspace(-10, 10, 200), np.linspace(-10, 10, 200)) # scatter plot plt.scatter(...
Python program to demonstrate the example of difference between np.mean() and tf.reduce_mean()# Import numpy import numpy as np # Import tensorflow import tensorflow as tf # Creating an array arr = np.array([[1,2],[3,4], [5,6], [6,7]]) # Display original array print("Original...
()主要是因为在多维的情况下,len()只能得出单维度参数print(p3)#linspace的使用print(np.linspace(5, 15, 8))#从5开始到15,中间要有8个元素,需要注意的是15是包括在内的print(np.linspace(5, 15, 3, retstep=True))#retstep 是打印出步长,'''结果如下: [5. 6.42857143 7.85714286 9.28571429 10.71428571...
a = torch.linspace(-math.pi, math.pi, 1500, device=device, datatype=datatype) b = torch.sin(a) m = torch.randn((), device=device, datatype=datatype, requires_grad=True) n = torch.randn((), device=device, datatype=datatype, requires_grad=True) ...
—___ is Eric.17年12月10日，甲公司因合同违约而涉及一桩诉讼案件。根据甲公司的法律顾问判断，最终的判决很可能对甲公司不利。2×17年12月31日，甲公司尚未接到法院的判决，因诉讼须承担的赔偿的金额也无法准确地确定。不过，据专业人士估计，赔偿金额可能在90万元至100万元之间（含甲公司将承担的诉讼费2万元...
In a boxplot graph, the box represents the data’s interquartile range (IQR), which is the 50 percent of data points above the first quartile and below the third quartile. Each whisker (line) on the side of a boxplot represents the top and bottom 25 percent of data points, where the...
dist = np.linspace(-0.5,0.5,1024) x,y = np.meshgrid(dist, dist) grid = (x**2+y**2) testpattern = sine(grid, frequency=frequency) methods = [None, 'none', 'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', ...