Question

在R中，我可以运行绘图和曲线，通过运行来获得预测概率和预测变量之间的关系：

plot(outcome~survrate, data = d, ylab = "P(outcome = 1 |
survrate)", xlab = "SURVRATE: Probability of Survival after 5
Years", xaxp = c(0, 95, 19))

curve(transform(coef(mod1)[1] + coef(mod1)[2]*x), add = TRUE)

其中transform是自定义R函数。

我正在尝试在rpy2中做同样的事情，到目前为止有以下内容：

rplot = ro.r('plot')
formula = Formula('outcome~survrate')
formula.getenvironment()['outcome'] = r_analytical_set.rx2('outcome')
formula.getenvironment()['survrate'] = r_analytical_set.rx2('survrate')
ro.r.plot(formula, data=r_analytical_set, ylab = 'P(outcome =  1 | pass)', xlab = 'SURVRATE: Probability of Survival after 5
Years', xaxp = ro.r.c(0, 95, 19))

# read in R function from file
with open('/Users/gregsilverman//development/python/rest_api/rest_api/utils.r', 'r') as f:
    string = f.read()

from rpy2.robjects.packages import STAP
invlogit = STAP(string, "invlogit")

ro.r.curve(transform(ro.r.coef(fit)[0] + ro.r.coef(fit)[1]*ro.r.x), add = True)

在此状态下，ro.r.curve会出现TypeError: unsupported operand type(s) for *: 'float' and 'FloatVector'

错误

所以，根据这个multiplying all elements of a vector in R，我跑了

ro.r.curve(transform(ro.r.coef(fit)[0] + ro.r.prod(ro.r.coef(fit)[1],ro.r.x)), add = True)

但是，现在我收到错误TypeError: unsupported operand type(s) for +: 'float' and 'FloatVector'

在我浪费任何时间弄清楚如何向矢量添加标量之前，我想知道是否有更有效的方法来实现我的最终目标。

Answer 1

使用访问者＆＃34; R-operator＆＃34; （.ro - 请参阅http://rpy2.readthedocs.io/en/version_2.8.x/vector.html#operators）：

In [1]: from rpy2.robjects.vectors import FloatVector

In [2]: FloatVector((1,2,3)).ro + 2
Out[2]: 
R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x7fde744c0308 / R:0x44db740>
[3.000000, 4.000000, 5.000000]

在rpy2中使用绘图和曲线

1 个答案: