我必须在我的antd输入字段中输入数字。但是它接受数字和字母。对于我的需求,逻辑工作正常,但字母除外。那么,我该怎么假设写一个只接受数字的正则表达式呢?
import React from 'react'
import * as AntD from "antd";
import { Input, Tooltip } from 'antd';
const { Row, Col } = AntD;
function creditCardFormatter(value) {
var v = value.replace(/\s+/g, '').replace(/[^0-9]/gi, '')
var matches = v.match(/\d{4,16}/g);
var match = matches && matches[0] || '';
var parts = [];
for (let i = 0, len = match.length; i < len; i += 4) {
parts.push(match.substring(i, i + 4));
console.log(parts)
console.log(match)}
if (parts.length){
console.log(parts.length)
return parts.join(' ');
} else {
return value;
}
}
// value += '';
// const list = value.split('.');
// const prefix = list[0].charAt(0) === '-' ? '-' : '';
// let num = prefix ? list[0].slice(2) : list[0];
// let result = '';
// while (num.length > 4) {
// result = ` ${num.slice(-4)}${result}`;
// num = num.slice(0, num.length - 4);
// }
// if (num) {
// result = num + result;
// }
// return `${prefix}${result}${list[1] ? `.${list[1]}` : ''}`;
// }
class NumericInput extends React.Component {
onChange = (e) => {
const { value } = e.target;
this.props.onChange(creditCardFormatter(value));
}
render() {
const { value } = this.props;
return (
<div align="center">
<Col push={5}>
<label>Enter Number Here :</label>
<br />
<Input
{...this.props}
onChange={this.onChange}
placeholder="Input a number"
/>
</Col>
</div>
);
}
}
class InputElement extends React.Component {
constructor(props) {
super(props);
this.state = { value: '' };
}
onChange = (value) => {
this.setState({ value });
}
render() {
return <NumericInput style={{ width: 120 }} value={this.state.value} onChange={this.onChange} />;
}
}
export default InputElement
答案 0 :(得分:3)
对于数字,您只能在antd中始终使用InputNumber。
如果您不想使用它,那么您仍然不必编写onchange函数,antd允许您在字段上添加validation rules。 例如:
def create_model(bert_config, is_training, input_ids, input_mask, segment_ids,
labels, num_labels, use_one_hot_embeddings):
"""Creates a classification model."""
model = modeling.BertModel(
config=bert_config,
is_training=is_training,
input_ids=input_ids,
input_mask=input_mask,
token_type_ids=segment_ids,
use_one_hot_embeddings=use_one_hot_embeddings)
# In the demo, we are doing a simple classification task on the entire
# segment.
#
# If you want to use the token-level output, use model.get_sequence_output()
# instead.
output_layer = model.get_pooled_output()
hidden_size = output_layer.shape[-1].value
with tf.variable_scope("cls/seq_relationship"):
output_weights = tf.get_variable(
"output_weights", [num_labels, hidden_size])
output_bias = tf.get_variable(
"output_bias", [num_labels])
with tf.variable_scope("loss"):
if is_training:
# I.e., 0.1 dropout
output_layer = tf.nn.dropout(output_layer, keep_prob=0.9)
logits = tf.matmul(output_layer, output_weights, transpose_b=True)
logits = tf.nn.bias_add(logits, output_bias)
probabilities = tf.nn.softmax(logits, axis=-1)
log_probs = tf.nn.log_softmax(logits, axis=-1)
one_hot_labels = tf.one_hot(labels, depth=num_labels, dtype=tf.float32)
per_example_loss = -tf.reduce_sum(one_hot_labels * log_probs, axis=-1)
loss = tf.reduce_mean(per_example_loss)
return (loss, per_example_loss, logits, probabilities)
现在仅数字正则表达式使用此
{getFieldDecorator("testNumber", {
rules: [
{
required: true,
type: "regexp",
pattern: new RegExp(/\d+/g),
message: "Wrong format!"
}
]
})(<Input />)}
答案 1 :(得分:1)
对于仅数字,您可以将类型设置为“数字”:https://github.com/yiminghe/async-validator#type
对于您的用例,我认为regexp更复杂。
答案 2 :(得分:0)
尝试使用onChange函数:
onChange = (e) => {
const { value } = e.target;
const reg = /^-?(0|[1-9][0-9]*)(\.[0-9]*)?$/;
if ((!Number.isNaN(value) && reg.test(value)) || value === '' || value === '-') {
this.props.onChange(value);
}
}