Question

我有一个接受或拒绝数据的页面。接受组件后，将数据重新加载到下一组并滚动到页面顶部。

我在滚动时遇到问题。加载数据时触发window.scroll（0,0）显然不起作用。我使用了ngAfterContentChecked（），但是即使单击按钮后页面仍在滚动（对话框中没有确认）。现在我有这样的事情。

顺便说一句。我无法更改路线参数，我已经尝试了document.body ...等等

import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import label_binarize
from sklearn.metrics import roc_curve, auc
from sklearn.multiclass import OneVsRestClassifier
from sklearn.tree import DecisionTreeClassifier

iris = datasets.load_iris()
X = iris.data
y = iris.target

# Binarize the output
y = label_binarize(y, classes=[0, 1, 2])
n_classes = y.shape[1]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.5, random_state=0)

classifier = OneVsRestClassifier(DecisionTreeClassifier(random_state=0))
y_score = classifier.fit(X_train, y_train).predict_proba(X_test)


fpr = dict()
tpr = dict()
roc_auc = dict()
for i in range(n_classes):
    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_score[:, i])
    roc_auc[i] = auc(fpr[i], tpr[i])
colors = cycle(['blue', 'red', 'green'])
for i, color in zip(range(n_classes), colors):
    plt.plot(fpr[i], tpr[i], color=color, lw=lw,
             label='ROC curve of class {0} (area = {1:0.2f})'
             ''.format(i, roc_auc[i]))

plt.plot([0, 1], [0, 1], 'k--', lw=lw)
plt.xlim([-0.05, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic for multi-class data')
plt.legend(loc="lower right")
plt.show()

角度-滚动到顶部按钮

0 个答案: