# 禁用 flake8 检查 # 导入 gym 库 import gym # 导入 Trainer 类 from numpy_ml.rl_models.trainer import Trainer # 导入不同的智能体类 from numpy_ml.rl_models.agents import ( CrossEntropyAgent, MonteCarloAgent, TemporalDifference
""" # 调用内部方法 _log_prob 来计算给定单词序列在 N-gram 语言模型下的总对数概率 return self._log_prob(words, N) # 计算 ngram 的平滑对数概率并返回 def _log_ngram_prob(self, ngram): """Return the smoothed log probability of the ngram""" N = len(ngram) sc, T = self._smooth...
You’d like to compare the two classes, student by student and test by test, to find the higher score in each case. NumPy has a function, np.maximum(), specifically designed for comparing two arrays in an element-by-element manner. Check it out in action:...
allclose(a, b[, rtol, atol, equal_nan])Returns True if two arrays are element-wise equal within a tolerance.isclose(a, b[, rtol, atol, equal_nan])Returns a boolean array where two arrays are element-wise equal within a tolerance.array_equal(a1, a2)True if two arrays have the same...
The only difference between these functions is that ``array_split`` allows `indices_or_sections` to be an integer that does *not* equally divide the axis. For an array of length l that should be split into n sections, it returns l % n sub-arrays of size l//n + 1 and the rest ...
In line 8, you call the new function and pass to it the arrays you want it to analyze. In this example, the output shows your profit, including the added bonus. If you compare the numbers to the straightforward profit calculation you did earlier, then you’ll notice that you’ve gotten...
1. Multidimensional Arrays NumPy introduces the ndarray data structure, which allows for efficient creation and manipulation of arrays of various dimensions. These arrays enable seamless representation of data such as images, time series, and matrices. 2. Efficient Mathematical Operations NumPy provides ...
Return the difference between the largest element of self along axis and the smallest element of self along axis . When the result is a single element, returns a numpy scalar instead of an ndarray. Note The rtype argument specifies the data-type the reduction should take place over. This ...
Write a NumPy program to find the set difference between two arrays. The set difference will return sorted, distinct values in array1 that are not in array2.Expected Output:Array1: [ 0 10 20 40 60 80] Array2: [10, 30, 40, 50, 70, 90] ...
With np.linspace() and np.arange() you can make arrays of evenly spaced values. The difference between these two functions is that the last value of the three that are passed in the code chunk above designates either the step value for np.linspace() or a number of samples for np.arange...