我正在运行以下分析并尝试绘制我的模型的逆逻辑:
R.plot(formula, data=data, ylab = 'P(outcome = 1 | outcome)', xlab = 'SURVRATE: Probability of Survival after 5 Years', xaxp = c(0, 95, 19)) a = R.coef(mod1)[0] b = R.coef(mod1)[1] R.curve(invlogit(a + b*R.x))invlogit是我通过STAP访问的R函数。
一切都很好,但是当我运行curve函数时,出现TypeError: unsupported operand type(s) for *: 'float' and 'ListVector'错误TypeError: unsupported operand type(s) for *: 'float' and 'ListVector' ...
我已经尝试过各种处理方式,比如使用np.multiply等,都无济于事。 我如何处理python中ListVector的标量乘法?
I'm running the following analysis and trying to plot the inverse logit of my model:
R.plot(formula, data=data, ylab = 'P(outcome = 1 | outcome)', xlab = 'SURVRATE: Probability of Survival after 5 Years', xaxp = c(0, 95, 19)) a = R.coef(mod1)[0] b = R.coef(mod1)[1] R.curve(invlogit(a + b*R.x))invlogit is an R function that I am accessing via STAP.
Everything works great, but when I run the curve function, I get an error that TypeError: unsupported operand type(s) for *: 'float' and 'ListVector'...
I've tried various ways of handling this, like using np.multiply among others, all to no avail. How do I handle multiplication of a scalar by a ListVector within python?
最满意答案
Kludgey解决方案就是使用rmagic命令。 它似乎是将我所有的R代码转换为rpy2等价物的阻力最小的路径。
Kludgey solution is to just use the rmagic commands. It appears to be the path of least resistance to convert all my R code to the rpy2 equivalent.
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