This module get a pretty print confusion matrix from a NumPy matrix or from 2 NumPy arrays (y_testandpredictions). Installation pip install pretty-confusion-matrix Get Started Plotting from DataFrame: importnumpyasnpimportpandasaspdfrompretty_confusion_matriximportpp_matrixarray=np.array([[13,0,1...
I know you wrote your example in raw Python lists, but if you decide to use numpy arrays instead (which would be perfectly legit in your example, because you seem to be dealing with arrays of numbers), there is (almost exactly) this command you said you made up: import numpy as np n...
First, declare an array of dictionaries. Afterward, pretty print it using the function pprint.pprint(). import pprint dct_arr = [ {"Name": "John", "Age": "23", "Country": "USA"}, {"Name": "Jose", "Age": "44", "Country": "Spain"}, {"Name": "Anne", "Age": "29", "...
Ifheaders="keys", then the keys of a dictionary/dataframe, or column indices are used. It also works for NumPy record arrays and lists of dictionaries or named tuples: >>>print(tabulate({"Name": ["Alice","Bob"], ..."Age": [24,19]}, headers="keys")) Name Age --- --- Alice...
Pretty Print XML in the Console The example below demonstrates how to create XML and pretty print it in the console: package delftstack; import java.io.File; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.transform.OutputKeys; import javax...
R = np.array([[5.0, 3.0, 0.0, 1.0], [4.0, 0.0 ,0.0 ,1.0], [1.0, 1.0, 0.0, 5.0], [1.0, 0.0, 0.0, 4.0], [0.0, 1.0, 5.0, 4.0]]) N,M = R.shape K = 2 R = torch.from_numpy(R).float() # 初始化矩阵P和Q P = Variable(torch.randn(N, K), requires_grad=True) Q...
TensorFlow的全部目的就是使用一个称之为计算图(computational graph)的东西,它会比直接在Python中进行相同计算量要高效得多。TensorFlow比Numpy更高效,因为TensorFlow了解整个需要运行的计算图,然而Numpy只知道某个时间点上唯一的数学运算。 TensorFlow也能够自动地计算需要优化的变量的梯度,使得模型有更好的表现。这是由于...
prettyprinter.install_extras(['numpy']) a = np.array([[1,2,3,0], [4,5,6,0], [7,8,9,0]]) prettyprinter.cpprint(a, width=30) 最终效果如下图所示,可以看到打印的结果有了颜色高亮: 对自定义类设计样式 我们可以对自定义类注册 pretty printer。我们定义一个类: class MyClass(object): ...
numpy basics such as array shape axis type broadcasting advanced indexing slicing sorting searching aggregating and statistics calculate basic statistics of multidimensional data arrays and the k means algorithms for unsupervised learning create more advanced regular...
Or, if you'd like to both set up Treescope as the default pretty printer and enable automatic array visualization, you can simply run: treescope.basic_interactive_setup(autovisualize_arrays=True) Once you've rendered an object, try clicking on it and pressing therkey! This turns on "roundtr...