Cocos Creator和TypeScript使用枚举作为属性

时间:2018-08-17 18:09:49

标签: typescript cocoscreator

这个问题完全是关于TypeScript的。如果我在Cocos Creator中有基于JavaScript的Cocos项目,那么我遇到的问题就可以很好地解决。

文件中有以下枚举,称为枚举。

export const enum CollisionType {
Static=    0,
Dynamic=   1,
Solid=     2,
SemiSolid= 3
}

在我的game.ts文件中,我具有以下内容

import {CollisionType} from "./Enums";

export default class PlayerControl extends cc.Component {

@property (CollisionType)
collisionType:CollisionType = CollisionType.Static;

,但是不幸的是,这不起作用。我在CollisionType下收到一条红线,并出现以下错误:

Argument of type 'typeof CollisionType' is not assignable to parameter of type 'string | number | boolean | Function | any[] | { type?: any; visible?: boolean | (() => boolean); displayName?: string; tooltip?: string; multiline?: boolean; readonly?: boolean; min?: number; max?: number; ... 7 more ...; animatable?: boolean; } | ValueType'.

如果我未将@property设置为我的变量,则可以正常使用,但此值无法在Cocos Creator编辑器中进行编辑。

有什么想法吗?

1 个答案:

答案 0 :(得分:2)

尝试以下代码

library(tidyverse)

iris %>% 
  mutate(out1 = Sepal.Length < 6,
         out2 = Sepal.Length < 5) %>% 
  group_by(Species) %>%
  summarise(p1 = mean(out1),
            p2 = mean(out2),
            pdiff = p1 - p2,
            p1_test = list(prop.test(sum(out1), length(out1))),  # create tests for p1, p2 and diff and save the outputs as list
            p2_test = list(prop.test(sum(out2), length(out2))),
            pdiff_test = list(prop.test(c(sum(out1),sum(out2)), c(length(out1),length(out2)))),
            p1_low = map_dbl(p1_test, ~.$conf.int[1]),     # extract low and high confidence intervals based on the corresponding test
            p1_high = map_dbl(p1_test, ~.$conf.int[2]),
            p2_low = map_dbl(p2_test, ~.$conf.int[1]),
            p2_high = map_dbl(p2_test, ~.$conf.int[2]),
            pdiff_low = map_dbl(pdiff_test, ~.$conf.int[1]),
            pdiff_high = map_dbl(pdiff_test, ~.$conf.int[2])) %>%
  select(-matches("test"))                                         # remove test columns


# # A tibble: 3 x 10
#    Species       p1    p2 pdiff p1_low p1_high  p2_low p2_high pdiff_low pdiff_high
#    <fct>      <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl>  <dbl>      <dbl>      <dbl>
# 1 setosa      1     0.4   0.6  0.911    1     0.267     0.548   0.444        0.756
# 2 versicolor  0.52  0.02  0.5  0.376    0.661 0.00104   0.120   0.336        0.664
# 3 virginica   0.14  0.02  0.12 0.0628   0.274 0.00104   0.120  -0.00371      0.244