翻译这段代码class GPR: def __init__(self, optimize=True): self.is_fit = False self.train_X, self.train_y = None, None self.params = {"l": 2, "sigma_f": 1} self.optimize = optimize def fit(self, X, y): # store train data self.train_X = np.asarray(X) self.train_y = np.asarray(y) # hyper parameters optimization def negative_log_likelihood_loss(params): self.params["l"], self.params["sigma_f"] = params[0], params[1] Kyy = self.kernel(self.train_X, self.train_X) + 1e-8 * np.eye(len(self.train_X)) loss = 0.5 * self.train_y.T.dot(np.linalg.inv(Kyy)).dot(self.train_y) + 0.5 * np.linalg.slogdet(Kyy)[ 1] + 0.5 * len(self.train_X) * np.log(2 * np.pi) return loss.ravel() if self.optimize: res = minimize(negative_log_likelihood_loss, [self.params["l"], self.params["sigma_f"]],bounds=((1e-4, 1e4), (1e-4, 1e4)),method='L-BFGS-B') self.params["l"], self.params["sigma_f"] = res.x[0], res.x[1] self.is_fit = True def predict(self, X): if not self.is_fit: print("GPR Model not fit yet.") return X = np.asarray(X) Kff = self.kernel(self.train_X, self.train_X) # (N, N) Kyy = self.kernel(X, X) # (k, k) Kfy = self.kernel(self.train_X, X) # (N, k) Kff_inv = np.linalg.inv(Kff + 0.5e-3 * np.eye(len(self.train_X))) # (N, N) mu = Kfy.T.dot(Kff_inv).dot(self.train_y) cov = Kyy - Kfy.T.dot(Kff_inv).dot(Kfy) return mu, cov def kernel(self, x1, x2): dist_matrix = np.sum(x1 ** 2, 1).reshape(-1, 1) + np.sum(x2 ** 2, 1) - 2 * np.dot(x1, x2.T) return self.params["sigma_f"] ** 2 * np.exp(-0.5 / self.params["l"] ** 2 * dist_matrix)
时间: 2023-05-22 07:04:20 浏览: 61
以上代码是一个名为GPR的类的定义,其中包含一个初始化函数__init__,和一个适应函数fit。
在初始化函数中,self.is_fit被赋值为False,self.train_X和self.train_y被赋值为None,self.params被赋值为{"l": 2, "sigma_f": 1},self.optimize被赋值为传入的参数optimize。
在适应函数中,传入参数为X和y,用于对模型进行适应操作。
相关问题
KeyError Traceback (most recent call last) Cell In[54], line 1 ----> 1 groupk1 = df.groupby('key2').mean() 2 print(groupk1) File ~\AppData\Roaming\Python\Python310\site-packages\pandas\core\frame.py:8252, in DataFrame.groupby(self, by, axis, level, as_index, sort, group_keys, observed, dropna) 8249 raise TypeError("You have to supply one of 'by' and 'level'") 8250 axis = self._get_axis_number(axis) -> 8252 return DataFrameGroupBy( 8253 obj=self, 8254 keys=by, 8255 axis=axis, 8256 level=level, 8257 as_index=as_index, 8258 sort=sort, 8259 group_keys=group_keys, 8260 observed=observed, 8261 dropna=dropna, 8262 ) File ~\AppData\Roaming\Python\Python310\site-packages\pandas\core\groupby\groupby.py:931, in GroupBy.__init__(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, observed, dropna) 928 self.dropna = dropna 930 if grouper is None: --> 931 grouper, exclusions, obj = get_grouper( 932 obj, 933 keys, 934 axis=axis, 935 level=level, 936 sort=sort, 937 observed=observed, 938 dropna=self.dropna, 939 ) 941 self.obj = obj 942 self.axis = obj._get_axis_number(axis) File ~\AppData\Roaming\Python\Python310\site-packages\pandas\core\groupby\grouper.py:985, in get_grouper(obj, key, axis, level, sort, observed, validate, dropna) 983 in_axis, level, gpr = False, gpr, None 984 else: --> 985 raise KeyError(gpr) 986 elif isinstance(gpr, Grouper) and gpr.key is not None: 987 # Add key to exclusions 988 exclusions.add(gpr.key) KeyError: 'key2'怎么解决
这是一个KeyError错误,意味着你试图访问一个不存在的键。在这种情况下,它是 'key2'。为了解决这个问题,你需要检查你的 DataFrame 中是否有一个名为 'key2' 的列。如果没有,请确保你正确地指定了该列的名称。如果你确定 DataFrame 中有 'key2' 这列,那么可能是大小写或者拼写错误导致的问题,你需要检查一下拼写是否正确,或者尝试使用 DataFrame.columns 检查列名。
d:\download\anaconda3\envs\tensorflow\lib\site-packages\pandas\core\frame.py in groupby(self, by, axis, level, as_index, sort, group_keys, squeeze, observed, dropna) 6523 squeeze=squeeze, 6524 observed=observed, -> 6525 dropna=dropna, 6526 ) 6527 d:\download\anaconda3\envs\tensorflow\lib\site-packages\pandas\core\groupby\groupby.py in __init__(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, squeeze, observed, mutated, dropna) 531 observed=observed, 532 mutated=self.mutated, --> 533 dropna=self.dropna, 534 ) 535 d:\download\anaconda3\envs\tensorflow\lib\site-packages\pandas\core\groupby\grouper.py in get_grouper(obj, key, axis, level, sort, observed, mutated, validate, dropna) 784 in_axis, name, level, gpr = False, None, gpr, None 785 else: --> 786 raise KeyError(gpr) 787 elif isinstance(gpr, Grouper) and gpr.key is not None: 788 # Add key to exclusions
这段错误信息主要是显示在调用groupby方法时出现了KeyError,即指定的分组列名不在数据集中。
可能原因是你指定的分组列名‘日期’不存在于数据集的列名之中,或者是数据集的列名中包含空格或其他特殊字符,导致无法正确识别。
建议检查一下数据集中的列名,确认是否正确指定了分组列名,并且尽量避免在列名中使用特殊字符和空格。